Fix display of tool results
This commit is contained in:
dimitrievgs
parent
305f8813a8
commit
82891822a5
27
app/api.py
27
app/api.py
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@ -10,6 +10,7 @@ from flask_cors import CORS
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from flask_socketio import SocketIO
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from workflows import graph_history_manager, run_agent_streaming
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from llm_client import DEFAULT_TEMPERATURE, MODELS, get_llm # Добавляем импорт списка моделей
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import base64
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api = Flask(__name__)
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CORS(
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@ -260,6 +261,11 @@ def chat_stream():
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# Запускаем стриминг ответа от LLM (используем обновленный агент)
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accumulated_content = ""
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# Вспомогательная функция для безопасной передачи JSON в HTML-атрибутах
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def safe_b64(text):
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if not text: return "e30=" # пустой json '{}'
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return base64.b64encode(str(text).encode('utf-8')).decode('utf-8')
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try:
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for chunk_data in run_agent_streaming(graph_id, user_node_id,
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assistant_node_id,
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@ -271,6 +277,27 @@ def chat_stream():
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if chunk_data.get("type") in ["chunk", "tool_start", "tool_end"]:
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if chunk_data.get("type") == "chunk":
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accumulated_content += chunk_data.get("content", "")
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elif chunk_data.get("type") == "tool_start":
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# Встраиваем стартовый маркер в память базы данных
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start_marker = f'\n\n<div class="agent-tool-call" data-name="{chunk_data.get("name")}" data-step="{chunk_data.get("step")}" data-status="start"></div>\n\n'
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accumulated_content += start_marker
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elif chunk_data.get("type") == "tool_end":
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# Находим стартовый маркер и меняем его на финальный с данными
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search_marker = f'<div class="agent-tool-call" data-name="{chunk_data.get("name")}" data-step="{chunk_data.get("step")}" data-status="start"></div>'
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req_b64 = safe_b64(chunk_data.get("request"))
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res_b64 = safe_b64(chunk_data.get("response"))
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status = "error" if chunk_data.get("is_error") else "success"
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end_marker = f'<div class="agent-tool-call" data-name="{chunk_data.get("name")}" data-step="{chunk_data.get("step")}" data-status="{status}" data-req="{req_b64}" data-res="{res_b64}"></div>'
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if search_marker in accumulated_content:
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accumulated_content = accumulated_content.replace(search_marker, end_marker)
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else:
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accumulated_content += f'\n\n{end_marker}\n\n'
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yield f"data: {json.dumps(chunk_data)}\n\n"
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# Обработка ошибки во время стриминга (крашим узел на фронте)
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125
app/mcp_tools.py
Normal file
125
app/mcp_tools.py
Normal file
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@ -0,0 +1,125 @@
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from pydantic import BaseModel, Field, create_model
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from langchain_core.tools import StructuredTool
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# ----------------- MCP MANAGER -----------------
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try:
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from mcp.client.stdio import stdio_client, StdioServerParameters
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from mcp.client.session import ClientSession
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MCP_AVAILABLE = True
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except ImportError:
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MCP_AVAILABLE = False
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_MCP_CACHED_TOOLS = {}
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def json_schema_to_pydantic(schema: dict, model_name: str) -> type[BaseModel]:
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"""Преобразует JSON Schema от MCP сервера в Pydantic модель для LangChain"""
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fields = {}
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properties = schema.get("properties", {})
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required = schema.get("required", [])
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for key, val in properties.items():
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t = val.get("type", "string")
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py_type = str
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if t == "integer": py_type = int
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elif t == "number": py_type = float
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elif t == "boolean": py_type = bool
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elif t == "array": py_type = list
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elif t == "object": py_type = dict
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desc = val.get("description", "")
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if key in required:
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fields[key] = (py_type, Field(..., description=desc))
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else:
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fields[key] = (py_type, Field(default=None, description=desc))
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if not fields:
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fields["kwargs"] = (dict, Field(default_factory=dict, description="Аргументы"))
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return create_model(model_name, **fields)
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def create_mcp_tool(server_config, tool_name, tool_desc, json_schema, full_env, args, debug_callback=None):
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"""Обертка, которая поднимает контейнер/процесс ровно на 1 вызов тула и убивает его"""
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args_schema = json_schema_to_pydantic(json_schema, f"MCP_{tool_name.replace('-','_')}_Schema")
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command = server_config.get("command")
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def mcp_tool_runner(**kwargs):
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import asyncio
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import json
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input_json = json.dumps(kwargs, indent=2, ensure_ascii=False)
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async def _run():
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server_params = StdioServerParameters(command=command, args=args, env=full_env)
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async with stdio_client(server_params) as (read, write):
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async with ClientSession(read, write) as session:
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await session.initialize()
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result = await session.call_tool(tool_name, arguments=kwargs)
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text_outputs = []
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for c in result.content:
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if hasattr(c, 'text'):
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text_outputs.append(c.text)
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else:
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text_outputs.append(str(c))
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return "\n".join(text_outputs)
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raw_output = asyncio.run(_run())
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if debug_callback:
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# debug_callback(f"MCP: {tool_name}\n" + input_json, raw_output)
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debug_callback(kwargs, raw_output)
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return f"Инструмент '{tool_name}' вернул следующий результат:\n<tool_output>\n{raw_output}\n</tool_output>"
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return StructuredTool.from_function(
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func=mcp_tool_runner,
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name=tool_name.replace('-','_'), # Langchain не любит тире в именах
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description=tool_desc or f"MCP Tool {tool_name}",
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args_schema=args_schema
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)
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def fetch_mcp_tools(server_config, debug_callback=None):
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"""Один раз читает список тулов от сервера и кеширует их схемы"""
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if not MCP_AVAILABLE:
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print("⚠️ MCP серверы настроены, но библиотека 'mcp' не установлена. Выполните: pip install mcp")
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return []
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import asyncio
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import shlex
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import os
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config_hash = str(server_config) # primitive hash
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if config_hash in _MCP_CACHED_TOOLS:
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return _MCP_CACHED_TOOLS[config_hash]
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async def _fetch():
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command = server_config.get("command", "")
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args_str = server_config.get("args", "")
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args = shlex.split(args_str) if args_str else []
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env_dict = {}
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env_str = server_config.get("envString", "")
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if env_str:
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for pair in env_str.split(','):
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if '=' in pair:
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k, v = pair.split('=', 1)
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env_dict[k.strip()] = v.strip()
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full_env = {**os.environ.copy(), **env_dict}
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server_params = StdioServerParameters(command=command, args=args, env=full_env)
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async with stdio_client(server_params) as (read, write):
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async with ClientSession(read, write) as session:
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await session.initialize()
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tools_resp = await session.list_tools()
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return tools_resp.tools, full_env, args
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try:
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raw_tools, full_env, args = asyncio.run(_fetch())
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wrapped_tools = []
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for t in raw_tools:
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wrapped_tools.append(create_mcp_tool(server_config, t.name, t.description, t.inputSchema, full_env, args, debug_callback))
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_MCP_CACHED_TOOLS[config_hash] = wrapped_tools
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print(f"🔌 Успешно загружено {len(wrapped_tools)} инструментов от MCP-сервера '{server_config.get('name')}'")
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return wrapped_tools
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except Exception as e:
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print(f"❌ Ошибка инициализации MCP сервера {server_config.get('name')}: {e}")
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return []
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@ -16,9 +16,10 @@ import json
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import os
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import sys
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from typing import Any, get_type_hints
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from langchain_core.tools import StructuredTool
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from pydantic import BaseModel, Field, create_model
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from mcp_tools import fetch_mcp_tools
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def build_react_agent(model_name: str, temperature: float, max_tokens: int, agency_mode: bool, obsidian_settings: dict, debug_callback=None):
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"""Инициализация ядра на базе LangGraph."""
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m_cfg = MODELS.get(model_name)
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@ -166,6 +167,8 @@ finally:
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def get_dynamic_tools(obsidian_settings: dict, debug_callback=None):
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"""Собирает инструменты двух видов на основе настроек Obsidian."""
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tools = []
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# Инициализация внутренних инструментов (скриптов)
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custom_tools = obsidian_settings.get("customTools", [])
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for ct in custom_tools:
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@ -247,6 +250,12 @@ def get_dynamic_tools(obsidian_settings: dict, debug_callback=None):
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)
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tools.append(help_tool)
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# Инициализация внутренних MCP серверов
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mcp_servers = obsidian_settings.get("mcpServers", [])
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for mcp_server in mcp_servers:
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mcp_tools = fetch_mcp_tools(mcp_server, debug_callback)
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tools.extend(mcp_tools)
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return tools
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def _build_pydantic_schema_from_func(func) -> type[BaseModel]:
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26
app/test_mcp.py
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26
app/test_mcp.py
Normal file
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@ -0,0 +1,26 @@
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# test_mcp.py
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import asyncio
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import sys
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print(f"Python: {sys.version}")
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from mcp.client.stdio import stdio_client, StdioServerParameters
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from mcp.client.session import ClientSession
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async def test():
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params = StdioServerParameters(
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command="podman",
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args=["run", "-i", "--rm", "ddg-mcp-server"],
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env=None
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)
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print("opening stdio_client...")
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async with stdio_client(params) as (read, write):
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print("creating session...")
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async with ClientSession(read, write) as session:
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print("initializing...")
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await session.initialize()
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print("OK!")
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tools = await session.list_tools()
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for t in tools.tools:
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print(f" - {t.name}")
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asyncio.run(test())
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@ -105,6 +105,7 @@ def run_agent_streaming(graph_id: str,
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# 4. Выполняем цикл с потоковой передачей событий
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step_counter = 0
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tool_mapping = {} # Хранит связку: ID вызова -> Номер шага
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# LangGraph Stream Mode 'messages': отдает чанки токенов и вызовы функций
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for chunk, metadata in agent_executor.stream({"messages": messages_for_llm}, stream_mode="messages"):
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@ -115,6 +116,10 @@ def run_agent_streaming(graph_id: str,
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for tc in chunk.tool_call_chunks:
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if "name" in tc and tc["name"]:
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step_counter += 1
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tc_id = tc.get("id", f"unknown_{step_counter}")
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# Сохраняем шаг для этого конкретного вызова
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tool_mapping[tc_id] = step_counter
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yield {
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"type": "tool_start",
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"name": tc["name"],
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@ -132,23 +137,31 @@ def run_agent_streaming(graph_id: str,
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# Тул отработал и принес ответ
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elif hasattr(chunk, "type") and chunk.type == "tool":
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req = ""
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res = str(chunk.content)
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# Достаем JSON отправленных параметров из последнего debug_callback
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if current_run_debug:
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dbg = current_run_debug.pop(0) # Берем первый из очереди
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req = dbg.get("req", "")
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# Ловушка для определения ошибок
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is_error = False
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if getattr(chunk, "status", "") == "error" or "ОШИБКА ИСПОЛНЕНИЯ" in res or "SCRIPT RUNTIME ERROR" in res:
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is_error = True
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# Достаем ИМЕННО ТОТ ШАГ, на котором начинался вызов этого инструмента
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tc_id = getattr(chunk, "tool_call_id", "")
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actual_step = tool_mapping.get(tc_id, step_counter) # Fallback, если id нет
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yield {
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"type": "tool_end",
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"name": chunk.name,
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"step": step_counter,
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"node_id": assistant_node_id
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}
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# В САМОМ КОНЦЕ, после того как агент закончил работу (вышел из цикла)
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if current_run_debug and obsidian_settings.get('showDebugInfo'):
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debug_section = "\n\n---\n" + "\n\n---\n".join([
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f"**JSON Request:**\n```json\n{d['req']}\n```\n**Result:**\n```text\n{d['res']}\n```"
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for d in current_run_debug
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])
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yield {
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"type": "chunk",
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"content": debug_section,
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"node_id": assistant_node_id
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"name": getattr(chunk, "name", "tool"),
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"step": actual_step,
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"node_id": assistant_node_id,
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"request": req,
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"response": res,
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"is_error": is_error
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}
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except Exception as e:
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