chore: refactor app MCP configuration and implement AI chat functionality

apps/application/chat_pipeline/step/chat_step/impl/base_chat_step.py

@@ -269,14 +269,8 @@ class BaseChatStep(IChatStep):
                 self.context['application_ids'] = application_ids
                 for application_id in application_ids:
                     app = QuerySet(Application).filter(id=application_id).first()
-                    app_key = QuerySet(ApplicationApiKey).filter(application_id=application_id, is_active=True).first()
-                    # TODO 处理api
-                    if app_key is not None:
-                        api_key = app_key.secret_key
-                    else:
-                        continue
                     executor = ToolExecutor()
-                    app_config = executor.get_app_mcp_config(api_key, app.name, app.desc)
+                    app_config = executor.get_app_mcp_config(app.id, app.name, app.desc)
                     mcp_servers_config[str(app.id)] = app_config
 
         if len(mcp_servers_config) > 0:

apps/common/utils/app_mcp.py

@@ -0,0 +1,70 @@
+import json
+import logging
+import os
+import sys
+
+import uuid_utils.compat as uuid
+from asgiref.sync import sync_to_async
+from mcp.server.fastmcp import FastMCP
+
+logging.basicConfig(level=logging.WARNING)
+logging.getLogger("mcp").setLevel(logging.ERROR)
+logging.getLogger("mcp.server").setLevel(logging.ERROR)
+
+
+def app_mcp_init(base_dir: str, application_id: str, name: str, description: str):
+    import django
+
+    sys.path.insert(0, base_dir)
+
+    os.environ.setdefault("DJANGO_SETTINGS_MODULE", "maxkb.settings")
+
+    django.setup()
+    mcp = FastMCP()
+
+    @sync_to_async
+    def _get_chat_id():
+        from application.models import ChatUserType
+        from chat.serializers.chat import OpenChatSerializers
+        from common.init import init_template
+
+        init_template.run()
+
+        return OpenChatSerializers(data={
+            'application_id': application_id,
+            'chat_user_id': str(uuid.uuid7()),
+            'chat_user_type': ChatUserType.ANONYMOUS_USER,
+            'debug': False
+        }).open()
+
+    @sync_to_async
+    def _chat_with_ai(chat_id: str, message: str) -> str:
+        from application.models import ChatUserType
+        from chat.serializers.chat import ChatSerializers
+
+        payload = {
+            'message': message,
+            'stream': False,
+            're_chat': False
+        }
+        resp = ChatSerializers(data={
+            'chat_id': chat_id,
+            'chat_user_id': str(uuid.uuid7()),
+            'chat_user_type': ChatUserType.ANONYMOUS_USER,
+            'application_id': application_id,
+            'debug': False,
+        }).chat(payload)
+        data = json.loads(str(resp.text))
+        return str(data.get("data", {}).get("content") or data.get("response"))
+
+    @mcp.tool(description=f'{name} {description}')
+    async def ai_chat(message: str) -> str:
+        chat_id = await _get_chat_id()
+        reply = await _chat_with_ai(chat_id, message)
+
+        return reply or "AI 未能生成回复"
+
+    mcp.run(transport='stdio')
+
+
+app_mcp_init(sys.argv[1], sys.argv[2], sys.argv[3], sys.argv[4])

apps/common/utils/tool_code.py

@@ -233,59 +233,18 @@ exec({dedent(code)!a})
         }
         return tool_config
 
-    def get_app_mcp_config(self, api_key, name, description):
-        chat_path = CONFIG.get_chat_path()
-        _code = f'''
-import requests
-from typing import Optional
-
-def _get_chat_id() -> Optional[str]:
-    url = f"http://127.0.0.1:8080{chat_path}/api/open"
-    headers = {{
-        'accept': '*/*',
-        'Authorization': f'Bearer {api_key}'
-    }}
-    try:
-        resp = requests.get(url, headers=headers, timeout=10)
-        resp.raise_for_status()
-        return resp.json().get("data")
-    except Exception as e:
-        raise e
-
-
-def _chat_with_ai(chat_id: str, message: str) -> Optional[str]:
-    url = f"http://127.0.0.1:8080{chat_path}/api/chat_message/{{chat_id}}"
-    headers = {{"Content-Type": "application/json", "Authorization": f'Bearer {api_key}'}}
-    payload = {{
-        "message": message,
-        "re_chat": False,
-        "stream": False
-    }}
-    try:
-        resp = requests.post(url, json=payload, headers=headers, timeout=600)
-        resp.raise_for_status()
-        data = resp.json()
-        return str(data.get("data", {{}}).get("content") or data.get("response"))
-    except Exception as e:
-        raise e
-
-def ai_chat(message: str) -> str:
-    chat_id = _get_chat_id()
-    reply = _chat_with_ai(chat_id, message)
-    return reply or "AI 未能生成回复"
-
-        '''
-        _code = self.generate_mcp_server_code(_code, {}, name, description)
-        # print(_code)
-        maxkb_logger.debug(f"Python code of mcp app: {_code}")
-        compressed_and_base64_encoded_code_str = base64.b64encode(gzip.compress(_code.encode())).decode()
+    def get_app_mcp_config(self, application_id, name, description):
+        cwd = os.path.dirname(os.path.abspath(__file__))
         app_config = {
             'command': sys.executable,
             'args': [
-                '-c',
-                f'import base64,gzip; exec(gzip.decompress(base64.b64decode(\'{compressed_and_base64_encoded_code_str}\')).decode())',
+                f'{cwd}/app_mcp.py',
+                BASE_DIR,
+                str(application_id),
+                name,
+                description,
             ],
-            'cwd': _sandbox_path,
+            'cwd': BASE_DIR,
             'env': {
                 'LD_PRELOAD': f'{_sandbox_path}/lib/sandbox.so',
             },