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from dotenv import load_dotenv
import pathlib
import asyncio
import sys
import os
from pydantic_ai import Agent
from openai import AsyncOpenAI, OpenAI
from pydantic_ai.models.openai import OpenAIModel
import mcp_client
# Get the directory where the current script is located
SCRIPT_DIR = pathlib.Path(__file__).parent.resolve()
# Define the path to the config file relative to the script directory
CONFIG_FILE = SCRIPT_DIR / "mcp_config.json"
load_dotenv()
def get_model():
llm = os.getenv('MODEL_CHOICE', 'gpt-4o-mini')
base_url = os.getenv('BASE_URL', 'https://api.openai.com/v1')
api_key = os.getenv('LLM_API_KEY', 'no-api-key-provided')
return OpenAIModel(
llm,
base_url=base_url,
api_key=api_key
)
async def get_pydantic_ai_agent():
client = mcp_client.MCPClient()
client.load_servers(str(CONFIG_FILE))
tools = await client.start()
return client, Agent(model=get_model(), tools=tools)
async def main():
client, agent = await get_pydantic_ai_agent()
while True:
# Example: Search the web to find the newest local LLMs.
user_input = input("\n[You] ")
# Check if user wants to exit
if user_input.lower() in ['exit', 'quit', 'bye', 'goodbye']:
print("Goodbye!")
break
result = await agent.run(user_input)
print('[Assistant] ', result.data)
if __name__ == '__main__':
asyncio.run(main()) |