pipelines.agent.base

Agent-based task execution pipeline that wraps smolagents to provide autonomous task completion capabilities using local LLMs.

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Agent

 Agent (llm:onprem.llm.base.LLM, agent_type:str='tool_calling',
        max_steps:int=20, tools:dict={}, **kwargs)

*Pipeline for agent-based task execution using smolagents. Extra kwargs are supplied directly to agent instantation.

Args: llm (LLM): An onprem LLM instance to use for agent reasoning agent_type (str, optional): Type of agent to use (‘tool_calling’ or ‘code’) max_steps (int, optional): Maximum number of steps the agent can take tools (dict, optional): a dictionary of tools for agent to use*

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Agent.add_tool

 Agent.add_tool (name:str, tool_instance)

*Add a tool to the agent.

Args: name (str): The name of the tool tool_instance (Tool): The tool instance*

	Type	Details
name	str
tool_instance		tool_instance is SA_Tool

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Agent.add_function_tool

 Agent.add_function_tool (func:Callable)

*Create a tool from a function and its documentation.

Args: func (Callable): The function to wrap as a tool name (str, optional): The name of the tool (defaults to function name) description (str, optional): The description of the tool (defaults to function docstring)

Returns: Tool: The created tool*

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Agent.add_vectorstore_tool

 Agent.add_vectorstore_tool (name:str,
                             store:onprem.ingest.base.VectorStore,
                             description:str='Search a vector database for
                             relevant information')

*Create a tool from a VectorStore instance.

Args: name (str): The name of the vector store tool store (VectorStore): The vector store instance description (str, optional): The description of the vector store
Returns: Tool: The created tool*

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