* test: fix structured tool tests
No tests were being executed from this file
* feat: support to run async tool
Some Tool requires async execution. This commit allow us to collect tool result from coroutines
* docs: add docs about asynchronous tool support
- Introduced a new documentation file for Integrations, detailing supported services and setup instructions.
- Updated the main docs.json to include the new "integrations" feature in the contextual options.
- Added several images related to integrations to enhance the documentation.
Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
* docs: add organization management in our CLI docs
* feat: improve user feedback when user is not authenticated
* feat: improve logging about current organization while publishing/install a Tool
* feat: improve logging when Agent repository is not found during fetch
* fix linter offences
* test: fix auth token error
* docs: added Maxim support for Agent Observability
* enhanced the maxim integration doc page as per the github PR reviewer bot suggestions
* Update maxim-observability.mdx
* Update maxim-observability.mdx
- Fixed Python version, >=3.10
- added expected_output field in Task
- Removed marketing links and added github link
* added maxim in observability
---------
Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
* ci: support python 3.13 on CI
* docs: update docs about support python version
* build: adds requires python <3.14
* build: explicit tokenizers dependency
Added explicit tokenizers dependency: Added tokenizers>=0.20.3 to ensure a version compatible with Python 3.13 is used.
* build: drop fastembed is not longer used
* build: attempt to build PyTorch on Python 3.13
* feat: upgrade fastavro, pyarrow and lancedb
* build: ensure tiktoken greather than 0.8.0 due Python 3.13 compatibility
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
* 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 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>
* 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
---------
Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
The Gemini & Vertex sections were conflated and a little hard to
distingush, so I have put them in separate sections.
Also added the latest 2.5 and 2.0 flash-lite models, and added a note
that Gemma models work too.
Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
* feat: implement knowledge retrieval events in Agent
This commit introduces a series of knowledge retrieval events in the Agent class, enhancing its ability to handle knowledge queries. New events include KnowledgeRetrievalStartedEvent, KnowledgeRetrievalCompletedEvent, KnowledgeQueryGeneratedEvent, KnowledgeQueryFailedEvent, and KnowledgeSearchQueryCompletedEvent. The Agent now emits these events during knowledge retrieval processes, allowing for better tracking and handling of knowledge queries. Additionally, the console formatter has been updated to handle these new events, providing visual feedback during knowledge retrieval operations.
* refactor: update knowledge query handling in Agent
This commit refines the knowledge query processing in the Agent class by renaming variables for clarity and optimizing the query rewriting logic. The system prompt has been updated in the translation file to enhance clarity and context for the query rewriting process. These changes aim to improve the overall readability and maintainability of the code.
* fix: add missing newline at end of en.json file
* fix broken tests
* refactor: rename knowledge query events and enhance retrieval handling
This commit renames the KnowledgeQueryGeneratedEvent to KnowledgeQueryStartedEvent to better reflect its purpose. It also updates the event handling in the EventListener and ConsoleFormatter classes to accommodate the new event structure. Additionally, the retrieval knowledge is now included in the KnowledgeRetrievalCompletedEvent, improving the overall knowledge retrieval process.
* docs for transparancy
* refactor: improve error handling in knowledge query processing
This commit refactors the knowledge query handling in the Agent class by changing the order of checks for LLM compatibility. It now logs a warning and emits a failure event if the LLM is not an instance of BaseLLM before attempting to call the LLM. Additionally, the task_prompt attribute has been removed from the KnowledgeQueryFailedEvent, simplifying the event structure.
* test: add unit test for knowledge search query and VCR cassette
This commit introduces a new test, `test_get_knowledge_search_query`, to verify that the `_get_knowledge_search_query` method in the Agent class correctly interacts with the LLM using the appropriate prompts. Additionally, a VCR cassette is added to record the interactions with the OpenAI API for this test, ensuring consistent and reliable test results.
Updated prereqs and setup steps to point to the now-more-model-agnostic
LLM setup guide, and updated the relevant text to go with it.
Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
This removes any specific model from the "Setting up your LLM" guide,
but provides examples for the top-3 providers.
This section also conflated "model selection" with "model
configuration", where configuration is provider-specific, so I've
focused this first section on just model selection, deferring the config
to the "provider" section that follows.
Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
