1.0.3

app/api/endpoints/knowledge_base.py

@@ -9,29 +9,25 @@ import datetime
 
 router = APIRouter()
 
-def _process_tags(cursor, tag_string: Optional[str]) -> List[Tag]:
+def _process_tags(cursor, tag_string: Optional[str], creator_id: Optional[int] = None) -> List[Tag]:
+    """
+    处理标签：查询已存在的标签，如果提供了 creator_id 则创建不存在的标签
+    """
     if not tag_string:
         return []
     tag_names = [name.strip() for name in tag_string.split(',') if name.strip()]
     if not tag_names:
         return []
 
-    placeholders = ','.join(['%s'] * len(tag_names))
-    select_query = f"SELECT id, name, color FROM tags WHERE name IN ({placeholders})"
-    cursor.execute(select_query, tuple(tag_names))
+    # 如果提供了 creator_id，则创建不存在的标签
+    if creator_id:
+        insert_ignore_query = "INSERT IGNORE INTO tags (name, creator_id) VALUES (%s, %s)"
+        cursor.executemany(insert_ignore_query, [(name, creator_id) for name in tag_names])
+
+    # 查询所有标签信息
+    format_strings = ', '.join(['%s'] * len(tag_names))
+    cursor.execute(f"SELECT id, name, color FROM tags WHERE name IN ({format_strings})", tuple(tag_names))
     tags_data = cursor.fetchall()
-    
-    existing_tags = {tag['name']: tag for tag in tags_data}
-    new_tags = [name for name in tag_names if name not in existing_tags]
-
-    if new_tags:
-        insert_query = "INSERT INTO tags (name) VALUES (%s)"
-        cursor.executemany(insert_query, [(name,) for name in new_tags])
-        
-        # Re-fetch all tags to get their IDs and default colors
-        cursor.execute(select_query, tuple(tag_names))
-        tags_data = cursor.fetchall()
-
     return [Tag(**tag) for tag in tags_data]
 
 
@@ -83,7 +79,8 @@ def get_knowledge_bases(
 
         kb_list = []
         for kb_data in kbs_data:
-            kb_data['tags'] = _process_tags(cursor, kb_data.get('tags'))
+            # 列表页不需要处理 tags，直接使用字符串
+            # kb_data['tags'] 保持原样（逗号分隔的标签名称字符串）
             # Count source meetings - filter empty strings
             if kb_data.get('source_meeting_ids'):
                 meeting_ids = [mid.strip() for mid in kb_data['source_meeting_ids'].split(',') if mid.strip()]
@@ -122,7 +119,7 @@ def create_knowledge_base(
             request.is_shared,
             request.source_meeting_ids,
             request.user_prompt,
-            request.tags,
+            request.tags,  # 创建时 tags 应该为 None 或空字符串
             now,
             now
         ))
@@ -171,7 +168,8 @@ def get_knowledge_base_detail(
         if not kb_data['is_shared'] and kb_data['creator_id'] != current_user['user_id']:
             raise HTTPException(status_code=403, detail="Access denied")
 
-        # Process tags
+        # Process tags - 获取标签的完整信息（包括颜色）
+        # 详情页不需要创建新标签，所以不传 creator_id
         kb_data['tags'] = _process_tags(cursor, kb_data.get('tags'))
 
         # Get source meetings details
@@ -220,6 +218,10 @@ def update_knowledge_base(
         if kb['creator_id'] != current_user['user_id']:
             raise HTTPException(status_code=403, detail="Only the creator can update this knowledge base")
 
+        # 使用 _process_tags 处理标签（会自动创建新标签）
+        if request.tags:
+            _process_tags(cursor, request.tags, current_user['user_id'])
+
         # Update the knowledge base
         now = datetime.datetime.utcnow()
         update_query = """

app/api/endpoints/meetings.py

@@ -5,7 +5,7 @@ from app.core.config import BASE_DIR, AUDIO_DIR, MARKDOWN_DIR, ALLOWED_EXTENSION
 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.services.async_meeting_service import async_meeting_service
 from app.core.auth import get_current_user
 from app.core.response import create_api_response
 from typing import List, Optional
@@ -23,14 +23,22 @@ transcription_service = AsyncTranscriptionService()
 class GenerateSummaryRequest(BaseModel):
     user_prompt: Optional[str] = ""
 
-def _process_tags(cursor, tag_string: Optional[str]) -> List[Tag]:
+def _process_tags(cursor, tag_string: Optional[str], creator_id: Optional[int] = None) -> List[Tag]:
+    """
+    处理标签：查询已存在的标签，如果提供了 creator_id 则创建不存在的标签
+    """
     if not tag_string:
         return []
     tag_names = [name.strip() for name in tag_string.split(',') if name.strip()]
     if not tag_names:
         return []
-    insert_ignore_query = "INSERT IGNORE INTO tags (name) VALUES (%s)"
-    cursor.executemany(insert_ignore_query, [(name,) for name in tag_names])
+
+    # 如果提供了 creator_id，则创建不存在的标签
+    if creator_id:
+        insert_ignore_query = "INSERT IGNORE INTO tags (name, creator_id) VALUES (%s, %s)"
+        cursor.executemany(insert_ignore_query, [(name, creator_id) for name in tag_names])
+
+    # 查询所有标签信息
     format_strings = ', '.join(['%s'] * len(tag_names))
     cursor.execute(f"SELECT id, name, color FROM tags WHERE name IN ({format_strings})", tuple(tag_names))
     tags_data = cursor.fetchall()
@@ -125,10 +133,9 @@ def get_meeting_transcript(meeting_id: int, current_user: dict = Depends(get_cur
 def create_meeting(meeting_request: CreateMeetingRequest, current_user: dict = Depends(get_current_user)):
     with get_db_connection() as connection:
         cursor = connection.cursor(dictionary=True)
+        # 使用 _process_tags 来处理标签创建
         if meeting_request.tags:
-            tag_names = [name.strip() for name in meeting_request.tags.split(',') if name.strip()]
-            if tag_names:
-                cursor.executemany("INSERT IGNORE INTO tags (name) VALUES (%s)", [(name,) for name in tag_names])
+            _process_tags(cursor, meeting_request.tags, current_user['user_id'])
         meeting_query = 'INSERT INTO meetings (user_id, title, meeting_time, summary, tags, created_at) VALUES (%s, %s, %s, %s, %s, %s)'
         cursor.execute(meeting_query, (meeting_request.user_id, meeting_request.title, meeting_request.meeting_time, None, meeting_request.tags, datetime.now().isoformat()))
         meeting_id = cursor.lastrowid
@@ -147,10 +154,9 @@ def update_meeting(meeting_id: int, meeting_request: UpdateMeetingRequest, curre
             return create_api_response(code="404", message="Meeting not found")
         if meeting['user_id'] != current_user['user_id']:
             return create_api_response(code="403", message="Permission denied")
+        # 使用 _process_tags 来处理标签创建
         if meeting_request.tags:
-            tag_names = [name.strip() for name in meeting_request.tags.split(',') if name.strip()]
-            if tag_names:
-                cursor.executemany("INSERT IGNORE INTO tags (name) VALUES (%s)", [(name,) for name in tag_names])
+            _process_tags(cursor, meeting_request.tags, current_user['user_id'])
         update_query = 'UPDATE meetings SET title = %s, meeting_time = %s, summary = %s, tags = %s WHERE meeting_id = %s'
         cursor.execute(update_query, (meeting_request.title, meeting_request.meeting_time, meeting_request.summary, meeting_request.tags, meeting_id))
         cursor.execute("DELETE FROM attendees WHERE meeting_id = %s", (meeting_id,))
@@ -449,8 +455,8 @@ def generate_meeting_summary_async(meeting_id: int, request: GenerateSummaryRequ
             cursor.execute("SELECT meeting_id FROM meetings WHERE meeting_id = %s", (meeting_id,))
             if not cursor.fetchone():
                 return create_api_response(code="404", message="Meeting not found")
-        task_id = async_llm_service.start_summary_generation(meeting_id, request.user_prompt)
-        background_tasks.add_task(async_llm_service._process_task, task_id)
+        task_id = async_meeting_service.start_summary_generation(meeting_id, request.user_prompt)
+        background_tasks.add_task(async_meeting_service._process_task, task_id)
         return create_api_response(code="200", message="Summary generation task has been accepted.", data={
             "task_id": task_id, "status": "pending", "meeting_id": meeting_id
         })
@@ -465,7 +471,7 @@ def get_meeting_llm_tasks(meeting_id: int, current_user: dict = Depends(get_curr
             cursor.execute("SELECT meeting_id FROM meetings WHERE meeting_id = %s", (meeting_id,))
             if not cursor.fetchone():
                 return create_api_response(code="404", message="Meeting not found")
-        tasks = async_llm_service.get_meeting_llm_tasks(meeting_id)
+        tasks = async_meeting_service.get_meeting_llm_tasks(meeting_id)
         return create_api_response(code="200", message="LLM tasks retrieved successfully", data={
             "tasks": tasks, "total": len(tasks)
         })

app/api/endpoints/prompts.py

@@ -2,7 +2,7 @@ from fastapi import APIRouter, Depends
 from pydantic import BaseModel
 from typing import List, Optional
 
-from app.core.auth import get_current_admin_user
+from app.core.auth import get_current_user
 from app.core.database import get_db_connection
 from app.core.response import create_api_response
 
@@ -23,14 +23,14 @@ class PromptListResponse(BaseModel):
     total: int
 
 @router.post("/prompts")
-def create_prompt(prompt: PromptIn, current_user: dict = Depends(get_current_admin_user)):
+def create_prompt(prompt: PromptIn, current_user: dict = Depends(get_current_user)):
     """Create a new prompt."""
     with get_db_connection() as connection:
         cursor = connection.cursor(dictionary=True)
         try:
             cursor.execute(
-                "INSERT INTO prompts (name, tags, content) VALUES (%s, %s, %s)",
-                (prompt.name, prompt.tags, prompt.content)
+                "INSERT INTO prompts (name, tags, content, creator_id) VALUES (%s, %s, %s, %s)",
+                (prompt.name, prompt.tags, prompt.content, current_user["user_id"])
             )
             connection.commit()
             new_id = cursor.lastrowid
@@ -41,23 +41,27 @@ def create_prompt(prompt: PromptIn, current_user: dict = Depends(get_current_adm
             return create_api_response(code="500", message=f"创建提示词失败: {e}")
 
 @router.get("/prompts")
-def get_prompts(page: int = 1, size: int = 12, current_user: dict = Depends(get_current_admin_user)):
-    """Get a paginated list of prompts."""
+def get_prompts(page: int = 1, size: int = 12, current_user: dict = Depends(get_current_user)):
+    """Get a paginated list of prompts filtered by current user."""
     with get_db_connection() as connection:
         cursor = connection.cursor(dictionary=True)
-        cursor.execute("SELECT COUNT(*) as total FROM prompts")
+        # 只获取当前用户创建的提示词
+        cursor.execute(
+            "SELECT COUNT(*) as total FROM prompts WHERE creator_id = %s",
+            (current_user["user_id"],)
+        )
         total = cursor.fetchone()['total']
 
         offset = (page - 1) * size
         cursor.execute(
-            "SELECT id, name, tags, content, created_at FROM prompts ORDER BY created_at DESC LIMIT %s OFFSET %s",
-            (size, offset)
+            "SELECT id, name, tags, content, created_at FROM prompts WHERE creator_id = %s ORDER BY created_at DESC LIMIT %s OFFSET %s",
+            (current_user["user_id"], size, offset)
         )
         prompts = cursor.fetchall()
         return create_api_response(code="200", message="获取提示词列表成功", data={"prompts": prompts, "total": total})
 
 @router.get("/prompts/{prompt_id}")
-def get_prompt(prompt_id: int, current_user: dict = Depends(get_current_admin_user)):
+def get_prompt(prompt_id: int, current_user: dict = Depends(get_current_user)):
     """Get a single prompt by its ID."""
     with get_db_connection() as connection:
         cursor = connection.cursor(dictionary=True)
@@ -68,7 +72,7 @@ def get_prompt(prompt_id: int, current_user: dict = Depends(get_current_admin_us
         return create_api_response(code="200", message="获取提示词成功", data=prompt)
 
 @router.put("/prompts/{prompt_id}")
-def update_prompt(prompt_id: int, prompt: PromptIn, current_user: dict = Depends(get_current_admin_user)):
+def update_prompt(prompt_id: int, prompt: PromptIn, current_user: dict = Depends(get_current_user)):
     """Update an existing prompt."""
     with get_db_connection() as connection:
         cursor = connection.cursor(dictionary=True)
@@ -87,12 +91,24 @@ def update_prompt(prompt_id: int, prompt: PromptIn, current_user: dict = Depends
             return create_api_response(code="500", message=f"更新提示词失败: {e}")
 
 @router.delete("/prompts/{prompt_id}")
-def delete_prompt(prompt_id: int, current_user: dict = Depends(get_current_admin_user)):
-    """Delete a prompt."""
+def delete_prompt(prompt_id: int, current_user: dict = Depends(get_current_user)):
+    """Delete a prompt. Only the creator can delete their own prompts."""
     with get_db_connection() as connection:
-        cursor = connection.cursor()
-        cursor.execute("DELETE FROM prompts WHERE id = %s", (prompt_id,))
-        if cursor.rowcount == 0:
+        cursor = connection.cursor(dictionary=True)
+        # 首先检查提示词是否存在以及是否属于当前用户
+        cursor.execute(
+            "SELECT creator_id FROM prompts WHERE id = %s",
+            (prompt_id,)
+        )
+        prompt = cursor.fetchone()
+
+        if not prompt:
             return create_api_response(code="404", message="提示词不存在")
+
+        if prompt['creator_id'] != current_user["user_id"]:
+            return create_api_response(code="403", message="无权删除其他用户的提示词")
+
+        # 删除提示词
+        cursor.execute("DELETE FROM prompts WHERE id = %s", (prompt_id,))
         connection.commit()
         return create_api_response(code="200", message="提示词删除成功")

app/api/endpoints/tags.py

@@ -1,6 +1,7 @@
 from fastapi import APIRouter, Depends
 from app.core.database import get_db_connection
 from app.core.response import create_api_response
+from app.core.auth import get_current_user
 from app.models.models import Tag
 from typing import List
 import mysql.connector
@@ -24,16 +25,16 @@ def get_all_tags():
         return create_api_response(code="500", message="获取标签失败")
 
 @router.post("/tags/")
-def create_tag(tag_in: Tag):
+def create_tag(tag_in: Tag, current_user: dict = Depends(get_current_user)):
     """_summary_
-    创建一个新标签
+    创建一个新标签，并记录创建者
     """
-    query = "INSERT INTO tags (name, color) VALUES (%s, %s)"
+    query = "INSERT INTO tags (name, color, creator_id) VALUES (%s, %s, %s)"
     try:
         with get_db_connection() as connection:
             with connection.cursor(dictionary=True) as cursor:
                 try:
-                    cursor.execute(query, (tag_in.name, tag_in.color))
+                    cursor.execute(query, (tag_in.name, tag_in.color, current_user["user_id"]))
                     connection.commit()
                     tag_id = cursor.lastrowid
                     new_tag = {"id": tag_id, "name": tag_in.name, "color": tag_in.color}

app/api/endpoints/tasks.py

@@ -2,7 +2,7 @@ from fastapi import APIRouter, Depends
 from app.core.auth import get_current_user
 from app.core.response import create_api_response
 from app.services.async_transcription_service import AsyncTranscriptionService
-from app.services.async_llm_service import async_llm_service
+from app.services.async_meeting_service import async_meeting_service
 
 router = APIRouter()
 
@@ -23,7 +23,7 @@ def get_transcription_task_status(task_id: str, current_user: dict = Depends(get
 def get_llm_task_status(task_id: str, current_user: dict = Depends(get_current_user)):
     """获取LLM总结任务状态（包括进度）"""
     try:
-        status = async_llm_service.get_task_status(task_id)
+        status = async_meeting_service.get_task_status(task_id)
         if status.get('status') == 'not_found':
             return create_api_response(code="404", message="Task not found")
         return create_api_response(code="200", message="Task status retrieved", data=status)

app/api/endpoints/voiceprint.py

@@ -0,0 +1,131 @@
+"""
+声纹采集API接口
+"""
+from fastapi import APIRouter, Depends, UploadFile, File, HTTPException
+from typing import Optional
+from pathlib import Path
+import datetime
+
+from app.models.models import VoiceprintStatus, VoiceprintTemplate
+from app.core.auth import get_current_user
+from app.core.response import create_api_response
+from app.services.voiceprint_service import voiceprint_service
+import app.core.config as config_module
+
+router = APIRouter()
+
+
+@router.get("/voiceprint/template", response_model=None)
+def get_voiceprint_template(current_user: dict = Depends(get_current_user)):
+    """
+    获取声纹采集朗读模板配置
+
+    权限：需要登录
+    """
+    try:
+        template_data = VoiceprintTemplate(**config_module.VOICEPRINT_CONFIG)
+        return create_api_response(code="200", message="获取朗读模板成功", data=template_data.dict())
+    except Exception as e:
+        return create_api_response(code="500", message=f"获取朗读模板失败: {str(e)}")
+
+
+@router.get("/voiceprint/{user_id}", response_model=None)
+def get_voiceprint_status(user_id: int, current_user: dict = Depends(get_current_user)):
+    """
+    获取用户声纹采集状态
+
+    权限：用户只能查询自己的声纹状态，管理员可查询所有
+    """
+    # 权限检查：只能查询自己的声纹，或者是管理员
+    if current_user['user_id'] != user_id and current_user['role_id'] != 1:
+        return create_api_response(code="403", message="无权限查询其他用户的声纹状态")
+
+    try:
+        status_data = voiceprint_service.get_user_voiceprint_status(user_id)
+        return create_api_response(code="200", message="获取声纹状态成功", data=status_data)
+    except Exception as e:
+        return create_api_response(code="500", message=f"获取声纹状态失败: {str(e)}")
+
+
+@router.post("/voiceprint/{user_id}", response_model=None)
+async def upload_voiceprint(
+    user_id: int,
+    audio_file: UploadFile = File(...),
+    current_user: dict = Depends(get_current_user)
+):
+    """
+    上传声纹音频文件（同步处理）
+
+    权限：用户只能上传自己的声纹，管理员可操作所有
+    """
+    # 权限检查
+    if current_user['user_id'] != user_id and current_user['role_id'] != 1:
+        return create_api_response(code="403", message="无权限上传其他用户的声纹")
+
+    # 检查文件格式
+    file_ext = Path(audio_file.filename).suffix.lower()
+    if file_ext not in config_module.ALLOWED_VOICEPRINT_EXTENSIONS:
+        return create_api_response(
+            code="400",
+            message=f"不支持的文件格式，仅支持: {', '.join(config_module.ALLOWED_VOICEPRINT_EXTENSIONS)}"
+        )
+
+    # 检查文件大小
+    max_size = config_module.VOICEPRINT_CONFIG.get('max_file_size', 5242880)  # 默认5MB
+    content = await audio_file.read()
+    file_size = len(content)
+
+    if file_size > max_size:
+        return create_api_response(
+            code="400",
+            message=f"文件过大，最大允许 {max_size / 1024 / 1024:.1f}MB"
+        )
+
+    try:
+        # 确保用户目录存在
+        user_voiceprint_dir = config_module.VOICEPRINT_DIR / str(user_id)
+        user_voiceprint_dir.mkdir(parents=True, exist_ok=True)
+
+        # 生成文件名：时间戳.wav
+        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+        filename = f"{timestamp}.wav"
+        file_path = user_voiceprint_dir / filename
+
+        # 保存文件
+        with open(file_path, "wb") as f:
+            f.write(content)
+
+        # 调用服务处理声纹（提取特征向量，保存到数据库）
+        result = voiceprint_service.save_voiceprint(user_id, str(file_path), file_size)
+
+        return create_api_response(code="200", message="声纹采集成功", data=result)
+
+    except Exception as e:
+        # 如果出错，删除已上传的文件
+        if 'file_path' in locals() and Path(file_path).exists():
+            Path(file_path).unlink()
+
+        return create_api_response(code="500", message=f"声纹采集失败: {str(e)}")
+
+
+@router.delete("/voiceprint/{user_id}", response_model=None)
+def delete_voiceprint(user_id: int, current_user: dict = Depends(get_current_user)):
+    """
+    删除用户声纹数据，允许重新采集
+
+    权限：用户只能删除自己的声纹，管理员可操作所有
+    """
+    # 权限检查
+    if current_user['user_id'] != user_id and current_user['role_id'] != 1:
+        return create_api_response(code="403", message="无权限删除其他用户的声纹")
+
+    try:
+        success = voiceprint_service.delete_voiceprint(user_id)
+
+        if success:
+            return create_api_response(code="200", message="声纹删除成功")
+        else:
+            return create_api_response(code="404", message="未找到该用户的声纹数据")
+
+    except Exception as e:
+        return create_api_response(code="500", message=f"删除声纹失败: {str(e)}")

app/core/config.py

@@ -1,4 +1,5 @@
 import os
+import json
 from pathlib import Path
 
 # 基础路径配置
@@ -6,10 +7,12 @@ BASE_DIR = Path(__file__).parent.parent.parent
 UPLOAD_DIR = BASE_DIR / "uploads"
 AUDIO_DIR = UPLOAD_DIR / "audio"
 MARKDOWN_DIR = UPLOAD_DIR / "markdown"
+VOICEPRINT_DIR = UPLOAD_DIR / "voiceprint"
 
 # 文件上传配置
 ALLOWED_EXTENSIONS = {".mp3", ".wav", ".m4a", ".mpeg", ".mp4"}
 ALLOWED_IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png", ".gif", ".webp"}
+ALLOWED_VOICEPRINT_EXTENSIONS = {".wav"}
 MAX_FILE_SIZE = 100 * 1024 * 1024  # 100MB
 MAX_IMAGE_SIZE = 10 * 1024 * 1024  # 10MB
 
@@ -17,6 +20,7 @@ MAX_IMAGE_SIZE = 10 * 1024 * 1024  # 10MB
 UPLOAD_DIR.mkdir(exist_ok=True)
 AUDIO_DIR.mkdir(exist_ok=True)
 MARKDOWN_DIR.mkdir(exist_ok=True)
+VOICEPRINT_DIR.mkdir(exist_ok=True)
 
 # 数据库配置
 DATABASE_CONFIG = {
@@ -82,3 +86,12 @@ LLM_CONFIG = {
 
 # 密码重置配置
 DEFAULT_RESET_PASSWORD = os.getenv('DEFAULT_RESET_PASSWORD', '111111')
+
+# 加载系统配置文件
+# 默认声纹配置
+VOICEPRINT_CONFIG = {
+    "template_text": "我正在进行声纹采集，这段语音将用于身份识别和验证。\n\n声纹技术能够准确识别每个人独特的声音特征。",
+    "duration_seconds": 12,
+    "sample_rate": 16000,
+    "channels": 1
+}

app/models/models.py

@@ -128,7 +128,7 @@ class KnowledgeBase(BaseModel):
     is_shared: bool
     source_meeting_ids: Optional[str] = None
     user_prompt: Optional[str] = None
-    tags: Optional[List[Tag]] = []
+    tags: Union[Optional[str], Optional[List[Tag]]] = None  # 支持字符串或Tag列表
     created_at: datetime.datetime
     updated_at: datetime.datetime
     source_meeting_count: Optional[int] = 0
@@ -204,3 +204,26 @@ class UpdateClientDownloadRequest(BaseModel):
 class ClientDownloadListResponse(BaseModel):
     clients: List[ClientDownload]
     total: int
+
+# 声纹采集相关模型
+class VoiceprintInfo(BaseModel):
+    vp_id: int
+    user_id: int
+    file_path: str
+    file_size: Optional[int] = None
+    duration_seconds: Optional[float] = None
+    collected_at: datetime.datetime
+    updated_at: datetime.datetime
+
+class VoiceprintStatus(BaseModel):
+    has_voiceprint: bool
+    vp_id: Optional[int] = None
+    file_path: Optional[str] = None
+    duration_seconds: Optional[float] = None
+    collected_at: Optional[datetime.datetime] = None
+
+class VoiceprintTemplate(BaseModel):
+    template_text: str
+    duration_seconds: int
+    sample_rate: int
+    channels: int

app/services/async_knowledge_base_service.py

@@ -1,3 +1,7 @@
+"""
+异步知识库服务 - 处理知识库生成的异步任务
+采用FastAPI BackgroundTasks模式
+"""
 import uuid
 from datetime import datetime
 from typing import Optional, Dict, Any, List
@@ -7,6 +11,7 @@ from app.core.database import get_db_connection
 from app.services.llm_service import LLMService
 
 class AsyncKnowledgeBaseService:
+    """异步知识库服务类 - 处理知识库相关的异步任务"""
 
     def __init__(self):
         from app.core.config import REDIS_CONFIG
@@ -16,6 +21,19 @@ class AsyncKnowledgeBaseService:
         self.llm_service = LLMService()
 
     def start_generation(self, user_id: int, kb_id: int, user_prompt: Optional[str], source_meeting_ids: Optional[str], cursor=None) -> str:
+        """
+        创建异步知识库生成任务
+
+        Args:
+            user_id: 用户ID
+            kb_id: 知识库ID
+            user_prompt: 用户提示词
+            source_meeting_ids: 源会议ID列表
+            cursor: 数据库游标（可选）
+
+        Returns:
+            str: 任务ID
+        """
         task_id = str(uuid.uuid4())
 
         # If a cursor is passed, use it directly to avoid creating a new transaction
@@ -47,8 +65,12 @@ class AsyncKnowledgeBaseService:
         return task_id
 
     def _process_task(self, task_id: str):
+        """
+        处理单个异步任务的函数，设计为由BackgroundTasks调用。
+        """
         print(f"Background task started for knowledge base task: {task_id}")
         try:
+            # 从Redis获取任务数据
             task_data = self.redis_client.hgetall(f"kb_task:{task_id}")
             if not task_data:
                 print(f"Error: Task {task_id} not found in Redis for processing.")
@@ -57,99 +79,136 @@ class AsyncKnowledgeBaseService:
             kb_id = int(task_data['kb_id'])
             user_prompt = task_data.get('user_prompt', '')
 
+            # 1. 更新状态为processing
             self._update_task_status_in_redis(task_id, 'processing', 10, message="任务已开始...")
 
+            # 2. 获取关联的会议总结
+            self._update_task_status_in_redis(task_id, 'processing', 20, message="获取关联会议纪要...")
+            source_text = self._get_meeting_summaries(kb_id)
+
+            # 3. 构建提示词
+            self._update_task_status_in_redis(task_id, 'processing', 30, message="准备AI提示词...")
+            full_prompt = self._build_prompt(source_text, user_prompt)
+
+            # 4. 调用LLM API
+            self._update_task_status_in_redis(task_id, 'processing', 50, message="AI正在生成知识库...")
+            generated_content = self.llm_service._call_llm_api(full_prompt)
+            if not generated_content:
+                raise Exception("LLM API调用失败或返回空内容")
+
+            # 5. 保存结果到数据库
+            self._update_task_status_in_redis(task_id, 'processing', 95, message="保存结果...")
+            self._save_result_to_db(kb_id, generated_content)
+
+            # 6. 任务完成
+            self._update_task_in_db(task_id, 'completed', 100)
+            self._update_task_status_in_redis(task_id, 'completed', 100)
+
+            print(f"Task {task_id} completed successfully")
+
+        except Exception as e:
+            error_msg = str(e)
+            print(f"Task {task_id} failed: {error_msg}")
+            # 更新失败状态
+            self._update_task_in_db(task_id, 'failed', 0, error_message=error_msg)
+            self._update_task_status_in_redis(task_id, 'failed', 0, error_message=error_msg)
+
+    # --- 知识库相关方法 ---
+
+    def _get_meeting_summaries(self, kb_id: int) -> str:
+        """
+        从数据库获取知识库关联的会议总结
+
+        Args:
+            kb_id: 知识库ID
+
+        Returns:
+            str: 拼接后的会议总结文本
+        """
+        try:
             with get_db_connection() as connection:
                 cursor = connection.cursor(dictionary=True)
 
-                # Get source meeting summaries
-                source_text = ""
+                # 获取知识库的源会议ID列表
                 cursor.execute("SELECT source_meeting_ids FROM knowledge_bases WHERE kb_id = %s", (kb_id,))
                 kb_info = cursor.fetchone()
-                if kb_info and kb_info['source_meeting_ids']:
-                    self._update_task_status_in_redis(task_id, 'processing', 20, message="获取关联会议纪要...")
+
+                if not kb_info or not kb_info['source_meeting_ids']:
+                    return ""
+
+                # 解析会议ID列表
                 meeting_ids = [int(m_id) for m_id in kb_info['source_meeting_ids'].split(',') if m_id.isdigit()]
-                    if meeting_ids:
+                if not meeting_ids:
+                    return ""
+
+                # 获取所有会议的总结
                 summaries = []
                 for meeting_id in meeting_ids:
                     cursor.execute("SELECT summary FROM meetings WHERE meeting_id = %s", (meeting_id,))
                     summary = cursor.fetchone()
                     if summary and summary['summary']:
                         summaries.append(summary['summary'])
-                        source_text = "\n\n---\n\n".join(summaries)
 
-                # Get system prompt
-                self._update_task_status_in_redis(task_id, 'processing', 30, message="获取知识库生成模版...")
-                system_prompt = self._get_knowledge_task_prompt(cursor)
-                
-                # Build final prompt
-                final_prompt = f"{system_prompt}\n\n"
-                if source_text:
-                    final_prompt += f"请参考以下会议纪要内容：\n{source_text}\n\n"
-                final_prompt += f"用户要求：{user_prompt}"
-
-                self._update_task_status_in_redis(task_id, 'processing', 50, message="AI正在生成知识库...")
-                generated_content = self.llm_service._call_llm_api(final_prompt)
-
-                if not generated_content:
-                    raise Exception("LLM API call failed or returned empty content")
-
-                self._update_task_status_in_redis(task_id, 'processing', 95, message="保存结果...")
-                self._save_result_to_db(kb_id, generated_content, cursor)
-
-                self._update_task_in_db(task_id, 'completed', 100, cursor=cursor)
-                self._update_task_status_in_redis(task_id, 'completed', 100)
-                
-                connection.commit()
-                print(f"Task {task_id} completed successfully")
+                # 用分隔符拼接多个会议总结
+                return "\n\n---\n\n".join(summaries)
 
         except Exception as e:
-            error_msg = str(e)
-            print(f"Task {task_id} failed: {error_msg}")
-            # Use a new connection for error logging to avoid issues with a potentially broken transaction
-            with get_db_connection() as err_conn:
-                err_cursor = err_conn.cursor()
-                self._update_task_in_db(task_id, 'failed', 0, error_message=error_msg, cursor=err_cursor)
-                err_conn.commit()
-            self._update_task_status_in_redis(task_id, 'failed', 0, error_message=error_msg)
+            print(f"获取会议总结错误: {e}")
+            return ""
 
-    def _get_knowledge_task_prompt(self, cursor) -> str:
-        query = """
-            SELECT p.content 
-            FROM prompt_config pc
-            JOIN prompts p ON pc.prompt_id = p.id
-            WHERE pc.task_name = 'KNOWLEDGE_TASK'
+    def _build_prompt(self, source_text: str, user_prompt: str) -> str:
         """
-        cursor.execute(query)
-        result = cursor.fetchone()
-        if result:
-            return result['content']
-        else:
-            # Fallback prompt
-            return "Please generate a knowledge base article based on the provided information."
+        构建完整的提示词
+        使用数据库中配置的KNOWLEDGE_TASK提示词模板
 
+        Args:
+            source_text: 源会议总结文本
+            user_prompt: 用户自定义提示词
 
+        Returns:
+            str: 完整的提示词
+        """
+        # 从数据库获取知识库任务的提示词模板
+        system_prompt = self.llm_service.get_task_prompt('KNOWLEDGE_TASK')
 
-    def _save_result_to_db(self, kb_id: int, content: str, cursor):
+        prompt = f"{system_prompt}\n\n"
+
+        if source_text:
+            prompt += f"请参考以下会议纪要内容：\n{source_text}\n\n"
+
+        prompt += f"用户要求：{user_prompt}"
+
+        return prompt
+
+    def _save_result_to_db(self, kb_id: int, content: str) -> Optional[int]:
+        """
+        保存生成结果到数据库
+
+        Args:
+            kb_id: 知识库ID
+            content: 生成的内容
+
+        Returns:
+            Optional[int]: 知识库ID，失败返回None
+        """
+        try:
+            with get_db_connection() as connection:
+                cursor = connection.cursor()
                 query = "UPDATE knowledge_bases SET content = %s, updated_at = NOW() WHERE kb_id = %s"
                 cursor.execute(query, (content, kb_id))
+                connection.commit()
 
-    def _update_task_in_db(self, task_id: str, status: str, progress: int, error_message: str = None, cursor=None):
-        query = "UPDATE knowledge_base_tasks SET status = %s, progress = %s, error_message = %s, updated_at = NOW(), completed_at = IF(%s = 'completed', NOW(), completed_at) WHERE task_id = %s"
-        cursor.execute(query, (status, progress, error_message, status, task_id))
+                print(f"成功保存知识库内容，kb_id: {kb_id}")
+                return kb_id
 
-    def _update_task_status_in_redis(self, task_id: str, status: str, progress: int, message: str = None, error_message: str = None):
-        update_data = {
-            'status': status,
-            'progress': str(progress),
-            'updated_at': datetime.now().isoformat()
-        }
-        if message: update_data['message'] = message
-        if error_message: update_data['error_message'] = error_message
-        self.redis_client.hset(f"kb_task:{task_id}", mapping=update_data)
+        except Exception as e:
+            print(f"保存知识库内容错误: {e}")
+            return None
+
+    # --- 状态查询和数据库操作方法 ---
 
     def get_task_status(self, task_id: str) -> Dict[str, Any]:
-        """获取任务状态 - 与 async_llm_service 保持一致"""
+        """获取任务状态"""
         try:
             task_data = self.redis_client.hgetall(f"kb_task:{task_id}")
             if not task_data:
@@ -170,6 +229,20 @@ class AsyncKnowledgeBaseService:
             print(f"Error getting task status: {e}")
             return {'task_id': task_id, 'status': 'error', 'error_message': str(e)}
 
+    def _update_task_status_in_redis(self, task_id: str, status: str, progress: int, message: str = None, error_message: str = None):
+        """更新Redis中的任务状态"""
+        try:
+            update_data = {
+                'status': status,
+                'progress': str(progress),
+                'updated_at': datetime.now().isoformat()
+            }
+            if message: update_data['message'] = message
+            if error_message: update_data['error_message'] = error_message
+            self.redis_client.hset(f"kb_task:{task_id}", mapping=update_data)
+        except Exception as e:
+            print(f"Error updating task status in Redis: {e}")
+
     def _save_task_to_db(self, task_id: str, user_id: int, kb_id: int, user_prompt: str):
         """保存任务到数据库"""
         try:
@@ -182,6 +255,17 @@ class AsyncKnowledgeBaseService:
             print(f"Error saving task to database: {e}")
             raise
 
+    def _update_task_in_db(self, task_id: str, status: str, progress: int, error_message: str = None):
+        """更新数据库中的任务状态"""
+        try:
+            with get_db_connection() as connection:
+                cursor = connection.cursor()
+                query = "UPDATE knowledge_base_tasks SET status = %s, progress = %s, error_message = %s, updated_at = NOW(), completed_at = IF(%s = 'completed', NOW(), completed_at) WHERE task_id = %s"
+                cursor.execute(query, (status, progress, error_message, status, task_id))
+                connection.commit()
+        except Exception as e:
+            print(f"Error updating task in database: {e}")
+
     def _get_task_from_db(self, task_id: str) -> Optional[Dict[str, str]]:
         """从数据库获取任务信息"""
         try:
@@ -198,4 +282,5 @@ class AsyncKnowledgeBaseService:
             print(f"Error getting task from database: {e}")
             return None
 
+# 创建全局实例
 async_kb_service = AsyncKnowledgeBaseService()

app/services/async_meeting_service.py

@@ -1,5 +1,5 @@
 """
-异步LLM服务 - 处理会议总结生成的异步任务
+异步会议服务 - 处理会议总结生成的异步任务
 采用FastAPI BackgroundTasks模式
 """
 import uuid
@@ -12,8 +12,8 @@ from app.core.config import REDIS_CONFIG
 from app.core.database import get_db_connection
 from app.services.llm_service import LLMService
 
-class AsyncLLMService:
-    """异步LLM服务类 - 采用FastAPI BackgroundTasks模式"""
+class AsyncMeetingService:
+    """异步会议服务类 - 处理会议相关的异步任务"""
 
     def __init__(self):
         # 确保redis客户端自动解码响应，代码更简洁
@@ -53,7 +53,7 @@ class AsyncLLMService:
             self.redis_client.hset(f"llm_task:{task_id}", mapping=task_data)
             self.redis_client.expire(f"llm_task:{task_id}", 86400)
 
-            print(f"LLM summary task created: {task_id} for meeting: {meeting_id}")
+            print(f"Meeting summary task created: {task_id} for meeting: {meeting_id}")
             return task_id
 
         except Exception as e:
@@ -64,7 +64,7 @@ class AsyncLLMService:
         """
         处理单个异步任务的函数，设计为由BackgroundTasks调用。
         """
-        print(f"Background task started for LLM task: {task_id}")
+        print(f"Background task started for meeting summary task: {task_id}")
         try:
             # 从Redis获取任务数据
             task_data = self.redis_client.hgetall(f"llm_task:{task_id}")
@@ -80,13 +80,13 @@ class AsyncLLMService:
 
             # 2. 获取会议转录内容
             self._update_task_status_in_redis(task_id, 'processing', 30, message="获取会议转录内容...")
-            transcript_text = self.llm_service._get_meeting_transcript(meeting_id)
+            transcript_text = self._get_meeting_transcript(meeting_id)
             if not transcript_text:
                 raise Exception("无法获取会议转录内容")
 
             # 3. 构建提示词
             self._update_task_status_in_redis(task_id, 'processing', 40, message="准备AI提示词...")
-            full_prompt = self.llm_service._build_prompt(transcript_text, user_prompt)
+            full_prompt = self._build_prompt(transcript_text, user_prompt)
 
             # 4. 调用LLM API
             self._update_task_status_in_redis(task_id, 'processing', 50, message="AI正在分析会议内容...")
@@ -96,7 +96,7 @@ class AsyncLLMService:
 
             # 5. 保存结果到主表
             self._update_task_status_in_redis(task_id, 'processing', 95, message="保存总结结果...")
-            self.llm_service._save_summary_to_db(meeting_id, summary_content, user_prompt)
+            self._save_summary_to_db(meeting_id, summary_content, user_prompt)
 
             # 6. 任务完成
             self._update_task_in_db(task_id, 'completed', 100, result=summary_content)
@@ -110,6 +110,78 @@ class AsyncLLMService:
             self._update_task_in_db(task_id, 'failed', 0, error_message=error_msg)
             self._update_task_status_in_redis(task_id, 'failed', 0, error_message=error_msg)
 
+    # --- 会议相关方法 ---
+
+    def _get_meeting_transcript(self, meeting_id: int) -> str:
+        """从数据库获取会议转录内容"""
+        try:
+            with get_db_connection() as connection:
+                cursor = connection.cursor()
+                query = """
+                    SELECT speaker_tag, start_time_ms, end_time_ms, text_content
+                    FROM transcript_segments
+                    WHERE meeting_id = %s
+                    ORDER BY start_time_ms
+                """
+                cursor.execute(query, (meeting_id,))
+                segments = cursor.fetchall()
+
+                if not segments:
+                    return ""
+
+                # 组装转录文本
+                transcript_lines = []
+                for speaker_tag, start_time, end_time, text in segments:
+                    # 将毫秒转换为分:秒格式
+                    start_min = start_time // 60000
+                    start_sec = (start_time % 60000) // 1000
+                    transcript_lines.append(f"[{start_min:02d}:{start_sec:02d}] 说话人{speaker_tag}: {text}")
+
+                return "\n".join(transcript_lines)
+
+        except Exception as e:
+            print(f"获取会议转录内容错误: {e}")
+            return ""
+
+    def _build_prompt(self, transcript_text: str, user_prompt: str) -> str:
+        """
+        构建完整的提示词
+        使用数据库中配置的MEETING_TASK提示词模板
+        """
+        # 从数据库获取会议任务的提示词模板
+        system_prompt = self.llm_service.get_task_prompt('MEETING_TASK')
+
+        prompt = f"{system_prompt}\n\n"
+
+        if user_prompt:
+            prompt += f"用户额外要求：{user_prompt}\n\n"
+
+        prompt += f"会议转录内容：\n{transcript_text}\n\n请根据以上内容生成会议总结："
+
+        return prompt
+
+    def _save_summary_to_db(self, meeting_id: int, summary_content: str, user_prompt: str) -> Optional[int]:
+        """保存总结到数据库 - 更新meetings表的summary、user_prompt和updated_at字段"""
+        try:
+            with get_db_connection() as connection:
+                cursor = connection.cursor()
+
+                # 更新meetings表的summary、user_prompt和updated_at字段
+                update_query = """
+                    UPDATE meetings
+                    SET summary = %s, user_prompt = %s, updated_at = NOW()
+                    WHERE meeting_id = %s
+                """
+                cursor.execute(update_query, (summary_content, user_prompt, meeting_id))
+                connection.commit()
+
+                print(f"成功保存会议总结到meetings表，meeting_id: {meeting_id}")
+                return meeting_id
+
+        except Exception as e:
+            print(f"保存总结到数据库错误: {e}")
+            return None
+
     # --- 状态查询和数据库操作方法 ---
 
     def get_task_status(self, task_id: str) -> Dict[str, Any]:
@@ -212,4 +284,4 @@ class AsyncLLMService:
             return None
 
 # 创建全局实例
-async_llm_service = AsyncLLMService()
+async_meeting_service = AsyncMeetingService()

app/services/llm_service.py

@@ -7,6 +7,8 @@ from app.core.database import get_db_connection
 
 
 class LLMService:
+    """LLM服务 - 专注于大模型API调用和提示词管理"""
+
     def __init__(self):
         # 设置dashscope API key
         dashscope.api_key = config_module.QWEN_API_KEY
@@ -36,123 +38,47 @@ class LLMService:
         """动态获取top_p"""
         return config_module.LLM_CONFIG["top_p"]
 
-    def generate_meeting_summary_stream(self, meeting_id: int, user_prompt: str = "") -> Generator[str, None, None]:
+    def get_task_prompt(self, task_name: str, cursor=None) -> str:
         """
-        流式生成会议总结
+        统一的提示词获取方法
 
         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
+            task_name: 任务名称，如 'MEETING_TASK', 'KNOWLEDGE_TASK' 等
+            cursor: 数据库游标，如果传入则使用，否则创建新连接
 
         Returns:
-            包含总结内容的字典，如果失败返回None
+            str: 提示词内容，如果未找到返回默认提示词
         """
-        try:
-            # 获取会议转录内容
-            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)
-                return {
-                    "summary_id": summary_id,
-                    "content": response,
-                    "meeting_id": meeting_id
-                }
-            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)}
-    
-    def _get_meeting_transcript(self, meeting_id: int) -> str:
-        """从数据库获取会议转录内容"""
-        try:
-            with get_db_connection() as connection:
-                cursor = connection.cursor()
         query = """
-                    SELECT speaker_tag, start_time_ms, end_time_ms, text_content
-                    FROM transcript_segments 
-                    WHERE meeting_id = %s 
-                    ORDER BY start_time_ms
+            SELECT p.content
+            FROM prompt_config pc
+            JOIN prompts p ON pc.prompt_id = p.id
+            WHERE pc.task_name = %s
         """
-                cursor.execute(query, (meeting_id,))
-                segments = cursor.fetchall()
 
-                if not segments:
-                    return ""
+        if cursor:
+            cursor.execute(query, (task_name,))
+            result = cursor.fetchone()
+            if result:
+                return result['content'] if isinstance(result, dict) else result[0]
+        else:
+            with get_db_connection() as connection:
+                cursor = connection.cursor(dictionary=True)
+                cursor.execute(query, (task_name,))
+                result = cursor.fetchone()
+                if result:
+                    return result['content']
 
-                # 组装转录文本
-                transcript_lines = []
-                for speaker_tag, start_time, end_time, text in segments:
-                    # 将毫秒转换为分:秒格式
-                    start_min = start_time // 60000
-                    start_sec = (start_time % 60000) // 1000
-                    transcript_lines.append(f"[{start_min:02d}:{start_sec:02d}] 说话人{speaker_tag}: {text}")
+        # 返回默认提示词
+        return self._get_default_prompt(task_name)
 
-                return "\n".join(transcript_lines)
-                
-        except Exception as e:
-            print(f"获取会议转录内容错误: {e}")
-            return ""
-    
-    def _build_prompt(self, transcript_text: str, user_prompt: str) -> str:
-        """构建完整的提示词"""
-        prompt = f"{self.system_prompt}\n\n"
-        
-        if user_prompt:
-            prompt += f"用户额外要求：{user_prompt}\n\n"
-        
-        prompt += f"会议转录内容：\n{transcript_text}\n\n请根据以上内容生成会议总结："
-        
-        return prompt
+    def _get_default_prompt(self, task_name: str) -> str:
+        """获取默认提示词"""
+        default_prompts = {
+            'MEETING_TASK': self.system_prompt,  # 使用配置文件中的系统提示词
+            'KNOWLEDGE_TASK': "请根据提供的信息生成知识库文章。",
+        }
+        return default_prompts.get(task_name, "请根据提供的内容进行总结和分析。")
 
     def _call_llm_api_stream(self, prompt: str) -> Generator[str, None, None]:
         """流式调用阿里Qwen3大模型API"""
@@ -185,7 +111,7 @@ class LLMService:
             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）"""
+        """调用阿里Qwen3大模型API（非流式）"""
         try:
             response = dashscope.Generation.call(
                 model=self.model_name,
@@ -205,95 +131,17 @@ class LLMService:
             print(f"调用大模型API错误: {e}")
             return None
 
-    def _save_summary_to_db(self, meeting_id: int, summary_content: str, user_prompt: str) -> Optional[int]:
-        """保存总结到数据库 - 更新meetings表的summary字段"""
-        try:
-            with get_db_connection() as connection:
-                cursor = connection.cursor()
-                
-                # 更新meetings表的summary字段
-                update_query = """
-                    UPDATE meetings 
-                    SET summary = %s 
-                    WHERE meeting_id = %s
-                """
-                cursor.execute(update_query, (summary_content, meeting_id))
-                connection.commit()
-                
-                print(f"成功保存会议总结到meetings表，meeting_id: {meeting_id}")
-                return meeting_id
-                
-        except Exception as e:
-            print(f"保存总结到数据库错误: {e}")
-            return None
-    
-    def get_meeting_summaries(self, meeting_id: int) -> List[Dict]:
-        """获取会议的当前总结 - 从meetings表的summary字段获取"""
-        try:
-            with get_db_connection() as connection:
-                cursor = connection.cursor()
-                query = """
-                    SELECT summary
-                    FROM meetings 
-                    WHERE meeting_id = %s
-                """
-                cursor.execute(query, (meeting_id,))
-                result = cursor.fetchone()
-                
-                # 如果有总结内容，返回一个包含当前总结的列表格式（保持API一致性）
-                if result and result[0]:
-                    return [{
-                        "id": meeting_id,
-                        "content": result[0],
-                        "user_prompt": "",  # meetings表中没有user_prompt字段
-                        "created_at": None  # meetings表中没有单独的总结创建时间
-                    }]
-                else:
-                    return []
-                
-        except Exception as e:
-            print(f"获取会议总结错误: {e}")
-            return []
-    
-    def get_current_meeting_summary(self, meeting_id: int) -> Optional[str]:
-        """获取会议当前的总结内容 - 从meetings表的summary字段获取"""
-        try:
-            with get_db_connection() as connection:
-                cursor = connection.cursor()
-                query = """
-                    SELECT summary
-                    FROM meetings 
-                    WHERE meeting_id = %s
-                """
-                cursor.execute(query, (meeting_id,))
-                result = cursor.fetchone()
-                
-                return result[0] if result and result[0] else None
-                
-        except Exception as e:
-            print(f"获取会议当前总结错误: {e}")
-            return None
-
 
 # 测试代码
 if __name__ == '__main__':
-    # 测试LLM服务
-    test_meeting_id = 38
-    test_user_prompt = "请重点关注决策事项和待办任务"
-    
     print("--- 运行LLM服务测试 ---")
     llm_service = LLMService()
 
-    # 生成总结
-    result = llm_service.generate_meeting_summary(test_meeting_id, test_user_prompt)
-    if result.get("error"):
-        print(f"生成总结失败: {result['error']}")
-    else:
-        print(f"总结生成成功，ID: {result.get('summary_id')}")
-        print(f"总结内容: {result.get('content')[:200]}...")
+    # 测试获取任务提示词
+    meeting_prompt = llm_service.get_task_prompt('MEETING_TASK')
+    print(f"会议任务提示词: {meeting_prompt[:100]}...")
 
-    # 获取历史总结
-    summaries = llm_service.get_meeting_summaries(test_meeting_id)
-    print(f"获取到 {len(summaries)} 个历史总结")
+    knowledge_prompt = llm_service.get_task_prompt('KNOWLEDGE_TASK')
+    print(f"知识库任务提示词: {knowledge_prompt[:100]}...")
 
     print("--- LLM服务测试完成 ---")

app/services/voiceprint_service.py

@@ -0,0 +1,218 @@
+"""
+声纹服务 - 处理用户声纹采集、存储和验证
+"""
+import os
+import json
+import wave
+from datetime import datetime
+from typing import Optional, Dict
+from pathlib import Path
+
+from app.core.database import get_db_connection
+import app.core.config as config_module
+
+
+class VoiceprintService:
+    """声纹服务类 - 同步处理声纹采集"""
+
+    def __init__(self):
+        self.voiceprint_dir = config_module.VOICEPRINT_DIR
+        self.voiceprint_config = config_module.VOICEPRINT_CONFIG
+
+    def get_user_voiceprint_status(self, user_id: int) -> Dict:
+        """
+        获取用户声纹状态
+
+        Args:
+            user_id: 用户ID
+
+        Returns:
+            Dict: 声纹状态信息
+        """
+        try:
+            with get_db_connection() as connection:
+                cursor = connection.cursor(dictionary=True)
+                query = """
+                    SELECT vp_id, user_id, file_path, file_size, duration_seconds, collected_at, updated_at
+                    FROM user_voiceprint
+                    WHERE user_id = %s
+                """
+                cursor.execute(query, (user_id,))
+                voiceprint = cursor.fetchone()
+
+                if voiceprint:
+                    return {
+                        "has_voiceprint": True,
+                        "vp_id": voiceprint['vp_id'],
+                        "file_path": voiceprint['file_path'],
+                        "duration_seconds": float(voiceprint['duration_seconds']) if voiceprint['duration_seconds'] else None,
+                        "collected_at": voiceprint['collected_at'].isoformat() if voiceprint['collected_at'] else None
+                    }
+                else:
+                    return {
+                        "has_voiceprint": False,
+                        "vp_id": None,
+                        "file_path": None,
+                        "duration_seconds": None,
+                        "collected_at": None
+                    }
+        except Exception as e:
+            print(f"获取声纹状态错误: {e}")
+            raise e
+
+    def save_voiceprint(self, user_id: int, audio_file_path: str, file_size: int) -> Dict:
+        """
+        保存声纹文件并提取特征向量
+
+        Args:
+            user_id: 用户ID
+            audio_file_path: 音频文件路径
+            file_size: 文件大小
+
+        Returns:
+            Dict: 保存结果
+        """
+        try:
+            # 1. 获取音频时长
+            duration = self._get_audio_duration(audio_file_path)
+
+            # 2. 提取声纹向量（调用FunASR）
+            vector_data = self._extract_voiceprint_vector(audio_file_path)
+
+            # 3. 保存到数据库
+            with get_db_connection() as connection:
+                cursor = connection.cursor(dictionary=True)
+
+                # 检查用户是否已有声纹
+                cursor.execute("SELECT vp_id FROM user_voiceprint WHERE user_id = %s", (user_id,))
+                existing = cursor.fetchone()
+
+                # 计算相对路径
+                relative_path = str(Path(audio_file_path).relative_to(config_module.BASE_DIR))
+
+                if existing:
+                    # 更新现有记录
+                    update_query = """
+                        UPDATE user_voiceprint
+                        SET file_path = %s, file_size = %s, duration_seconds = %s,
+                            vector_data = %s, updated_at = NOW()
+                        WHERE user_id = %s
+                    """
+                    cursor.execute(update_query, (
+                        relative_path, file_size, duration,
+                        json.dumps(vector_data) if vector_data else None,
+                        user_id
+                    ))
+                    vp_id = existing['vp_id']
+                else:
+                    # 插入新记录
+                    insert_query = """
+                        INSERT INTO user_voiceprint
+                        (user_id, file_path, file_size, duration_seconds, vector_data, collected_at, updated_at)
+                        VALUES (%s, %s, %s, %s, %s, NOW(), NOW())
+                    """
+                    cursor.execute(insert_query, (
+                        user_id, relative_path, file_size, duration,
+                        json.dumps(vector_data) if vector_data else None
+                    ))
+                    vp_id = cursor.lastrowid
+
+                connection.commit()
+
+                return {
+                    "vp_id": vp_id,
+                    "user_id": user_id,
+                    "file_path": relative_path,
+                    "file_size": file_size,
+                    "duration_seconds": duration,
+                    "has_vector": vector_data is not None
+                }
+
+        except Exception as e:
+            print(f"保存声纹错误: {e}")
+            raise e
+
+    def delete_voiceprint(self, user_id: int) -> bool:
+        """
+        删除用户声纹
+
+        Args:
+            user_id: 用户ID
+
+        Returns:
+            bool: 是否删除成功
+        """
+        try:
+            with get_db_connection() as connection:
+                cursor = connection.cursor(dictionary=True)
+
+                # 获取文件路径
+                cursor.execute("SELECT file_path FROM user_voiceprint WHERE user_id = %s", (user_id,))
+                voiceprint = cursor.fetchone()
+
+                if voiceprint:
+                    # 构建完整文件路径
+                    relative_path = voiceprint['file_path']
+                    if relative_path.startswith('/'):
+                        relative_path = relative_path.lstrip('/')
+                    file_path = config_module.BASE_DIR / relative_path
+
+                    # 删除数据库记录
+                    cursor.execute("DELETE FROM user_voiceprint WHERE user_id = %s", (user_id,))
+                    connection.commit()
+
+                    # 删除文件
+                    if file_path.exists():
+                        os.remove(file_path)
+
+                    return True
+                else:
+                    return False
+
+        except Exception as e:
+            print(f"删除声纹错误: {e}")
+            raise e
+
+    def _get_audio_duration(self, audio_file_path: str) -> float:
+        """
+        获取音频文件时长
+
+        Args:
+            audio_file_path: 音频文件路径
+
+        Returns:
+            float: 时长（秒）
+        """
+        try:
+            with wave.open(audio_file_path, 'rb') as wav_file:
+                frames = wav_file.getnframes()
+                rate = wav_file.getframerate()
+                duration = frames / float(rate)
+                return round(duration, 2)
+        except Exception as e:
+            print(f"获取音频时长错误: {e}")
+            return 10.0  # 默认返回10秒
+
+    def _extract_voiceprint_vector(self, audio_file_path: str) -> Optional[list]:
+        """
+        提取声纹特征向量（调用FunASR）
+
+        Args:
+            audio_file_path: 音频文件路径
+
+        Returns:
+            Optional[list]: 声纹向量（192维），失败返回None
+        """
+        # TODO: 集成FunASR的说话人识别模型
+        # 使用 speech_campplus_sv_zh-cn_16k-common 模型
+        # 返回192维的embedding向量
+
+        print(f"[TODO] 调用FunASR提取声纹向量: {audio_file_path}")
+
+        # 暂时返回None，等待FunASR集成
+        # 集成后应该返回类似: [0.123, -0.456, 0.789, ...]
+        return None
+
+
+# 创建全局实例
+voiceprint_service = VoiceprintService()

config/system_config.json

@@ -1,7 +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总结包括五个部分（名称严格一致，生成为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": "111111",
-  "MAX_FILE_SIZE": 209715200,
+  "DEFAULT_RESET_PASSWORD": "123456",
+  "MAX_FILE_SIZE": 208666624,
   "MAX_IMAGE_SIZE": 10485760
 }

main.py

@@ -2,7 +2,7 @@ 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, admin, tasks, prompts, knowledge_base, client_downloads
+from app.api.endpoints import auth, users, meetings, tags, admin, tasks, prompts, knowledge_base, client_downloads, voiceprint
 from app.core.config import UPLOAD_DIR, API_CONFIG
 from app.api.endpoints.admin import load_system_config
 import os
@@ -39,6 +39,7 @@ app.include_router(tasks.router, prefix="/api", tags=["Tasks"])
 app.include_router(prompts.router, prefix="/api", tags=["Prompts"])
 app.include_router(knowledge_base.router, prefix="/api", tags=["KnowledgeBase"])
 app.include_router(client_downloads.router, prefix="/api/clients", tags=["ClientDownloads"])
+app.include_router(voiceprint.router, prefix="/api", tags=["Voiceprint"])
 
 @app.get("/")
 def read_root():

test/test_create_task.py

@@ -6,10 +6,10 @@ import sys
 import os
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 
-from app.services.async_llm_service import AsyncLLMService
+from app.services.async_meeting_service import AsyncMeetingService
 
 # 创建服务实例
-service = AsyncLLMService()
+service = AsyncMeetingService()
 
 # 创建测试任务
 meeting_id = 38

test/test_worker_thread.py

@@ -8,10 +8,10 @@ import time
 import threading
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 
-from app.services.async_llm_service import AsyncLLMService
+from app.services.async_meeting_service import AsyncMeetingService
 
 # 创建服务实例
-service = AsyncLLMService()
+service = AsyncMeetingService()
 
 # 直接调用处理任务方法测试
 print("测试直接调用_process_tasks方法...")

test_voiceprint_api.py

@@ -0,0 +1,141 @@
+"""
+声纹采集API测试脚本
+
+使用方法：
+1. 确保后端服务正在运行
+2. 修改 USER_ID 和 TOKEN 为实际值
+3. 准备一个10秒的WAV音频文件
+4. 运行: python test_voiceprint_api.py
+"""
+
+import requests
+import json
+
+# 配置
+BASE_URL = "http://localhost:8000/api"
+USER_ID = 1  # 修改为实际用户ID
+TOKEN = ""  # 登录后获取的token
+
+# 请求头
+headers = {
+    "Authorization": f"Bearer {TOKEN}",
+    "Content-Type": "application/json"
+}
+
+
+def test_get_template():
+    """测试获取朗读模板"""
+    print("\n=== 测试1: 获取朗读模板 ===")
+    url = f"{BASE_URL}/voiceprint/template"
+    response = requests.get(url, headers=headers)
+    print(f"状态码: {response.status_code}")
+    print(f"响应: {json.dumps(response.json(), ensure_ascii=False, indent=2)}")
+    return response.json()
+
+
+def test_get_status(user_id):
+    """测试获取声纹状态"""
+    print(f"\n=== 测试2: 获取用户 {user_id} 的声纹状态 ===")
+    url = f"{BASE_URL}/voiceprint/{user_id}"
+    response = requests.get(url, headers=headers)
+    print(f"状态码: {response.status_code}")
+    print(f"响应: {json.dumps(response.json(), ensure_ascii=False, indent=2)}")
+    return response.json()
+
+
+def test_upload_voiceprint(user_id, audio_file_path):
+    """测试上传声纹"""
+    print(f"\n=== 测试3: 上传声纹音频 ===")
+    url = f"{BASE_URL}/voiceprint/{user_id}"
+
+    # 移除Content-Type，让requests自动设置multipart/form-data
+    upload_headers = {
+        "Authorization": f"Bearer {TOKEN}"
+    }
+
+    with open(audio_file_path, 'rb') as f:
+        files = {'audio_file': (audio_file_path.split('/')[-1], f, 'audio/wav')}
+        response = requests.post(url, headers=upload_headers, files=files)
+
+    print(f"状态码: {response.status_code}")
+    print(f"响应: {json.dumps(response.json(), ensure_ascii=False, indent=2)}")
+    return response.json()
+
+
+def test_delete_voiceprint(user_id):
+    """测试删除声纹"""
+    print(f"\n=== 测试4: 删除用户 {user_id} 的声纹 ===")
+    url = f"{BASE_URL}/voiceprint/{user_id}"
+    response = requests.delete(url, headers=headers)
+    print(f"状态码: {response.status_code}")
+    print(f"响应: {json.dumps(response.json(), ensure_ascii=False, indent=2)}")
+    return response.json()
+
+
+def login(username, password):
+    """登录获取token"""
+    print("\n=== 登录获取Token ===")
+    url = f"{BASE_URL}/auth/login"
+    data = {
+        "username": username,
+        "password": password
+    }
+    response = requests.post(url, json=data)
+    if response.status_code == 200:
+        result = response.json()
+        if result.get('code') == '200':
+            token = result['data']['token']
+            print(f"登录成功，Token: {token[:20]}...")
+            return token
+        else:
+            print(f"登录失败: {result.get('message')}")
+            return None
+    else:
+        print(f"请求失败，状态码: {response.status_code}")
+        return None
+
+
+if __name__ == "__main__":
+    print("=" * 60)
+    print("声纹采集API测试脚本")
+    print("=" * 60)
+
+    # 步骤1: 登录（如果没有token）
+    if not TOKEN:
+        print("\n请先登录获取Token...")
+        username = input("用户名: ")
+        password = input("密码: ")
+        TOKEN = login(username, password)
+        if TOKEN:
+            headers["Authorization"] = f"Bearer {TOKEN}"
+        else:
+            print("登录失败，退出测试")
+            exit(1)
+
+    # 步骤2: 测试获取朗读模板
+    test_get_template()
+
+    # 步骤3: 测试获取声纹状态
+    test_get_status(USER_ID)
+
+    # 步骤4: 测试上传声纹（需要准备音频文件）
+    audio_file = input("\n请输入WAV音频文件路径 (回车跳过上传测试): ")
+    if audio_file.strip():
+        test_upload_voiceprint(USER_ID, audio_file.strip())
+
+        # 上传后再次查看状态
+        print("\n=== 上传后再次查看状态 ===")
+        test_get_status(USER_ID)
+
+    # 步骤5: 测试删除声纹
+    confirm = input("\n是否测试删除声纹? (yes/no): ")
+    if confirm.lower() == 'yes':
+        test_delete_voiceprint(USER_ID)
+
+        # 删除后再次查看状态
+        print("\n=== 删除后再次查看状态 ===")
+        test_get_status(USER_ID)
+
+    print("\n" + "=" * 60)
+    print("测试完成")
+    print("=" * 60)