Implements native support for OpenAI's Responses API (/v1/responses) as a new
LLM provider in CrewAI. This addresses feature request #4152.
Key features:
- New OpenAIResponsesCompletion class extending BaseLLM
- Support for both explicit provider parameter and model prefix routing
- Message conversion from CrewAI format to Responses API format
- Tool/function calling support
- Streaming support (sync and async)
- Structured output via Pydantic models
- Token usage tracking
- Support for o-series reasoning models with reasoning_effort parameter
- Support for stateful conversations via previous_response_id
Usage:
# Option 1: Using provider parameter
llm = LLM(model='gpt-4o', provider='openai_responses')
# Option 2: Using model prefix
llm = LLM(model='openai_responses/gpt-4o')
Includes comprehensive test coverage for:
- Provider routing
- Message conversion
- Tool conversion
- API calls
- Parameter preparation
- Context window sizes
- Feature support methods
- Token usage extraction
Co-Authored-By: João <joao@crewai.com>
* 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
* fix: use CREWAI_PLUS_URL env var in precedence over PlusAPI configured value
* feat: bypass TLS certificate verification when calling platform
* test: fix test
- Replace Python representation with JsonSchema for tool arguments
- Remove deprecated PydanticSchemaParser in favor of direct schema generation
- Add handling for VAR_POSITIONAL and VAR_KEYWORD parameters
- Improve tool argument schema collection
* fix: gracefully terminate the future when executing a task async
* core: add unit test
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Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
* supporting thinking for anthropic models
* drop comments here
* thinking and tool calling support
* fix: properly mock tool use and text block types in Anthropic tests
- Updated the test for the Anthropic tool use conversation flow to include type attributes for mocked ToolUseBlock and text blocks, ensuring accurate simulation of tool interactions during testing.
* feat: add AnthropicThinkingConfig for enhanced thinking capabilities
This update introduces the AnthropicThinkingConfig class to manage thinking parameters for the Anthropic completion model. The LLM and AnthropicCompletion classes have been updated to utilize this new configuration. Additionally, new test cassettes have been added to validate the functionality of thinking blocks across interactions.
Adds async support for tools with tests, async execution in the agent executor, and async operations for memory (with aiosqlite). Improves tool decorator typing, ensures _run backward compatibility, updates docs and docstrings, adds tests, and regenerates lockfiles.
Introduces async tool support with new tests, adds async execution to the agent executor, improves tool decorator typing, ensures _run backward compatibility, updates docs and docstrings, and adds additional tests.
* refactor: enhance model validation and provider inference in LLM class
- Updated the model validation logic to support pattern matching for new models and "latest" versions, improving flexibility for various providers.
- Refactored the `_validate_model_in_constants` method to first check hardcoded constants and then fall back to pattern matching.
- Introduced `_matches_provider_pattern` to streamline provider-specific model checks.
- Enhanced the `_infer_provider_from_model` method to utilize pattern matching for better provider inference.
This refactor aims to improve the extensibility of the LLM class, allowing it to accommodate new models without requiring constant updates to the hardcoded lists.
* feat: add new Anthropic model versions to constants
- Introduced "claude-opus-4-5-20251101" and "claude-opus-4-5" to the AnthropicModels and ANTHROPIC_MODELS lists for enhanced model support.
- Added "anthropic.claude-opus-4-5-20251101-v1:0" to BedrockModels and BEDROCK_MODELS to ensure compatibility with the latest model offerings.
- Updated test cases to ensure proper environment variable handling for model validation, improving robustness in testing scenarios.
* dont infer this way - dropped
