This commit includes several enhancements to the MCP integration guide:
- Adds a section on connecting to multiple MCP servers with a runnable example.
- Ensures consistent mention and examples for Streamable HTTP transport.
- Adds a manual lifecycle example for Streamable HTTP.
- Clarifies Stdio command examples.
- Refines definitions of Stdio, SSE, and Streamable HTTP transports.
- Simplifies comments in code examples for clarity.
* docs: Fix major memory system documentation issues - Remove misleading deprecation warnings, fix confusing comments, clearly separate three memory approaches, provide accurate examples that match implementation
* fix: Correct broken image paths in README - Update crewai_logo.png and asset.png paths to point to docs/images/ directory instead of docs/ directly
* docs: Add system prompt transparency and customization guide - Add 'Understanding Default System Instructions' section to address black-box concerns - Document what CrewAI automatically injects into prompts - Provide code examples to inspect complete system prompts - Show 3 methods to override default instructions - Include observability integration examples with Langfuse - Add best practices for production prompt management
* docs: Fix implementation accuracy issues in memory documentation - Fix Ollama embedding URL parameter and remove unsupported Cohere input_type parameter
* docs: Reference observability docs instead of showing specific tool examples
* docs: Reorganize knowledge documentation for better developer experience - Move quickstart examples right after overview for immediate hands-on experience - Create logical learning progression: basics → configuration → advanced → troubleshooting - Add comprehensive agent vs crew knowledge guide with working examples - Consolidate debugging and troubleshooting in dedicated section - Organize best practices by topic in accordion format - Improve content flow from simple concepts to advanced features - Ensure all examples are grounded in actual codebase implementation
* docs: enhance custom LLM documentation with comprehensive examples and accurate imports
* docs: reorganize observability tools into dedicated section with comprehensive overview and improved navigation
* docs: rename how-to section to learn and add comprehensive overview page
* docs: finalize documentation reorganization and update navigation labels
* docs: enhance README with comprehensive badges, navigation links, and getting started video
* Add Common Room tracking to documentation - Script will track all documentation page views - Follows Mintlify custom JS implementation pattern - Enables comprehensive docs usage insights
* docs: move human-in-the-loop guide to enterprise section and update navigation - Move human-in-the-loop.mdx from learn to enterprise/guides - Update docs.json navigation to reflect new organization
* docs: Fix major memory system documentation issues - Remove misleading deprecation warnings, fix confusing comments, clearly separate three memory approaches, provide accurate examples that match implementation
* fix: Correct broken image paths in README - Update crewai_logo.png and asset.png paths to point to docs/images/ directory instead of docs/ directly
* docs: Add system prompt transparency and customization guide - Add 'Understanding Default System Instructions' section to address black-box concerns - Document what CrewAI automatically injects into prompts - Provide code examples to inspect complete system prompts - Show 3 methods to override default instructions - Include observability integration examples with Langfuse - Add best practices for production prompt management
* docs: Fix implementation accuracy issues in memory documentation - Fix Ollama embedding URL parameter and remove unsupported Cohere input_type parameter
* docs: Reference observability docs instead of showing specific tool examples
* docs: Reorganize knowledge documentation for better developer experience - Move quickstart examples right after overview for immediate hands-on experience - Create logical learning progression: basics → configuration → advanced → troubleshooting - Add comprehensive agent vs crew knowledge guide with working examples - Consolidate debugging and troubleshooting in dedicated section - Organize best practices by topic in accordion format - Improve content flow from simple concepts to advanced features - Ensure all examples are grounded in actual codebase implementation
* docs: enhance custom LLM documentation with comprehensive examples and accurate imports
* docs: reorganize observability tools into dedicated section with comprehensive overview and improved navigation
* docs: rename how-to section to learn and add comprehensive overview page
* docs: finalize documentation reorganization and update navigation labels
* docs: enhance README with comprehensive badges, navigation links, and getting started video
* feat: add ZapierActionTool and ZapierActionsAdapter for integrating with Zapier actions
- Introduced ZapierActionTool to execute Zapier actions with dynamic parameter handling.
- Added ZapierActionsAdapter to fetch available Zapier actions and convert them into BaseTool instances.
- Updated __init__.py files to include new tools and ensure proper imports.
- Created README.md for ZapierActionTools with installation instructions and usage examples.
* fix: restore ZapierActionTool import and enhance logging in Zapier adapter
- Reintroduced the import of ZapierActionTool in __init__.py for proper accessibility.
- Added logging for error handling in ZapierActionsAdapter to improve debugging.
- Updated ZapierActionTools factory function to include logging for missing API key.
* Add usage limit feature to BaseTool class
- Add max_usage_count and current_usage_count attributes to BaseTool
- Implement usage limit checking in ToolUsage._use method
- Add comprehensive tests for usage limit functionality
- Maintain backward compatibility with None default for unlimited usage
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix CI failures and address code review feedback
- Add max_usage_count/current_usage_count to CrewStructuredTool
- Add input validation for positive max_usage_count
- Add reset_usage_count method to BaseTool
- Extract usage limit check into separate method
- Add comprehensive edge case tests
- Add proper type hints throughout
- Fix linting issues
Co-Authored-By: Joe Moura <joao@crewai.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
* docs: enterprise hallucination guardrails
Documents the `HallucinationGuardrail` feature for enterprise users, including usage examples, configuration options, and integration patterns.
* fix: update import
in the tin
* chore: add docs.json route
Add route for hallucination guardrail mdx
* feat: Add inject_date flag to Agent for automatic date injection
Co-Authored-By: Joe Moura <joao@crewai.com>
* feat: Add date_format parameter and error handling to inject_date feature
Co-Authored-By: Joe Moura <joao@crewai.com>
* fix: Update test implementation for inject_date feature
Co-Authored-By: Joe Moura <joao@crewai.com>
* fix: Add date format validation to prevent invalid formats
Co-Authored-By: Joe Moura <joao@crewai.com>
* docs: Update documentation for inject_date feature
Co-Authored-By: Joe Moura <joao@crewai.com>
* unnecesary
* new tests
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
Co-authored-by: João Moura <joaomdmoura@gmail.com>
- Add `HallucinationGuardrail` class as enterprise feature placeholder
- Update LLM guardrail events to support `HallucinationGuardrail` instances
- Add comprehensive tests for `HallucinationGuardrail` initialization and behavior
- Add integration tests for `HallucinationGuardrail` with task execution system
- Ensure no-op behavior always returns True
* Refactor Crew class memory initialization and enhance event handling
- Simplified the initialization of the external memory attribute in the Crew class.
- Updated memory system retrieval logic for consistency in key usage.
- Introduced a singleton pattern for the Telemetry class to ensure a single instance.
- Replaced telemetry usage in CrewEvaluator with event bus emissions for test results.
- Added new CrewTestResultEvent to handle crew test results more effectively.
- Updated event listener to process CrewTestResultEvent and log telemetry data accordingly.
- Enhanced tests to validate the singleton pattern in Telemetry and the new event handling logic.
* linted
* Remove unused telemetry attribute from Crew class memory initialization
* fix ordering of test
* Implement thread-safe singleton pattern in Telemetry class
- Introduced a threading lock to ensure safe instantiation of the Telemetry singleton.
- Updated the __new__ method to utilize double-checked locking for instance creation.
* Add reasoning attribute to Agent class
Co-Authored-By: Joe Moura <joao@crewai.com>
* Address PR feedback: improve type hints, error handling, refactor reasoning handler, and enhance tests and docs
Co-Authored-By: Joe Moura <joao@crewai.com>
* Implement function calling for reasoning and move prompts to translations
Co-Authored-By: Joe Moura <joao@crewai.com>
* Simplify function calling implementation with better error handling
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance system prompts to leverage agent context (role, goal, backstory)
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix lint and type-checker issues
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance system prompts to better leverage agent context
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix backstory access in reasoning handler for Python 3.12 compatibility
Co-Authored-By: Joe Moura <joao@crewai.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
Co-authored-by: João Moura <joaomdmoura@gmail.com>
* Add markdown attribute to Task class for formatting responses in Markdown
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance markdown feature based on PR feedback
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix lint error and validation error in test_markdown_task.py
Co-Authored-By: Joe Moura <joao@crewai.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
* Changed test case
* Addd new interaction with llama
* fixed linting issue
* Gemma Flaky test case
* Gemma Flaky test case
* Minor change
* Minor change
* Dropped API key
* Removed falky test case check file
* Enhance string interpolation to support hyphens in variable names and add corresponding test cases. Update existing tests for consistency and formatting.
* Refactor tests in task_test.py by removing unused Task instances to streamline test cases for the interpolate_only method and related functions.
* CLI command added
* Added reset agent knowledge function
* Reduced verbose
* Added test cases
* Added docs
* Llama test case failing
* Changed _reset_agent_knowledge function
* Fixed new line error
* Added docs
* fixed the new line error
* Refractored
* Uncommmented some test cases
* ruff check fixed
* fixed run type checks
* fixed run type checks
* fixed run type checks
* Made reset_fn callable by casting to silence run type checks
* Changed the reset_knowledge as it expects only list of knowledge
* Fixed typo in docs
* Refractored the memory_system
* Minor Changes
* fixed test case
* Fixed linting issues
* Network test cases failing
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Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
* feat(tavily): add TavilyExtractorTool and TavilySearchTool with documentation
* feat(tavily): enhance TavilyExtractorTool and TavilySearchTool with additional parameters and improved error handling
* fix(tavily): update installation instructions for 'tavily-python' package in TavilyExtractorTool and TavilySearchTool
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Co-authored-by: lorenzejay <lorenzejaytech@gmail.com>
The built-in `callable` type is not subscriptable, and thus not usable
in a type annotation. When this tool is used, this warning is generated:
```
.../_generate_schema.py:623: UserWarning: <built-in function callable> is not a Python type (it may be an instance of an object), Pydantic will allow any object with no validation since we cannot even enforce that the input is an instance of the given type. To get rid of this error wrap the type with `pydantic.SkipValidation`.
```
This change fixes the warning.
