优化了部分代码

app/api/endpoints/admin.py

@@ -0,0 +1,145 @@
+from fastapi import APIRouter, HTTPException, Depends
+from app.core.auth import get_current_admin_user
+from app.core.config import LLM_CONFIG, DEFAULT_RESET_PASSWORD, MAX_FILE_SIZE, MAX_IMAGE_SIZE
+from pydantic import BaseModel
+import os
+import json
+from pathlib import Path
+
+router = APIRouter()
+
+# 配置文件路径
+CONFIG_FILE = Path(__file__).parent.parent.parent.parent / "config" / "system_config.json"
+
+class SystemConfigModel(BaseModel):
+    model_name: str
+    system_prompt: str
+    DEFAULT_RESET_PASSWORD: str
+    MAX_FILE_SIZE: int  # 字节为单位
+    MAX_IMAGE_SIZE: int  # 字节为单位
+
+class SystemConfigResponse(BaseModel):
+    model_name: str
+    system_prompt: str
+    DEFAULT_RESET_PASSWORD: str
+    MAX_FILE_SIZE: int
+    MAX_IMAGE_SIZE: int
+    message: str = ""
+
+def load_config_from_file():
+    """从文件加载配置，如果文件不存在则返回默认配置"""
+    try:
+        if CONFIG_FILE.exists():
+            with open(CONFIG_FILE, 'r', encoding='utf-8') as f:
+                return json.load(f)
+    except Exception:
+        pass
+
+    # 返回默认配置
+    return {
+        'model_name': LLM_CONFIG['model_name'],
+        'system_prompt': LLM_CONFIG['system_prompt'],
+        'DEFAULT_RESET_PASSWORD': DEFAULT_RESET_PASSWORD,
+        'MAX_FILE_SIZE': MAX_FILE_SIZE,
+        'MAX_IMAGE_SIZE': MAX_IMAGE_SIZE
+    }
+
+def save_config_to_file(config_data):
+    """将配置保存到文件"""
+    try:
+        # 确保配置目录存在
+        CONFIG_FILE.parent.mkdir(parents=True, exist_ok=True)
+
+        with open(CONFIG_FILE, 'w', encoding='utf-8') as f:
+            json.dump(config_data, f, ensure_ascii=False, indent=2)
+        return True
+    except Exception as e:
+        print(f"保存配置文件失败: {e}")
+        return False
+
+@router.get("/admin/system-config", response_model=SystemConfigResponse)
+async def get_system_config(current_user=Depends(get_current_admin_user)):
+    """
+    获取系统配置
+    只有管理员才能访问
+    """
+    try:
+        # 优先从文件加载配置，然后从内存配置补充
+        config = load_config_from_file()
+
+        return SystemConfigResponse(
+            model_name=config.get('model_name', LLM_CONFIG['model_name']),
+            system_prompt=config.get('system_prompt', LLM_CONFIG['system_prompt']),
+            DEFAULT_RESET_PASSWORD=config.get('DEFAULT_RESET_PASSWORD', DEFAULT_RESET_PASSWORD),
+            MAX_FILE_SIZE=config.get('MAX_FILE_SIZE', MAX_FILE_SIZE),
+            MAX_IMAGE_SIZE=config.get('MAX_IMAGE_SIZE', MAX_IMAGE_SIZE),
+            message="配置获取成功"
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"获取配置失败: {str(e)}")
+
+@router.put("/admin/system-config", response_model=SystemConfigResponse)
+async def update_system_config(
+    config: SystemConfigModel,
+    current_user=Depends(get_current_admin_user)
+):
+    """
+    更新系统配置
+    只有管理员才能访问
+    """
+    try:
+        # 准备要保存的配置数据
+        config_data = {
+            'model_name': config.model_name,
+            'system_prompt': config.system_prompt,
+            'DEFAULT_RESET_PASSWORD': config.DEFAULT_RESET_PASSWORD,
+            'MAX_FILE_SIZE': config.MAX_FILE_SIZE,
+            'MAX_IMAGE_SIZE': config.MAX_IMAGE_SIZE
+        }
+
+        # 保存到文件
+        if not save_config_to_file(config_data):
+            raise HTTPException(status_code=500, detail="配置保存到文件失败")
+
+        # 更新运行时配置
+        LLM_CONFIG['model_name'] = config.model_name
+        LLM_CONFIG['system_prompt'] = config.system_prompt
+
+        # 更新模块级别的配置
+        import app.core.config as config_module
+        config_module.DEFAULT_RESET_PASSWORD = config.DEFAULT_RESET_PASSWORD
+        config_module.MAX_FILE_SIZE = config.MAX_FILE_SIZE
+        config_module.MAX_IMAGE_SIZE = config.MAX_IMAGE_SIZE
+
+        return SystemConfigResponse(
+            model_name=config.model_name,
+            system_prompt=config.system_prompt,
+            DEFAULT_RESET_PASSWORD=config.DEFAULT_RESET_PASSWORD,
+            MAX_FILE_SIZE=config.MAX_FILE_SIZE,
+            MAX_IMAGE_SIZE=config.MAX_IMAGE_SIZE,
+            message="配置更新成功，重启服务后完全生效"
+        )
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"更新配置失败: {str(e)}")
+
+# 在应用启动时加载配置
+def load_system_config():
+    """在应用启动时调用，加载保存的配置"""
+    try:
+        config = load_config_from_file()
+
+        # 更新运行时配置
+        LLM_CONFIG['model_name'] = config.get('model_name', LLM_CONFIG['model_name'])
+        LLM_CONFIG['system_prompt'] = config.get('system_prompt', LLM_CONFIG['system_prompt'])
+
+        # 更新其他配置
+        import app.core.config as config_module
+        config_module.DEFAULT_RESET_PASSWORD = config.get('DEFAULT_RESET_PASSWORD', DEFAULT_RESET_PASSWORD)
+        config_module.MAX_FILE_SIZE = config.get('MAX_FILE_SIZE', MAX_FILE_SIZE)
+        config_module.MAX_IMAGE_SIZE = config.get('MAX_IMAGE_SIZE', MAX_IMAGE_SIZE)
+
+        print(f"系统配置加载成功: model={config.get('model_name')}")
+    except Exception as e:
+        print(f"加载系统配置失败，使用默认配置: {e}")

app/api/endpoints/meetings.py

@@ -1,13 +1,14 @@
 
 from fastapi import APIRouter, HTTPException, UploadFile, File, Form, Depends, BackgroundTasks
+from fastapi.responses import StreamingResponse
 from app.models.models import Meeting, TranscriptSegment, TranscriptionTaskStatus, CreateMeetingRequest, UpdateMeetingRequest, SpeakerTagUpdateRequest, BatchSpeakerTagUpdateRequest, TranscriptUpdateRequest, BatchTranscriptUpdateRequest, Tag
 from app.core.database import get_db_connection
-from app.core.config import BASE_DIR, UPLOAD_DIR, AUDIO_DIR, MARKDOWN_DIR, ALLOWED_EXTENSIONS, ALLOWED_IMAGE_EXTENSIONS, MAX_FILE_SIZE, MAX_IMAGE_SIZE
-from app.services.qiniu_service import qiniu_service
+from app.core.config import BASE_DIR, AUDIO_DIR, MARKDOWN_DIR, ALLOWED_EXTENSIONS, ALLOWED_IMAGE_EXTENSIONS
+import app.core.config as config_module
 from app.services.llm_service import LLMService
 from app.services.async_transcription_service import AsyncTranscriptionService
 from app.services.async_llm_service import async_llm_service
-from app.core.auth import get_current_user, get_optional_current_user
+from app.core.auth import get_current_user
 from typing import List, Optional
 from datetime import datetime
 from pydantic import BaseModel
@@ -398,11 +399,13 @@ async def upload_audio(
             detail=f"Unsupported file type. Allowed types: {', '.join(ALLOWED_EXTENSIONS)}"
         )
     
-    # Check file size
-    if audio_file.size > MAX_FILE_SIZE:
+    # Check file size using dynamic config
+    max_file_size = getattr(config_module, 'MAX_FILE_SIZE', 100 * 1024 * 1024)
+    if audio_file.size > max_file_size:
+        max_size_mb = max_file_size // (1024 * 1024)
         raise HTTPException(
             status_code=400,
-            detail="File size exceeds 100MB limit"
+            detail=f"File size exceeds {max_size_mb}MB limit"
         )
     
     # 检查是否已有音频文件和转录记录
@@ -646,11 +649,13 @@ async def upload_image(
             detail=f"Unsupported image type. Allowed types: {', '.join(ALLOWED_IMAGE_EXTENSIONS)}"
         )
     
-    # Check file size
-    if image_file.size > MAX_IMAGE_SIZE:
+    # Check file size using dynamic config
+    max_image_size = getattr(config_module, 'MAX_IMAGE_SIZE', 10 * 1024 * 1024)
+    if image_file.size > max_image_size:
+        max_size_mb = max_image_size // (1024 * 1024)
         raise HTTPException(
             status_code=400,
-            detail="Image size exceeds 10MB limit"
+            detail=f"Image size exceeds {max_size_mb}MB limit"
         )
     
     # Check if meeting exists and user has permission
@@ -767,6 +772,47 @@ def batch_update_transcript(meeting_id: int, request: BatchTranscriptUpdateReque
         raise HTTPException(status_code=500, detail=f"Failed to update transcript: {str(e)}")
 
 # AI总结相关接口
+@router.post("/meetings/{meeting_id}/generate-summary-stream")
+def generate_meeting_summary_stream(meeting_id: int, request: GenerateSummaryRequest, current_user: dict = Depends(get_current_user)):
+    """生成会议AI总结（流式输出）"""
+    try:
+        # 检查会议是否存在
+        with get_db_connection() as connection:
+            cursor = connection.cursor(dictionary=True)
+            cursor.execute("SELECT meeting_id FROM meetings WHERE meeting_id = %s", (meeting_id,))
+            if not cursor.fetchone():
+                raise HTTPException(status_code=404, detail="Meeting not found")
+
+        # 创建流式生成器
+        def generate_stream():
+            for chunk in llm_service.generate_meeting_summary_stream(meeting_id, request.user_prompt):
+                if chunk.startswith("error:"):
+                    # 如果遇到错误，发送错误信息并结束
+                    yield f"data: {{\"error\": \"{chunk[6:]}\"}}\n\n"
+                    break
+                else:
+                    # 发送正常的内容块
+                    import json
+                    yield f"data: {{\"content\": {json.dumps(chunk, ensure_ascii=False)}}}\n\n"
+
+            # 发送结束标记
+            yield "data: {\"done\": true}\n\n"
+
+        return StreamingResponse(
+            generate_stream(),
+            media_type="text/plain",
+            headers={
+                "Cache-Control": "no-cache",
+                "Connection": "keep-alive",
+                "Content-Type": "text/plain; charset=utf-8"
+            }
+        )
+
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to start stream generation: {str(e)}")
+
 @router.post("/meetings/{meeting_id}/generate-summary")
 def generate_meeting_summary(meeting_id: int, request: GenerateSummaryRequest, current_user: dict = Depends(get_current_user)):
     """生成会议AI总结"""
@@ -887,12 +933,12 @@ def get_llm_task_status(task_id: str, current_user: dict = Depends(get_current_u
     """获取LLM任务状态（包括进度）"""
     try:
         status = async_llm_service.get_task_status(task_id)
-        
+
         if status.get('status') == 'not_found':
             raise HTTPException(status_code=404, detail="Task not found")
-        
+
         return status
-        
+
     except HTTPException:
         raise
     except Exception as e:

app/api/endpoints/users.py

@@ -3,7 +3,7 @@ from fastapi import APIRouter, HTTPException, Depends
 from app.models.models import UserInfo, PasswordChangeRequest, UserListResponse, CreateUserRequest, UpdateUserRequest, RoleInfo
 from app.core.database import get_db_connection
 from app.core.auth import get_current_user
-from app.core.config import DEFAULT_RESET_PASSWORD
+import app.core.config as config_module
 import hashlib
 import datetime
 import re
@@ -48,7 +48,7 @@ def create_user(request: CreateUserRequest, current_user: dict = Depends(get_cur
             raise HTTPException(status_code=400, detail="用户名已存在")
 
         # Use provided password or default password
-        password = request.password if request.password else DEFAULT_RESET_PASSWORD
+        password = request.password if request.password else config_module.DEFAULT_RESET_PASSWORD
         hashed_password = hash_password(password)
         
         # Insert new user
@@ -150,7 +150,7 @@ def reset_password(user_id: int, current_user: dict = Depends(get_current_user))
             raise HTTPException(status_code=404, detail="用户不存在")
 
         # Hash password
-        hashed_password = hash_password(DEFAULT_RESET_PASSWORD)
+        hashed_password = hash_password(config_module.DEFAULT_RESET_PASSWORD)
         
         # Update user password
         query = "UPDATE users SET password_hash = %s WHERE user_id = %s"

app/core/auth.py

@@ -38,6 +38,19 @@ def get_current_user(credentials: HTTPAuthorizationCredentials = Depends(securit
     
     return user
 
+def get_current_admin_user(credentials: HTTPAuthorizationCredentials = Depends(security)):
+    """获取当前管理员用户信息的依赖函数"""
+    user = get_current_user(credentials)
+
+    # 检查用户是否是管理员 (role_id = 1)
+    if user.get('role_id') != 1:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Admin access required",
+        )
+
+    return user
+
 def get_optional_current_user(request: Request) -> Optional[dict]:
     """可选的用户认证（不强制要求登录）"""
     auth_header = request.headers.get("Authorization")

app/core/config.py

@@ -60,8 +60,7 @@ QWEN_API_KEY = os.getenv('QWEN_API_KEY', 'sk-c2bf06ea56b4491ea3d1e37fdb472b8f')
 # LLM配置 - 阿里Qwen3大模型
 LLM_CONFIG = {
     'model_name': os.getenv('LLM_MODEL_NAME', 'qwen-plus'),
-    'api_url': os.getenv('LLM_API_URL', 'https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation'),
-    'max_tokens': int(os.getenv('LLM_MAX_TOKENS', '2000')),
+    'time_out': int(os.getenv('LLM_TIMEOUT', '120')),
     'temperature': float(os.getenv('LLM_TEMPERATURE', '0.7')),
     'top_p': float(os.getenv('LLM_TOP_P', '0.9')),
     'system_prompt': """你是一个专业的会议记录分析助手。请根据提供的会议转录内容，生成简洁明了的会议总结。

app/services/llm_service.py

@@ -1,28 +1,87 @@
 import json
-import requests
-from typing import Optional, Dict, List
-from app.core.config import LLM_CONFIG, QWEN_API_KEY
+import dashscope
+from http import HTTPStatus
+from typing import Optional, Dict, List, Generator
+import app.core.config as config_module
 from app.core.database import get_db_connection
 
 
 class LLMService:
     def __init__(self):
-        self.api_key = QWEN_API_KEY
-        self.model_name = LLM_CONFIG["model_name"]
-        self.api_url = LLM_CONFIG["api_url"]
-        self.system_prompt = LLM_CONFIG["system_prompt"]
-        self.max_tokens = LLM_CONFIG["max_tokens"]
-        self.temperature = LLM_CONFIG["temperature"]
-        self.top_p = LLM_CONFIG["top_p"]
+        # 设置dashscope API key
+        dashscope.api_key = config_module.QWEN_API_KEY
+
+    @property
+    def model_name(self):
+        """动态获取模型名称"""
+        return config_module.LLM_CONFIG["model_name"]
+
+    @property
+    def system_prompt(self):
+        """动态获取系统提示词"""
+        return config_module.LLM_CONFIG["system_prompt"]
+
+    @property
+    def time_out(self):
+        """动态获取超时时间"""
+        return config_module.LLM_CONFIG["time_out"]
+
+    @property
+    def temperature(self):
+        """动态获取temperature"""
+        return config_module.LLM_CONFIG["temperature"]
+
+    @property
+    def top_p(self):
+        """动态获取top_p"""
+        return config_module.LLM_CONFIG["top_p"]
     
-    def generate_meeting_summary(self, meeting_id: int, user_prompt: str = "") -> Optional[Dict]:
+    def generate_meeting_summary_stream(self, meeting_id: int, user_prompt: str = "") -> Generator[str, None, None]:
         """
-        生成会议总结
-        
+        流式生成会议总结
+
         Args:
             meeting_id: 会议ID
             user_prompt: 用户额外提示词
-            
+
+        Yields:
+            str: 流式输出的内容片段
+        """
+        try:
+            # 获取会议转录内容
+            transcript_text = self._get_meeting_transcript(meeting_id)
+            if not transcript_text:
+                yield "error: 无法获取会议转录内容"
+                return
+
+            # 构建完整提示词
+            full_prompt = self._build_prompt(transcript_text, user_prompt)
+
+            # 调用大模型API进行流式生成
+            full_content = ""
+            for chunk in self._call_llm_api_stream(full_prompt):
+                if chunk.startswith("error:"):
+                    yield chunk
+                    return
+                full_content += chunk
+                yield chunk
+
+            # 保存完整总结到数据库
+            if full_content:
+                self._save_summary_to_db(meeting_id, full_content, user_prompt)
+
+        except Exception as e:
+            print(f"流式生成会议总结错误: {e}")
+            yield f"error: {str(e)}"
+
+    def generate_meeting_summary(self, meeting_id: int, user_prompt: str = "") -> Optional[Dict]:
+        """
+        生成会议总结（非流式，保持向后兼容）
+
+        Args:
+            meeting_id: 会议ID
+            user_prompt: 用户额外提示词
+
         Returns:
             包含总结内容的字典，如果失败返回None
         """
@@ -31,13 +90,13 @@ class LLMService:
             transcript_text = self._get_meeting_transcript(meeting_id)
             if not transcript_text:
                 return {"error": "无法获取会议转录内容"}
-            
+
             # 构建完整提示词
             full_prompt = self._build_prompt(transcript_text, user_prompt)
-            
+
             # 调用大模型API
             response = self._call_llm_api(full_prompt)
-            
+
             if response:
                 # 保存总结到数据库
                 summary_id = self._save_summary_to_db(meeting_id, response, user_prompt)
@@ -48,7 +107,7 @@ class LLMService:
                 }
             else:
                 return {"error": "大模型API调用失败"}
-                
+
         except Exception as e:
             print(f"生成会议总结错误: {e}")
             return {"error": str(e)}
@@ -95,52 +154,53 @@ class LLMService:
         
         return prompt
     
-    def _call_llm_api(self, prompt: str) -> Optional[str]:
-        """调用阿里Qwen3大模型API"""
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json"
-        }
-        
-        data = {
-            "model": self.model_name,
-            "input": {
-                "messages": [
-                    {
-                        "role": "user",
-                        "content": prompt
-                    }
-                ]
-            },
-            "parameters": {
-                "max_tokens": self.max_tokens,
-                "temperature": self.temperature,
-                "top_p": self.top_p,
-                "incremental_output": False
-            }
-        }
-        
+    def _call_llm_api_stream(self, prompt: str) -> Generator[str, None, None]:
+        """流式调用阿里Qwen3大模型API"""
         try:
-            response = requests.post(self.api_url, headers=headers, json=data, timeout=60)
-            response.raise_for_status()
-            
-            result = response.json()
-            
-            # 处理阿里Qwen API的响应格式
-            if result.get("output") and result["output"].get("text"):
-                return result["output"]["text"]
-            elif result.get("output") and result["output"].get("choices"):
-                return result["output"]["choices"][0]["message"]["content"]
+            responses = dashscope.Generation.call(
+                model=self.model_name,
+                prompt=prompt,
+                stream=True,
+                timeout=self.time_out,
+                temperature=self.temperature,
+                top_p=self.top_p,
+                incremental_output=True  # 开启增量输出模式
+            )
+
+            for response in responses:
+                if response.status_code == HTTPStatus.OK:
+                    # 增量输出内容
+                    new_content = response.output.get('text', '')
+                    if new_content:
+                        yield new_content
+                else:
+                    error_msg = f"Request failed with status code: {response.status_code}, Error: {response.message}"
+                    print(error_msg)
+                    yield f"error: {error_msg}"
+                    break
+
+        except Exception as e:
+            error_msg = f"流式调用大模型API错误: {e}"
+            print(error_msg)
+            yield f"error: {error_msg}"
+
+    def _call_llm_api(self, prompt: str) -> Optional[str]:
+        """调用阿里Qwen3大模型API（非流式，保持向后兼容）"""
+        try:
+            response = dashscope.Generation.call(
+                model=self.model_name,
+                prompt=prompt,
+                timeout=self.time_out,
+                temperature=self.temperature,
+                top_p=self.top_p
+            )
+
+            if response.status_code == HTTPStatus.OK:
+                return response.output.get('text', '')
             else:
-                print(f"API响应格式错误: {result}")
+                print(f"API调用失败: {response.status_code}, {response.message}")
                 return None
-                
-        except requests.exceptions.RequestException as e:
-            print(f"API请求错误: {e}")
-            return None
-        except json.JSONDecodeError as e:
-            print(f"JSON解析错误: {e}")
-            return None
+
         except Exception as e:
             print(f"调用大模型API错误: {e}")
             return None

config/system_config.json

@@ -0,0 +1,7 @@
+{
+  "model_name": "qwen-plus",
+  "system_prompt": "你是一个专业的会议记录分析助手。请根据提供的会议转录内容，生成简洁明了的会议总结。\n\n总结应该包括以下几部分（生成MD二级目录）：\n1. 会议概述 - 简要说明会议的主要目的和背景(生成MD引用)\n2. 主要讨论点 - 列出会议中讨论的重要话题和内容\n3. 决策事项 - 明确记录会议中做出的决定和结论\n4. 待办事项 - 列出需要后续跟进的任务和责任人\n5. 关键信息 - 其他重要的信息点\n\n输出要求：\n- 保持客观中性，不添加个人观点\n- 使用简洁、准确的中文表达\n- 按重要性排序各项内容\n- 如果某个部分没有相关内容，可以说明\"无相关内容\"\n- 总字数控制在500字以内",
+  "DEFAULT_RESET_PASSWORD": "123456",
+  "MAX_FILE_SIZE": 209715200,
+  "MAX_IMAGE_SIZE": 10485760
+}

docker-compose.prod.yml

@@ -39,8 +39,7 @@ services:
       # LLM配置
       - QWEN_API_KEY=sk-c2bf06ea56b4491ea3d1e37fdb472b8f
       - LLM_MODEL_NAME=qwen-plus
-      - LLM_API_URL=https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation
-      - LLM_MAX_TOKENS=2000
+      - LLM_TIMEOUT=120
       - LLM_TEMPERATURE=0.7
       - LLM_TOP_P=0.9
       

main.py

@@ -2,9 +2,10 @@ import uvicorn
 from fastapi import FastAPI, Request, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
-from app.api.endpoints import auth, users, meetings, tags
+from app.api.endpoints import auth, users, meetings, tags, admin
 from app.core.config import UPLOAD_DIR, API_CONFIG, MAX_FILE_SIZE
 from app.services.async_llm_service import async_llm_service
+from app.api.endpoints.admin import load_system_config
 import os
 
 app = FastAPI(
@@ -13,6 +14,9 @@ app = FastAPI(
     version="1.0.2"
 )
 
+# 加载系统配置
+load_system_config()
+
 # 添加CORS中间件
 app.add_middleware(
     CORSMiddleware,
@@ -31,6 +35,7 @@ app.include_router(auth.router, prefix="/api", tags=["Authentication"])
 app.include_router(users.router, prefix="/api", tags=["Users"])
 app.include_router(meetings.router, prefix="/api", tags=["Meetings"])
 app.include_router(tags.router, prefix="/api", tags=["Tags"])
+app.include_router(admin.router, prefix="/api", tags=["Admin"])
 
 @app.get("/")
 def read_root():

test_stream_llm.py

@@ -0,0 +1,54 @@
+#!/usr/bin/env python3
+"""
+测试流式LLM服务
+"""
+import sys
+import os
+sys.path.append(os.path.dirname(__file__))
+
+from app.services.llm_service import LLMService
+
+def test_stream_generation():
+    """测试流式生成功能"""
+    print("=== 测试流式LLM生成 ===")
+
+    llm_service = LLMService()
+    test_meeting_id = 38  # 使用一个存在的会议ID
+    test_user_prompt = "请重点关注决策事项和待办任务"
+
+    print(f"开始为会议 {test_meeting_id} 生成流式总结...")
+    print("输出内容:")
+    print("-" * 50)
+
+    full_content = ""
+    chunk_count = 0
+
+    try:
+        for chunk in llm_service.generate_meeting_summary_stream(test_meeting_id, test_user_prompt):
+            if chunk.startswith("error:"):
+                print(f"\n生成过程中出现错误: {chunk}")
+                break
+            else:
+                print(chunk, end='', flush=True)
+                full_content += chunk
+                chunk_count += 1
+
+        print(f"\n\n-" * 50)
+        print(f"流式生成完成!")
+        print(f"总共接收到 {chunk_count} 个数据块")
+        print(f"完整内容长度: {len(full_content)} 字符")
+
+        # 测试传统方式（对比）
+        print("\n=== 对比测试传统生成方式 ===")
+        result = llm_service.generate_meeting_summary(test_meeting_id, test_user_prompt)
+        if result.get("error"):
+            print(f"传统方式生成失败: {result['error']}")
+        else:
+            print("传统方式生成成功!")
+            print(f"内容长度: {len(result['content'])} 字符")
+
+    except Exception as e:
+        print(f"\n测试过程中出现异常: {e}")
+
+if __name__ == '__main__':
+    test_stream_generation()