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Agent vector store tool doc (#9029)

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I was initially confused weather to use create_vectorstore_agent or
create_vectorstore_router_agent due to lack of documentation so I
created a simple documentation for each of the function about their
different usecase.
Replace this comment with:
- Description: Added the doc_strings in create_vectorstore_agent and
create_vectorstore_router_agent to point out the difference in their
usecase
  - Tag maintainer: @rlancemartin, @eyurtsev

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
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TRY-ER 2023-08-10 23:43:12 +05:30 committed by GitHub
parent 641cb80c9d
commit 2431eca700
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1 changed files with 28 additions and 2 deletions
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30
libs/langchain/langchain/agents/agent_toolkits/vectorstore/base.py
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@ -22,7 +22,20 @@ def create_vectorstore_agent(
agent_executor_kwargs: Optional[Dict[str, Any]] = None,
**kwargs: Dict[str, Any],
) -> AgentExecutor:
"""Construct a VectorStore agent from an LLM and tools."""
"""Construct a VectorStore agent from an LLM and tools.
Args:
llm (BaseLanguageModel): LLM that will be used by the agent
toolkit (VectorStoreToolkit): Set of tools for the agent
callback_manager (Optional[BaseCallbackManager], optional): Object to handle the callback [ Defaults to None. ]
prefix (str, optional): The prefix prompt for the agent. If not provided uses default PREFIX.
verbose (bool, optional): If you want to see the content of the scratchpad. [ Defaults to False ]
agent_executor_kwargs (Optional[Dict[str, Any]], optional): If there is any other parameter you want to send to the agent. [ Defaults to None ]
**kwargs: Additional named parameters to pass to the ZeroShotAgent.
Returns:
AgentExecutor: Returns a callable AgentExecutor object. Either you can call it or use run method with the query to get the response
""" # noqa: E501
tools = toolkit.get_tools()
prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix)
llm_chain = LLMChain(
@ -50,7 +63,20 @@ def create_vectorstore_router_agent(
agent_executor_kwargs: Optional[Dict[str, Any]] = None,
**kwargs: Dict[str, Any],
) -> AgentExecutor:
"""Construct a VectorStore router agent from an LLM and tools."""
"""Construct a VectorStore router agent from an LLM and tools.
Args:
llm (BaseLanguageModel): LLM that will be used by the agent
toolkit (VectorStoreRouterToolkit): Set of tools for the agent which have routing capability with multiple vector stores
callback_manager (Optional[BaseCallbackManager], optional): Object to handle the callback [ Defaults to None. ]
prefix (str, optional): The prefix prompt for the router agent. If not provided uses default ROUTER_PREFIX.
verbose (bool, optional): If you want to see the content of the scratchpad. [ Defaults to False ]
agent_executor_kwargs (Optional[Dict[str, Any]], optional): If there is any other parameter you want to send to the agent. [ Defaults to None ]
**kwargs: Additional named parameters to pass to the ZeroShotAgent.
Returns:
AgentExecutor: Returns a callable AgentExecutor object. Either you can call it or use run method with the query to get the response.
""" # noqa: E501
tools = toolkit.get_tools()
prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix)
llm_chain = LLMChain(