12 Commits

Author	SHA1	Message	Date
João Moura	bb477f8a91	JSON first crews (#6131) ... * feat(cli): introduce JSON crew project support and TUI enhancements - Added support for creating and running JSON-defined crew projects, allowing users to scaffold projects with a new `create_json_crew.py` file. - Implemented a full-screen Textual TUI for crew execution in `crew_run_tui.py`, enhancing user interaction with a two-column layout. - Updated `run_crew.py` to prioritize JSON crew projects and added daemon mode for running without TUI. - Introduced interactive pickers in `tui_picker.py` for improved CLI prompts. - Enhanced validation for JSON crew files in `validate.py` to ensure proper structure and agent definitions. - Updated `.gitignore` to exclude demo and crewai directories. * feat: update LLM model references to gpt-5.4-mini - Changed default LLM model from gpt-4o-mini to gpt-5.4-mini across various files, including CLI options, JSON crew configurations, and agent definitions. - Enhanced benchmark and human feedback functionalities to utilize the new model. - Improved user interface elements in the TUI for better interaction and feedback during execution. - Added support for new skills directory in JSON crew project creation. * feat(benchmark): add crew-level benchmarking functionality - Introduced a new `benchmark` command in the CLI for crew-level benchmarking, allowing users to specify agents, models, and timeout settings. - Implemented `CrewBenchmarkCase` to handle crew-level benchmark cases with inputs and criteria. - Enhanced the benchmark runner to support progress tracking and detailed reporting of results for multiple models. - Added tests for loading crew benchmark cases and validating their structure. - Updated existing benchmark functions to accommodate the new crew-level execution model. * feat(cli): enhance JSON crew project functionality and TUI improvements - Added optional agent-level guardrails and advanced options in JSON crew configurations to improve output validation and flexibility. - Updated the TUI to better handle plan step statuses, including visual indicators for task completion and failure. - Introduced methods for parsing and managing step observation events, ensuring accurate updates to task statuses during execution. - Enhanced validation for JSON crew projects, ensuring proper structure and error handling for agent and task definitions. - Added comprehensive tests for new features and validation logic, ensuring robustness in JSON crew project handling. * refactor(cli): streamline JSON crew project handling and improve validation - Refactored JSON crew project loading and validation logic to enhance clarity and maintainability. - Introduced utility functions for finding JSON crew files, improving code reuse across modules. - Removed deprecated benchmark functionality and associated tests to simplify the codebase. - Updated CLI commands to utilize the new JSON project structure, ensuring compatibility with recent changes. - Enhanced test coverage for JSON crew project features, ensuring robust validation and error handling. * feat(cli): enhance activity log navigation and focus management - Added functionality to focus on the activity log when navigating through log entries. - Implemented refresh logic for the log panel to ensure updates are displayed correctly during navigation. - Improved keyboard navigation for log entries, allowing users to expand and scroll through logs seamlessly. - Added tests to verify the correct behavior of log navigation and focus management in the TUI. * feat(cli): enhance JSON crew project interaction and input handling - Introduced a new function to enable prompt line editing for better user experience during input prompts. - Updated the JSON crew project wizards to show interpolation hints for dynamic values, improving user guidance. - Enhanced the handling of missing input placeholders by prompting users for required values during crew setup. - Refactored the crew run logic to ensure proper loading and preparation of JSON-defined crews, including runtime input management. - Added tests to verify the correct behavior of new input handling features and JSON crew project interactions. * feat(cli): improve crew project input prompts and event handling - Enhanced the `_prompt_text` function to allow for configurable spacing before prompts, improving user experience during input collection. - Updated the wizards for agent and task creation to utilize the new prompt configuration, ensuring a more compact and streamlined interaction. - Introduced new plan step lifecycle events (`PlanStepStartedEvent`, `PlanStepCompletedEvent`) to better track the execution status of plan steps. - Refactored the step executor to emit these events during the execution of tasks, improving observability and debugging capabilities. - Added tests to verify the correct behavior of new prompt handling and event emissions during crew project execution. * fix: refine json-first crew interactions * fix: prioritize common json crew tools * fix: make json crew more tools expandable * fix: show json crew tools by category * feat(memory): update default embedder to OpenAI text-embedding-3-large and enhance memory compatibility - Changed the default embedding model for Memory to OpenAI text-embedding-3-large, which uses 3072-dimensional vectors. - Added warnings regarding compatibility issues with existing local memory stores created with 1536-dimensional embeddings. - Updated documentation to reflect the new default embedder and its configuration options. - Enhanced the CLI and codebase to support the new embedding model across various components, ensuring a seamless transition for users. * fix: address PR review feedback for JSON-first crews Review blockers: - Forward trained_agents_file to JSON crews: crewai run -f now exports CREWAI_TRAINED_AGENTS_FILE for the in-process JSON crew path - Wizard agent picker: Esc/cancel now reprompts instead of silently assigning the first agent - JSON tool resolution hard-fails: unknown tool names, missing custom tool files, and invalid custom tool modules raise JSONProjectError with actionable messages instead of warn-and-continue - Embedding dimension mismatch: LanceDB and Qdrant Edge storages raise EmbeddingDimensionMismatchError with reset/pin guidance instead of silently zero-filling vectors or returning empty search results - Custom tool code execution documented in loader docstring and the scaffolded project README CI fixes: - ruff format across lib/ - All 133 PR-introduced mypy errors fixed (llm.py lazy-litellm and cli.py lazy command shims now use TYPE_CHECKING imports; textual is_mounted misuse fixed; pick_many overloads; misc annotations) Bot review comments: - Empty except blocks now have explanatory comments or debug logging - Removed unused _C_BG/_C_PANEL/_C_BORDER globals and redundant import re; tests use a single import style for create_json_crew Tests: trained-agents propagation, wizard cancel, tool resolution failures, and dimension mismatch guidance. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: address second round of PR review comments Cursor Bugbot: - Wizard agent slugs: strip to [a-z0-9_] and fall back to agent_<n> so symbol-only roles can't produce an empty agents/.jsonc filename - Wizard task names: dedupe against prior task names and fall back to task_<n> for symbol-only descriptions CodeRabbit: - Agent.message(): import Task explicitly at runtime instead of relying on the namespace injection done by crewai/__init__ - Async executor: move the native-tools-unsupported fallback from _ainvoke_loop_react (self-recursion) to _ainvoke_loop_native_tools, mirroring the sync implementation - StepExecutor downgrade: keep the in-step conversation and append the text-tooling instructions instead of rebuilding messages, so completed native tool calls are not re-executed - crewai-files: extension-based MIME lookup now runs before byte sniffing so csv/xml types are not degraded to text/plain - Memory storages: validate every record in a save() batch against a consistent embedding dimension (LanceDB previously checked only the first record); added mixed-batch tests - _print_post_tui_summary now typed against CrewRunApp - Docs: Azure OpenAI default embedder change called out in the memory migration warning and provider table Code quality bots: - Removed unused _C_YELLOW/_C_CYAN (crew_run_tui) and _GREEN (tui_picker) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * feat(cli): accordion tool picker in JSON crew wizard The flat tool list had grown to ~90 rows. The picker now shows: - Common tools always visible at the top - Every other category as a single expandable row with tool and selection counts (e.g. "Search & Research (27 tools, 2 selected)") - Expanding a category collapses the previously expanded one - Selections persist across expand/collapse via new preselected support in pick_many; cursor follows the toggled category row tui_picker gains preselected + initial_cursor options on pick_many, and Esc in multi-select now confirms the current selection instead of discarding it (required so collapsing can't silently drop choices). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor(cli): remove --daemon flag from crewai run The flag only affected JSON crew projects — classic and flow projects ignored it entirely, which made the behavior inconsistent. Removed the option, the daemon code path (_run_json_crew_daemon), and its helper (_load_json_crew_with_inputs). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: update run command tests after --daemon removal lib/crewai/tests/cli/test_run_crew.py still asserted the old run_crew(trained_agents_file=..., daemon=False) call signature. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(cli): exit codes, mid-run quit, async statuses, hyphen placeholders Addresses the latest Bugbot review round: - Failed JSON crew runs now exit non-zero (SystemExit(1)) so scripts and CI don't treat failures as success, mirroring the classic path - Quitting the TUI mid-run now ends the process (os._exit(130)); kickoff runs in a thread worker that cannot be force-cancelled, so letting the CLI return would leave LLM/tool work burning tokens in the background - Sidebar task statuses are now async-safe: completion/failure events resolve the task's own row via identity instead of assuming the most recently started task, and starting a task no longer blanket-marks earlier active rows as done - The runtime-input prompt regex now accepts hyphenated placeholder names ({my-topic}), matching kickoff's interpolation pattern Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: validation safety, custom tool sandboxing, TUI log integrity, memory error surfacing - Deploy validation no longer executes project code: validation mode checks tool declarations structurally (well-formed entries, custom tool file exists) without importing or instantiating anything. custom:<name> resolution only happens on the actual run path. - custom:<name> is constrained to [A-Za-z_][A-Za-z0-9_]* and the resolved path must stay inside the project's tools/ directory, so custom:../foo or absolute-path names cannot execute code outside it. Tool paths resolve relative to the crew project root, not cwd. - TUI task logs are built from per-task state captured at task start (idx, description, agent, start time); an out-of-order completion takes its output from the event and no longer steals or resets the current task's streamed steps/output. - EmbeddingDimensionMismatchError now inherits ValueError instead of RuntimeError so background saves surface it through MemorySaveFailedEvent instead of silently dropping the save; the shutdown catch in _background_encode_batch is narrowed to the "cannot schedule new futures" case. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(cli): declared project type wins over crew.json presence A flow project that also contains a crew.json(c) file now runs and validates as the flow it declares in pyproject.toml instead of being hijacked by the JSON crew path. Both crewai run (_has_json_crew) and deploy validation (_is_json_crew) check tool.crewai.type; a missing or unreadable pyproject still means a bare JSON crew project. Also documents why StepObservationFailedEvent intentionally marks the plan step "done": the event signals an observer failure, not a step failure, and the executor continues past it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(cli): type the declared_type locals so mypy stays clean Comparing an Any-typed .get() chain returns Any, which tripped no-any-return on the previous commit. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>	2026-06-14 04:19:48 -03:00
Vini Brasil	6ad821b157	Add expressions to FlowDefinition actions (#6145) ... * Add expressions to FlowDefinition actions Let definitions compute values without Python. A new `call: expression` action evaluates a Common Expression Language (CEL) expression, and tool `with:` blocks now render `${...}` CEL templates. Example 1: ```yaml decide: do: call: expression expr: "state.score >= 80 ? 'qualified' : 'nurture'" router: true emit: [qualified, nurture] ``` Example 2: ```yaml search: do: call: tool ref: my.pkg:SearchTool with: search_query: "${outputs.build_query.query + ' news'}" max_results: "${state.limit}" ``` * Address code review comments * Address code review comments * Fix linting offenses * Address code review comments * Fix scrapgraph issue	2026-06-12 21:56:02 -07:00
Vini Brasil	bf291a7a55	Drive human feedback from the flow definition (#6133) ... * Drive human feedback from the flow definition @human_feedback previously wrapped methods with the full HITL runtime (feedback request, outcome collapse, learn loop), so flows built from a YAML definition — which carry no decorated callables — could not pause for or route on human feedback. # Conflicts: # lib/crewai/src/crewai/flow/persistence/decorators.py # lib/crewai/src/crewai/flow/runtime/__init__.py * Address code review comments	2026-06-12 14:48:43 -07:00
Vini Brasil	051fa0c1cb	Build FlowDefinition from Flow DSL metadata (#6017) ... * Build FlowDefinition from Flow DSL metadata Introduce `FlowDefinition`, a serializable model built from the Flow DSL's runtime metadata. It becomes the structural contract for Flow methods, triggers, routers, state, and configuration. The visualization layer is the first consumer: `flow_structure` and `build_flow_structure` now project from the definition instead of re-introspecting the class. The runner still executes from live registries, but the definition gives future runners a single static contract to read. This replaces AST source parsing for router return values, crew references, and state schema with runtime metadata plus explicit `@router(paths=...)` or `Literal`/`Enum` return hints. AST parsing was fragile and could silently fail for dynamic or non-inspectable methods. The refactor removes obsolete introspection and serializer code: * Delete `flow_serializer.py`, `flow/utils.py`, and `visualization/schema.py` * Move flow structure modeling into `flow_definition.py` * Simplify visualization building around the static definition contract * Format files	2026-06-03 18:02:56 -03:00
Vini Brasil	1aba9fe415	Split flow.py into DSL, definition, and runtime (#5997) ... This commit separates the monolithic `flow.py` into three modules, each with one job: - `dsl.py` - the Python DSL for flows (@start/@listen/@router, or_/and_) - `flow_definition.py` - the structural model extracted from the DSL - `runtime.py` - the execution engine and state for flows This phase moves code only and should not have any breaking changes.	2026-06-01 18:37:10 -03:00
Greyson LaLonde	fd10c64148	chore(crewai): drop self-explanatory comments	2026-05-26 10:23:33 -07:00
Greyson LaLonde	d6714a0e60	refactor: convert Flow to Pydantic BaseModel	2026-04-01 03:48:41 +08:00
Lorenze Jay	85199e9ffc	better serialization for human feedback in flow with models defined a… (#5029) ... * better serialization for human feedback in flow with models defined as dicts * linted * linted * fix and adjust tests	2026-03-23 14:43:43 -07:00
alex-clawd	09b84dd2b0	fix: preserve full LLM config across HITL resume for non-OpenAI providers (#4970) ... When a flow with @human_feedback(llm=create_llm()) pauses for HITL and later resumes: 1. The LLM object was being serialized to just a model string via _serialize_llm_for_context() (e.g. 'gemini/gemini-3.1-flash-lite-preview') 2. On resume, resume_async() was creating LLM(model=string) with NO credentials, project, location, safety_settings, or client_params 3. OpenAI worked by accident (OPENAI_API_KEY from env), but Gemini with service accounts broke This fix: - Stashes the live LLM object on the wrapper as _hf_llm attribute - On resume, looks up the method and retrieves the live LLM if available - Falls back to the serialized string for backward compatibility - Preserves _hf_llm through FlowMethod wrapper decorators Co-authored-by: Joao Moura <joao@crewai.com> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>	2026-03-20 18:42:28 -03:00
João Moura	6235810844	fix: enhance LLM response handling and serialization (#4909) ... * fix: enhance LLM response handling and serialization * Updated the Flow class to improve error handling when both structured and simple prompting fail, ensuring the first outcome is returned as a fallback. * Introduced a new function, _serialize_llm_for_context, to properly serialize LLM objects with provider prefixes for better context management. * Added tests to validate the new serialization logic and ensure correct behavior when LLM calls fail. This update enhances the robustness of LLM interactions and improves the overall flow of handling outcomes. * fix: patch VCR response handling to prevent httpx.ResponseNotRead errors (#4917) * fix: enhance LLM response handling and serialization * Updated the Flow class to improve error handling when both structured and simple prompting fail, ensuring the first outcome is returned as a fallback. * Introduced a new function, _serialize_llm_for_context, to properly serialize LLM objects with provider prefixes for better context management. * Added tests to validate the new serialization logic and ensure correct behavior when LLM calls fail. This update enhances the robustness of LLM interactions and improves the overall flow of handling outcomes. * fix: patch VCR response handling to prevent httpx.ResponseNotRead errors VCR's _from_serialized_response mocks httpx.Response.read(), which prevents the response's internal _content attribute from being properly initialized. When OpenAI's client (using with_raw_response) accesses response.content, httpx raises ResponseNotRead. This patch explicitly sets response._content after the response is created, ensuring that tests using VCR cassettes work correctly with the OpenAI client's raw response handling. Fixes tests: - test_hierarchical_crew_creation_tasks_with_sync_last - test_conditional_task_last_task_when_conditional_is_false - test_crew_log_file_output Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> --------- Co-authored-by: Joao Moura <joaomdmoura@gmail.com> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> --------- Co-authored-by: alex-clawd <alex@crewai.com> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>	2026-03-17 05:19:31 -03:00
João Moura	f070ce8abd	fix: update llm parameter handling in human_feedback function (#4801) ... Modified the llm parameter assignment to retrieve the model attribute from llm if it is not a string, ensuring compatibility with different llm types.	2026-03-10 14:27:09 -03:00
João Moura	c73b36a4c5	Adding HITL for Flows (#4143) ... * feat: introduce human feedback events and decorator for flow methods - Added HumanFeedbackRequestedEvent and HumanFeedbackReceivedEvent classes to handle human feedback interactions within flows. - Implemented the @human_feedback decorator to facilitate human-in-the-loop workflows, allowing for feedback collection and routing based on responses. - Enhanced Flow class to store human feedback history and manage feedback outcomes. - Updated flow wrappers to preserve attributes from methods decorated with @human_feedback. - Added integration and unit tests for the new human feedback functionality, ensuring proper validation and routing behavior. * adding deployment docs * New docs * fix printer * wrong change * Adding Async Support feat: enhance human feedback support in flows - Updated the @human_feedback decorator to use 'message' parameter instead of 'request' for clarity. - Introduced new FlowPausedEvent and MethodExecutionPausedEvent to handle flow and method pauses during human feedback. - Added ConsoleProvider for synchronous feedback collection and integrated async feedback capabilities. - Implemented SQLite persistence for managing pending feedback context. - Expanded documentation to include examples of async human feedback usage and best practices. * linter * fix * migrating off printer * updating docs * new tests * doc update	2025-12-25 21:04:10 -03:00