aiq.agent.react_agent.agent#
Attributes#
Classes#
State schema for the ReAct Agent Graph |
|
Configurable LangGraph ReAct Agent. A ReAct Agent performs reasoning inbetween tool calls, and utilizes the tool |
Module Contents#
- logger#
- TOOL_NOT_FOUND_ERROR_MESSAGE = 'There is no tool named {tool_name}. Tool must be one of {tools}.'#
- INPUT_SCHEMA_MESSAGE = '. Arguments must be provided as a valid JSON object following this format: {schema}'#
- class ReActGraphState(/, **data: Any)#
Bases:
pydantic.BaseModel
State schema for the ReAct Agent Graph
Create a new model by parsing and validating input data from keyword arguments.
Raises [
ValidationError
][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.self
is explicitly positional-only to allowself
as a field name.
- class ReActAgentGraph(
- llm: langchain_core.language_models.BaseChatModel,
- prompt: langchain_core.prompts.chat.ChatPromptTemplate,
- tools: list[langchain_core.tools.BaseTool],
- use_tool_schema: bool = True,
- callbacks: list[langchain_core.callbacks.base.AsyncCallbackHandler] = None,
- detailed_logs: bool = False,
- retry_parsing_errors: bool = True,
- max_retries: int = 1,
Bases:
aiq.agent.base.BaseAgent
Configurable LangGraph ReAct Agent. A ReAct Agent performs reasoning inbetween tool calls, and utilizes the tool names and descriptions to select the optimal tool. Supports retrying on output parsing errors. Argument “detailed_logs” toggles logging of inputs, outputs, and intermediate steps.
- retry_parsing_errors = True#
- max_tries = 2#
- agent#
- tools_dict#
- _get_tool(tool_name)#
- async agent_node(state: ReActGraphState)#
- async conditional_edge(state: ReActGraphState)#
- async tool_node(state: ReActGraphState)#
- async build_graph()#