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* feat: add OpenAI agent adapter implementation - Introduced OpenAIAgentAdapter class to facilitate interaction with OpenAI Assistants. - Implemented methods for task execution, tool configuration, and response processing. - Added support for converting CrewAI tools to OpenAI format and handling delegation tools. * created an adapter for the delegate and ask_question tools * delegate and ask_questions work and it delegates to crewai agents* * refactor: introduce OpenAIAgentToolAdapter for tool management - Created OpenAIAgentToolAdapter class to encapsulate tool configuration and conversion for OpenAI Assistant. - Removed tool configuration logic from OpenAIAgentAdapter and integrated it into the new adapter. - Enhanced the tool conversion process to ensure compatibility with OpenAI's requirements. * feat: implement BaseAgentAdapter for agent integration - Introduced BaseAgentAdapter as an abstract base class for agent adapters in CrewAI. - Defined common interface and methods for configuring tools and structured output. - Updated OpenAIAgentAdapter to inherit from BaseAgentAdapter, enhancing its structure and functionality. * feat: add LangGraph agent and tool adapter for CrewAI integration - Introduced LangGraphAgentAdapter to facilitate interaction with LangGraph agents. - Implemented methods for task execution, context handling, and tool configuration. - Created LangGraphToolAdapter to convert CrewAI tools into LangGraph-compatible format. - Enhanced error handling and logging for task execution and streaming processes. * feat: enhance LangGraphToolAdapter and improve conversion instructions - Added type hints for better clarity and type checking in LangGraphToolAdapter. - Updated conversion instructions to ensure compatibility with optional LLM checks. * feat: integrate structured output handling in LangGraph and OpenAI agents - Added LangGraphConverterAdapter for managing structured output in LangGraph agents. - Enhanced LangGraphAgentAdapter to utilize the new converter for system prompt and task execution. - Updated LangGraphToolAdapter to use StructuredTool for better compatibility. - Introduced OpenAIConverterAdapter for structured output management in OpenAI agents. - Improved task execution flow in OpenAIAgentAdapter to incorporate structured output configuration and post-processing. * feat: implement BaseToolAdapter for tool integration - Introduced BaseToolAdapter as an abstract base class for tool adapters in CrewAI. - Updated LangGraphToolAdapter and OpenAIAgentToolAdapter to inherit from BaseToolAdapter, enhancing their structure and functionality. - Improved tool configuration methods to support better integration with various frameworks. - Added type hints and documentation for clarity and maintainability. * feat: enhance OpenAIAgentAdapter with configurable agent properties - Refactored OpenAIAgentAdapter to accept agent configuration as an argument. - Introduced a method to build a system prompt for the OpenAI agent, improving task execution context. - Updated initialization to utilize role, goal, and backstory from kwargs, enhancing flexibility in agent setup. - Improved tool handling and integration within the adapter. * feat: enhance agent adapters with structured output support - Introduced BaseConverterAdapter as an abstract class for structured output handling. - Implemented LangGraphConverterAdapter and OpenAIConverterAdapter to manage structured output in their respective agents. - Updated BaseAgentAdapter to accept an agent configuration dictionary during initialization. - Enhanced LangGraphAgentAdapter to utilize the new converter and improved tool handling. - Added methods for configuring structured output and enhancing system prompts in converter adapters. * refactor: remove _parse_tools method from OpenAIAgentAdapter and BaseAgent - Eliminated the _parse_tools method from OpenAIAgentAdapter and its abstract declaration in BaseAgent. - Cleaned up related test code in MockAgent to reflect the removal of the method. * also removed _parse_tools here as not used * feat: add dynamic import handling for LangGraph dependencies - Implemented conditional imports for LangGraph components to handle ImportError gracefully. - Updated LangGraphAgentAdapter initialization to check for LangGraph availability and raise an informative error if dependencies are missing. - Enhanced the agent adapter's robustness by ensuring it only initializes components when the required libraries are present. * fix: improve error handling for agent adapters - Updated LangGraphAgentAdapter to raise an ImportError with a clear message if LangGraph dependencies are not installed. - Refactored OpenAIAgentAdapter to include a similar check for OpenAI dependencies, ensuring robust initialization and user guidance for missing libraries. - Enhanced overall error handling in agent adapters to prevent runtime issues when dependencies are unavailable. * refactor: enhance tool handling in agent adapters - Updated BaseToolAdapter to initialize original and converted tools in the constructor. - Renamed method `all_tools` to `tools` for clarity in BaseToolAdapter. - Added `sanitize_tool_name` method to ensure tool names are API compatible. - Modified LangGraphAgentAdapter to utilize the updated tool handling and ensure proper tool configuration. - Refactored LangGraphToolAdapter to streamline tool conversion and ensure consistent naming conventions. * feat: emit AgentExecutionCompletedEvent in agent adapters - Added emission of AgentExecutionCompletedEvent in both LangGraphAgentAdapter and OpenAIAgentAdapter to signal task completion. - Enhanced event handling to include agent, task, and output details for better tracking of execution results. * docs: Enhance BaseConverterAdapter documentation - Added a detailed docstring to the BaseConverterAdapter class, outlining its purpose and the expected functionality for all converter adapters. - Updated the post_process_result method's docstring to specify the expected format of the result as a string. * docs: Add comprehensive guide for bringing custom agents into CrewAI - Introduced a new documentation file detailing the process of integrating custom agents using the BaseAgentAdapter, BaseToolAdapter, and BaseConverter. - Included step-by-step instructions for creating custom adapters, configuring tools, and handling structured output. - Provided examples for implementing adapters for various frameworks, enhancing the usability of CrewAI for developers. * feat: Introduce adapted_agent flag in BaseAgent and update BaseAgentAdapter initialization - Added an `adapted_agent` boolean field to the BaseAgent class to indicate if the agent is adapted. - Updated the BaseAgentAdapter's constructor to pass `adapted_agent=True` to the superclass, ensuring proper initialization of the new field. * feat: Enhance LangGraphAgentAdapter to support optional agent configuration - Updated LangGraphAgentAdapter to conditionally apply agent configuration when creating the agent graph, allowing for more flexible initialization. - Modified LangGraphToolAdapter to ensure only instances of BaseTool are converted, improving tool compatibility and handling. * feat: Introduce OpenAIConverterAdapter for structured output handling - Added OpenAIConverterAdapter to manage structured output conversion for OpenAI agents, enhancing their ability to process and format results. - Updated OpenAIAgentAdapter to utilize the new converter for configuring structured output and post-processing results. - Removed the deprecated get_output_converter method from OpenAIAgentAdapter. - Added unit tests for BaseAgentAdapter and BaseToolAdapter to ensure proper functionality and integration of new features. * feat: Enhance tool adapters to support asynchronous execution - Updated LangGraphToolAdapter and OpenAIAgentToolAdapter to handle asynchronous tool execution by checking if the output is awaitable. - Introduced `inspect` import to facilitate the awaitability check. - Refactored tool wrapper functions to ensure proper handling of both synchronous and asynchronous tool results. * fix: Correct method definition syntax and enhance tool adapter implementation - Updated the method definition for `configure_structured_output` to include the `def` keyword for clarity. - Added an asynchronous tool wrapper to ensure tools can operate in both synchronous and asynchronous contexts. - Modified the constructor of the custom converter adapter to directly assign the agent adapter, improving clarity and functionality. * linted * refactor: Improve tool processing logic in BaseAgent - Added a check to return an empty list if no tools are provided. - Simplified the tool attribute validation by using a list of required attributes. - Removed commented-out abstract method definition for clarity. * refactor: Simplify tool handling in agent adapters - Changed default value of `tools` parameter in LangGraphAgentAdapter to None for better handling of empty tool lists. - Updated tool initialization in both LangGraphAgentAdapter and OpenAIAgentAdapter to directly pass the `tools` parameter, removing unnecessary list handling. - Cleaned up commented-out code in OpenAIConverterAdapter to improve readability. * refactor: Remove unused stream_task method from LangGraphAgentAdapter - Deleted the `stream_task` method from LangGraphAgentAdapter to streamline the code and eliminate unnecessary complexity. - This change enhances maintainability by focusing on essential functionalities within the agent adapter.
62 lines
2.0 KiB
Python
62 lines
2.0 KiB
Python
import inspect
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from typing import Any, List, Optional
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from crewai.agents.agent_adapters.base_tool_adapter import BaseToolAdapter
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from crewai.tools.base_tool import BaseTool
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class LangGraphToolAdapter(BaseToolAdapter):
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"""Adapts CrewAI tools to LangGraph agent tool compatible format"""
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def __init__(self, tools: Optional[List[BaseTool]] = None):
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self.original_tools = tools or []
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self.converted_tools = []
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def configure_tools(self, tools: List[BaseTool]) -> None:
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"""
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Configure and convert CrewAI tools to LangGraph-compatible format.
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LangGraph expects tools in langchain_core.tools format.
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"""
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from langchain_core.tools import BaseTool, StructuredTool
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converted_tools = []
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if self.original_tools:
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all_tools = tools + self.original_tools
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else:
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all_tools = tools
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for tool in all_tools:
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if isinstance(tool, BaseTool):
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converted_tools.append(tool)
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continue
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sanitized_name = self.sanitize_tool_name(tool.name)
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async def tool_wrapper(*args, tool=tool, **kwargs):
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output = None
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if len(args) > 0 and isinstance(args[0], str):
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output = tool.run(args[0])
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elif "input" in kwargs:
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output = tool.run(kwargs["input"])
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else:
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output = tool.run(**kwargs)
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if inspect.isawaitable(output):
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result = await output
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else:
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result = output
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return result
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converted_tool = StructuredTool(
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name=sanitized_name,
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description=tool.description,
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func=tool_wrapper,
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args_schema=tool.args_schema,
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)
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converted_tools.append(converted_tool)
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self.converted_tools = converted_tools
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def tools(self) -> List[Any]:
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return self.converted_tools or []
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