andre/crewAI
1
0
Fork 0
mirror of https://github.com/crewAIInc/crewAI.git synced 2026-01-09 16:18:30 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity
Files
Canary-Crew-Github-Action-
crewAI/tests/cassettes/test_using_contextual_memory.yaml
Lorenze Jay 7addda9398
Some checks failed
Notify Downstream / notify-downstream (push) Has been cancelled
Details
Lorenze/better tracing events (#3382) 
* feat: implement tool usage limit exception handling

- Introduced `ToolUsageLimitExceeded` exception to manage maximum usage limits for tools.
- Enhanced `CrewStructuredTool` to check and raise this exception when the usage limit is reached.
- Updated `_run` and `_execute` methods to include usage limit checks and handle exceptions appropriately, improving reliability and user feedback.

* feat: enhance PlusAPI and ToolUsage with task metadata

- Removed the `send_trace_batch` method from PlusAPI to streamline the API.
- Added timeout parameters to trace event methods in PlusAPI for improved reliability.
- Updated ToolUsage to include task metadata (task name and ID) in event emissions, enhancing traceability and context during tool usage.
- Refactored event handling in LLM and ToolUsage events to ensure task information is consistently captured.

* feat: enhance memory and event handling with task and agent metadata

- Added task and agent metadata to various memory and event classes, improving traceability and context during memory operations.
- Updated the `ContextualMemory` and `Memory` classes to associate tasks and agents, allowing for better context management.
- Enhanced event emissions in `LLM`, `ToolUsage`, and memory events to include task and agent information, facilitating improved debugging and monitoring.
- Refactored event handling to ensure consistent capture of task and agent details across the system.

* drop

* refactor: clean up unused imports in memory and event modules

- Removed unused TYPE_CHECKING imports from long_term_memory.py to streamline the code.
- Eliminated unnecessary import from memory_events.py, enhancing clarity and maintainability.

* fix memory tests

* fix task_completed payload

* fix: remove unused test agent variable in external memory tests

* refactor: remove unused agent parameter from Memory class save method

- Eliminated the agent parameter from the save method in the Memory class to streamline the code and improve clarity.
- Updated the TraceBatchManager class by moving initialization of attributes into the constructor for better organization and readability.

* refactor: enhance ExecutionState and ReasoningEvent classes with optional task and agent identifiers

- Added optional `current_agent_id` and `current_task_id` attributes to the `ExecutionState` class for better tracking of agent and task states.
- Updated the `from_task` attribute in the `ReasoningEvent` class to use `Optional[Any]` instead of a specific type, improving flexibility in event handling.

* refactor: update ExecutionState class by removing unused agent and task identifiers

- Removed the `current_agent_id` and `current_task_id` attributes from the `ExecutionState` class to simplify the code and enhance clarity.
- Adjusted the import statements to include `Optional` for better type handling.

* refactor: streamline LLM event handling in LiteAgent

- Removed unused LLM event emissions (LLMCallStartedEvent, LLMCallCompletedEvent, LLMCallFailedEvent) from the LiteAgent class to simplify the code and improve performance.
- Adjusted the flow of LLM response handling by eliminating unnecessary event bus interactions, enhancing clarity and maintainability.

* flow ownership and not emitting events when a crew is done

* refactor: remove unused agent parameter from ShortTermMemory save method

- Eliminated the agent parameter from the save method in the ShortTermMemory class to streamline the code and improve clarity.
- This change enhances the maintainability of the memory management system by reducing unnecessary complexity.

* runtype check fix

* fixing tests

* fix lints

* fix: update event assertions in test_llm_emits_event_with_lite_agent

- Adjusted the expected counts for completed and started events in the test to reflect the correct behavior of the LiteAgent.
- Updated assertions for agent roles and IDs to match the expected values after recent changes in event handling.

* fix: update task name assertions in event tests

- Modified assertions in `test_stream_llm_emits_event_with_task_and_agent_info` and `test_llm_emits_event_with_task_and_agent_info` to use `task.description` as a fallback for `task.name`. This ensures that the tests correctly validate the task name even when it is not explicitly set.

* fix: update test assertions for output values and improve readability

- Updated assertions in `test_output_json_dict_hierarchical` to reflect the correct expected score value.
- Enhanced readability of assertions in `test_output_pydantic_to_another_task` and `test_key` by formatting the error messages for clarity.
- These changes ensure that the tests accurately validate the expected outputs and improve overall code quality.

* test fixes

* fix crew_test

* added another fixture

* fix: ensure agent and task assignments in contextual memory are conditional

- Updated the ContextualMemory class to check for the existence of short-term, long-term, external, and extended memory before assigning agent and task attributes. This prevents potential attribute errors when memory types are not initialized.
2025-08-26 09:09:46 -07:00

1671 lines
90 KiB
YAML
Raw Permalink Blame History

interactions:
- request:
body: !!binary |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headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '2241'
Content-Type:
- application/x-protobuf
User-Agent:
- OTel-OTLP-Exporter-Python/1.27.0
method: POST
uri: https://telemetry.crewai.com:4319/v1/traces
response:
body:
string: "\n\0"
headers:
Content-Length:
- '2'
Content-Type:
- application/x-protobuf
Date:
- Tue, 24 Sep 2024 21:45:01 GMT
status:
code: 200
message: OK
- request:
body: '{"messages": [{"role": "system", "content": "You are Researcher. You''re
an expert in research and you love to learn new things.\nYour personal goal
is: You research about math.\nTo give my best complete final answer to the task
use 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: Research a topic to teach
a kid aged 6 about math.\n\nThis is the expect criteria for your final answer:
A topic, explanation, angle, and examples.\nyou MUST return the actual complete
content as the final answer, not a summary.\n\n# Useful context: \n<MagicMock
name=''build_context_for_task()'' id=''6251497744''>\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"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate
connection:
- keep-alive
content-length:
- '985'
content-type:
- application/json
cookie:
- __cf_bm=9.8sBYBkvBR8R1K_bVF7xgU..80XKlEIg3N2OBbTSCU-1727214102-1.0.1.1-.qiTLXbPamYUMSuyNsOEB9jhGu.jOifujOrx9E2JZvStbIZ9RTIiE44xKKNfLPxQkOi6qAT3h6htK8lPDGV_5g;
_cfuvid=lbRdAddVWV6W3f5Dm9SaOPWDUOxqtZBSPr_fTW26nEA-1727213194587-0.0.1.1-604800000
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.47.0
x-stainless-arch:
- arm64
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
x-stainless-package-version:
- 1.47.0
x-stainless-raw-response:
- 'true'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.11.7
method: POST
uri: https://api.openai.com/v1/chat/completions
response:
content: "{\n \"id\": \"chatcmpl-AB7d4BrARnIWeNI7ngTDSTGu9XBPA\",\n \"object\":
\"chat.completion\",\n \"created\": 1727214298,\n \"model\": \"gpt-4o-2024-05-13\",\n
\ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\":
\"assistant\",\n \"content\": \"I now can give a great answer.\\nFinal
Answer: \\n**Topic**: Basic Addition\\n\\n**Explanation**:\\nAddition is a fundamental
concept in math that means combining two or more numbers to get a new total.
It's like putting together pieces of a puzzle to see the whole picture. When
we add, we take two or more groups of things and count them all together.\\n\\n**Angle**:\\nUse
relatable and engaging real-life scenarios to illustrate addition, making it
fun and easier for a 6-year-old to understand and apply.\\n\\n**Examples**:\\n\\n1.
**Counting Apples**:\\n Let's say you have 2 apples and your friend gives
you 3 more apples. How many apples do you have in total?\\n - You start with
2 apples.\\n - Your friend gives you 3 more apples.\\n - Now, you count
all the apples together: 2 + 3 = 5.\\n - So, you have 5 apples in total.\\n\\n2.
**Toy Cars**:\\n Imagine you have 4 toy cars and you find 2 more toy cars
in your room. How many toy cars do you have now?\\n - You start with 4 toy
cars.\\n - You find 2 more toy cars.\\n - You count them all together: 4
+ 2 = 6.\\n - So, you have 6 toy cars in total.\\n\\n3. **Drawing Pictures**:\\n
\ If you draw 3 pictures today and 2 pictures tomorrow, how many pictures will
you have drawn in total?\\n - You draw 3 pictures today.\\n - You draw 2
pictures tomorrow.\\n - You add them together: 3 + 2 = 5.\\n - So, you will
have drawn 5 pictures in total.\\n\\n4. **Using Fingers**:\\n Let's use your
fingers to practice addition. Show 3 fingers on one hand and 1 finger on the
other hand. How many fingers are you holding up?\\n - 3 fingers on one hand.\\n
\ - 1 finger on the other hand.\\n - Put them together and count: 3 + 1 =
4.\\n - So, you are holding up 4 fingers.\\n\\nBy using objects that kids
are familiar with, such as apples, toy cars, drawings, and even their own fingers,
we can make the concept of addition relatable and enjoyable. Practicing with
real items helps children visualize the math and understand that addition is
simply combining groups to find out how many there are altogether.\",\n \"refusal\":
null\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n
\ }\n ],\n \"usage\": {\n \"prompt_tokens\": 205,\n \"completion_tokens\":
511,\n \"total_tokens\": 716,\n \"completion_tokens_details\": {\n \"reasoning_tokens\":
0\n }\n },\n \"system_fingerprint\": \"fp_3537616b13\"\n}\n"
headers:
CF-Cache-Status:
- DYNAMIC
CF-RAY:
- 8c85f5764a851cf3-GRU
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Tue, 24 Sep 2024 21:45:06 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-expose-headers:
- X-Request-ID
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '7751'
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '30000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '29999765'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_2ac1e3cef69e9b09b7ade0e1d010fc08
http_version: HTTP/1.1
status_code: 200
- request:
body: '{"input": ["I now can give a great answer. Final Answer: **Topic**: Basic
Addition **Explanation**: Addition is a fundamental concept in math that means
combining two or more numbers to get a new total. It''s like putting together
pieces of a puzzle to see the whole picture. When we add, we take two or more
groups of things and count them all together. **Angle**: Use relatable and
engaging real-life scenarios to illustrate addition, making it fun and easier
for a 6-year-old to understand and apply. **Examples**: 1. **Counting Apples**: Let''s
say you have 2 apples and your friend gives you 3 more apples. How many apples
do you have in total? - You start with 2 apples. - Your friend gives you
3 more apples. - Now, you count all the apples together: 2 + 3 = 5. -
So, you have 5 apples in total. 2. **Toy Cars**: Imagine you have 4 toy
cars and you find 2 more toy cars in your room. How many toy cars do you have
now? - You start with 4 toy cars. - You find 2 more toy cars. - You
count them all together: 4 + 2 = 6. - So, you have 6 toy cars in total. 3.
**Drawing Pictures**: If you draw 3 pictures today and 2 pictures tomorrow,
how many pictures will you have drawn in total? - You draw 3 pictures today. -
You draw 2 pictures tomorrow. - You add them together: 3 + 2 = 5. - So,
you will have drawn 5 pictures in total. 4. **Using Fingers**: Let''s use
your fingers to practice addition. Show 3 fingers on one hand and 1 finger on
the other hand. How many fingers are you holding up? - 3 fingers on one hand. -
1 finger on the other hand. - Put them together and count: 3 + 1 = 4. -
So, you are holding up 4 fingers. By using objects that kids are familiar with,
such as apples, toy cars, drawings, and even their own fingers, we can make
the concept of addition relatable and enjoyable. Practicing with real items
helps children visualize the math and understand that addition is simply combining
groups to find out how many there are altogether."], "model": "text-embedding-3-small",
"encoding_format": "base64"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '2092'
content-type:
- application/json
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-read-timeout:
- '600'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |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headers:
CF-RAY:
- 94f4c6967c75fb3c-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Fri, 13 Jun 2025 21:45:35 GMT
Server:
- cloudflare
Set-Cookie:
- __cf_bm=I11FOm0L.OsIzhpXscunzNqcbLqgXE1LlRgqtNWazAs-1749851135-1.0.1.1-R2n01WWaBpL_jzTwLFUo8WNM2u_1OD78QDkM9lSQoM9Av669lg1O9RgxK.Eew7KQ1MP_oJ9WkD408NuNCPwFcLRzX8TqwMNow5Gb_N1LChY;
path=/; expires=Fri, 13-Jun-25 22:15:35 GMT; domain=.api.openai.com; HttpOnly;
Secure; SameSite=None
- _cfuvid=TSYyYzslZUaIRAy.2QeTpFy6uf5Di7f.JM5ndpSEYhs-1749851135188-0.0.1.1-604800000;
path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-allow-origin:
- '*'
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-model:
- text-embedding-3-small
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '76'
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
via:
- envoy-router-86bb9759f6-ksq4x
x-envoy-upstream-service-time:
- '80'
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '10000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '9999496'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 3ms
x-request-id:
- req_335974d1e85d40d312fb1989e3b2ade5
status:
code: 200
message: OK
- request:
body: '{"messages": [{"role": "user", "content": "Assess the quality of the task
completed based on the description, expected output, and actual results.\n\nTask
Description:\nResearch a topic to teach a kid aged 6 about math.\n\nExpected
Output:\nA topic, explanation, angle, and examples.\n\nActual Output:\nI now
can give a great answer.\nFinal Answer: \n**Topic**: Basic Addition\n\n**Explanation**:\nAddition
is a fundamental concept in math that means combining two or more numbers to
get a new total. It''s like putting together pieces of a puzzle to see the whole
picture. When we add, we take two or more groups of things and count them all
together.\n\n**Angle**:\nUse relatable and engaging real-life scenarios to illustrate
addition, making it fun and easier for a 6-year-old to understand and apply.\n\n**Examples**:\n\n1.
**Counting Apples**:\n Let''s say you have 2 apples and your friend gives
you 3 more apples. How many apples do you have in total?\n - You start with
2 apples.\n - Your friend gives you 3 more apples.\n - Now, you count all
the apples together: 2 + 3 = 5.\n - So, you have 5 apples in total.\n\n2.
**Toy Cars**:\n Imagine you have 4 toy cars and you find 2 more toy cars in
your room. How many toy cars do you have now?\n - You start with 4 toy cars.\n -
You find 2 more toy cars.\n - You count them all together: 4 + 2 = 6.\n -
So, you have 6 toy cars in total.\n\n3. **Drawing Pictures**:\n If you draw
3 pictures today and 2 pictures tomorrow, how many pictures will you have drawn
in total?\n - You draw 3 pictures today.\n - You draw 2 pictures tomorrow.\n -
You add them together: 3 + 2 = 5.\n - So, you will have drawn 5 pictures in
total.\n\n4. **Using Fingers**:\n Let''s use your fingers to practice addition.
Show 3 fingers on one hand and 1 finger on the other hand. How many fingers
are you holding up?\n - 3 fingers on one hand.\n - 1 finger on the other
hand.\n - Put them together and count: 3 + 1 = 4.\n - So, you are holding
up 4 fingers.\n\nBy using objects that kids are familiar with, such as apples,
toy cars, drawings, and even their own fingers, we can make the concept of addition
relatable and enjoyable. Practicing with real items helps children visualize
the math and understand that addition is simply combining groups to find out
how many there are altogether.\n\nPlease provide:\n- Bullet points suggestions
to improve future similar tasks\n- A score from 0 to 10 evaluating on completion,
quality, and overall performance- Entities extracted from the task output, if
any, their type, description, and relationships"}], "model": "gpt-4o-mini",
"tool_choice": {"type": "function", "function": {"name": "TaskEvaluation"}},
"tools": [{"type": "function", "function": {"name": "TaskEvaluation", "description":
"Correctly extracted `TaskEvaluation` with all the required parameters with
correct types", "parameters": {"$defs": {"Entity": {"properties": {"name": {"description":
"The name of the entity.", "title": "Name", "type": "string"}, "type": {"description":
"The type of the entity.", "title": "Type", "type": "string"}, "description":
{"description": "Description of the entity.", "title": "Description", "type":
"string"}, "relationships": {"description": "Relationships of the entity.",
"items": {"type": "string"}, "title": "Relationships", "type": "array"}}, "required":
["name", "type", "description", "relationships"], "title": "Entity", "type":
"object"}}, "properties": {"suggestions": {"description": "Suggestions to improve
future similar tasks.", "items": {"type": "string"}, "title": "Suggestions",
"type": "array"}, "quality": {"description": "A score from 0 to 10 evaluating
on completion, quality, and overall performance, all taking into account the
task description, expected output, and the result of the task.", "title": "Quality",
"type": "number"}, "entities": {"description": "Entities extracted from the
task output.", "items": {"$ref": "#/$defs/Entity"}, "title": "Entities", "type":
"array"}}, "required": ["entities", "quality", "suggestions"], "type": "object"}}}]}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '4092'
content-type:
- application/json
cookie:
- _cfuvid=63wmKMTuFamkLN8FBI4fP8JZWbjWiRxWm7wb3kz.z_A-1735447412038-0.0.1.1-604800000
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: !!binary |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=
headers:
CF-RAY:
- 94f4c6a1cf5afb44-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Fri, 13 Jun 2025 21:45:40 GMT
Server:
- cloudflare
Set-Cookie:
- __cf_bm=RNxOcvndh1ViOpBviaCq8vg2oE59_B32cF84QEfAM8M-1749851140-1.0.1.1-161vq6SqDcfIu41VKaJdjmGjwyhGQ3AyY0VDnfk1SUfufmIewYKYnNufCV49o2gCDVOzInyRnwwp3.Sk2rj9DoDtAbcdOdEHxpr34JvDa8w;
path=/; expires=Fri, 13-Jun-25 22:15:40 GMT; domain=.api.openai.com; HttpOnly;
Secure; SameSite=None
- _cfuvid=uF44YidguuLD6X0Fw3uiyzdru2Ad2jXf2Nx1M4V87qI-1749851140865-0.0.1.1-604800000;
path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
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:
- '4149'
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
x-envoy-upstream-service-time:
- '4154'
x-ratelimit-limit-requests:
- '30000'
x-ratelimit-limit-tokens:
- '150000000'
x-ratelimit-remaining-requests:
- '29999'
x-ratelimit-remaining-tokens:
- '149999368'
x-ratelimit-reset-requests:
- 2ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_437679f0db60c9eec6bbdf32d399f960
status:
code: 200
message: OK
- request:
body: '{"input": ["Example: Counting Apples(Math Example): An example used to
explain basic addition by counting physical objects, apples in this case."],
"model": "text-embedding-3-small", "encoding_format": "base64"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '211'
content-type:
- application/json
cookie:
- __cf_bm=I11FOm0L.OsIzhpXscunzNqcbLqgXE1LlRgqtNWazAs-1749851135-1.0.1.1-R2n01WWaBpL_jzTwLFUo8WNM2u_1OD78QDkM9lSQoM9Av669lg1O9RgxK.Eew7KQ1MP_oJ9WkD408NuNCPwFcLRzX8TqwMNow5Gb_N1LChY;
_cfuvid=TSYyYzslZUaIRAy.2QeTpFy6uf5Di7f.JM5ndpSEYhs-1749851135188-0.0.1.1-604800000
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-read-timeout:
- '600'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |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headers:
CF-RAY:
- 94f4c6bed82cfac6-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Fri, 13 Jun 2025 21:45:41 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-allow-origin:
- '*'
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-model:
- text-embedding-3-small
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '457'
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
via:
- envoy-router-6c6c4dc575-7ps9v
x-envoy-upstream-service-time:
- '459'
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '10000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '9999967'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_eba1229193b2c4c623e7661cac3bec77
status:
code: 200
message: OK
- request:
body: '{"input": ["Example: Drawing Pictures(Math Example): An example that combines
art and math to explain addition with pictures."], "model": "text-embedding-3-small",
"encoding_format": "base64"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '192'
content-type:
- application/json
cookie:
- __cf_bm=I11FOm0L.OsIzhpXscunzNqcbLqgXE1LlRgqtNWazAs-1749851135-1.0.1.1-R2n01WWaBpL_jzTwLFUo8WNM2u_1OD78QDkM9lSQoM9Av669lg1O9RgxK.Eew7KQ1MP_oJ9WkD408NuNCPwFcLRzX8TqwMNow5Gb_N1LChY;
_cfuvid=TSYyYzslZUaIRAy.2QeTpFy6uf5Di7f.JM5ndpSEYhs-1749851135188-0.0.1.1-604800000
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-read-timeout:
- '600'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |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headers:
CF-RAY:
- 94f4c6c3be7efac6-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Fri, 13 Jun 2025 21:45:42 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-allow-origin:
- '*'
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-model:
- text-embedding-3-small
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '128'
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
via:
- envoy-router-675c5bcfc8-v6fpw
x-envoy-upstream-service-time:
- '131'
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '10000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '9999972'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_7f9985e9b536960af27b96d0fd747fbb
status:
code: 200
message: OK
- request:
body: '{"input": ["Example: Toy Cars(Math Example): An example used to illustrate
addition by counting toy cars."], "model": "text-embedding-3-small", "encoding_format":
"base64"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '172'
content-type:
- application/json
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.93.0
x-stainless-arch:
- arm64
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
x-stainless-package-version:
- 1.93.0
x-stainless-read-timeout:
- '600'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |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headers:
CF-RAY:
- 974f08951aa4251c-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Mon, 25 Aug 2025 23:57:45 GMT
Server:
- cloudflare
Set-Cookie:
- __cf_bm=L28ZVHkSMOSpzu9MoQzdDgOYGHI9uQZnBcGj5Txg9e8-1756166265-1.0.1.1-9494dtPfVD9FwZG8RVJ6EnsQqAuzb2nnmeyRQLpPrX5IK2bR3KadJFV3K8HTAJa0lU9lIhCtu4fezMScnlMYOGAO0zGsIWMyozgrpePziWg;
path=/; expires=Tue, 26-Aug-25 00:27:45 GMT; domain=.api.openai.com; HttpOnly;
Secure; SameSite=None
- _cfuvid=NaNzk_g04ozIFjR4zD0Joz9IJWntjKPTzifJUuegmAo-1756166265356-0.0.1.1-604800000;
path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-allow-origin:
- '*'
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-model:
- text-embedding-3-small
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '69'
openai-project:
- proj_xitITlrFeen7zjNSzML82h9x
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
via:
- envoy-router-74b9c68cd4-sld2z
x-envoy-upstream-service-time:
- '183'
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '10000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '9999977'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_f779ba78781c452aa13e52ea0ca6a682
status:
code: 200
message: OK
- request:
body: '{"input": ["Example: Using Fingers(Math Example): An interactive way to
teach addition using fingers as counting tools."], "model": "text-embedding-3-small",
"encoding_format": "base64"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '186'
content-type:
- application/json
cookie:
- __cf_bm=L28ZVHkSMOSpzu9MoQzdDgOYGHI9uQZnBcGj5Txg9e8-1756166265-1.0.1.1-9494dtPfVD9FwZG8RVJ6EnsQqAuzb2nnmeyRQLpPrX5IK2bR3KadJFV3K8HTAJa0lU9lIhCtu4fezMScnlMYOGAO0zGsIWMyozgrpePziWg;
_cfuvid=NaNzk_g04ozIFjR4zD0Joz9IJWntjKPTzifJUuegmAo-1756166265356-0.0.1.1-604800000
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.93.0
x-stainless-arch:
- arm64
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
x-stainless-package-version:
- 1.93.0
x-stainless-read-timeout:
- '600'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |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headers:
CF-RAY:
- 974f0896accb251c-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Mon, 25 Aug 2025 23:57:45 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-allow-origin:
- '*'
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-model:
- text-embedding-3-small
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '86'
openai-project:
- proj_xitITlrFeen7zjNSzML82h9x
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
via:
- envoy-router-74b9c68cd4-l7mvz
x-envoy-upstream-service-time:
- '120'
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '10000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '9999974'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_3118ad98ecf3443a93df58599e50e305
status:
code: 200
message: OK
- request:
body: '{"input": ["Example: Using Fingers(Math Example): An interactive way to
teach addition using fingers as counting tools."], "model": "text-embedding-3-small",
"encoding_format": "base64"}'
headers:
accept:
- application/json
accept-encoding:
- gzip, deflate, zstd
connection:
- keep-alive
content-length:
- '186'
content-type:
- application/json
cookie:
- __cf_bm=L28ZVHkSMOSpzu9MoQzdDgOYGHI9uQZnBcGj5Txg9e8-1756166265-1.0.1.1-9494dtPfVD9FwZG8RVJ6EnsQqAuzb2nnmeyRQLpPrX5IK2bR3KadJFV3K8HTAJa0lU9lIhCtu4fezMScnlMYOGAO0zGsIWMyozgrpePziWg;
_cfuvid=NaNzk_g04ozIFjR4zD0Joz9IJWntjKPTzifJUuegmAo-1756166265356-0.0.1.1-604800000
host:
- api.openai.com
user-agent:
- OpenAI/Python 1.93.0
x-stainless-arch:
- arm64
x-stainless-async:
- 'false'
x-stainless-lang:
- python
x-stainless-os:
- MacOS
x-stainless-package-version:
- 1.93.0
x-stainless-read-timeout:
- '600'
x-stainless-retry-count:
- '0'
x-stainless-runtime:
- CPython
x-stainless-runtime-version:
- 3.12.9
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |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headers:
CF-RAY:
- 974f1417bd93ed39-SJC
Connection:
- keep-alive
Content-Encoding:
- gzip
Content-Type:
- application/json
Date:
- Tue, 26 Aug 2025 00:05:36 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
X-Content-Type-Options:
- nosniff
access-control-allow-origin:
- '*'
access-control-expose-headers:
- X-Request-ID
alt-svc:
- h3=":443"; ma=86400
cf-cache-status:
- DYNAMIC
openai-model:
- text-embedding-3-small
openai-organization:
- crewai-iuxna1
openai-processing-ms:
- '67'
openai-project:
- proj_xitITlrFeen7zjNSzML82h9x
openai-version:
- '2020-10-01'
strict-transport-security:
- max-age=31536000; includeSubDomains; preload
via:
- envoy-router-6855f85975-l2j69
x-envoy-upstream-service-time:
- '85'
x-ratelimit-limit-requests:
- '10000'
x-ratelimit-limit-tokens:
- '10000000'
x-ratelimit-remaining-requests:
- '9999'
x-ratelimit-remaining-tokens:
- '9999974'
x-ratelimit-reset-requests:
- 6ms
x-ratelimit-reset-tokens:
- 0s
x-request-id:
- req_415fc597e216418bba813b4bb2f0e130
status:
code: 200
message: OK
version: 1
Reference in New Issue View Git Blame Copy Permalink