AISE1_Project_Irina_Livio/backend/agent/mcp_server_adapter_RAG.py
2026-05-07 11:36:56 +02:00

115 lines
4.8 KiB
Python

import asyncio
import json
# import os
import numpy as np
from typing import List, Dict, Any
from pathlib import Path
from sentence_transformers import SentenceTransformer # embedder
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
class MCPToolRAGAdapter:
def __init__ (self, config_path: str = "mcp_server_config.json"):
self.config_path = config_path
self.tools = []
self.toolnames = []
self.embedder = SentenceTransformer('all-MiniLM-L6-v2') # for embedding tool descriptions
self.sessions = {}
self.exit_stack = {}
self.tool_registry = {}
self.tool_embeddings = None
def _load_config(self) -> Dict[str, Any]:
config_path = Path(__file__).parent / self.config_path
if not config_path.exists():
return {}
try:
with open(self.config_path, 'r') as f:
return json.load(f)
except json.JSONDecodeError as e:
print(f"Error decoding JSON config: {e}")
return {}
async def initialize_all_sessions(self):
"""Initialize all MCP sessions defined in the config file and index their tools."""
config = self._load_config()
for server_name, params in config.items():
print(f"initializing session for {server_name} with params: {params}")
server_params = StdioServerParameters(
commanf=params["command"],
args=params.get("args", []),
# env=params.get("env", {}),
)
# Verbindung aufbauen (Kontext-Manager manuell handhaben für Langzeit-Sessions)
transport_gen = stdio_client(server_params)
read, write = await transport_gen.__aenter__()
session = ClientSession(read, write)
await session.__aenter__()
await session.initialize()
self.sessions[server_name] = session
self.exit_stack[server_name] = (transport_gen, session) # Zum späteren sauberen Schließen speichern
print(f"Session for {server_name} initialized successfully.")
# call tools and index thme
result = await session.list_tools()
tools = result.get("tools", [])
for tool in tools:
self.tool_registry.append({
"server": server_name,
"tool_name": tool["name"],
"definition": tool,
"search_text": f"{tool['name']}: {tool.get('description', '')}",
})
self.tool_names.append(tool["name"])
# embeddings for all tools in this session
if self.tool_registry:
texts = [t["search_text"] for t in self.tool_registry]
self.tool_embeddings = self.embedder.encode(texts)
print(f"Indexing completed. {len(texts)} tools ready.")
def get_relevant_tools(self, query: str, top_k: int = 5) -> List[Dict[str, Any]]:
"""Given a user query, return the most relevant tools based on semantic similarity."""
if not self.tool_embeddings or not self.tool_registry:
print("No tools indexed yet.")
return []
query_embedding = self.embedder.encode([query])
similarities = np.dot(self.tool_embeddings, query_embedding.T).flatten()
top_indices = np.argsort(similarities)[-top_k:][::-1]
relevant_tools = [self.tool_registry[i] for i in top_indices]
return relevant_tools
async def call_tool(self, tool_name: str, arguments: Dict):
""" Finds the right server for the tool and calls it with the provided arguments. """
for item in self.tool_registry:
if item["definition"].name == tool_name:
server_name = item["server"]
session = self.sessions.get(server_name)
if session:
try:
result = await session.call_tool(tool_name, arguments)
return result
except Exception as e:
print(f"Error calling tool {tool_name} on server {server_name}: {e}")
return f"Error calling tool: {e}"
return f"Tool '{tool_name}' not found in registry."
async def shutdown_all_sessions(self):
"""Gracefully shutdown all MCP sessions."""
for server_name, (transport_gen, session) in self.exit_stack.items():
try:
await session.__aexit__(None, None, None)
await transport_gen.__aexit__(None, None, None)
print(f"Session for {server_name} shut down successfully.")
except Exception as e:
print(f"Error shutting down session for {server_name}: {e}")