mirror of
https://gitcode.com/JianFeeeee/TrulyMEM-TrueHumanMEM.git
synced 2026-10-15 12:15:32 +00:00
refactor: 统一 Packet 通信协议 + 后端配置管理 + UI 清理
- 合并 server.py 到 core/__init__.py，使用统一 Packet 协议 - 后端管理配置持久化 (~/.trulymem/config.json) - 前端移除 ConfigService，通过 BackendClient 与后端通信 - 删除 UI 中冗余的 AI 推理逻辑 (chat_service, tool_service, message_handler) - 删除 core/tools 重复文件 (tool_executor, tool_limiter) - 提示词管理器支持用户自定义 (~/.trulyemem/system_prompt.md) - 启动入口优化配置路径逻辑 - 更新测试覆盖 (42 tests) - 更新文档
This commit is contained in:
root
250
core/__init__.py
250
core/__init__.py
@ -1,242 +1,12 @@
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import threading
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import queue
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import time
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from typing import Any, Dict
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from dataclasses import dataclass, field
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from enum import Enum
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class PacketType(Enum):
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MESSAGE = "message"
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CONFIG = "config"
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TOOL = "tool"
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STATUS = "status"
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HISTORY = "history"
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@dataclass
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class Packet:
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id: str
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type: PacketType
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body: Dict[str, Any]
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created_at: float = field(default_factory=time.time)
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from .server import BackendServer, Packet, PacketType, PacketResponse
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from .client import BackendClient
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from .embedded_db import EmbeddedGraphDB
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class BackendServer:
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def __init__(self, db_path: str = "graph_memory.db", use_embedded_db: bool = True):
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self._db_path = db_path
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self._use_embedded_db = use_embedded_db
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self._graph = None
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self._client = None
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self._running = False
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self._thread = None
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self._input_queue: queue.Queue[Packet] = queue.Queue()
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self._response_queues: Dict[str, queue.Queue] = {}
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self._lock = threading.Lock()
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self._config = {"api_key": "", "base_url": "https://api.deepseek.com"}
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def start(self, api_key: str = "", base_url: str = "https://api.deepseek.com") -> None:
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if self._running:
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return
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self._init_graph()
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self._config = {"api_key": api_key, "base_url": base_url}
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if api_key:
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from .graph_client import GraphMemoryClient
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self._client = GraphMemoryClient(api_key=api_key, base_url=base_url, graph=self._graph)
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self._running = True
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self._thread = threading.Thread(target=self._run_loop, daemon=True)
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self._thread.start()
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def _init_graph(self) -> None:
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if self._use_embedded_db:
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self._graph = EmbeddedGraphDB(db_path=self._db_path)
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else:
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from .graph_client import Neo4jGraph
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self._graph = Neo4jGraph(uri="bolt://localhost:7687", user="neo4j", password="graphmemory123")
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def _run_loop(self) -> None:
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while self._running:
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try:
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packet = self._input_queue.get(timeout=0.1)
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except queue.Empty:
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continue
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self._process_packet(packet)
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def _process_packet(self, packet: Packet) -> None:
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body = {"success": False, "error": "not implemented"}
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try:
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if packet.type == PacketType.MESSAGE:
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body = self._handle_message(packet.body)
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elif packet.type == PacketType.CONFIG:
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body = self._handle_config(packet.body)
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elif packet.type == PacketType.TOOL:
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body = self._handle_tool(packet.body)
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elif packet.type == PacketType.STATUS:
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body = self._handle_status()
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elif packet.type == PacketType.HISTORY:
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body = self._handle_history(packet.body)
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body["success"] = True
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except Exception as e:
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body["error"] = str(e)
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finally:
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self._send_response(packet.id, Packet(id=packet.id, type=packet.type, body=body))
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def _handle_message(self, body: Dict) -> Dict:
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from .tool_executor import execute_tool
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from .tool_limiter import ToolLimiter
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limiter = ToolLimiter()
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user_input = body.get("message", "")
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if not self._client:
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return {"error": "API Key not configured", "content": "请先配置 API Key"}
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messages = [{"role": "user", "content": user_input}]
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response = self._client.send_message_with_history(messages)
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message = response.choices[0].message
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content = message.content or "(无回复)"
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tool_calls = []
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while message.tool_calls:
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# 处理所有工具调用
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tool_results = []
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for tool_call in message.tool_calls:
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args = {}
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try:
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import json
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args = json.loads(tool_call.function.arguments)
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except:
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pass
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allowed, reason = limiter.can_call(tool_call.function.name, args)
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if not allowed:
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tool_calls.append({"name": tool_call.function.name, "result": f"工具调用被拒绝: {reason}"})
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tool_results.append({"role": "tool", "tool_call_id": tool_call.id, "content": f"工具调用被拒绝: {reason}"})
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continue
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limiter.record_call(tool_call.function.name, args)
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result = execute_tool(self._graph, tool_call.function.name, args)
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tool_calls.append({"name": tool_call.function.name, "result": result})
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tool_results.append({"role": "tool", "tool_call_id": tool_call.id, "content": result})
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# 添加 assistant 消息（包含完整的 tool_calls，必须有 type 字段）
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assistant_msg = {
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"role": "assistant",
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"content": message.content or "",
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"tool_calls": [{
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"id": tc.id,
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"type": "function",
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"function": {
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"name": tc.function.name,
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"arguments": tc.function.arguments
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}
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} for tc in message.tool_calls]
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}
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messages.append(assistant_msg)
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# 添加工具结果
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messages.extend(tool_results)
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response = self._client.send_message_with_history(messages)
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message = response.choices[0].message
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content = message.content or content
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return {"content": content, "tool_calls": tool_calls}
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def _handle_config(self, body: Dict) -> Dict:
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api_key = body.get("api_key", "")
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base_url = body.get("base_url", "https://api.deepseek.com")
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self._config = {"api_key": api_key, "base_url": base_url}
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if api_key and self._graph:
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from .graph_client import GraphMemoryClient
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self._client = GraphMemoryClient(api_key=api_key, base_url=base_url, graph=self._graph)
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return {"status": "config_updated"}
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def _handle_tool(self, body: Dict) -> Dict:
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from .tool_executor import execute_tool
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name = body.get("name", "")
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args = body.get("arguments", {})
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result = execute_tool(self._graph, name, args)
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return {"result": result}
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def _handle_status(self) -> Dict:
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return {"running": self._running, "config": self._config, "client_ready": self._client is not None}
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def _handle_history(self, body: Dict) -> Dict:
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action = body.get("action", "get")
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if action == "save":
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self._message_history = body.get("messages", [])
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return {"status": "saved"}
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return {"history": getattr(self, "_message_history", [])}
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def send(self, packet: Packet) -> Packet:
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resp_q = queue.Queue()
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with self._lock:
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self._response_queues[packet.id] = resp_q
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self._input_queue.put(packet)
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try:
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return resp_q.get(timeout=30.0)
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except queue.Empty:
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return Packet(id=packet.id, type=packet.type, body={"success": False, "error": "timeout"})
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finally:
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with self._lock:
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self._response_queues.pop(packet.id, None)
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def _send_response(self, request_id: str, packet: Packet) -> None:
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with self._lock:
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q = self._response_queues.pop(request_id, None)
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if q:
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q.put(packet)
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def shutdown(self) -> None:
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self._running = False
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if self._thread:
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self._thread.join(timeout=2.0)
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if self._graph:
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self._graph.close()
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self._graph = None
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class BackendClient:
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def __init__(self, server: BackendServer):
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self._server = server
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self._counter = 0
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self._lock = threading.Lock()
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def _next_id(self) -> str:
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with self._lock:
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self._counter += 1
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return f"{time.time()}_{self._counter}"
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def send_message(self, message: str) -> Dict:
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packet = Packet(id=self._next_id(), type=PacketType.MESSAGE, body={"message": message})
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return self._server.send(packet).body
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def update_config(self, api_key: str, base_url: str = "https://api.deepseek.com") -> Dict:
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packet = Packet(id=self._next_id(), type=PacketType.CONFIG, body={"api_key": api_key, "base_url": base_url})
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return self._server.send(packet).body
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def execute_tool(self, name: str, arguments: Dict) -> str:
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packet = Packet(id=self._next_id(), type=PacketType.TOOL, body={"name": name, "arguments": arguments})
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return self._server.send(packet).body.get("result", "")
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def get_status(self) -> Dict:
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packet = Packet(id=self._next_id(), type=PacketType.STATUS, body={})
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return self._server.send(packet).body
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def save_history(self, messages: list) -> None:
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packet = Packet(id=self._next_id(), type=PacketType.HISTORY, body={"action": "save", "messages": messages})
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self._server.send(packet)
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def get_history(self) -> list:
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packet = Packet(id=self._next_id(), type=PacketType.HISTORY, body={"action": "get"})
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return self._server.send(packet).body.get("history", [])
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def shutdown(self) -> None:
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self._server.shutdown()
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__all__ = ["BackendServer", "BackendClient", "EmbeddedGraphDB", "Packet", "PacketType"]
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__all__ = [
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"BackendServer",
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"BackendClient",
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"EmbeddedGraphDB",
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"Packet",
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"PacketType",
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"PacketResponse"
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]
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100
core/client.py
100
core/client.py
@ -1,61 +1,75 @@
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import threading
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import time
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from typing import Any, Dict
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from .server import BackendServer, MessageType
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from .server import BackendServer, Packet, PacketType
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class BackendClient:
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def __init__(self, server: BackendServer):
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self._server = server
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self._request_counter = 0
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self._counter = 0
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self._lock = threading.Lock()
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def process_message(self, user_input: str, timeout: float = 30.0) -> Dict[str, Any]:
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def _next_id(self) -> str:
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with self._lock:
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self._request_counter += 1
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return self._server.process_message(user_input, timeout)
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self._counter += 1
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return f"{time.time()}_{self._counter}"
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def execute_tool(self, tool_name: str, arguments: Dict[str, Any], timeout: float = 10.0) -> str:
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with self._lock:
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self._request_counter += 1
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return self._server.execute_tool(tool_name, arguments, timeout)
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def send(self, message: str) -> Dict:
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return self.process_message(message)
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def update_config(self, api_key: str, base_url: str = "https://api.deepseek.com") -> Dict[str, Any]:
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return self._send_request(MessageType.SET_CONFIG, {"api_key": api_key, "base_url": base_url})
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def process_message(self, user_input: str) -> Dict:
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return self._server.process_message(user_input)
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def get_config(self) -> Dict[str, str]:
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result = self._send_request(MessageType.GET_CONFIG, {})
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return result.get("data", {"api_key": "", "base_url": "https://api.deepseek.com"})
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def get_message_history(self) -> list:
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result = self._send_request(MessageType.GET_HISTORY, {})
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return result.get("data", {}).get("history", [])
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def save_message_history(self, messages: list) -> None:
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self._send_request(MessageType.SAVE_HISTORY, {"messages": messages})
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def _send_request(self, message_type: MessageType, payload: Dict[str, Any]) -> Dict[str, Any]:
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import queue
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request_id = f"{id(self)}"
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response_queue = queue.Queue()
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from .server import BackendRequest
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request = BackendRequest(
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request_id=request_id,
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message_type=message_type,
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payload=payload,
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response_queue=response_queue
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def update_config(self, api_key: str, base_url: str = "https://api.deepseek.com", model: str = "deepseek-chat") -> Dict:
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packet = Packet(
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id=self._next_id(),
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type=PacketType.SET_CONFIG,
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body={"api_key": api_key, "base_url": base_url, "model": model}
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)
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self._server._request_queue.put(request)
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try:
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response = response_queue.get(timeout=5.0)
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if not response.success:
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raise Exception(response.error)
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return {"success": True, "data": response.data}
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except queue.Empty:
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return {"success": False, "error": "timeout"}
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return self._server.send(packet).body
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def execute_tool(self, name: str, arguments: Dict) -> Dict:
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packet = Packet(
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id=self._next_id(),
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type=PacketType.EXECUTE_TOOL,
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body={"tool_name": name, "arguments": arguments}
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)
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return self._server.send(packet).body
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def get_status(self) -> Dict:
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packet = Packet(
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id=self._next_id(),
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type=PacketType.GET_STATUS,
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body={}
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)
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return self._server.send(packet).body
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def get_config(self) -> Dict:
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packet = Packet(
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id=self._next_id(),
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type=PacketType.GET_CONFIG,
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body={}
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)
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return self._server.send(packet).body
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def save_history(self, messages: list) -> None:
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packet = Packet(
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id=self._next_id(),
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type=PacketType.SAVE_HISTORY,
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body={"messages": messages}
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)
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self._server.send(packet)
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def get_history(self) -> list:
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packet = Packet(
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id=self._next_id(),
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type=PacketType.GET_HISTORY,
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body={}
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)
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return self._server.send(packet).body.get("history", [])
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def shutdown(self) -> None:
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self._server.shutdown()
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@ -303,12 +303,12 @@ class Neo4jGraph:
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class GraphMemoryClient:
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"""图记忆客户端"""
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def __init__(self, api_key: str, base_url: str, graph):
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def __init__(self, api_key: str, base_url: str, graph, model: str = "deepseek-chat"):
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self.client = OpenAI(api_key=api_key, base_url=base_url)
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self.graph = graph
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self.tools = TOOLS
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self.model = model
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# 使用新的提示词管理器
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prompt_manager = PromptManager()
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self.system_prompt = prompt_manager.get_system_prompt()
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@ -330,7 +330,7 @@ class GraphMemoryClient:
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messages.extend(tool_results)
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response = self.client.chat.completions.create(
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model=MODEL_NAME,
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model=self.model,
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messages=messages,
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tools=self.tools,
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tool_choice="auto"
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@ -347,7 +347,7 @@ class GraphMemoryClient:
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messages.extend(messages_history)
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|
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response = self.client.chat.completions.create(
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model=MODEL_NAME,
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model=self.model,
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messages=messages,
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tools=self.tools,
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tool_choice="auto"
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@ -373,7 +373,7 @@ class GraphMemoryClient:
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messages.extend(tool_results)
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stream = self.client.chat.completions.create(
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model=MODEL_NAME,
|
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model=self.model,
|
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messages=messages,
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tools=self.tools,
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tool_choice="auto",
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|
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@ -10,6 +10,9 @@ class PromptManager:
|
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_instance = None
|
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_cached_prompt = None
|
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|
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# 用户自定义提示词路径
|
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USER_PROMPT_PATH = Path.home() / ".trulymem" / "system_prompt.md"
|
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|
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def __new__(cls):
|
||||
"""单例模式，避免重复加载"""
|
||||
if cls._instance is None:
|
||||
@ -26,11 +29,19 @@ class PromptManager:
|
||||
if PromptManager._cached_prompt is not None:
|
||||
return PromptManager._cached_prompt
|
||||
|
||||
# 1. 优先使用用户自定义提示词
|
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if self.USER_PROMPT_PATH.exists():
|
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with open(self.USER_PROMPT_PATH, "r", encoding="utf-8") as f:
|
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PromptManager._cached_prompt = f.read()
|
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return PromptManager._cached_prompt
|
||||
|
||||
# 2. 使用打包的提示词
|
||||
prompt_file = self.prompts_dir / "system_prompt.md"
|
||||
if prompt_file.exists():
|
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with open(prompt_file, "r", encoding="utf-8") as f:
|
||||
PromptManager._cached_prompt = f.read()
|
||||
else:
|
||||
# 3. 使用内置默认提示词
|
||||
PromptManager._cached_prompt = self._build_default_prompt()
|
||||
|
||||
return PromptManager._cached_prompt
|
||||
@ -78,3 +89,9 @@ class PromptManager:
|
||||
- 如何使用工具
|
||||
|
||||
记住：灵活应对，保持自然对话体验。"""
|
||||
|
||||
@staticmethod
|
||||
def clear_cache():
|
||||
"""清除缓存，强制重新加载提示词"""
|
||||
PromptManager._cached_prompt = None
|
||||
PromptManager._instance = None
|
||||
588
core/server.py
588
core/server.py
@ -2,17 +2,16 @@ import threading
|
||||
import queue
|
||||
import time
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, Optional
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
|
||||
from .embedded_db import EmbeddedGraphDB
|
||||
from .graph_client import GraphMemoryClient
|
||||
from .tool_executor import execute_tool
|
||||
from .tool_limiter import ToolLimiter
|
||||
|
||||
|
||||
class MessageType(Enum):
|
||||
class PacketType(Enum):
|
||||
PROCESS_MESSAGE = "process_message"
|
||||
EXECUTE_TOOL = "execute_tool"
|
||||
GET_STATUS = "get_status"
|
||||
@ -24,46 +23,66 @@ class MessageType(Enum):
|
||||
|
||||
|
||||
@dataclass
|
||||
class BackendRequest:
|
||||
request_id: str
|
||||
message_type: MessageType
|
||||
payload: Dict[str, Any]
|
||||
response_queue: queue.Queue = field(default=None)
|
||||
class Packet:
|
||||
id: str
|
||||
type: PacketType
|
||||
body: Dict[str, Any]
|
||||
response_queue: Optional[queue.Queue] = field(default=None)
|
||||
created_at: float = field(default_factory=time.time)
|
||||
|
||||
|
||||
@dataclass
|
||||
class BackendResponse:
|
||||
request_id: str
|
||||
class PacketResponse:
|
||||
id: str
|
||||
success: bool
|
||||
data: Any = None
|
||||
error: Optional[str] = None
|
||||
|
||||
|
||||
class BackendServer:
|
||||
def __init__(self, db_path: str = "graph_memory.db", use_embedded_db: bool = True):
|
||||
|
||||
DEFAULT_CONFIG_PATH = Path.home() / ".trulymem" / "config.json"
|
||||
|
||||
def __init__(self, db_path: str = "graph_memory.db", use_embedded_db: bool = True, config_file: str = None):
|
||||
self._db_path = db_path
|
||||
self._use_embedded_db = use_embedded_db
|
||||
self._config_file = Path(config_file) if config_file else self.DEFAULT_CONFIG_PATH
|
||||
|
||||
self._graph = None
|
||||
self._client = None
|
||||
self._tool_limiter = ToolLimiter()
|
||||
self._tool_limiter = None
|
||||
|
||||
self._request_queue: queue.Queue[BackendRequest] = queue.Queue()
|
||||
self._input_queue: queue.Queue[Packet] = queue.Queue()
|
||||
self._response_queues: Dict[str, queue.Queue] = {}
|
||||
self._running = False
|
||||
self._thread: Optional[threading.Thread] = None
|
||||
|
||||
self._lock = threading.Lock()
|
||||
self._config = {"api_key": "", "base_url": "https://api.deepseek.com", "model": "deepseek-chat"}
|
||||
self._message_history: list = []
|
||||
|
||||
def start(self, api_key: str = "", base_url: str = "https://api.deepseek.com") -> None:
|
||||
def start(self, api_key: str = "", base_url: str = "https://api.deepseek.com", model: str = "deepseek-chat") -> None:
|
||||
if self._running:
|
||||
return
|
||||
|
||||
self._init_graph()
|
||||
self._load_config()
|
||||
|
||||
if api_key:
|
||||
self._config["api_key"] = api_key
|
||||
if base_url:
|
||||
self._config["base_url"] = base_url
|
||||
if model:
|
||||
self._config["model"] = model
|
||||
|
||||
self._init_graph()
|
||||
self._tool_limiter = self._create_tool_limiter()
|
||||
|
||||
if self._config["api_key"]:
|
||||
from .graph_client import GraphMemoryClient
|
||||
self._client = GraphMemoryClient(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
api_key=self._config["api_key"],
|
||||
base_url=self._config["base_url"],
|
||||
model=self._config.get("model", "deepseek-chat"),
|
||||
graph=self._graph
|
||||
)
|
||||
|
||||
@ -71,6 +90,24 @@ class BackendServer:
|
||||
self._thread = threading.Thread(target=self._run_loop, daemon=True)
|
||||
self._thread.start()
|
||||
|
||||
def _load_config(self) -> None:
|
||||
if self._config_file.exists():
|
||||
try:
|
||||
with open(self._config_file, 'r') as f:
|
||||
saved = json.load(f)
|
||||
self._config.update(saved)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
def _save_config(self) -> None:
|
||||
self._config_file.parent.mkdir(parents=True, exist_ok=True)
|
||||
with open(self._config_file, 'w') as f:
|
||||
json.dump(self._config, f, indent=2)
|
||||
|
||||
def _create_tool_limiter(self):
|
||||
from .tool_limiter import ToolLimiter
|
||||
return ToolLimiter()
|
||||
|
||||
def _init_graph(self) -> None:
|
||||
if self._use_embedded_db:
|
||||
self._graph = EmbeddedGraphDB(db_path=self._db_path)
|
||||
@ -85,310 +122,276 @@ class BackendServer:
|
||||
def _run_loop(self) -> None:
|
||||
while self._running:
|
||||
try:
|
||||
request = self._request_queue.get(timeout=0.1)
|
||||
packet = self._input_queue.get(timeout=0.1)
|
||||
except queue.Empty:
|
||||
continue
|
||||
|
||||
if request.message_type == MessageType.PROCESS_MESSAGE:
|
||||
self._handle_process_message(request)
|
||||
elif request.message_type == MessageType.EXECUTE_TOOL:
|
||||
self._handle_execute_tool(request)
|
||||
elif request.message_type == MessageType.GET_STATUS:
|
||||
self._handle_get_status(request)
|
||||
elif request.message_type == MessageType.GET_CONFIG:
|
||||
self._handle_get_config(request)
|
||||
elif request.message_type == MessageType.SET_CONFIG:
|
||||
self._handle_set_config(request)
|
||||
elif request.message_type == MessageType.GET_HISTORY:
|
||||
self._handle_get_history(request)
|
||||
elif request.message_type == MessageType.SAVE_HISTORY:
|
||||
self._handle_save_history(request)
|
||||
elif request.message_type == MessageType.SHUTDOWN:
|
||||
self._running = False
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data={"status": "shutdown"}
|
||||
))
|
||||
self._process_packet(packet)
|
||||
|
||||
def _handle_process_message(self, request: BackendRequest) -> None:
|
||||
def _process_packet(self, packet: Packet) -> None:
|
||||
response_body = {"error": "not implemented"}
|
||||
|
||||
try:
|
||||
user_input = request.payload.get("user_input", "")
|
||||
if packet.type == PacketType.PROCESS_MESSAGE:
|
||||
response_body = self._handle_process_message(packet.body)
|
||||
elif packet.type == PacketType.EXECUTE_TOOL:
|
||||
response_body = self._handle_execute_tool(packet.body)
|
||||
elif packet.type == PacketType.GET_STATUS:
|
||||
response_body = self._handle_get_status()
|
||||
elif packet.type == PacketType.GET_CONFIG:
|
||||
response_body = self._handle_get_config()
|
||||
elif packet.type == PacketType.SET_CONFIG:
|
||||
response_body = self._handle_set_config(packet.body)
|
||||
elif packet.type == PacketType.GET_HISTORY:
|
||||
response_body = self._handle_get_history()
|
||||
elif packet.type == PacketType.SAVE_HISTORY:
|
||||
response_body = self._handle_save_history(packet.body)
|
||||
elif packet.type == PacketType.SHUTDOWN:
|
||||
self._running = False
|
||||
response_body = {"success": True, "status": "shutdown"}
|
||||
|
||||
if not self._client:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error="API Key 未配置"
|
||||
))
|
||||
return
|
||||
if "success" not in response_body:
|
||||
response_body["success"] = True
|
||||
except Exception as e:
|
||||
response_body["success"] = False
|
||||
response_body["error"] = str(e)
|
||||
|
||||
self._send_response(packet.id, PacketResponse(
|
||||
id=packet.id,
|
||||
success=response_body.get("success", False),
|
||||
data=response_body if response_body.get("success") else None,
|
||||
error=response_body.get("error")
|
||||
))
|
||||
|
||||
def _handle_process_message(self, body: Dict) -> Dict:
|
||||
from .tool_executor import execute_tool
|
||||
|
||||
user_input = body.get("user_input", "")
|
||||
|
||||
if not self._client:
|
||||
return {"success": False, "error": "API Key 未配置", "content": "请先配置 API Key"}
|
||||
|
||||
self._tool_limiter.reset()
|
||||
|
||||
messages_history = [{"role": "user", "content": user_input}]
|
||||
|
||||
response = self._client.send_message_with_history(messages_history)
|
||||
message = response.choices[0].message
|
||||
|
||||
tool_calls = []
|
||||
accumulated_content = ""
|
||||
rejected_tools = []
|
||||
|
||||
while message.tool_calls:
|
||||
if message.content:
|
||||
accumulated_content += message.content + "\n\n"
|
||||
|
||||
self._tool_limiter.reset()
|
||||
|
||||
messages_history = [{"role": "user", "content": user_input}]
|
||||
|
||||
response = self._client.send_message_with_history(messages_history)
|
||||
message = response.choices[0].message
|
||||
|
||||
tool_calls = []
|
||||
accumulated_content = ""
|
||||
rejected_tools = []
|
||||
|
||||
while message.tool_calls:
|
||||
if message.content:
|
||||
accumulated_content += message.content + "\n\n"
|
||||
|
||||
assistant_msg = {
|
||||
"role": "assistant",
|
||||
"content": message.content,
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": tc.id,
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tc.function.name,
|
||||
"arguments": tc.function.arguments
|
||||
}
|
||||
} for tc in message.tool_calls
|
||||
]
|
||||
}
|
||||
messages_history.append(assistant_msg)
|
||||
|
||||
current_tool_results = []
|
||||
for tool_call in message.tool_calls:
|
||||
args = json.loads(tool_call.function.arguments)
|
||||
|
||||
allowed, reason = self._tool_limiter.can_call(tool_call.function.name, args)
|
||||
|
||||
if not allowed:
|
||||
rejected_tools.append((tool_call.function.name, reason))
|
||||
result = f"工具调用被拒绝: {reason}"
|
||||
tool_result_msg = {
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call.id,
|
||||
"content": result
|
||||
assistant_msg = {
|
||||
"role": "assistant",
|
||||
"content": message.content,
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": tc.id,
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tc.function.name,
|
||||
"arguments": tc.function.arguments
|
||||
}
|
||||
current_tool_results.append(tool_result_msg)
|
||||
continue
|
||||
|
||||
self._tool_limiter.record_call(tool_call.function.name, args)
|
||||
|
||||
result = execute_tool(self._graph, tool_call.function.name, args)
|
||||
tool_calls.append({
|
||||
"name": tool_call.function.name,
|
||||
"arguments": args,
|
||||
"result": result
|
||||
})
|
||||
|
||||
} for tc in message.tool_calls
|
||||
]
|
||||
}
|
||||
messages_history.append(assistant_msg)
|
||||
|
||||
current_tool_results = []
|
||||
for tool_call in message.tool_calls:
|
||||
args = json.loads(tool_call.function.arguments)
|
||||
|
||||
allowed, reason = self._tool_limiter.can_call(tool_call.function.name, args)
|
||||
|
||||
if not allowed:
|
||||
rejected_tools.append((tool_call.function.name, reason))
|
||||
result = f"工具调用被拒绝: {reason}"
|
||||
tool_result_msg = {
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call.id,
|
||||
"content": result
|
||||
}
|
||||
current_tool_results.append(tool_result_msg)
|
||||
continue
|
||||
|
||||
messages_history.extend(current_tool_results)
|
||||
self._tool_limiter.record_call(tool_call.function.name, args)
|
||||
|
||||
response = self._client.send_message_with_history(messages_history)
|
||||
message = response.choices[0].message
|
||||
|
||||
final_content = message.content or ""
|
||||
content = accumulated_content + final_content if accumulated_content else final_content
|
||||
|
||||
if not content:
|
||||
content = "(无回复)"
|
||||
|
||||
if tool_calls:
|
||||
tool_names = [tc["name"] for tc in tool_calls]
|
||||
content = f"已执行工具: {', '.join(tool_names)}\n\n{content}"
|
||||
|
||||
if rejected_tools:
|
||||
rejected_info = "\n".join([f"{name}: {reason}" for name, reason in rejected_tools])
|
||||
content += f"\n\n部分工具调用被限制:\n{rejected_info}"
|
||||
content += f"\n\n工具调用统计:\n{self._tool_limiter.get_summary()}"
|
||||
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data={
|
||||
"content": content,
|
||||
"tool_calls": tool_calls,
|
||||
"rejected_tools": rejected_tools
|
||||
result = execute_tool(self._graph, tool_call.function.name, args)
|
||||
tool_calls.append({
|
||||
"name": tool_call.function.name,
|
||||
"arguments": args,
|
||||
"result": result
|
||||
})
|
||||
|
||||
tool_result_msg = {
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call.id,
|
||||
"content": result
|
||||
}
|
||||
))
|
||||
current_tool_results.append(tool_result_msg)
|
||||
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
messages_history.extend(current_tool_results)
|
||||
|
||||
response = self._client.send_message_with_history(messages_history)
|
||||
message = response.choices[0].message
|
||||
|
||||
final_content = message.content or ""
|
||||
content = accumulated_content + final_content if accumulated_content else final_content
|
||||
|
||||
if not content:
|
||||
content = "(无回复)"
|
||||
|
||||
if tool_calls:
|
||||
tool_names = [tc["name"] for tc in tool_calls]
|
||||
content = f"已执行工具: {', '.join(tool_names)}\n\n{content}"
|
||||
|
||||
if rejected_tools:
|
||||
rejected_info = "\n".join([f"{name}: {reason}" for name, reason in rejected_tools])
|
||||
content += f"\n\n部分工具调用被限制:\n{rejected_info}"
|
||||
content += f"\n\n工具调用统计:\n{self._tool_limiter.get_summary()}"
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"content": content,
|
||||
"tool_calls": tool_calls,
|
||||
"rejected_tools": rejected_tools
|
||||
}
|
||||
|
||||
def _handle_execute_tool(self, request: BackendRequest) -> None:
|
||||
"""处理直接工具调用请求（前端直接调用，不受次数限制）"""
|
||||
def _handle_execute_tool(self, body: Dict) -> Dict:
|
||||
from .tool_executor import execute_tool
|
||||
|
||||
try:
|
||||
tool_name = request.payload.get("tool_name")
|
||||
arguments = request.payload.get("arguments", {})
|
||||
tool_name = body.get("tool_name")
|
||||
arguments = body.get("arguments", {})
|
||||
|
||||
# 前端直接调用的工具不受次数限制，直接执行
|
||||
result = execute_tool(self._graph, tool_name, arguments)
|
||||
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data={"result": result}
|
||||
))
|
||||
|
||||
return {"success": True, "result": result}
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
return {"success": False, "error": str(e)}
|
||||
|
||||
def _handle_get_status(self, request: BackendRequest) -> None:
|
||||
try:
|
||||
status = {
|
||||
"graph_initialized": self._graph is not None,
|
||||
"client_initialized": self._client is not None,
|
||||
"running": self._running
|
||||
}
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data=status
|
||||
))
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
def _handle_get_status(self) -> Dict:
|
||||
return {
|
||||
"running": self._running,
|
||||
"config": self._config,
|
||||
"graph_initialized": self._graph is not None,
|
||||
"client_initialized": self._client is not None
|
||||
}
|
||||
|
||||
def _handle_get_config(self, request: BackendRequest) -> None:
|
||||
try:
|
||||
config = self.get_config()
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data=config
|
||||
))
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
def _handle_get_config(self) -> Dict:
|
||||
return self._config.copy()
|
||||
|
||||
def _handle_set_config(self, request: BackendRequest) -> None:
|
||||
try:
|
||||
api_key = request.payload.get("api_key", "")
|
||||
base_url = request.payload.get("base_url", "https://api.deepseek.com")
|
||||
self.update_config(api_key, base_url)
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data={"status": "config_updated"}
|
||||
))
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
|
||||
def _handle_get_history(self, request: BackendRequest) -> None:
|
||||
try:
|
||||
history = self.get_message_history()
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data={"history": history}
|
||||
))
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
|
||||
def _handle_save_history(self, request: BackendRequest) -> None:
|
||||
try:
|
||||
messages = request.payload.get("messages", [])
|
||||
self.save_message_history(messages)
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=True,
|
||||
data={"status": "history_saved"}
|
||||
))
|
||||
except Exception as e:
|
||||
self._send_response(request, BackendResponse(
|
||||
request_id=request.request_id,
|
||||
success=False,
|
||||
error=str(e)
|
||||
))
|
||||
|
||||
def _send_response(self, request: BackendRequest, response: BackendResponse) -> None:
|
||||
if request.response_queue:
|
||||
request.response_queue.put(response)
|
||||
|
||||
def process_message(self, user_input: str, timeout: float = 30.0) -> Dict[str, Any]:
|
||||
request_id = f"{time.time()}"
|
||||
response_queue = queue.Queue()
|
||||
def _handle_set_config(self, body: Dict) -> Dict:
|
||||
api_key = body.get("api_key", "")
|
||||
base_url = body.get("base_url", "https://api.deepseek.com")
|
||||
model = body.get("model", "deepseek-chat")
|
||||
|
||||
request = BackendRequest(
|
||||
request_id=request_id,
|
||||
message_type=MessageType.PROCESS_MESSAGE,
|
||||
payload={"user_input": user_input},
|
||||
response_queue=response_queue
|
||||
self.update_config(api_key, base_url, model)
|
||||
self._save_config()
|
||||
return {"status": "config_updated"}
|
||||
|
||||
def _handle_get_history(self) -> Dict:
|
||||
return {"history": self._message_history}
|
||||
|
||||
def _handle_save_history(self, body: Dict) -> Dict:
|
||||
messages = body.get("messages", [])
|
||||
self._message_history = messages
|
||||
return {"status": "history_saved"}
|
||||
|
||||
def _send_response(self, request_id: str, response: PacketResponse) -> None:
|
||||
with self._lock:
|
||||
q = self._response_queues.pop(request_id, None)
|
||||
if q:
|
||||
q.put(response)
|
||||
|
||||
def send(self, packet: Packet) -> Packet:
|
||||
resp_q = queue.Queue()
|
||||
|
||||
with self._lock:
|
||||
self._response_queues[packet.id] = resp_q
|
||||
|
||||
self._input_queue.put(packet)
|
||||
|
||||
try:
|
||||
response = resp_q.get(timeout=30.0)
|
||||
return Packet(
|
||||
id=response.id,
|
||||
type=packet.type,
|
||||
body={
|
||||
"success": response.success,
|
||||
"data": response.data,
|
||||
"error": response.error
|
||||
}
|
||||
)
|
||||
except queue.Empty:
|
||||
return Packet(
|
||||
id=packet.id,
|
||||
type=packet.type,
|
||||
body={"success": False, "error": "timeout"}
|
||||
)
|
||||
finally:
|
||||
with self._lock:
|
||||
self._response_queues.pop(packet.id, None)
|
||||
|
||||
def process_message(self, user_input: str) -> Dict[str, Any]:
|
||||
packet = Packet(
|
||||
id=f"{time.time()}",
|
||||
type=PacketType.PROCESS_MESSAGE,
|
||||
body={"user_input": user_input}
|
||||
)
|
||||
|
||||
self._request_queue.put(request)
|
||||
|
||||
try:
|
||||
response = response_queue.get(timeout=timeout)
|
||||
if not response.success:
|
||||
raise Exception(response.error)
|
||||
return response.data
|
||||
except queue.Empty:
|
||||
raise TimeoutError("请求超时")
|
||||
response = self.send(packet)
|
||||
return response.body
|
||||
|
||||
def execute_tool(self, tool_name: str, arguments: Dict[str, Any], timeout: float = 10.0) -> str:
|
||||
request_id = f"{time.time()}"
|
||||
response_queue = queue.Queue()
|
||||
|
||||
request = BackendRequest(
|
||||
request_id=request_id,
|
||||
message_type=MessageType.EXECUTE_TOOL,
|
||||
payload={"tool_name": tool_name, "arguments": arguments},
|
||||
response_queue=response_queue
|
||||
def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
|
||||
packet = Packet(
|
||||
id=f"{time.time()}",
|
||||
type=PacketType.EXECUTE_TOOL,
|
||||
body={"tool_name": tool_name, "arguments": arguments}
|
||||
)
|
||||
|
||||
self._request_queue.put(request)
|
||||
response = self.send(packet)
|
||||
return response.body
|
||||
|
||||
def update_config(self, api_key: str, base_url: str = "https://api.deepseek.com", model: str = "deepseek-chat") -> None:
|
||||
with self._lock:
|
||||
self._config["api_key"] = api_key
|
||||
self._config["base_url"] = base_url
|
||||
self._config["model"] = model
|
||||
|
||||
try:
|
||||
response = response_queue.get(timeout=timeout)
|
||||
if not response.success:
|
||||
raise Exception(response.error)
|
||||
return response.data["result"]
|
||||
except queue.Empty:
|
||||
raise TimeoutError("工具执行超时")
|
||||
if api_key and self._graph:
|
||||
from .graph_client import GraphMemoryClient
|
||||
self._client = GraphMemoryClient(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
model=model,
|
||||
graph=self._graph
|
||||
)
|
||||
|
||||
def get_config(self) -> Dict[str, str]:
|
||||
return self._config.copy()
|
||||
|
||||
def save_message_history(self, messages: list) -> None:
|
||||
self._message_history = messages
|
||||
|
||||
def get_message_history(self) -> list:
|
||||
return self._message_history.copy()
|
||||
|
||||
def shutdown(self) -> None:
|
||||
if not self._running:
|
||||
return
|
||||
|
||||
request_id = f"{time.time()}"
|
||||
response_queue = queue.Queue()
|
||||
|
||||
request = BackendRequest(
|
||||
request_id=request_id,
|
||||
message_type=MessageType.SHUTDOWN,
|
||||
payload={},
|
||||
response_queue=response_queue
|
||||
packet = Packet(
|
||||
id=f"{time.time()}",
|
||||
type=PacketType.SHUTDOWN,
|
||||
body={}
|
||||
)
|
||||
|
||||
self._request_queue.put(request)
|
||||
self.send(packet)
|
||||
|
||||
if self._thread:
|
||||
self._thread.join(timeout=2.0)
|
||||
@ -396,22 +399,5 @@ class BackendServer:
|
||||
if self._graph:
|
||||
self._graph.close()
|
||||
self._graph = None
|
||||
|
||||
def update_config(self, api_key: str, base_url: str = "https://api.deepseek.com") -> None:
|
||||
with self._lock:
|
||||
self._config = {"api_key": api_key, "base_url": base_url}
|
||||
if api_key and self._graph:
|
||||
self._client = GraphMemoryClient(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
graph=self._graph
|
||||
)
|
||||
|
||||
def get_config(self) -> Dict[str, str]:
|
||||
return getattr(self, "_config", {"api_key": "", "base_url": "https://api.deepseek.com"})
|
||||
|
||||
def save_message_history(self, messages: list) -> None:
|
||||
self._message_history = messages
|
||||
|
||||
def get_message_history(self) -> list:
|
||||
return getattr(self, "_message_history", [])
|
||||
|
||||
self._running = False
|
||||
@ -2,7 +2,7 @@
|
||||
工具定义模块
|
||||
"""
|
||||
from .memory_tools import TOOLS
|
||||
from .tool_executor import execute_tool
|
||||
from .tool_limiter import ToolLimiter, ToolLimits, ToolCallCount
|
||||
from ..tool_executor import execute_tool
|
||||
from ..tool_limiter import ToolLimiter, ToolLimits, ToolCallCount
|
||||
|
||||
__all__ = ["TOOLS", "execute_tool", "ToolLimiter", "ToolLimits", "ToolCallCount"]
|
||||
|
||||
@ -1,307 +0,0 @@
|
||||
"""
|
||||
工具执行器
|
||||
"""
|
||||
import json
|
||||
from typing import Any, Dict
|
||||
|
||||
|
||||
def execute_tool(graph: Any, tool_name: str, arguments: dict) -> str:
|
||||
"""执行工具调用"""
|
||||
print(f"\n[工具调用] {tool_name}")
|
||||
print(f"[参数] {json.dumps(arguments, ensure_ascii=False, indent=2)}")
|
||||
|
||||
try:
|
||||
# 基础记忆工具
|
||||
if tool_name == "memory_recall":
|
||||
result = graph.recall(
|
||||
query_intent=arguments.get("query_intent", ""),
|
||||
seed_entities=arguments.get("seed_entities"),
|
||||
depth=arguments.get("depth", 2),
|
||||
time_range=arguments.get("time_range"),
|
||||
session_filter=arguments.get("session_filter")
|
||||
)
|
||||
return format_recall_result(result)
|
||||
|
||||
elif tool_name == "memory_commit":
|
||||
result = graph.commit(
|
||||
triplets=arguments.get("triplets", []),
|
||||
entity_types=arguments.get("entity_types"),
|
||||
temporal_tag=arguments.get("temporal_tag")
|
||||
)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "memory_purge":
|
||||
result = graph.purge(
|
||||
criteria=arguments.get("criteria", {}),
|
||||
mode=arguments.get("mode", "soft"),
|
||||
new_relation=arguments.get("new_relation")
|
||||
)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "memory_introspect":
|
||||
result = graph.introspect(session_id=arguments.get("session_id"))
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "memory_archive":
|
||||
result = graph.archive(days=arguments.get("days", 30))
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "memory_cleanup":
|
||||
result = graph.cleanup(dry_run=arguments.get("dry_run", True))
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
# 人设图管理工具
|
||||
elif tool_name == "persona_update":
|
||||
result = execute_persona_update(graph, arguments)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "persona_clear":
|
||||
result = execute_persona_clear(graph, arguments)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
# 工作记忆链管理工具
|
||||
elif tool_name == "task_create":
|
||||
result = execute_task_create(graph, arguments)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "task_set_state":
|
||||
result = execute_task_set_state(graph, arguments)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "task_delete":
|
||||
result = execute_task_delete(graph, arguments)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
elif tool_name == "task_link_info":
|
||||
result = execute_task_link_info(graph, arguments)
|
||||
return json.dumps(result, ensure_ascii=False, default=str)
|
||||
|
||||
return f"未知工具: {tool_name}"
|
||||
|
||||
except Exception as e:
|
||||
return f"工具执行错误: {str(e)}"
|
||||
|
||||
|
||||
def format_recall_result(result: dict) -> str:
|
||||
"""格式化检索结果"""
|
||||
lines = ["===== 记忆检索结果 ====="]
|
||||
|
||||
if result.get("entities"):
|
||||
lines.append(f"\n实体 ({len(result['entities'])} 个):")
|
||||
for e in result["entities"]:
|
||||
if e and isinstance(e, dict):
|
||||
lines.append(f" - {e.get('name', 'N/A')} (类型: {e.get('type', 'unknown')}, 提及: {e.get('mention_count', 1)}次)")
|
||||
|
||||
if result.get("relations"):
|
||||
lines.append(f"\n关系 ({len(result['relations'])} 条):")
|
||||
for r in result["relations"]:
|
||||
if r and isinstance(r, dict):
|
||||
lines.append(f" - {r.get('source', 'N/A')} --[{r.get('type', 'N/A')}]--> {r.get('target', 'N/A')}")
|
||||
created = r.get("created_at", "N/A")
|
||||
if created and created != "N/A":
|
||||
created = created[:19] if "T" in str(created) else str(created)
|
||||
session_id = r.get('session_id', 'N/A')
|
||||
session_display = session_id[:20] if session_id and session_id != 'N/A' else 'N/A'
|
||||
lines.append(f" 时间: {created}, 会话: {session_display}, 轮次: {r.get('turn_id', 0)}, 置信度: {r.get('confidence', 1.0)}")
|
||||
|
||||
if not result.get("entities") and not result.get("relations"):
|
||||
lines.append("\n(未找到相关记忆)")
|
||||
|
||||
lines.append("=" * 30)
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
# 人设图管理工具实现
|
||||
def execute_persona_update(graph: Any, arguments: dict) -> dict:
|
||||
"""更新人设"""
|
||||
attributes = arguments.get("attributes", [])
|
||||
mode = arguments.get("mode", "merge")
|
||||
|
||||
if mode == "replace":
|
||||
# 先清除旧人设
|
||||
graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "扮演角色"},
|
||||
mode="soft"
|
||||
)
|
||||
graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "说话风格"},
|
||||
mode="soft"
|
||||
)
|
||||
graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "性格特点"},
|
||||
mode="soft"
|
||||
)
|
||||
|
||||
# 写入新人设
|
||||
triplets = []
|
||||
for attr in attributes:
|
||||
triplets.append({
|
||||
"subject": "AI",
|
||||
"relation": attr["attribute"],
|
||||
"object": attr["value"],
|
||||
"confidence": 1.0
|
||||
})
|
||||
|
||||
result = graph.commit(triplets=triplets)
|
||||
return {
|
||||
"status": "success",
|
||||
"mode": mode,
|
||||
"updated_attributes": len(attributes),
|
||||
"details": result
|
||||
}
|
||||
|
||||
|
||||
def execute_persona_clear(graph: Any, arguments: dict) -> dict:
|
||||
"""清除人设"""
|
||||
if not arguments.get("confirm", True):
|
||||
return {"status": "cancelled", "message": "需要确认才能清除人设"}
|
||||
|
||||
# 删除所有人设相关关系
|
||||
result1 = graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "扮演角色"},
|
||||
mode="soft"
|
||||
)
|
||||
result2 = graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "说话风格"},
|
||||
mode="soft"
|
||||
)
|
||||
result3 = graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "性格特点"},
|
||||
mode="soft"
|
||||
)
|
||||
result4 = graph.purge(
|
||||
criteria={"subject_contains": "AI", "relation_type": "语气特征"},
|
||||
mode="soft"
|
||||
)
|
||||
|
||||
total_deleted = (
|
||||
result1.get("deleted_count", 0) +
|
||||
result2.get("deleted_count", 0) +
|
||||
result3.get("deleted_count", 0) +
|
||||
result4.get("deleted_count", 0)
|
||||
)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"deleted_count": total_deleted,
|
||||
"message": "人设已清除，恢复默认身份"
|
||||
}
|
||||
|
||||
|
||||
# 工作记忆链管理工具实现
|
||||
def execute_task_create(graph: Any, arguments: dict) -> dict:
|
||||
"""创建任务节点"""
|
||||
task_id = arguments.get("task_id")
|
||||
description = arguments.get("description")
|
||||
info_nodes = arguments.get("info_nodes", [])
|
||||
|
||||
# 创建任务节点
|
||||
triplets = [
|
||||
{"subject": task_id, "relation": "is_type", "object": "TaskNode"},
|
||||
{"subject": task_id, "relation": "has_description", "object": description},
|
||||
{"subject": task_id, "relation": "HAS_STATE", "object": "State_进行中"}
|
||||
]
|
||||
|
||||
result = graph.commit(triplets=triplets)
|
||||
|
||||
# 关联信息节点
|
||||
if info_nodes:
|
||||
link_triplets = []
|
||||
for node_name in info_nodes:
|
||||
link_triplets.append({
|
||||
"subject": task_id,
|
||||
"relation": "CONTAINS_INFO",
|
||||
"object": node_name
|
||||
})
|
||||
graph.commit(triplets=link_triplets)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"task_id": task_id,
|
||||
"description": description,
|
||||
"info_nodes": info_nodes,
|
||||
"details": result
|
||||
}
|
||||
|
||||
|
||||
def execute_task_set_state(graph: Any, arguments: dict) -> dict:
|
||||
"""设置任务状态"""
|
||||
task_id = arguments.get("task_id")
|
||||
state = arguments.get("state")
|
||||
|
||||
# 删除旧状态
|
||||
graph.purge(
|
||||
criteria={"subject_contains": task_id, "relation_type": "HAS_STATE"},
|
||||
mode="soft"
|
||||
)
|
||||
|
||||
# 设置新状态
|
||||
state_node = f"State_{state}"
|
||||
result = graph.commit(
|
||||
triplets=[{"subject": task_id, "relation": "HAS_STATE", "object": state_node}]
|
||||
)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"task_id": task_id,
|
||||
"new_state": state,
|
||||
"details": result
|
||||
}
|
||||
|
||||
|
||||
def execute_task_delete(graph: Any, arguments: dict) -> dict:
|
||||
"""删除任务节点"""
|
||||
task_id = arguments.get("task_id")
|
||||
delete_info_nodes = arguments.get("delete_info_nodes", True)
|
||||
|
||||
# 查询关联的信息节点
|
||||
if delete_info_nodes:
|
||||
recall_result = graph.recall(
|
||||
query_intent=f"{task_id},CONTAINS_INFO",
|
||||
depth=1
|
||||
)
|
||||
|
||||
# 删除信息节点
|
||||
for relation in recall_result.get("relations", []):
|
||||
if relation.get("type") == "CONTAINS_INFO" and relation.get("source") == task_id:
|
||||
info_node = relation.get("target")
|
||||
graph.purge(
|
||||
criteria={"subject_contains": info_node},
|
||||
mode="soft"
|
||||
)
|
||||
|
||||
# 删除任务节点
|
||||
result = graph.purge(
|
||||
criteria={"subject_contains": task_id},
|
||||
mode="soft"
|
||||
)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"task_id": task_id,
|
||||
"deleted_info_nodes": delete_info_nodes,
|
||||
"details": result
|
||||
}
|
||||
|
||||
|
||||
def execute_task_link_info(graph: Any, arguments: dict) -> dict:
|
||||
"""关联信息节点"""
|
||||
task_id = arguments.get("task_id")
|
||||
info_node_names = arguments.get("info_node_names", [])
|
||||
|
||||
triplets = []
|
||||
for node_name in info_node_names:
|
||||
triplets.append({
|
||||
"subject": task_id,
|
||||
"relation": "CONTAINS_INFO",
|
||||
"object": node_name
|
||||
})
|
||||
|
||||
result = graph.commit(triplets=triplets)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"task_id": task_id,
|
||||
"linked_nodes": info_node_names,
|
||||
"details": result
|
||||
}
|
||||
@ -1,164 +0,0 @@
|
||||
"""
|
||||
工具调用限制器 - 限制每轮对话中各类工具的调用次数
|
||||
"""
|
||||
from typing import Dict, List, Optional
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
|
||||
@dataclass
|
||||
class ToolLimits:
|
||||
"""工具调用限制配置"""
|
||||
# 人设图限制
|
||||
persona_query_max: int = 1 # 每轮最多查询1次人设图
|
||||
persona_update_max: int = 1 # 每轮最多修改1次人设图
|
||||
|
||||
# 工作记忆链限制
|
||||
task_query_max: int = 4 # 每轮最多查询4次工作记忆链
|
||||
task_update_max: int = 2 # 每轮最多修改2次工作记忆链
|
||||
|
||||
# 一般记忆限制
|
||||
memory_query_max: int = 20 # 每轮最多查询20次一般记忆
|
||||
memory_update_max: int = 10 # 每轮最多修改10次一般记忆
|
||||
|
||||
|
||||
@dataclass
|
||||
class ToolCallCount:
|
||||
"""工具调用计数"""
|
||||
# 人设图
|
||||
persona_query: int = 0
|
||||
persona_update: int = 0
|
||||
|
||||
# 工作记忆链
|
||||
task_query: int = 0
|
||||
task_update: int = 0
|
||||
|
||||
# 一般记忆
|
||||
memory_query: int = 0
|
||||
memory_update: int = 0
|
||||
|
||||
|
||||
class ToolLimiter:
|
||||
"""工具调用限制器"""
|
||||
|
||||
def __init__(self, limits: Optional[ToolLimits] = None):
|
||||
self.limits = limits or ToolLimits()
|
||||
self.counts = ToolCallCount()
|
||||
|
||||
def _classify_tool(self, tool_name: str, arguments: dict) -> tuple:
|
||||
"""
|
||||
分类工具调用
|
||||
返回: (category, operation)
|
||||
category: 'persona', 'task', 'memory'
|
||||
operation: 'query', 'update'
|
||||
"""
|
||||
# 人设图工具
|
||||
if tool_name in ('persona_update', 'persona_clear'):
|
||||
return ('persona', 'update')
|
||||
|
||||
# 工作记忆链工具
|
||||
if tool_name in ('task_create', 'task_set_state', 'task_delete', 'task_link_info'):
|
||||
# task_link_info 是关联操作，算作更新
|
||||
return ('task', 'update')
|
||||
|
||||
# 一般记忆工具
|
||||
if tool_name == 'memory_recall':
|
||||
# 判断是查询人设图、工作记忆链还是一般记忆
|
||||
query_intent = arguments.get('query_intent', '').lower()
|
||||
|
||||
# 检查是否查询人设图
|
||||
if any(kw in query_intent for kw in ['人设', '角色', '性格', '语气', '说话风格', '扮演']):
|
||||
return ('persona', 'query')
|
||||
|
||||
# 检查是否查询工作记忆链
|
||||
if any(kw in query_intent for kw in ['tasknode', '工作记忆', '任务链', '任务', 'task']):
|
||||
return ('task', 'query')
|
||||
|
||||
# 一般记忆查询
|
||||
return ('memory', 'query')
|
||||
|
||||
if tool_name == 'memory_commit':
|
||||
return ('memory', 'update')
|
||||
|
||||
if tool_name == 'memory_purge':
|
||||
return ('memory', 'update')
|
||||
|
||||
if tool_name == 'memory_introspect':
|
||||
return ('memory', 'query')
|
||||
|
||||
if tool_name in ('memory_archive', 'memory_cleanup'):
|
||||
return ('memory', 'update')
|
||||
|
||||
# 未知工具，归类为一般记忆更新
|
||||
return ('memory', 'update')
|
||||
|
||||
def can_call(self, tool_name: str, arguments: dict) -> tuple:
|
||||
"""
|
||||
检查是否允许调用工具
|
||||
返回: (allowed, reason)
|
||||
"""
|
||||
category, operation = self._classify_tool(tool_name, arguments)
|
||||
|
||||
# 获取当前计数和限制
|
||||
if category == 'persona':
|
||||
if operation == 'query':
|
||||
if self.counts.persona_query >= self.limits.persona_query_max:
|
||||
return (False, f"人设图查询次数已达上限({self.limits.persona_query_max}次)")
|
||||
else: # update
|
||||
if self.counts.persona_update >= self.limits.persona_update_max:
|
||||
return (False, f"人设图修改次数已达上限({self.limits.persona_update_max}次)")
|
||||
|
||||
elif category == 'task':
|
||||
if operation == 'query':
|
||||
if self.counts.task_query >= self.limits.task_query_max:
|
||||
return (False, f"工作记忆链查询次数已达上限({self.limits.task_query_max}次)")
|
||||
else: # update
|
||||
if self.counts.task_update >= self.limits.task_update_max:
|
||||
return (False, f"工作记忆链修改次数已达上限({self.limits.task_update_max}次)")
|
||||
|
||||
elif category == 'memory':
|
||||
if operation == 'query':
|
||||
if self.counts.memory_query >= self.limits.memory_query_max:
|
||||
return (False, f"一般记忆查询次数已达上限({self.limits.memory_query_max}次)")
|
||||
else: # update
|
||||
if self.counts.memory_update >= self.limits.memory_update_max:
|
||||
return (False, f"一般记忆修改次数已达上限({self.limits.memory_update_max}次)")
|
||||
|
||||
return (True, "允许调用")
|
||||
|
||||
def record_call(self, tool_name: str, arguments: dict) -> None:
|
||||
"""记录工具调用"""
|
||||
category, operation = self._classify_tool(tool_name, arguments)
|
||||
|
||||
if category == 'persona':
|
||||
if operation == 'query':
|
||||
self.counts.persona_query += 1
|
||||
else:
|
||||
self.counts.persona_update += 1
|
||||
|
||||
elif category == 'task':
|
||||
if operation == 'query':
|
||||
self.counts.task_query += 1
|
||||
else:
|
||||
self.counts.task_update += 1
|
||||
|
||||
elif category == 'memory':
|
||||
if operation == 'query':
|
||||
self.counts.memory_query += 1
|
||||
else:
|
||||
self.counts.memory_update += 1
|
||||
|
||||
def get_summary(self) -> str:
|
||||
"""获取调用统计摘要"""
|
||||
lines = [
|
||||
f"人设图: 查询{self.counts.persona_query}/{self.limits.persona_query_max}次, "
|
||||
f"修改{self.counts.persona_update}/{self.limits.persona_update_max}次",
|
||||
f"工作记忆链: 查询{self.counts.task_query}/{self.limits.task_query_max}次, "
|
||||
f"修改{self.counts.task_update}/{self.limits.task_update_max}次",
|
||||
f"一般记忆: 查询{self.counts.memory_query}/{self.limits.memory_query_max}次, "
|
||||
f"修改{self.counts.memory_update}/{self.limits.memory_update_max}次"
|
||||
]
|
||||
return "\n".join(lines)
|
||||
|
||||
def reset(self) -> None:
|
||||
"""重置计数（新的一轮对话开始时调用）"""
|
||||
self.counts = ToolCallCount()
|
||||
Reference in New Issue
Block a user