autogen/python/samples/agentchat_graphrag/app.py

63 lines
2.4 KiB
Python

import argparse
import asyncio
import logging
from typing import Any, Dict
import yaml
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_core.models import ChatCompletionClient
from autogen_ext.tools.graphrag import (
GlobalSearchTool,
LocalSearchTool,
)
async def main(model_config: Dict[str, Any]) -> None:
# Initialize the model client from config
model_client = ChatCompletionClient.load_component(model_config)
# Set up global search tool
global_tool = GlobalSearchTool.from_settings(settings_path="./settings.yaml")
local_tool = LocalSearchTool.from_settings(settings_path="./settings.yaml")
# Create assistant agent with both search tools
assistant_agent = AssistantAgent(
name="search_assistant",
tools=[global_tool, local_tool],
model_client=model_client,
system_message=(
"You are a tool selector AI assistant using the GraphRAG framework. "
"Your primary task is to determine the appropriate search tool to call based on the user's query. "
"For specific, detailed information about particular entities or relationships, call the 'local_search' function. "
"For broader, abstract questions requiring a comprehensive understanding of the dataset, call the 'global_search' function. "
"Do not attempt to answer the query directly; focus solely on selecting and calling the correct function."
),
)
# Run a sample query
query = "What does the station-master says about Dr. Becher?"
print(f"\nQuery: {query}")
await Console(assistant_agent.run_stream(task=query))
await model_client.close()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run a GraphRAG search with an agent.")
parser.add_argument("--verbose", action="store_true", help="Enable verbose logging.")
parser.add_argument(
"--model-config", type=str, help="Path to the model configuration file.", default="model_config.yaml"
)
args = parser.parse_args()
if args.verbose:
logging.basicConfig(level=logging.WARNING)
logging.getLogger("autogen_core").setLevel(logging.DEBUG)
handler = logging.FileHandler("graphrag_search.log")
logging.getLogger("autogen_core").addHandler(handler)
with open(args.model_config, "r") as f:
model_config = yaml.safe_load(f)
asyncio.run(main(model_config))