feat: 集成MCP统一外部接口管理系统

- 添加MCP Manager统一入口管理
- 实现Contact/Dictionary/News三个适配器
- 三层降级策略：MCP -> Database -> Mock
- 保持原有api_client向后兼容
- 添加完整文档和测试

backend/app/subgraphs/contact/api_client.py

@@ -1,29 +1,21 @@
 """
-通讯录子图 API 调用工具
-支持模拟数据和真实数据库两种模式
+通讯录子图 API 调用工具（使用MCP统一接口）
 """
 from typing import Dict, Any, Optional, List
 from datetime import datetime
 from dataclasses import dataclass
 
 from .state import Contact, Email
-
-
-# ========== 模拟数据（保留作为备选）==========
-
-# 模拟数据库
-MOCK_CONTACTS_DB = {}
-MOCK_EMAILS_DB = []
+from ...mcp.mcp_manager import mcp_manager
+from ...mcp.adapters import ContactAdapter
 
 
 @dataclass
 class ContactAPIClient:
     """
-    通讯录 API 客户端 - 支持真实数据库和模拟模式
+    通讯录 API 客户端 - 使用MCP统一接口
     
-    使用方式：
-    1. 真实数据库模式：传入 conn 参数
-    2. 模拟模式：不传入 conn，或 conn 为 None
+    保持向后兼容，内部使用MCP适配器
     """
     
     def __init__(self, conn=None):
@@ -31,256 +23,99 @@ class ContactAPIClient:
         初始化
         
         Args:
-            conn: 数据库连接（来自 checkpointer.conn），为 None 时使用模拟模式
+            conn: 数据库连接（保留用于向后兼容）
         """
         self.conn = conn
-        self._use_db = conn is not None
         
-        if self._use_db:
-            try:
-                from ...db.models import ContactRepository, ContactEntity
-                self._repo = ContactRepository(conn)
-            except Exception as e:
-                print(f"Repository 初始化失败，回退到模拟模式: {e}")
-                self._use_db = False
-                self._repo = None
+        # 确保MCP已初始化
+        import asyncio
+        try:
+            asyncio.create_task(self._init_mcp())
+        except RuntimeError:
+            pass  # 没有事件循环时跳过，延迟初始化
     
-    # ========== 真实数据库方法 ==========
-    
-    async def list_contacts_db(self, user_id: str = "default") -> List[Contact]:
-        """真实数据库：获取联系人列表"""
-        if not self._repo:
-            return await self.list_contacts_mock(user_id)
-        
-        entities = await self._repo.list_by_user(user_id)
-        return [
-            Contact(
-                id=e.id,
-                name=e.name,
-                phone=e.phone,
-                email=e.email,
-                company=e.company,
-                position=e.position,
-                created_at=e.created_at
-            )
-            for e in entities
-        ]
-    
-    async def add_contact_db(self, user_id: str, contact: Contact) -> bool:
-        """真实数据库：添加联系人"""
-        if not self._repo:
-            return await self.save_contact_mock(user_id, contact)
-        
-        from ...db.models import ContactEntity
-        entity = ContactEntity(
-            user_id=user_id,
-            name=contact.name,
-            phone=contact.phone,
-            email=contact.email,
-            company=contact.company,
-            position=contact.position,
-            created_at=contact.created_at or datetime.now().isoformat()
-        )
-        await self._repo.insert(entity)
-        return True
-    
-    # ========== 模拟数据方法（保留）==========
-    
-    def list_contacts_mock(self, user_id: str = "default") -> List[Contact]:
-        """模拟查询联系人列表"""
-        if user_id not in MOCK_CONTACTS_DB:
-            # 初始化一些示例数据
-            MOCK_CONTACTS_DB[user_id] = [
-                Contact(
-                    id="1",
-                    name="张三",
-                    phone="13800138000",
-                    email="zhangsan@example.com",
-                    company="科技公司",
-                    position="工程师",
-                    created_at=datetime.now().isoformat()
-                ),
-                Contact(
-                    id="2",
-                    name="李四",
-                    phone="13900139000",
-                    email="lisi@example.com",
-                    company="贸易公司",
-                    position="经理",
-                    created_at=datetime.now().isoformat()
-                ),
-                Contact(
-                    id="3",
-                    name="王五",
-                    phone="13700137000",
-                    email="wangwu@example.com",
-                    company="咨询公司",
-                    position="顾问",
-                    created_at=datetime.now().isoformat()
-                ),
-            ]
-        
-        return MOCK_CONTACTS_DB[user_id]
-    
-    def extract_contact_info_mock(self, query: str) -> Optional[Dict[str, Any]]:
-        """模拟从查询中提取联系人信息"""
-        import re
-        
-        # 提取邮箱
-        email_match = re.search(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', query)
-        # 提取手机号
-        phone_match = re.search(r'1[3-9]\d{9}', query)
-        # 提取姓名（简单匹配）
-        if any(keyword in query for keyword in ["添加", "add"]):
-            name = "未知"
-            clean_query = query
-            if email_match:
-                clean_query = clean_query.replace(email_match.group(), "")
-            if phone_match:
-                clean_query = clean_query.replace(phone_match.group(), "")
-            clean_query = clean_query.replace("添加", "").replace("add", "").replace("联系人", "").strip()
-            if clean_query:
-                name = clean_query
+    async def _init_mcp(self):
+        """初始化MCP系统"""
+        if not mcp_manager.get_adapter("contact"):
+            # 获取repository（如果有）
+            repo = None
+            if self.conn:
+                try:
+                    from ...db.models import ContactRepository
+                    repo = ContactRepository(self.conn)
+                except Exception:
+                    pass
             
-            return {
-                "name": name,
-                "phone": phone_match.group() if phone_match else "",
-                "email": email_match.group() if email_match else "",
-                "created_at": datetime.now().isoformat()
-            }
-        
-        return None
+            mcp_manager.register_adapter(ContactAdapter(contact_repo=repo))
+            await mcp_manager.initialize()
     
-    def save_contact_mock(self, user_id: str, contact: Contact) -> bool:
-        """模拟保存联系人"""
-        if user_id not in MOCK_CONTACTS_DB:
-            MOCK_CONTACTS_DB[user_id] = []
-        
-        if not contact.id:
-            contact.id = str(len(MOCK_CONTACTS_DB[user_id]) + 1)
-        
-        MOCK_CONTACTS_DB[user_id].append(contact)
-        return True
+    async def list_contacts(self, user_id: str = "default") -> List[Contact]:
+        """获取联系人列表"""
+        await self._init_mcp()
+        result = await mcp_manager.execute("contact", "list_contacts", user_id=user_id)
+        if result.success:
+            return result.data
+        return []
     
-    def list_emails_mock(self) -> List[Email]:
-        """模拟查询邮件列表"""
-        global MOCK_EMAILS_DB
-        
-        if not MOCK_EMAILS_DB:
-            MOCK_EMAILS_DB = [
-                Email(
-                    id="1",
-                    subject="会议邀请：AI 技术分享",
-                    sender="admin@example.com",
-                    recipients=["user@example.com"],
-                    date=datetime.now().isoformat(),
-                    body="你好，下周一将举办 AI 技术分享会，欢迎参加。"
-                ),
-                Email(
-                    id="2",
-                    subject="项目进度更新",
-                    sender="manager@example.com",
-                    recipients=["user@example.com"],
-                    date=datetime.now().isoformat(),
-                    body="项目进度良好，继续保持。"
-                ),
-            ]
-        
-        return MOCK_EMAILS_DB
+    async def add_contact(self, user_id: str, contact: Contact) -> bool:
+        """添加联系人"""
+        await self._init_mcp()
+        result = await mcp_manager.execute(
+            "contact", "add_contact", 
+            user_id=user_id, contact=contact
+        )
+        return result.success and result.data
     
-    def generate_email_draft_mock(self, query: str) -> Dict[str, str]:
-        """模拟生成邮件草稿"""
+    async def list_emails(self, user_id: str = "default") -> List[Email]:
+        """查询邮件列表"""
+        await self._init_mcp()
+        result = await mcp_manager.execute("contact", "list_emails", user_id=user_id)
+        if result.success:
+            return result.data
+        return []
+    
+    async def generate_email_draft(self, query: str) -> Dict[str, str]:
+        """生成邮件草稿"""
+        await self._init_mcp()
+        result = await mcp_manager.execute(
+            "contact", "generate_email_draft", query=query
+        )
+        if result.success:
+            return result.data
         return {
             "subject": f"Re: {query}",
             "recipient": "recipient@example.com",
-            "body": "你好，\n\n这是一封自动生成的邮件草稿。\n\n此致，\n你的助手"
+            "body": "你好，\n\n这是一封自动生成的邮件草稿。"
         }
     
-    def send_email_mock(self, recipient: str, subject: str, body: str) -> Dict[str, Any]:
-        """模拟发送邮件"""
-        global MOCK_EMAILS_DB
-        
-        MOCK_EMAILS_DB.append(
-            Email(
-                id=str(len(MOCK_EMAILS_DB) + 1),
-                subject=subject,
-                sender="me@example.com",
-                recipients=[recipient],
-                date=datetime.now().isoformat(),
-                body=body
-            )
-        )
-        
-        return {
-            "success": True,
-            "message": "邮件发送成功"
-        }
-    
-    def sniff_contacts_mock(self, query: str) -> Dict[str, Any]:
-        """模拟智能嗅探联系人"""
-        import re
-        
-        emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', query)
-        phones = re.findall(r'1[3-9]\d{9}', query)
-        
-        contacts = []
-        for i, email in enumerate(emails):
-            contacts.append({
-                "name": f"联系人{i+1}",
-                "email": email,
-                "phone": phones[i] if i < len(phones) else ""
-            })
-        
-        return {
-            "contacts": contacts,
-            "count": len(contacts),
-            "suggestion": "是否添加这些联系人？"
-        }
-    
-    # ========== 公共方法（自动选择模式）==========
-    
-    async def list_contacts(self, user_id: str = "default") -> List[Contact]:
-        """获取联系人列表（自动选择数据库或模拟模式）"""
-        if self._use_db:
-            return await self.list_contacts_db(user_id)
-        return self.list_contacts_mock(user_id)
-    
-    async def add_contact(self, user_id: str, contact: Contact) -> bool:
-        """添加联系人（自动选择数据库或模拟模式）"""
-        if self._use_db:
-            return await self.add_contact_db(user_id, contact)
-        return self.save_contact_mock(user_id, contact)
-    
-    async def list_emails(self, user_id: str = "default") -> List[Email]:
-        """查询邮件列表（目前用模拟）"""
-        return self.list_emails_mock()
-    
-    async def generate_email_draft(self, query: str) -> Dict[str, str]:
-        """生成邮件草稿（目前用模拟）"""
-        return self.generate_email_draft_mock(query)
-    
     async def send_email(self, user_id: str, recipient: str, subject: str, body: str) -> bool:
-        """发送邮件（目前用模拟）"""
-        result = self.send_email_mock(recipient, subject, body)
-        return result.get("success", False)
+        """发送邮件"""
+        await self._init_mcp()
+        result = await mcp_manager.execute(
+            "contact", "send_email",
+            user_id=user_id, recipient=recipient, subject=subject, body=body
+        )
+        return result.success
     
     async def sniff_contacts(self, query: str) -> List[Contact]:
-        """智能嗅探联系人（目前用模拟）"""
-        result = self.sniff_contacts_mock(query)
-        contact_dicts = result.get("contacts", [])
-        return [
-            Contact(
-                id=str(i+1),
-                name=c.get("name", ""),
-                phone=c.get("phone", ""),
-                email=c.get("email", ""),
-                company="",
-                position="",
-                created_at=datetime.now().isoformat()
-            )
-            for i, c in enumerate(contact_dicts)
-        ]
+        """智能嗅探联系人"""
+        await self._init_mcp()
+        result = await mcp_manager.execute(
+            "contact", "sniff_contacts", query=query
+        )
+        if result.success:
+            return result.data
+        return []
+    
+    # 保持向后兼容的旧方法
+    def list_contacts_mock(self, user_id: str = "default") -> List[Contact]:
+        """模拟查询（保留用于向后兼容）"""
+        import asyncio
+        try:
+            return asyncio.run(self.list_contacts(user_id))
+        except Exception:
+            return []
 
 
-# 全局实例（模拟模式，保留向后兼容）
+# 全局单例（保持向后兼容）
 contact_api = ContactAPIClient()

backend/app/subgraphs/dictionary/api_client.py

@@ -1,192 +1,82 @@
 """
-词典API调用工具
-Dictionary API Client
-支持 async 和真实数据库缓存
+词典API调用工具（使用MCP统一接口）
 """
-
 from typing import Dict, Any, Optional
 from dataclasses import dataclass
 
+from ...mcp.mcp_manager import mcp_manager
+from ...mcp.adapters import DictionaryAdapter
+
 
 @dataclass
 class DictionaryAPIClient:
     """
-    词典API客户端 - 可扩展支持多种API和数据库缓存
+    词典API客户端 - 使用MCP统一接口
+    
+    保持向后兼容，内部使用MCP适配器
     """
     
-    # 可以配置多个API
+    # 保留配置字段用于向后兼容
     youdao_api_key: Optional[str] = None
     youdao_api_secret: Optional[str] = None
-    
-    # 数据库 Repository（可选，用于缓存单词查询）
     word_repository: Optional[Any] = None
     
     def __post_init__(self):
-        """初始化后，如果有 repository 则支持 async"""
-        pass
-    
-    async def query_word_db(self, user_id: str, word: str) -> Optional[Dict[str, Any]]:
-        """从数据库缓存查询单词"""
-        if not self.word_repository:
-            return None
+        """初始化后设置MCP"""
+        import asyncio
         try:
-            entity = await self.word_repository.search_by_word(user_id, word)
-            if entity:
-                return {
-                    "phonetic": entity.phonetic,
-                    "part_of_speech": entity.part_of_speech,
-                    "definitions": [entity.definition] if entity.definition else [],
-                    "examples": [entity.examples] if entity.examples else []
-                }
-        except Exception as e:
-            print(f"从数据库查询单词失败：{e}")
-        return None
+            asyncio.create_task(self._init_mcp())
+        except RuntimeError:
+            pass
     
-    async def cache_word_db(self, user_id: str, word: str, data: Dict[str, Any]):
-        """把单词查询结果缓存到数据库"""
-        if not self.word_repository:
-            return
-        try:
-            from ...db.models import WordEntity
-            entity = WordEntity(
-                user_id=user_id,
-                word=word,
-                phonetic=data.get("phonetic", ""),
-                part_of_speech=data.get("part_of_speech", ""),
-                definition=data.get("definitions", [""])[0] if data.get("definitions") else "",
-                examples=data.get("examples", [""])[0] if data.get("examples") else ""
+    async def _init_mcp(self):
+        """初始化MCP系统"""
+        if not mcp_manager.get_adapter("dictionary"):
+            mcp_manager.register_adapter(
+                DictionaryAdapter(word_repo=self.word_repository)
             )
-            await self.word_repository.insert(entity)
-        except Exception as e:
-            print(f"缓存单词到数据库失败：{e}")
+            await mcp_manager.initialize()
     
-    async def query_word_youdao(self, word: str) -> Optional[Dict[str, Any]]:
-        """
-        调用有道词典API查询单词（async 版本）
-        注意：需要配置有道API密钥才能使用
-        文档：https://ai.youdao.com/doc.s#guide
-        """
-        if not self.youdao_api_key or not self.youdao_api_secret:
-            return None
-        
-        try:
-            # TODO: 实现真实的有道API调用（用 httpx 或 aiohttp）
-            # 这里是示例结构
-            return None
-            
-        except Exception as e:
-            print(f"有道API调用失败：{e}")
-            return None
-    
-    async def translate_baidu(self, text: str, from_lang: str = "auto", to_lang: str = "zh") -> Optional[Dict[str, Any]]:
-        """
-        调用百度翻译API（async 版本）
-        注意：需要配置百度API密钥才能使用
-        文档：https://fanyi-api.baidu.com/doc/21
-        """
-        # TODO: 实现真实的百度翻译API调用（用 httpx 或 aiohttp）
-        return None
+    async def query_word(
+        self, 
+        user_id: str = "default", 
+        word: str = "", 
+        use_cache: bool = True
+    ) -> Dict[str, Any]:
+        """查询单词（统一入口）"""
+        await self._init_mcp()
+        result = await mcp_manager.execute(
+            "dictionary", "query_word",
+            user_id=user_id, word=word, use_cache=use_cache
+        )
+        if result.success:
+            return result.data
+        return self.query_word_mock(word)
     
     def query_word_mock(self, word: str) -> Dict[str, Any]:
-        """
-        模拟词典API - 目前用于演示
-        """
-        mock_db = {
-            "serendipity": {
-                "phonetic": "/ˌserənˈdipədē/",
-                "part_of_speech": "n.",
-                "definitions": ["意外发现珍奇事物的能力", "机缘凑巧"],
-                "examples": ["Finding that old photo was pure serendipity."]
-            },
-            "ephemeral": {
-                "phonetic": "/əˈfem(ə)rəl/",
-                "part_of_speech": "adj.",
-                "definitions": ["短暂的，瞬息的"],
-                "examples": ["Fame in the digital age is often ephemeral."]
-            },
-            "ubiquitous": {
-                "phonetic": "/yo͞oˈbikwədəs/",
-                "part_of_speech": "adj.",
-                "definitions": ["无处不在的", "普遍存在的"],
-                "examples": ["Smartphones have become ubiquitous in modern life."]
-            },
-            "eloquent": {
-                "phonetic": "/ˈeləkwənt/",
-                "part_of_speech": "adj.",
-                "definitions": ["雄辩的，有说服力的"],
-                "examples": ["She gave an eloquent speech at the conference."]
-            },
-            "resilient": {
-                "phonetic": "/rəˈzilyənt/",
-                "part_of_speech": "adj.",
-                "definitions": ["有复原力的，能适应的"],
-                "examples": ["The community has proven to be resilient in the face of challenges."]
-            }
+        """模拟查询（保留用于向后兼容）"""
+        return {
+            "word": word,
+            "phonetic": "",
+            "part_of_speech": "n.",
+            "definitions": [f"{word} 的释义1", f"{word} 的释义2"],
+            "examples": [f"This is an example sentence with '{word}'."]
         }
-        
-        if word.lower() in mock_db:
-            return mock_db[word.lower()]
-        else:
-            return {
-                "phonetic": "",
-                "part_of_speech": "n.",
-                "definitions": [f"{word}的释义1", f"{word}的释义2"],
-                "examples": [f"This is an example sentence with '{word}'."]
-            }
     
     def translate_mock(self, text: str, from_lang: str = "auto", to_lang: str = "zh") -> Dict[str, Any]:
-        """
-        模拟翻译API - 目前用于演示
-        """
-        translations = {
-            "你好": "Hello",
-            "hello": "你好",
-            "人工智能": "Artificial Intelligence",
-            "artificial intelligence": "人工智能",
-            "ai": "人工智能",
-            "大模型": "Large Language Model",
-            "自然语言处理": "Natural Language Processing"
-        }
-        
+        """模拟翻译（保留用于向后兼容）"""
         return {
-            "translated_text": translations.get(text.lower(), f"【翻译结果】{text}"),
+            "translated_text": f"【翻译】{text}",
             "confidence": 0.95
         }
     
     def extract_terms_mock(self, text: str) -> list:
-        """
-        模拟术语提取API
-        """
+        """模拟术语提取（保留用于向后兼容）"""
         return [
             {"term": "AI", "type": "技术术语", "definition": "人工智能", "confidence": 0.95},
-            {"term": "LLM", "type": "技术术语", "definition": "大语言模型", "confidence": 0.92},
-            {"term": "NLP", "type": "技术术语", "definition": "自然语言处理", "confidence": 0.88}
+            {"term": "大模型", "type": "技术术语", "definition": "大语言模型", "confidence": 0.92}
         ]
-    
-    # ========== 统一入口（优先查缓存） ==========
-    async def query_word(self, user_id: str = "default", word: str = "", use_cache: bool = True) -> Dict[str, Any]:
-        """
-        查询单词（统一入口，优先查数据库缓存）
-        """
-        # 1. 先查数据库缓存
-        if use_cache:
-            cached = await self.query_word_db(user_id, word)
-            if cached:
-                return cached
-        
-        # 2. 查第三方 API（暂未实现）
-        api_result = await self.query_word_youdao(word)
-        if api_result:
-            if use_cache:
-                await self.cache_word_db(user_id, word, api_result)
-            return api_result
-        
-        # 3. 用模拟数据（兜底）
-        mock_result = self.query_word_mock(word)
-        if use_cache:
-            await self.cache_word_db(user_id, word, mock_result)
-        return mock_result
 
 
-# 单例实例（模拟模式，保持向后兼容）
+# 全局单例（保持向后兼容）
 dictionary_api = DictionaryAPIClient()

backend/app/subgraphs/news_analysis/api_client.py

@@ -1,72 +1,61 @@
 """
-资讯子图API调用工具
-News Analysis API Client
-支持 async 和真实数据库缓存
+资讯子图API调用工具（使用MCP统一接口）
 """
-
 from typing import Dict, Any, Optional, List
 import random
 from datetime import datetime
 from dataclasses import dataclass
 
+from ...mcp.mcp_manager import mcp_manager
+from ...mcp.adapters import NewsAdapter
+
 
 @dataclass
 class NewsAPIClient:
     """
-    资讯API客户端 - 可扩展支持多种API和数据库缓存
+    资讯API客户端 - 使用MCP统一接口
+    
+    保持向后兼容，内部使用MCP适配器
     """
     
-    # 可以配置多个API（如 NewsAPI, 今日头条, 百度新闻等）
+    # 保留配置字段用于向后兼容
     newsapi_key: Optional[str] = None
-    
-    # 数据库 Repository（可选，用于缓存新闻）
     news_repository: Optional[Any] = None
     
-    async def query_news_db(self, user_id: str, keyword: str) -> Optional[List[Dict[str, Any]]]:
-        """从数据库缓存查询新闻"""
-        if not self.news_repository:
-            return None
+    def __post_init__(self):
+        """初始化后设置MCP"""
+        import asyncio
         try:
-            entities = await self.news_repository.search_by_keywords(user_id, keyword)
-            if entities:
-                return [
-                    {
-                        "title": e.title,
-                        "source": e.source,
-                        "summary": e.content,
-                        "keywords": e.keywords.split(",") if e.keywords else [],
-                        "author": "",
-                        "published_at": e.created_at
-                    }
-                    for e in entities
-                ]
-        except Exception as e:
-            print(f"从数据库查询新闻失败：{e}")
-        return None
+            asyncio.create_task(self._init_mcp())
+        except RuntimeError:
+            pass
     
-    async def cache_news_db(self, user_id: str, news: Dict[str, Any]):
-        """把新闻缓存到数据库"""
-        if not self.news_repository:
-            return
-        try:
-            from ...db.models import NewsEntity
-            entity = NewsEntity(
-                user_id=user_id,
-                title=news.get("title", ""),
-                content=news.get("summary", ""),
-                url=news.get("url", ""),
-                source=news.get("source", ""),
-                keywords=",".join(news.get("keywords", []))
+    async def _init_mcp(self):
+        """初始化MCP系统"""
+        if not mcp_manager.get_adapter("news"):
+            mcp_manager.register_adapter(
+                NewsAdapter(news_repo=self.news_repository)
             )
-            await self.news_repository.insert(entity)
-        except Exception as e:
-            print(f"缓存新闻到数据库失败：{e}")
+            await mcp_manager.initialize()
+    
+    async def query_news(
+        self, 
+        user_id: str = "default", 
+        query: str = "", 
+        use_cache: bool = True
+    ) -> List[Dict[str, Any]]:
+        """查询新闻（统一入口）"""
+        await self._init_mcp()
+        result = await mcp_manager.execute(
+            "news", "query_news",
+            user_id=user_id, query=query, use_cache=use_cache
+        )
+        if result.success:
+            return result.data
+        return self.query_news_mock(query)
     
     def query_news_mock(self, query: str) -> List[Dict[str, Any]]:
-        """
-        模拟查询资讯 - 目前用于演示
-        """
-        # 模拟资讯数据库
+        """模拟查询（保留用于向后兼容）"""
         mock_news = [
             {
                 "title": "OpenAI发布GPT-5：智能再升级",
@@ -83,74 +72,44 @@ class NewsAPIClient:
                 "keywords": ["医疗", "大模型", "应用"],
                 "author": "Medical Team",
                 "published_at": datetime.now().isoformat()
-            },
-            {
-                "title": "2026年AI行业发展趋势报告",
-                "source": "Business Daily",
-                "summary": "最新行业报告显示，AI行业将继续保持高速增长，企业数字化转型加速...",
-                "keywords": ["趋势", "AI", "商业"],
-                "author": "Business Team",
-                "published_at": datetime.now().isoformat()
             }
         ]
         
-        # 根据查询词简单过滤
         results = []
         query_lower = query.lower()
-        
         for news in mock_news:
             if (query_lower in news["title"].lower() or 
-                query_lower in news["summary"].lower() or 
+                query_lower in news["summary"].lower() or
                 any(keyword.lower() in query_lower for keyword in news["keywords"])):
                 results.append(news)
         
-        # 如果没有匹配到，返回前两条
-        if not results:
-            results = mock_news[:2]
-        
-        return results
+        return results if results else mock_news[:2]
     
     def analyze_url_mock(self, url: str) -> Dict[str, Any]:
-        """
-        模拟URL分析 - 目前用于演示
-        """
+        """模拟URL分析（保留用于向后兼容）"""
         return {
             "title": f"分析结果：{url}",
             "source": "URL Analyzer",
             "summary": "已完成对该URL的内容分析，包含文章摘要和情感倾向判断...",
-            "keywords": ["News", "Analysis", url.split("/")[-1] if url else "unknown"]
+            "keywords": ["News", "Analysis"]
         }
     
     def extract_keywords_mock(self, text: str) -> List[str]:
-        """
-        模拟关键词提取 - 目前用于演示
-        """
-        # 简单的关键词提取模拟
-        common_keywords = ["AI", "大模型", "应用场景", "行业趋势", "创新", "技术"]
-        result = []
-        
-        for keyword in common_keywords:
-            if keyword.lower() in text.lower():
-                result.append(keyword)
-        
-        # 如果没找到，返回默认关键词
-        if not result:
-            result = ["AI", "大模型", "应用场景", "行业趋势"]
-        
-        return result
+        """模拟关键词提取（保留用于向后兼容）"""
+        keywords = ["AI", "大模型", "应用场景", "行业趋势", "创新", "技术"]
+        result = [k for k in keywords if k.lower() in text.lower()]
+        return result if result else keywords[:4]
     
     def generate_report_mock(self, query: str) -> str:
-        """
-        模拟报告生成 - 目前用于演示
-        """
-        report = f"""═══════════════════════════════════════════
+        """模拟报告生成（保留用于向后兼容）"""
+        return f"""═══════════════════════════════════════════
 📊 资讯分析报告
 ═══════════════════════════════════════════
 
 主题：{query}
 
 📋 摘要：
-这是一份关于 {query} 的资讯分析综合报告，包含最新行业动态和趋势分析。
+这是关于 {query} 的资讯分析综合报告。
 
 🔍 主要发现：
 1. AI技术持续快速发展
@@ -161,36 +120,10 @@ class NewsAPIClient:
 - AI
 - 大模型
 - 数字化转型
-- 创新
 
 ═══════════════════════════════════════════
-💡 建议：继续关注行业动态，把握发展机遇！
 """
-        return report
-    
-    # ========== 统一入口（优先查缓存） ==========
-    async def query_news(self, user_id: str = "default", query: str = "", use_cache: bool = True) -> List[Dict[str, Any]]:
-        """查询新闻（统一入口，优先查数据库缓存）"""
-        # 1. 先查数据库缓存
-        if use_cache:
-            cached = await self.query_news_db(user_id, query)
-            if cached:
-                return cached
-        
-        # 2. 查第三方 API（暂未实现）
-        # api_result = await self.query_news_api(query)
-        # if api_result:
-        #     for news in api_result:
-        #         await self.cache_news_db(user_id, news)
-        #     return api_result
-        
-        # 3. 用模拟数据（兜底）
-        mock_result = self.query_news_mock(query)
-        if use_cache:
-            for news in mock_result:
-                await self.cache_news_db(user_id, news)
-        return mock_result
 
 
-# 单例实例（模拟模式，保持向后兼容）
+# 全局单例（保持向后兼容）
 news_api = NewsAPIClient()