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crewAI/tests/agents/agent_adapters/test_base_agent_adapter.py
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Feat/byoa (#2523)
* 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.
2025-04-17 09:22:48 -07:00

114 lines
3.6 KiB
Python

from typing import Any, Dict, List, Optional
import pytest
from pydantic import BaseModel
from crewai.agent import BaseAgent
from crewai.agents.agent_adapters.base_agent_adapter import BaseAgentAdapter
from crewai.tools import BaseTool
from crewai.utilities.token_counter_callback import TokenProcess
# Concrete implementation for testing
class ConcreteAgentAdapter(BaseAgentAdapter):
def configure_tools(
self, tools: Optional[List[BaseTool]] = None, **kwargs: Any
) -> None:
# Simple implementation for testing
self.tools = tools or []
def execute_task(
self,
task: Any,
context: Optional[str] = None,
tools: Optional[List[Any]] = None,
) -> str:
# Dummy implementation needed due to BaseAgent inheritance
return "Task executed"
def create_agent_executor(self, tools: Optional[List[BaseTool]] = None) -> Any:
# Dummy implementation
return None
def get_delegation_tools(
self, tools: List[BaseTool], tool_map: Optional[Dict[str, BaseTool]]
) -> List[BaseTool]:
# Dummy implementation
return []
def _parse_output(self, agent_output: Any, token_process: TokenProcess):
# Dummy implementation
pass
def get_output_converter(self, tools: Optional[List[BaseTool]] = None) -> Any:
# Dummy implementation
return None
def test_base_agent_adapter_initialization():
"""Test initialization of the concrete agent adapter."""
adapter = ConcreteAgentAdapter(
role="test role", goal="test goal", backstory="test backstory"
)
assert isinstance(adapter, BaseAgent)
assert isinstance(adapter, BaseAgentAdapter)
assert adapter.role == "test role"
assert adapter._agent_config is None
assert adapter.adapted_structured_output is False
def test_base_agent_adapter_initialization_with_config():
"""Test initialization with agent_config."""
config = {"model": "gpt-4"}
adapter = ConcreteAgentAdapter(
agent_config=config,
role="test role",
goal="test goal",
backstory="test backstory",
)
assert adapter._agent_config == config
def test_configure_tools_method_exists():
"""Test that configure_tools method exists and can be called."""
adapter = ConcreteAgentAdapter(
role="test role", goal="test goal", backstory="test backstory"
)
# Create dummy tools if needed, or pass None
tools = []
adapter.configure_tools(tools)
assert hasattr(adapter, "tools")
assert adapter.tools == tools
def test_configure_structured_output_method_exists():
"""Test that configure_structured_output method exists and can be called."""
adapter = ConcreteAgentAdapter(
role="test role", goal="test goal", backstory="test backstory"
)
# Define a dummy structure or pass None/Any
class DummyOutput(BaseModel):
data: str
structured_output = DummyOutput
adapter.configure_structured_output(structured_output)
# Add assertions here if configure_structured_output modifies state
# For now, just ensuring it runs without error is sufficient
pass
def test_base_agent_adapter_inherits_base_agent():
"""Test that BaseAgentAdapter inherits from BaseAgent."""
assert issubclass(BaseAgentAdapter, BaseAgent)
class ConcreteAgentAdapterWithoutRequiredMethods(BaseAgentAdapter):
pass
def test_base_agent_adapter_fails_without_required_methods():
"""Test that BaseAgentAdapter fails without required methods."""
with pytest.raises(TypeError):
ConcreteAgentAdapterWithoutRequiredMethods() # type: ignore