def make_react_duckdb_agent()

in databao/duckdb/react_tools.py [0:0]

• 12 lines of code
• 1 McCabe index (conditional complexity)

def make_react_duckdb_agent(con: DuckDBPyConnection, llm: BaseChatModel) -> CompiledStateGraph[Any]:
    """
    Create a ReAct agent configured to work with DuckDB.

    Args:
        con: DuckDB connection to execute queries against.
        llm: Language model to use for the agent.

    Returns:
        A compiled LangGraph ReAct agent.
    """
    schema_text = describe_duckdb_schema(con)
    # TODO move to .jinja (and fix indendation)
    SYSTEM_PROMPT = f"""You are a careful data analyst using the ReAct pattern with tools.
    Use the `execute_sql` tool to run exactly one DuckDB SQL statement when needed.

    Guidelines:
    - Translate the NL question to ONE DuckDB SQL statement.
    - Use provided schema.
    - You can fetch extra details about schema/tables/columns if needed using SQL queries.
    - After running, write a concise, user-friendly explanation.
    - Do NOT write any tables/lists to the output.
    - Always include the exact SQL you ran.
    - Always use the full table name in query with db name and schema name.

    Available schema:
    {schema_text}
    """
    # LangGraph prebuilt ReAct agent
    execute_sql_tool = make_duckdb_tool(con)
    tools = [execute_sql_tool]
    agent = create_react_agent(
        llm,
        tools=tools,
        prompt=SYSTEM_PROMPT,
        response_format=AgentResponse,
    )
    return agent