autogen.agentchat.contrib.graph_rag.graph_rag_capability.GraphRagCapability

GraphRagCapability

GraphRagCapability(query_engine: GraphQueryEngine)

A graph-based RAG capability uses a graph query engine to give a conversable agent the graph-based RAG ability.
An agent class with graph-based RAG capability could

1. create a graph in the underlying database with input documents.
   2. retrieved relevant information based on messages received by the agent.
   3. generate answers from retrieved information and send messages back.
   For example,

graph_query_engine = GraphQueryEngine(...)
graph_query_engine.init_db([Document(doc1), Document(doc2), ...])

graph_rag_agent = ConversableAgent(
    name="graph_rag_agent",
    max_consecutive_auto_reply=3,
    ...<br/>)
graph_rag_capability = GraphRagCapbility(graph_query_engine)
graph_rag_capability.add_to_agent(graph_rag_agent)

user_proxy = UserProxyAgent(
    name="user_proxy",
    code_execution_config=False,
    is_termination_msg=lambda msg: "TERMINATE" in msg["content"],
    human_input_mode="ALWAYS",
)
user_proxy.initiate_chat(graph_rag_agent, message="Name a few actors who've played in 'The Matrix'")

# ChatResult(
    # chat_id=None,
    # chat_history=[
        # \{'content': 'Name a few actors who've played in 'The Matrix'', 'role': 'graph_rag_agent'},
        # \{'content': 'A few actors who have played in The Matrix are: <br/>        #   - Keanu Reeves
        #   - Laurence Fishburne
        #   - Carrie-Anne Moss
        #   - Hugo Weaving',
        #   'role': 'user_proxy'},
    # ...)

Initialize graph-based RAG capability with a graph query engine

Parameters:

Name	Description
query_engine	Type: GraphQueryEngine

Instance Methods

add_to_agent

add_to_agent(self, agent: ConversableAgent) -> None

Add the capability to an agent

Parameters:

Name	Description
agent	Type: ConversableAgent