Compare commits

...

21 Commits

Author SHA1 Message Date
Rip&Tear
db0c8ff468 Merge branch 'main' into codex/nl2sql-security-docs 2026-02-12 13:44:54 +08:00
Greyson LaLonde
cde33fd981 feat: add yanked detection for version notes
Some checks are pending
CodeQL Advanced / Analyze (actions) (push) Waiting to run
CodeQL Advanced / Analyze (python) (push) Waiting to run
Notify Downstream / notify-downstream (push) Waiting to run
2026-02-11 23:31:06 -05:00
theCyberTech
1f8cfe3282 docs: clarify NL2SQL security model and hardening guidance 2026-02-12 10:32:56 +08:00
Lorenze Jay
2ed0c2c043 imp compaction (#4399)
Some checks failed
Check Documentation Broken Links / Check broken links (push) Waiting to run
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
* imp compaction

* fix lint

* cassette gen

* cassette gen

* improve assert

* adding azure

* fix global docstring
2026-02-11 15:52:03 -08:00
Lorenze Jay
0341e5aee7 supporting prompt cache results show (#4447)
* supporting prompt cache

* droped azure tests

* fix tests

---------

Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2026-02-11 14:07:15 -08:00
Mike Plachta
397d14c772 fix: correct CLI flag format from --skip-provider to --skip_provider (#4462)
Update documentation to use underscore instead of hyphen in the `--skip_provider` flag across all CLI command examples for consistency with actual CLI implementation.
2026-02-11 13:51:54 -08:00
Lucas Gomide
fc3e86e9a3 docs Adding 96 missing actions across 9 integrations (#4460)
* docs: add missing integration actions from OAuth config

Sync enterprise integration docs with crewai-oauth apps.js config.
Adds ~96 missing actions across 9 integrations:
- Google Contacts: 4 contact group actions
- Google Slides: 14 slide manipulation/content actions
- Microsoft SharePoint: 27 file, Excel, and Word actions
- Microsoft Excel: 2 actions (get_used_range_metadata, get_table_data)
- Microsoft Word: 2 actions (copy_document, move_document)
- Google Docs: 27 text formatting, table, and header/footer actions
- Microsoft Outlook: 7 message and calendar event actions
- Microsoft OneDrive: 5 path-based and discovery actions
- Microsoft Teams: 8 meeting, channel, and reply actions

* docs: add missing integration actions from OAuth config

Sync pt-BR enterprise integration docs with crewai-oauth apps.js config.
Adds ~96 missing actions across 9 integrations, translated to Portuguese:
- Google Contacts: 2 contact group actions
- Google Slides: 14 slide manipulation/content actions
- Microsoft SharePoint: 27 file, Excel, and Word actions
- Microsoft Excel: 2 actions (get_used_range_metadata, get_table_data)
- Microsoft Word: 2 actions (copy_document, move_document)
- Google Docs: 27 text formatting, table, and header/footer actions
- Microsoft Outlook: 7 message and calendar event actions
- Microsoft OneDrive: 5 path-based and discovery actions
- Microsoft Teams: 8 meeting, channel, and reply actions

* docs: add missing integration actions from OAuth config

Sync Korean enterprise integration docs with crewai-oauth apps.js config.
Adds ~96 missing actions across 9 integrations, translated to Korean:
- Google Contacts: 2 contact group actions
- Google Slides: 14 slide manipulation/content actions
- Microsoft SharePoint: 27 file, Excel, and Word actions
- Microsoft Excel: 2 actions (get_used_range_metadata, get_table_data)
- Microsoft Word: 2 actions (copy_document, move_document)
- Google Docs: 27 text formatting, table, and header/footer actions
- Microsoft Outlook: 7 message and calendar event actions
- Microsoft OneDrive: 5 path-based and discovery actions
- Microsoft Teams: 8 meeting, channel, and reply actions

---------

Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2026-02-11 15:17:54 -05:00
Mike Plachta
2882df5daf replace old .cursorrules with AGENTS.md (#4451)
* chore: remove .cursorrules file
feat: add AGENTS.md file to any newly created file

* move the copy of the tests
2026-02-11 10:07:24 -08:00
Greyson LaLonde
3a22e80764 fix: ensure openai tool call stream is finalized
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
2026-02-11 10:02:31 -05:00
Greyson LaLonde
9b585a934d fix: pass started_event_id to crew 2026-02-11 09:30:07 -05:00
Rip&Tear
46e1b02154 chore: fix codeql coverage and action version (#4454) 2026-02-11 18:20:07 +08:00
Rip&Tear
87675b49fd test: avoid URL substring assertion in brave search test (#4453)
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Mark stale issues and pull requests / stale (push) Has been cancelled
2026-02-11 14:32:10 +08:00
Lucas Gomide
a3bee66be8 Address OpenSSL CVE-2025-15467 vulnerability (#4426)
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Build uv cache / build-cache (3.10) (push) Has been cancelled
Build uv cache / build-cache (3.11) (push) Has been cancelled
Build uv cache / build-cache (3.12) (push) Has been cancelled
Build uv cache / build-cache (3.13) (push) Has been cancelled
* fix(security): bump regex from 2024.9.11 to 2026.1.15

Address security vulnerability flagged in regex==2024.9.11

* bump mcp from 1.23.1 to 1.26.0

Address security vulnerability flagged in mcp==1.16.0 (resolved to 1.23.3)
2026-02-10 09:39:35 -08:00
Greyson LaLonde
f6fa04528a fix: add async HITL support and chained-router tests
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Mark stale issues and pull requests / stale (push) Has been cancelled
Build uv cache / build-cache (3.10) (push) Has been cancelled
Build uv cache / build-cache (3.11) (push) Has been cancelled
Build uv cache / build-cache (3.12) (push) Has been cancelled
Build uv cache / build-cache (3.13) (push) Has been cancelled
asynchronous human-in-the-loop handling and related fixes.

- Extend human_input provider with async support: AsyncExecutorContext, handle_feedback_async, async prompt helpers (_prompt_input_async, _async_readline), and async training/regular feedback loops in SyncHumanInputProvider.
- Add async handler methods in CrewAgentExecutor and AgentExecutor (_ahandle_human_feedback, _ainvoke_loop) to integrate async provider flows.
- Change PlusAPI.get_agent to an async httpx call and adapt caller in agent_utils to run it via asyncio.run.
- Simplify listener execution in flow.Flow to correctly pass HumanFeedbackResult to listeners and unify execution path for router outcomes.
- Remove deprecated types/hitl.py definitions.
- Add tests covering chained router feedback, rejected paths, and mixed router/non-router listeners to prevent regressions.
2026-02-06 16:29:27 -05:00
Greyson LaLonde
7d498b29be fix: event ordering; flow state locks, routing
* fix: add current task id context and flow updates

introduce a context var for the current task id in `crewai.context` to track task scope. update `Flow._execute_single_listener` to return `(result, event_id)` and adjust callers to unpack it and append `FlowMethodName(str(result))` to `router_results`. set/reset the current task id at the start/end of task execution (async + sync) with minor import and call-site tweaks.

* fix: await event futures and flush event bus

call `crewai_event_bus.flush()` after crew kickoff. in `Flow`, await event handler futures instead of just collecting them: await pending `_event_futures` before finishing, await emitted futures immediately with try/except to log failures, then clear `_event_futures`. ensures handlers complete and errors surface.

* fix: continue iteration on tool completion events

expand the loop bridge listener to also trigger on tool completion events (`tool_completed` and `native_tool_completed`) so agent iteration resumes after tools finish. add a `requests.post` mock and response fixture in the liteagent test to simulate platform tool execution. refresh and sanitize vcr cassettes (updated model responses, timestamps, and header placeholders) to reflect tool-call flows and new recordings.

* fix: thread-safe state proxies & native routing

add thread-safe state proxies and refactor native tool routing.

* introduce `LockedListProxy` and `LockedDictProxy` in `flow.py` and update `StateProxy` to return them for list/dict attrs so mutations are protected by the flow lock.
* update `AgentExecutor` to use `StateProxy` on flow init, guard the messages setter with the state lock, and return a `StateProxy` from the temp state accessor.
* convert `call_llm_native_tools` into a listener (no direct routing return) and add `route_native_tool_result` to route based on state (pending tool calls, final answer, or context error).
* minor cleanup in `continue_iteration` to drop orphan listeners on init.
* update test cassettes for new native tool call responses, timestamps, and ids.

improves concurrency safety for shared state and makes native tool routing explicit.

* chore: regen cassettes

* chore: regen cassettes, remove duplicate listener call path
2026-02-06 14:02:43 -05:00
Greyson LaLonde
1308bdee63 feat: add started_event_id and set in eventbus
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Mark stale issues and pull requests / stale (push) Has been cancelled
* feat: add started_event_id and set in eventbus

* chore: update additional test assumption

* fix: restore event bus handlers on context exit

fix rollback in crewai events bus so that exiting the context restores
the previous _sync_handlers, _async_handlers, _handler_dependencies, and _execution_plan_cache by assigning shallow copies of the saved dicts. previously these
were set to empty dicts on exit, which caused registered handlers and cached execution plans to be lost.
2026-02-05 21:28:23 -05:00
Greyson LaLonde
6bb1b178a1 chore: extension points
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Build uv cache / build-cache (3.10) (push) Has been cancelled
Build uv cache / build-cache (3.11) (push) Has been cancelled
Build uv cache / build-cache (3.12) (push) Has been cancelled
Build uv cache / build-cache (3.13) (push) Has been cancelled
Introduce ContextVar-backed hooks and small API/behavior changes to improve extensibility and testability.

Changes include:
- agents: mark configure_structured_output as abstract and change its parameter to task to reflect use of task metadata.
- tracing: convert _first_time_trace_hook to a ContextVar and call .get() to safely retrieve the hook.
- console formatter: add _disable_version_check ContextVar and skip version checks when set (avoids noisy checks in certain contexts).
- flow: use current_triggering_event_id variable when scheduling listener tasks to keep naming consistent.
- hallucination guardrail: make context optional, add _validate_output_hook to allow custom validation hooks, update examples and return contract to allow hooks to override behavior.
- agent utilities: add _create_plus_client_hook for injecting a Plus client (used in tests/alternate flows), ensure structured tools have current_usage_count initialized and propagate to original tool, and fall back to creating PlusAPI client when no hook is provided.
2026-02-05 12:49:54 -05:00
Greyson LaLonde
fe2a4b4e40 chore: bug fixes and more refactor
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Mark stale issues and pull requests / stale (push) Has been cancelled
Refactor agent executor to delegate human interactions to a provider: add messages and ask_for_human_input properties, implement _invoke_loop and _format_feedback_message, and replace the internal iterative/training feedback logic with a call to get_provider().handle_feedback.

Make LLMGuardrail kickoff coroutine-aware by detecting coroutines and running them via asyncio.run so both sync and async agents are supported.

Make telemetry more robust by safely handling missing task.output (use empty string) and returning early if span is None before setting attributes.

Improve serialization to detect circular references via an _ancestors set, propagate it through recursive calls, and pass exclude/max_depth/_current_depth consistently to prevent infinite recursion and produce stable serializable output.
2026-02-04 21:21:54 -05:00
Greyson LaLonde
711e7171e1 chore: improve hook typing and registration
Allow hook registration to accept both typed hook types and plain callables by importing and using After*/Before*CallHookCallable types; add explicit LLMCallHookContext and ToolCallHookContext typing in crew_base. Introduce a post-initialize crew hook list and invoke hooks after Crew instance initialization. Refactor filtered hook factory functions to include precise typing and clearer local names (before_llm_hook/after_llm_hook/before_tool_hook/after_tool_hook) and register those with the instance. Update CrewInstance protocol to include _registered_hook_functions and _hooks_being_registered fields.
2026-02-04 21:16:20 -05:00
Vini Brasil
76b5f72e81 Fix tool error causing double event scope pop (#4373)
When a tool raises an error, both ToolUsageErrorEvent and
ToolUsageFinishedEvent were being emitted. Since both events pop the
event scope stack, this caused the agent scope to be incorrectly popped
along with the tool scope.
2026-02-04 20:34:08 -03:00
Greyson LaLonde
d86d43d3e0 chore: refactor crew to provider
Some checks failed
CodeQL Advanced / Analyze (actions) (push) Has been cancelled
CodeQL Advanced / Analyze (python) (push) Has been cancelled
Notify Downstream / notify-downstream (push) Has been cancelled
Enable dynamic extension exports and small behavior fixes across events and flow modules:

- events/__init__.py: Added _extension_exports and extended __getattr__ to lazily resolve registered extension values or import paths.
- events/event_bus.py: Implemented off() to unregister sync/async handlers, clean handler dependencies, and invalidate execution plan cache.
- events/listeners/tracing/utils.py: Added Callable import and _first_time_trace_hook to allow overriding first-time trace auto-collection behavior.
- events/types/tool_usage_events.py: Changed ToolUsageEvent.run_attempts default from None to 0 to avoid nullable handling.
- events/utils/console_formatter.py: Respect CREWAI_DISABLE_VERSION_CHECK env var to skip version checks in CI-like flows.
- flow/async_feedback/__init__.py: Added typing.Any import, _extension_exports and __getattr__ to support extensions via attribute lookup.

These changes add extension points and safer defaults, and provide a way to unregister event handlers.
2026-02-04 16:05:21 -05:00
123 changed files with 14124 additions and 2608 deletions

File diff suppressed because it is too large Load Diff

View File

@@ -14,13 +14,18 @@ paths-ignore:
- "lib/crewai/src/crewai/experimental/a2a/**"
paths:
# Include GitHub Actions workflows/composite actions for CodeQL actions analysis
- ".github/workflows/**"
- ".github/actions/**"
# Include all Python source code from workspace packages
- "lib/crewai/src/**"
- "lib/crewai-tools/src/**"
- "lib/crewai-files/src/**"
- "lib/devtools/src/**"
# Include tests (but exclude cassettes via paths-ignore)
- "lib/crewai/tests/**"
- "lib/crewai-tools/tests/**"
- "lib/crewai-files/tests/**"
- "lib/devtools/tests/**"
# Configure specific queries or packs if needed

View File

@@ -69,7 +69,7 @@ jobs:
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@v3
uses: github/codeql-action/init@v4
with:
languages: ${{ matrix.language }}
build-mode: ${{ matrix.build-mode }}
@@ -98,6 +98,6 @@ jobs:
exit 1
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@v3
uses: github/codeql-action/analyze@v4
with:
category: "/language:${{matrix.language}}"

View File

@@ -111,6 +111,13 @@
"en/guides/flows/mastering-flow-state"
]
},
{
"group": "Coding Tools",
"icon": "terminal",
"pages": [
"en/guides/coding-tools/agents-md"
]
},
{
"group": "Advanced",
"icon": "gear",
@@ -1571,4 +1578,4 @@
"reddit": "https://www.reddit.com/r/crewAIInc/"
}
}
}
}

View File

@@ -224,6 +224,60 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `groupFields` (string, optional): Fields to include (e.g., 'name,memberCount,clientData'). Default: name,memberCount
</Accordion>
<Accordion title="google_contacts/get_contact_group">
**Description:** Get a specific contact group by resource name.
**Parameters:**
- `resourceName` (string, required): The resource name of the contact group (e.g., 'contactGroups/myContactGroup')
- `maxMembers` (integer, optional): Maximum number of members to include. Minimum: 0, Maximum: 20000
- `groupFields` (string, optional): Fields to include (e.g., 'name,memberCount,clientData'). Default: name,memberCount
</Accordion>
<Accordion title="google_contacts/create_contact_group">
**Description:** Create a new contact group (label).
**Parameters:**
- `name` (string, required): The name of the contact group
- `clientData` (array, optional): Client-specific data
```json
[
{
"key": "data_key",
"value": "data_value"
}
]
```
</Accordion>
<Accordion title="google_contacts/update_contact_group">
**Description:** Update a contact group's information.
**Parameters:**
- `resourceName` (string, required): The resource name of the contact group (e.g., 'contactGroups/myContactGroup')
- `name` (string, required): The name of the contact group
- `clientData` (array, optional): Client-specific data
```json
[
{
"key": "data_key",
"value": "data_value"
}
]
```
</Accordion>
<Accordion title="google_contacts/delete_contact_group">
**Description:** Delete a contact group.
**Parameters:**
- `resourceName` (string, required): The resource name of the contact group to delete (e.g., 'contactGroups/myContactGroup')
- `deleteContacts` (boolean, optional): Whether to delete contacts in the group as well. Default: false
</Accordion>
</AccordionGroup>
## Usage Examples

View File

@@ -132,6 +132,297 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `endIndex` (integer, required): The end index of the range.
</Accordion>
<Accordion title="google_docs/create_document_with_content">
**Description:** Create a new Google Document with content in one action.
**Parameters:**
- `title` (string, required): The title for the new document. Appears at the top of the document and in Google Drive.
- `content` (string, optional): The text content to insert into the document. Use `\n` for new paragraphs.
</Accordion>
<Accordion title="google_docs/append_text">
**Description:** Append text to the end of a Google Document. Automatically inserts at the document end without needing to specify an index.
**Parameters:**
- `documentId` (string, required): The document ID from create_document response or URL.
- `text` (string, required): Text to append at the end of the document. Use `\n` for new paragraphs.
</Accordion>
<Accordion title="google_docs/set_text_bold">
**Description:** Make text bold or remove bold formatting in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to format.
- `endIndex` (integer, required): End position of text to format (exclusive).
- `bold` (boolean, required): Set `true` to make bold, `false` to remove bold.
</Accordion>
<Accordion title="google_docs/set_text_italic">
**Description:** Make text italic or remove italic formatting in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to format.
- `endIndex` (integer, required): End position of text to format (exclusive).
- `italic` (boolean, required): Set `true` to make italic, `false` to remove italic.
</Accordion>
<Accordion title="google_docs/set_text_underline">
**Description:** Add or remove underline formatting from text in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to format.
- `endIndex` (integer, required): End position of text to format (exclusive).
- `underline` (boolean, required): Set `true` to underline, `false` to remove underline.
</Accordion>
<Accordion title="google_docs/set_text_strikethrough">
**Description:** Add or remove strikethrough formatting from text in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to format.
- `endIndex` (integer, required): End position of text to format (exclusive).
- `strikethrough` (boolean, required): Set `true` to add strikethrough, `false` to remove.
</Accordion>
<Accordion title="google_docs/set_font_size">
**Description:** Change the font size of text in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to format.
- `endIndex` (integer, required): End position of text to format (exclusive).
- `fontSize` (number, required): Font size in points. Common sizes: 10, 11, 12, 14, 16, 18, 24, 36.
</Accordion>
<Accordion title="google_docs/set_text_color">
**Description:** Change the color of text using RGB values (0-1 scale) in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to format.
- `endIndex` (integer, required): End position of text to format (exclusive).
- `red` (number, required): Red component (0-1). Example: `1` for full red.
- `green` (number, required): Green component (0-1). Example: `0.5` for half green.
- `blue` (number, required): Blue component (0-1). Example: `0` for no blue.
</Accordion>
<Accordion title="google_docs/create_hyperlink">
**Description:** Turn existing text into a clickable hyperlink in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of text to make into a link.
- `endIndex` (integer, required): End position of text to make into a link (exclusive).
- `url` (string, required): The URL the link should point to. Example: `"https://example.com"`.
</Accordion>
<Accordion title="google_docs/apply_heading_style">
**Description:** Apply a heading or paragraph style to a text range in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of paragraph(s) to style.
- `endIndex` (integer, required): End position of paragraph(s) to style.
- `style` (string, required): The style to apply. Enum: `NORMAL_TEXT`, `TITLE`, `SUBTITLE`, `HEADING_1`, `HEADING_2`, `HEADING_3`, `HEADING_4`, `HEADING_5`, `HEADING_6`.
</Accordion>
<Accordion title="google_docs/set_paragraph_alignment">
**Description:** Set text alignment for paragraphs in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of paragraph(s) to align.
- `endIndex` (integer, required): End position of paragraph(s) to align.
- `alignment` (string, required): Text alignment. Enum: `START` (left), `CENTER`, `END` (right), `JUSTIFIED`.
</Accordion>
<Accordion title="google_docs/set_line_spacing">
**Description:** Set line spacing for paragraphs in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of paragraph(s).
- `endIndex` (integer, required): End position of paragraph(s).
- `lineSpacing` (number, required): Line spacing as percentage. `100` = single, `115` = 1.15x, `150` = 1.5x, `200` = double.
</Accordion>
<Accordion title="google_docs/create_paragraph_bullets">
**Description:** Convert paragraphs to a bulleted or numbered list in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of paragraphs to convert to list.
- `endIndex` (integer, required): End position of paragraphs to convert to list.
- `bulletPreset` (string, required): Bullet/numbering style. Enum: `BULLET_DISC_CIRCLE_SQUARE`, `BULLET_DIAMONDX_ARROW3D_SQUARE`, `BULLET_CHECKBOX`, `BULLET_ARROW_DIAMOND_DISC`, `BULLET_STAR_CIRCLE_SQUARE`, `NUMBERED_DECIMAL_ALPHA_ROMAN`, `NUMBERED_DECIMAL_ALPHA_ROMAN_PARENS`, `NUMBERED_DECIMAL_NESTED`, `NUMBERED_UPPERALPHA_ALPHA_ROMAN`, `NUMBERED_UPPERROMAN_UPPERALPHA_DECIMAL`.
</Accordion>
<Accordion title="google_docs/delete_paragraph_bullets">
**Description:** Remove bullets or numbering from paragraphs in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `startIndex` (integer, required): Start position of list paragraphs.
- `endIndex` (integer, required): End position of list paragraphs.
</Accordion>
<Accordion title="google_docs/insert_table_with_content">
**Description:** Insert a table with content into a Google Document in one action. Provide content as a 2D array.
**Parameters:**
- `documentId` (string, required): The document ID.
- `rows` (integer, required): Number of rows in the table.
- `columns` (integer, required): Number of columns in the table.
- `index` (integer, optional): Position to insert the table. If not provided, the table is inserted at the end of the document.
- `content` (array, required): Table content as a 2D array. Each inner array is a row. Example: `[["Year", "Revenue"], ["2023", "$43B"], ["2024", "$45B"]]`.
</Accordion>
<Accordion title="google_docs/insert_table_row">
**Description:** Insert a new row above or below a reference cell in an existing table.
**Parameters:**
- `documentId` (string, required): The document ID.
- `tableStartIndex` (integer, required): The start index of the table. Get from get_document.
- `rowIndex` (integer, required): Row index (0-based) of reference cell.
- `columnIndex` (integer, optional): Column index (0-based) of reference cell. Default is `0`.
- `insertBelow` (boolean, optional): If `true`, insert below the reference row. If `false`, insert above. Default is `true`.
</Accordion>
<Accordion title="google_docs/insert_table_column">
**Description:** Insert a new column left or right of a reference cell in an existing table.
**Parameters:**
- `documentId` (string, required): The document ID.
- `tableStartIndex` (integer, required): The start index of the table.
- `rowIndex` (integer, optional): Row index (0-based) of reference cell. Default is `0`.
- `columnIndex` (integer, required): Column index (0-based) of reference cell.
- `insertRight` (boolean, optional): If `true`, insert to the right. If `false`, insert to the left. Default is `true`.
</Accordion>
<Accordion title="google_docs/delete_table_row">
**Description:** Delete a row from an existing table in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `tableStartIndex` (integer, required): The start index of the table.
- `rowIndex` (integer, required): Row index (0-based) to delete.
- `columnIndex` (integer, optional): Column index (0-based) of any cell in the row. Default is `0`.
</Accordion>
<Accordion title="google_docs/delete_table_column">
**Description:** Delete a column from an existing table in a Google Document.
**Parameters:**
- `documentId` (string, required): The document ID.
- `tableStartIndex` (integer, required): The start index of the table.
- `rowIndex` (integer, optional): Row index (0-based) of any cell in the column. Default is `0`.
- `columnIndex` (integer, required): Column index (0-based) to delete.
</Accordion>
<Accordion title="google_docs/merge_table_cells">
**Description:** Merge a range of table cells into a single cell. Content from all cells is preserved.
**Parameters:**
- `documentId` (string, required): The document ID.
- `tableStartIndex` (integer, required): The start index of the table.
- `rowIndex` (integer, required): Starting row index (0-based) for the merge.
- `columnIndex` (integer, required): Starting column index (0-based) for the merge.
- `rowSpan` (integer, required): Number of rows to merge.
- `columnSpan` (integer, required): Number of columns to merge.
</Accordion>
<Accordion title="google_docs/unmerge_table_cells">
**Description:** Unmerge previously merged table cells back into individual cells.
**Parameters:**
- `documentId` (string, required): The document ID.
- `tableStartIndex` (integer, required): The start index of the table.
- `rowIndex` (integer, required): Row index (0-based) of the merged cell.
- `columnIndex` (integer, required): Column index (0-based) of the merged cell.
- `rowSpan` (integer, required): Number of rows the merged cell spans.
- `columnSpan` (integer, required): Number of columns the merged cell spans.
</Accordion>
<Accordion title="google_docs/insert_inline_image">
**Description:** Insert an image from a public URL into a Google Document. The image must be publicly accessible, under 50MB, and in PNG/JPEG/GIF format.
**Parameters:**
- `documentId` (string, required): The document ID.
- `uri` (string, required): Public URL of the image. Must be accessible without authentication.
- `index` (integer, optional): Position to insert the image. If not provided, the image is inserted at the end of the document. Default is `1`.
</Accordion>
<Accordion title="google_docs/insert_section_break">
**Description:** Insert a section break to create document sections with different formatting.
**Parameters:**
- `documentId` (string, required): The document ID.
- `index` (integer, required): Position to insert the section break.
- `sectionType` (string, required): The type of section break. Enum: `CONTINUOUS` (stays on same page), `NEXT_PAGE` (starts a new page).
</Accordion>
<Accordion title="google_docs/create_header">
**Description:** Create a header for the document. Returns a headerId which can be used with insert_text to add header content.
**Parameters:**
- `documentId` (string, required): The document ID.
- `type` (string, optional): Header type. Enum: `DEFAULT`. Default is `DEFAULT`.
</Accordion>
<Accordion title="google_docs/create_footer">
**Description:** Create a footer for the document. Returns a footerId which can be used with insert_text to add footer content.
**Parameters:**
- `documentId` (string, required): The document ID.
- `type` (string, optional): Footer type. Enum: `DEFAULT`. Default is `DEFAULT`.
</Accordion>
<Accordion title="google_docs/delete_header">
**Description:** Delete a header from the document. Use get_document to find the headerId.
**Parameters:**
- `documentId` (string, required): The document ID.
- `headerId` (string, required): The header ID to delete. Get from get_document response.
</Accordion>
<Accordion title="google_docs/delete_footer">
**Description:** Delete a footer from the document. Use get_document to find the footerId.
**Parameters:**
- `documentId` (string, required): The document ID.
- `footerId` (string, required): The footer ID to delete. Get from get_document response.
</Accordion>
</AccordionGroup>
## Usage Examples

View File

@@ -62,6 +62,22 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="google_slides/get_presentation_metadata">
**Description:** Get lightweight metadata about a presentation (title, slide count, slide IDs). Use this first before fetching full content.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation to retrieve.
</Accordion>
<Accordion title="google_slides/get_presentation_text">
**Description:** Extract all text content from a presentation. Returns slide IDs and text from shapes and tables only (no formatting).
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
</Accordion>
<Accordion title="google_slides/get_presentation">
**Description:** Retrieves a presentation by ID.
@@ -96,6 +112,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="google_slides/get_slide_text">
**Description:** Extract text content from a single slide. Returns only text from shapes and tables (no formatting or styling).
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `pageObjectId` (string, required): The ID of the slide/page to get text from.
</Accordion>
<Accordion title="google_slides/get_page">
**Description:** Retrieves a specific page by its ID.
@@ -114,6 +139,120 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="google_slides/create_slide">
**Description:** Add an additional blank slide to a presentation. New presentations already have one blank slide - check get_presentation_metadata first. For slides with title/body areas, use create_slide_with_layout instead.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `insertionIndex` (integer, optional): Where to insert the slide (0-based). If omitted, adds at the end.
</Accordion>
<Accordion title="google_slides/create_slide_with_layout">
**Description:** Create a slide with a predefined layout containing placeholder areas for title, body, etc. This is better than create_slide for structured content. After creating, use get_page to find placeholder IDs, then insert text into them.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `layout` (string, required): Layout type. One of: `BLANK`, `TITLE`, `TITLE_AND_BODY`, `TITLE_AND_TWO_COLUMNS`, `TITLE_ONLY`, `SECTION_HEADER`, `ONE_COLUMN_TEXT`, `MAIN_POINT`, `BIG_NUMBER`. TITLE_AND_BODY is best for title+description. TITLE for title-only slides. SECTION_HEADER for section dividers.
- `insertionIndex` (integer, optional): Where to insert (0-based). Omit to add at end.
</Accordion>
<Accordion title="google_slides/create_text_box">
**Description:** Create a text box on a slide with content. Use this for titles, descriptions, paragraphs - not tables. Optionally specify position (x, y) and size (width, height) in EMU units (914400 EMU = 1 inch).
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The ID of the slide to add the text box to.
- `text` (string, required): The text content for the text box.
- `x` (integer, optional): X position in EMU (914400 = 1 inch). Default: 914400 (1 inch from left).
- `y` (integer, optional): Y position in EMU (914400 = 1 inch). Default: 914400 (1 inch from top).
- `width` (integer, optional): Width in EMU. Default: 7315200 (~8 inches).
- `height` (integer, optional): Height in EMU. Default: 914400 (~1 inch).
</Accordion>
<Accordion title="google_slides/delete_slide">
**Description:** Remove a slide from the presentation. Use get_presentation first to find the slide ID.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The object ID of the slide to delete. Get from get_presentation.
</Accordion>
<Accordion title="google_slides/duplicate_slide">
**Description:** Create a copy of an existing slide. The duplicate is inserted immediately after the original.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The object ID of the slide to duplicate. Get from get_presentation.
</Accordion>
<Accordion title="google_slides/move_slides">
**Description:** Reorder slides by moving them to a new position. Slide IDs must be in their current presentation order (no duplicates).
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideIds` (array of strings, required): Array of slide IDs to move. Must be in current presentation order.
- `insertionIndex` (integer, required): Target position (0-based). 0 = beginning, slide count = end.
</Accordion>
<Accordion title="google_slides/insert_youtube_video">
**Description:** Embed a YouTube video on a slide. The video ID is the value after "v=" in YouTube URLs (e.g., for youtube.com/watch?v=abc123, use "abc123").
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The ID of the slide to add the video to. Get from get_presentation.
- `videoId` (string, required): The YouTube video ID (the value after v= in the URL).
</Accordion>
<Accordion title="google_slides/insert_drive_video">
**Description:** Embed a video from Google Drive on a slide. The file ID can be found in the Drive file URL.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The ID of the slide to add the video to. Get from get_presentation.
- `fileId` (string, required): The Google Drive file ID of the video.
</Accordion>
<Accordion title="google_slides/set_slide_background_image">
**Description:** Set a background image for a slide. The image URL must be publicly accessible.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The ID of the slide to set the background for. Get from get_presentation.
- `imageUrl` (string, required): Publicly accessible URL of the image to use as background.
</Accordion>
<Accordion title="google_slides/create_table">
**Description:** Create an empty table on a slide. To create a table with content, use create_table_with_content instead.
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The ID of the slide to add the table to. Get from get_presentation.
- `rows` (integer, required): Number of rows in the table.
- `columns` (integer, required): Number of columns in the table.
</Accordion>
<Accordion title="google_slides/create_table_with_content">
**Description:** Create a table with content in one action. Provide content as a 2D array where each inner array is a row. Example: [["Header1", "Header2"], ["Row1Col1", "Row1Col2"]].
**Parameters:**
- `presentationId` (string, required): The ID of the presentation.
- `slideId` (string, required): The ID of the slide to add the table to. Get from get_presentation.
- `rows` (integer, required): Number of rows in the table.
- `columns` (integer, required): Number of columns in the table.
- `content` (array, required): Table content as 2D array. Each inner array is a row. Example: [["Year", "Revenue"], ["2023", "$10M"]].
</Accordion>
<Accordion title="google_slides/import_data_from_sheet">
**Description:** Imports data from a Google Sheet into a presentation.

View File

@@ -169,6 +169,16 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_excel/get_table_data">
**Description:** Get data from a specific table in an Excel worksheet.
**Parameters:**
- `file_id` (string, required): The ID of the Excel file
- `worksheet_name` (string, required): Name of the worksheet
- `table_name` (string, required): Name of the table
</Accordion>
<Accordion title="microsoft_excel/create_chart">
**Description:** Create a chart in an Excel worksheet.
@@ -201,6 +211,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_excel/get_used_range_metadata">
**Description:** Get the used range metadata (dimensions only, no data) of an Excel worksheet.
**Parameters:**
- `file_id` (string, required): The ID of the Excel file
- `worksheet_name` (string, required): Name of the worksheet
</Accordion>
<Accordion title="microsoft_excel/list_charts">
**Description:** Get all charts in an Excel worksheet.

View File

@@ -151,6 +151,49 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `item_id` (string, required): The ID of the file.
</Accordion>
<Accordion title="microsoft_onedrive/list_files_by_path">
**Description:** List files and folders in a specific OneDrive path.
**Parameters:**
- `folder_path` (string, required): The folder path (e.g., 'Documents/Reports').
- `top` (integer, optional): Number of items to retrieve (max 1000). Default is `50`.
- `orderby` (string, optional): Order by field (e.g., "name asc", "lastModifiedDateTime desc"). Default is "name asc".
</Accordion>
<Accordion title="microsoft_onedrive/get_recent_files">
**Description:** Get recently accessed files from OneDrive.
**Parameters:**
- `top` (integer, optional): Number of items to retrieve (max 200). Default is `25`.
</Accordion>
<Accordion title="microsoft_onedrive/get_shared_with_me">
**Description:** Get files and folders shared with the user.
**Parameters:**
- `top` (integer, optional): Number of items to retrieve (max 200). Default is `50`.
- `orderby` (string, optional): Order by field. Default is "name asc".
</Accordion>
<Accordion title="microsoft_onedrive/get_file_by_path">
**Description:** Get information about a specific file or folder by path.
**Parameters:**
- `file_path` (string, required): The file or folder path (e.g., 'Documents/report.docx').
</Accordion>
<Accordion title="microsoft_onedrive/download_file_by_path">
**Description:** Download a file from OneDrive by its path.
**Parameters:**
- `file_path` (string, required): The file path (e.g., 'Documents/report.docx').
</Accordion>
</AccordionGroup>
## Usage Examples

View File

@@ -133,6 +133,74 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `companyName` (string, optional): Contact's company name.
</Accordion>
<Accordion title="microsoft_outlook/get_message">
**Description:** Get a specific email message by ID.
**Parameters:**
- `message_id` (string, required): The unique identifier of the message. Obtain from get_messages action.
- `select` (string, optional): Comma-separated list of properties to return. Example: "id,subject,body,from,receivedDateTime". Default is "id,subject,body,from,toRecipients,receivedDateTime".
</Accordion>
<Accordion title="microsoft_outlook/reply_to_email">
**Description:** Reply to an email message.
**Parameters:**
- `message_id` (string, required): The unique identifier of the message to reply to. Obtain from get_messages action.
- `comment` (string, required): The reply message content. Can be plain text or HTML. The original message will be quoted below this content.
</Accordion>
<Accordion title="microsoft_outlook/forward_email">
**Description:** Forward an email message.
**Parameters:**
- `message_id` (string, required): The unique identifier of the message to forward. Obtain from get_messages action.
- `to_recipients` (array, required): Array of recipient email addresses to forward to. Example: ["john@example.com", "jane@example.com"].
- `comment` (string, optional): Optional message to include above the forwarded content. Can be plain text or HTML.
</Accordion>
<Accordion title="microsoft_outlook/mark_message_read">
**Description:** Mark a message as read or unread.
**Parameters:**
- `message_id` (string, required): The unique identifier of the message. Obtain from get_messages action.
- `is_read` (boolean, required): Set to true to mark as read, false to mark as unread.
</Accordion>
<Accordion title="microsoft_outlook/delete_message">
**Description:** Delete an email message.
**Parameters:**
- `message_id` (string, required): The unique identifier of the message to delete. Obtain from get_messages action.
</Accordion>
<Accordion title="microsoft_outlook/update_event">
**Description:** Update an existing calendar event.
**Parameters:**
- `event_id` (string, required): The unique identifier of the event. Obtain from get_calendar_events action.
- `subject` (string, optional): New subject/title for the event.
- `start_time` (string, optional): New start time in ISO 8601 format (e.g., "2024-01-20T10:00:00"). REQUIRED: Must also provide start_timezone when using this field.
- `start_timezone` (string, optional): Timezone for start time. REQUIRED when updating start_time. Examples: "Pacific Standard Time", "Eastern Standard Time", "UTC".
- `end_time` (string, optional): New end time in ISO 8601 format. REQUIRED: Must also provide end_timezone when using this field.
- `end_timezone` (string, optional): Timezone for end time. REQUIRED when updating end_time. Examples: "Pacific Standard Time", "Eastern Standard Time", "UTC".
- `location` (string, optional): New location for the event.
- `body` (string, optional): New body/description for the event. Supports HTML formatting.
</Accordion>
<Accordion title="microsoft_outlook/delete_event">
**Description:** Delete a calendar event.
**Parameters:**
- `event_id` (string, required): The unique identifier of the event to delete. Obtain from get_calendar_events action.
</Accordion>
</AccordionGroup>
## Usage Examples

View File

@@ -78,6 +78,17 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_sharepoint/get_drives">
**Description:** List all document libraries (drives) in a SharePoint site. Use this to discover available libraries before using file operations.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `top` (integer, optional): Maximum number of drives to return per page (1-999). Default is 100
- `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'id,name,webUrl,driveType')
</Accordion>
<Accordion title="microsoft_sharepoint/get_site_lists">
**Description:** Get all lists in a SharePoint site.
@@ -159,20 +170,317 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_sharepoint/get_drive_items">
**Description:** Get files and folders from a SharePoint document library.
<Accordion title="microsoft_sharepoint/list_files">
**Description:** Retrieve files and folders from a SharePoint document library. By default lists the root folder, but you can navigate into subfolders by providing a folder_id.
**Parameters:**
- `site_id` (string, required): The ID of the SharePoint site
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `folder_id` (string, optional): The ID of the folder to list contents from. Use 'root' for the root folder, or provide a folder ID from a previous list_files call. Default is 'root'
- `top` (integer, optional): Maximum number of items to return per page (1-1000). Default is 50
- `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
- `orderby` (string, optional): Sort order for results (e.g., 'name asc', 'size desc', 'lastModifiedDateTime desc'). Default is 'name asc'
- `filter` (string, optional): OData filter to narrow results (e.g., 'file ne null' for files only, 'folder ne null' for folders only)
- `select` (string, optional): Comma-separated list of fields to return (e.g., 'id,name,size,folder,file,webUrl,lastModifiedDateTime')
</Accordion>
<Accordion title="microsoft_sharepoint/delete_drive_item">
**Description:** Delete a file or folder from SharePoint document library.
<Accordion title="microsoft_sharepoint/delete_file">
**Description:** Delete a file or folder from a SharePoint document library. For folders, all contents are deleted recursively. Items are moved to the site recycle bin.
**Parameters:**
- `site_id` (string, required): The ID of the SharePoint site
- `item_id` (string, required): The ID of the file or folder to delete
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the file or folder to delete. Obtain from list_files
</Accordion>
<Accordion title="microsoft_sharepoint/list_files_by_path">
**Description:** List files and folders in a SharePoint document library folder by its path. More efficient than multiple list_files calls for deep navigation.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `folder_path` (string, required): The full path to the folder without leading/trailing slashes (e.g., 'Documents', 'Reports/2024/Q1')
- `top` (integer, optional): Maximum number of items to return per page (1-1000). Default is 50
- `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
- `orderby` (string, optional): Sort order for results (e.g., 'name asc', 'size desc'). Default is 'name asc'
- `select` (string, optional): Comma-separated list of fields to return (e.g., 'id,name,size,folder,file,webUrl,lastModifiedDateTime')
</Accordion>
<Accordion title="microsoft_sharepoint/download_file">
**Description:** Download raw file content from a SharePoint document library. Use only for plain text files (.txt, .csv, .json). For Excel files, use the Excel-specific actions. For Word files, use get_word_document_content.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the file to download. Obtain from list_files or list_files_by_path
</Accordion>
<Accordion title="microsoft_sharepoint/get_file_info">
**Description:** Retrieve detailed metadata for a specific file or folder in a SharePoint document library, including name, size, created/modified dates, and author information.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the file or folder. Obtain from list_files or list_files_by_path
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'id,name,size,createdDateTime,lastModifiedDateTime,webUrl,createdBy,lastModifiedBy')
</Accordion>
<Accordion title="microsoft_sharepoint/create_folder">
**Description:** Create a new folder in a SharePoint document library. By default creates the folder in the root; use parent_id to create subfolders.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `folder_name` (string, required): Name for the new folder. Cannot contain: \ / : * ? " < > |
- `parent_id` (string, optional): The ID of the parent folder. Use 'root' for the document library root, or provide a folder ID from list_files. Default is 'root'
</Accordion>
<Accordion title="microsoft_sharepoint/search_files">
**Description:** Search for files and folders in a SharePoint document library by keywords. Searches file names, folder names, and file contents for Office documents. Do not use wildcards or special characters.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `query` (string, required): Search keywords (e.g., 'report', 'budget 2024'). Wildcards like *.txt are not supported
- `top` (integer, optional): Maximum number of results to return per page (1-1000). Default is 50
- `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
- `select` (string, optional): Comma-separated list of fields to return (e.g., 'id,name,size,folder,file,webUrl,lastModifiedDateTime')
</Accordion>
<Accordion title="microsoft_sharepoint/copy_file">
**Description:** Copy a file or folder to a new location within SharePoint. The original item remains unchanged. The copy operation is asynchronous for large files.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the file or folder to copy. Obtain from list_files or search_files
- `destination_folder_id` (string, required): The ID of the destination folder. Use 'root' for the root folder, or a folder ID from list_files
- `new_name` (string, optional): New name for the copy. If not provided, the original name is used
</Accordion>
<Accordion title="microsoft_sharepoint/move_file">
**Description:** Move a file or folder to a new location within SharePoint. The item is removed from its original location. For folders, all contents are moved as well.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the file or folder to move. Obtain from list_files or search_files
- `destination_folder_id` (string, required): The ID of the destination folder. Use 'root' for the root folder, or a folder ID from list_files
- `new_name` (string, optional): New name for the moved item. If not provided, the original name is kept
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_worksheets">
**Description:** List all worksheets (tabs) in an Excel workbook stored in a SharePoint document library. Use the returned worksheet name with other Excel actions.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'id,name,position,visibility')
- `filter` (string, optional): OData filter expression (e.g., "visibility eq 'Visible'" to exclude hidden sheets)
- `top` (integer, optional): Maximum number of worksheets to return. Minimum: 1, Maximum: 999
- `orderby` (string, optional): Sort order (e.g., 'position asc' to return sheets in tab order)
</Accordion>
<Accordion title="microsoft_sharepoint/create_excel_worksheet">
**Description:** Create a new worksheet (tab) in an Excel workbook stored in a SharePoint document library. The new sheet is added at the end of the tab list.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `name` (string, required): Name for the new worksheet. Maximum 31 characters. Cannot contain: \ / * ? : [ ]. Must be unique within the workbook
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_range_data">
**Description:** Retrieve cell values from a specific range in an Excel worksheet stored in SharePoint. For reading all data without knowing dimensions, use get_excel_used_range instead.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet (tab) to read from. Obtain from get_excel_worksheets. Case-sensitive
- `range` (string, required): Cell range in A1 notation (e.g., 'A1:C10', 'A:C', '1:5', 'A1')
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text')
</Accordion>
<Accordion title="microsoft_sharepoint/update_excel_range_data">
**Description:** Write values to a specific range in an Excel worksheet stored in SharePoint. Overwrites existing cell contents. The values array dimensions must match the range dimensions exactly.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet (tab) to update. Obtain from get_excel_worksheets. Case-sensitive
- `range` (string, required): Cell range in A1 notation where values will be written (e.g., 'A1:C3' for a 3x3 block)
- `values` (array, required): 2D array of values (rows containing cells). Example for A1:B2: [["Header1", "Header2"], ["Value1", "Value2"]]. Use null to clear a cell
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_used_range_metadata">
**Description:** Return only the metadata (address and dimensions) of the used range in a worksheet, without the actual cell values. Ideal for large files to understand spreadsheet size before reading data in chunks.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet (tab) to read. Obtain from get_excel_worksheets. Case-sensitive
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_used_range">
**Description:** Retrieve all cells containing data in a worksheet stored in SharePoint. Do not use for files larger than 2MB. For large files, use get_excel_used_range_metadata first, then get_excel_range_data to read in smaller chunks.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet (tab) to read. Obtain from get_excel_worksheets. Case-sensitive
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text,rowCount,columnCount')
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_cell">
**Description:** Retrieve the value of a single cell by row and column index from an Excel file in SharePoint. Indices are 0-based (row 0 = Excel row 1, column 0 = column A).
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet (tab). Obtain from get_excel_worksheets. Case-sensitive
- `row` (integer, required): 0-based row index (row 0 = Excel row 1). Valid range: 0-1048575
- `column` (integer, required): 0-based column index (column 0 = A, column 1 = B). Valid range: 0-16383
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text')
</Accordion>
<Accordion title="microsoft_sharepoint/add_excel_table">
**Description:** Convert a cell range into a formatted Excel table with filtering, sorting, and structured data capabilities. Tables enable add_excel_table_row for appending data.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet containing the data range. Obtain from get_excel_worksheets
- `range` (string, required): Cell range to convert into a table, including headers and data (e.g., 'A1:D10' where A1:D1 contains column headers)
- `has_headers` (boolean, optional): Set to true if the first row contains column headers. Default is true
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_tables">
**Description:** List all tables in a specific Excel worksheet stored in SharePoint. Returns table properties including id, name, showHeaders, and showTotals.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet to get tables from. Obtain from get_excel_worksheets
</Accordion>
<Accordion title="microsoft_sharepoint/add_excel_table_row">
**Description:** Append a new row to the end of an Excel table in a SharePoint file. The values array must have the same number of elements as the table has columns.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet containing the table. Obtain from get_excel_worksheets
- `table_name` (string, required): Name of the table to add the row to (e.g., 'Table1'). Obtain from get_excel_tables. Case-sensitive
- `values` (array, required): Array of cell values for the new row, one per column in table order (e.g., ["John Doe", "john@example.com", 25])
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_table_data">
**Description:** Get all rows from an Excel table in a SharePoint file as a data range. Easier than get_excel_range_data when working with structured tables since you don't need to know the exact range.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet containing the table. Obtain from get_excel_worksheets
- `table_name` (string, required): Name of the table to get data from (e.g., 'Table1'). Obtain from get_excel_tables. Case-sensitive
- `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text')
</Accordion>
<Accordion title="microsoft_sharepoint/create_excel_chart">
**Description:** Create a chart visualization in an Excel worksheet stored in SharePoint from a data range. The chart is embedded in the worksheet.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet where the chart will be created. Obtain from get_excel_worksheets
- `chart_type` (string, required): Chart type (e.g., 'ColumnClustered', 'ColumnStacked', 'Line', 'LineMarkers', 'Pie', 'Bar', 'BarClustered', 'Area', 'Scatter', 'Doughnut')
- `source_data` (string, required): Data range for the chart in A1 notation, including headers (e.g., 'A1:B10')
- `series_by` (string, optional): How data series are organized: 'Auto', 'Columns', or 'Rows'. Default is 'Auto'
</Accordion>
<Accordion title="microsoft_sharepoint/list_excel_charts">
**Description:** List all charts embedded in an Excel worksheet stored in SharePoint. Returns chart properties including id, name, chartType, height, width, and position.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet to list charts from. Obtain from get_excel_worksheets
</Accordion>
<Accordion title="microsoft_sharepoint/delete_excel_worksheet">
**Description:** Permanently remove a worksheet (tab) and all its contents from an Excel workbook stored in SharePoint. Cannot be undone. A workbook must have at least one worksheet.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet to delete. Case-sensitive. All data, tables, and charts on this sheet will be permanently removed
</Accordion>
<Accordion title="microsoft_sharepoint/delete_excel_table">
**Description:** Remove a table from an Excel worksheet in SharePoint. This deletes the table structure (filtering, formatting, table features) but preserves the underlying cell data.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
- `worksheet_name` (string, required): Name of the worksheet containing the table. Obtain from get_excel_worksheets
- `table_name` (string, required): Name of the table to delete (e.g., 'Table1'). Obtain from get_excel_tables. The data in the cells will remain after table deletion
</Accordion>
<Accordion title="microsoft_sharepoint/list_excel_names">
**Description:** Retrieve all named ranges defined in an Excel workbook stored in SharePoint. Named ranges are user-defined labels for cell ranges (e.g., 'SalesData' for A1:D100).
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
</Accordion>
<Accordion title="microsoft_sharepoint/get_word_document_content">
**Description:** Download and extract text content from a Word document (.docx) stored in a SharePoint document library. This is the recommended way to read Word documents from SharePoint.
**Parameters:**
- `site_id` (string, required): The full SharePoint site identifier from get_sites
- `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
- `item_id` (string, required): The unique identifier of the Word document (.docx) in SharePoint. Obtain from list_files or search_files
</Accordion>
</AccordionGroup>

View File

@@ -108,6 +108,86 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `join_web_url` (string, required): The join web URL of the meeting to search for.
</Accordion>
<Accordion title="microsoft_teams/search_online_meetings_by_meeting_id">
**Description:** Search online meetings by external Meeting ID.
**Parameters:**
- `join_meeting_id` (string, required): The meeting ID (numeric code) that attendees use to join. This is the joinMeetingId shown in meeting invitations, not the Graph API meeting id.
</Accordion>
<Accordion title="microsoft_teams/get_meeting">
**Description:** Get details of a specific online meeting.
**Parameters:**
- `meeting_id` (string, required): The Graph API meeting ID (a long alphanumeric string). Obtain from create_meeting or search_online_meetings actions. Different from the numeric joinMeetingId.
</Accordion>
<Accordion title="microsoft_teams/get_team_members">
**Description:** Get members of a specific team.
**Parameters:**
- `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
- `top` (integer, optional): Maximum number of members to retrieve per page (1-999). Default is `100`.
- `skip_token` (string, optional): Pagination token from a previous response. When the response includes @odata.nextLink, extract the $skiptoken parameter value and pass it here to get the next page of results.
</Accordion>
<Accordion title="microsoft_teams/create_channel">
**Description:** Create a new channel in a team.
**Parameters:**
- `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
- `display_name` (string, required): Name of the channel as displayed in Teams. Must be unique within the team. Max 50 characters.
- `description` (string, optional): Optional description explaining the channel's purpose. Visible in channel details. Max 1024 characters.
- `membership_type` (string, optional): Channel visibility. Enum: `standard`, `private`. "standard" = visible to all team members, "private" = visible only to specifically added members. Default is `standard`.
</Accordion>
<Accordion title="microsoft_teams/get_message_replies">
**Description:** Get replies to a specific message in a channel.
**Parameters:**
- `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
- `channel_id` (string, required): The unique identifier of the channel. Obtain from get_channels action.
- `message_id` (string, required): The unique identifier of the parent message. Obtain from get_messages action.
- `top` (integer, optional): Maximum number of replies to retrieve per page (1-50). Default is `50`.
- `skip_token` (string, optional): Pagination token from a previous response. When the response includes @odata.nextLink, extract the $skiptoken parameter value and pass it here to get the next page of results.
</Accordion>
<Accordion title="microsoft_teams/reply_to_message">
**Description:** Reply to a message in a Teams channel.
**Parameters:**
- `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
- `channel_id` (string, required): The unique identifier of the channel. Obtain from get_channels action.
- `message_id` (string, required): The unique identifier of the message to reply to. Obtain from get_messages action.
- `message` (string, required): The reply content. For HTML, include formatting tags. For text, plain text only.
- `content_type` (string, optional): Content format. Enum: `html`, `text`. "text" for plain text, "html" for rich text with formatting. Default is `text`.
</Accordion>
<Accordion title="microsoft_teams/update_meeting">
**Description:** Update an existing online meeting.
**Parameters:**
- `meeting_id` (string, required): The unique identifier of the meeting. Obtain from create_meeting or search_online_meetings actions.
- `subject` (string, optional): New meeting title.
- `startDateTime` (string, optional): New start time in ISO 8601 format with timezone. Example: "2024-01-20T10:00:00-08:00".
- `endDateTime` (string, optional): New end time in ISO 8601 format with timezone.
</Accordion>
<Accordion title="microsoft_teams/delete_meeting">
**Description:** Delete an online meeting.
**Parameters:**
- `meeting_id` (string, required): The unique identifier of the meeting to delete. Obtain from create_meeting or search_online_meetings actions.
</Accordion>
</AccordionGroup>
## Usage Examples

View File

@@ -98,6 +98,26 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `file_id` (string, required): The ID of the document to delete.
</Accordion>
<Accordion title="microsoft_word/copy_document">
**Description:** Copy a document to a new location in OneDrive.
**Parameters:**
- `file_id` (string, required): The ID of the document to copy
- `name` (string, optional): New name for the copied document
- `parent_id` (string, optional): The ID of the destination folder (defaults to root)
</Accordion>
<Accordion title="microsoft_word/move_document">
**Description:** Move a document to a new location in OneDrive.
**Parameters:**
- `file_id` (string, required): The ID of the document to move
- `parent_id` (string, required): The ID of the destination folder
- `name` (string, optional): New name for the moved document
</Accordion>
</AccordionGroup>
## Usage Examples

View File

@@ -0,0 +1,61 @@
---
title: Coding Tools
description: Use AGENTS.md to guide coding agents and IDEs across your CrewAI projects.
icon: terminal
mode: "wide"
---
## Why AGENTS.md
`AGENTS.md` is a lightweight, repo-local instruction file that gives coding agents consistent, project-specific guidance. Keep it in the project root and treat it as the source of truth for how you want assistants to work: conventions, commands, architecture notes, and guardrails.
## Create a Project with the CLI
Use the CrewAI CLI to scaffold a project, then `AGENTS.md` will be automatically added at the root.
```bash
# Crew
crewai create crew my_crew
# Flow
crewai create flow my_flow
# Tool repository
crewai tool create my_tool
```
## Tool Setup: Point Assistants to AGENTS.md
### Codex
Codex can be guided by `AGENTS.md` files placed in your repository. Use them to supply persistent project context such as conventions, commands, and workflow expectations.
### Claude Code
Claude Code stores project memory in `CLAUDE.md`. You can bootstrap it with `/init` and edit it using `/memory`. Claude Code also supports imports inside `CLAUDE.md`, so you can add a single line like `@AGENTS.md` to pull in the shared instructions without duplicating them.
You can simply use:
```bash
mv AGENTS.md CLAUDE.md
```
### Gemini CLI and Google Antigravity
Gemini CLI and Antigravity load a project context file (default: `GEMINI.md`) from the repo root and parent directories. You can configure it to read `AGENTS.md` instead (or in addition) by setting `context.fileName` in your Gemini CLI settings. For example, set it to `AGENTS.md` only, or include both `AGENTS.md` and `GEMINI.md` if you want to keep each tools format.
You can simply use:
```bash
mv AGENTS.md GEMINI.md
```
### Cursor
Cursor supports `AGENTS.md` as a project instruction file. Place it at the project root to provide guidance for Cursors coding assistant.
### Windsurf
Claude Code provides an official integration with Windsurf. If you use Claude Code inside Windsurf, follow the Claude Code guidance above and import `AGENTS.md` from `CLAUDE.md`.
If you are using Windsurfs native assistant, configure its project rules or instructions feature (if available) to read from `AGENTS.md` or paste the contents directly.

View File

@@ -15,6 +15,29 @@ Along with that provides the ability for the Agent to update the database based
**Attention**: Make sure that the Agent has access to a Read-Replica or that is okay for the Agent to run insert/update queries on the database.
## Security Model
`NL2SQLTool` is an execution-capable tool. It runs model-generated SQL directly against the configured database connection.
This means risk depends on your deployment choices:
- Which credentials you provide in `db_uri`
- Whether untrusted input can influence prompts
- Whether you add tool-call guardrails before execution
If you route untrusted input to agents using this tool, treat it as a high-risk integration.
## Hardening Recommendations
Use all of the following in production:
- Use a read-only database user whenever possible
- Prefer a read replica for analytics/retrieval workloads
- Grant least privilege (no superuser/admin roles, no file/system-level capabilities)
- Apply database-side resource limits (statement timeout, lock timeout, cost/row limits)
- Add `before_tool_call` hooks to enforce allowed query patterns
- Enable query logging and alerting for destructive statements
## Requirements
- SqlAlchemy

View File

@@ -200,6 +200,25 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `clientData` (array, 선택사항): 클라이언트별 데이터. 각 항목은 `key` (string)와 `value` (string)가 있는 객체.
</Accordion>
<Accordion title="google_contacts/update_contact_group">
**설명:** 연락처 그룹의 정보를 업데이트합니다.
**매개변수:**
- `resourceName` (string, 필수): 연락처 그룹의 리소스 이름 (예: 'contactGroups/myContactGroup').
- `name` (string, 필수): 연락처 그룹의 이름.
- `clientData` (array, 선택사항): 클라이언트별 데이터. 각 항목은 `key` (string)와 `value` (string)가 있는 객체.
</Accordion>
<Accordion title="google_contacts/delete_contact_group">
**설명:** 연락처 그룹을 삭제합니다.
**매개변수:**
- `resourceName` (string, 필수): 삭제할 연락처 그룹의 리소스 이름 (예: 'contactGroups/myContactGroup').
- `deleteContacts` (boolean, 선택사항): 그룹 내 연락처도 삭제할지 여부. 기본값: false
</Accordion>
</AccordionGroup>
## 사용 예제

View File

@@ -131,6 +131,297 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `endIndex` (integer, 필수): 범위의 끝 인덱스.
</Accordion>
<Accordion title="google_docs/create_document_with_content">
**설명:** 내용이 포함된 새 Google 문서를 한 번에 만듭니다.
**매개변수:**
- `title` (string, 필수): 새 문서의 제목. 문서 상단과 Google Drive에 표시됩니다.
- `content` (string, 선택사항): 문서에 삽입할 텍스트 내용. 새 단락에는 `\n`을 사용하세요.
</Accordion>
<Accordion title="google_docs/append_text">
**설명:** Google 문서의 끝에 텍스트를 추가합니다. 인덱스를 지정할 필요 없이 자동으로 문서 끝에 삽입됩니다.
**매개변수:**
- `documentId` (string, 필수): create_document 응답 또는 URL에서 가져온 문서 ID.
- `text` (string, 필수): 문서 끝에 추가할 텍스트. 새 단락에는 `\n`을 사용하세요.
</Accordion>
<Accordion title="google_docs/set_text_bold">
**설명:** Google 문서에서 텍스트를 굵게 만들거나 굵게 서식을 제거합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
- `bold` (boolean, 필수): 굵게 만들려면 `true`, 굵게를 제거하려면 `false`로 설정.
</Accordion>
<Accordion title="google_docs/set_text_italic">
**설명:** Google 문서에서 텍스트를 기울임꼴로 만들거나 기울임꼴 서식을 제거합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
- `italic` (boolean, 필수): 기울임꼴로 만들려면 `true`, 기울임꼴을 제거하려면 `false`로 설정.
</Accordion>
<Accordion title="google_docs/set_text_underline">
**설명:** Google 문서에서 텍스트에 밑줄 서식을 추가하거나 제거합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
- `underline` (boolean, 필수): 밑줄을 추가하려면 `true`, 밑줄을 제거하려면 `false`로 설정.
</Accordion>
<Accordion title="google_docs/set_text_strikethrough">
**설명:** Google 문서에서 텍스트에 취소선 서식을 추가하거나 제거합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
- `strikethrough` (boolean, 필수): 취소선을 추가하려면 `true`, 제거하려면 `false`로 설정.
</Accordion>
<Accordion title="google_docs/set_font_size">
**설명:** Google 문서에서 텍스트의 글꼴 크기를 변경합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
- `fontSize` (number, 필수): 포인트 단위의 글꼴 크기. 일반적인 크기: 10, 11, 12, 14, 16, 18, 24, 36.
</Accordion>
<Accordion title="google_docs/set_text_color">
**설명:** Google 문서에서 RGB 값(0-1 스케일)을 사용하여 텍스트 색상을 변경합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
- `red` (number, 필수): 빨강 구성 요소 (0-1). 예: `1`은 완전한 빨강.
- `green` (number, 필수): 초록 구성 요소 (0-1). 예: `0.5`는 절반 초록.
- `blue` (number, 필수): 파랑 구성 요소 (0-1). 예: `0`은 파랑 없음.
</Accordion>
<Accordion title="google_docs/create_hyperlink">
**설명:** Google 문서에서 기존 텍스트를 클릭 가능한 하이퍼링크로 변환합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 링크로 만들 텍스트의 시작 위치.
- `endIndex` (integer, 필수): 링크로 만들 텍스트의 끝 위치 (배타적).
- `url` (string, 필수): 링크가 가리킬 URL. 예: `"https://example.com"`.
</Accordion>
<Accordion title="google_docs/apply_heading_style">
**설명:** Google 문서에서 텍스트 범위에 제목 또는 단락 스타일을 적용합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 스타일을 적용할 단락의 시작 위치.
- `endIndex` (integer, 필수): 스타일을 적용할 단락의 끝 위치.
- `style` (string, 필수): 적용할 스타일. 옵션: `NORMAL_TEXT`, `TITLE`, `SUBTITLE`, `HEADING_1`, `HEADING_2`, `HEADING_3`, `HEADING_4`, `HEADING_5`, `HEADING_6`.
</Accordion>
<Accordion title="google_docs/set_paragraph_alignment">
**설명:** Google 문서에서 단락의 텍스트 정렬을 설정합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 정렬할 단락의 시작 위치.
- `endIndex` (integer, 필수): 정렬할 단락의 끝 위치.
- `alignment` (string, 필수): 텍스트 정렬. 옵션: `START` (왼쪽), `CENTER`, `END` (오른쪽), `JUSTIFIED`.
</Accordion>
<Accordion title="google_docs/set_line_spacing">
**설명:** Google 문서에서 단락의 줄 간격을 설정합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 단락의 시작 위치.
- `endIndex` (integer, 필수): 단락의 끝 위치.
- `lineSpacing` (number, 필수): 백분율로 나타낸 줄 간격. `100` = 단일, `115` = 1.15배, `150` = 1.5배, `200` = 이중.
</Accordion>
<Accordion title="google_docs/create_paragraph_bullets">
**설명:** Google 문서에서 단락을 글머리 기호 또는 번호 매기기 목록으로 변환합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 목록으로 변환할 단락의 시작 위치.
- `endIndex` (integer, 필수): 목록으로 변환할 단락의 끝 위치.
- `bulletPreset` (string, 필수): 글머리 기호/번호 매기기 스타일. 옵션: `BULLET_DISC_CIRCLE_SQUARE`, `BULLET_DIAMONDX_ARROW3D_SQUARE`, `BULLET_CHECKBOX`, `BULLET_ARROW_DIAMOND_DISC`, `BULLET_STAR_CIRCLE_SQUARE`, `NUMBERED_DECIMAL_ALPHA_ROMAN`, `NUMBERED_DECIMAL_ALPHA_ROMAN_PARENS`, `NUMBERED_DECIMAL_NESTED`, `NUMBERED_UPPERALPHA_ALPHA_ROMAN`, `NUMBERED_UPPERROMAN_UPPERALPHA_DECIMAL`.
</Accordion>
<Accordion title="google_docs/delete_paragraph_bullets">
**설명:** Google 문서에서 단락의 글머리 기호 또는 번호 매기기를 제거합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `startIndex` (integer, 필수): 목록 단락의 시작 위치.
- `endIndex` (integer, 필수): 목록 단락의 끝 위치.
</Accordion>
<Accordion title="google_docs/insert_table_with_content">
**설명:** Google 문서에 내용이 포함된 표를 한 번에 삽입합니다. 내용은 2D 배열로 제공하세요.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `rows` (integer, 필수): 표의 행 수.
- `columns` (integer, 필수): 표의 열 수.
- `index` (integer, 선택사항): 표를 삽입할 위치. 제공하지 않으면 문서 끝에 삽입됩니다.
- `content` (array, 필수): 2D 배열로 된 표 내용. 각 내부 배열은 행입니다. 예: `[["Year", "Revenue"], ["2023", "$43B"], ["2024", "$45B"]]`.
</Accordion>
<Accordion title="google_docs/insert_table_row">
**설명:** 기존 표의 참조 셀 위 또는 아래에 새 행을 삽입합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `tableStartIndex` (integer, 필수): 표의 시작 인덱스. get_document에서 가져오세요.
- `rowIndex` (integer, 필수): 참조 셀의 행 인덱스 (0 기반).
- `columnIndex` (integer, 선택사항): 참조 셀의 열 인덱스 (0 기반). 기본값: `0`.
- `insertBelow` (boolean, 선택사항): `true`이면 참조 행 아래에, `false`이면 위에 삽입. 기본값: `true`.
</Accordion>
<Accordion title="google_docs/insert_table_column">
**설명:** 기존 표의 참조 셀 왼쪽 또는 오른쪽에 새 열을 삽입합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
- `rowIndex` (integer, 선택사항): 참조 셀의 행 인덱스 (0 기반). 기본값: `0`.
- `columnIndex` (integer, 필수): 참조 셀의 열 인덱스 (0 기반).
- `insertRight` (boolean, 선택사항): `true`이면 오른쪽에, `false`이면 왼쪽에 삽입. 기본값: `true`.
</Accordion>
<Accordion title="google_docs/delete_table_row">
**설명:** Google 문서의 기존 표에서 행을 삭제합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
- `rowIndex` (integer, 필수): 삭제할 행 인덱스 (0 기반).
- `columnIndex` (integer, 선택사항): 행의 아무 셀의 열 인덱스 (0 기반). 기본값: `0`.
</Accordion>
<Accordion title="google_docs/delete_table_column">
**설명:** Google 문서의 기존 표에서 열을 삭제합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
- `rowIndex` (integer, 선택사항): 열의 아무 셀의 행 인덱스 (0 기반). 기본값: `0`.
- `columnIndex` (integer, 필수): 삭제할 열 인덱스 (0 기반).
</Accordion>
<Accordion title="google_docs/merge_table_cells">
**설명:** 표 셀 범위를 단일 셀로 병합합니다. 모든 셀의 내용이 보존됩니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
- `rowIndex` (integer, 필수): 병합의 시작 행 인덱스 (0 기반).
- `columnIndex` (integer, 필수): 병합의 시작 열 인덱스 (0 기반).
- `rowSpan` (integer, 필수): 병합할 행 수.
- `columnSpan` (integer, 필수): 병합할 열 수.
</Accordion>
<Accordion title="google_docs/unmerge_table_cells">
**설명:** 이전에 병합된 표 셀을 개별 셀로 분리합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
- `rowIndex` (integer, 필수): 병합된 셀의 행 인덱스 (0 기반).
- `columnIndex` (integer, 필수): 병합된 셀의 열 인덱스 (0 기반).
- `rowSpan` (integer, 필수): 병합된 셀이 차지하는 행 수.
- `columnSpan` (integer, 필수): 병합된 셀이 차지하는 열 수.
</Accordion>
<Accordion title="google_docs/insert_inline_image">
**설명:** 공개 URL에서 Google 문서에 이미지를 삽입합니다. 이미지는 공개적으로 접근 가능해야 하고, 50MB 미만이며, PNG/JPEG/GIF 형식이어야 합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `uri` (string, 필수): 이미지의 공개 URL. 인증 없이 접근 가능해야 합니다.
- `index` (integer, 선택사항): 이미지를 삽입할 위치. 제공하지 않으면 문서 끝에 삽입됩니다. 기본값: `1`.
</Accordion>
<Accordion title="google_docs/insert_section_break">
**설명:** 서로 다른 서식을 가진 문서 섹션을 만들기 위해 섹션 나누기를 삽입합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `index` (integer, 필수): 섹션 나누기를 삽입할 위치.
- `sectionType` (string, 필수): 섹션 나누기의 유형. 옵션: `CONTINUOUS` (같은 페이지에 유지), `NEXT_PAGE` (새 페이지 시작).
</Accordion>
<Accordion title="google_docs/create_header">
**설명:** 문서의 머리글을 만듭니다. insert_text를 사용하여 머리글 내용을 추가할 수 있는 headerId를 반환합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `type` (string, 선택사항): 머리글 유형. 옵션: `DEFAULT`. 기본값: `DEFAULT`.
</Accordion>
<Accordion title="google_docs/create_footer">
**설명:** 문서의 바닥글을 만듭니다. insert_text를 사용하여 바닥글 내용을 추가할 수 있는 footerId를 반환합니다.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `type` (string, 선택사항): 바닥글 유형. 옵션: `DEFAULT`. 기본값: `DEFAULT`.
</Accordion>
<Accordion title="google_docs/delete_header">
**설명:** 문서에서 머리글을 삭제합니다. headerId를 찾으려면 get_document를 사용하세요.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `headerId` (string, 필수): 삭제할 머리글 ID. get_document 응답에서 가져오세요.
</Accordion>
<Accordion title="google_docs/delete_footer">
**설명:** 문서에서 바닥글을 삭제합니다. footerId를 찾으려면 get_document를 사용하세요.
**매개변수:**
- `documentId` (string, 필수): 문서 ID.
- `footerId` (string, 필수): 삭제할 바닥글 ID. get_document 응답에서 가져오세요.
</Accordion>
</AccordionGroup>
## 사용 예제

View File

@@ -61,6 +61,22 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="google_slides/get_presentation_metadata">
**설명:** 프레젠테이션에 대한 가벼운 메타데이터(제목, 슬라이드 수, 슬라이드 ID)를 가져옵니다. 전체 콘텐츠를 가져오기 전에 먼저 사용하세요.
**매개변수:**
- `presentationId` (string, 필수): 검색할 프레젠테이션의 ID.
</Accordion>
<Accordion title="google_slides/get_presentation_text">
**설명:** 프레젠테이션에서 모든 텍스트 콘텐츠를 추출합니다. 슬라이드 ID와 도형 및 테이블의 텍스트만 반환합니다 (포맷팅 없음).
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
</Accordion>
<Accordion title="google_slides/get_presentation">
**설명:** ID로 프레젠테이션을 검색합니다.
@@ -80,6 +96,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="google_slides/get_slide_text">
**설명:** 단일 슬라이드에서 텍스트 콘텐츠를 추출합니다. 도형 및 테이블의 텍스트만 반환합니다 (포맷팅 또는 스타일 없음).
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `pageObjectId` (string, 필수): 텍스트를 가져올 슬라이드/페이지의 ID.
</Accordion>
<Accordion title="google_slides/get_page">
**설명:** ID로 특정 페이지를 검색합니다.
@@ -98,6 +123,120 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="google_slides/create_slide">
**설명:** 프레젠테이션에 추가 빈 슬라이드를 추가합니다. 새 프레젠테이션에는 이미 빈 슬라이드가 하나 있습니다. 먼저 get_presentation_metadata를 확인하세요. 제목/본문 영역이 있는 슬라이드는 create_slide_with_layout을 사용하세요.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `insertionIndex` (integer, 선택사항): 슬라이드를 삽입할 위치 (0 기반). 생략하면 맨 끝에 추가됩니다.
</Accordion>
<Accordion title="google_slides/create_slide_with_layout">
**설명:** 제목, 본문 등의 플레이스홀더 영역이 있는 미리 정의된 레이아웃으로 슬라이드를 만듭니다. 구조화된 콘텐츠에는 create_slide보다 적합합니다. 생성 후 get_page로 플레이스홀더 ID를 찾고, 그 안에 텍스트를 삽입하세요.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `layout` (string, 필수): 레이아웃 유형. 옵션: `BLANK`, `TITLE`, `TITLE_AND_BODY`, `TITLE_AND_TWO_COLUMNS`, `TITLE_ONLY`, `SECTION_HEADER`, `ONE_COLUMN_TEXT`, `MAIN_POINT`, `BIG_NUMBER`. 제목+설명은 TITLE_AND_BODY, 제목만은 TITLE, 섹션 구분은 SECTION_HEADER가 적합합니다.
- `insertionIndex` (integer, 선택사항): 삽입할 위치 (0 기반). 생략하면 맨 끝에 추가됩니다.
</Accordion>
<Accordion title="google_slides/create_text_box">
**설명:** 콘텐츠가 있는 텍스트 상자를 슬라이드에 만듭니다. 제목, 설명, 단락에 사용합니다. 테이블에는 사용하지 마세요. 선택적으로 EMU 단위로 위치(x, y)와 크기(width, height)를 지정할 수 있습니다 (914400 EMU = 1 인치).
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 텍스트 상자를 추가할 슬라이드의 ID.
- `text` (string, 필수): 텍스트 상자의 텍스트 내용.
- `x` (integer, 선택사항): EMU 단위 X 위치 (914400 = 1 인치). 기본값: 914400 (왼쪽에서 1 인치).
- `y` (integer, 선택사항): EMU 단위 Y 위치 (914400 = 1 인치). 기본값: 914400 (위에서 1 인치).
- `width` (integer, 선택사항): EMU 단위 너비. 기본값: 7315200 (약 8 인치).
- `height` (integer, 선택사항): EMU 단위 높이. 기본값: 914400 (약 1 인치).
</Accordion>
<Accordion title="google_slides/delete_slide">
**설명:** 프레젠테이션에서 슬라이드를 제거합니다. 슬라이드 ID를 찾으려면 먼저 get_presentation을 사용하세요.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 삭제할 슬라이드의 객체 ID. get_presentation에서 가져옵니다.
</Accordion>
<Accordion title="google_slides/duplicate_slide">
**설명:** 기존 슬라이드의 복사본을 만듭니다. 복사본은 원본 바로 다음에 삽입됩니다.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 복제할 슬라이드의 객체 ID. get_presentation에서 가져옵니다.
</Accordion>
<Accordion title="google_slides/move_slides">
**설명:** 슬라이드를 새 위치로 이동하여 순서를 변경합니다. 슬라이드 ID는 현재 프레젠테이션 순서대로 있어야 합니다 (중복 없음).
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideIds` (string 배열, 필수): 이동할 슬라이드 ID 배열. 현재 프레젠테이션 순서대로 있어야 합니다.
- `insertionIndex` (integer, 필수): 대상 위치 (0 기반). 0 = 맨 앞, 슬라이드 수 = 맨 끝.
</Accordion>
<Accordion title="google_slides/insert_youtube_video">
**설명:** 슬라이드에 YouTube 동영상을 삽입합니다. 동영상 ID는 YouTube URL의 "v=" 다음 값입니다 (예: youtube.com/watch?v=abc123의 경우 "abc123" 사용).
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 동영상을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
- `videoId` (string, 필수): YouTube 동영상 ID (URL의 v= 다음 값).
</Accordion>
<Accordion title="google_slides/insert_drive_video">
**설명:** 슬라이드에 Google Drive의 동영상을 삽입합니다. 파일 ID는 Drive 파일 URL에서 찾을 수 있습니다.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 동영상을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
- `fileId` (string, 필수): 동영상의 Google Drive 파일 ID.
</Accordion>
<Accordion title="google_slides/set_slide_background_image">
**설명:** 슬라이드의 배경 이미지를 설정합니다. 이미지 URL은 공개적으로 액세스 가능해야 합니다.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 배경을 설정할 슬라이드의 ID. get_presentation에서 가져옵니다.
- `imageUrl` (string, 필수): 배경으로 사용할 이미지의 공개적으로 액세스 가능한 URL.
</Accordion>
<Accordion title="google_slides/create_table">
**설명:** 슬라이드에 빈 테이블을 만듭니다. 콘텐츠가 있는 테이블을 만들려면 create_table_with_content를 사용하세요.
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 테이블을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
- `rows` (integer, 필수): 테이블의 행 수.
- `columns` (integer, 필수): 테이블의 열 수.
</Accordion>
<Accordion title="google_slides/create_table_with_content">
**설명:** 한 번의 작업으로 콘텐츠가 있는 테이블을 만듭니다. 콘텐츠는 2D 배열로 제공하며, 각 내부 배열은 행을 나타냅니다. 예: [["Header1", "Header2"], ["Row1Col1", "Row1Col2"]].
**매개변수:**
- `presentationId` (string, 필수): 프레젠테이션의 ID.
- `slideId` (string, 필수): 테이블을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
- `rows` (integer, 필수): 테이블의 행 수.
- `columns` (integer, 필수): 테이블의 열 수.
- `content` (array, 필수): 2D 배열 형태의 테이블 콘텐츠. 각 내부 배열은 행입니다. 예: [["Year", "Revenue"], ["2023", "$10M"]].
</Accordion>
<Accordion title="google_slides/import_data_from_sheet">
**설명:** Google 시트에서 프레젠테이션으로 데이터를 가져옵니다.

View File

@@ -148,6 +148,16 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_excel/get_table_data">
**설명:** Excel 워크시트의 특정 테이블에서 데이터를 가져옵니다.
**매개변수:**
- `file_id` (string, 필수): Excel 파일의 ID.
- `worksheet_name` (string, 필수): 워크시트의 이름.
- `table_name` (string, 필수): 테이블의 이름.
</Accordion>
<Accordion title="microsoft_excel/create_chart">
**설명:** Excel 워크시트에 차트를 만듭니다.
@@ -180,6 +190,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_excel/get_used_range_metadata">
**설명:** Excel 워크시트의 사용된 범위 메타데이터(크기만, 데이터 없음)를 가져옵니다.
**매개변수:**
- `file_id` (string, 필수): Excel 파일의 ID.
- `worksheet_name` (string, 필수): 워크시트의 이름.
</Accordion>
<Accordion title="microsoft_excel/list_charts">
**설명:** Excel 워크시트의 모든 차트를 가져옵니다.

View File

@@ -150,6 +150,49 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `item_id` (string, 필수): 파일의 ID.
</Accordion>
<Accordion title="microsoft_onedrive/list_files_by_path">
**설명:** 특정 OneDrive 경로의 파일과 폴더를 나열합니다.
**매개변수:**
- `folder_path` (string, 필수): 폴더 경로 (예: 'Documents/Reports').
- `top` (integer, 선택사항): 검색할 항목 수 (최대 1000). 기본값: 50.
- `orderby` (string, 선택사항): 필드별 정렬 (예: "name asc", "lastModifiedDateTime desc"). 기본값: "name asc".
</Accordion>
<Accordion title="microsoft_onedrive/get_recent_files">
**설명:** OneDrive에서 최근에 액세스한 파일을 가져옵니다.
**매개변수:**
- `top` (integer, 선택사항): 검색할 항목 수 (최대 200). 기본값: 25.
</Accordion>
<Accordion title="microsoft_onedrive/get_shared_with_me">
**설명:** 사용자와 공유된 파일과 폴더를 가져옵니다.
**매개변수:**
- `top` (integer, 선택사항): 검색할 항목 수 (최대 200). 기본값: 50.
- `orderby` (string, 선택사항): 필드별 정렬. 기본값: "name asc".
</Accordion>
<Accordion title="microsoft_onedrive/get_file_by_path">
**설명:** 경로로 특정 파일 또는 폴더에 대한 정보를 가져옵니다.
**매개변수:**
- `file_path` (string, 필수): 파일 또는 폴더 경로 (예: 'Documents/report.docx').
</Accordion>
<Accordion title="microsoft_onedrive/download_file_by_path">
**설명:** 경로로 OneDrive에서 파일을 다운로드합니다.
**매개변수:**
- `file_path` (string, 필수): 파일 경로 (예: 'Documents/report.docx').
</Accordion>
</AccordionGroup>
## 사용 예제
@@ -183,6 +226,62 @@ crew = Crew(
crew.kickoff()
```
### 파일 업로드 및 관리
```python
from crewai import Agent, Task, Crew
# 파일 작업에 특화된 에이전트 생성
file_operator = Agent(
role="파일 운영자",
goal="파일을 정확하게 업로드, 다운로드 및 관리",
backstory="파일 처리 및 콘텐츠 관리에 능숙한 AI 어시스턴트.",
apps=['microsoft_onedrive/upload_file', 'microsoft_onedrive/download_file', 'microsoft_onedrive/get_file_info']
)
# 파일 업로드 및 관리 작업
file_management_task = Task(
description="'report.txt'라는 이름의 텍스트 파일을 'This is a sample report for the project.' 내용으로 업로드한 다음 업로드된 파일에 대한 정보를 가져오세요.",
agent=file_operator,
expected_output="파일이 성공적으로 업로드되고 파일 정보가 검색됨."
)
crew = Crew(
agents=[file_operator],
tasks=[file_management_task]
)
crew.kickoff()
```
### 파일 정리 및 공유
```python
from crewai import Agent, Task, Crew
# 파일 정리 및 공유를 위한 에이전트 생성
file_organizer = Agent(
role="파일 정리자",
goal="파일을 정리하고 협업을 위한 공유 링크 생성",
backstory="파일 정리 및 공유 권한 관리에 뛰어난 AI 어시스턴트.",
apps=['microsoft_onedrive/search_files', 'microsoft_onedrive/move_item', 'microsoft_onedrive/share_item', 'microsoft_onedrive/create_folder']
)
# 파일 정리 및 공유 작업
organize_share_task = Task(
description="이름에 'presentation'이 포함된 파일을 검색하고, '프레젠테이션'이라는 폴더를 만든 다음, 찾은 파일을 이 폴더로 이동하고 폴더에 대한 읽기 전용 공유 링크를 생성하세요.",
agent=file_organizer,
expected_output="파일이 '프레젠테이션' 폴더로 정리되고 공유 링크가 생성됨."
)
crew = Crew(
agents=[file_organizer],
tasks=[organize_share_task]
)
crew.kickoff()
```
## 문제 해결
### 일반적인 문제
@@ -196,6 +295,30 @@ crew.kickoff()
- 파일 업로드 시 `file_name`과 `content`가 제공되는지 확인하세요.
- 바이너리 파일의 경우 내용이 Base64로 인코딩되어야 합니다.
- OneDrive에 대한 쓰기 권한이 있는지 확인하세요.
**파일/폴더 ID 문제**
- 특정 파일 또는 폴더에 액세스할 때 항목 ID가 올바른지 다시 확인하세요.
- 항목 ID는 `list_files` 또는 `search_files`와 같은 다른 작업에서 반환됩니다.
- 참조하는 항목이 존재하고 액세스 가능한지 확인하세요.
**검색 및 필터 작업**
- `search_files` 작업에 적절한 검색어를 사용하세요.
- `filter` 매개변수의 경우 올바른 OData 문법을 사용하세요.
**파일 작업 (복사/이동)**
- `move_item`의 경우 `item_id`와 `parent_id`가 모두 제공되는지 확인하세요.
- `copy_item`의 경우 `item_id`만 필요합니다. `parent_id`는 지정하지 않으면 루트로 기본 설정됩니다.
- 대상 폴더가 존재하고 액세스 가능한지 확인하세요.
**공유 링크 생성**
- 공유 링크를 만들기 전에 항목이 존재하는지 확인하세요.
- 공유 요구 사항에 따라 적절한 `type`과 `scope`를 선택하세요.
- `anonymous` 범위는 로그인 없이 액세스를 허용합니다. `organization`은 조직 계정이 필요합니다.
### 도움 받기

View File

@@ -132,6 +132,74 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `companyName` (string, 선택사항): 연락처의 회사 이름.
</Accordion>
<Accordion title="microsoft_outlook/get_message">
**설명:** ID로 특정 이메일 메시지를 가져옵니다.
**매개변수:**
- `message_id` (string, 필수): 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록. 예: "id,subject,body,from,receivedDateTime". 기본값: "id,subject,body,from,toRecipients,receivedDateTime".
</Accordion>
<Accordion title="microsoft_outlook/reply_to_email">
**설명:** 이메일 메시지에 회신합니다.
**매개변수:**
- `message_id` (string, 필수): 회신할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
- `comment` (string, 필수): 회신 메시지 내용. 일반 텍스트 또는 HTML 가능. 원본 메시지가 이 내용 아래에 인용됩니다.
</Accordion>
<Accordion title="microsoft_outlook/forward_email">
**설명:** 이메일 메시지를 전달합니다.
**매개변수:**
- `message_id` (string, 필수): 전달할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
- `to_recipients` (array, 필수): 전달할 받는 사람의 이메일 주소 배열. 예: ["john@example.com", "jane@example.com"].
- `comment` (string, 선택사항): 전달된 콘텐츠 위에 포함할 선택적 메시지. 일반 텍스트 또는 HTML 가능.
</Accordion>
<Accordion title="microsoft_outlook/mark_message_read">
**설명:** 메시지를 읽음 또는 읽지 않음으로 표시합니다.
**매개변수:**
- `message_id` (string, 필수): 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
- `is_read` (boolean, 필수): 읽음으로 표시하려면 true, 읽지 않음으로 표시하려면 false로 설정합니다.
</Accordion>
<Accordion title="microsoft_outlook/delete_message">
**설명:** 이메일 메시지를 삭제합니다.
**매개변수:**
- `message_id` (string, 필수): 삭제할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
</Accordion>
<Accordion title="microsoft_outlook/update_event">
**설명:** 기존 캘린더 이벤트를 업데이트합니다.
**매개변수:**
- `event_id` (string, 필수): 이벤트의 고유 식별자. get_calendar_events 작업에서 얻을 수 있습니다.
- `subject` (string, 선택사항): 이벤트의 새 제목/제목.
- `start_time` (string, 선택사항): ISO 8601 형식의 새 시작 시간 (예: "2024-01-20T10:00:00"). 필수: 이 필드 사용 시 start_timezone도 제공해야 합니다.
- `start_timezone` (string, 선택사항): 시작 시간의 시간대. start_time 업데이트 시 필수. 예: "Pacific Standard Time", "Eastern Standard Time", "UTC".
- `end_time` (string, 선택사항): ISO 8601 형식의 새 종료 시간. 필수: 이 필드 사용 시 end_timezone도 제공해야 합니다.
- `end_timezone` (string, 선택사항): 종료 시간의 시간대. end_time 업데이트 시 필수. 예: "Pacific Standard Time", "Eastern Standard Time", "UTC".
- `location` (string, 선택사항): 이벤트의 새 위치.
- `body` (string, 선택사항): 이벤트의 새 본문/설명. HTML 형식 지원.
</Accordion>
<Accordion title="microsoft_outlook/delete_event">
**설명:** 캘린더 이벤트를 삭제합니다.
**매개변수:**
- `event_id` (string, 필수): 삭제할 이벤트의 고유 식별자. get_calendar_events 작업에서 얻을 수 있습니다.
</Accordion>
</AccordionGroup>
## 사용 예제
@@ -165,6 +233,62 @@ crew = Crew(
crew.kickoff()
```
### 이메일 관리 및 검색
```python
from crewai import Agent, Task, Crew
# 이메일 관리에 특화된 에이전트 생성
email_manager = Agent(
role="이메일 관리자",
goal="이메일 메시지를 검색하고 가져와 정리",
backstory="이메일 정리 및 관리에 능숙한 AI 어시스턴트.",
apps=['microsoft_outlook/get_messages']
)
# 이메일 검색 및 가져오기 작업
search_emails_task = Task(
description="최신 읽지 않은 이메일 20건을 가져와 가장 중요한 것들의 요약을 제공하세요.",
agent=email_manager,
expected_output="주요 읽지 않은 이메일의 요약과 핵심 세부 정보."
)
crew = Crew(
agents=[email_manager],
tasks=[search_emails_task]
)
crew.kickoff()
```
### 캘린더 및 연락처 관리
```python
from crewai import Agent, Task, Crew
# 캘린더 및 연락처 관리를 위한 에이전트 생성
scheduler = Agent(
role="캘린더 및 연락처 관리자",
goal="캘린더 이벤트를 관리하고 연락처 정보를 유지",
backstory="일정 관리 및 연락처 정리를 담당하는 AI 어시스턴트.",
apps=['microsoft_outlook/create_calendar_event', 'microsoft_outlook/get_calendar_events', 'microsoft_outlook/create_contact']
)
# 회의 생성 및 연락처 추가 작업
schedule_task = Task(
description="내일 오후 2시 '팀 회의' 제목으로 '회의실 A' 장소의 캘린더 이벤트를 만들고, 'john.smith@example.com' 이메일과 '프로젝트 매니저' 직책으로 'John Smith'의 새 연락처를 추가하세요.",
agent=scheduler,
expected_output="캘린더 이벤트가 생성되고 새 연락처가 추가됨."
)
crew = Crew(
agents=[scheduler],
tasks=[schedule_task]
)
crew.kickoff()
```
## 문제 해결
### 일반적인 문제
@@ -173,11 +297,29 @@ crew.kickoff()
- Microsoft 계정이 이메일, 캘린더 및 연락처 액세스에 필요한 권한을 가지고 있는지 확인하세요.
- 필요한 범위: `Mail.Read`, `Mail.Send`, `Calendars.Read`, `Calendars.ReadWrite`, `Contacts.Read`, `Contacts.ReadWrite`.
- OAuth 연결에 필요한 모든 범위가 포함되어 있는지 확인하세요.
**이메일 보내기 문제**
- `send_email`에 `to_recipients`, `subject`, `body`가 제공되는지 확인하세요.
- 이메일 주소가 올바르게 형식화되어 있는지 확인하세요.
- 계정에 `Mail.Send` 권한이 있는지 확인하세요.
**캘린더 이벤트 생성**
- `subject`, `start_datetime`, `end_datetime`이 제공되는지 확인하세요.
- 날짜/시간 필드에 적절한 ISO 8601 형식을 사용하세요 (예: '2024-01-20T10:00:00').
- 이벤트가 잘못된 시간에 표시되는 경우 시간대 설정을 확인하세요.
**연락처 관리**
- `create_contact`의 경우 필수인 `displayName`이 제공되는지 확인하세요.
- `emailAddresses`를 제공할 때 `address`와 `name` 속성이 있는 올바른 객체 형식을 사용하세요.
**검색 및 필터 문제**
- `filter` 매개변수에 올바른 OData 문법을 사용하세요.
- 날짜 필터의 경우 ISO 8601 형식을 사용하세요 (예: "receivedDateTime ge '2024-01-01T00:00:00Z'").
### 도움 받기

View File

@@ -77,6 +77,17 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_sharepoint/get_drives">
**설명:** SharePoint 사이트의 모든 문서 라이브러리(드라이브)를 나열합니다. 파일 작업을 사용하기 전에 사용 가능한 라이브러리를 찾으려면 이 작업을 사용하세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `top` (integer, 선택사항): 페이지당 반환할 최대 드라이브 수 (1-999). 기본값: 100
- `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'id,name,webUrl,driveType').
</Accordion>
<Accordion title="microsoft_sharepoint/get_site_lists">
**설명:** SharePoint 사이트의 모든 목록을 가져옵니다.
@@ -145,20 +156,317 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
</Accordion>
<Accordion title="microsoft_sharepoint/get_drive_items">
**설명:** SharePoint 문서 라이브러리에서 파일과 폴더를 가져옵니다.
<Accordion title="microsoft_sharepoint/list_files">
**설명:** SharePoint 문서 라이브러리에서 파일과 폴더를 가져옵니다. 기본적으로 루트 폴더를 나열하지만 folder_id를 제공하여 하위 폴더로 이동할 수 있습니다.
**매개변수:**
- `site_id` (string, 필수): SharePoint 사이트의 ID.
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `folder_id` (string, 선택사항): 내용을 나열할 폴더의 ID. 루트 폴더의 경우 'root'를 사용하거나 이전 list_files 호출에서 가져온 폴더 ID를 제공하세요. 기본값: 'root'
- `top` (integer, 선택사항): 페이지당 반환할 최대 항목 수 (1-1000). 기본값: 50
- `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
- `orderby` (string, 선택사항): 결과 정렬 순서 (예: 'name asc', 'size desc', 'lastModifiedDateTime desc'). 기본값: 'name asc'
- `filter` (string, 선택사항): 결과를 좁히기 위한 OData 필터 (예: 'file ne null'은 파일만, 'folder ne null'은 폴더만).
- `select` (string, 선택사항): 반환할 필드의 쉼표로 구분된 목록 (예: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
</Accordion>
<Accordion title="microsoft_sharepoint/delete_drive_item">
**설명:** SharePoint 문서 라이브러리에서 파일 또는 폴더를 삭제합니다.
<Accordion title="microsoft_sharepoint/delete_file">
**설명:** SharePoint 문서 라이브러리에서 파일 또는 폴더를 삭제합니다. 폴더의 경우 모든 내용이 재귀적으로 삭제됩니다. 항목은 사이트 휴지통으로 이동됩니다.
**매개변수:**
- `site_id` (string, 필수): SharePoint 사이트의 ID.
- `item_id` (string, 필수): 삭제할 파일 또는 폴더의 ID.
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): 삭제할 파일 또는 폴더의 고유 식별자. list_files에서 가져오세요.
</Accordion>
<Accordion title="microsoft_sharepoint/list_files_by_path">
**설명:** 경로로 SharePoint 문서 라이브러리 폴더의 파일과 폴더를 나열합니다. 깊은 탐색을 위해 여러 list_files 호출보다 더 효율적입니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `folder_path` (string, 필수): 앞뒤 슬래시 없이 폴더의 전체 경로 (예: 'Documents', 'Reports/2024/Q1').
- `top` (integer, 선택사항): 페이지당 반환할 최대 항목 수 (1-1000). 기본값: 50
- `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
- `orderby` (string, 선택사항): 결과 정렬 순서 (예: 'name asc', 'size desc'). 기본값: 'name asc'
- `select` (string, 선택사항): 반환할 필드의 쉼표로 구분된 목록 (예: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
</Accordion>
<Accordion title="microsoft_sharepoint/download_file">
**설명:** SharePoint 문서 라이브러리에서 원시 파일 내용을 다운로드합니다. 일반 텍스트 파일(.txt, .csv, .json)에만 사용하세요. Excel 파일의 경우 Excel 전용 작업을 사용하세요. Word 파일의 경우 get_word_document_content를 사용하세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): 다운로드할 파일의 고유 식별자. list_files 또는 list_files_by_path에서 가져오세요.
</Accordion>
<Accordion title="microsoft_sharepoint/get_file_info">
**설명:** SharePoint 문서 라이브러리의 특정 파일 또는 폴더에 대한 자세한 메타데이터를 가져옵니다. 이름, 크기, 생성/수정 날짜 및 작성자 정보가 포함됩니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): 파일 또는 폴더의 고유 식별자. list_files 또는 list_files_by_path에서 가져오세요.
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'id,name,size,createdDateTime,lastModifiedDateTime,webUrl,createdBy,lastModifiedBy').
</Accordion>
<Accordion title="microsoft_sharepoint/create_folder">
**설명:** SharePoint 문서 라이브러리에 새 폴더를 만듭니다. 기본적으로 루트에 폴더를 만들며 하위 폴더를 만들려면 parent_id를 사용하세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `folder_name` (string, 필수): 새 폴더의 이름. 사용할 수 없는 문자: \ / : * ? " < > |
- `parent_id` (string, 선택사항): 상위 폴더의 ID. 문서 라이브러리 루트의 경우 'root'를 사용하거나 list_files에서 가져온 폴더 ID를 제공하세요. 기본값: 'root'
</Accordion>
<Accordion title="microsoft_sharepoint/search_files">
**설명:** 키워드로 SharePoint 문서 라이브러리에서 파일과 폴더를 검색합니다. 파일 이름, 폴더 이름 및 Office 문서의 파일 내용을 검색합니다. 와일드카드나 특수 문자를 사용하지 마세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `query` (string, 필수): 검색 키워드 (예: 'report', 'budget 2024'). *.txt와 같은 와일드카드는 지원되지 않습니다.
- `top` (integer, 선택사항): 페이지당 반환할 최대 결과 수 (1-1000). 기본값: 50
- `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
- `select` (string, 선택사항): 반환할 필드의 쉼표로 구분된 목록 (예: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
</Accordion>
<Accordion title="microsoft_sharepoint/copy_file">
**설명:** SharePoint 내에서 파일 또는 폴더를 새 위치로 복사합니다. 원본 항목은 변경되지 않습니다. 대용량 파일의 경우 복사 작업은 비동기적입니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): 복사할 파일 또는 폴더의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `destination_folder_id` (string, 필수): 대상 폴더의 ID. 루트 폴더의 경우 'root'를 사용하거나 list_files에서 가져온 폴더 ID를 사용하세요.
- `new_name` (string, 선택사항): 복사본의 새 이름. 제공하지 않으면 원래 이름이 사용됩니다.
</Accordion>
<Accordion title="microsoft_sharepoint/move_file">
**설명:** SharePoint 내에서 파일 또는 폴더를 새 위치로 이동합니다. 항목은 원래 위치에서 제거됩니다. 폴더의 경우 모든 내용도 함께 이동됩니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): 이동할 파일 또는 폴더의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `destination_folder_id` (string, 필수): 대상 폴더의 ID. 루트 폴더의 경우 'root'를 사용하거나 list_files에서 가져온 폴더 ID를 사용하세요.
- `new_name` (string, 선택사항): 이동된 항목의 새 이름. 제공하지 않으면 원래 이름이 유지됩니다.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_worksheets">
**설명:** SharePoint 문서 라이브러리에 저장된 Excel 통합 문서의 모든 워크시트(탭)를 나열합니다. 반환된 워크시트 이름을 다른 Excel 작업에 사용하세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'id,name,position,visibility').
- `filter` (string, 선택사항): OData 필터 표현식 (예: "visibility eq 'Visible'"로 숨겨진 시트 제외).
- `top` (integer, 선택사항): 반환할 최대 워크시트 수. 최소: 1, 최대: 999
- `orderby` (string, 선택사항): 정렬 순서 (예: 'position asc'로 탭 순서대로 반환).
</Accordion>
<Accordion title="microsoft_sharepoint/create_excel_worksheet">
**설명:** SharePoint 문서 라이브러리에 저장된 Excel 통합 문서에 새 워크시트(탭)를 만듭니다. 새 시트는 탭 목록의 끝에 추가됩니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `name` (string, 필수): 새 워크시트의 이름. 최대 31자. 사용할 수 없는 문자: \ / * ? : [ ]. 통합 문서 내에서 고유해야 합니다.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_range_data">
**설명:** SharePoint에 저장된 Excel 워크시트의 특정 범위에서 셀 값을 가져옵니다. 크기를 모르는 상태에서 모든 데이터를 읽으려면 대신 get_excel_used_range를 사용하세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 읽을 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
- `range` (string, 필수): A1 표기법의 셀 범위 (예: 'A1:C10', 'A:C', '1:5', 'A1').
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text').
</Accordion>
<Accordion title="microsoft_sharepoint/update_excel_range_data">
**설명:** SharePoint에 저장된 Excel 워크시트의 특정 범위에 값을 씁니다. 기존 셀 내용을 덮어씁니다. values 배열의 크기는 범위 크기와 정확히 일치해야 합니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 업데이트할 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
- `range` (string, 필수): 값을 쓸 A1 표기법의 셀 범위 (예: 'A1:C3'은 3x3 블록).
- `values` (array, 필수): 2D 값 배열 (셀을 포함하는 행). A1:B2의 예: [["Header1", "Header2"], ["Value1", "Value2"]]. 셀을 지우려면 null을 사용하세요.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_used_range_metadata">
**설명:** 실제 셀 값 없이 워크시트에서 사용된 범위의 메타데이터(주소 및 크기)만 반환합니다. 대용량 파일에서 데이터를 청크로 읽기 전에 스프레드시트 크기를 파악하는 데 이상적입니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 읽을 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_used_range">
**설명:** SharePoint에 저장된 워크시트에서 데이터가 포함된 모든 셀을 가져옵니다. 2MB보다 큰 파일에는 사용하지 마세요. 대용량 파일의 경우 먼저 get_excel_used_range_metadata를 사용한 다음 get_excel_range_data로 작은 청크로 읽으세요.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 읽을 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text,rowCount,columnCount').
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_cell">
**설명:** SharePoint의 Excel 파일에서 행과 열 인덱스로 단일 셀의 값을 가져옵니다. 인덱스는 0 기반입니다 (행 0 = Excel 행 1, 열 0 = 열 A).
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
- `row` (integer, 필수): 0 기반 행 인덱스 (행 0 = Excel 행 1). 유효 범위: 0-1048575
- `column` (integer, 필수): 0 기반 열 인덱스 (열 0 = A, 열 1 = B). 유효 범위: 0-16383
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text').
</Accordion>
<Accordion title="microsoft_sharepoint/add_excel_table">
**설명:** 셀 범위를 필터링, 정렬 및 구조화된 데이터 기능이 있는 서식이 지정된 Excel 테이블로 변환합니다. 테이블을 만들면 add_excel_table_row로 데이터를 추가할 수 있습니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 데이터 범위가 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
- `range` (string, 필수): 헤더와 데이터를 포함하여 테이블로 변환할 셀 범위 (예: 'A1:D10'에서 A1:D1은 열 헤더).
- `has_headers` (boolean, 선택사항): 첫 번째 행에 열 헤더가 포함되어 있으면 true로 설정. 기본값: true
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_tables">
**설명:** SharePoint에 저장된 특정 Excel 워크시트의 모든 테이블을 나열합니다. id, name, showHeaders 및 showTotals를 포함한 테이블 속성을 반환합니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 테이블을 가져올 워크시트의 이름. get_excel_worksheets에서 가져오세요.
</Accordion>
<Accordion title="microsoft_sharepoint/add_excel_table_row">
**설명:** SharePoint 파일의 Excel 테이블 끝에 새 행을 추가합니다. values 배열은 테이블의 열 수와 같은 수의 요소를 가져야 합니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 테이블이 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
- `table_name` (string, 필수): 행을 추가할 테이블의 이름 (예: 'Table1'). get_excel_tables에서 가져오세요. 대소문자를 구분합니다.
- `values` (array, 필수): 새 행의 셀 값 배열로 테이블 순서대로 열당 하나씩 (예: ["John Doe", "john@example.com", 25]).
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_table_data">
**설명:** SharePoint 파일의 Excel 테이블에서 모든 행을 데이터 범위로 가져옵니다. 정확한 범위를 알 필요가 없으므로 구조화된 테이블 작업 시 get_excel_range_data보다 쉽습니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 테이블이 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
- `table_name` (string, 필수): 데이터를 가져올 테이블의 이름 (예: 'Table1'). get_excel_tables에서 가져오세요. 대소문자를 구분합니다.
- `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text').
</Accordion>
<Accordion title="microsoft_sharepoint/create_excel_chart">
**설명:** SharePoint에 저장된 Excel 워크시트에 데이터 범위에서 차트 시각화를 만듭니다. 차트는 워크시트에 포함됩니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 차트를 만들 워크시트의 이름. get_excel_worksheets에서 가져오세요.
- `chart_type` (string, 필수): 차트 유형 (예: 'ColumnClustered', 'ColumnStacked', 'Line', 'LineMarkers', 'Pie', 'Bar', 'BarClustered', 'Area', 'Scatter', 'Doughnut').
- `source_data` (string, 필수): 헤더를 포함한 A1 표기법의 차트 데이터 범위 (예: 'A1:B10').
- `series_by` (string, 선택사항): 데이터 계열 구성 방법: 'Auto', 'Columns' 또는 'Rows'. 기본값: 'Auto'
</Accordion>
<Accordion title="microsoft_sharepoint/list_excel_charts">
**설명:** SharePoint에 저장된 Excel 워크시트에 포함된 모든 차트를 나열합니다. id, name, chartType, height, width 및 position을 포함한 차트 속성을 반환합니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 차트를 나열할 워크시트의 이름. get_excel_worksheets에서 가져오세요.
</Accordion>
<Accordion title="microsoft_sharepoint/delete_excel_worksheet">
**설명:** SharePoint에 저장된 Excel 통합 문서에서 워크시트(탭)와 모든 내용을 영구적으로 제거합니다. 실행 취소할 수 없습니다. 통합 문서에는 최소 하나의 워크시트가 있어야 합니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 삭제할 워크시트의 이름. 대소문자를 구분합니다. 이 시트의 모든 데이터, 테이블 및 차트가 영구적으로 제거됩니다.
</Accordion>
<Accordion title="microsoft_sharepoint/delete_excel_table">
**설명:** SharePoint의 Excel 워크시트에서 테이블을 제거합니다. 테이블 구조(필터링, 서식, 테이블 기능)는 삭제되지만 기본 셀 데이터는 보존됩니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
- `worksheet_name` (string, 필수): 테이블이 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
- `table_name` (string, 필수): 삭제할 테이블의 이름 (예: 'Table1'). get_excel_tables에서 가져오세요. 테이블 삭제 후에도 셀의 데이터는 유지됩니다.
</Accordion>
<Accordion title="microsoft_sharepoint/list_excel_names">
**설명:** SharePoint에 저장된 Excel 통합 문서에 정의된 모든 명명된 범위를 가져옵니다. 명명된 범위는 셀 범위에 대한 사용자 정의 레이블입니다 (예: 'SalesData'는 A1:D100을 가리킴).
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
</Accordion>
<Accordion title="microsoft_sharepoint/get_word_document_content">
**설명:** SharePoint 문서 라이브러리에 저장된 Word 문서(.docx)에서 텍스트 내용을 다운로드하고 추출합니다. SharePoint에서 Word 문서를 읽는 권장 방법입니다.
**매개변수:**
- `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
- `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
- `item_id` (string, 필수): SharePoint에 있는 Word 문서(.docx)의 고유 식별자. list_files 또는 search_files에서 가져오세요.
</Accordion>
</AccordionGroup>

View File

@@ -107,6 +107,86 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `join_web_url` (string, 필수): 검색할 회의의 웹 참가 URL.
</Accordion>
<Accordion title="microsoft_teams/search_online_meetings_by_meeting_id">
**설명:** 외부 Meeting ID로 온라인 회의를 검색합니다.
**매개변수:**
- `join_meeting_id` (string, 필수): 참석자가 참가할 때 사용하는 회의 ID(숫자 코드). 회의 초대에 표시되는 joinMeetingId이며, Graph API meeting id가 아닙니다.
</Accordion>
<Accordion title="microsoft_teams/get_meeting">
**설명:** 특정 온라인 회의의 세부 정보를 가져옵니다.
**매개변수:**
- `meeting_id` (string, 필수): Graph API 회의 ID(긴 영숫자 문자열). create_meeting 또는 search_online_meetings 작업에서 얻을 수 있습니다. 숫자 joinMeetingId와 다릅니다.
</Accordion>
<Accordion title="microsoft_teams/get_team_members">
**설명:** 특정 팀의 멤버를 가져옵니다.
**매개변수:**
- `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
- `top` (integer, 선택사항): 페이지당 검색할 멤버 수 (1-999). 기본값: 100.
- `skip_token` (string, 선택사항): 이전 응답의 페이지네이션 토큰. 응답에 @odata.nextLink가 포함된 경우 $skiptoken 매개변수 값을 추출하여 여기에 전달하면 다음 페이지 결과를 가져올 수 있습니다.
</Accordion>
<Accordion title="microsoft_teams/create_channel">
**설명:** 팀에 새 채널을 만듭니다.
**매개변수:**
- `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
- `display_name` (string, 필수): Teams에 표시되는 채널 이름. 팀 내에서 고유해야 합니다. 최대 50자.
- `description` (string, 선택사항): 채널 목적을 설명하는 선택적 설명. 채널 세부 정보에 표시됩니다. 최대 1024자.
- `membership_type` (string, 선택사항): 채널 가시성. 옵션: standard, private. "standard" = 모든 팀 멤버에게 표시, "private" = 명시적으로 추가된 멤버에게만 표시. 기본값: standard.
</Accordion>
<Accordion title="microsoft_teams/get_message_replies">
**설명:** 채널의 특정 메시지에 대한 회신을 가져옵니다.
**매개변수:**
- `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
- `channel_id` (string, 필수): 채널의 고유 식별자. get_channels 작업에서 얻을 수 있습니다.
- `message_id` (string, 필수): 상위 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
- `top` (integer, 선택사항): 페이지당 검색할 회신 수 (1-50). 기본값: 50.
- `skip_token` (string, 선택사항): 이전 응답의 페이지네이션 토큰. 응답에 @odata.nextLink가 포함된 경우 $skiptoken 매개변수 값을 추출하여 여기에 전달하면 다음 페이지 결과를 가져올 수 있습니다.
</Accordion>
<Accordion title="microsoft_teams/reply_to_message">
**설명:** Teams 채널의 메시지에 회신합니다.
**매개변수:**
- `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
- `channel_id` (string, 필수): 채널의 고유 식별자. get_channels 작업에서 얻을 수 있습니다.
- `message_id` (string, 필수): 회신할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
- `message` (string, 필수): 회신 내용. HTML의 경우 서식 태그 포함. 텍스트의 경우 일반 텍스트만.
- `content_type` (string, 선택사항): 콘텐츠 형식. 옵션: html, text. "text"는 일반 텍스트, "html"은 서식이 있는 리치 텍스트. 기본값: text.
</Accordion>
<Accordion title="microsoft_teams/update_meeting">
**설명:** 기존 온라인 회의를 업데이트합니다.
**매개변수:**
- `meeting_id` (string, 필수): 회의의 고유 식별자. create_meeting 또는 search_online_meetings 작업에서 얻을 수 있습니다.
- `subject` (string, 선택사항): 새 회의 제목.
- `startDateTime` (string, 선택사항): 시간대가 포함된 ISO 8601 형식의 새 시작 시간. 예: "2024-01-20T10:00:00-08:00".
- `endDateTime` (string, 선택사항): 시간대가 포함된 ISO 8601 형식의 새 종료 시간.
</Accordion>
<Accordion title="microsoft_teams/delete_meeting">
**설명:** 온라인 회의를 삭제합니다.
**매개변수:**
- `meeting_id` (string, 필수): 삭제할 회의의 고유 식별자. create_meeting 또는 search_online_meetings 작업에서 얻을 수 있습니다.
</Accordion>
</AccordionGroup>
## 사용 예제
@@ -140,6 +220,62 @@ crew = Crew(
crew.kickoff()
```
### 메시징 및 커뮤니케이션
```python
from crewai import Agent, Task, Crew
# 메시징에 특화된 에이전트 생성
messenger = Agent(
role="Teams 메신저",
goal="Teams 채널에서 메시지 전송 및 검색",
backstory="팀 커뮤니케이션 및 메시지 관리에 능숙한 AI 어시스턴트.",
apps=['microsoft_teams/send_message', 'microsoft_teams/get_messages']
)
# 메시지 전송 및 최근 메시지 검색 작업
messaging_task = Task(
description="'your_team_id' 팀의 General 채널에 'Hello team! This is an automated update from our AI assistant.' 메시지를 보낸 다음 해당 채널의 최근 10개 메시지를 검색하세요.",
agent=messenger,
expected_output="메시지가 성공적으로 전송되고 최근 메시지가 검색됨."
)
crew = Crew(
agents=[messenger],
tasks=[messaging_task]
)
crew.kickoff()
```
### 회의 관리
```python
from crewai import Agent, Task, Crew
# 회의 관리를 위한 에이전트 생성
meeting_scheduler = Agent(
role="회의 스케줄러",
goal="Teams 회의 생성 및 관리",
backstory="회의 일정 관리 및 정리를 담당하는 AI 어시스턴트.",
apps=['microsoft_teams/create_meeting', 'microsoft_teams/search_online_meetings_by_join_url']
)
# 회의 생성 작업
schedule_meeting_task = Task(
description="내일 오전 10시에 1시간 동안 진행되는 '주간 팀 동기화' 제목의 Teams 회의를 생성하세요 (시간대가 포함된 적절한 ISO 8601 형식 사용).",
agent=meeting_scheduler,
expected_output="회의 세부 정보와 함께 Teams 회의가 성공적으로 생성됨."
)
crew = Crew(
agents=[meeting_scheduler],
tasks=[schedule_meeting_task]
)
crew.kickoff()
```
## 문제 해결
### 일반적인 문제
@@ -148,11 +284,35 @@ crew.kickoff()
- Microsoft 계정이 Teams 액세스에 필요한 권한을 가지고 있는지 확인하세요.
- 필요한 범위: `Team.ReadBasic.All`, `Channel.ReadBasic.All`, `ChannelMessage.Send`, `ChannelMessage.Read.All`, `OnlineMeetings.ReadWrite`, `OnlineMeetings.Read`.
- OAuth 연결에 필요한 모든 범위가 포함되어 있는지 확인하세요.
**팀 및 채널 액세스**
- 액세스하려는 팀의 멤버인지 확인하세요.
- 팀 및 채널 ID가 올바른지 다시 확인하세요.
- 팀 및 채널 ID는 `get_teams` 및 `get_channels` 작업을 사용하여 얻을 수 있습니다.
**메시지 전송 문제**
- `send_message`에 `team_id`, `channel_id`, `message`가 제공되는지 확인하세요.
- 지정된 채널에 메시지를 보낼 권한이 있는지 확인하세요.
- 메시지 형식에 따라 적절한 `content_type`(text 또는 html)을 선택하세요.
**회의 생성**
- `subject`, `startDateTime`, `endDateTime`이 제공되는지 확인하세요.
- 날짜/시간 필드에 시간대가 포함된 적절한 ISO 8601 형식을 사용하세요 (예: '2024-01-20T10:00:00-08:00').
- 회의 시간이 미래인지 확인하세요.
**메시지 검색 제한**
- `get_messages` 작업은 요청당 최대 50개 메시지만 검색할 수 있습니다.
- 메시지는 역시간순(최신순)으로 반환됩니다.
**회의 검색**
- `search_online_meetings_by_join_url`의 경우 참가 URL이 정확하고 올바르게 형식화되어 있는지 확인하세요.
- URL은 완전한 Teams 회의 참가 URL이어야 합니다.
### 도움 받기

View File

@@ -97,6 +97,26 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
- `file_id` (string, 필수): 삭제할 문서의 ID.
</Accordion>
<Accordion title="microsoft_word/copy_document">
**설명:** OneDrive의 새 위치에 문서를 복사합니다.
**매개변수:**
- `file_id` (string, 필수): 복사할 문서의 ID.
- `name` (string, 선택사항): 복사된 문서의 새 이름.
- `parent_id` (string, 선택사항): 대상 폴더의 ID (기본값: 루트).
</Accordion>
<Accordion title="microsoft_word/move_document">
**설명:** OneDrive의 새 위치로 문서를 이동합니다.
**매개변수:**
- `file_id` (string, 필수): 이동할 문서의 ID.
- `parent_id` (string, 필수): 대상 폴더의 ID.
- `name` (string, 선택사항): 이동된 문서의 새 이름.
</Accordion>
</AccordionGroup>
## 사용 예제

View File

@@ -200,6 +200,25 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
- `clientData` (array, opcional): Dados específicos do cliente. Cada item é um objeto com `key` (string) e `value` (string).
</Accordion>
<Accordion title="google_contacts/update_contact_group">
**Descrição:** Atualizar informações de um grupo de contatos.
**Parâmetros:**
- `resourceName` (string, obrigatório): O nome do recurso do grupo de contatos (ex: 'contactGroups/myContactGroup').
- `name` (string, obrigatório): O nome do grupo de contatos.
- `clientData` (array, opcional): Dados específicos do cliente. Cada item é um objeto com `key` (string) e `value` (string).
</Accordion>
<Accordion title="google_contacts/delete_contact_group">
**Descrição:** Excluir um grupo de contatos.
**Parâmetros:**
- `resourceName` (string, obrigatório): O nome do recurso do grupo de contatos a excluir (ex: 'contactGroups/myContactGroup').
- `deleteContacts` (boolean, opcional): Se os contatos do grupo também devem ser excluídos. Padrão: false
</Accordion>
</AccordionGroup>
## Exemplos de Uso

View File

@@ -131,6 +131,297 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
- `endIndex` (integer, obrigatório): O índice final do intervalo.
</Accordion>
<Accordion title="google_docs/create_document_with_content">
**Descrição:** Criar um novo documento do Google com conteúdo em uma única ação.
**Parâmetros:**
- `title` (string, obrigatório): O título para o novo documento. Aparece no topo do documento e no Google Drive.
- `content` (string, opcional): O conteúdo de texto a inserir no documento. Use `\n` para novos parágrafos.
</Accordion>
<Accordion title="google_docs/append_text">
**Descrição:** Adicionar texto ao final de um documento do Google. Insere automaticamente no final do documento sem necessidade de especificar um índice.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento obtido da resposta de create_document ou URL.
- `text` (string, obrigatório): Texto a adicionar ao final do documento. Use `\n` para novos parágrafos.
</Accordion>
<Accordion title="google_docs/set_text_bold">
**Descrição:** Aplicar ou remover formatação de negrito em texto de um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
- `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
- `bold` (boolean, obrigatório): Defina `true` para aplicar negrito, `false` para remover negrito.
</Accordion>
<Accordion title="google_docs/set_text_italic">
**Descrição:** Aplicar ou remover formatação de itálico em texto de um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
- `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
- `italic` (boolean, obrigatório): Defina `true` para aplicar itálico, `false` para remover itálico.
</Accordion>
<Accordion title="google_docs/set_text_underline">
**Descrição:** Adicionar ou remover formatação de sublinhado em texto de um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
- `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
- `underline` (boolean, obrigatório): Defina `true` para sublinhar, `false` para remover sublinhado.
</Accordion>
<Accordion title="google_docs/set_text_strikethrough">
**Descrição:** Adicionar ou remover formatação de tachado em texto de um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
- `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
- `strikethrough` (boolean, obrigatório): Defina `true` para adicionar tachado, `false` para remover.
</Accordion>
<Accordion title="google_docs/set_font_size">
**Descrição:** Alterar o tamanho da fonte do texto em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
- `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
- `fontSize` (number, obrigatório): Tamanho da fonte em pontos. Tamanhos comuns: 10, 11, 12, 14, 16, 18, 24, 36.
</Accordion>
<Accordion title="google_docs/set_text_color">
**Descrição:** Alterar a cor do texto usando valores RGB (escala 0-1) em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
- `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
- `red` (number, obrigatório): Componente vermelho (0-1). Exemplo: `1` para vermelho total.
- `green` (number, obrigatório): Componente verde (0-1). Exemplo: `0.5` para metade verde.
- `blue` (number, obrigatório): Componente azul (0-1). Exemplo: `0` para sem azul.
</Accordion>
<Accordion title="google_docs/create_hyperlink">
**Descrição:** Transformar texto existente em um hyperlink clicável em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do texto a transformar em link.
- `endIndex` (integer, obrigatório): Posição final do texto a transformar em link (exclusivo).
- `url` (string, obrigatório): A URL para a qual o link deve apontar. Exemplo: `"https://example.com"`.
</Accordion>
<Accordion title="google_docs/apply_heading_style">
**Descrição:** Aplicar um estilo de título ou parágrafo a um intervalo de texto em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do(s) parágrafo(s) a estilizar.
- `endIndex` (integer, obrigatório): Posição final do(s) parágrafo(s) a estilizar.
- `style` (string, obrigatório): O estilo a aplicar. Opções: `NORMAL_TEXT`, `TITLE`, `SUBTITLE`, `HEADING_1`, `HEADING_2`, `HEADING_3`, `HEADING_4`, `HEADING_5`, `HEADING_6`.
</Accordion>
<Accordion title="google_docs/set_paragraph_alignment">
**Descrição:** Definir o alinhamento de texto para parágrafos em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do(s) parágrafo(s) a alinhar.
- `endIndex` (integer, obrigatório): Posição final do(s) parágrafo(s) a alinhar.
- `alignment` (string, obrigatório): Alinhamento do texto. Opções: `START` (esquerda), `CENTER`, `END` (direita), `JUSTIFIED`.
</Accordion>
<Accordion title="google_docs/set_line_spacing">
**Descrição:** Definir o espaçamento entre linhas para parágrafos em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial do(s) parágrafo(s).
- `endIndex` (integer, obrigatório): Posição final do(s) parágrafo(s).
- `lineSpacing` (number, obrigatório): Espaçamento entre linhas como porcentagem. `100` = simples, `115` = 1.15x, `150` = 1.5x, `200` = duplo.
</Accordion>
<Accordion title="google_docs/create_paragraph_bullets">
**Descrição:** Converter parágrafos em uma lista com marcadores ou numerada em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial dos parágrafos a converter em lista.
- `endIndex` (integer, obrigatório): Posição final dos parágrafos a converter em lista.
- `bulletPreset` (string, obrigatório): Estilo de marcadores/numeração. Opções: `BULLET_DISC_CIRCLE_SQUARE`, `BULLET_DIAMONDX_ARROW3D_SQUARE`, `BULLET_CHECKBOX`, `BULLET_ARROW_DIAMOND_DISC`, `BULLET_STAR_CIRCLE_SQUARE`, `NUMBERED_DECIMAL_ALPHA_ROMAN`, `NUMBERED_DECIMAL_ALPHA_ROMAN_PARENS`, `NUMBERED_DECIMAL_NESTED`, `NUMBERED_UPPERALPHA_ALPHA_ROMAN`, `NUMBERED_UPPERROMAN_UPPERALPHA_DECIMAL`.
</Accordion>
<Accordion title="google_docs/delete_paragraph_bullets">
**Descrição:** Remover marcadores ou numeração de parágrafos em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `startIndex` (integer, obrigatório): Posição inicial dos parágrafos de lista.
- `endIndex` (integer, obrigatório): Posição final dos parágrafos de lista.
</Accordion>
<Accordion title="google_docs/insert_table_with_content">
**Descrição:** Inserir uma tabela com conteúdo em um documento do Google em uma única ação. Forneça o conteúdo como um array 2D.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `rows` (integer, obrigatório): Número de linhas na tabela.
- `columns` (integer, obrigatório): Número de colunas na tabela.
- `index` (integer, opcional): Posição para inserir a tabela. Se não fornecido, a tabela é inserida no final do documento.
- `content` (array, obrigatório): Conteúdo da tabela como um array 2D. Cada array interno é uma linha. Exemplo: `[["Ano", "Receita"], ["2023", "$43B"], ["2024", "$45B"]]`.
</Accordion>
<Accordion title="google_docs/insert_table_row">
**Descrição:** Inserir uma nova linha acima ou abaixo de uma célula de referência em uma tabela existente.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `tableStartIndex` (integer, obrigatório): O índice inicial da tabela. Obtenha de get_document.
- `rowIndex` (integer, obrigatório): Índice da linha (baseado em 0) da célula de referência.
- `columnIndex` (integer, opcional): Índice da coluna (baseado em 0) da célula de referência. Padrão: `0`.
- `insertBelow` (boolean, opcional): Se `true`, insere abaixo da linha de referência. Se `false`, insere acima. Padrão: `true`.
</Accordion>
<Accordion title="google_docs/insert_table_column">
**Descrição:** Inserir uma nova coluna à esquerda ou à direita de uma célula de referência em uma tabela existente.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
- `rowIndex` (integer, opcional): Índice da linha (baseado em 0) da célula de referência. Padrão: `0`.
- `columnIndex` (integer, obrigatório): Índice da coluna (baseado em 0) da célula de referência.
- `insertRight` (boolean, opcional): Se `true`, insere à direita. Se `false`, insere à esquerda. Padrão: `true`.
</Accordion>
<Accordion title="google_docs/delete_table_row">
**Descrição:** Excluir uma linha de uma tabela existente em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
- `rowIndex` (integer, obrigatório): Índice da linha (baseado em 0) a excluir.
- `columnIndex` (integer, opcional): Índice da coluna (baseado em 0) de qualquer célula na linha. Padrão: `0`.
</Accordion>
<Accordion title="google_docs/delete_table_column">
**Descrição:** Excluir uma coluna de uma tabela existente em um documento do Google.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
- `rowIndex` (integer, opcional): Índice da linha (baseado em 0) de qualquer célula na coluna. Padrão: `0`.
- `columnIndex` (integer, obrigatório): Índice da coluna (baseado em 0) a excluir.
</Accordion>
<Accordion title="google_docs/merge_table_cells">
**Descrição:** Mesclar um intervalo de células de tabela em uma única célula. O conteúdo de todas as células é preservado.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
- `rowIndex` (integer, obrigatório): Índice da linha inicial (baseado em 0) para a mesclagem.
- `columnIndex` (integer, obrigatório): Índice da coluna inicial (baseado em 0) para a mesclagem.
- `rowSpan` (integer, obrigatório): Número de linhas a mesclar.
- `columnSpan` (integer, obrigatório): Número de colunas a mesclar.
</Accordion>
<Accordion title="google_docs/unmerge_table_cells">
**Descrição:** Desfazer a mesclagem de células de tabela previamente mescladas, retornando-as a células individuais.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
- `rowIndex` (integer, obrigatório): Índice da linha (baseado em 0) da célula mesclada.
- `columnIndex` (integer, obrigatório): Índice da coluna (baseado em 0) da célula mesclada.
- `rowSpan` (integer, obrigatório): Número de linhas que a célula mesclada abrange.
- `columnSpan` (integer, obrigatório): Número de colunas que a célula mesclada abrange.
</Accordion>
<Accordion title="google_docs/insert_inline_image">
**Descrição:** Inserir uma imagem de uma URL pública em um documento do Google. A imagem deve ser publicamente acessível, ter menos de 50MB e estar no formato PNG/JPEG/GIF.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `uri` (string, obrigatório): URL pública da imagem. Deve ser acessível sem autenticação.
- `index` (integer, opcional): Posição para inserir a imagem. Se não fornecido, a imagem é inserida no final do documento. Padrão: `1`.
</Accordion>
<Accordion title="google_docs/insert_section_break">
**Descrição:** Inserir uma quebra de seção para criar seções de documento com formatação diferente.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `index` (integer, obrigatório): Posição para inserir a quebra de seção.
- `sectionType` (string, obrigatório): O tipo de quebra de seção. Opções: `CONTINUOUS` (permanece na mesma página), `NEXT_PAGE` (inicia uma nova página).
</Accordion>
<Accordion title="google_docs/create_header">
**Descrição:** Criar um cabeçalho para o documento. Retorna um headerId que pode ser usado com insert_text para adicionar conteúdo ao cabeçalho.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `type` (string, opcional): Tipo de cabeçalho. Opções: `DEFAULT`. Padrão: `DEFAULT`.
</Accordion>
<Accordion title="google_docs/create_footer">
**Descrição:** Criar um rodapé para o documento. Retorna um footerId que pode ser usado com insert_text para adicionar conteúdo ao rodapé.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `type` (string, opcional): Tipo de rodapé. Opções: `DEFAULT`. Padrão: `DEFAULT`.
</Accordion>
<Accordion title="google_docs/delete_header">
**Descrição:** Excluir um cabeçalho do documento. Use get_document para encontrar o headerId.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `headerId` (string, obrigatório): O ID do cabeçalho a excluir. Obtenha da resposta de get_document.
</Accordion>
<Accordion title="google_docs/delete_footer">
**Descrição:** Excluir um rodapé do documento. Use get_document para encontrar o footerId.
**Parâmetros:**
- `documentId` (string, obrigatório): O ID do documento.
- `footerId` (string, obrigatório): O ID do rodapé a excluir. Obtenha da resposta de get_document.
</Accordion>
</AccordionGroup>
## Exemplos de Uso

View File

@@ -61,6 +61,22 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="google_slides/get_presentation_metadata">
**Descrição:** Obter metadados leves de uma apresentação (título, número de slides, IDs dos slides). Use isso primeiro antes de recuperar o conteúdo completo.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação a ser recuperada.
</Accordion>
<Accordion title="google_slides/get_presentation_text">
**Descrição:** Extrair todo o conteúdo de texto de uma apresentação. Retorna IDs dos slides e texto de formas e tabelas apenas (sem formatação).
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
</Accordion>
<Accordion title="google_slides/get_presentation">
**Descrição:** Recupera uma apresentação por ID.
@@ -80,6 +96,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="google_slides/get_slide_text">
**Descrição:** Extrair conteúdo de texto de um único slide. Retorna apenas texto de formas e tabelas (sem formatação ou estilo).
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `pageObjectId` (string, obrigatório): O ID do slide/página para obter o texto.
</Accordion>
<Accordion title="google_slides/get_page">
**Descrição:** Recupera uma página específica por seu ID.
@@ -98,6 +123,120 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="google_slides/create_slide">
**Descrição:** Adicionar um slide em branco adicional a uma apresentação. Novas apresentações já possuem um slide em branco - verifique get_presentation_metadata primeiro. Para slides com áreas de título/corpo, use create_slide_with_layout.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `insertionIndex` (integer, opcional): Onde inserir o slide (baseado em 0). Se omitido, adiciona no final.
</Accordion>
<Accordion title="google_slides/create_slide_with_layout">
**Descrição:** Criar um slide com layout predefinido contendo áreas de espaço reservado para título, corpo, etc. Melhor que create_slide para conteúdo estruturado. Após criar, use get_page para encontrar os IDs de espaço reservado, depois insira texto neles.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `layout` (string, obrigatório): Tipo de layout. Um de: `BLANK`, `TITLE`, `TITLE_AND_BODY`, `TITLE_AND_TWO_COLUMNS`, `TITLE_ONLY`, `SECTION_HEADER`, `ONE_COLUMN_TEXT`, `MAIN_POINT`, `BIG_NUMBER`. TITLE_AND_BODY é melhor para título+descrição. TITLE para slides apenas com título. SECTION_HEADER para divisores de seção.
- `insertionIndex` (integer, opcional): Onde inserir (baseado em 0). Se omitido, adiciona no final.
</Accordion>
<Accordion title="google_slides/create_text_box">
**Descrição:** Criar uma caixa de texto em um slide com conteúdo. Use para títulos, descrições, parágrafos - não para tabelas. Opcionalmente especifique posição (x, y) e tamanho (width, height) em unidades EMU (914400 EMU = 1 polegada).
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do slide para adicionar a caixa de texto.
- `text` (string, obrigatório): O conteúdo de texto da caixa de texto.
- `x` (integer, opcional): Posição X em EMU (914400 = 1 polegada). Padrão: 914400 (1 polegada da esquerda).
- `y` (integer, opcional): Posição Y em EMU (914400 = 1 polegada). Padrão: 914400 (1 polegada do topo).
- `width` (integer, opcional): Largura em EMU. Padrão: 7315200 (~8 polegadas).
- `height` (integer, opcional): Altura em EMU. Padrão: 914400 (~1 polegada).
</Accordion>
<Accordion title="google_slides/delete_slide">
**Descrição:** Remover um slide de uma apresentação. Use get_presentation primeiro para encontrar o ID do slide.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do objeto do slide a excluir. Obtenha de get_presentation.
</Accordion>
<Accordion title="google_slides/duplicate_slide">
**Descrição:** Criar uma cópia de um slide existente. A duplicata é inserida imediatamente após o original.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do objeto do slide a duplicar. Obtenha de get_presentation.
</Accordion>
<Accordion title="google_slides/move_slides">
**Descrição:** Reordenar slides movendo-os para uma nova posição. Os IDs dos slides devem estar na ordem atual da apresentação (sem duplicatas).
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideIds` (array de strings, obrigatório): Array de IDs dos slides a mover. Obrigatoriamente na ordem atual da apresentação.
- `insertionIndex` (integer, obrigatório): Posição de destino (baseado em 0). 0 = início, número de slides = final.
</Accordion>
<Accordion title="google_slides/insert_youtube_video">
**Descrição:** Incorporar um vídeo do YouTube em um slide. O ID do vídeo é o valor após "v=" nas URLs do YouTube (ex: para youtube.com/watch?v=abc123, use "abc123").
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do slide para adicionar o vídeo. Obtenha de get_presentation.
- `videoId` (string, obrigatório): O ID do vídeo do YouTube (o valor após v= na URL).
</Accordion>
<Accordion title="google_slides/insert_drive_video">
**Descrição:** Incorporar um vídeo do Google Drive em um slide. O ID do arquivo pode ser encontrado na URL do arquivo no Drive.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do slide para adicionar o vídeo. Obtenha de get_presentation.
- `fileId` (string, obrigatório): O ID do arquivo do Google Drive do vídeo.
</Accordion>
<Accordion title="google_slides/set_slide_background_image">
**Descrição:** Definir uma imagem de fundo para um slide. A URL da imagem deve ser publicamente acessível.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do slide para definir o fundo. Obtenha de get_presentation.
- `imageUrl` (string, obrigatório): URL publicamente acessível da imagem a usar como fundo.
</Accordion>
<Accordion title="google_slides/create_table">
**Descrição:** Criar uma tabela vazia em um slide. Para criar uma tabela com conteúdo, use create_table_with_content.
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do slide para adicionar a tabela. Obtenha de get_presentation.
- `rows` (integer, obrigatório): Número de linhas na tabela.
- `columns` (integer, obrigatório): Número de colunas na tabela.
</Accordion>
<Accordion title="google_slides/create_table_with_content">
**Descrição:** Criar uma tabela com conteúdo em uma única ação. Forneça o conteúdo como uma matriz 2D onde cada array interno é uma linha. Exemplo: [["Cabeçalho1", "Cabeçalho2"], ["Linha1Col1", "Linha1Col2"]].
**Parâmetros:**
- `presentationId` (string, obrigatório): O ID da apresentação.
- `slideId` (string, obrigatório): O ID do slide para adicionar a tabela. Obtenha de get_presentation.
- `rows` (integer, obrigatório): Número de linhas na tabela.
- `columns` (integer, obrigatório): Número de colunas na tabela.
- `content` (array, obrigatório): Conteúdo da tabela como matriz 2D. Cada array interno é uma linha. Exemplo: [["Ano", "Receita"], ["2023", "$10M"]].
</Accordion>
<Accordion title="google_slides/import_data_from_sheet">
**Descrição:** Importa dados de uma planilha do Google para uma apresentação.

View File

@@ -148,6 +148,16 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="microsoft_excel/get_table_data">
**Descrição:** Obter dados de uma tabela específica em uma planilha do Excel.
**Parâmetros:**
- `file_id` (string, obrigatório): O ID do arquivo Excel.
- `worksheet_name` (string, obrigatório): Nome da planilha.
- `table_name` (string, obrigatório): Nome da tabela.
</Accordion>
<Accordion title="microsoft_excel/create_chart">
**Descrição:** Criar um gráfico em uma planilha do Excel.
@@ -180,6 +190,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="microsoft_excel/get_used_range_metadata">
**Descrição:** Obter os metadados do intervalo usado (apenas dimensões, sem dados) de uma planilha do Excel.
**Parâmetros:**
- `file_id` (string, obrigatório): O ID do arquivo Excel.
- `worksheet_name` (string, obrigatório): Nome da planilha.
</Accordion>
<Accordion title="microsoft_excel/list_charts">
**Descrição:** Obter todos os gráficos em uma planilha do Excel.

View File

@@ -150,6 +150,49 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
- `item_id` (string, obrigatório): O ID do arquivo.
</Accordion>
<Accordion title="microsoft_onedrive/list_files_by_path">
**Descrição:** Listar arquivos e pastas em um caminho específico do OneDrive.
**Parâmetros:**
- `folder_path` (string, obrigatório): O caminho da pasta (ex: 'Documents/Reports').
- `top` (integer, opcional): Número de itens a recuperar (máx 1000). Padrão: 50.
- `orderby` (string, opcional): Ordenar por campo (ex: "name asc", "lastModifiedDateTime desc"). Padrão: "name asc".
</Accordion>
<Accordion title="microsoft_onedrive/get_recent_files">
**Descrição:** Obter arquivos acessados recentemente no OneDrive.
**Parâmetros:**
- `top` (integer, opcional): Número de itens a recuperar (máx 200). Padrão: 25.
</Accordion>
<Accordion title="microsoft_onedrive/get_shared_with_me">
**Descrição:** Obter arquivos e pastas compartilhados com o usuário.
**Parâmetros:**
- `top` (integer, opcional): Número de itens a recuperar (máx 200). Padrão: 50.
- `orderby` (string, opcional): Ordenar por campo. Padrão: "name asc".
</Accordion>
<Accordion title="microsoft_onedrive/get_file_by_path">
**Descrição:** Obter informações sobre um arquivo ou pasta específica pelo caminho.
**Parâmetros:**
- `file_path` (string, obrigatório): O caminho do arquivo ou pasta (ex: 'Documents/report.docx').
</Accordion>
<Accordion title="microsoft_onedrive/download_file_by_path">
**Descrição:** Baixar um arquivo do OneDrive pelo seu caminho.
**Parâmetros:**
- `file_path` (string, obrigatório): O caminho do arquivo (ex: 'Documents/report.docx').
</Accordion>
</AccordionGroup>
## Exemplos de Uso

View File

@@ -132,6 +132,74 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
- `companyName` (string, opcional): Nome da empresa do contato.
</Accordion>
<Accordion title="microsoft_outlook/get_message">
**Descrição:** Obter uma mensagem de email específica por ID.
**Parâmetros:**
- `message_id` (string, obrigatório): O identificador único da mensagem. Obter pela ação get_messages.
- `select` (string, opcional): Lista separada por vírgulas de propriedades a retornar. Exemplo: "id,subject,body,from,receivedDateTime". Padrão: "id,subject,body,from,toRecipients,receivedDateTime".
</Accordion>
<Accordion title="microsoft_outlook/reply_to_email">
**Descrição:** Responder a uma mensagem de email.
**Parâmetros:**
- `message_id` (string, obrigatório): O identificador único da mensagem a responder. Obter pela ação get_messages.
- `comment` (string, obrigatório): O conteúdo da mensagem de resposta. Pode ser texto simples ou HTML. A mensagem original será citada abaixo deste conteúdo.
</Accordion>
<Accordion title="microsoft_outlook/forward_email">
**Descrição:** Encaminhar uma mensagem de email.
**Parâmetros:**
- `message_id` (string, obrigatório): O identificador único da mensagem a encaminhar. Obter pela ação get_messages.
- `to_recipients` (array, obrigatório): Array de endereços de email dos destinatários. Exemplo: ["john@example.com", "jane@example.com"].
- `comment` (string, opcional): Mensagem opcional a incluir acima do conteúdo encaminhado. Pode ser texto simples ou HTML.
</Accordion>
<Accordion title="microsoft_outlook/mark_message_read">
**Descrição:** Marcar uma mensagem como lida ou não lida.
**Parâmetros:**
- `message_id` (string, obrigatório): O identificador único da mensagem. Obter pela ação get_messages.
- `is_read` (boolean, obrigatório): Definir como true para marcar como lida, false para marcar como não lida.
</Accordion>
<Accordion title="microsoft_outlook/delete_message">
**Descrição:** Excluir uma mensagem de email.
**Parâmetros:**
- `message_id` (string, obrigatório): O identificador único da mensagem a excluir. Obter pela ação get_messages.
</Accordion>
<Accordion title="microsoft_outlook/update_event">
**Descrição:** Atualizar um evento de calendário existente.
**Parâmetros:**
- `event_id` (string, obrigatório): O identificador único do evento. Obter pela ação get_calendar_events.
- `subject` (string, opcional): Novo assunto/título do evento.
- `start_time` (string, opcional): Nova hora de início no formato ISO 8601 (ex: "2024-01-20T10:00:00"). OBRIGATÓRIO: Também deve fornecer start_timezone ao usar este campo.
- `start_timezone` (string, opcional): Fuso horário da hora de início. OBRIGATÓRIO ao atualizar start_time. Exemplos: "Pacific Standard Time", "Eastern Standard Time", "UTC".
- `end_time` (string, opcional): Nova hora de término no formato ISO 8601. OBRIGATÓRIO: Também deve fornecer end_timezone ao usar este campo.
- `end_timezone` (string, opcional): Fuso horário da hora de término. OBRIGATÓRIO ao atualizar end_time. Exemplos: "Pacific Standard Time", "Eastern Standard Time", "UTC".
- `location` (string, opcional): Novo local do evento.
- `body` (string, opcional): Novo corpo/descrição do evento. Suporta formatação HTML.
</Accordion>
<Accordion title="microsoft_outlook/delete_event">
**Descrição:** Excluir um evento de calendário.
**Parâmetros:**
- `event_id` (string, obrigatório): O identificador único do evento a excluir. Obter pela ação get_calendar_events.
</Accordion>
</AccordionGroup>
## Exemplos de Uso

View File

@@ -77,6 +77,17 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="microsoft_sharepoint/get_drives">
**Descrição:** Listar todas as bibliotecas de documentos (drives) em um site do SharePoint. Use isto para descobrir bibliotecas disponíveis antes de usar operações de arquivo.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `top` (integer, opcional): Número máximo de drives a retornar por página (1-999). Padrão: 100
- `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'id,name,webUrl,driveType').
</Accordion>
<Accordion title="microsoft_sharepoint/get_site_lists">
**Descrição:** Obter todas as listas em um site do SharePoint.
@@ -145,20 +156,317 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
</Accordion>
<Accordion title="microsoft_sharepoint/get_drive_items">
**Descrição:** Obter arquivos e pastas de uma biblioteca de documentos do SharePoint.
<Accordion title="microsoft_sharepoint/list_files">
**Descrição:** Recuperar arquivos e pastas de uma biblioteca de documentos do SharePoint. Por padrão, lista a pasta raiz, mas você pode navegar em subpastas fornecendo um folder_id.
**Parâmetros:**
- `site_id` (string, obrigatório): O ID do site do SharePoint.
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `folder_id` (string, opcional): O ID da pasta para listar o conteúdo. Use 'root' para a pasta raiz, ou forneça um ID de pasta de uma chamada anterior de list_files. Padrão: 'root'
- `top` (integer, opcional): Número máximo de itens a retornar por página (1-1000). Padrão: 50
- `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
- `orderby` (string, opcional): Ordem de classificação dos resultados (ex: 'name asc', 'size desc', 'lastModifiedDateTime desc'). Padrão: 'name asc'
- `filter` (string, opcional): Filtro OData para restringir resultados (ex: 'file ne null' apenas para arquivos, 'folder ne null' apenas para pastas).
- `select` (string, opcional): Lista de campos separados por vírgula para retornar (ex: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
</Accordion>
<Accordion title="microsoft_sharepoint/delete_drive_item">
**Descrição:** Excluir um arquivo ou pasta da biblioteca de documentos do SharePoint.
<Accordion title="microsoft_sharepoint/delete_file">
**Descrição:** Excluir um arquivo ou pasta de uma biblioteca de documentos do SharePoint. Para pastas, todo o conteúdo é excluído recursivamente. Os itens são movidos para a lixeira do site.
**Parâmetros:**
- `site_id` (string, obrigatório): O ID do site do SharePoint.
- `item_id` (string, obrigatório): O ID do arquivo ou pasta a excluir.
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo ou pasta a excluir. Obtenha de list_files.
</Accordion>
<Accordion title="microsoft_sharepoint/list_files_by_path">
**Descrição:** Listar arquivos e pastas em uma pasta de biblioteca de documentos do SharePoint pelo caminho. Mais eficiente do que múltiplas chamadas list_files para navegação profunda.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `folder_path` (string, obrigatório): O caminho completo para a pasta sem barras iniciais/finais (ex: 'Documents', 'Reports/2024/Q1').
- `top` (integer, opcional): Número máximo de itens a retornar por página (1-1000). Padrão: 50
- `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
- `orderby` (string, opcional): Ordem de classificação dos resultados (ex: 'name asc', 'size desc'). Padrão: 'name asc'
- `select` (string, opcional): Lista de campos separados por vírgula para retornar (ex: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
</Accordion>
<Accordion title="microsoft_sharepoint/download_file">
**Descrição:** Baixar conteúdo bruto de um arquivo de uma biblioteca de documentos do SharePoint. Use apenas para arquivos de texto simples (.txt, .csv, .json). Para arquivos Excel, use as ações específicas de Excel. Para arquivos Word, use get_word_document_content.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo a baixar. Obtenha de list_files ou list_files_by_path.
</Accordion>
<Accordion title="microsoft_sharepoint/get_file_info">
**Descrição:** Recuperar metadados detalhados de um arquivo ou pasta específico em uma biblioteca de documentos do SharePoint, incluindo nome, tamanho, datas de criação/modificação e informações do autor.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo ou pasta. Obtenha de list_files ou list_files_by_path.
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'id,name,size,createdDateTime,lastModifiedDateTime,webUrl,createdBy,lastModifiedBy').
</Accordion>
<Accordion title="microsoft_sharepoint/create_folder">
**Descrição:** Criar uma nova pasta em uma biblioteca de documentos do SharePoint. Por padrão, cria a pasta na raiz; use parent_id para criar subpastas.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `folder_name` (string, obrigatório): Nome para a nova pasta. Não pode conter: \ / : * ? " < > |
- `parent_id` (string, opcional): O ID da pasta pai. Use 'root' para a raiz da biblioteca de documentos, ou forneça um ID de pasta de list_files. Padrão: 'root'
</Accordion>
<Accordion title="microsoft_sharepoint/search_files">
**Descrição:** Pesquisar arquivos e pastas em uma biblioteca de documentos do SharePoint por palavras-chave. Pesquisa nomes de arquivos, nomes de pastas e conteúdo de arquivos para documentos Office. Não use curingas ou caracteres especiais.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `query` (string, obrigatório): Palavras-chave de pesquisa (ex: 'relatório', 'orçamento 2024'). Curingas como *.txt não são suportados.
- `top` (integer, opcional): Número máximo de resultados a retornar por página (1-1000). Padrão: 50
- `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
- `select` (string, opcional): Lista de campos separados por vírgula para retornar (ex: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
</Accordion>
<Accordion title="microsoft_sharepoint/copy_file">
**Descrição:** Copiar um arquivo ou pasta para um novo local dentro do SharePoint. O item original permanece inalterado. A operação de cópia é assíncrona para arquivos grandes.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo ou pasta a copiar. Obtenha de list_files ou search_files.
- `destination_folder_id` (string, obrigatório): O ID da pasta de destino. Use 'root' para a pasta raiz, ou um ID de pasta de list_files.
- `new_name` (string, opcional): Novo nome para a cópia. Se não fornecido, o nome original é usado.
</Accordion>
<Accordion title="microsoft_sharepoint/move_file">
**Descrição:** Mover um arquivo ou pasta para um novo local dentro do SharePoint. O item é removido de sua localização original. Para pastas, todo o conteúdo é movido também.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo ou pasta a mover. Obtenha de list_files ou search_files.
- `destination_folder_id` (string, obrigatório): O ID da pasta de destino. Use 'root' para a pasta raiz, ou um ID de pasta de list_files.
- `new_name` (string, opcional): Novo nome para o item movido. Se não fornecido, o nome original é mantido.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_worksheets">
**Descrição:** Listar todas as planilhas (abas) em uma pasta de trabalho Excel armazenada em uma biblioteca de documentos do SharePoint. Use o nome da planilha retornado com outras ações de Excel.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'id,name,position,visibility').
- `filter` (string, opcional): Expressão de filtro OData (ex: "visibility eq 'Visible'" para excluir planilhas ocultas).
- `top` (integer, opcional): Número máximo de planilhas a retornar. Mínimo: 1, Máximo: 999
- `orderby` (string, opcional): Ordem de classificação (ex: 'position asc' para retornar planilhas na ordem das abas).
</Accordion>
<Accordion title="microsoft_sharepoint/create_excel_worksheet">
**Descrição:** Criar uma nova planilha (aba) em uma pasta de trabalho Excel armazenada em uma biblioteca de documentos do SharePoint. A nova planilha é adicionada no final da lista de abas.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `name` (string, obrigatório): Nome para a nova planilha. Máximo de 31 caracteres. Não pode conter: \ / * ? : [ ]. Deve ser único na pasta de trabalho.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_range_data">
**Descrição:** Recuperar valores de células de um intervalo específico em uma planilha Excel armazenada no SharePoint. Para ler todos os dados sem saber as dimensões, use get_excel_used_range em vez disso.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha (aba) para leitura. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
- `range` (string, obrigatório): Intervalo de células em notação A1 (ex: 'A1:C10', 'A:C', '1:5', 'A1').
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text').
</Accordion>
<Accordion title="microsoft_sharepoint/update_excel_range_data">
**Descrição:** Escrever valores em um intervalo específico em uma planilha Excel armazenada no SharePoint. Sobrescreve o conteúdo existente das células. As dimensões do array de valores devem corresponder exatamente às dimensões do intervalo.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha (aba) a atualizar. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
- `range` (string, obrigatório): Intervalo de células em notação A1 onde os valores serão escritos (ex: 'A1:C3' para um bloco 3x3).
- `values` (array, obrigatório): Array 2D de valores (linhas contendo células). Exemplo para A1:B2: [["Cabeçalho1", "Cabeçalho2"], ["Valor1", "Valor2"]]. Use null para limpar uma célula.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_used_range_metadata">
**Descrição:** Retornar apenas os metadados (endereço e dimensões) do intervalo utilizado em uma planilha, sem os valores reais das células. Ideal para arquivos grandes para entender o tamanho da planilha antes de ler dados em blocos.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha (aba) para leitura. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_used_range">
**Descrição:** Recuperar todas as células contendo dados em uma planilha armazenada no SharePoint. Não use para arquivos maiores que 2MB. Para arquivos grandes, use get_excel_used_range_metadata primeiro, depois get_excel_range_data para ler em blocos menores.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha (aba) para leitura. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text,rowCount,columnCount').
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_cell">
**Descrição:** Recuperar o valor de uma única célula por índice de linha e coluna de um arquivo Excel no SharePoint. Os índices são baseados em 0 (linha 0 = linha 1 do Excel, coluna 0 = coluna A).
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha (aba). Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
- `row` (integer, obrigatório): Índice de linha baseado em 0 (linha 0 = linha 1 do Excel). Intervalo válido: 0-1048575
- `column` (integer, obrigatório): Índice de coluna baseado em 0 (coluna 0 = A, coluna 1 = B). Intervalo válido: 0-16383
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text').
</Accordion>
<Accordion title="microsoft_sharepoint/add_excel_table">
**Descrição:** Converter um intervalo de células em uma tabela Excel formatada com recursos de filtragem, classificação e dados estruturados. Tabelas habilitam add_excel_table_row para adicionar dados.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha contendo o intervalo de dados. Obtenha de get_excel_worksheets.
- `range` (string, obrigatório): Intervalo de células para converter em tabela, incluindo cabeçalhos e dados (ex: 'A1:D10' onde A1:D1 contém cabeçalhos de coluna).
- `has_headers` (boolean, opcional): Defina como true se a primeira linha contém cabeçalhos de coluna. Padrão: true
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_tables">
**Descrição:** Listar todas as tabelas em uma planilha Excel específica armazenada no SharePoint. Retorna propriedades da tabela incluindo id, name, showHeaders e showTotals.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha para obter tabelas. Obtenha de get_excel_worksheets.
</Accordion>
<Accordion title="microsoft_sharepoint/add_excel_table_row">
**Descrição:** Adicionar uma nova linha ao final de uma tabela Excel em um arquivo do SharePoint. O array de valores deve ter o mesmo número de elementos que o número de colunas da tabela.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha contendo a tabela. Obtenha de get_excel_worksheets.
- `table_name` (string, obrigatório): Nome da tabela para adicionar a linha (ex: 'Table1'). Obtenha de get_excel_tables. Sensível a maiúsculas e minúsculas.
- `values` (array, obrigatório): Array de valores de células para a nova linha, um por coluna na ordem da tabela (ex: ["João Silva", "joao@exemplo.com", 25]).
</Accordion>
<Accordion title="microsoft_sharepoint/get_excel_table_data">
**Descrição:** Obter todas as linhas de uma tabela Excel em um arquivo do SharePoint como um intervalo de dados. Mais fácil do que get_excel_range_data ao trabalhar com tabelas estruturadas, pois não é necessário saber o intervalo exato.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha contendo a tabela. Obtenha de get_excel_worksheets.
- `table_name` (string, obrigatório): Nome da tabela para obter dados (ex: 'Table1'). Obtenha de get_excel_tables. Sensível a maiúsculas e minúsculas.
- `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text').
</Accordion>
<Accordion title="microsoft_sharepoint/create_excel_chart">
**Descrição:** Criar uma visualização de gráfico em uma planilha Excel armazenada no SharePoint a partir de um intervalo de dados. O gráfico é incorporado na planilha.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha onde o gráfico será criado. Obtenha de get_excel_worksheets.
- `chart_type` (string, obrigatório): Tipo de gráfico (ex: 'ColumnClustered', 'ColumnStacked', 'Line', 'LineMarkers', 'Pie', 'Bar', 'BarClustered', 'Area', 'Scatter', 'Doughnut').
- `source_data` (string, obrigatório): Intervalo de dados para o gráfico em notação A1, incluindo cabeçalhos (ex: 'A1:B10').
- `series_by` (string, opcional): Como as séries de dados são organizadas: 'Auto', 'Columns' ou 'Rows'. Padrão: 'Auto'
</Accordion>
<Accordion title="microsoft_sharepoint/list_excel_charts">
**Descrição:** Listar todos os gráficos incorporados em uma planilha Excel armazenada no SharePoint. Retorna propriedades do gráfico incluindo id, name, chartType, height, width e position.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha para listar gráficos. Obtenha de get_excel_worksheets.
</Accordion>
<Accordion title="microsoft_sharepoint/delete_excel_worksheet">
**Descrição:** Remover permanentemente uma planilha (aba) e todo seu conteúdo de uma pasta de trabalho Excel armazenada no SharePoint. Não pode ser desfeito. Uma pasta de trabalho deve ter pelo menos uma planilha.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha a excluir. Sensível a maiúsculas e minúsculas. Todos os dados, tabelas e gráficos nesta planilha serão permanentemente removidos.
</Accordion>
<Accordion title="microsoft_sharepoint/delete_excel_table">
**Descrição:** Remover uma tabela de uma planilha Excel no SharePoint. Isto exclui a estrutura da tabela (filtragem, formatação, recursos de tabela) mas preserva os dados subjacentes das células.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
- `worksheet_name` (string, obrigatório): Nome da planilha contendo a tabela. Obtenha de get_excel_worksheets.
- `table_name` (string, obrigatório): Nome da tabela a excluir (ex: 'Table1'). Obtenha de get_excel_tables. Os dados nas células permanecerão após a exclusão da tabela.
</Accordion>
<Accordion title="microsoft_sharepoint/list_excel_names">
**Descrição:** Recuperar todos os intervalos nomeados definidos em uma pasta de trabalho Excel armazenada no SharePoint. Intervalos nomeados são rótulos definidos pelo usuário para intervalos de células (ex: 'DadosVendas' para A1:D100).
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
</Accordion>
<Accordion title="microsoft_sharepoint/get_word_document_content">
**Descrição:** Baixar e extrair conteúdo de texto de um documento Word (.docx) armazenado em uma biblioteca de documentos do SharePoint. Esta é a maneira recomendada de ler documentos Word do SharePoint.
**Parâmetros:**
- `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
- `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
- `item_id` (string, obrigatório): O identificador único do documento Word (.docx) no SharePoint. Obtenha de list_files ou search_files.
</Accordion>
</AccordionGroup>

View File

@@ -107,6 +107,86 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
- `join_web_url` (string, obrigatório): A URL de participação na web da reunião a pesquisar.
</Accordion>
<Accordion title="microsoft_teams/search_online_meetings_by_meeting_id">
**Descrição:** Pesquisar reuniões online por ID externo da reunião.
**Parâmetros:**
- `join_meeting_id` (string, obrigatório): O ID da reunião (código numérico) que os participantes usam para entrar. É o joinMeetingId exibido nos convites da reunião, não o meeting id da API Graph.
</Accordion>
<Accordion title="microsoft_teams/get_meeting">
**Descrição:** Obter detalhes de uma reunião online específica.
**Parâmetros:**
- `meeting_id` (string, obrigatório): O ID da reunião na API Graph (string alfanumérica longa). Obter pelas ações create_meeting ou search_online_meetings. Diferente do joinMeetingId numérico.
</Accordion>
<Accordion title="microsoft_teams/get_team_members">
**Descrição:** Obter membros de uma equipe específica.
**Parâmetros:**
- `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
- `top` (integer, opcional): Número máximo de membros a recuperar por página (1-999). Padrão: 100.
- `skip_token` (string, opcional): Token de paginação de uma resposta anterior. Quando a resposta incluir @odata.nextLink, extraia o valor do parâmetro $skiptoken e passe aqui para obter a próxima página de resultados.
</Accordion>
<Accordion title="microsoft_teams/create_channel">
**Descrição:** Criar um novo canal em uma equipe.
**Parâmetros:**
- `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
- `display_name` (string, obrigatório): Nome do canal exibido no Teams. Deve ser único na equipe. Máx 50 caracteres.
- `description` (string, opcional): Descrição opcional explicando o propósito do canal. Visível nos detalhes do canal. Máx 1024 caracteres.
- `membership_type` (string, opcional): Visibilidade do canal. Opções: standard, private. "standard" = visível para todos os membros da equipe, "private" = visível apenas para membros adicionados especificamente. Padrão: standard.
</Accordion>
<Accordion title="microsoft_teams/get_message_replies">
**Descrição:** Obter respostas a uma mensagem específica em um canal.
**Parâmetros:**
- `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
- `channel_id` (string, obrigatório): O identificador único do canal. Obter pela ação get_channels.
- `message_id` (string, obrigatório): O identificador único da mensagem pai. Obter pela ação get_messages.
- `top` (integer, opcional): Número máximo de respostas a recuperar por página (1-50). Padrão: 50.
- `skip_token` (string, opcional): Token de paginação de uma resposta anterior. Quando a resposta incluir @odata.nextLink, extraia o valor do parâmetro $skiptoken e passe aqui para obter a próxima página de resultados.
</Accordion>
<Accordion title="microsoft_teams/reply_to_message">
**Descrição:** Responder a uma mensagem em um canal do Teams.
**Parâmetros:**
- `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
- `channel_id` (string, obrigatório): O identificador único do canal. Obter pela ação get_channels.
- `message_id` (string, obrigatório): O identificador único da mensagem a responder. Obter pela ação get_messages.
- `message` (string, obrigatório): O conteúdo da resposta. Para HTML, inclua tags de formatação. Para texto, use apenas texto simples.
- `content_type` (string, opcional): Formato do conteúdo. Opções: html, text. "text" para texto simples, "html" para texto rico com formatação. Padrão: text.
</Accordion>
<Accordion title="microsoft_teams/update_meeting">
**Descrição:** Atualizar uma reunião online existente.
**Parâmetros:**
- `meeting_id` (string, obrigatório): O identificador único da reunião. Obter pelas ações create_meeting ou search_online_meetings.
- `subject` (string, opcional): Novo título da reunião.
- `startDateTime` (string, opcional): Nova hora de início no formato ISO 8601 com fuso horário. Exemplo: "2024-01-20T10:00:00-08:00".
- `endDateTime` (string, opcional): Nova hora de término no formato ISO 8601 com fuso horário.
</Accordion>
<Accordion title="microsoft_teams/delete_meeting">
**Descrição:** Excluir uma reunião online.
**Parâmetros:**
- `meeting_id` (string, obrigatório): O identificador único da reunião a excluir. Obter pelas ações create_meeting ou search_online_meetings.
</Accordion>
</AccordionGroup>
## Exemplos de Uso

View File

@@ -97,6 +97,26 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
- `file_id` (string, obrigatório): O ID do documento a excluir.
</Accordion>
<Accordion title="microsoft_word/copy_document">
**Descrição:** Copiar um documento para um novo local no OneDrive.
**Parâmetros:**
- `file_id` (string, obrigatório): O ID do documento a copiar.
- `name` (string, opcional): Novo nome para o documento copiado.
- `parent_id` (string, opcional): O ID da pasta de destino (padrão: raiz).
</Accordion>
<Accordion title="microsoft_word/move_document">
**Descrição:** Mover um documento para um novo local no OneDrive.
**Parâmetros:**
- `file_id` (string, obrigatório): O ID do documento a mover.
- `parent_id` (string, obrigatório): O ID da pasta de destino.
- `name` (string, opcional): Novo nome para o documento movido.
</Accordion>
</AccordionGroup>
## Exemplos de Uso

View File

@@ -8,6 +8,29 @@ This enables multiple workflows like having an Agent to access the database fetc
**Attention**: Make sure that the Agent has access to a Read-Replica or that is okay for the Agent to run insert/update queries on the database.
## Security Model
`NL2SQLTool` is an execution-capable tool. It runs model-generated SQL directly against the configured database connection.
Risk depends on deployment choices:
- Which credentials are used in `db_uri`
- Whether untrusted input can influence prompts
- Whether tool-call guardrails are enforced before execution
If untrusted input can reach this tool, treat the integration as high risk.
## Hardening Recommendations
Use all of the following in production:
- Use a read-only database user whenever possible
- Prefer a read replica for analytics/retrieval workloads
- Grant least privilege (no superuser/admin roles, no file/system-level capabilities)
- Apply database-side resource limits (statement timeout, lock timeout, cost/row limits)
- Add `before_tool_call` hooks to enforce allowed query patterns
- Enable query logging and alerting for destructive statements
## Requirements
- SqlAlchemy

View File

@@ -33,8 +33,11 @@ def test_brave_tool_search(mock_get, brave_tool):
mock_get.return_value.json.return_value = mock_response
result = brave_tool.run(query="test")
assert "Test Title" in result
assert "http://test.com" in result
data = json.loads(result)
assert isinstance(data, list)
assert len(data) >= 1
assert data[0]["title"] == "Test Title"
assert data[0]["url"] == "http://test.com"
@patch("requests.get")

View File

@@ -14,7 +14,7 @@ dependencies = [
"instructor>=1.3.3",
# Text Processing
"pdfplumber~=0.11.4",
"regex~=2024.9.11",
"regex~=2026.1.15",
# Telemetry and Monitoring
"opentelemetry-api~=1.34.0",
"opentelemetry-sdk~=1.34.0",
@@ -36,7 +36,7 @@ dependencies = [
"json5~=0.10.0",
"portalocker~=2.7.0",
"pydantic-settings~=2.10.1",
"mcp~=1.23.1",
"mcp~=1.26.0",
"uv~=0.9.13",
"aiosqlite~=0.21.0",
]

View File

@@ -37,9 +37,10 @@ class BaseAgentAdapter(BaseAgent, ABC):
tools: Optional list of BaseTool instances to be configured
"""
def configure_structured_output(self, structured_output: Any) -> None:
@abstractmethod
def configure_structured_output(self, task: Any) -> None:
"""Configure the structured output for the specific agent implementation.
Args:
structured_output: The structured output to be configured
task: The task object containing output format specifications.
"""

View File

@@ -814,6 +814,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
agent_key=agent_key,
),
)
error_event_emitted = False
track_delegation_if_needed(func_name, args_dict, self.task)
@@ -896,6 +897,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
error=e,
),
)
error_event_emitted = True
elif max_usage_reached and original_tool:
# Return error message when max usage limit is reached
result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
@@ -923,20 +925,20 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
color="red",
)
# Emit tool usage finished event
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
if not error_event_emitted:
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
# Append tool result message
tool_message: LLMMessage = {
@@ -1007,7 +1009,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
raise
if self.ask_for_human_input:
formatted_answer = self._handle_human_feedback(formatted_answer)
formatted_answer = await self._ahandle_human_feedback(formatted_answer)
self._create_short_term_memory(formatted_answer)
self._create_long_term_memory(formatted_answer)
@@ -1506,6 +1508,20 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
provider = get_provider()
return provider.handle_feedback(formatted_answer, self)
async def _ahandle_human_feedback(
self, formatted_answer: AgentFinish
) -> AgentFinish:
"""Process human feedback asynchronously via the configured provider.
Args:
formatted_answer: Initial agent result.
Returns:
Final answer after feedback.
"""
provider = get_provider()
return await provider.handle_feedback_async(formatted_answer, self)
def _is_training_mode(self) -> bool:
"""Check if training mode is active.

View File

@@ -143,6 +143,12 @@ def create_folder_structure(
(folder_path / "src" / folder_name).mkdir(parents=True)
(folder_path / "src" / folder_name / "tools").mkdir(parents=True)
(folder_path / "src" / folder_name / "config").mkdir(parents=True)
# Copy AGENTS.md to project root (top-level projects only)
package_dir = Path(__file__).parent
agents_md_src = package_dir / "templates" / "AGENTS.md"
if agents_md_src.exists():
shutil.copy2(agents_md_src, folder_path / "AGENTS.md")
return folder_path, folder_name, class_name

View File

@@ -1,3 +1,4 @@
import shutil
from pathlib import Path
import click
@@ -34,6 +35,11 @@ def create_flow(name):
package_dir = Path(__file__).parent
templates_dir = package_dir / "templates" / "flow"
# Copy AGENTS.md to project root
agents_md_src = package_dir / "templates" / "AGENTS.md"
if agents_md_src.exists():
shutil.copy2(agents_md_src, project_root / "AGENTS.md")
# List of template files to copy
root_template_files = [".gitignore", "pyproject.toml", "README.md"]
src_template_files = ["__init__.py", "main.py"]

View File

@@ -1,6 +1,8 @@
import os
from typing import Any
from urllib.parse import urljoin
import os
import httpx
import requests
from crewai.cli.config import Settings
@@ -33,7 +35,11 @@ class PlusAPI:
if settings.org_uuid:
self.headers["X-Crewai-Organization-Id"] = settings.org_uuid
self.base_url = os.getenv("CREWAI_PLUS_URL") or str(settings.enterprise_base_url) or DEFAULT_CREWAI_ENTERPRISE_URL
self.base_url = (
os.getenv("CREWAI_PLUS_URL")
or str(settings.enterprise_base_url)
or DEFAULT_CREWAI_ENTERPRISE_URL
)
def _make_request(
self, method: str, endpoint: str, **kwargs: Any
@@ -49,8 +55,10 @@ class PlusAPI:
def get_tool(self, handle: str) -> requests.Response:
return self._make_request("GET", f"{self.TOOLS_RESOURCE}/{handle}")
def get_agent(self, handle: str) -> requests.Response:
return self._make_request("GET", f"{self.AGENTS_RESOURCE}/{handle}")
async def get_agent(self, handle: str) -> httpx.Response:
url = urljoin(self.base_url, f"{self.AGENTS_RESOURCE}/{handle}")
async with httpx.AsyncClient() as client:
return await client.get(url, headers=self.headers)
def publish_tool(
self,

File diff suppressed because it is too large Load Diff

View File

@@ -2,6 +2,7 @@ import base64
from json import JSONDecodeError
import os
from pathlib import Path
import shutil
import subprocess
import tempfile
from typing import Any
@@ -55,6 +56,11 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
tree_find_and_replace(project_root, "{{folder_name}}", folder_name)
tree_find_and_replace(project_root, "{{class_name}}", class_name)
# Copy AGENTS.md to project root
agents_md_src = Path(__file__).parent.parent / "templates" / "AGENTS.md"
if agents_md_src.exists():
shutil.copy2(agents_md_src, project_root / "AGENTS.md")
old_directory = os.getcwd()
os.chdir(project_root)
try:

View File

@@ -6,12 +6,12 @@ from functools import lru_cache
import importlib.metadata
import json
from pathlib import Path
from typing import Any, cast
from typing import Any
from urllib import request
from urllib.error import URLError
import appdirs
from packaging.version import InvalidVersion, parse
from packaging.version import InvalidVersion, Version, parse
@lru_cache(maxsize=1)
@@ -42,21 +42,88 @@ def _is_cache_valid(cache_data: Mapping[str, Any]) -> bool:
return False
def _find_latest_non_yanked_version(
releases: Mapping[str, list[dict[str, Any]]],
) -> str | None:
"""Find the latest non-yanked version from PyPI releases data.
Args:
releases: PyPI releases dict mapping version strings to file info lists.
Returns:
The latest non-yanked version string, or None if all versions are yanked.
"""
best_version: Version | None = None
best_version_str: str | None = None
for version_str, files in releases.items():
try:
v = parse(version_str)
except InvalidVersion:
continue
if v.is_prerelease or v.is_devrelease:
continue
if not files:
continue
all_yanked = all(f.get("yanked", False) for f in files)
if all_yanked:
continue
if best_version is None or v > best_version:
best_version = v
best_version_str = version_str
return best_version_str
def _is_version_yanked(
version_str: str,
releases: Mapping[str, list[dict[str, Any]]],
) -> tuple[bool, str]:
"""Check if a specific version is yanked.
Args:
version_str: The version string to check.
releases: PyPI releases dict mapping version strings to file info lists.
Returns:
Tuple of (is_yanked, yanked_reason).
"""
files = releases.get(version_str, [])
if not files:
return False, ""
all_yanked = all(f.get("yanked", False) for f in files)
if not all_yanked:
return False, ""
for f in files:
reason = f.get("yanked_reason", "")
if reason:
return True, str(reason)
return True, ""
def get_latest_version_from_pypi(timeout: int = 2) -> str | None:
"""Get the latest version of CrewAI from PyPI.
"""Get the latest non-yanked version of CrewAI from PyPI.
Args:
timeout: Request timeout in seconds.
Returns:
Latest version string or None if unable to fetch.
Latest non-yanked version string or None if unable to fetch.
"""
cache_file = _get_cache_file()
if cache_file.exists():
try:
cache_data = json.loads(cache_file.read_text())
if _is_cache_valid(cache_data):
return cast(str | None, cache_data.get("version"))
if _is_cache_valid(cache_data) and "current_version" in cache_data:
version: str | None = cache_data.get("version")
return version
except (json.JSONDecodeError, OSError):
pass
@@ -65,11 +132,18 @@ def get_latest_version_from_pypi(timeout: int = 2) -> str | None:
"https://pypi.org/pypi/crewai/json", timeout=timeout
) as response:
data = json.loads(response.read())
latest_version = cast(str, data["info"]["version"])
releases: dict[str, list[dict[str, Any]]] = data["releases"]
latest_version = _find_latest_non_yanked_version(releases)
current_version = get_crewai_version()
is_yanked, yanked_reason = _is_version_yanked(current_version, releases)
cache_data = {
"version": latest_version,
"timestamp": datetime.now().isoformat(),
"current_version": current_version,
"current_version_yanked": is_yanked,
"current_version_yanked_reason": yanked_reason,
}
cache_file.write_text(json.dumps(cache_data))
@@ -78,6 +152,40 @@ def get_latest_version_from_pypi(timeout: int = 2) -> str | None:
return None
def is_current_version_yanked() -> tuple[bool, str]:
"""Check if the currently installed version has been yanked on PyPI.
Reads from cache if available, otherwise triggers a fetch.
Returns:
Tuple of (is_yanked, yanked_reason).
"""
cache_file = _get_cache_file()
if cache_file.exists():
try:
cache_data = json.loads(cache_file.read_text())
if _is_cache_valid(cache_data) and "current_version" in cache_data:
current = get_crewai_version()
if cache_data.get("current_version") == current:
return (
bool(cache_data.get("current_version_yanked", False)),
str(cache_data.get("current_version_yanked_reason", "")),
)
except (json.JSONDecodeError, OSError):
pass
get_latest_version_from_pypi()
try:
cache_data = json.loads(cache_file.read_text())
return (
bool(cache_data.get("current_version_yanked", False)),
str(cache_data.get("current_version_yanked_reason", "")),
)
except (json.JSONDecodeError, OSError):
return False, ""
def check_version() -> tuple[str, str | None]:
"""Check current and latest versions.

View File

@@ -43,3 +43,23 @@ def platform_context(integration_token: str) -> Generator[None, Any, None]:
yield
finally:
_platform_integration_token.reset(token)
_current_task_id: contextvars.ContextVar[str | None] = contextvars.ContextVar(
"current_task_id", default=None
)
def set_current_task_id(task_id: str | None) -> contextvars.Token[str | None]:
"""Set the current task ID in the context. Returns a token for reset."""
return _current_task_id.set(task_id)
def reset_current_task_id(token: contextvars.Token[str | None]) -> None:
"""Reset the current task ID to its previous value."""
_current_task_id.reset(token)
def get_current_task_id() -> str | None:
"""Get the current task ID from the context."""
return _current_task_id.get()

View File

@@ -2,7 +2,9 @@
from __future__ import annotations
import asyncio
from contextvars import ContextVar, Token
import sys
from typing import TYPE_CHECKING, Protocol, runtime_checkable
@@ -46,13 +48,21 @@ class ExecutorContext(Protocol):
...
class AsyncExecutorContext(ExecutorContext, Protocol):
"""Extended context for executors that support async invocation."""
async def _ainvoke_loop(self) -> AgentFinish:
"""Invoke the agent loop asynchronously and return the result."""
...
@runtime_checkable
class HumanInputProvider(Protocol):
"""Protocol for human input handling.
Implementations handle the full feedback flow:
- Sync: prompt user, loop until satisfied
- Async: raise exception for external handling
- Async: use non-blocking I/O and async invoke loop
"""
def setup_messages(self, context: ExecutorContext) -> bool:
@@ -86,7 +96,7 @@ class HumanInputProvider(Protocol):
formatted_answer: AgentFinish,
context: ExecutorContext,
) -> AgentFinish:
"""Handle the full human feedback flow.
"""Handle the full human feedback flow synchronously.
Args:
formatted_answer: The agent's current answer.
@@ -100,6 +110,25 @@ class HumanInputProvider(Protocol):
"""
...
async def handle_feedback_async(
self,
formatted_answer: AgentFinish,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Handle the full human feedback flow asynchronously.
Uses non-blocking I/O for user prompts and async invoke loop
for agent re-execution.
Args:
formatted_answer: The agent's current answer.
context: Async executor context for callbacks.
Returns:
The final answer after feedback processing.
"""
...
@staticmethod
def _get_output_string(answer: AgentFinish) -> str:
"""Extract output string from answer.
@@ -116,7 +145,7 @@ class HumanInputProvider(Protocol):
class SyncHumanInputProvider(HumanInputProvider):
"""Default synchronous human input via terminal."""
"""Default human input provider with sync and async support."""
def setup_messages(self, context: ExecutorContext) -> bool:
"""Use standard message setup.
@@ -157,6 +186,33 @@ class SyncHumanInputProvider(HumanInputProvider):
return self._handle_regular_feedback(formatted_answer, feedback, context)
async def handle_feedback_async(
self,
formatted_answer: AgentFinish,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Handle feedback asynchronously without blocking the event loop.
Args:
formatted_answer: The agent's current answer.
context: Async executor context for callbacks.
Returns:
The final answer after feedback processing.
"""
feedback = await self._prompt_input_async(context.crew)
if context._is_training_mode():
return await self._handle_training_feedback_async(
formatted_answer, feedback, context
)
return await self._handle_regular_feedback_async(
formatted_answer, feedback, context
)
# ── Sync helpers ──────────────────────────────────────────────────
@staticmethod
def _handle_training_feedback(
initial_answer: AgentFinish,
@@ -209,6 +265,62 @@ class SyncHumanInputProvider(HumanInputProvider):
return answer
# ── Async helpers ─────────────────────────────────────────────────
@staticmethod
async def _handle_training_feedback_async(
initial_answer: AgentFinish,
feedback: str,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Process training feedback asynchronously (single iteration).
Args:
initial_answer: The agent's initial answer.
feedback: Human feedback string.
context: Async executor context for callbacks.
Returns:
Improved answer after processing feedback.
"""
context._handle_crew_training_output(initial_answer, feedback)
context.messages.append(context._format_feedback_message(feedback))
improved_answer = await context._ainvoke_loop()
context._handle_crew_training_output(improved_answer)
context.ask_for_human_input = False
return improved_answer
async def _handle_regular_feedback_async(
self,
current_answer: AgentFinish,
initial_feedback: str,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Process regular feedback with async iteration loop.
Args:
current_answer: The agent's current answer.
initial_feedback: Initial human feedback string.
context: Async executor context for callbacks.
Returns:
Final answer after all feedback iterations.
"""
feedback = initial_feedback
answer = current_answer
while context.ask_for_human_input:
if feedback.strip() == "":
context.ask_for_human_input = False
else:
context.messages.append(context._format_feedback_message(feedback))
answer = await context._ainvoke_loop()
feedback = await self._prompt_input_async(context.crew)
return answer
# ── I/O ───────────────────────────────────────────────────────────
@staticmethod
def _prompt_input(crew: Crew | None) -> str:
"""Show rich panel and prompt for input.
@@ -262,6 +374,79 @@ class SyncHumanInputProvider(HumanInputProvider):
finally:
formatter.resume_live_updates()
@staticmethod
async def _prompt_input_async(crew: Crew | None) -> str:
"""Show rich panel and prompt for input without blocking the event loop.
Args:
crew: The crew instance for context.
Returns:
User input string from terminal.
"""
from rich.panel import Panel
from rich.text import Text
from crewai.events.event_listener import event_listener
formatter = event_listener.formatter
formatter.pause_live_updates()
try:
if crew and getattr(crew, "_train", False):
prompt_text = (
"TRAINING MODE: Provide feedback to improve the agent's performance.\n\n"
"This will be used to train better versions of the agent.\n"
"Please provide detailed feedback about the result quality and reasoning process."
)
title = "🎓 Training Feedback Required"
else:
prompt_text = (
"Provide feedback on the Final Result above.\n\n"
"• If you are happy with the result, simply hit Enter without typing anything.\n"
"• Otherwise, provide specific improvement requests.\n"
"• You can provide multiple rounds of feedback until satisfied."
)
title = "💬 Human Feedback Required"
content = Text()
content.append(prompt_text, style="yellow")
prompt_panel = Panel(
content,
title=title,
border_style="yellow",
padding=(1, 2),
)
formatter.console.print(prompt_panel)
response = await _async_readline()
if response.strip() != "":
formatter.console.print("\n[cyan]Processing your feedback...[/cyan]")
return response
finally:
formatter.resume_live_updates()
async def _async_readline() -> str:
"""Read a line from stdin using the event loop's native I/O.
Falls back to asyncio.to_thread on platforms where piping stdin
is unsupported.
Returns:
The line read from stdin, with trailing newline stripped.
"""
loop = asyncio.get_running_loop()
try:
reader = asyncio.StreamReader()
protocol = asyncio.StreamReaderProtocol(reader)
await loop.connect_read_pipe(lambda: protocol, sys.stdin)
raw = await reader.readline()
return raw.decode().rstrip("\n")
except (OSError, NotImplementedError, ValueError):
return await asyncio.to_thread(input)
_provider: ContextVar[HumanInputProvider | None] = ContextVar(
"human_input_provider",

View File

@@ -187,6 +187,7 @@ class Crew(FlowTrackable, BaseModel):
_task_output_handler: TaskOutputStorageHandler = PrivateAttr(
default_factory=TaskOutputStorageHandler
)
_kickoff_event_id: str | None = PrivateAttr(default=None)
name: str | None = Field(default="crew")
cache: bool = Field(default=True)
@@ -751,19 +752,28 @@ class Crew(FlowTrackable, BaseModel):
for after_callback in self.after_kickoff_callbacks:
result = after_callback(result)
result = self._post_kickoff(result)
self.usage_metrics = self.calculate_usage_metrics()
return result
except Exception as e:
crewai_event_bus.emit(
self,
CrewKickoffFailedEvent(error=str(e), crew_name=self.name),
CrewKickoffFailedEvent(
error=str(e),
crew_name=self.name,
started_event_id=self._kickoff_event_id,
),
)
raise
finally:
clear_files(self.id)
detach(token)
def _post_kickoff(self, result: CrewOutput) -> CrewOutput:
return result
def kickoff_for_each(
self,
inputs: list[dict[str, Any]],
@@ -936,13 +946,19 @@ class Crew(FlowTrackable, BaseModel):
for after_callback in self.after_kickoff_callbacks:
result = after_callback(result)
result = self._post_kickoff(result)
self.usage_metrics = self.calculate_usage_metrics()
return result
except Exception as e:
crewai_event_bus.emit(
self,
CrewKickoffFailedEvent(error=str(e), crew_name=self.name),
CrewKickoffFailedEvent(
error=str(e),
crew_name=self.name,
started_event_id=self._kickoff_event_id,
),
)
raise
finally:
@@ -1181,6 +1197,9 @@ class Crew(FlowTrackable, BaseModel):
self.manager_agent = manager
manager.crew = self
def _get_execution_start_index(self, tasks: list[Task]) -> int | None:
return None
def _execute_tasks(
self,
tasks: list[Task],
@@ -1197,6 +1216,9 @@ class Crew(FlowTrackable, BaseModel):
Returns:
CrewOutput: Final output of the crew
"""
custom_start = self._get_execution_start_index(tasks)
if custom_start is not None:
start_index = custom_start
task_outputs: list[TaskOutput] = []
futures: list[tuple[Task, Future[TaskOutput], int]] = []
@@ -1305,8 +1327,10 @@ class Crew(FlowTrackable, BaseModel):
if files:
supported_types: list[str] = []
if agent and agent.llm and agent.llm.supports_multimodal():
provider = getattr(agent.llm, "provider", None) or getattr(
agent.llm, "model", "openai"
provider = (
getattr(agent.llm, "provider", None)
or getattr(agent.llm, "model", None)
or "openai"
)
api = getattr(agent.llm, "api", None)
supported_types = get_supported_content_types(provider, api)
@@ -1502,12 +1526,14 @@ class Crew(FlowTrackable, BaseModel):
final_string_output = final_task_output.raw
self._finish_execution(final_string_output)
self.token_usage = self.calculate_usage_metrics()
crewai_event_bus.flush()
crewai_event_bus.emit(
self,
CrewKickoffCompletedEvent(
crew_name=self.name,
output=final_task_output,
total_tokens=self.token_usage.total_tokens,
started_event_id=self._kickoff_event_id,
),
)
@@ -2011,7 +2037,13 @@ class Crew(FlowTrackable, BaseModel):
@staticmethod
def _show_tracing_disabled_message() -> None:
"""Show a message when tracing is disabled."""
from crewai.events.listeners.tracing.utils import has_user_declined_tracing
from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
should_suppress_tracing_messages,
)
if should_suppress_tracing_messages():
return
console = Console()

View File

@@ -265,10 +265,9 @@ def prepare_kickoff(
normalized = {}
normalized = before_callback(normalized)
future = crewai_event_bus.emit(
crew,
CrewKickoffStartedEvent(crew_name=crew.name, inputs=normalized),
)
started_event = CrewKickoffStartedEvent(crew_name=crew.name, inputs=normalized)
crew._kickoff_event_id = started_event.event_id
future = crewai_event_bus.emit(crew, started_event)
if future is not None:
try:
future.result()

View File

@@ -195,6 +195,7 @@ __all__ = [
"ToolUsageFinishedEvent",
"ToolUsageStartedEvent",
"ToolValidateInputErrorEvent",
"_extension_exports",
"crewai_event_bus",
]
@@ -210,14 +211,29 @@ _AGENT_EVENT_MAPPING = {
"LiteAgentExecutionStartedEvent": "crewai.events.types.agent_events",
}
_extension_exports: dict[str, Any] = {}
def __getattr__(name: str) -> Any:
"""Lazy import for agent events to avoid circular imports."""
"""Lazy import for agent events and registered extensions."""
if name in _AGENT_EVENT_MAPPING:
import importlib
module_path = _AGENT_EVENT_MAPPING[name]
module = importlib.import_module(module_path)
return getattr(module, name)
if name in _extension_exports:
import importlib
value = _extension_exports[name]
if isinstance(value, str):
module_path, _, attr_name = value.rpartition(".")
if module_path:
module = importlib.import_module(module_path)
return getattr(module, attr_name)
return importlib.import_module(value)
return value
msg = f"module {__name__!r} has no attribute {name!r}"
raise AttributeError(msg)

View File

@@ -63,6 +63,7 @@ class BaseEvent(BaseModel):
parent_event_id: str | None = None
previous_event_id: str | None = None
triggered_by_event_id: str | None = None
started_event_id: str | None = None
emission_sequence: int | None = None
def to_json(self, exclude: set[str] | None = None) -> Serializable:

View File

@@ -227,6 +227,39 @@ class CrewAIEventsBus:
return decorator
def off(
self,
event_type: type[BaseEvent],
handler: Callable[..., Any],
) -> None:
"""Unregister an event handler for a specific event type.
Args:
event_type: The event class to stop listening for
handler: The handler function to unregister
"""
with self._rwlock.w_locked():
if event_type in self._sync_handlers:
existing_sync = self._sync_handlers[event_type]
if handler in existing_sync:
self._sync_handlers[event_type] = existing_sync - {handler}
if not self._sync_handlers[event_type]:
del self._sync_handlers[event_type]
if event_type in self._async_handlers:
existing_async = self._async_handlers[event_type]
if handler in existing_async:
self._async_handlers[event_type] = existing_async - {handler}
if not self._async_handlers[event_type]:
del self._async_handlers[event_type]
if event_type in self._handler_dependencies:
self._handler_dependencies[event_type].pop(handler, None)
if not self._handler_dependencies[event_type]:
del self._handler_dependencies[event_type]
self._execution_plan_cache.pop(event_type, None)
def _call_handlers(
self,
source: Any,
@@ -374,7 +407,8 @@ class CrewAIEventsBus:
if popped is None:
handle_empty_pop(event_type_name)
else:
_, popped_type = popped
popped_event_id, popped_type = popped
event.started_event_id = popped_event_id
expected_start = VALID_EVENT_PAIRS.get(event_type_name)
if expected_start and popped_type and popped_type != expected_start:
handle_mismatch(event_type_name, popped_type, expected_start)
@@ -536,24 +570,52 @@ class CrewAIEventsBus:
... # Do stuff...
... # Handlers are cleared after the context
"""
with self._rwlock.w_locked():
prev_sync = self._sync_handlers
prev_async = self._async_handlers
prev_deps = self._handler_dependencies
prev_cache = self._execution_plan_cache
self._sync_handlers = {}
self._async_handlers = {}
self._handler_dependencies = {}
self._execution_plan_cache = {}
with self._rwlock.r_locked():
saved_sync: dict[type[BaseEvent], frozenset[SyncHandler]] = dict(
self._sync_handlers
)
saved_async: dict[type[BaseEvent], frozenset[AsyncHandler]] = dict(
self._async_handlers
)
saved_deps: dict[type[BaseEvent], dict[Handler, list[Depends[Any]]]] = {
event_type: dict(handlers)
for event_type, handlers in self._handler_dependencies.items()
}
for event_type, sync_handlers in saved_sync.items():
for sync_handler in sync_handlers:
self.off(event_type, sync_handler)
for event_type, async_handlers in saved_async.items():
for async_handler in async_handlers:
self.off(event_type, async_handler)
try:
yield
finally:
with self._rwlock.w_locked():
self._sync_handlers = prev_sync
self._async_handlers = prev_async
self._handler_dependencies = prev_deps
self._execution_plan_cache = prev_cache
with self._rwlock.r_locked():
current_sync = dict(self._sync_handlers)
current_async = dict(self._async_handlers)
for event_type, cur_sync in current_sync.items():
orig_sync = saved_sync.get(event_type, frozenset())
for new_handler in cur_sync - orig_sync:
self.off(event_type, new_handler)
for event_type, cur_async in current_async.items():
orig_async = saved_async.get(event_type, frozenset())
for new_async_handler in cur_async - orig_async:
self.off(event_type, new_async_handler)
for event_type, sync_handlers in saved_sync.items():
for sync_handler in sync_handlers:
deps = saved_deps.get(event_type, {}).get(sync_handler)
self._register_handler(event_type, sync_handler, deps)
for event_type, async_handlers in saved_async.items():
for async_handler in async_handlers:
deps = saved_deps.get(event_type, {}).get(async_handler)
self._register_handler(event_type, async_handler, deps)
def shutdown(self, wait: bool = True) -> None:
"""Gracefully shutdown the event loop and wait for all tasks to finish.

View File

@@ -797,7 +797,13 @@ class TraceCollectionListener(BaseEventListener):
from rich.console import Console
from rich.panel import Panel
from crewai.events.listeners.tracing.utils import has_user_declined_tracing
from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
should_suppress_tracing_messages,
)
if should_suppress_tracing_messages():
return
console = Console()

View File

@@ -1,3 +1,4 @@
from collections.abc import Callable
from contextvars import ContextVar, Token
from datetime import datetime
import getpass
@@ -26,6 +27,35 @@ logger = logging.getLogger(__name__)
_tracing_enabled: ContextVar[bool | None] = ContextVar("_tracing_enabled", default=None)
_first_time_trace_hook: ContextVar[Callable[[], bool] | None] = ContextVar(
"_first_time_trace_hook", default=None
)
_suppress_tracing_messages: ContextVar[bool] = ContextVar(
"_suppress_tracing_messages", default=False
)
def set_suppress_tracing_messages(suppress: bool) -> object:
"""Set whether to suppress tracing-related console messages.
Args:
suppress: True to suppress messages, False to show them.
Returns:
A token that can be used to restore the previous value.
"""
return _suppress_tracing_messages.set(suppress)
def should_suppress_tracing_messages() -> bool:
"""Check if tracing messages should be suppressed.
Returns:
True if messages should be suppressed, False otherwise.
"""
return _suppress_tracing_messages.get()
def should_enable_tracing(*, override: bool | None = None) -> bool:
"""Determine if tracing should be enabled.
@@ -407,10 +437,13 @@ def truncate_messages(
def should_auto_collect_first_time_traces() -> bool:
"""True if we should auto-collect traces for first-time user.
Returns:
True if first-time user AND telemetry not disabled AND tracing not explicitly enabled, False otherwise.
"""
hook = _first_time_trace_hook.get()
if hook is not None:
return hook()
if _is_test_environment():
return False
@@ -432,6 +465,9 @@ def prompt_user_for_trace_viewing(timeout_seconds: int = 20) -> bool:
if _is_test_environment():
return False
if should_suppress_tracing_messages():
return False
try:
import threading

View File

@@ -16,7 +16,7 @@ class ToolUsageEvent(BaseEvent):
tool_name: str
tool_args: dict[str, Any] | str
tool_class: str | None = None
run_attempts: int | None = None
run_attempts: int = 0
delegations: int | None = None
agent: Any | None = None
task_name: str | None = None
@@ -26,7 +26,7 @@ class ToolUsageEvent(BaseEvent):
model_config = ConfigDict(arbitrary_types_allowed=True)
def __init__(self, **data):
def __init__(self, **data: Any) -> None:
if data.get("from_task"):
task = data["from_task"]
data["task_id"] = str(task.id)
@@ -96,10 +96,10 @@ class ToolExecutionErrorEvent(BaseEvent):
type: str = "tool_execution_error"
tool_name: str
tool_args: dict[str, Any]
tool_class: Callable
tool_class: Callable[..., Any]
agent: Any | None = None
def __init__(self, **data):
def __init__(self, **data: Any) -> None:
super().__init__(**data)
# Set fingerprint data from the agent
if self.agent and hasattr(self.agent, "fingerprint") and self.agent.fingerprint:

View File

@@ -1,3 +1,4 @@
from contextvars import ContextVar
import os
import threading
from typing import Any, ClassVar, cast
@@ -7,7 +8,37 @@ from rich.live import Live
from rich.panel import Panel
from rich.text import Text
from crewai.cli.version import is_newer_version_available
from crewai.cli.version import is_current_version_yanked, is_newer_version_available
_disable_version_check: ContextVar[bool] = ContextVar(
"_disable_version_check", default=False
)
_suppress_console_output: ContextVar[bool] = ContextVar(
"_suppress_console_output", default=False
)
def set_suppress_console_output(suppress: bool) -> object:
"""Set whether to suppress all console output.
Args:
suppress: True to suppress output, False to show it.
Returns:
A token that can be used to restore the previous value.
"""
return _suppress_console_output.set(suppress)
def should_suppress_console_output() -> bool:
"""Check if console output should be suppressed.
Returns:
True if output should be suppressed, False otherwise.
"""
return _suppress_console_output.get()
class ConsoleFormatter:
@@ -46,9 +77,15 @@ class ConsoleFormatter:
if not self.verbose:
return
if _disable_version_check.get():
return
if os.getenv("CI", "").lower() in ("true", "1"):
return
if os.getenv("CREWAI_DISABLE_VERSION_CHECK", "").lower() in ("true", "1"):
return
try:
is_newer, current, latest = is_newer_version_available()
if is_newer and latest:
@@ -67,6 +104,22 @@ To update, run: uv sync --upgrade-package crewai"""
)
self.console.print(panel)
self.console.print()
is_yanked, yanked_reason = is_current_version_yanked()
if is_yanked:
yanked_message = f"Version {current} has been yanked from PyPI."
if yanked_reason:
yanked_message += f"\nReason: {yanked_reason}"
yanked_message += "\n\nTo update, run: uv sync --upgrade-package crewai"
yanked_panel = Panel(
yanked_message,
title="Yanked Version",
border_style="red",
padding=(1, 2),
)
self.console.print(yanked_panel)
self.console.print()
except Exception: # noqa: S110
# Silently ignore errors in version check - it's non-critical
pass
@@ -76,8 +129,12 @@ To update, run: uv sync --upgrade-package crewai"""
from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
is_tracing_enabled_in_context,
should_suppress_tracing_messages,
)
if should_suppress_tracing_messages():
return
if not is_tracing_enabled_in_context():
if has_user_declined_tracing():
message = """Info: Tracing is disabled.
@@ -129,6 +186,8 @@ To enable tracing, do any one of these:
def print(self, *args: Any, **kwargs: Any) -> None:
"""Print to console. Simplified to only handle panel-based output."""
if should_suppress_console_output():
return
# Skip blank lines during streaming
if len(args) == 0 and self._is_streaming:
return
@@ -485,6 +544,9 @@ To enable tracing, do any one of these:
if not self.verbose:
return
if should_suppress_console_output():
return
self._is_streaming = True
self._last_stream_call_type = call_type

View File

@@ -18,6 +18,7 @@ from crewai.agents.parser import (
AgentFinish,
OutputParserError,
)
from crewai.core.providers.human_input import get_provider
from crewai.events.event_bus import crewai_event_bus
from crewai.events.listeners.tracing.utils import (
is_tracing_enabled_in_context,
@@ -31,7 +32,8 @@ from crewai.events.types.tool_usage_events import (
ToolUsageFinishedEvent,
ToolUsageStartedEvent,
)
from crewai.flow.flow import Flow, listen, or_, router, start
from crewai.flow.flow import Flow, StateProxy, listen, or_, router, start
from crewai.flow.types import FlowMethodName
from crewai.hooks.llm_hooks import (
get_after_llm_call_hooks,
get_before_llm_call_hooks,
@@ -41,7 +43,12 @@ from crewai.hooks.tool_hooks import (
get_after_tool_call_hooks,
get_before_tool_call_hooks,
)
from crewai.hooks.types import AfterLLMCallHookType, BeforeLLMCallHookType
from crewai.hooks.types import (
AfterLLMCallHookCallable,
AfterLLMCallHookType,
BeforeLLMCallHookCallable,
BeforeLLMCallHookType,
)
from crewai.utilities.agent_utils import (
convert_tools_to_openai_schema,
enforce_rpm_limit,
@@ -191,8 +198,12 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
self._instance_id = str(uuid4())[:8]
self.before_llm_call_hooks: list[BeforeLLMCallHookType] = []
self.after_llm_call_hooks: list[AfterLLMCallHookType] = []
self.before_llm_call_hooks: list[
BeforeLLMCallHookType | BeforeLLMCallHookCallable
] = []
self.after_llm_call_hooks: list[
AfterLLMCallHookType | AfterLLMCallHookCallable
] = []
self.before_llm_call_hooks.extend(get_before_llm_call_hooks())
self.after_llm_call_hooks.extend(get_after_llm_call_hooks())
@@ -207,6 +218,71 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._state = AgentReActState()
@property
def messages(self) -> list[LLMMessage]:
"""Delegate to state for ExecutorContext conformance."""
return self._state.messages
@messages.setter
def messages(self, value: list[LLMMessage]) -> None:
"""Delegate to state for ExecutorContext conformance."""
if self._flow_initialized and hasattr(self, "_state_lock"):
with self._state_lock:
self._state.messages = value
else:
self._state.messages = value
@property
def ask_for_human_input(self) -> bool:
"""Delegate to state for ExecutorContext conformance."""
return self._state.ask_for_human_input
@ask_for_human_input.setter
def ask_for_human_input(self, value: bool) -> None:
"""Delegate to state for ExecutorContext conformance."""
self._state.ask_for_human_input = value
def _invoke_loop(self) -> AgentFinish:
"""Invoke the agent loop and return the result.
Required by ExecutorContext protocol.
"""
self._state.iterations = 0
self._state.is_finished = False
self._state.current_answer = None
self.kickoff()
answer = self._state.current_answer
if not isinstance(answer, AgentFinish):
raise RuntimeError("Agent loop did not produce a final answer")
return answer
async def _ainvoke_loop(self) -> AgentFinish:
"""Invoke the agent loop asynchronously and return the result.
Required by AsyncExecutorContext protocol.
"""
self._state.iterations = 0
self._state.is_finished = False
self._state.current_answer = None
await self.akickoff()
answer = self._state.current_answer
if not isinstance(answer, AgentFinish):
raise RuntimeError("Agent loop did not produce a final answer")
return answer
def _format_feedback_message(self, feedback: str) -> LLMMessage:
"""Format feedback as a message for the LLM.
Required by ExecutorContext protocol.
"""
return format_message_for_llm(
self._i18n.slice("feedback_instructions").format(feedback=feedback)
)
def _ensure_flow_initialized(self) -> None:
"""Ensure Flow.__init__() has been called.
@@ -298,18 +374,10 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
Flow initialization is deferred to prevent event emission during agent setup.
Returns the temporary state until invoke() is called.
"""
if self._flow_initialized and hasattr(self, "_state_lock"):
return StateProxy(self._state, self._state_lock) # type: ignore[return-value]
return self._state
@property
def messages(self) -> list[LLMMessage]:
"""Compatibility property for mixin - returns state messages."""
return self._state.messages
@messages.setter
def messages(self, value: list[LLMMessage]) -> None:
"""Set state messages."""
self._state.messages = value
@property
def iterations(self) -> int:
"""Compatibility property for mixin - returns state iterations."""
@@ -416,15 +484,14 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
raise
@listen("continue_reasoning_native")
def call_llm_native_tools(
self,
) -> Literal["native_tool_calls", "native_finished", "context_error"]:
def call_llm_native_tools(self) -> None:
"""Execute LLM call with native function calling.
Always calls the LLM so it can read reflection prompts and decide
whether to provide a final answer or request more tools.
Returns routing decision based on whether tool calls or final answer.
Note: This is a listener, not a router. The route_native_tool_result
router fires after this to determine the next step based on state.
"""
try:
# Clear pending tools - LLM will decide what to do next after reading
@@ -454,8 +521,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
if isinstance(answer, list) and answer and self._is_tool_call_list(answer):
# Store tool calls for sequential processing
self.state.pending_tool_calls = list(answer)
return "native_tool_calls"
return # Router will check pending_tool_calls
if isinstance(answer, BaseModel):
self.state.current_answer = AgentFinish(
@@ -465,7 +531,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._invoke_step_callback(self.state.current_answer)
self._append_message_to_state(answer.model_dump_json())
return "native_finished"
return # Router will check current_answer
# Text response - this is the final answer
if isinstance(answer, str):
@@ -476,8 +542,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._invoke_step_callback(self.state.current_answer)
self._append_message_to_state(answer)
return "native_finished"
return # Router will check current_answer
# Unexpected response type, treat as final answer
self.state.current_answer = AgentFinish(
@@ -487,13 +552,12 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._invoke_step_callback(self.state.current_answer)
self._append_message_to_state(str(answer))
return "native_finished"
# Router will check current_answer
except Exception as e:
if is_context_length_exceeded(e):
self._last_context_error = e
return "context_error"
return # Router will check _last_context_error
if e.__class__.__module__.startswith("litellm"):
raise e
handle_unknown_error(self._printer, e, verbose=self.agent.verbose)
@@ -506,6 +570,22 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
return "execute_tool"
return "agent_finished"
@router(call_llm_native_tools)
def route_native_tool_result(
self,
) -> Literal["native_tool_calls", "native_finished", "context_error"]:
"""Route based on LLM response for native tool calling.
Checks state set by call_llm_native_tools to determine next step.
This router is needed because only router return values trigger
downstream listeners.
"""
if self._last_context_error is not None:
return "context_error"
if self.state.pending_tool_calls:
return "native_tool_calls"
return "native_finished"
@listen("execute_tool")
def execute_tool_action(self) -> Literal["tool_completed", "tool_result_is_final"]:
"""Execute the tool action and handle the result."""
@@ -689,6 +769,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
agent_key=agent_key,
),
)
error_event_emitted = False
track_delegation_if_needed(func_name, args_dict, self.task)
@@ -764,6 +845,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
error=e,
),
)
error_event_emitted = True
elif max_usage_reached and original_tool:
# Return error message when max usage limit is reached
result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
@@ -792,20 +874,20 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
color="red",
)
# Emit tool usage finished event
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
if not error_event_emitted:
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
# Append tool result message
tool_message: LLMMessage = {
@@ -861,9 +943,11 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
self.state.iterations += 1
return "initialized"
@listen("initialized")
@listen(or_("initialized", "tool_completed", "native_tool_completed"))
def continue_iteration(self) -> Literal["check_iteration"]:
"""Bridge listener that connects iteration loop back to iteration check."""
if self._flow_initialized:
self._discard_or_listener(FlowMethodName("continue_iteration"))
return "check_iteration"
@router(or_(initialize_reasoning, continue_iteration))
@@ -1105,7 +1189,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
if self.state.ask_for_human_input:
formatted_answer = self._handle_human_feedback(formatted_answer)
formatted_answer = await self._ahandle_human_feedback(formatted_answer)
self._create_short_term_memory(formatted_answer)
self._create_long_term_memory(formatted_answer)
@@ -1319,17 +1403,22 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
Returns:
Final answer after feedback.
"""
output_str = (
str(formatted_answer.output)
if isinstance(formatted_answer.output, BaseModel)
else formatted_answer.output
)
human_feedback = self._ask_human_input(output_str)
provider = get_provider()
return provider.handle_feedback(formatted_answer, self)
if self._is_training_mode():
return self._handle_training_feedback(formatted_answer, human_feedback)
async def _ahandle_human_feedback(
self, formatted_answer: AgentFinish
) -> AgentFinish:
"""Process human feedback asynchronously and refine answer.
return self._handle_regular_feedback(formatted_answer, human_feedback)
Args:
formatted_answer: Initial agent result.
Returns:
Final answer after feedback.
"""
provider = get_provider()
return await provider.handle_feedback_async(formatted_answer, self)
def _is_training_mode(self) -> bool:
"""Check if training mode is active.
@@ -1339,101 +1428,6 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
"""
return bool(self.crew and self.crew._train)
def _handle_training_feedback(
self, initial_answer: AgentFinish, feedback: str
) -> AgentFinish:
"""Process training feedback and generate improved answer.
Args:
initial_answer: Initial agent output.
feedback: Training feedback.
Returns:
Improved answer.
"""
self._handle_crew_training_output(initial_answer, feedback)
self.state.messages.append(
format_message_for_llm(
self._i18n.slice("feedback_instructions").format(feedback=feedback)
)
)
# Re-run flow for improved answer
self.state.iterations = 0
self.state.is_finished = False
self.state.current_answer = None
self.kickoff()
# Get improved answer from state
improved_answer = self.state.current_answer
if not isinstance(improved_answer, AgentFinish):
raise RuntimeError(
"Training feedback iteration did not produce final answer"
)
self._handle_crew_training_output(improved_answer)
self.state.ask_for_human_input = False
return improved_answer
def _handle_regular_feedback(
self, current_answer: AgentFinish, initial_feedback: str
) -> AgentFinish:
"""Process regular feedback iteratively until user is satisfied.
Args:
current_answer: Current agent output.
initial_feedback: Initial user feedback.
Returns:
Final answer after iterations.
"""
feedback = initial_feedback
answer = current_answer
while self.state.ask_for_human_input:
if feedback.strip() == "":
self.state.ask_for_human_input = False
else:
answer = self._process_feedback_iteration(feedback)
output_str = (
str(answer.output)
if isinstance(answer.output, BaseModel)
else answer.output
)
feedback = self._ask_human_input(output_str)
return answer
def _process_feedback_iteration(self, feedback: str) -> AgentFinish:
"""Process a single feedback iteration and generate updated response.
Args:
feedback: User feedback.
Returns:
Updated agent response.
"""
self.state.messages.append(
format_message_for_llm(
self._i18n.slice("feedback_instructions").format(feedback=feedback)
)
)
# Re-run flow
self.state.iterations = 0
self.state.is_finished = False
self.state.current_answer = None
self.kickoff()
# Get answer from state
answer = self.state.current_answer
if not isinstance(answer, AgentFinish):
raise RuntimeError("Feedback iteration did not produce final answer")
return answer
@classmethod
def __get_pydantic_core_schema__(
cls, _source_type: Any, _handler: GetCoreSchemaHandler

View File

@@ -28,6 +28,8 @@ Example:
```
"""
from typing import Any
from crewai.flow.async_feedback.providers import ConsoleProvider
from crewai.flow.async_feedback.types import (
HumanFeedbackPending,
@@ -41,4 +43,15 @@ __all__ = [
"HumanFeedbackPending",
"HumanFeedbackProvider",
"PendingFeedbackContext",
"_extension_exports",
]
_extension_exports: dict[str, Any] = {}
def __getattr__(name: str) -> Any:
"""Support extensions via dynamic attribute lookup."""
if name in _extension_exports:
return _extension_exports[name]
msg = f"module {__name__!r} has no attribute {name!r}"
raise AttributeError(msg)

View File

@@ -7,7 +7,14 @@ for building event-driven workflows with conditional execution and routing.
from __future__ import annotations
import asyncio
from collections.abc import Callable, Sequence
from collections.abc import (
Callable,
ItemsView,
Iterator,
KeysView,
Sequence,
ValuesView,
)
from concurrent.futures import Future
import copy
import inspect
@@ -45,6 +52,7 @@ from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
set_tracing_enabled,
should_enable_tracing,
should_suppress_tracing_messages,
)
from crewai.events.types.flow_events import (
FlowCreatedEvent,
@@ -408,6 +416,132 @@ def and_(*conditions: str | FlowCondition | Callable[..., Any]) -> FlowCondition
return {"type": AND_CONDITION, "conditions": processed_conditions}
class LockedListProxy(Generic[T]):
"""Thread-safe proxy for list operations.
Wraps a list and uses a lock for all mutating operations.
"""
def __init__(self, lst: list[T], lock: threading.Lock) -> None:
self._list = lst
self._lock = lock
def append(self, item: T) -> None:
with self._lock:
self._list.append(item)
def extend(self, items: list[T]) -> None:
with self._lock:
self._list.extend(items)
def insert(self, index: int, item: T) -> None:
with self._lock:
self._list.insert(index, item)
def remove(self, item: T) -> None:
with self._lock:
self._list.remove(item)
def pop(self, index: int = -1) -> T:
with self._lock:
return self._list.pop(index)
def clear(self) -> None:
with self._lock:
self._list.clear()
def __setitem__(self, index: int, value: T) -> None:
with self._lock:
self._list[index] = value
def __delitem__(self, index: int) -> None:
with self._lock:
del self._list[index]
def __getitem__(self, index: int) -> T:
return self._list[index]
def __len__(self) -> int:
return len(self._list)
def __iter__(self) -> Iterator[T]:
return iter(self._list)
def __contains__(self, item: object) -> bool:
return item in self._list
def __repr__(self) -> str:
return repr(self._list)
def __bool__(self) -> bool:
return bool(self._list)
class LockedDictProxy(Generic[T]):
"""Thread-safe proxy for dict operations.
Wraps a dict and uses a lock for all mutating operations.
"""
def __init__(self, d: dict[str, T], lock: threading.Lock) -> None:
self._dict = d
self._lock = lock
def __setitem__(self, key: str, value: T) -> None:
with self._lock:
self._dict[key] = value
def __delitem__(self, key: str) -> None:
with self._lock:
del self._dict[key]
def pop(self, key: str, *default: T) -> T:
with self._lock:
return self._dict.pop(key, *default)
def update(self, other: dict[str, T]) -> None:
with self._lock:
self._dict.update(other)
def clear(self) -> None:
with self._lock:
self._dict.clear()
def setdefault(self, key: str, default: T) -> T:
with self._lock:
return self._dict.setdefault(key, default)
def __getitem__(self, key: str) -> T:
return self._dict[key]
def __len__(self) -> int:
return len(self._dict)
def __iter__(self) -> Iterator[str]:
return iter(self._dict)
def __contains__(self, key: object) -> bool:
return key in self._dict
def keys(self) -> KeysView[str]:
return self._dict.keys()
def values(self) -> ValuesView[T]:
return self._dict.values()
def items(self) -> ItemsView[str, T]:
return self._dict.items()
def get(self, key: str, default: T | None = None) -> T | None:
return self._dict.get(key, default)
def __repr__(self) -> str:
return repr(self._dict)
def __bool__(self) -> bool:
return bool(self._dict)
class StateProxy(Generic[T]):
"""Proxy that provides thread-safe access to flow state.
@@ -422,7 +556,13 @@ class StateProxy(Generic[T]):
object.__setattr__(self, "_proxy_lock", lock)
def __getattr__(self, name: str) -> Any:
return getattr(object.__getattribute__(self, "_proxy_state"), name)
value = getattr(object.__getattribute__(self, "_proxy_state"), name)
lock = object.__getattribute__(self, "_proxy_lock")
if isinstance(value, list):
return LockedListProxy(value, lock)
if isinstance(value, dict):
return LockedDictProxy(value, lock)
return value
def __setattr__(self, name: str, value: Any) -> None:
if name in ("_proxy_state", "_proxy_lock"):
@@ -1592,7 +1732,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
reset_emission_counter()
reset_last_event_id()
# Emit FlowStartedEvent and log the start of the flow.
if not self.suppress_flow_events:
future = crewai_event_bus.emit(
self,
@@ -1603,7 +1742,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
),
)
if future:
self._event_futures.append(future)
try:
await asyncio.wrap_future(future)
except Exception:
logger.warning("FlowStartedEvent handler failed", exc_info=True)
self._log_flow_event(
f"Flow started with ID: {self.flow_id}", color="bold magenta"
)
@@ -1695,6 +1837,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
final_output = self._method_outputs[-1] if self._method_outputs else None
if self._event_futures:
await asyncio.gather(
*[asyncio.wrap_future(f) for f in self._event_futures]
)
self._event_futures.clear()
if not self.suppress_flow_events:
future = crewai_event_bus.emit(
self,
@@ -1706,13 +1854,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
),
)
if future:
self._event_futures.append(future)
if self._event_futures:
await asyncio.gather(
*[asyncio.wrap_future(f) for f in self._event_futures]
)
self._event_futures.clear()
try:
await asyncio.wrap_future(future)
except Exception:
logger.warning(
"FlowFinishedEvent handler failed", exc_info=True
)
if not self.suppress_flow_events:
trace_listener = TraceCollectionListener()
@@ -1787,40 +1934,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
await self._execute_listeners(start_method_name, result, finished_event_id)
# Then execute listeners for the router result (e.g., "approved")
router_result_trigger = FlowMethodName(str(result))
listeners_for_result = self._find_triggered_methods(
router_result_trigger, router_only=False
listener_result = (
self.last_human_feedback
if self.last_human_feedback is not None
else result
)
await self._execute_listeners(
router_result_trigger, listener_result, finished_event_id
)
if listeners_for_result:
# Pass the HumanFeedbackResult if available
listener_result = (
self.last_human_feedback
if self.last_human_feedback is not None
else result
)
racing_group = self._get_racing_group_for_listeners(
listeners_for_result
)
if racing_group:
racing_members, _ = racing_group
other_listeners = [
name
for name in listeners_for_result
if name not in racing_members
]
await self._execute_racing_listeners(
racing_members,
other_listeners,
listener_result,
finished_event_id,
)
else:
tasks = [
self._execute_single_listener(
listener_name, listener_result, finished_event_id
)
for listener_name in listeners_for_result
]
await asyncio.gather(*tasks)
else:
await self._execute_listeners(start_method_name, result, finished_event_id)
@@ -2026,15 +2147,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
router_input = router_result_to_feedback.get(
str(current_trigger), current_result
)
current_triggering_event_id = await self._execute_single_listener(
(
router_result,
current_triggering_event_id,
) = await self._execute_single_listener(
router_name, router_input, current_triggering_event_id
)
# After executing router, the router's result is the path
router_result = (
self._method_outputs[-1] if self._method_outputs else None
)
if router_result: # Only add non-None results
router_results.append(router_result)
router_results.append(FlowMethodName(str(router_result)))
# If this was a human_feedback router, map the outcome to the feedback
if self.last_human_feedback is not None:
router_result_to_feedback[str(router_result)] = (
@@ -2074,12 +2194,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
racing_members,
other_listeners,
listener_result,
triggering_event_id,
current_triggering_event_id,
)
else:
tasks = [
self._execute_single_listener(
listener_name, listener_result, triggering_event_id
listener_name,
listener_result,
current_triggering_event_id,
)
for listener_name in listeners_triggered
]
@@ -2262,7 +2384,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
listener_name: FlowMethodName,
result: Any,
triggering_event_id: str | None = None,
) -> str | None:
) -> tuple[Any, str | None]:
"""Executes a single listener method with proper event handling.
This internal method manages the execution of an individual listener,
@@ -2275,8 +2397,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
used for causal chain tracking.
Returns:
The event_id of the MethodExecutionFinishedEvent emitted by this listener,
or None if events are suppressed.
A tuple of (listener_result, event_id) where listener_result is the return
value of the listener method and event_id is the MethodExecutionFinishedEvent
id, or (None, None) if skipped during resumption.
Note:
- Inspects method signature to determine if it accepts the trigger result
@@ -2302,7 +2425,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
):
# This conditional start was executed, continue its chain
await self._execute_start_method(start_method_name)
return None
return (None, None)
# For cyclic flows, clear from completed to allow re-execution
self._completed_methods.discard(listener_name)
# Also clear from fired OR listeners for cyclic flows
@@ -2340,46 +2463,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
listener_name, listener_result, finished_event_id
)
# If this listener is also a router (e.g., has @human_feedback with emit),
# we need to trigger listeners for the router result as well
if listener_name in self._routers and listener_result is not None:
router_result_trigger = FlowMethodName(str(listener_result))
listeners_for_result = self._find_triggered_methods(
router_result_trigger, router_only=False
)
if listeners_for_result:
# Pass the HumanFeedbackResult if available
feedback_result = (
self.last_human_feedback
if self.last_human_feedback is not None
else listener_result
)
racing_group = self._get_racing_group_for_listeners(
listeners_for_result
)
if racing_group:
racing_members, _ = racing_group
other_listeners = [
name
for name in listeners_for_result
if name not in racing_members
]
await self._execute_racing_listeners(
racing_members,
other_listeners,
feedback_result,
finished_event_id,
)
else:
tasks = [
self._execute_single_listener(
name, feedback_result, finished_event_id
)
for name in listeners_for_result
]
await asyncio.gather(*tasks)
return finished_event_id
return (listener_result, finished_event_id)
except Exception as e:
# Don't log HumanFeedbackPending as an error - it's expected control flow
@@ -2626,6 +2710,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
@staticmethod
def _show_tracing_disabled_message() -> None:
"""Show a message when tracing is disabled."""
if should_suppress_tracing_messages():
return
console = Console()

View File

@@ -3,7 +3,12 @@ from __future__ import annotations
from typing import TYPE_CHECKING, Any, cast
from crewai.events.event_listener import event_listener
from crewai.hooks.types import AfterLLMCallHookType, BeforeLLMCallHookType
from crewai.hooks.types import (
AfterLLMCallHookCallable,
AfterLLMCallHookType,
BeforeLLMCallHookCallable,
BeforeLLMCallHookType,
)
from crewai.utilities.printer import Printer
@@ -149,12 +154,12 @@ class LLMCallHookContext:
event_listener.formatter.resume_live_updates()
_before_llm_call_hooks: list[BeforeLLMCallHookType] = []
_after_llm_call_hooks: list[AfterLLMCallHookType] = []
_before_llm_call_hooks: list[BeforeLLMCallHookType | BeforeLLMCallHookCallable] = []
_after_llm_call_hooks: list[AfterLLMCallHookType | AfterLLMCallHookCallable] = []
def register_before_llm_call_hook(
hook: BeforeLLMCallHookType,
hook: BeforeLLMCallHookType | BeforeLLMCallHookCallable,
) -> None:
"""Register a global before_llm_call hook.
@@ -190,7 +195,7 @@ def register_before_llm_call_hook(
def register_after_llm_call_hook(
hook: AfterLLMCallHookType,
hook: AfterLLMCallHookType | AfterLLMCallHookCallable,
) -> None:
"""Register a global after_llm_call hook.
@@ -217,7 +222,9 @@ def register_after_llm_call_hook(
_after_llm_call_hooks.append(hook)
def get_before_llm_call_hooks() -> list[BeforeLLMCallHookType]:
def get_before_llm_call_hooks() -> list[
BeforeLLMCallHookType | BeforeLLMCallHookCallable
]:
"""Get all registered global before_llm_call hooks.
Returns:
@@ -226,7 +233,7 @@ def get_before_llm_call_hooks() -> list[BeforeLLMCallHookType]:
return _before_llm_call_hooks.copy()
def get_after_llm_call_hooks() -> list[AfterLLMCallHookType]:
def get_after_llm_call_hooks() -> list[AfterLLMCallHookType | AfterLLMCallHookCallable]:
"""Get all registered global after_llm_call hooks.
Returns:
@@ -236,7 +243,7 @@ def get_after_llm_call_hooks() -> list[AfterLLMCallHookType]:
def unregister_before_llm_call_hook(
hook: BeforeLLMCallHookType,
hook: BeforeLLMCallHookType | BeforeLLMCallHookCallable,
) -> bool:
"""Unregister a specific global before_llm_call hook.
@@ -262,7 +269,7 @@ def unregister_before_llm_call_hook(
def unregister_after_llm_call_hook(
hook: AfterLLMCallHookType,
hook: AfterLLMCallHookType | AfterLLMCallHookCallable,
) -> bool:
"""Unregister a specific global after_llm_call hook.

View File

@@ -3,7 +3,12 @@ from __future__ import annotations
from typing import TYPE_CHECKING, Any
from crewai.events.event_listener import event_listener
from crewai.hooks.types import AfterToolCallHookType, BeforeToolCallHookType
from crewai.hooks.types import (
AfterToolCallHookCallable,
AfterToolCallHookType,
BeforeToolCallHookCallable,
BeforeToolCallHookType,
)
from crewai.utilities.printer import Printer
@@ -112,12 +117,12 @@ class ToolCallHookContext:
# Global hook registries
_before_tool_call_hooks: list[BeforeToolCallHookType] = []
_after_tool_call_hooks: list[AfterToolCallHookType] = []
_before_tool_call_hooks: list[BeforeToolCallHookType | BeforeToolCallHookCallable] = []
_after_tool_call_hooks: list[AfterToolCallHookType | AfterToolCallHookCallable] = []
def register_before_tool_call_hook(
hook: BeforeToolCallHookType,
hook: BeforeToolCallHookType | BeforeToolCallHookCallable,
) -> None:
"""Register a global before_tool_call hook.
@@ -154,7 +159,7 @@ def register_before_tool_call_hook(
def register_after_tool_call_hook(
hook: AfterToolCallHookType,
hook: AfterToolCallHookType | AfterToolCallHookCallable,
) -> None:
"""Register a global after_tool_call hook.
@@ -184,7 +189,9 @@ def register_after_tool_call_hook(
_after_tool_call_hooks.append(hook)
def get_before_tool_call_hooks() -> list[BeforeToolCallHookType]:
def get_before_tool_call_hooks() -> list[
BeforeToolCallHookType | BeforeToolCallHookCallable
]:
"""Get all registered global before_tool_call hooks.
Returns:
@@ -193,7 +200,9 @@ def get_before_tool_call_hooks() -> list[BeforeToolCallHookType]:
return _before_tool_call_hooks.copy()
def get_after_tool_call_hooks() -> list[AfterToolCallHookType]:
def get_after_tool_call_hooks() -> list[
AfterToolCallHookType | AfterToolCallHookCallable
]:
"""Get all registered global after_tool_call hooks.
Returns:
@@ -203,7 +212,7 @@ def get_after_tool_call_hooks() -> list[AfterToolCallHookType]:
def unregister_before_tool_call_hook(
hook: BeforeToolCallHookType,
hook: BeforeToolCallHookType | BeforeToolCallHookCallable,
) -> bool:
"""Unregister a specific global before_tool_call hook.
@@ -229,7 +238,7 @@ def unregister_before_tool_call_hook(
def unregister_after_tool_call_hook(
hook: AfterToolCallHookType,
hook: AfterToolCallHookType | AfterToolCallHookCallable,
) -> bool:
"""Unregister a specific global after_tool_call hook.

View File

@@ -0,0 +1 @@
"""Knowledge source utilities."""

View File

@@ -0,0 +1,70 @@
"""Helper utilities for knowledge sources."""
from typing import Any, ClassVar
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.knowledge.source.csv_knowledge_source import CSVKnowledgeSource
from crewai.knowledge.source.excel_knowledge_source import ExcelKnowledgeSource
from crewai.knowledge.source.json_knowledge_source import JSONKnowledgeSource
from crewai.knowledge.source.pdf_knowledge_source import PDFKnowledgeSource
from crewai.knowledge.source.text_file_knowledge_source import TextFileKnowledgeSource
class SourceHelper:
"""Helper class for creating and managing knowledge sources."""
SUPPORTED_FILE_TYPES: ClassVar[list[str]] = [
".csv",
".pdf",
".json",
".txt",
".xlsx",
".xls",
]
_FILE_TYPE_MAP: ClassVar[dict[str, type[BaseKnowledgeSource]]] = {
".csv": CSVKnowledgeSource,
".pdf": PDFKnowledgeSource,
".json": JSONKnowledgeSource,
".txt": TextFileKnowledgeSource,
".xlsx": ExcelKnowledgeSource,
".xls": ExcelKnowledgeSource,
}
@classmethod
def is_supported_file(cls, file_path: str) -> bool:
"""Check if a file type is supported.
Args:
file_path: Path to the file.
Returns:
True if the file type is supported.
"""
return file_path.lower().endswith(tuple(cls.SUPPORTED_FILE_TYPES))
@classmethod
def get_source(
cls, file_path: str, metadata: dict[str, Any] | None = None
) -> BaseKnowledgeSource:
"""Create appropriate KnowledgeSource based on file extension.
Args:
file_path: Path to the file.
metadata: Optional metadata to attach to the source.
Returns:
The appropriate KnowledgeSource instance.
Raises:
ValueError: If the file type is not supported.
"""
if not cls.is_supported_file(file_path):
raise ValueError(f"Unsupported file type: {file_path}")
lower_path = file_path.lower()
for ext, source_cls in cls._FILE_TYPE_MAP.items():
if lower_path.endswith(ext):
return source_cls(file_path=[file_path], metadata=metadata)
raise ValueError(f"Unsupported file type: {file_path}")

View File

@@ -1580,10 +1580,12 @@ class AnthropicCompletion(BaseLLM):
usage = response.usage
input_tokens = getattr(usage, "input_tokens", 0)
output_tokens = getattr(usage, "output_tokens", 0)
cache_read_tokens = getattr(usage, "cache_read_input_tokens", 0) or 0
return {
"input_tokens": input_tokens,
"output_tokens": output_tokens,
"total_tokens": input_tokens + output_tokens,
"cached_prompt_tokens": cache_read_tokens,
}
return {"total_tokens": 0}

View File

@@ -425,8 +425,9 @@ class AzureCompletion(BaseLLM):
"stream": self.stream,
}
model_extras: dict[str, Any] = {}
if self.stream:
params["model_extras"] = {"stream_options": {"include_usage": True}}
model_extras["stream_options"] = {"include_usage": True}
if response_model and self.is_openai_model:
model_description = generate_model_description(response_model)
@@ -464,6 +465,13 @@ class AzureCompletion(BaseLLM):
params["tools"] = self._convert_tools_for_interference(tools)
params["tool_choice"] = "auto"
prompt_cache_key = self.additional_params.get("prompt_cache_key")
if prompt_cache_key:
model_extras["prompt_cache_key"] = prompt_cache_key
if model_extras:
params["model_extras"] = model_extras
additional_params = self.additional_params
additional_drop_params = additional_params.get("additional_drop_params")
drop_params = additional_params.get("drop_params")
@@ -1063,10 +1071,15 @@ class AzureCompletion(BaseLLM):
"""Extract token usage from Azure response."""
if hasattr(response, "usage") and response.usage:
usage = response.usage
cached_tokens = 0
prompt_details = getattr(usage, "prompt_tokens_details", None)
if prompt_details:
cached_tokens = getattr(prompt_details, "cached_tokens", 0) or 0
return {
"prompt_tokens": getattr(usage, "prompt_tokens", 0),
"completion_tokens": getattr(usage, "completion_tokens", 0),
"total_tokens": getattr(usage, "total_tokens", 0),
"cached_prompt_tokens": cached_tokens,
}
return {"total_tokens": 0}

View File

@@ -1295,11 +1295,13 @@ class GeminiCompletion(BaseLLM):
"""Extract token usage from Gemini response."""
if response.usage_metadata:
usage = response.usage_metadata
cached_tokens = getattr(usage, "cached_content_token_count", 0) or 0
return {
"prompt_token_count": getattr(usage, "prompt_token_count", 0),
"candidates_token_count": getattr(usage, "candidates_token_count", 0),
"total_token_count": getattr(usage, "total_token_count", 0),
"total_tokens": getattr(usage, "total_token_count", 0),
"cached_prompt_tokens": cached_tokens,
}
return {"total_tokens": 0}

View File

@@ -1094,11 +1094,7 @@ class OpenAICompletion(BaseLLM):
if reasoning_items:
self._last_reasoning_items = reasoning_items
if event.response and event.response.usage:
usage = {
"prompt_tokens": event.response.usage.input_tokens,
"completion_tokens": event.response.usage.output_tokens,
"total_tokens": event.response.usage.total_tokens,
}
usage = self._extract_responses_token_usage(event.response)
self._track_token_usage_internal(usage)
# If parse_tool_outputs is enabled, return structured result
@@ -1222,11 +1218,7 @@ class OpenAICompletion(BaseLLM):
if reasoning_items:
self._last_reasoning_items = reasoning_items
if event.response and event.response.usage:
usage = {
"prompt_tokens": event.response.usage.input_tokens,
"completion_tokens": event.response.usage.output_tokens,
"total_tokens": event.response.usage.total_tokens,
}
usage = self._extract_responses_token_usage(event.response)
self._track_token_usage_internal(usage)
# If parse_tool_outputs is enabled, return structured result
@@ -1310,11 +1302,18 @@ class OpenAICompletion(BaseLLM):
def _extract_responses_token_usage(self, response: Response) -> dict[str, Any]:
"""Extract token usage from Responses API response."""
if response.usage:
return {
result = {
"prompt_tokens": response.usage.input_tokens,
"completion_tokens": response.usage.output_tokens,
"total_tokens": response.usage.total_tokens,
}
# Extract cached prompt tokens from input_tokens_details
input_details = getattr(response.usage, "input_tokens_details", None)
if input_details:
result["cached_prompt_tokens"] = (
getattr(input_details, "cached_tokens", 0) or 0
)
return result
return {"total_tokens": 0}
def _extract_builtin_tool_outputs(self, response: Response) -> ResponsesAPIResult:
@@ -1696,6 +1695,99 @@ class OpenAICompletion(BaseLLM):
return content
def _finalize_streaming_response(
self,
full_response: str,
tool_calls: dict[int, dict[str, Any]],
usage_data: dict[str, int],
params: dict[str, Any],
available_functions: dict[str, Any] | None = None,
from_task: Any | None = None,
from_agent: Any | None = None,
) -> str | list[dict[str, Any]]:
"""Finalize a streaming response with usage tracking, tool call handling, and events.
Args:
full_response: The accumulated text response from the stream.
tool_calls: Accumulated tool calls from the stream, keyed by index.
usage_data: Token usage data from the stream.
params: The completion parameters containing messages.
available_functions: Available functions for tool calling.
from_task: Task that initiated the call.
from_agent: Agent that initiated the call.
Returns:
Tool calls list when tools were invoked without available_functions,
tool execution result when available_functions is provided,
or the text response string.
"""
self._track_token_usage_internal(usage_data)
if tool_calls and not available_functions:
tool_calls_list = [
{
"id": call_data["id"],
"type": "function",
"function": {
"name": call_data["name"],
"arguments": call_data["arguments"],
},
"index": call_data["index"],
}
for call_data in tool_calls.values()
]
self._emit_call_completed_event(
response=tool_calls_list,
call_type=LLMCallType.TOOL_CALL,
from_task=from_task,
from_agent=from_agent,
messages=params["messages"],
)
return tool_calls_list
if tool_calls and available_functions:
for call_data in tool_calls.values():
function_name = call_data["name"]
arguments = call_data["arguments"]
if not function_name or not arguments:
continue
if function_name not in available_functions:
logging.warning(
f"Function '{function_name}' not found in available functions"
)
continue
try:
function_args = json.loads(arguments)
except json.JSONDecodeError as e:
logging.error(f"Failed to parse streamed tool arguments: {e}")
continue
result = self._handle_tool_execution(
function_name=function_name,
function_args=function_args,
available_functions=available_functions,
from_task=from_task,
from_agent=from_agent,
)
if result is not None:
return result
full_response = self._apply_stop_words(full_response)
self._emit_call_completed_event(
response=full_response,
call_type=LLMCallType.LLM_CALL,
from_task=from_task,
from_agent=from_agent,
messages=params["messages"],
)
return full_response
def _handle_streaming_completion(
self,
params: dict[str, Any],
@@ -1703,7 +1795,7 @@ class OpenAICompletion(BaseLLM):
from_task: Any | None = None,
from_agent: Any | None = None,
response_model: type[BaseModel] | None = None,
) -> str | BaseModel:
) -> str | list[dict[str, Any]] | BaseModel:
"""Handle streaming chat completion."""
full_response = ""
tool_calls: dict[int, dict[str, Any]] = {}
@@ -1820,54 +1912,20 @@ class OpenAICompletion(BaseLLM):
response_id=response_id_stream,
)
self._track_token_usage_internal(usage_data)
if tool_calls and available_functions:
for call_data in tool_calls.values():
function_name = call_data["name"]
arguments = call_data["arguments"]
# Skip if function name is empty or arguments are empty
if not function_name or not arguments:
continue
# Check if function exists in available functions
if function_name not in available_functions:
logging.warning(
f"Function '{function_name}' not found in available functions"
)
continue
try:
function_args = json.loads(arguments)
except json.JSONDecodeError as e:
logging.error(f"Failed to parse streamed tool arguments: {e}")
continue
result = self._handle_tool_execution(
function_name=function_name,
function_args=function_args,
available_functions=available_functions,
from_task=from_task,
from_agent=from_agent,
)
if result is not None:
return result
full_response = self._apply_stop_words(full_response)
self._emit_call_completed_event(
response=full_response,
call_type=LLMCallType.LLM_CALL,
result = self._finalize_streaming_response(
full_response=full_response,
tool_calls=tool_calls,
usage_data=usage_data,
params=params,
available_functions=available_functions,
from_task=from_task,
from_agent=from_agent,
messages=params["messages"],
)
return self._invoke_after_llm_call_hooks(
params["messages"], full_response, from_agent
)
if isinstance(result, str):
return self._invoke_after_llm_call_hooks(
params["messages"], result, from_agent
)
return result
async def _ahandle_completion(
self,
@@ -2016,7 +2074,7 @@ class OpenAICompletion(BaseLLM):
from_task: Any | None = None,
from_agent: Any | None = None,
response_model: type[BaseModel] | None = None,
) -> str | BaseModel:
) -> str | list[dict[str, Any]] | BaseModel:
"""Handle async streaming chat completion."""
full_response = ""
tool_calls: dict[int, dict[str, Any]] = {}
@@ -2142,51 +2200,16 @@ class OpenAICompletion(BaseLLM):
response_id=response_id_stream,
)
self._track_token_usage_internal(usage_data)
if tool_calls and available_functions:
for call_data in tool_calls.values():
function_name = call_data["name"]
arguments = call_data["arguments"]
if not function_name or not arguments:
continue
if function_name not in available_functions:
logging.warning(
f"Function '{function_name}' not found in available functions"
)
continue
try:
function_args = json.loads(arguments)
except json.JSONDecodeError as e:
logging.error(f"Failed to parse streamed tool arguments: {e}")
continue
result = self._handle_tool_execution(
function_name=function_name,
function_args=function_args,
available_functions=available_functions,
from_task=from_task,
from_agent=from_agent,
)
if result is not None:
return result
full_response = self._apply_stop_words(full_response)
self._emit_call_completed_event(
response=full_response,
call_type=LLMCallType.LLM_CALL,
return self._finalize_streaming_response(
full_response=full_response,
tool_calls=tool_calls,
usage_data=usage_data,
params=params,
available_functions=available_functions,
from_task=from_task,
from_agent=from_agent,
messages=params["messages"],
)
return full_response
def supports_function_calling(self) -> bool:
"""Check if the model supports function calling."""
return not self.is_o1_model
@@ -2240,11 +2263,18 @@ class OpenAICompletion(BaseLLM):
"""Extract token usage from OpenAI ChatCompletion or ChatCompletionChunk response."""
if hasattr(response, "usage") and response.usage:
usage = response.usage
return {
result = {
"prompt_tokens": getattr(usage, "prompt_tokens", 0),
"completion_tokens": getattr(usage, "completion_tokens", 0),
"total_tokens": getattr(usage, "total_tokens", 0),
}
# Extract cached prompt tokens from prompt_tokens_details
prompt_details = getattr(usage, "prompt_tokens_details", None)
if prompt_details:
result["cached_prompt_tokens"] = (
getattr(prompt_details, "cached_tokens", 0) or 0
)
return result
return {"total_tokens": 0}
def _format_messages(self, messages: str | list[LLMMessage]) -> list[LLMMessage]:

View File

@@ -27,6 +27,8 @@ if TYPE_CHECKING:
from crewai import Agent, Task
from crewai.agents.cache.cache_handler import CacheHandler
from crewai.crews.crew_output import CrewOutput
from crewai.hooks.llm_hooks import LLMCallHookContext
from crewai.hooks.tool_hooks import ToolCallHookContext
from crewai.project.wrappers import (
CrewInstance,
OutputJsonClass,
@@ -34,6 +36,8 @@ if TYPE_CHECKING:
)
from crewai.tasks.task_output import TaskOutput
_post_initialize_crew_hooks: list[Callable[[Any], None]] = []
class AgentConfig(TypedDict, total=False):
"""Type definition for agent configuration dictionary.
@@ -266,6 +270,9 @@ class CrewBaseMeta(type):
instance.map_all_agent_variables()
instance.map_all_task_variables()
for hook in _post_initialize_crew_hooks:
hook(instance)
original_methods = {
name: method
for name, method in cls.__dict__.items()
@@ -485,47 +492,61 @@ def _register_crew_hooks(instance: CrewInstance, cls: type) -> None:
if has_agent_filter:
agents_filter = hook_method._filter_agents
def make_filtered_before_llm(bound_fn, agents_list):
def filtered(context):
def make_filtered_before_llm(
bound_fn: Callable[[LLMCallHookContext], bool | None],
agents_list: list[str],
) -> Callable[[LLMCallHookContext], bool | None]:
def filtered(context: LLMCallHookContext) -> bool | None:
if context.agent and context.agent.role not in agents_list:
return None
return bound_fn(context)
return filtered
final_hook = make_filtered_before_llm(bound_hook, agents_filter)
before_llm_hook = make_filtered_before_llm(bound_hook, agents_filter)
else:
final_hook = bound_hook
before_llm_hook = bound_hook
register_before_llm_call_hook(final_hook)
instance._registered_hook_functions.append(("before_llm_call", final_hook))
register_before_llm_call_hook(before_llm_hook)
instance._registered_hook_functions.append(
("before_llm_call", before_llm_hook)
)
if hasattr(hook_method, "is_after_llm_call_hook"):
if has_agent_filter:
agents_filter = hook_method._filter_agents
def make_filtered_after_llm(bound_fn, agents_list):
def filtered(context):
def make_filtered_after_llm(
bound_fn: Callable[[LLMCallHookContext], str | None],
agents_list: list[str],
) -> Callable[[LLMCallHookContext], str | None]:
def filtered(context: LLMCallHookContext) -> str | None:
if context.agent and context.agent.role not in agents_list:
return None
return bound_fn(context)
return filtered
final_hook = make_filtered_after_llm(bound_hook, agents_filter)
after_llm_hook = make_filtered_after_llm(bound_hook, agents_filter)
else:
final_hook = bound_hook
after_llm_hook = bound_hook
register_after_llm_call_hook(final_hook)
instance._registered_hook_functions.append(("after_llm_call", final_hook))
register_after_llm_call_hook(after_llm_hook)
instance._registered_hook_functions.append(
("after_llm_call", after_llm_hook)
)
if hasattr(hook_method, "is_before_tool_call_hook"):
if has_tool_filter or has_agent_filter:
tools_filter = getattr(hook_method, "_filter_tools", None)
agents_filter = getattr(hook_method, "_filter_agents", None)
def make_filtered_before_tool(bound_fn, tools_list, agents_list):
def filtered(context):
def make_filtered_before_tool(
bound_fn: Callable[[ToolCallHookContext], bool | None],
tools_list: list[str] | None,
agents_list: list[str] | None,
) -> Callable[[ToolCallHookContext], bool | None]:
def filtered(context: ToolCallHookContext) -> bool | None:
if tools_list and context.tool_name not in tools_list:
return None
if (
@@ -538,22 +559,28 @@ def _register_crew_hooks(instance: CrewInstance, cls: type) -> None:
return filtered
final_hook = make_filtered_before_tool(
before_tool_hook = make_filtered_before_tool(
bound_hook, tools_filter, agents_filter
)
else:
final_hook = bound_hook
before_tool_hook = bound_hook
register_before_tool_call_hook(final_hook)
instance._registered_hook_functions.append(("before_tool_call", final_hook))
register_before_tool_call_hook(before_tool_hook)
instance._registered_hook_functions.append(
("before_tool_call", before_tool_hook)
)
if hasattr(hook_method, "is_after_tool_call_hook"):
if has_tool_filter or has_agent_filter:
tools_filter = getattr(hook_method, "_filter_tools", None)
agents_filter = getattr(hook_method, "_filter_agents", None)
def make_filtered_after_tool(bound_fn, tools_list, agents_list):
def filtered(context):
def make_filtered_after_tool(
bound_fn: Callable[[ToolCallHookContext], str | None],
tools_list: list[str] | None,
agents_list: list[str] | None,
) -> Callable[[ToolCallHookContext], str | None]:
def filtered(context: ToolCallHookContext) -> str | None:
if tools_list and context.tool_name not in tools_list:
return None
if (
@@ -566,14 +593,16 @@ def _register_crew_hooks(instance: CrewInstance, cls: type) -> None:
return filtered
final_hook = make_filtered_after_tool(
after_tool_hook = make_filtered_after_tool(
bound_hook, tools_filter, agents_filter
)
else:
final_hook = bound_hook
after_tool_hook = bound_hook
register_after_tool_call_hook(final_hook)
instance._registered_hook_functions.append(("after_tool_call", final_hook))
register_after_tool_call_hook(after_tool_hook)
instance._registered_hook_functions.append(
("after_tool_call", after_tool_hook)
)
instance._hooks_being_registered = False

View File

@@ -72,6 +72,8 @@ class CrewInstance(Protocol):
__crew_metadata__: CrewMetadata
_mcp_server_adapter: Any
_all_methods: dict[str, Callable[..., Any]]
_registered_hook_functions: list[tuple[str, Callable[..., Any]]]
_hooks_being_registered: bool
agents: list[Agent]
tasks: list[Task]
base_directory: Path

View File

@@ -31,6 +31,7 @@ from pydantic_core import PydanticCustomError
from typing_extensions import Self
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.context import reset_current_task_id, set_current_task_id
from crewai.core.providers.content_processor import process_content
from crewai.events.event_bus import crewai_event_bus
from crewai.events.types.task_events import (
@@ -561,6 +562,7 @@ class Task(BaseModel):
tools: list[Any] | None,
) -> TaskOutput:
"""Run the core execution logic of the task asynchronously."""
task_id_token = set_current_task_id(str(self.id))
self._store_input_files()
try:
agent = agent or self.agent
@@ -648,6 +650,7 @@ class Task(BaseModel):
raise e # Re-raise the exception after emitting the event
finally:
clear_task_files(self.id)
reset_current_task_id(task_id_token)
def _execute_core(
self,
@@ -656,6 +659,7 @@ class Task(BaseModel):
tools: list[Any] | None,
) -> TaskOutput:
"""Run the core execution logic of the task."""
task_id_token = set_current_task_id(str(self.id))
self._store_input_files()
try:
agent = agent or self.agent
@@ -744,6 +748,7 @@ class Task(BaseModel):
raise e # Re-raise the exception after emitting the event
finally:
clear_task_files(self.id)
reset_current_task_id(task_id_token)
def _post_agent_execution(self, agent: BaseAgent) -> None:
pass

View File

@@ -6,6 +6,7 @@ Classes:
HallucinationGuardrail: Placeholder guardrail that validates task outputs.
"""
from collections.abc import Callable
from typing import Any
from crewai.llm import LLM
@@ -13,32 +14,36 @@ from crewai.tasks.task_output import TaskOutput
from crewai.utilities.logger import Logger
_validate_output_hook: Callable[..., tuple[bool, Any]] | None = None
class HallucinationGuardrail:
"""Placeholder for the HallucinationGuardrail feature.
Attributes:
context: The reference context that outputs would be checked against.
context: Optional reference context that outputs would be checked against.
llm: The language model that would be used for evaluation.
threshold: Optional minimum faithfulness score that would be required to pass.
tool_response: Optional tool response information that would be used in evaluation.
Examples:
>>> # Basic usage with default verdict logic
>>> # Basic usage without context (uses task expected_output as context)
>>> guardrail = HallucinationGuardrail(llm=agent.llm)
>>> # With context for reference
>>> guardrail = HallucinationGuardrail(
... context="AI helps with various tasks including analysis and generation.",
... llm=agent.llm,
... context="AI helps with various tasks including analysis and generation.",
... )
>>> # With custom threshold for stricter validation
>>> strict_guardrail = HallucinationGuardrail(
... context="Quantum computing uses qubits in superposition.",
... llm=agent.llm,
... threshold=8.0, # Would require score >= 8 to pass in enterprise version
... threshold=8.0, # Require score >= 8 to pass
... )
>>> # With tool response for additional context
>>> guardrail_with_tools = HallucinationGuardrail(
... context="The current weather data",
... llm=agent.llm,
... tool_response="Weather API returned: Temperature 22°C, Humidity 65%",
... )
@@ -46,16 +51,17 @@ class HallucinationGuardrail:
def __init__(
self,
context: str,
llm: LLM,
context: str | None = None,
threshold: float | None = None,
tool_response: str = "",
):
"""Initialize the HallucinationGuardrail placeholder.
Args:
context: The reference context that outputs would be checked against.
llm: The language model that would be used for evaluation.
context: Optional reference context that outputs would be checked against.
If not provided, the task's expected_output will be used as context.
threshold: Optional minimum faithfulness score that would be required to pass.
tool_response: Optional tool response information that would be used in evaluation.
"""
@@ -78,16 +84,17 @@ class HallucinationGuardrail:
def __call__(self, task_output: TaskOutput) -> tuple[bool, Any]:
"""Validate a task output against hallucination criteria.
In the open source, this method always returns that the output is valid.
Args:
task_output: The output to be validated.
Returns:
A tuple containing:
- True
- The raw task output
- True if validation passed, False otherwise
- The raw task output if valid, or error feedback if invalid
"""
if callable(_validate_output_hook):
return _validate_output_hook(self, task_output)
self._logger.log(
"warning",
"Premium hallucination detection skipped (use for free at https://app.crewai.com)\n",

View File

@@ -1,6 +1,10 @@
import asyncio
from collections.abc import Coroutine
import inspect
from typing import Any
from pydantic import BaseModel, Field
from typing_extensions import TypeIs
from crewai.agent import Agent
from crewai.lite_agent_output import LiteAgentOutput
@@ -8,6 +12,13 @@ from crewai.llms.base_llm import BaseLLM
from crewai.tasks.task_output import TaskOutput
def _is_coroutine(
obj: LiteAgentOutput | Coroutine[Any, Any, LiteAgentOutput],
) -> TypeIs[Coroutine[Any, Any, LiteAgentOutput]]:
"""Check if obj is a coroutine for type narrowing."""
return inspect.iscoroutine(obj)
class LLMGuardrailResult(BaseModel):
valid: bool = Field(
description="Whether the task output complies with the guardrail"
@@ -62,7 +73,10 @@ class LLMGuardrail:
- If the Task result complies with the guardrail, saying that is valid
"""
return agent.kickoff(query, response_format=LLMGuardrailResult)
kickoff_result = agent.kickoff(query, response_format=LLMGuardrailResult)
if _is_coroutine(kickoff_result):
return asyncio.run(kickoff_result)
return kickoff_result
def __call__(self, task_output: TaskOutput) -> tuple[bool, Any]:
"""Validates the output of a task based on specified criteria.

View File

@@ -903,7 +903,7 @@ class Telemetry:
{
"id": str(task.id),
"description": task.description,
"output": task.output.raw_output,
"output": task.output.raw if task.output else "",
}
for task in crew.tasks
]
@@ -923,6 +923,9 @@ class Telemetry:
value: The attribute value.
"""
if span is None:
return
def _operation() -> None:
return span.set_attribute(key, value)

View File

@@ -270,6 +270,7 @@ class ToolUsage:
result = None # type: ignore
should_retry = False
available_tool = None
error_event_emitted = False
try:
if self.tools_handler and self.tools_handler.cache:
@@ -408,6 +409,7 @@ class ToolUsage:
except Exception as e:
self.on_tool_error(tool=tool, tool_calling=calling, e=e)
error_event_emitted = True
self._run_attempts += 1
if self._run_attempts > self._max_parsing_attempts:
self._telemetry.tool_usage_error(llm=self.function_calling_llm)
@@ -435,7 +437,7 @@ class ToolUsage:
result = self._format_result(result=result)
finally:
if started_event_emitted:
if started_event_emitted and not error_event_emitted:
self.on_tool_use_finished(
tool=tool,
tool_calling=calling,
@@ -500,6 +502,7 @@ class ToolUsage:
result = None # type: ignore
should_retry = False
available_tool = None
error_event_emitted = False
try:
if self.tools_handler and self.tools_handler.cache:
@@ -638,6 +641,7 @@ class ToolUsage:
except Exception as e:
self.on_tool_error(tool=tool, tool_calling=calling, e=e)
error_event_emitted = True
self._run_attempts += 1
if self._run_attempts > self._max_parsing_attempts:
self._telemetry.tool_usage_error(llm=self.function_calling_llm)
@@ -665,7 +669,7 @@ class ToolUsage:
result = self._format_result(result=result)
finally:
if started_event_emitted:
if started_event_emitted and not error_event_emitted:
self.on_tool_use_finished(
tool=tool,
tool_calling=calling,

View File

@@ -22,9 +22,9 @@
"expected_output": "\nThis is the expected criteria for your final answer: {expected_output}\nyou MUST return the actual complete content as the final answer, not a summary.",
"human_feedback": "You got human feedback on your work, re-evaluate it and give a new Final Answer when ready.\n {human_feedback}",
"getting_input": "This is the agent's final answer: {final_answer}\n\n",
"summarizer_system_message": "You are a helpful assistant that summarizes text.",
"summarize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
"summary": "This is a summary of our conversation so far:\n{merged_summary}",
"summarizer_system_message": "You are a precise assistant that creates structured summaries of agent conversations. You preserve critical context needed for seamless task continuation.",
"summarize_instruction": "Analyze the following conversation and create a structured summary that preserves all information needed to continue the task seamlessly.\n\n<conversation>\n{conversation}\n</conversation>\n\nCreate a summary with these sections:\n1. **Task Overview**: What is the agent trying to accomplish?\n2. **Current State**: What has been completed so far? What step is the agent on?\n3. **Important Discoveries**: Key facts, data, tool results, or findings that must not be lost.\n4. **Next Steps**: What should the agent do next based on the conversation?\n5. **Context to Preserve**: Any specific values, names, URLs, code snippets, or details referenced in the conversation.\n\nWrap your entire summary in <summary> tags.\n\n<summary>\n[Your structured summary here]\n</summary>",
"summary": "<summary>\n{merged_summary}\n</summary>\n\nContinue the task from where the conversation left off. The above is a structured summary of prior context.",
"manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
"formatted_task_instructions": "Format your final answer according to the following OpenAPI schema: {output_format}\n\nIMPORTANT: Preserve the original content exactly as-is. Do NOT rewrite, paraphrase, or modify the meaning of the content. Only structure it to match the schema format.\n\nDo not include the OpenAPI schema in the final output. Ensure the final output does not include any code block markers like ```json or ```python.",
"conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.",

View File

@@ -1,37 +0,0 @@
"""Human-in-the-loop (HITL) type definitions.
This module provides type definitions for human-in-the-loop interactions
in crew executions.
"""
from typing import TypedDict
class HITLResumeInfo(TypedDict, total=False):
"""HITL resume information passed from flow to crew.
Attributes:
task_id: Unique identifier for the task.
crew_execution_id: Unique identifier for the crew execution.
task_key: Key identifying the specific task.
task_output: Output from the task before human intervention.
human_feedback: Feedback provided by the human.
previous_messages: History of messages in the conversation.
"""
task_id: str
crew_execution_id: str
task_key: str
task_output: str
human_feedback: str
previous_messages: list[dict[str, str]]
class CrewInputsWithHITL(TypedDict, total=False):
"""Crew inputs that may contain HITL resume information.
Attributes:
_hitl_resume: Optional HITL resume information for continuing execution.
"""
_hitl_resume: HITLResumeInfo

View File

@@ -2,6 +2,7 @@ from __future__ import annotations
import asyncio
from collections.abc import Callable, Sequence
import concurrent.futures
import json
import re
from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict
@@ -42,6 +43,8 @@ if TYPE_CHECKING:
from crewai.llm import LLM
from crewai.task import Task
_create_plus_client_hook: Callable[[], Any] | None = None
class SummaryContent(TypedDict):
"""Structure for summary content entries.
@@ -91,7 +94,11 @@ def parse_tools(tools: list[BaseTool]) -> list[CrewStructuredTool]:
for tool in tools:
if isinstance(tool, CrewAITool):
tools_list.append(tool.to_structured_tool())
structured_tool = tool.to_structured_tool()
structured_tool.current_usage_count = 0
if structured_tool._original_tool:
structured_tool._original_tool.current_usage_count = 0
tools_list.append(structured_tool)
else:
raise ValueError("Tool is not a CrewStructuredTool or BaseTool")
@@ -634,6 +641,180 @@ def handle_context_length(
)
def _estimate_token_count(text: str) -> int:
"""Estimate token count using a conservative cross-provider heuristic.
Args:
text: The text to estimate tokens for.
Returns:
Estimated token count (roughly 1 token per 4 characters).
"""
return len(text) // 4
def _format_messages_for_summary(messages: list[LLMMessage]) -> str:
"""Format messages with role labels for summarization.
Skips system messages. Handles None content, tool_calls, and
multimodal content blocks.
Args:
messages: List of messages to format.
Returns:
Role-labeled conversation text.
"""
lines: list[str] = []
for msg in messages:
role = msg.get("role", "user")
if role == "system":
continue
content = msg.get("content")
if content is None:
# Check for tool_calls on assistant messages with no content
tool_calls = msg.get("tool_calls")
if tool_calls:
tool_names = []
for tc in tool_calls:
func = tc.get("function", {})
name = (
func.get("name", "unknown")
if isinstance(func, dict)
else "unknown"
)
tool_names.append(name)
content = f"[Called tools: {', '.join(tool_names)}]"
else:
content = ""
elif isinstance(content, list):
# Multimodal content blocks — extract text parts
text_parts = [
block.get("text", "")
for block in content
if isinstance(block, dict) and block.get("type") == "text"
]
content = " ".join(text_parts) if text_parts else "[multimodal content]"
if role == "assistant":
label = "[ASSISTANT]:"
elif role == "tool":
tool_name = msg.get("name", "unknown")
label = f"[TOOL_RESULT ({tool_name})]:"
else:
label = "[USER]:"
lines.append(f"{label} {content}")
return "\n\n".join(lines)
def _split_messages_into_chunks(
messages: list[LLMMessage], max_tokens: int
) -> list[list[LLMMessage]]:
"""Split messages into chunks at message boundaries.
Excludes system messages from chunks. Each chunk stays under
max_tokens based on estimated token count.
Args:
messages: List of messages to split.
max_tokens: Maximum estimated tokens per chunk.
Returns:
List of message chunks.
"""
non_system = [m for m in messages if m.get("role") != "system"]
if not non_system:
return []
chunks: list[list[LLMMessage]] = []
current_chunk: list[LLMMessage] = []
current_tokens = 0
for msg in non_system:
content = msg.get("content")
if content is None:
msg_text = ""
elif isinstance(content, list):
msg_text = str(content)
else:
msg_text = str(content)
msg_tokens = _estimate_token_count(msg_text)
# If adding this message would exceed the limit and we already have
# messages in the current chunk, start a new chunk
if current_chunk and (current_tokens + msg_tokens) > max_tokens:
chunks.append(current_chunk)
current_chunk = []
current_tokens = 0
current_chunk.append(msg)
current_tokens += msg_tokens
if current_chunk:
chunks.append(current_chunk)
return chunks
def _extract_summary_tags(text: str) -> str:
"""Extract content between <summary></summary> tags.
Falls back to the full text if no tags are found.
Args:
text: Text potentially containing summary tags.
Returns:
Extracted summary content, or full text if no tags found.
"""
match = re.search(r"<summary>(.*?)</summary>", text, re.DOTALL)
if match:
return match.group(1).strip()
return text.strip()
async def _asummarize_chunks(
chunks: list[list[LLMMessage]],
llm: LLM | BaseLLM,
callbacks: list[TokenCalcHandler],
i18n: I18N,
) -> list[SummaryContent]:
"""Summarize multiple message chunks concurrently using asyncio.
Args:
chunks: List of message chunks to summarize.
llm: LLM instance (must support ``acall``).
callbacks: List of callbacks for the LLM.
i18n: I18N instance for prompt templates.
Returns:
Ordered list of summary contents, one per chunk.
"""
async def _summarize_one(chunk: list[LLMMessage]) -> SummaryContent:
conversation_text = _format_messages_for_summary(chunk)
summarization_messages = [
format_message_for_llm(
i18n.slice("summarizer_system_message"), role="system"
),
format_message_for_llm(
i18n.slice("summarize_instruction").format(
conversation=conversation_text
),
),
]
summary = await llm.acall(summarization_messages, callbacks=callbacks)
extracted = _extract_summary_tags(str(summary))
return {"content": extracted}
results = await asyncio.gather(*[_summarize_one(chunk) for chunk in chunks])
return list(results)
def summarize_messages(
messages: list[LLMMessage],
llm: LLM | BaseLLM,
@@ -643,6 +824,10 @@ def summarize_messages(
) -> None:
"""Summarize messages to fit within context window.
Uses structured context compaction: preserves system messages,
splits at message boundaries, formats with role labels, and
produces structured summaries for seamless task continuation.
Preserves any files attached to user messages and re-attaches them to
the summarized message. Files from all user messages are merged.
@@ -651,49 +836,74 @@ def summarize_messages(
llm: LLM instance for summarization
callbacks: List of callbacks for LLM
i18n: I18N instance for messages
verbose: Whether to print progress.
"""
# 1. Extract & preserve file attachments from user messages
preserved_files: dict[str, Any] = {}
for msg in messages:
if msg.get("role") == "user" and msg.get("files"):
preserved_files.update(msg["files"])
messages_string = " ".join(
[str(message.get("content", "")) for message in messages]
)
cut_size = llm.get_context_window_size()
# 2. Extract system messages — never summarize them
system_messages = [m for m in messages if m.get("role") == "system"]
non_system_messages = [m for m in messages if m.get("role") != "system"]
messages_groups = [
{"content": messages_string[i : i + cut_size]}
for i in range(0, len(messages_string), cut_size)
]
# If there are only system messages (or no non-system messages), nothing to summarize
if not non_system_messages:
return
summarized_contents: list[SummaryContent] = []
# 3. Split non-system messages into chunks at message boundaries
max_tokens = llm.get_context_window_size()
chunks = _split_messages_into_chunks(non_system_messages, max_tokens)
total_groups = len(messages_groups)
for idx, group in enumerate(messages_groups, 1):
# 4. Summarize each chunk with role-labeled formatting
total_chunks = len(chunks)
if total_chunks <= 1:
# Single chunk — no benefit from async overhead
summarized_contents: list[SummaryContent] = []
for idx, chunk in enumerate(chunks, 1):
if verbose:
Printer().print(
content=f"Summarizing {idx}/{total_chunks}...",
color="yellow",
)
conversation_text = _format_messages_for_summary(chunk)
summarization_messages = [
format_message_for_llm(
i18n.slice("summarizer_system_message"), role="system"
),
format_message_for_llm(
i18n.slice("summarize_instruction").format(
conversation=conversation_text
),
),
]
summary = llm.call(summarization_messages, callbacks=callbacks)
extracted = _extract_summary_tags(str(summary))
summarized_contents.append({"content": extracted})
else:
# Multiple chunks — summarize in parallel via asyncio
if verbose:
Printer().print(
content=f"Summarizing {idx}/{total_groups}...",
content=f"Summarizing {total_chunks} chunks in parallel...",
color="yellow",
)
summarization_messages = [
format_message_for_llm(
i18n.slice("summarizer_system_message"), role="system"
),
format_message_for_llm(
i18n.slice("summarize_instruction").format(group=group["content"]),
),
]
summary = llm.call(
summarization_messages,
callbacks=callbacks,
coro = _asummarize_chunks(
chunks=chunks, llm=llm, callbacks=callbacks, i18n=i18n
)
summarized_contents.append({"content": str(summary)})
if is_inside_event_loop():
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
summarized_contents = pool.submit(asyncio.run, coro).result()
else:
summarized_contents = asyncio.run(coro)
merged_summary = " ".join(content["content"] for content in summarized_contents)
merged_summary = "\n\n".join(content["content"] for content in summarized_contents)
# 6. Reconstruct messages: [system messages...] + [summary user message]
messages.clear()
messages.extend(system_messages)
summary_message = format_message_for_llm(
i18n.slice("summary").format(merged_summary=merged_summary)
)
@@ -818,12 +1028,15 @@ def load_agent_from_repository(from_repository: str) -> dict[str, Any]:
if from_repository:
import importlib
from crewai.cli.authentication.token import get_auth_token
from crewai.cli.plus_api import PlusAPI
if callable(_create_plus_client_hook):
client = _create_plus_client_hook()
else:
from crewai.cli.authentication.token import get_auth_token
from crewai.cli.plus_api import PlusAPI
client = PlusAPI(api_key=get_auth_token())
client = PlusAPI(api_key=get_auth_token())
_print_current_organization()
response = client.get_agent(from_repository)
response = asyncio.run(client.get_agent(from_repository))
if response.status_code == 404:
raise AgentRepositoryError(
f"Agent {from_repository} does not exist, make sure the name is correct or the agent is available on your organization."

View File

@@ -1,7 +1,7 @@
from __future__ import annotations
from collections import defaultdict
from typing import TYPE_CHECKING
from typing import TYPE_CHECKING, Any
from pydantic import BaseModel, Field, InstanceOf
from rich.box import HEAVY_EDGE
@@ -36,7 +36,13 @@ class CrewEvaluator:
iteration: The current iteration of the evaluation.
"""
def __init__(self, crew: Crew, eval_llm: InstanceOf[BaseLLM]) -> None:
def __init__(
self,
crew: Crew,
eval_llm: InstanceOf[BaseLLM] | str | None = None,
openai_model_name: str | None = None,
llm: InstanceOf[BaseLLM] | str | None = None,
) -> None:
self.crew = crew
self.llm = eval_llm
self.tasks_scores: defaultdict[int, list[float]] = defaultdict(list)
@@ -86,7 +92,9 @@ class CrewEvaluator:
"""
self.iteration = iteration
def print_crew_evaluation_result(self) -> None:
def print_crew_evaluation_result(
self, token_usage: list[dict[str, Any]] | None = None
) -> None:
"""
Prints the evaluation result of the crew in a table.
A Crew with 2 tasks using the command crewai test -n 3
@@ -204,7 +212,7 @@ class CrewEvaluator:
CrewTestResultEvent(
quality=quality_score,
execution_duration=current_task.execution_duration,
model=self.llm.model,
model=getattr(self.llm, "model", str(self.llm)),
crew_name=self.crew.name,
crew=self.crew,
),

View File

@@ -4,6 +4,8 @@ from __future__ import annotations
from typing import TYPE_CHECKING, Final, Literal, NamedTuple
from crewai.events.utils.console_formatter import should_suppress_console_output
if TYPE_CHECKING:
from _typeshed import SupportsWrite
@@ -77,6 +79,8 @@ class Printer:
file: A file-like object (stream); defaults to the current sys.stdout.
flush: Whether to forcibly flush the stream.
"""
if should_suppress_console_output():
return
if isinstance(content, str):
content = [ColoredText(content, color)]
print(

View File

@@ -19,6 +19,7 @@ def to_serializable(
exclude: set[str] | None = None,
max_depth: int = 5,
_current_depth: int = 0,
_ancestors: set[int] | None = None,
) -> Serializable:
"""Converts a Python object into a JSON-compatible representation.
@@ -31,6 +32,7 @@ def to_serializable(
exclude: Set of keys to exclude from the result.
max_depth: Maximum recursion depth. Defaults to 5.
_current_depth: Current recursion depth (for internal use).
_ancestors: Set of ancestor object ids for cycle detection (for internal use).
Returns:
Serializable: A JSON-compatible structure.
@@ -41,16 +43,29 @@ def to_serializable(
if exclude is None:
exclude = set()
if _ancestors is None:
_ancestors = set()
if isinstance(obj, (str, int, float, bool, type(None))):
return obj
if isinstance(obj, uuid.UUID):
return str(obj)
if isinstance(obj, (date, datetime)):
return obj.isoformat()
object_id = id(obj)
if object_id in _ancestors:
return f"<circular_ref:{type(obj).__name__}>"
new_ancestors = _ancestors | {object_id}
if isinstance(obj, (list, tuple, set)):
return [
to_serializable(
item, max_depth=max_depth, _current_depth=_current_depth + 1
item,
exclude=exclude,
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
)
for item in obj
]
@@ -61,6 +76,7 @@ def to_serializable(
exclude=exclude,
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
)
for key, value in obj.items()
if key not in exclude
@@ -71,12 +87,16 @@ def to_serializable(
obj=obj.model_dump(exclude=exclude),
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
)
except Exception:
try:
return {
_to_serializable_key(k): to_serializable(
v, max_depth=max_depth, _current_depth=_current_depth + 1
v,
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
)
for k, v in obj.__dict__.items()
if k not in (exclude or set())

View File

@@ -51,6 +51,10 @@ class ConcreteAgentAdapter(BaseAgentAdapter):
# Dummy implementation for MCP tools
return []
def configure_structured_output(self, task: Any) -> None:
# Dummy implementation for structured output
pass
async def aexecute_task(
self,
task: Any,

View File

@@ -606,9 +606,10 @@ def test_lite_agent_with_invalid_llm():
@patch.dict("os.environ", {"CREWAI_PLATFORM_INTEGRATION_TOKEN": "test_token"})
@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_action_tool.requests.post")
@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_tool_builder.requests.get")
@pytest.mark.vcr()
def test_agent_kickoff_with_platform_tools(mock_get):
def test_agent_kickoff_with_platform_tools(mock_get, mock_post):
"""Test that Agent.kickoff() properly integrates platform tools with LiteAgent"""
mock_response = Mock()
mock_response.raise_for_status.return_value = None
@@ -632,6 +633,15 @@ def test_agent_kickoff_with_platform_tools(mock_get):
}
mock_get.return_value = mock_response
# Mock the platform tool execution
mock_post_response = Mock()
mock_post_response.ok = True
mock_post_response.json.return_value = {
"success": True,
"issue_url": "https://github.com/test/repo/issues/1"
}
mock_post.return_value = mock_post_response
agent = Agent(
role="Test Agent",
goal="Test goal",

View File

@@ -1,98 +1,227 @@
interactions:
- request:
body: '{"messages": [{"role": "system", "content": "You are Test Agent. Test backstory\nYour personal goal is: Test goal\n\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\nTool Name: create_issue\nTool Arguments: {''title'': {''description'': ''Issue title'', ''type'': ''str''}, ''body'': {''description'': ''Issue body'', ''type'': ''Union[str, NoneType]''}}\nTool Description: Create a GitHub issue\nDetailed Parameter Structure:\nObject with properties:\n - title: Issue title (required)\n - body: Issue body (optional)\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: you should always think about what to do\nAction: the action to take, only one name of [create_issue], just the name, exactly as it''s written.\nAction Input: the input to the action, just a simple JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce all necessary information
is gathered, return the following format:\n\n```\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n```"}, {"role": "user", "content": "Create a GitHub issue"}], "model": "gpt-3.5-turbo", "stream": false}'
body: '{"messages":[{"role":"system","content":"You are Test Agent. Test backstory\nYour
personal goal is: Test goal"},{"role":"user","content":"\nCurrent Task: Create
a GitHub issue"}],"model":"gpt-3.5-turbo","tool_choice":"auto","tools":[{"type":"function","function":{"name":"create_issue","description":"Create
a GitHub issue","strict":true,"parameters":{"additionalProperties":false,"properties":{"title":{"description":"Issue
title","title":"Title","type":"string"},"body":{"default":null,"description":"Issue
body","title":"Body","type":"string"}},"required":["title","body"],"type":"object"}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- gzip, deflate
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '1233'
- '596'
content-type:
- application/json
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.109.1
x-stainless-arch:
- arm64
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.109.1
- 1.83.0
x-stainless-read-timeout:
- '600'
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-CULxKTEIB85AVItcEQ09z4Xi0JCID\",\n \"object\": \"chat.completion\",\n \"created\": 1761350274,\n \"model\": \"gpt-3.5-turbo-0125\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"I will need more specific information to create a GitHub issue. Could you please provide more details such as the title and body of the issue you would like to create?\",\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 255,\n \"completion_tokens\": 33,\n \"total_tokens\": 288,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n \
\ }\n },\n \"service_tier\": \"default\",\n \"system_fingerprint\": null\n}\n"
string: "{\n \"id\": \"chatcmpl-D6L3fqygkUIZ3bN4wvSpAhdaSk7MF\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403287,\n \"model\": \"gpt-3.5-turbo-0125\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n
\ \"id\": \"call_RuWuYzjzgRL3byVGhLlPi0rq\",\n \"type\":
\"function\",\n \"function\": {\n \"name\": \"create_issue\",\n
\ \"arguments\": \"{\\\"title\\\":\\\"Test issue\\\",\\\"body\\\":\\\"This
is a test issue created for testing purposes.\\\"}\"\n }\n }\n
\ ],\n \"refusal\": null,\n \"annotations\": []\n },\n
\ \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n }\n
\ ],\n \"usage\": {\n \"prompt_tokens\": 93,\n \"completion_tokens\":
28,\n \"total_tokens\": 121,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": null\n}\n"
headers:
CF-RAY:
- 993d6b4be9862379-SJC
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Fri, 24 Oct 2025 23:57:54 GMT
- Fri, 06 Feb 2026 18:41:28 GMT
Server:
- cloudflare
Set-Cookie:
- __cf_bm=WY9bgemMDI_hUYISAPlQ2a.DBGeZfM6AjVEa3SKNg1c-1761350274-1.0.1.1-K3Qm2cl6IlDAgmocoKZ8IMUTmue6Q81hH9stECprUq_SM8LF8rR9d1sHktvRCN3.jEM.twEuFFYDNpBnN8NBRJFZcea1yvpm8Uo0G_UhyDs; path=/; expires=Sat, 25-Oct-25 00:27:54 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
- _cfuvid=JklLS4i3hBGELpS9cz1KMpTbj72hCwP41LyXDSxWIv8-1761350274521-0.0.1.1-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
- SET-COOKIE-XXX
Strict-Transport-Security:
- max-age=31536000; includeSubDomains; preload
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- X-Request-ID
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- crewai-iuxna1
- OPENAI-ORG-XXX
openai-processing-ms:
- '487'
- '1406'
openai-project:
- proj_xitITlrFeen7zjNSzML82h9x
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '526'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- '10000'
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- '50000000'
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- '9999'
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- '49999727'
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- 6ms
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- 0s
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- req_1708dc0928c64882aaa5bc2c168c140f
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages":[{"role":"system","content":"You are Test Agent. Test backstory\nYour
personal goal is: Test goal"},{"role":"user","content":"\nCurrent Task: Create
a GitHub issue"},{"role":"assistant","content":null,"tool_calls":[{"id":"call_RuWuYzjzgRL3byVGhLlPi0rq","type":"function","function":{"name":"create_issue","arguments":"{\"title\":\"Test
issue\",\"body\":\"This is a test issue created for testing purposes.\"}"}}]},{"role":"tool","tool_call_id":"call_RuWuYzjzgRL3byVGhLlPi0rq","name":"create_issue","content":"{\n \"success\":
true,\n \"issue_url\": \"https://github.com/test/repo/issues/1\"\n}"}],"model":"gpt-3.5-turbo","tool_choice":"auto","tools":[{"type":"function","function":{"name":"create_issue","description":"Create
a GitHub issue","strict":true,"parameters":{"additionalProperties":false,"properties":{"title":{"description":"Issue
title","title":"Title","type":"string"},"body":{"default":null,"description":"Issue
body","title":"Body","type":"string"}},"required":["title","body"],"type":"object"}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '1028'
content-type:
- application/json
cookie:
- COOKIE-XXX
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D6L3hfuBxk36LIb3ekD1IVwFD5VVL\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403289,\n \"model\": \"gpt-3.5-turbo-0125\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"I have successfully created a GitHub
issue for testing purposes. You can view the issue at this URL: [Test issue](https://github.com/test/repo/issues/1)\",\n
\ \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\":
null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\":
154,\n \"completion_tokens\": 36,\n \"total_tokens\": 190,\n \"prompt_tokens_details\":
{\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": null\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Fri, 06 Feb 2026 18:41:29 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '888'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK

View File

@@ -1,400 +1,428 @@
interactions:
- request:
body: '{"messages": [{"role": "system", "content": "You are Sports Analyst. You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.\nYour personal goal is: Gather information about the best soccer players\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!"}, {"role": "user", "content": "Top 10 best players in the world?"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
body: '{"messages":[{"role":"system","content":"You are Sports Analyst. You are
an expert at gathering and organizing information. You carefully collect details
and present them in a structured way.\nYour personal goal is: Gather information
about the best soccer players"},{"role":"user","content":"\nCurrent Task: Top
10 best players in the world?\n\nProvide your complete response:"}],"model":"gpt-4.1-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '694'
- '404'
content-type:
- application/json
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.78.0
x-stainless-arch:
- arm64
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.78.0
x-stainless-raw-response:
- 'true'
- 1.83.0
x-stainless-read-timeout:
- '600.0'
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-BgufUtDqGzvqPZx2NmkqqxdW4G8rQ\",\n \"object\": \"chat.completion\",\n \"created\": 1749567308,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"Thought: I now can give a great answer \\nFinal Answer: The top 10 best soccer players in the world, as of October 2023, can be identified based on their recent performances, skills, impact on games, and overall contributions to their teams. Here is the structured list:\\n\\n1. **Lionel Messi (Inter Miami CF)**\\n - Position: Forward\\n - Key Attributes: Dribbling, vision, goal-scoring ability.\\n - Achievements: Multiple Ballon d'Or winner, Copa America champion, World Cup champion (2022).\\n\\n2. **Kylian Mbappé (Paris Saint-Germain)**\\n - Position: Forward\\n - Key Attributes: Speed, technique, finishing.\\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple\
\ domestic cups.\\n\\n3. **Erling Haaland (Manchester City)**\\n - Position: Forward\\n - Key Attributes: Power, speed, goal-scoring instinct.\\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\\n\\n4. **Kevin De Bruyne (Manchester City)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, creativity.\\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\\n\\n5. **Karim Benzema (Al-Ittihad)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\\n - Achievements: 2022 Ballon d'Or winner, multiple Champions Leagues with Real Madrid.\\n\\n6. **Neymar Jr. (Al Hilal)**\\n - Position: Forward\\n - Key Attributes: Flair, dribbling, creativity.\\n - Achievements: Multiple domestic league titles, Champions League runner-up.\\n\\n7. **Robert Lewandowski (FC Barcelona)**\\n - Position: Forward\\n - Key Attributes: Finishing,\
\ positioning, aerial ability.\\n - Achievements: FIFA Best Men's Player, multiple Bundesliga titles, La Liga champion (2023).\\n\\n8. **Mohamed Salah (Liverpool)**\\n - Position: Forward\\n - Key Attributes: Speed, finishing, dribbling.\\n - Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\\n\\n9. **Vinícius Júnior (Real Madrid)**\\n - Position: Forward\\n - Key Attributes: Speed, dribbling, creativity.\\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\\n\\n10. **Luka Modrić (Real Madrid)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, tactical intelligence.\\n - Achievements: Multiple Champions League titles, Ballon d'Or winner (2018).\\n\\nThis list is compiled based on their current form, past performances, and contributions to their respective teams in both domestic and international competitions. Player rankings can vary based on personal opinion and specific criteria used for\
\ evaluation, but these players have consistently been regarded as some of the best in the world as of October 2023.\",\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 122,\n \"completion_tokens\": 643,\n \"total_tokens\": 765,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\",\n \"system_fingerprint\": \"fp_34a54ae93c\"\n}\n"
string: "{\n \"id\": \"chatcmpl-D6L3hzoRVVEa07HZsM9wpi2RVRKQp\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403289,\n \"model\": \"gpt-4.1-mini-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"Here is a structured list of the top
10 best soccer players in the world as of 2024, based on recent performances,
awards, and overall impact on the game:\\n\\n1. **Kylian Mbapp\xE9** \\n
\ - Nationality: French \\n - Club: Paris Saint-Germain (PSG) \\n -
Position: Forward \\n - Key Highlights: Multiple Ligue 1 titles, World
Cup winner (2018), known for speed, dribbling, and scoring prowess.\\n\\n2.
**Erling Haaland** \\n - Nationality: Norwegian \\n - Club: Manchester
City \\n - Position: Striker \\n - Key Highlights: Premier League Golden
Boot winner, incredible goal-scoring record, physical presence, and finishing
skills.\\n\\n3. **Lionel Messi** \\n - Nationality: Argentine \\n -
Club: Inter Miami \\n - Position: Forward/Attacking Midfielder \\n -
Key Highlights: Seven Ballon d\u2019Or awards, World Cup winner (2022), exceptional
playmaking and dribbling ability.\\n\\n4. **Kevin De Bruyne** \\n - Nationality:
Belgian \\n - Club: Manchester City \\n - Position: Midfielder \\n
\ - Key Highlights: One of the best playmakers globally, assists leader,
consistent high-level performance in the Premier League.\\n\\n5. **Robert
Lewandowski** \\n - Nationality: Polish \\n - Club: FC Barcelona \\n
\ - Position: Striker \\n - Key Highlights: Exceptional goal-scoring record,
multiple Bundesliga top scorer awards, key figure in Bayern Munich\u2019s
dominance before transferring.\\n\\n6. **Karim Benzema** \\n - Nationality:
French \\n - Club: Al-Ittihad \\n - Position: Striker \\n - Key Highlights:
Ballon d\u2019Or winner (2022), excellent technical skills, leadership at
Real Madrid before recent transfer.\\n\\n7. **Mohamed Salah** \\n - Nationality:
Egyptian \\n - Club: Liverpool \\n - Position: Forward \\n - Key
Highlights: Premier League Golden Boot winner, known for speed, dribbling,
and goal-scoring consistency.\\n\\n8. **Vin\xEDcius J\xFAnior** \\n - Nationality:
Brazilian \\n - Club: Real Madrid \\n - Position: Winger \\n - Key
Highlights: Key player for Real Madrid, exceptional dribbling and pace, rising
star in world football.\\n\\n9. **Jude Bellingham** \\n - Nationality:
English \\n - Club: Real Madrid \\n - Position: Midfielder \\n -
Key Highlights: Young talent with maturity beyond years, influential midfielder
with great vision and work rate.\\n\\n10. **Thibaut Courtois** \\n - Nationality:
Belgian \\n - Club: Real Madrid \\n - Position: Goalkeeper \\n -
Key Highlights: One of the best goalkeepers globally, crucial performances
in La Liga and Champions League.\\n\\nThese rankings consider individual talent,
recent achievements, influence on matches, and overall contribution to club
and country.\",\n \"refusal\": null,\n \"annotations\": []\n
\ },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n
\ ],\n \"usage\": {\n \"prompt_tokens\": 68,\n \"completion_tokens\":
621,\n \"total_tokens\": 689,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_75546bd1a7\"\n}\n"
headers:
CF-RAY:
- 94d9b5400dcd624b-GRU
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Jun 2025 14:55:42 GMT
- Fri, 06 Feb 2026 18:41:40 GMT
Server:
- cloudflare
Set-Cookie:
- __cf_bm=8Yv8F0ZCFAo2lf.qoqxao70yxyjVvIV90zQqVF6bVzQ-1749567342-1.0.1.1-fZgnv3RDfunvCO1koxwwFJrHnxSx_rwS_FHvQ6xxDPpKHwYr7dTqIQLZrNgSX5twGyK4F22rUmkuiS6KMVogcinChk8lmHtJBTUVTFjr2KU; path=/; expires=Tue, 10-Jun-25 15:25:42 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
- _cfuvid=wzh8YnmXvLq1G0RcIVijtzboQtCZyIe2uZiochkBLqE-1749567342267-0.0.1.1-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
- SET-COOKIE-XXX
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- X-Request-ID
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- crewai-iuxna1
- OPENAI-ORG-XXX
openai-processing-ms:
- '33288'
- '10634'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
x-envoy-upstream-service-time:
- '33292'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- '30000'
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- '150000000'
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- '29999'
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- '149999859'
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- 2ms
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- 0s
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- req_6a587ea22edef774ecdada790a320cab
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages": [{"role": "system", "content": "You are Sports Analyst. You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.\nYour personal goal is: Gather information about the best soccer players\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!"}, {"role": "user", "content": "Top 10 best players in the world?"}, {"role": "assistant", "content": "Thought: I now can give a great answer \nFinal Answer: The top 10 best soccer players in the world, as of October 2023, can be identified based on their recent performances, skills, impact on games, and overall contributions to their teams. Here is the structured list:\n\n1. **Lionel Messi (Inter Miami CF)**\n -
Position: Forward\n - Key Attributes: Dribbling, vision, goal-scoring ability.\n - Achievements: Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2. **Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n - Position: Forward\n - Key Attributes: Speed, technique, finishing.\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple domestic cups.\n\n3. **Erling Haaland (Manchester City)**\n - Position: Forward\n - Key Attributes: Power, speed, goal-scoring instinct.\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, creativity.\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n - Position: Forward\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n - Achievements:
2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6. **Neymar Jr. (Al Hilal)**\n - Position: Forward\n - Key Attributes: Flair, dribbling, creativity.\n - Achievements: Multiple domestic league titles, Champions League runner-up.\n\n7. **Robert Lewandowski (FC Barcelona)**\n - Position: Forward\n - Key Attributes: Finishing, positioning, aerial ability.\n - Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion (2023).\n\n8. **Mohamed Salah (Liverpool)**\n - Position: Forward\n - Key Attributes: Speed, finishing, dribbling.\n - Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\n\n9. **Vin\u00edcius J\u00fanior (Real Madrid)**\n - Position: Forward\n - Key Attributes: Speed, dribbling, creativity.\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\n\n10. **Luka Modri\u0107 (Real Madrid)**\n - Position: Midfielder\n - Key Attributes: Passing, vision,
tactical intelligence.\n - Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\nThis list is compiled based on their current form, past performances, and contributions to their respective teams in both domestic and international competitions. Player rankings can vary based on personal opinion and specific criteria used for evaluation, but these players have consistently been regarded as some of the best in the world as of October 2023."}, {"role": "user", "content": "You are not allowed to include Brazilian players"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
body: '{"messages":[{"role":"system","content":"You are Sports Analyst. You are
an expert at gathering and organizing information. You carefully collect details
and present them in a structured way.\nYour personal goal is: Gather information
about the best soccer players"},{"role":"user","content":"\nCurrent Task: Top
10 best players in the world?\n\nProvide your complete response:"}],"model":"gpt-4.1-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '3594'
- '404'
content-type:
- application/json
cookie:
- __cf_bm=8Yv8F0ZCFAo2lf.qoqxao70yxyjVvIV90zQqVF6bVzQ-1749567342-1.0.1.1-fZgnv3RDfunvCO1koxwwFJrHnxSx_rwS_FHvQ6xxDPpKHwYr7dTqIQLZrNgSX5twGyK4F22rUmkuiS6KMVogcinChk8lmHtJBTUVTFjr2KU; _cfuvid=wzh8YnmXvLq1G0RcIVijtzboQtCZyIe2uZiochkBLqE-1749567342267-0.0.1.1-604800000
- COOKIE-XXX
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.78.0
x-stainless-arch:
- arm64
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.78.0
x-stainless-raw-response:
- 'true'
- 1.83.0
x-stainless-read-timeout:
- '600.0'
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-BgugJkCDtB2EfvAMiIFK0reeLKFBl\",\n \"object\": \"chat.completion\",\n \"created\": 1749567359,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"Thought: I now can give a great answer \\nFinal Answer: Here is an updated list of the top 10 best soccer players in the world as of October 2023, excluding Brazilian players:\\n\\n1. **Lionel Messi (Inter Miami CF)**\\n - Position: Forward\\n - Key Attributes: Dribbling, vision, goal-scoring ability.\\n - Achievements: Multiple Ballon d'Or winner, Copa America champion, World Cup champion (2022).\\n\\n2. **Kylian Mbappé (Paris Saint-Germain)**\\n - Position: Forward\\n - Key Attributes: Speed, technique, finishing.\\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple domestic cups.\\n\\n3. **Erling Haaland (Manchester City)**\\n - Position: Forward\\\
n - Key Attributes: Power, speed, goal-scoring instinct.\\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\\n\\n4. **Kevin De Bruyne (Manchester City)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, creativity.\\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\\n\\n5. **Karim Benzema (Al-Ittihad)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\\n - Achievements: 2022 Ballon d'Or winner, multiple Champions Leagues with Real Madrid.\\n\\n6. **Robert Lewandowski (FC Barcelona)**\\n - Position: Forward\\n - Key Attributes: Finishing, positioning, aerial ability.\\n - Achievements: FIFA Best Men's Player, multiple Bundesliga titles, La Liga champion (2023).\\n\\n7. **Mohamed Salah (Liverpool)**\\n - Position: Forward\\n - Key Attributes: Speed, finishing, dribbling.\\n - Achievements: Premier League\
\ champion, FA Cup, UEFA Champions League winner.\\n\\n8. **Vinícius Júnior (Real Madrid)**\\n - Position: Forward\\n - Key Attributes: Speed, dribbling, creativity.\\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\\n\\n9. **Luka Modrić (Real Madrid)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, tactical intelligence.\\n - Achievements: Multiple Champions League titles, Ballon d'Or winner (2018).\\n\\n10. **Harry Kane (Bayern Munich)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, technique, playmaking.\\n - Achievements: Golden Boot winner, Premier League titles, UEFA European Championship runner-up.\\n\\nThis list has been adjusted to exclude Brazilian players and focuses on those who have made significant impacts in their clubs and on the international stage as of October 2023. Each player is recognized for their exceptional skills, performances, and achievements.\",\n \"refusal\": null,\n\
\ \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 781,\n \"completion_tokens\": 610,\n \"total_tokens\": 1391,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\",\n \"system_fingerprint\": \"fp_34a54ae93c\"\n}\n"
string: "{\n \"id\": \"chatcmpl-D6L3sn9nSnGGOMKrS88avliVF7XTv\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403300,\n \"model\": \"gpt-4.1-mini-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"Certainly! Here's a structured list
of the top 10 best soccer players in the world as of 2024, considering their
performance, skills, achievements, and impact in recent seasons:\\n\\n###
Top 10 Best Soccer Players in the World (2024)\\n\\n| Rank | Player Name |
Nationality | Club (2023/24 Season) | Position | Key Attributes
\ | Recent Achievements |\\n|-------|---------------------|-------------|----------------------------|------------------|---------------------------------|------------------------------------|\\n|
1 | Lionel Messi | Argentina | Paris Saint-Germain (PSG) |
Forward/Playmaker| Dribbling, Vision, Free kicks | 2023 World Cup Golden
Ball, Club Successes |\\n| 2 | Kylian Mbapp\xE9 | France |
Paris Saint-Germain (PSG) | Forward | Speed, Finishing, Dribbling
\ | Ligue 1 Top Scorer, World Cup Winner 2018|\\n| 3 | Erling Haaland
\ | Norway | Manchester City | Striker | Strength,
Finishing, Positioning| Premier League Golden Boot, Champions League Impact|\\n|
4 | Kevin De Bruyne | Belgium | Manchester City |
Midfielder | Passing, Vision, Creativity | Premier League Titles,
Key Playmaker|\\n| 5 | Robert Lewandowski | Poland | FC Barcelona
\ | Striker | Finishing, Positioning, Composure| La
Liga Top Scorer, Consistent Scorer|\\n| 6 | Neymar Jr. | Brazil
\ | Al-Hilal | Forward/Winger | Dribbling, Creativity,
Flair | Copa America Titles, Club Success |\\n| 7 | Mohamed Salah |
Egypt | Liverpool | Forward/Winger | Pace, Finishing,
Work Rate | Premier League Golden Boot, Champions League Winner|\\n|
8 | Vin\xEDcius Jr. | Brazil | Real Madrid |
Winger | Speed, Dribbling, Crossing | La Liga Titles, UEFA Champions
League Winner|\\n| 9 | Luka Modri\u0107 | Croatia | Real Madrid
\ | Midfielder | Passing, Control, Experience | Ballon
d\u2019Or 2018, Multiple Champions League Titles|\\n| 10 | Karim Benzema
\ | France | Al-Ittihad | Striker | Finishing,
Link-up Play, Movements| Ballon d\u2019Or 2022, UEFA Champions League Top
Scorer |\\n\\n### Notes:\\n- The rankings reflect a combination of individual
skill, recent performance, consistency, and influence on the game.\\n- Players\u2019
clubs are based on the 2023/24 season affiliations.\\n- Achievements highlight
recent titles, awards, or standout contributions.\\n\\nIf you would like me
to focus on specific leagues, historical players, or emerging talents, just
let me know!\",\n \"refusal\": null,\n \"annotations\": []\n
\ },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n
\ ],\n \"usage\": {\n \"prompt_tokens\": 68,\n \"completion_tokens\":
605,\n \"total_tokens\": 673,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_75546bd1a7\"\n}\n"
headers:
CF-RAY:
- 94d9b6782db84d3b-GRU
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Jun 2025 14:56:30 GMT
- Fri, 06 Feb 2026 18:41:49 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- X-Request-ID
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- crewai-iuxna1
- OPENAI-ORG-XXX
openai-processing-ms:
- '31484'
- '9044'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
x-envoy-upstream-service-time:
- '31490'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- '30000'
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- '150000000'
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- '29999'
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- '149999166'
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- 2ms
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- 0s
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- req_aa737cf40bb76af9f458bfd35f7a77a1
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages": [{"role": "system", "content": "You are Sports Analyst. You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.\nYour personal goal is: Gather information about the best soccer players\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!"}, {"role": "user", "content": "Top 10 best players in the world?"}, {"role": "assistant", "content": "Thought: I now can give a great answer \nFinal Answer: The top 10 best soccer players in the world, as of October 2023, can be identified based on their recent performances, skills, impact on games, and overall contributions to their teams. Here is the structured list:\n\n1. **Lionel Messi (Inter Miami CF)**\n -
Position: Forward\n - Key Attributes: Dribbling, vision, goal-scoring ability.\n - Achievements: Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2. **Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n - Position: Forward\n - Key Attributes: Speed, technique, finishing.\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple domestic cups.\n\n3. **Erling Haaland (Manchester City)**\n - Position: Forward\n - Key Attributes: Power, speed, goal-scoring instinct.\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, creativity.\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n - Position: Forward\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n - Achievements:
2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6. **Neymar Jr. (Al Hilal)**\n - Position: Forward\n - Key Attributes: Flair, dribbling, creativity.\n - Achievements: Multiple domestic league titles, Champions League runner-up.\n\n7. **Robert Lewandowski (FC Barcelona)**\n - Position: Forward\n - Key Attributes: Finishing, positioning, aerial ability.\n - Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion (2023).\n\n8. **Mohamed Salah (Liverpool)**\n - Position: Forward\n - Key Attributes: Speed, finishing, dribbling.\n - Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\n\n9. **Vin\u00edcius J\u00fanior (Real Madrid)**\n - Position: Forward\n - Key Attributes: Speed, dribbling, creativity.\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\n\n10. **Luka Modri\u0107 (Real Madrid)**\n - Position: Midfielder\n - Key Attributes: Passing, vision,
tactical intelligence.\n - Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\nThis list is compiled based on their current form, past performances, and contributions to their respective teams in both domestic and international competitions. Player rankings can vary based on personal opinion and specific criteria used for evaluation, but these players have consistently been regarded as some of the best in the world as of October 2023."}, {"role": "user", "content": "You are not allowed to include Brazilian players"}, {"role": "assistant", "content": "Thought: I now can give a great answer \nFinal Answer: Here is an updated list of the top 10 best soccer players in the world as of October 2023, excluding Brazilian players:\n\n1. **Lionel Messi (Inter Miami CF)**\n - Position: Forward\n - Key Attributes: Dribbling, vision, goal-scoring ability.\n - Achievements: Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2.
**Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n - Position: Forward\n - Key Attributes: Speed, technique, finishing.\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple domestic cups.\n\n3. **Erling Haaland (Manchester City)**\n - Position: Forward\n - Key Attributes: Power, speed, goal-scoring instinct.\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, creativity.\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n - Position: Forward\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n - Achievements: 2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6. **Robert Lewandowski (FC Barcelona)**\n - Position: Forward\n - Key Attributes: Finishing, positioning,
aerial ability.\n - Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion (2023).\n\n7. **Mohamed Salah (Liverpool)**\n - Position: Forward\n - Key Attributes: Speed, finishing, dribbling.\n - Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\n\n8. **Vin\u00edcius J\u00fanior (Real Madrid)**\n - Position: Forward\n - Key Attributes: Speed, dribbling, creativity.\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\n\n9. **Luka Modri\u0107 (Real Madrid)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, tactical intelligence.\n - Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\n10. **Harry Kane (Bayern Munich)**\n - Position: Forward\n - Key Attributes: Goal-scoring, technique, playmaking.\n - Achievements: Golden Boot winner, Premier League titles, UEFA European Championship runner-up.\n\nThis list has been adjusted to exclude Brazilian
players and focuses on those who have made significant impacts in their clubs and on the international stage as of October 2023. Each player is recognized for their exceptional skills, performances, and achievements."}, {"role": "user", "content": "You are not allowed to include Brazilian players"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
body: '{"messages":[{"role":"system","content":"You are Sports Analyst. You are
an expert at gathering and organizing information. You carefully collect details
and present them in a structured way.\nYour personal goal is: Gather information
about the best soccer players"},{"role":"user","content":"\nCurrent Task: Top
10 best players in the world?\n\nProvide your complete response:"}],"model":"gpt-4.1-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '6337'
- '404'
content-type:
- application/json
cookie:
- __cf_bm=8Yv8F0ZCFAo2lf.qoqxao70yxyjVvIV90zQqVF6bVzQ-1749567342-1.0.1.1-fZgnv3RDfunvCO1koxwwFJrHnxSx_rwS_FHvQ6xxDPpKHwYr7dTqIQLZrNgSX5twGyK4F22rUmkuiS6KMVogcinChk8lmHtJBTUVTFjr2KU; _cfuvid=wzh8YnmXvLq1G0RcIVijtzboQtCZyIe2uZiochkBLqE-1749567342267-0.0.1.1-604800000
- COOKIE-XXX
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.78.0
x-stainless-arch:
- arm64
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.78.0
x-stainless-raw-response:
- 'true'
- 1.83.0
x-stainless-read-timeout:
- '600.0'
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-BgugsAmyI50uQ6SpCp89ZZY4eD1Pz\",\n \"object\": \"chat.completion\",\n \"created\": 1749567394,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"Thought: I now can give a great answer \\nFinal Answer: Here is the revised list of the top 10 best soccer players in the world as of October 2023, explicitly excluding Brazilian players:\\n\\n1. **Lionel Messi (Inter Miami CF)**\\n - Position: Forward\\n - Key Attributes: Dribbling, vision, goal-scoring ability.\\n - Achievements: Multiple Ballon d'Or winner, Copa America champion, World Cup champion (2022).\\n\\n2. **Kylian Mbappé (Paris Saint-Germain)**\\n - Position: Forward\\n - Key Attributes: Speed, technique, finishing.\\n - Achievements: FIFA World Cup champion (2018), multiple Ligue 1 titles, and various domestic cups.\\n\\n3. **Erling Haaland (Manchester City)**\\n\
\ - Position: Forward\\n - Key Attributes: Power, speed, goal-scoring instinct.\\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\\n\\n4. **Kevin De Bruyne (Manchester City)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, creativity.\\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\\n\\n5. **Karim Benzema (Al-Ittihad)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\\n - Achievements: 2022 Ballon d'Or winner, multiple Champions Leagues with Real Madrid.\\n\\n6. **Robert Lewandowski (FC Barcelona)**\\n - Position: Forward\\n - Key Attributes: Finishing, positioning, aerial ability.\\n - Achievements: FIFA Best Men's Player, multiple Bundesliga titles, La Liga champion (2023).\\n\\n7. **Mohamed Salah (Liverpool)**\\n - Position: Forward\\n - Key Attributes: Speed, finishing, dribbling.\\n -\
\ Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\\n\\n8. **Luka Modrić (Real Madrid)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, tactical intelligence.\\n - Achievements: Multiple Champions League titles, Ballon d'Or winner (2018).\\n\\n9. **Harry Kane (Bayern Munich)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, technique, playmaking.\\n - Achievements: Golden Boot winner, Premier League titles, UEFA European Championship runner-up.\\n\\n10. **Rodri (Manchester City)**\\n - Position: Midfielder\\n - Key Attributes: Defensive skills, passing, positional awareness.\\n - Achievements: Premier League titles, UEFA Champions League winner (2023).\\n\\nThis list is curated while adhering to the restriction of excluding Brazilian players. Each player included has demonstrated exceptional skills and remarkable performances, solidifying their status as some of the best in the world as of October 2023.\"\
,\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 1407,\n \"completion_tokens\": 605,\n \"total_tokens\": 2012,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\",\n \"system_fingerprint\": \"fp_62a23a81ef\"\n}\n"
string: "{\n \"id\": \"chatcmpl-D6L4102eMwTEPeHxfyN9Kh7rjBoX6\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403309,\n \"model\": \"gpt-4.1-mini-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"Certainly! Here is a list of the top
10 best soccer players in the world as of 2024, considering their recent performances,
skills, impact, and accolades:\\n\\n1. **Lionel Messi** \\n - Nationality:
Argentine \\n - Position: Forward \\n - Key Achievements: 7 Ballon d'Or
awards, led Argentina to 2021 Copa Am\xE9rica victory and 2022 FIFA World
Cup triumph, exceptional dribbling and playmaking skills.\\n\\n2. **Kylian
Mbapp\xE9** \\n - Nationality: French \\n - Position: Forward \\n -
Key Achievements: FIFA World Cup winner (2018), multiple Ligue 1 titles, known
for incredible speed, finishing, and consistency.\\n\\n3. **Erling Haaland**
\ \\n - Nationality: Norwegian \\n - Position: Striker \\n - Key Achievements:
Premier League Golden Boot winner (2022-23), prolific goal scorer, physical
presence, and finishing ability.\\n\\n4. **Karim Benzema** \\n - Nationality:
French \\n - Position: Forward \\n - Key Achievements: 2022 Ballon d'Or
winner, key player for Real Madrid\u2019s recent Champions League victories,
excellent technical skills and leadership.\\n\\n5. **Kevin De Bruyne** \\n
\ - Nationality: Belgian \\n - Position: Midfielder \\n - Key Achievements:
Premier League playmaker, known for vision, passing accuracy, and creativity.\\n\\n6.
**Robert Lewandowski** \\n - Nationality: Polish \\n - Position: Striker
\ \\n - Key Achievements: Multiple Bundesliga top scorer titles, consistent
goal scorer, known for positioning and finishing.\\n\\n7. **Neymar Jr.** \\n
\ - Nationality: Brazilian \\n - Position: Forward \\n - Key Achievements:
Exceptional dribbling, creativity, and flair; multiple domestic titles and
Copa Libertadores winner.\\n\\n8. **Mohamed Salah** \\n - Nationality:
Egyptian \\n - Position: Forward \\n - Key Achievements: Premier League
Golden Boot, consistent goal scoring with Liverpool, known for speed and finishing.\\n\\n9.
**Luka Modri\u0107** \\n - Nationality: Croatian \\n - Position: Midfielder
\ \\n - Key Achievements: 2018 Ballon d\u2019Or winner, pivotal midfield
maestro, excellent passing and control.\\n\\n10. **Thibaut Courtois** \\n
\ - Nationality: Belgian \\n - Position: Goalkeeper \\n - Key Achievements:
Exceptional shot-stopper, key player in Real Madrid's recent successes.\\n\\nThis
list includes a blend of forwards, midfielders, and a goalkeeper, showcasing
the best talents in various positions worldwide. The rankings may vary slightly
depending on current form and opinions, but these players consistently rank
among the best globally.\",\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 68,\n \"completion_tokens\":
575,\n \"total_tokens\": 643,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_75546bd1a7\"\n}\n"
headers:
CF-RAY:
- 94d9b7561f204d3b-GRU
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Jun 2025 14:56:46 GMT
- Fri, 06 Feb 2026 18:41:57 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- X-Request-ID
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- crewai-iuxna1
- OPENAI-ORG-XXX
openai-processing-ms:
- '12189'
- '7948'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
x-envoy-upstream-service-time:
- '12193'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- '30000'
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- '150000000'
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- '29999'
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- '149998513'
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- 2ms
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- 0s
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- req_1098f5a5384f4a26aecf0c9e4e4d1fc0
status:
code: 200
message: OK
- request:
body: '{"messages": [{"role": "system", "content": "You are Sports Analyst. You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.\nYour personal goal is: Gather information about the best soccer players\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!"}, {"role": "user", "content": "Top 10 best players in the world?"}, {"role": "assistant", "content": "Thought: I now can give a great answer \nFinal Answer: The top 10 best soccer players in the world, as of October 2023, can be identified based on their recent performances, skills, impact on games, and overall contributions to their teams. Here is the structured list:\n\n1. **Lionel Messi (Inter Miami CF)**\n -
Position: Forward\n - Key Attributes: Dribbling, vision, goal-scoring ability.\n - Achievements: Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2. **Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n - Position: Forward\n - Key Attributes: Speed, technique, finishing.\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple domestic cups.\n\n3. **Erling Haaland (Manchester City)**\n - Position: Forward\n - Key Attributes: Power, speed, goal-scoring instinct.\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, creativity.\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n - Position: Forward\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n - Achievements:
2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6. **Neymar Jr. (Al Hilal)**\n - Position: Forward\n - Key Attributes: Flair, dribbling, creativity.\n - Achievements: Multiple domestic league titles, Champions League runner-up.\n\n7. **Robert Lewandowski (FC Barcelona)**\n - Position: Forward\n - Key Attributes: Finishing, positioning, aerial ability.\n - Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion (2023).\n\n8. **Mohamed Salah (Liverpool)**\n - Position: Forward\n - Key Attributes: Speed, finishing, dribbling.\n - Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\n\n9. **Vin\u00edcius J\u00fanior (Real Madrid)**\n - Position: Forward\n - Key Attributes: Speed, dribbling, creativity.\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\n\n10. **Luka Modri\u0107 (Real Madrid)**\n - Position: Midfielder\n - Key Attributes: Passing, vision,
tactical intelligence.\n - Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\nThis list is compiled based on their current form, past performances, and contributions to their respective teams in both domestic and international competitions. Player rankings can vary based on personal opinion and specific criteria used for evaluation, but these players have consistently been regarded as some of the best in the world as of October 2023."}, {"role": "user", "content": "You are not allowed to include Brazilian players"}, {"role": "assistant", "content": "Thought: I now can give a great answer \nFinal Answer: Here is an updated list of the top 10 best soccer players in the world as of October 2023, excluding Brazilian players:\n\n1. **Lionel Messi (Inter Miami CF)**\n - Position: Forward\n - Key Attributes: Dribbling, vision, goal-scoring ability.\n - Achievements: Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2.
**Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n - Position: Forward\n - Key Attributes: Speed, technique, finishing.\n - Achievements: FIFA World Cup champion (2018), Ligue 1 titles, multiple domestic cups.\n\n3. **Erling Haaland (Manchester City)**\n - Position: Forward\n - Key Attributes: Power, speed, goal-scoring instinct.\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, creativity.\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n - Position: Forward\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n - Achievements: 2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6. **Robert Lewandowski (FC Barcelona)**\n - Position: Forward\n - Key Attributes: Finishing, positioning,
aerial ability.\n - Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion (2023).\n\n7. **Mohamed Salah (Liverpool)**\n - Position: Forward\n - Key Attributes: Speed, finishing, dribbling.\n - Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\n\n8. **Vin\u00edcius J\u00fanior (Real Madrid)**\n - Position: Forward\n - Key Attributes: Speed, dribbling, creativity.\n - Achievements: UEFA Champions League winner (2022), La Liga champion (2023).\n\n9. **Luka Modri\u0107 (Real Madrid)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, tactical intelligence.\n - Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\n10. **Harry Kane (Bayern Munich)**\n - Position: Forward\n - Key Attributes: Goal-scoring, technique, playmaking.\n - Achievements: Golden Boot winner, Premier League titles, UEFA European Championship runner-up.\n\nThis list has been adjusted to exclude Brazilian
players and focuses on those who have made significant impacts in their clubs and on the international stage as of October 2023. Each player is recognized for their exceptional skills, performances, and achievements."}, {"role": "user", "content": "You are not allowed to include Brazilian players"}, {"role": "assistant", "content": "Thought: I now can give a great answer \nFinal Answer: Here is the revised list of the top 10 best soccer players in the world as of October 2023, explicitly excluding Brazilian players:\n\n1. **Lionel Messi (Inter Miami CF)**\n - Position: Forward\n - Key Attributes: Dribbling, vision, goal-scoring ability.\n - Achievements: Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2. **Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n - Position: Forward\n - Key Attributes: Speed, technique, finishing.\n - Achievements: FIFA World Cup champion (2018), multiple Ligue 1 titles, and various domestic cups.\n\n3. **Erling Haaland
(Manchester City)**\n - Position: Forward\n - Key Attributes: Power, speed, goal-scoring instinct.\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, creativity.\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n - Position: Forward\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n - Achievements: 2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6. **Robert Lewandowski (FC Barcelona)**\n - Position: Forward\n - Key Attributes: Finishing, positioning, aerial ability.\n - Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion (2023).\n\n7. **Mohamed Salah (Liverpool)**\n - Position: Forward\n - Key Attributes: Speed, finishing, dribbling.\n - Achievements:
Premier League champion, FA Cup, UEFA Champions League winner.\n\n8. **Luka Modri\u0107 (Real Madrid)**\n - Position: Midfielder\n - Key Attributes: Passing, vision, tactical intelligence.\n - Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\n9. **Harry Kane (Bayern Munich)**\n - Position: Forward\n - Key Attributes: Goal-scoring, technique, playmaking.\n - Achievements: Golden Boot winner, Premier League titles, UEFA European Championship runner-up.\n\n10. **Rodri (Manchester City)**\n - Position: Midfielder\n - Key Attributes: Defensive skills, passing, positional awareness.\n - Achievements: Premier League titles, UEFA Champions League winner (2023).\n\nThis list is curated while adhering to the restriction of excluding Brazilian players. Each player included has demonstrated exceptional skills and remarkable performances, solidifying their status as some of the best in the world as of October 2023."}, {"role": "user", "content":
"You are not allowed to include Brazilian players"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '9093'
content-type:
- application/json
cookie:
- __cf_bm=8Yv8F0ZCFAo2lf.qoqxao70yxyjVvIV90zQqVF6bVzQ-1749567342-1.0.1.1-fZgnv3RDfunvCO1koxwwFJrHnxSx_rwS_FHvQ6xxDPpKHwYr7dTqIQLZrNgSX5twGyK4F22rUmkuiS6KMVogcinChk8lmHtJBTUVTFjr2KU; _cfuvid=wzh8YnmXvLq1G0RcIVijtzboQtCZyIe2uZiochkBLqE-1749567342267-0.0.1.1-604800000
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.78.0
x-stainless-arch:
- arm64
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
x-stainless-package-version:
- 1.78.0
x-stainless-raw-response:
- 'true'
x-stainless-read-timeout:
- '600.0'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-BguhCefN1bN2OeYRo5ChhUqNBLUda\",\n \"object\": \"chat.completion\",\n \"created\": 1749567414,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"Thought: I now can give a great answer \\nFinal Answer: Here is a refined list of the top 10 best soccer players in the world as of October 2023, ensuring that no Brazilian players are included:\\n\\n1. **Lionel Messi (Inter Miami CF)**\\n - Position: Forward\\n - Key Attributes: Dribbling, vision, goal-scoring ability.\\n - Achievements: Multiple Ballon d'Or winner, Copa America champion, World Cup champion (2022).\\n\\n2. **Kylian Mbappé (Paris Saint-Germain)**\\n - Position: Forward\\n - Key Attributes: Speed, technique, finishing.\\n - Achievements: FIFA World Cup champion (2018), multiple Ligue 1 titles, various domestic cups.\\n\\n3. **Erling Haaland (Manchester City)**\\\
n - Position: Forward\\n - Key Attributes: Power, speed, goal-scoring instinct.\\n - Achievements: Bundesliga top scorer, UEFA Champions League winner (2023), Premier League titles.\\n\\n4. **Kevin De Bruyne (Manchester City)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, creativity.\\n - Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League winner (2023).\\n\\n5. **Karim Benzema (Al-Ittihad)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, playmaking, tactical intelligence.\\n - Achievements: 2022 Ballon d'Or winner, multiple Champions Leagues with Real Madrid.\\n\\n6. **Robert Lewandowski (FC Barcelona)**\\n - Position: Forward\\n - Key Attributes: Finishing, positioning, aerial ability.\\n - Achievements: FIFA Best Men's Player, multiple Bundesliga titles, La Liga champion (2023).\\n\\n7. **Mohamed Salah (Liverpool)**\\n - Position: Forward\\n - Key Attributes: Speed, finishing, dribbling.\\n -\
\ Achievements: Premier League champion, FA Cup, UEFA Champions League winner.\\n\\n8. **Luka Modrić (Real Madrid)**\\n - Position: Midfielder\\n - Key Attributes: Passing, vision, tactical intelligence.\\n - Achievements: Multiple Champions League titles, Ballon d'Or winner (2018).\\n\\n9. **Harry Kane (Bayern Munich)**\\n - Position: Forward\\n - Key Attributes: Goal-scoring, technique, playmaking.\\n - Achievements: Golden Boot winner, multiple Premier League titles, UEFA European Championship runner-up.\\n\\n10. **Son Heung-min (Tottenham Hotspur)**\\n - Position: Forward\\n - Key Attributes: Speed, finishing, playmaking.\\n - Achievements: Premier League Golden Boot winner, multiple domestic cup titles.\\n\\nThis list has been carefully revised to exclude all Brazilian players while highlighting some of the most talented individuals in soccer as of October 2023. Each player has showcased remarkable effectiveness and skill, contributing significantly to their\
\ teams on both domestic and international stages.\",\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 2028,\n \"completion_tokens\": 614,\n \"total_tokens\": 2642,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 1280,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\",\n \"system_fingerprint\": \"fp_34a54ae93c\"\n}\n"
headers:
CF-RAY:
- 94d9b7d24d991d2c-GRU
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Jun 2025 14:57:29 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '35291'
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
x-envoy-upstream-service-time:
- '35294'
x-ratelimit-limit-requests:
- '30000'
x-ratelimit-limit-tokens:
- '150000000'
x-ratelimit-remaining-requests:
- '29999'
x-ratelimit-remaining-tokens:
- '149997855'
x-ratelimit-reset-requests:
- 2ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_4676152d4227ac1825d1240ddef231d6
- X-REQUEST-ID-XXX
status:
code: 200
message: OK

View File

@@ -1,14 +1,8 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are Test Agent. A helpful
test assistant\nYour personal goal is: Answer questions\nTo give my best complete
final answer to the task respond using the exact following format:\n\nThought:
I now can give a great answer\nFinal Answer: Your final answer must be the great
and the most complete as possible, it must be outcome described.\n\nI MUST use
these formats, my job depends on it!"},{"role":"user","content":"\nCurrent Task:
What is 2+2? Reply with just the number.\n\nBegin! This is VERY important to
you, use the tools available and give your best Final Answer, your job depends
on it!\n\nThought:"}],"model":"gpt-4o-mini"}'
test assistant\nYour personal goal is: Answer questions"},{"role":"user","content":"\nCurrent
Task: What is 2+2? Reply with just the number.\n\nProvide your complete response:"}],"model":"gpt-4o-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
@@ -21,7 +15,7 @@ interactions:
connection:
- keep-alive
content-length:
- '673'
- '272'
content-type:
- application/json
host:
@@ -43,23 +37,22 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-Cy7b0HjL79y39EkUcMLrRhPFe3XGj\",\n \"object\":
\"chat.completion\",\n \"created\": 1768444914,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
string: "{\n \"id\": \"chatcmpl-D6L4AzMHXLXDfyclWS6fJSwS0cvOl\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403318,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"I now can give a great answer \\nFinal
Answer: 4\",\n \"refusal\": null,\n \"annotations\": []\n },\n
\ \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n
\ \"usage\": {\n \"prompt_tokens\": 136,\n \"completion_tokens\": 13,\n
\ \"total_tokens\": 149,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
\"assistant\",\n \"content\": \"4\",\n \"refusal\": null,\n
\ \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\":
\"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 50,\n \"completion_tokens\":
1,\n \"total_tokens\": 51,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8bbc38b4db\"\n}\n"
\"default\",\n \"system_fingerprint\": \"fp_f4ae844694\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
@@ -68,7 +61,7 @@ interactions:
Content-Type:
- application/json
Date:
- Thu, 15 Jan 2026 02:41:55 GMT
- Fri, 06 Feb 2026 18:41:58 GMT
Server:
- cloudflare
Set-Cookie:
@@ -85,18 +78,14 @@ interactions:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
content-length:
- '857'
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '341'
- '264'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '358'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:

View File

@@ -1,14 +1,8 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are Standalone Agent. A helpful
assistant\nYour personal goal is: Answer questions\nTo give my best complete
final answer to the task respond using the exact following format:\n\nThought:
I now can give a great answer\nFinal Answer: Your final answer must be the great
and the most complete as possible, it must be outcome described.\n\nI MUST use
these formats, my job depends on it!"},{"role":"user","content":"\nCurrent Task:
What is 5+5? Reply with just the number.\n\nBegin! This is VERY important to
you, use the tools available and give your best Final Answer, your job depends
on it!\n\nThought:"}],"model":"gpt-4o-mini"}'
assistant\nYour personal goal is: Answer questions"},{"role":"user","content":"\nCurrent
Task: What is 5+5? Reply with just the number.\n\nProvide your complete response:"}],"model":"gpt-4o-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
@@ -21,7 +15,7 @@ interactions:
connection:
- keep-alive
content-length:
- '674'
- '273'
content-type:
- application/json
host:
@@ -43,23 +37,22 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-Cy7azhPwUHQ0p5tdhxSAmLPoE8UgC\",\n \"object\":
\"chat.completion\",\n \"created\": 1768444913,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
string: "{\n \"id\": \"chatcmpl-D6L3cLs2ndBaXV2wnqYCdi6X1ykvv\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403284,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"I now can give a great answer \\nFinal
Answer: 10\",\n \"refusal\": null,\n \"annotations\": []\n },\n
\ \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n
\ \"usage\": {\n \"prompt_tokens\": 136,\n \"completion_tokens\": 13,\n
\ \"total_tokens\": 149,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
\"assistant\",\n \"content\": \"10\",\n \"refusal\": null,\n
\ \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\":
\"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 50,\n \"completion_tokens\":
1,\n \"total_tokens\": 51,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_29330a9688\"\n}\n"
\"default\",\n \"system_fingerprint\": \"fp_f4ae844694\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
@@ -68,7 +61,7 @@ interactions:
Content-Type:
- application/json
Date:
- Thu, 15 Jan 2026 02:41:54 GMT
- Fri, 06 Feb 2026 18:41:25 GMT
Server:
- cloudflare
Set-Cookie:
@@ -85,18 +78,14 @@ interactions:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
content-length:
- '858'
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '455'
- '270'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '583'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:

View File

@@ -1,13 +1,8 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are First Agent. A friendly
greeter\nYour personal goal is: Greet users\nTo give my best complete final
answer to the task respond using the exact following format:\n\nThought: I now
can give a great answer\nFinal Answer: Your final answer must be the great and
the most complete as possible, it must be outcome described.\n\nI MUST use these
formats, my job depends on it!"},{"role":"user","content":"\nCurrent Task: Say
hello\n\nBegin! This is VERY important to you, use the tools available and give
your best Final Answer, your job depends on it!\n\nThought:"}],"model":"gpt-4o-mini"}'
greeter\nYour personal goal is: Greet users"},{"role":"user","content":"\nCurrent
Task: Say hello\n\nProvide your complete response:"}],"model":"gpt-4o-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
@@ -20,7 +15,7 @@ interactions:
connection:
- keep-alive
content-length:
- '632'
- '231'
content-type:
- application/json
host:
@@ -42,24 +37,22 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-CyRKzgODZ9yn3F9OkaXsscLk2Ln3N\",\n \"object\":
\"chat.completion\",\n \"created\": 1768520801,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
string: "{\n \"id\": \"chatcmpl-D6L4A8Aad6P1YUxWjQpvyltn8GaKT\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403318,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"I now can give a great answer \\nFinal
Answer: Hello! Welcome! I'm so glad to see you here. If you need any assistance
or have any questions, feel free to ask. Have a wonderful day!\",\n \"refusal\":
null,\n \"annotations\": []\n },\n \"logprobs\": null,\n
\ \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\":
127,\n \"completion_tokens\": 43,\n \"total_tokens\": 170,\n \"prompt_tokens_details\":
\"assistant\",\n \"content\": \"Hello! \U0001F60A How are you today?\",\n
\ \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\":
null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\":
41,\n \"completion_tokens\": 8,\n \"total_tokens\": 49,\n \"prompt_tokens_details\":
{\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_c4585b5b9c\"\n}\n"
\"default\",\n \"system_fingerprint\": \"fp_f4ae844694\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
@@ -68,7 +61,7 @@ interactions:
Content-Type:
- application/json
Date:
- Thu, 15 Jan 2026 23:46:42 GMT
- Fri, 06 Feb 2026 18:41:58 GMT
Server:
- cloudflare
Set-Cookie:
@@ -85,18 +78,14 @@ interactions:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
content-length:
- '990'
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '880'
- '325'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '1160'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
@@ -118,13 +107,8 @@ interactions:
message: OK
- request:
body: '{"messages":[{"role":"system","content":"You are Second Agent. A polite
farewell agent\nYour personal goal is: Say goodbye\nTo give my best complete
final answer to the task respond using the exact following format:\n\nThought:
I now can give a great answer\nFinal Answer: Your final answer must be the great
and the most complete as possible, it must be outcome described.\n\nI MUST use
these formats, my job depends on it!"},{"role":"user","content":"\nCurrent Task:
Say goodbye\n\nBegin! This is VERY important to you, use the tools available
and give your best Final Answer, your job depends on it!\n\nThought:"}],"model":"gpt-4o-mini"}'
farewell agent\nYour personal goal is: Say goodbye"},{"role":"user","content":"\nCurrent
Task: Say goodbye\n\nProvide your complete response:"}],"model":"gpt-4o-mini"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
@@ -137,7 +121,7 @@ interactions:
connection:
- keep-alive
content-length:
- '640'
- '239'
content-type:
- application/json
host:
@@ -159,27 +143,24 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-CyRL1Ua2PkK5xXPp3KeF0AnGAk3JP\",\n \"object\":
\"chat.completion\",\n \"created\": 1768520803,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
string: "{\n \"id\": \"chatcmpl-D6L4BLMYC3ODccwbKfBIdtrEyd3no\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403319,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"I now can give a great answer \\nFinal
Answer: As we reach the end of our conversation, I want to express my gratitude
for the time we've shared. It's been a pleasure assisting you, and I hope
you found our interaction helpful and enjoyable. Remember, whenever you need
assistance, I'm just a message away. Wishing you all the best in your future
endeavors. Goodbye and take care!\",\n \"refusal\": null,\n \"annotations\":
\"assistant\",\n \"content\": \"Thank you for the time we've spent
together! I wish you all the best in your future endeavors. Take care, and
until we meet again, goodbye!\",\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 126,\n \"completion_tokens\":
79,\n \"total_tokens\": 205,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 40,\n \"completion_tokens\":
31,\n \"total_tokens\": 71,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_29330a9688\"\n}\n"
\"default\",\n \"system_fingerprint\": \"fp_f4ae844694\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
@@ -188,7 +169,7 @@ interactions:
Content-Type:
- application/json
Date:
- Thu, 15 Jan 2026 23:46:44 GMT
- Fri, 06 Feb 2026 18:41:59 GMT
Server:
- cloudflare
Set-Cookie:
@@ -205,18 +186,14 @@ interactions:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
content-length:
- '1189'
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '1363'
- '726'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '1605'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:

View File

@@ -2,9 +2,8 @@ interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are Calculator. You calculate
things.\nYour personal goal is: Perform calculations efficiently"},{"role":"user","content":"\nCurrent
Task: Use the failing_tool to do something.\n\nThis is VERY important to you,
your job depends on it!"}],"model":"gpt-4o-mini","tool_choice":"auto","tools":[{"type":"function","function":{"name":"failing_tool","description":"This
tool always fails","parameters":{"properties":{},"type":"object"}}}]}'
Task: Use the failing_tool to do something."}],"model":"gpt-4o-mini","tool_choice":"auto","tools":[{"type":"function","function":{"name":"failing_tool","description":"This
tool always fails","strict":true,"parameters":{"properties":{},"type":"object","additionalProperties":false,"required":[]}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
@@ -17,7 +16,7 @@ interactions:
connection:
- keep-alive
content-length:
- '477'
- '476'
content-type:
- application/json
host:
@@ -39,26 +38,26 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D0vm2JDsOmy0czXPAr4vnw3wvuqYZ\",\n \"object\":
\"chat.completion\",\n \"created\": 1769114454,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
string: "{\n \"id\": \"chatcmpl-D6L3dV6acwapgRyxmnzGfuOXemtjJ\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403285,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n
\ \"id\": \"call_8xr8rPUDWzLfQ3LOWPHtBUjK\",\n \"type\":
\ \"id\": \"call_GCdaOdo32pr1sSk4RzO0tiB9\",\n \"type\":
\"function\",\n \"function\": {\n \"name\": \"failing_tool\",\n
\ \"arguments\": \"{}\"\n }\n }\n ],\n
\ \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\":
null,\n \"finish_reason\": \"tool_calls\"\n }\n ],\n \"usage\":
{\n \"prompt_tokens\": 78,\n \"completion_tokens\": 11,\n \"total_tokens\":
89,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\":
{\n \"prompt_tokens\": 65,\n \"completion_tokens\": 11,\n \"total_tokens\":
76,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\":
0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\":
0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n
\ \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_c4585b5b9c\"\n}\n"
\"default\",\n \"system_fingerprint\": \"fp_6c0d1490cb\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
@@ -67,7 +66,7 @@ interactions:
Content-Type:
- application/json
Date:
- Thu, 22 Jan 2026 20:40:54 GMT
- Fri, 06 Feb 2026 18:41:25 GMT
Server:
- cloudflare
Set-Cookie:
@@ -87,13 +86,11 @@ interactions:
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '593'
- '436'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '621'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
@@ -116,12 +113,9 @@ interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are Calculator. You calculate
things.\nYour personal goal is: Perform calculations efficiently"},{"role":"user","content":"\nCurrent
Task: Use the failing_tool to do something.\n\nThis is VERY important to you,
your job depends on it!"},{"role":"assistant","content":null,"tool_calls":[{"id":"call_8xr8rPUDWzLfQ3LOWPHtBUjK","type":"function","function":{"name":"failing_tool","arguments":"{}"}}]},{"role":"tool","tool_call_id":"call_8xr8rPUDWzLfQ3LOWPHtBUjK","content":"Error
executing tool: This tool always fails"},{"role":"user","content":"Analyze the
tool result. If requirements are met, provide the Final Answer. Otherwise, call
the next tool. Deliver only the answer without meta-commentary."}],"model":"gpt-4o-mini","tool_choice":"auto","tools":[{"type":"function","function":{"name":"failing_tool","description":"This
tool always fails","parameters":{"properties":{},"type":"object"}}}]}'
Task: Use the failing_tool to do something."},{"role":"assistant","content":null,"tool_calls":[{"id":"call_GCdaOdo32pr1sSk4RzO0tiB9","type":"function","function":{"name":"failing_tool","arguments":"{}"}}]},{"role":"tool","tool_call_id":"call_GCdaOdo32pr1sSk4RzO0tiB9","name":"failing_tool","content":"Error
executing tool: This tool always fails"}],"model":"gpt-4o-mini","tool_choice":"auto","tools":[{"type":"function","function":{"name":"failing_tool","description":"This
tool always fails","strict":true,"parameters":{"properties":{},"type":"object","additionalProperties":false,"required":[]}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
@@ -134,7 +128,7 @@ interactions:
connection:
- keep-alive
content-length:
- '941'
- '778'
content-type:
- application/json
cookie:
@@ -158,22 +152,25 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D0vm3xcywoKBW75bhBXfkGJNim6Th\",\n \"object\":
\"chat.completion\",\n \"created\": 1769114455,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
string: "{\n \"id\": \"chatcmpl-D6L3dhjDZOoihHvXvRpbJD3ReGu0z\",\n \"object\":
\"chat.completion\",\n \"created\": 1770403285,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"Error: This tool always fails.\",\n
\ \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\":
null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\":
141,\n \"completion_tokens\": 8,\n \"total_tokens\": 149,\n \"prompt_tokens_details\":
{\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
\"assistant\",\n \"content\": \"The attempt to use the failing tool
resulted in an error, as expected since it is designed to always fail. If
there's anything else you would like to calculate or explore, please let me
know!\",\n \"refusal\": null,\n \"annotations\": []\n },\n
\ \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n
\ \"usage\": {\n \"prompt_tokens\": 93,\n \"completion_tokens\": 40,\n
\ \"total_tokens\": 133,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_c4585b5b9c\"\n}\n"
\"default\",\n \"system_fingerprint\": \"fp_6c0d1490cb\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
@@ -182,7 +179,7 @@ interactions:
Content-Type:
- application/json
Date:
- Thu, 22 Jan 2026 20:40:55 GMT
- Fri, 06 Feb 2026 18:41:26 GMT
Server:
- cloudflare
Strict-Transport-Security:
@@ -200,13 +197,11 @@ interactions:
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '420'
- '776'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
x-envoy-upstream-service-time:
- '436'
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:

View File

@@ -43,15 +43,15 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: '{"model":"claude-3-5-haiku-20241022","id":"msg_0149zKBgM47utdBdrfJjM6YZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_011jnBYLgtzXqdmSi7JDyQHj","name":"structured_output","input":{"operation":"Addition","result":42,"explanation":"Adding
15 and 27 together results in 42"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":573,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":79,"service_tier":"standard"}}'
string: '{"model":"claude-3-5-haiku-20241022","id":"msg_01A41GpDoJbZLUhR8dQzUcUX","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01UNPdzpayoWyqDYVE7fR5oA","name":"structured_output","input":{"operation":"Addition","result":42,"explanation":"Added
15 and 27 together"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":573,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":75,"service_tier":"standard","inference_geo":"not_available"}}'
headers:
CF-RAY:
- CF-RAY-XXX
@@ -62,7 +62,7 @@ interactions:
Content-Type:
- application/json
Date:
- Fri, 30 Jan 2026 18:56:15 GMT
- Fri, 06 Feb 2026 18:41:25 GMT
Server:
- cloudflare
Transfer-Encoding:
@@ -88,7 +88,7 @@ interactions:
anthropic-ratelimit-requests-remaining:
- '3999'
anthropic-ratelimit-requests-reset:
- '2026-01-30T18:56:14Z'
- '2026-02-06T18:41:24Z'
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
@@ -102,7 +102,7 @@ interactions:
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '1473'
- '1247'
status:
code: 200
message: OK

View File

@@ -44,21 +44,20 @@ interactions:
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
- 3.13.5
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: '{"model":"claude-3-5-haiku-20241022","id":"msg_013iHkpmto99iyH5kDvn8uER","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Kpda2DzHBqWq9a2FS2Bdw6","name":"structured_output","input":{"topic":"Benefits
string: '{"model":"claude-3-5-haiku-20241022","id":"msg_016wrV83wm3FLYD4JoTy2Piw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01V6Pzr7eGfuG4Q3mc25ZXwN","name":"structured_output","input":{"topic":"Benefits
of Remote Work","summary":"Remote work offers significant advantages for both
employees and employers, transforming traditional work paradigms by providing
flexibility, increased productivity, and cost savings.","key_points":["Increased
employee flexibility and work-life balance","Reduced commuting time and associated
stress","Cost savings for companies on office infrastructure","Access to a
global talent pool","Higher employee productivity and job satisfaction","Lower
carbon footprint due to reduced travel"]}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":589,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":153,"service_tier":"standard"}}'
employees and employers, transforming traditional workplace dynamics.","key_points":["Increased
flexibility in work schedule","Reduced commute time and transportation costs","Improved
work-life balance","Higher productivity for many employees","Cost savings
for companies on office infrastructure","Expanded talent pool for hiring","Enhanced
employee job satisfaction"]}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":589,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":142,"service_tier":"standard","inference_geo":"not_available"}}'
headers:
CF-RAY:
- CF-RAY-XXX
@@ -69,7 +68,7 @@ interactions:
Content-Type:
- application/json
Date:
- Fri, 30 Jan 2026 18:56:19 GMT
- Fri, 06 Feb 2026 18:41:28 GMT
Server:
- cloudflare
Transfer-Encoding:
@@ -95,7 +94,7 @@ interactions:
anthropic-ratelimit-requests-remaining:
- '3999'
anthropic-ratelimit-requests-reset:
- '2026-01-30T18:56:16Z'
- '2026-02-06T18:41:26Z'
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
@@ -109,7 +108,7 @@ interactions:
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '3107'
- '2650'
status:
code: 200
message: OK

View File

@@ -0,0 +1,332 @@
interactions:
- request:
body: '{"max_tokens":4096,"messages":[{"role":"user","content":[{"type":"text","text":"Say
hello in one word.","cache_control":{"type":"ephemeral"}}]}],"model":"claude-sonnet-4-5-20250929","stream":false,"system":"You
are a helpful assistant. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. "}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
anthropic-version:
- '2023-06-01'
connection:
- keep-alive
content-length:
- '5918'
content-type:
- application/json
host:
- api.anthropic.com
x-api-key:
- X-API-KEY-XXX
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 0.73.0
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: '{"model":"claude-sonnet-4-5-20250929","id":"msg_013xTaKq41TFn6drdxt1mFdx","type":"message","role":"assistant","content":[{"type":"text","text":"Hello!"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":1217,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"not_available"}}'
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Security-Policy:
- CSP-FILTERED
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:27:40 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Robots-Tag:
- none
anthropic-organization-id:
- ANTHROPIC-ORGANIZATION-ID-XXX
anthropic-ratelimit-input-tokens-limit:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-input-tokens-remaining:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-input-tokens-reset:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-RESET-XXX
anthropic-ratelimit-output-tokens-limit:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-output-tokens-remaining:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-output-tokens-reset:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-RESET-XXX
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
- ANTHROPIC-RATELIMIT-TOKENS-REMAINING-XXX
anthropic-ratelimit-tokens-reset:
- ANTHROPIC-RATELIMIT-TOKENS-RESET-XXX
cf-cache-status:
- DYNAMIC
request-id:
- REQUEST-ID-XXX
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '726'
status:
code: 200
message: OK
- request:
body: '{"max_tokens":4096,"messages":[{"role":"user","content":[{"type":"text","text":"Say
goodbye in one word.","cache_control":{"type":"ephemeral"}}]}],"model":"claude-sonnet-4-5-20250929","stream":false,"system":"You
are a helpful assistant. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. "}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
anthropic-version:
- '2023-06-01'
connection:
- keep-alive
content-length:
- '5920'
content-type:
- application/json
host:
- api.anthropic.com
x-api-key:
- X-API-KEY-XXX
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 0.73.0
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: '{"model":"claude-sonnet-4-5-20250929","id":"msg_01LdueHX7nvf19wD8Uxn4EZD","type":"message","role":"assistant","content":[{"type":"text","text":"Goodbye"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":1217,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"not_available"}}'
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Security-Policy:
- CSP-FILTERED
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:27:41 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Robots-Tag:
- none
anthropic-organization-id:
- ANTHROPIC-ORGANIZATION-ID-XXX
anthropic-ratelimit-input-tokens-limit:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-input-tokens-remaining:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-input-tokens-reset:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-RESET-XXX
anthropic-ratelimit-output-tokens-limit:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-output-tokens-remaining:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-output-tokens-reset:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-RESET-XXX
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
- ANTHROPIC-RATELIMIT-TOKENS-REMAINING-XXX
anthropic-ratelimit-tokens-reset:
- ANTHROPIC-RATELIMIT-TOKENS-RESET-XXX
cf-cache-status:
- DYNAMIC
request-id:
- REQUEST-ID-XXX
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '759'
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,336 @@
interactions:
- request:
body: '{"max_tokens":4096,"messages":[{"role":"user","content":[{"type":"text","text":"What
is the weather in Tokyo?","cache_control":{"type":"ephemeral"}}]}],"model":"claude-sonnet-4-5-20250929","stream":false,"system":"You
are a helpful assistant that uses tools. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. ","tool_choice":{"type":"tool","name":"get_weather"},"tools":[{"name":"get_weather","description":"Get
the current weather for a location","input_schema":{"type":"object","properties":{"location":{"type":"string","description":"The
city name"}},"required":["location"]}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
anthropic-version:
- '2023-06-01'
connection:
- keep-alive
content-length:
- '6211'
content-type:
- application/json
host:
- api.anthropic.com
x-api-key:
- X-API-KEY-XXX
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 0.73.0
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: '{"model":"claude-sonnet-4-5-20250929","id":"msg_01WhFk2ppoz43nbh4uNhXBfL","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CX1yZuJ5MQaJbXNSrnCiqf","name":"get_weather","input":{"location":"Tokyo"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":24,"cache_creation_input_tokens":0,"cache_read_input_tokens":1857,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":33,"service_tier":"standard","inference_geo":"not_available"}}'
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Security-Policy:
- CSP-FILTERED
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:27:38 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Robots-Tag:
- none
anthropic-organization-id:
- ANTHROPIC-ORGANIZATION-ID-XXX
anthropic-ratelimit-input-tokens-limit:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-input-tokens-remaining:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-input-tokens-reset:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-RESET-XXX
anthropic-ratelimit-output-tokens-limit:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-output-tokens-remaining:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-output-tokens-reset:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-RESET-XXX
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
- ANTHROPIC-RATELIMIT-TOKENS-REMAINING-XXX
anthropic-ratelimit-tokens-reset:
- ANTHROPIC-RATELIMIT-TOKENS-RESET-XXX
cf-cache-status:
- DYNAMIC
request-id:
- REQUEST-ID-XXX
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '1390'
status:
code: 200
message: OK
- request:
body: '{"max_tokens":4096,"messages":[{"role":"user","content":[{"type":"text","text":"What
is the weather in Paris?","cache_control":{"type":"ephemeral"}}]}],"model":"claude-sonnet-4-5-20250929","stream":false,"system":"You
are a helpful assistant that uses tools. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. ","tool_choice":{"type":"tool","name":"get_weather"},"tools":[{"name":"get_weather","description":"Get
the current weather for a location","input_schema":{"type":"object","properties":{"location":{"type":"string","description":"The
city name"}},"required":["location"]}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
anthropic-version:
- '2023-06-01'
connection:
- keep-alive
content-length:
- '6211'
content-type:
- application/json
host:
- api.anthropic.com
x-api-key:
- X-API-KEY-XXX
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 0.73.0
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: '{"model":"claude-sonnet-4-5-20250929","id":"msg_01Nmw5NyAEwCLGjpVnf15rh4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01DEe9K7N4EfhPFqxHhqEHCE","name":"get_weather","input":{"location":"Paris"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":24,"cache_creation_input_tokens":0,"cache_read_input_tokens":1857,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":33,"service_tier":"standard","inference_geo":"not_available"}}'
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Security-Policy:
- CSP-FILTERED
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:27:40 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Robots-Tag:
- none
anthropic-organization-id:
- ANTHROPIC-ORGANIZATION-ID-XXX
anthropic-ratelimit-input-tokens-limit:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-input-tokens-remaining:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-input-tokens-reset:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-RESET-XXX
anthropic-ratelimit-output-tokens-limit:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-output-tokens-remaining:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-output-tokens-reset:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-RESET-XXX
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
- ANTHROPIC-RATELIMIT-TOKENS-REMAINING-XXX
anthropic-ratelimit-tokens-reset:
- ANTHROPIC-RATELIMIT-TOKENS-RESET-XXX
cf-cache-status:
- DYNAMIC
request-id:
- REQUEST-ID-XXX
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '1259'
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,411 @@
interactions:
- request:
body: '{"max_tokens":4096,"messages":[{"role":"user","content":[{"type":"text","text":"Say
hello in one word.","cache_control":{"type":"ephemeral"}}]}],"model":"claude-sonnet-4-5-20250929","system":"You
are a helpful assistant. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. ","stream":true}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
anthropic-version:
- '2023-06-01'
connection:
- keep-alive
content-length:
- '5917'
content-type:
- application/json
host:
- api.anthropic.com
x-api-key:
- X-API-KEY-XXX
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 0.73.0
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
x-stainless-stream-helper:
- messages
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: 'event: message_start
data: {"type":"message_start","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_01LshZroyEGgd3HfDrKdQMLm","type":"message","role":"assistant","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":1217,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"}} }
event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} }
event: ping
data: {"type": "ping"}
event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hello"} }
event: content_block_stop
data: {"type":"content_block_stop","index":0 }
event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":1217,"output_tokens":4}
}
event: message_stop
data: {"type":"message_stop" }
'
headers:
CF-RAY:
- CF-RAY-XXX
Cache-Control:
- no-cache
Connection:
- keep-alive
Content-Security-Policy:
- CSP-FILTERED
Content-Type:
- text/event-stream; charset=utf-8
Date:
- Tue, 10 Feb 2026 18:27:43 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Robots-Tag:
- none
anthropic-organization-id:
- ANTHROPIC-ORGANIZATION-ID-XXX
anthropic-ratelimit-input-tokens-limit:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-input-tokens-remaining:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-input-tokens-reset:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-RESET-XXX
anthropic-ratelimit-output-tokens-limit:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-output-tokens-remaining:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-output-tokens-reset:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-RESET-XXX
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
- ANTHROPIC-RATELIMIT-TOKENS-REMAINING-XXX
anthropic-ratelimit-tokens-reset:
- ANTHROPIC-RATELIMIT-TOKENS-RESET-XXX
cf-cache-status:
- DYNAMIC
request-id:
- REQUEST-ID-XXX
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '837'
status:
code: 200
message: OK
- request:
body: '{"max_tokens":4096,"messages":[{"role":"user","content":[{"type":"text","text":"Say
goodbye in one word.","cache_control":{"type":"ephemeral"}}]}],"model":"claude-sonnet-4-5-20250929","system":"You
are a helpful assistant. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. ","stream":true}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
anthropic-version:
- '2023-06-01'
connection:
- keep-alive
content-length:
- '5919'
content-type:
- application/json
host:
- api.anthropic.com
x-api-key:
- X-API-KEY-XXX
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 0.73.0
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
x-stainless-stream-helper:
- messages
x-stainless-timeout:
- NOT_GIVEN
method: POST
uri: https://api.anthropic.com/v1/messages
response:
body:
string: 'event: message_start
data: {"type":"message_start","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_01MZSWarEUbFXmek8aEpwKDu","type":"message","role":"assistant","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":1217,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"not_available"}} }
event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}
event: ping
data: {"type": "ping"}
event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Goodbye."} }
event: content_block_stop
data: {"type":"content_block_stop","index":0 }
event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":1217,"output_tokens":6} }
event: message_stop
data: {"type":"message_stop" }
'
headers:
CF-RAY:
- CF-RAY-XXX
Cache-Control:
- no-cache
Connection:
- keep-alive
Content-Security-Policy:
- CSP-FILTERED
Content-Type:
- text/event-stream; charset=utf-8
Date:
- Tue, 10 Feb 2026 18:27:44 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Robots-Tag:
- none
anthropic-organization-id:
- ANTHROPIC-ORGANIZATION-ID-XXX
anthropic-ratelimit-input-tokens-limit:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-input-tokens-remaining:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-input-tokens-reset:
- ANTHROPIC-RATELIMIT-INPUT-TOKENS-RESET-XXX
anthropic-ratelimit-output-tokens-limit:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-LIMIT-XXX
anthropic-ratelimit-output-tokens-remaining:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-REMAINING-XXX
anthropic-ratelimit-output-tokens-reset:
- ANTHROPIC-RATELIMIT-OUTPUT-TOKENS-RESET-XXX
anthropic-ratelimit-tokens-limit:
- ANTHROPIC-RATELIMIT-TOKENS-LIMIT-XXX
anthropic-ratelimit-tokens-remaining:
- ANTHROPIC-RATELIMIT-TOKENS-REMAINING-XXX
anthropic-ratelimit-tokens-reset:
- ANTHROPIC-RATELIMIT-TOKENS-RESET-XXX
cf-cache-status:
- DYNAMIC
request-id:
- REQUEST-ID-XXX
strict-transport-security:
- STS-XXX
x-envoy-upstream-service-time:
- '870'
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,266 @@
interactions:
- request:
body: '{"contents": [{"parts": [{"text": "Say hello in one word."}], "role": "user"}],
"systemInstruction": {"parts": [{"text": "You are a helpful assistant. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
"}], "role": "user"}, "generationConfig": {}}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- '*/*'
accept-encoding:
- ACCEPT-ENCODING-XXX
connection:
- keep-alive
content-length:
- '5876'
content-type:
- application/json
host:
- generativelanguage.googleapis.com
x-goog-api-client:
- google-genai-sdk/1.49.0 gl-python/3.13.3
x-goog-api-key:
- X-GOOG-API-KEY-XXX
method: POST
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
response:
body:
string: "{\n \"candidates\": [\n {\n \"content\": {\n \"parts\":
[\n {\n \"text\": \"Hello\"\n }\n ],\n
\ \"role\": \"model\"\n },\n \"finishReason\": \"STOP\",\n
\ \"index\": 0\n }\n ],\n \"usageMetadata\": {\n \"promptTokenCount\":
1135,\n \"candidatesTokenCount\": 1,\n \"totalTokenCount\": 1158,\n
\ \"promptTokensDetails\": [\n {\n \"modality\": \"TEXT\",\n
\ \"tokenCount\": 1135\n }\n ],\n \"thoughtsTokenCount\":
22\n },\n \"modelVersion\": \"gemini-2.5-flash\",\n \"responseId\": \"46GLaf60NYmY-8YP--PB6QE\"\n}\n"
headers:
Alt-Svc:
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
Content-Type:
- application/json; charset=UTF-8
Date:
- Tue, 10 Feb 2026 21:23:47 GMT
Server:
- scaffolding on HTTPServer2
Server-Timing:
- gfet4t7; dur=773
Transfer-Encoding:
- chunked
Vary:
- Origin
- X-Origin
- Referer
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
X-Frame-Options:
- X-FRAME-OPTIONS-XXX
X-XSS-Protection:
- '0'
status:
code: 200
message: OK
- request:
body: '{"contents": [{"parts": [{"text": "Say goodbye in one word."}], "role":
"user"}], "systemInstruction": {"parts": [{"text": "You are a helpful assistant.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. "}], "role": "user"}, "generationConfig": {}}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- '*/*'
accept-encoding:
- ACCEPT-ENCODING-XXX
connection:
- keep-alive
content-length:
- '5878'
content-type:
- application/json
host:
- generativelanguage.googleapis.com
x-goog-api-client:
- google-genai-sdk/1.49.0 gl-python/3.13.3
x-goog-api-key:
- X-GOOG-API-KEY-XXX
method: POST
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
response:
body:
string: "{\n \"candidates\": [\n {\n \"content\": {\n \"parts\":
[\n {\n \"text\": \"Farewell.\"\n }\n ],\n
\ \"role\": \"model\"\n },\n \"finishReason\": \"STOP\",\n
\ \"index\": 0\n }\n ],\n \"usageMetadata\": {\n \"promptTokenCount\":
1135,\n \"candidatesTokenCount\": 3,\n \"totalTokenCount\": 1164,\n
\ \"promptTokensDetails\": [\n {\n \"modality\": \"TEXT\",\n
\ \"tokenCount\": 1135\n }\n ],\n \"thoughtsTokenCount\":
26\n },\n \"modelVersion\": \"gemini-2.5-flash\",\n \"responseId\": \"5KGLafeeIv-G-8YP_MfPgAI\"\n}\n"
headers:
Alt-Svc:
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
Content-Type:
- application/json; charset=UTF-8
Date:
- Tue, 10 Feb 2026 21:23:48 GMT
Server:
- scaffolding on HTTPServer2
Server-Timing:
- gfet4t7; dur=662
Transfer-Encoding:
- chunked
Vary:
- Origin
- X-Origin
- Referer
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
X-Frame-Options:
- X-FRAME-OPTIONS-XXX
X-XSS-Protection:
- '0'
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,280 @@
interactions:
- request:
body: '{"contents": [{"parts": [{"text": "What is the weather in Tokyo?"}], "role":
"user"}], "systemInstruction": {"parts": [{"text": "You are a helpful assistant
that uses tools. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. "}], "role": "user"}, "tools": [{"functionDeclarations":
[{"description": "Get the current weather for a location", "name": "get_weather",
"parameters_json_schema": {"type": "object", "properties": {"location": {"type":
"string", "description": "The city name"}}, "required": ["location"]}}]}], "generationConfig":
{}}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- '*/*'
accept-encoding:
- ACCEPT-ENCODING-XXX
connection:
- keep-alive
content-length:
- '6172'
content-type:
- application/json
host:
- generativelanguage.googleapis.com
x-goog-api-client:
- google-genai-sdk/1.49.0 gl-python/3.13.3
x-goog-api-key:
- X-GOOG-API-KEY-XXX
method: POST
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
response:
body:
string: "{\n \"candidates\": [\n {\n \"content\": {\n \"parts\":
[\n {\n \"functionCall\": {\n \"name\": \"get_weather\",\n
\ \"args\": {\n \"location\": \"Tokyo\"\n }\n
\ },\n \"thoughtSignature\": \"CpECAb4+9vvTFzaczX2PeZjKEs1f6+MRyTMz+xxqs37q0INQ6e0WLt1soet6CL/uzRML9LsycSeQTraXtXR8qcGj6dnrhKLpovpy8EkrtfK6P57PGpostE/UJ6TIKPlWi0pY1h2u9vyy5yGLzpp0PZM6d6f8rzV9uPFNM+onGvcFOdzghRZlHmYkQdbdpZaFQBAK6QFuh8oGbC0Ygrsk1guJo1YZaKtU5Rp/k2rJO61Obgq7aYEb7ACVx7DM9ZlVCun/PbXR4UolFeNPxNdwzC5AVvP7UKa2Cxi8dzQ8RNebtd39/gNO546XzADGZkpSqG6QF0S4IEsmB9FFCctN1evgKicgT2Qo+AR6BY8uzZyWkGQx\"\n
\ }\n ],\n \"role\": \"model\"\n },\n \"finishReason\":
\"STOP\",\n \"index\": 0,\n \"finishMessage\": \"Model generated
function call(s).\"\n }\n ],\n \"usageMetadata\": {\n \"promptTokenCount\":
1180,\n \"candidatesTokenCount\": 15,\n \"totalTokenCount\": 1253,\n
\ \"promptTokensDetails\": [\n {\n \"modality\": \"TEXT\",\n
\ \"tokenCount\": 1180\n }\n ],\n \"thoughtsTokenCount\":
58\n },\n \"modelVersion\": \"gemini-2.5-flash\",\n \"responseId\": \"wHmLacb_GL-J-sAPn6azgAo\"\n}\n"
headers:
Alt-Svc:
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
Content-Type:
- application/json; charset=UTF-8
Date:
- Tue, 10 Feb 2026 18:32:32 GMT
Server:
- scaffolding on HTTPServer2
Server-Timing:
- gfet4t7; dur=755
Transfer-Encoding:
- chunked
Vary:
- Origin
- X-Origin
- Referer
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
X-Frame-Options:
- X-FRAME-OPTIONS-XXX
X-XSS-Protection:
- '0'
status:
code: 200
message: OK
- request:
body: '{"contents": [{"parts": [{"text": "What is the weather in Paris?"}], "role":
"user"}], "systemInstruction": {"parts": [{"text": "You are a helpful assistant
that uses tools. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. "}], "role": "user"}, "tools": [{"functionDeclarations":
[{"description": "Get the current weather for a location", "name": "get_weather",
"parameters_json_schema": {"type": "object", "properties": {"location": {"type":
"string", "description": "The city name"}}, "required": ["location"]}}]}], "generationConfig":
{}}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- '*/*'
accept-encoding:
- ACCEPT-ENCODING-XXX
connection:
- keep-alive
content-length:
- '6172'
content-type:
- application/json
host:
- generativelanguage.googleapis.com
x-goog-api-client:
- google-genai-sdk/1.49.0 gl-python/3.13.3
x-goog-api-key:
- X-GOOG-API-KEY-XXX
method: POST
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
response:
body:
string: "{\n \"candidates\": [\n {\n \"content\": {\n \"parts\":
[\n {\n \"functionCall\": {\n \"name\": \"get_weather\",\n
\ \"args\": {\n \"location\": \"Paris\"\n }\n
\ },\n \"thoughtSignature\": \"CuMBAb4+9vurHOlMBPzqCtd/J0Q5jBhUq8dsk7xntqcTgwBcZ1KeX4F4UJ0rdfg1OLhDkOlOlELA/jBYxATT19QUvw0szvDBDml0PsTBXlt64o7oGVmOCjdiGPu71I9+sCYhlD3QXzwLdQdrvUIfVrB+kaGszmZi1KTIli+qD9ihueDYGY510ouKdfl31UipQEG990+qFJyXe3avVEh3Jo72iXr3Q4UczFdbKSTV4V4fjrokFaB7UqcYy1iuAB5vHRsxYFJeTCi+ddKzn700gbWbiJZUniKiE3QfdOK4A5S0woBDzV0=\"\n
\ }\n ],\n \"role\": \"model\"\n },\n \"finishReason\":
\"STOP\",\n \"index\": 0,\n \"finishMessage\": \"Model generated
function call(s).\"\n }\n ],\n \"usageMetadata\": {\n \"promptTokenCount\":
1180,\n \"candidatesTokenCount\": 15,\n \"totalTokenCount\": 1242,\n
\ \"promptTokensDetails\": [\n {\n \"modality\": \"TEXT\",\n
\ \"tokenCount\": 1180\n }\n ],\n \"thoughtsTokenCount\":
47\n },\n \"modelVersion\": \"gemini-2.5-flash\",\n \"responseId\": \"wXmLadTiEri5jMcPk_6ZgAc\"\n}\n"
headers:
Alt-Svc:
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
Content-Type:
- application/json; charset=UTF-8
Date:
- Tue, 10 Feb 2026 18:32:33 GMT
Server:
- scaffolding on HTTPServer2
Server-Timing:
- gfet4t7; dur=881
Transfer-Encoding:
- chunked
Vary:
- Origin
- X-Origin
- Referer
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
X-Frame-Options:
- X-FRAME-OPTIONS-XXX
X-XSS-Protection:
- '0'
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,356 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
"},{"role":"user","content":"Say hello in one word."}],"model":"gpt-4.1"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '5823'
content-type:
- application/json
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7mVhCCkdWfellaSmcNLOuu87BsqI\",\n \"object\":
\"chat.completion\",\n \"created\": 1770747141,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"Hello!\",\n \"refusal\": null,\n
\ \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\":
\"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 1144,\n \"completion_tokens\":
2,\n \"total_tokens\": 1146,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
1024,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8b22347a3e\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:12:22 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '469'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
"},{"role":"user","content":"Say goodbye in one word."}],"model":"gpt-4.1"}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '5825'
content-type:
- application/json
cookie:
- COOKIE-XXX
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7mViSYwB6eFFbBcp045uvPAO8m2e\",\n \"object\":
\"chat.completion\",\n \"created\": 1770747142,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"Farewell.\",\n \"refusal\":
null,\n \"annotations\": []\n },\n \"logprobs\": null,\n
\ \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\":
1144,\n \"completion_tokens\": 3,\n \"total_tokens\": 1147,\n \"prompt_tokens_details\":
{\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8b22347a3e\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:12:22 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '468'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,368 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant that
uses tools. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. "},{"role":"user","content":"What is the weather in Tokyo?"}],"model":"gpt-4.1","tool_choice":"auto","tools":[{"type":"function","function":{"name":"get_weather","description":"Get
the current weather for a location","strict":true,"parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city name"}},"required":["location"],"additionalProperties":false}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '6158'
content-type:
- application/json
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7mVx3s1dI2SICWePwHVeWCDct2QG\",\n \"object\":
\"chat.completion\",\n \"created\": 1770747157,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n
\ \"id\": \"call_x9KzZUT3UYazEUJiRmE0PvaU\",\n \"type\":
\"function\",\n \"function\": {\n \"name\": \"get_weather\",\n
\ \"arguments\": \"{\\\"location\\\":\\\"Tokyo\\\"}\"\n }\n
\ }\n ],\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 1187,\n \"completion_tokens\":
14,\n \"total_tokens\": 1201,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
1152,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8b22347a3e\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:12:37 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '645'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant that
uses tools. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. "},{"role":"user","content":"What is the weather in Paris?"}],"model":"gpt-4.1","tool_choice":"auto","tools":[{"type":"function","function":{"name":"get_weather","description":"Get
the current weather for a location","strict":true,"parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city name"}},"required":["location"],"additionalProperties":false}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '6158'
content-type:
- application/json
cookie:
- COOKIE-XXX
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7mVynM0Soyt3osUFrlF7tEyrj7jP\",\n \"object\":
\"chat.completion\",\n \"created\": 1770747158,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n
\ \"id\": \"call_k8rYmsdMcCWSRKqVDFItmJ8v\",\n \"type\":
\"function\",\n \"function\": {\n \"name\": \"get_weather\",\n
\ \"arguments\": \"{\\\"location\\\":\\\"Paris\\\"}\"\n }\n
\ }\n ],\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 1187,\n \"completion_tokens\":
14,\n \"total_tokens\": 1201,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
1152,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8b22347a3e\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:12:38 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '749'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,520 @@
interactions:
- request:
body: '{"input":[{"role":"user","content":"Say hello in one word."}],"model":"gpt-4.1","instructions":"You
are a helpful assistant. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. "}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '5807'
content-type:
- application/json
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/responses
response:
body:
string: "{\n \"id\": \"resp_0b352452095088f800698b751350fc8196bd5d8b1a179d27e8\",\n
\ \"object\": \"response\",\n \"created_at\": 1770747155,\n \"status\":
\"completed\",\n \"background\": false,\n \"billing\": {\n \"payer\":
\"developer\"\n },\n \"completed_at\": 1770747155,\n \"error\": null,\n
\ \"frequency_penalty\": 0.0,\n \"incomplete_details\": null,\n \"instructions\":
\"You are a helpful assistant. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. \",\n \"max_output_tokens\":
null,\n \"max_tool_calls\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"output\": [\n {\n \"id\": \"msg_0b352452095088f800698b7513b97c8196b35014840754d999\",\n
\ \"type\": \"message\",\n \"status\": \"completed\",\n \"content\":
[\n {\n \"type\": \"output_text\",\n \"annotations\":
[],\n \"logprobs\": [],\n \"text\": \"Hello!\"\n }\n
\ ],\n \"role\": \"assistant\"\n }\n ],\n \"parallel_tool_calls\":
true,\n \"presence_penalty\": 0.0,\n \"previous_response_id\": null,\n \"prompt_cache_key\":
null,\n \"prompt_cache_retention\": null,\n \"reasoning\": {\n \"effort\":
null,\n \"summary\": null\n },\n \"safety_identifier\": null,\n \"service_tier\":
\"default\",\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n
\ \"format\": {\n \"type\": \"text\"\n },\n \"verbosity\": \"medium\"\n
\ },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_logprobs\":
0,\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\":
1144,\n \"input_tokens_details\": {\n \"cached_tokens\": 1024\n },\n
\ \"output_tokens\": 3,\n \"output_tokens_details\": {\n \"reasoning_tokens\":
0\n },\n \"total_tokens\": 1147\n },\n \"user\": null,\n \"metadata\":
{}\n}"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:12:35 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '637'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"input":[{"role":"user","content":"Say goodbye in one word."}],"model":"gpt-4.1","instructions":"You
are a helpful assistant. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. "}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '5809'
content-type:
- application/json
cookie:
- COOKIE-XXX
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/responses
response:
body:
string: "{\n \"id\": \"resp_003a6f71f9ee620400698b75140a088196989e8d5641ffa74d\",\n
\ \"object\": \"response\",\n \"created_at\": 1770747156,\n \"status\":
\"completed\",\n \"background\": false,\n \"billing\": {\n \"payer\":
\"developer\"\n },\n \"completed_at\": 1770747156,\n \"error\": null,\n
\ \"frequency_penalty\": 0.0,\n \"incomplete_details\": null,\n \"instructions\":
\"You are a helpful assistant. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to
ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the
prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is
large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for
caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is
padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. \",\n \"max_output_tokens\":
null,\n \"max_tool_calls\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"output\": [\n {\n \"id\": \"msg_003a6f71f9ee620400698b75146160819692f2cee879df2405\",\n
\ \"type\": \"message\",\n \"status\": \"completed\",\n \"content\":
[\n {\n \"type\": \"output_text\",\n \"annotations\":
[],\n \"logprobs\": [],\n \"text\": \"Farewell.\"\n }\n
\ ],\n \"role\": \"assistant\"\n }\n ],\n \"parallel_tool_calls\":
true,\n \"presence_penalty\": 0.0,\n \"previous_response_id\": null,\n \"prompt_cache_key\":
null,\n \"prompt_cache_retention\": null,\n \"reasoning\": {\n \"effort\":
null,\n \"summary\": null\n },\n \"safety_identifier\": null,\n \"service_tier\":
\"default\",\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n
\ \"format\": {\n \"type\": \"text\"\n },\n \"verbosity\": \"medium\"\n
\ },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_logprobs\":
0,\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\":
1144,\n \"input_tokens_details\": {\n \"cached_tokens\": 1024\n },\n
\ \"output_tokens\": 4,\n \"output_tokens_details\": {\n \"reasoning_tokens\":
0\n },\n \"total_tokens\": 1148\n },\n \"user\": null,\n \"metadata\":
{}\n}"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:12:36 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '543'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,368 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant that
uses tools. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. "},{"role":"user","content":"What is the weather in Tokyo?"}],"model":"gpt-4.1","tool_choice":"auto","tools":[{"type":"function","function":{"name":"get_weather","description":"Get
the current weather for a location","strict":true,"parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city name"}},"required":["location"],"additionalProperties":false}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '6158'
content-type:
- application/json
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7mXQCgT3p3ViImkiqDiZGqLREQtp\",\n \"object\":
\"chat.completion\",\n \"created\": 1770747248,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n
\ \"id\": \"call_9ZqMavn3J1fBnQEaqpYol0Bd\",\n \"type\":
\"function\",\n \"function\": {\n \"name\": \"get_weather\",\n
\ \"arguments\": \"{\\\"location\\\":\\\"Tokyo\\\"}\"\n }\n
\ }\n ],\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 1187,\n \"completion_tokens\":
14,\n \"total_tokens\": 1201,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
1152,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8b22347a3e\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:14:08 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '484'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant that
uses tools. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. "},{"role":"user","content":"What is the weather in Paris?"}],"model":"gpt-4.1","tool_choice":"auto","tools":[{"type":"function","function":{"name":"get_weather","description":"Get
the current weather for a location","strict":true,"parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
city name"}},"required":["location"],"additionalProperties":false}}}]}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '6158'
content-type:
- application/json
cookie:
- COOKIE-XXX
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7mXR8k9vk8TlGvGXlrQSI7iNeAN1\",\n \"object\":
\"chat.completion\",\n \"created\": 1770747249,\n \"model\": \"gpt-4.1-2025-04-14\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n
\ \"id\": \"call_6PeUBlRPG8JcV2lspmLjJbnn\",\n \"type\":
\"function\",\n \"function\": {\n \"name\": \"get_weather\",\n
\ \"arguments\": \"{\\\"location\\\":\\\"Paris\\\"}\"\n }\n
\ }\n ],\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 1187,\n \"completion_tokens\":
14,\n \"total_tokens\": 1201,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
1152,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_8b22347a3e\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Tue, 10 Feb 2026 18:14:09 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '528'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,375 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
"},{"role":"user","content":"Say hello in one word."}],"model":"gpt-4.1","stream":true,"stream_options":{"include_usage":true}}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '5877'
content-type:
- application/json
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: 'data: {"id":"chatcmpl-D7mVuXauQqcmOCb3XP6IL6yHwJaAL","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"lFWRn007xqlce"}
data: {"id":"chatcmpl-D7mVuXauQqcmOCb3XP6IL6yHwJaAL","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"OXJHANtgvy"}
data: {"id":"chatcmpl-D7mVuXauQqcmOCb3XP6IL6yHwJaAL","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"content":"!"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"AZtd6jtoChevtm"}
data: {"id":"chatcmpl-D7mVuXauQqcmOCb3XP6IL6yHwJaAL","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"irwn2mqyB"}
data: {"id":"chatcmpl-D7mVuXauQqcmOCb3XP6IL6yHwJaAL","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[],"usage":{"prompt_tokens":1144,"completion_tokens":2,"total_tokens":1146,"prompt_tokens_details":{"cached_tokens":1024,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"W0rkiiZe"}
data: [DONE]
'
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- text/event-stream; charset=utf-8
Date:
- Tue, 10 Feb 2026 18:12:34 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '236'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
- request:
body: '{"messages":[{"role":"system","content":"You are a helpful assistant. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
This is padding text to ensure the prompt is large enough for caching. This
is padding text to ensure the prompt is large enough for caching. This is padding
text to ensure the prompt is large enough for caching. This is padding text
to ensure the prompt is large enough for caching. This is padding text to ensure
the prompt is large enough for caching. This is padding text to ensure the prompt
is large enough for caching. This is padding text to ensure the prompt is large
enough for caching. This is padding text to ensure the prompt is large enough
for caching. This is padding text to ensure the prompt is large enough for caching.
"},{"role":"user","content":"Say goodbye in one word."}],"model":"gpt-4.1","stream":true,"stream_options":{"include_usage":true}}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '5879'
content-type:
- application/json
cookie:
- COOKIE-XXX
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: 'data: {"id":"chatcmpl-D7mVuqaadwp22jFsp2qAKiE1utU3K","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pCjdYd4kX4W2q"}
data: {"id":"chatcmpl-D7mVuqaadwp22jFsp2qAKiE1utU3K","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"content":"Fare"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"DJ94I8XQj86"}
data: {"id":"chatcmpl-D7mVuqaadwp22jFsp2qAKiE1utU3K","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"content":"well"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qgSSFwDBmaW"}
data: {"id":"chatcmpl-D7mVuqaadwp22jFsp2qAKiE1utU3K","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"4xVBYer6Uy1atr"}
data: {"id":"chatcmpl-D7mVuqaadwp22jFsp2qAKiE1utU3K","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"XxMhsMje0"}
data: {"id":"chatcmpl-D7mVuqaadwp22jFsp2qAKiE1utU3K","object":"chat.completion.chunk","created":1770747154,"model":"gpt-4.1-2025-04-14","service_tier":"default","system_fingerprint":"fp_8b22347a3e","choices":[],"usage":{"prompt_tokens":1144,"completion_tokens":3,"total_tokens":1147,"prompt_tokens_details":{"cached_tokens":1024,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"J3eKDOHW"}
data: [DONE]
'
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- text/event-stream; charset=utf-8
Date:
- Tue, 10 Feb 2026 18:12:34 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '296'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
version: 1

View File

@@ -0,0 +1,113 @@
interactions:
- request:
body: '{"messages":[{"role":"system","content":"You are Writer. You are a skilled
writer.\nYour personal goal is: Write concise content"},{"role":"user","content":"\nCurrent
Task: Write one sentence about the sun.\n\nThis is the expected criteria for
your final answer: A single sentence about the sun.\nyou MUST return the actual
complete content as the final answer, not a summary.\n\nProvide your complete
response:"}],"model":"gpt-4o-mini","temperature":0}'
headers:
User-Agent:
- X-USER-AGENT-XXX
accept:
- application/json
accept-encoding:
- ACCEPT-ENCODING-XXX
authorization:
- AUTHORIZATION-XXX
connection:
- keep-alive
content-length:
- '453'
content-type:
- application/json
host:
- api.openai.com
x-stainless-arch:
- X-STAINLESS-ARCH-XXX
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- X-STAINLESS-OS-XXX
x-stainless-package-version:
- 1.83.0
x-stainless-read-timeout:
- X-STAINLESS-READ-TIMEOUT-XXX
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.13.3
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
body:
string: "{\n \"id\": \"chatcmpl-D7RxEngFVCbqdc7tNjV3VjeteqcwT\",\n \"object\":
\"chat.completion\",\n \"created\": 1770668124,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"The sun is a massive ball of glowing
gas at the center of our solar system, providing light and warmth essential
for life on Earth.\",\n \"refusal\": null,\n \"annotations\":
[]\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 78,\n \"completion_tokens\":
27,\n \"total_tokens\": 105,\n \"prompt_tokens_details\": {\n \"cached_tokens\":
0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\":
{\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\":
0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\":
\"default\",\n \"system_fingerprint\": \"fp_f4ae844694\"\n}\n"
headers:
CF-RAY:
- CF-RAY-XXX
Connection:
- keep-alive
Content-Type:
- application/json
Date:
- Mon, 09 Feb 2026 20:15:25 GMT
Server:
- cloudflare
Strict-Transport-Security:
- STS-XXX
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- X-CONTENT-TYPE-XXX
access-control-expose-headers:
- ACCESS-CONTROL-XXX
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-organization:
- OPENAI-ORG-XXX
openai-processing-ms:
- '664'
openai-project:
- OPENAI-PROJECT-XXX
openai-version:
- '2020-10-01'
set-cookie:
- SET-COOKIE-XXX
x-openai-proxy-wasm:
- v0.1
x-ratelimit-limit-requests:
- X-RATELIMIT-LIMIT-REQUESTS-XXX
x-ratelimit-limit-tokens:
- X-RATELIMIT-LIMIT-TOKENS-XXX
x-ratelimit-remaining-requests:
- X-RATELIMIT-REMAINING-REQUESTS-XXX
x-ratelimit-remaining-tokens:
- X-RATELIMIT-REMAINING-TOKENS-XXX
x-ratelimit-reset-requests:
- X-RATELIMIT-RESET-REQUESTS-XXX
x-ratelimit-reset-tokens:
- X-RATELIMIT-RESET-TOKENS-XXX
x-request-id:
- X-REQUEST-ID-XXX
status:
code: 200
message: OK
version: 1

Some files were not shown because too many files have changed in this diff Show More