From 205235867e1aa46a9d5fa7dbba7ec2f1bfb5644a Mon Sep 17 00:00:00 2001
From: PierreCashon <1775967499@qq.com>
Date: Wed, 7 Jan 2026 16:30:31 +0800
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 create mode 100644 services/__pycache__/deepseek_service.cpython-312.pyc
 create mode 100644 services/deepseek_service.py
 create mode 100644 static/css/style.css
 create mode 100644 static/js/main.js
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diff --git a/Project_Design.md b/Project_Design.md
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index 0000000..9378cb0
--- /dev/null
+++ b/Project_Design.md
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+# 项目设计思路
+
+## 一、项目概述
+
+### 名称
+面试官（Interviewer）
+
+### 目标用户
+正在求职的求职者，尤其是：
+- 应届毕业生
+- 跳槽求职者
+- 转行求职者
+- 希望提升面试技巧的职场人士
+
+### 核心价值
+通过AI技术降低面试准备门槛，提供个性化、即时反馈的面试练习体验，帮助求职者提升成功率。
+
+## 二、问题分析
+
+### 用户痛点
+1. 简历不知道怎么优化才能脱颖而出
+2. 缺乏面试经验，不知道面试官会问什么
+3. 面试后不知道回答得好不好，如何改进
+4. 准备效率低，缺乏针对性的练习
+
+### 市场现状
+- 传统面试辅导价格昂贵（500-2000元/小时）
+- 面试题库类产品只提供题目，缺乏交互反馈
+- AI面试产品多面向企业端，个人用户选择少
+
+## 三、解决方案
+
+### 产品形态
+Web应用（可扩展为小程序、APP）
+
+### 核心功能设计
+
+#### 功能一：简历定制问答
+
+**用户场景**
+用户有一份简历，想要针对特定岗位进行优化，或者不确定简历内容是否合适。
+
+**实现方案**
+- 支持文本输入和文件上传（后续扩展PDF解析）
+- AI分析简历与目标岗位的匹配度
+- 提供具体的优化建议：关键词补充、表述改进、内容增删
+
+**交互示例**
+```
+用户：我想应聘产品经理，这是我的一段项目经历：
+「我负责了一个电商小程序，从0到1搭建，用了3个月时间。」
+
+AI建议：
+1. 补充具体职责：负责产品规划、需求分析、原型设计等
+2. 添加数据成果：用户增长XX%、转化率提升XX%
+3. 突出技能匹配：强调需求分析、用户调研、数据分析等产品经理核心能力
+```
+
+#### 功能二：面试模拟练习
+
+**用户场景**
+用户想要练习面试，但身边没有面试官，或者不想浪费真实面试机会。
+
+**实现方案**
+- 用户选择目标岗位、经验级别
+- AI根据岗位特性生成面试问题
+- 支持多轮对话，模拟真实面试节奏
+- 可随时暂停、继续、重新开始
+
+**问题类型覆盖**
+- 自我介绍类
+- 经历描述类（STAR法则）
+- 岗位专业类
+- 情景假设类
+- 压力测试类
+- 职业规划类
+
+#### 功能三：练习反馈与改进建议
+
+**用户场景**
+用户回答完面试问题后，想要知道回答得好不好，如何改进。
+
+**实现方案**
+- 实时评估用户回答（不等到面试结束）
+- 评估维度：内容完整性、逻辑清晰度、专业匹配度、表达流畅度
+- 提供0-100分评分和星级评价
+- 给出具体改进建议
+- 提供参考回答范例（可选）
+
+**反馈示例**
+```
+问题：请介绍一下你的项目管理经验。
+
+你的回答：我之前带过两个项目，都按时交付了。
+
+AI反馈：
+- 评分：45/100
+- 内容完整度：★☆☆☆☆（过于简略，缺少关键信息）
+- 改进建议：
+  1. 补充项目背景（项目类型、规模、团队人数）
+  2. 说明具体职责和贡献
+  3. 强调遇到的挑战和解决方案
+  4. 添加可量化的成果
+
+参考回答：我在A公司担任产品经理期间，负责过2个B端SaaS产品的迭代项目...
+```
+
+## 四、技术架构
+
+### 前端
+- 技术选型：原生HTML/CSS/JS（降低学习成本）或 React/Vue
+- 核心页面：首页、简历优化页、模拟面试页、反馈页
+- 交互特点：对话式界面，模拟真实面试场景
+
+### 后端
+- 技术选型：Flask（轻量级，适合快速开发）或 FastAPI（异步支持好）
+- 职责：路由管理、API调用封装、请求处理
+
+### AI服务层
+- DeepSeek API（deepseek-chat模型）
+- 服务封装：统一调用接口、错误处理、上下文管理
+- 提示词工程：针对不同场景优化系统提示词
+
+### 数据流
+```
+用户输入 → 前端收集 → 后端接收 → AI服务调用 → 结果返回 → 前端展示
+```
+
+## 五、交互设计
+
+### 页面结构
+1. **首页**：功能入口展示，快速开始按钮
+2. **简历优化页**：输入区域、目标岗位选择、结果显示
+3. **模拟面试页**：对话式界面，问题展示区、回答输入区、提交按钮
+4. **反馈页**：评分展示、详细建议、改进后的参考回答
+
+### 视觉风格
+- 专业、简洁、智能感
+- 主色调：蓝色系（科技、专业、信任）
+- 辅助色：绿色（正面反馈）、橙色（提醒）
+
+### 响应式设计
+- 适配桌面端和移动端
+- 移动端优先考虑对话体验
+
+## 六、开发计划
+
+### 第一阶段：MVP（第1-2天）
+- 完成项目结构搭建
+- 实现DeepSeek API集成
+- 实现简历问答功能
+- 实现基础对话界面
+
+### 第二阶段：完善功能（第3-4天）
+- 实现面试模拟对话流程
+- 实现评分反馈系统
+- 优化UI/UX
+
+### 第三阶段：优化与测试（第5天）
+- Bug修复和性能优化
+- 多轮对话测试
+- 用户体验测试
+
+## 七、成功指标
+
+1. 功能完整性：所有核心功能可正常运行
+2. 响应速度：AI回复时间<3秒
+3. 用户体验：操作流程顺畅，界面清晰
+4. AI质量：回答有针对性，建议有实用价值
+
+## 八、风险与应对
+
+| 风险 | 应对措施 |
+|------|----------|
+| API调用失败 | 添加错误提示和重试机制 |
+| AI回答质量不稳定 | 优化提示词，添加回答质量过滤 |
+| 用户数据安全 | 本地存储敏感信息，不上传服务器 |
+| 并发访问压力 | 后续考虑添加请求队列和限流 |
+
+## 九、成本估算
+
+- DeepSeek API：约0.1-0.5元/千token（根据使用量）
+- 服务器：云服务器约50-200元/月（可选，本地运行则免费）
+- 域名：约50-100元/年（可选）
+
+## 十、扩展方向
+
+### 短期扩展
+- PDF简历解析
+- 多岗位预设
+- 语音输入支持
+
+### 中期扩展
+- 用户账号系统
+- 历史记录保存
+- 面试报告导出
+
+### 长期扩展
+- 职业规划建议
+- 薪资谈判指导
+- 行业趋势分析
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..380f0d2
--- /dev/null
+++ b/README.md
@@ -0,0 +1,129 @@
+# 面试官
+
+> 面向求职者的AI面试助手，提供简历定制问答和面试练习反馈服务。
+
+## 一句话描述
+
+「面试官」是一款基于DeepSeek AI的智能面试助手，帮助求职者优化简历、模拟面试并获取专业改进建议。
+
+## 核心功能（MVP）
+
+### 1. 简历定制问答
+- 用户上传简历或描述求职意向
+- AI分析简历内容，提供优化建议
+- 针对目标岗位定制简历关键词和表述
+
+### 2. 面试模拟练习
+- 用户选择目标岗位和难度级别
+- AI扮演面试官进行多轮问答
+- 实时生成针对性的面试问题
+
+### 3. 练习反馈与改进建议
+- 实时分析用户回答内容
+- 提供结构化评分（逻辑性、专业性、表达力）
+- 给出具体改进建议和参考回答
+
+## 交互流程
+
+### 简历定制问答流程
+```
+1. 用户打开应用
+2. 点击「简历优化」或输入目标岗位
+3. 上传简历文件或粘贴简历内容
+4. AI分析并展示优化建议
+5. 用户查看、采纳或继续咨询
+```
+
+### 面试模拟练习流程
+```
+1. 用户打开应用
+2. 点击「模拟面试」
+3. 选择目标岗位和难度（初级/中级/高级）
+4. AI开始面试问答（循环进行）
+5. 用户回答每个问题
+6. 点击「结束面试」查看详细反馈
+7. 查看评分和改进建议
+```
+
+## 技术栈
+
+- **后端**：Python + Flask/FastAPI
+- **前端**：HTML/CSS/JavaScript（可扩展为React/Vue）
+- **AI服务**：DeepSeek API
+- **部署**：本地运行或云服务器
+
+## 项目结构
+
+```
+面试官/
+├── README.md                 # 项目说明文档
+├── Project_Design.md         # 项目设计思路
+├── app.py                    # 主应用入口
+├── config.py                 # 配置文件（API密钥等）
+├── requirements.txt          # Python依赖
+├── static/                   # 静态资源
+│   ├── css/
+│   │   └── style.css        # 样式文件
+│   └── js/
+│       └── main.js          # 前端脚本
+├── templates/                # HTML模板
+│   └── index.html           # 主页面
+└── services/                 # 业务逻辑层
+    └── deepseek_service.py  # DeepSeek API服务
+```
+
+## 快速开始
+
+### 1. 环境准备
+
+确保已安装Python 3.8+：
+
+```bash
+python --version
+```
+
+### 2. 安装依赖
+
+```bash
+pip install -r requirements.txt
+```
+
+### 3. 配置API密钥
+
+编辑`config.py`文件：
+
+```python
+DEEPSEEK_API_KEY = "sk-9f449a2d06f644d082e32863d7c2d37c"
+```
+
+### 4. 启动应用
+
+```bash
+python app.py
+```
+
+### 5. 访问应用
+
+打开浏览器访问：http://localhost:5000
+
+## API配置
+
+本项目使用DeepSeek Chat API，官方文档：https://platform.deepseek.com/
+
+### 模型选择
+
+- `deepseek-chat`：通用对话模型（推荐）
+- `deepseek-reasoner`：推理增强模型
+
+## 后续扩展功能
+
+- [ ] 多语言支持
+- [ ] 语音面试模拟
+- [ ] 面试题库管理
+- [ ] 用户历史记录
+- [ ] PDF简历解析
+- [ ] 岗位推荐分析
+
+## 许可证
+
+MIT License
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diff --git a/app.py b/app.py
new file mode 100644
index 0000000..6cb79d4
--- /dev/null
+++ b/app.py
@@ -0,0 +1,284 @@
+from flask import Flask, render_template, request, jsonify, session
+from services.deepseek_service import deepseek_service
+from config import Config
+import uuid
+
+app = Flask(__name__)
+app.secret_key = "interviewer-secret-key-change-in-production"
+
+INTERVIEW_PHASES = {
+    "intro": "自我介绍",
+    "professional": "专业能力",
+    "scenario": "情景假设",
+    "career": "职业规划",
+    "closing": "面试结束"
+}
+
+QUESTION_COUNTS = {
+    "intro": 2,
+    "professional": 4,
+    "scenario": 2,
+    "career": 1
+}
+
+@app.route("/")
+def index():
+    return render_template("index.html")
+
+
+@app.route("/api/chat", methods=["POST"])
+def chat():
+    data = request.json
+    user_input = data.get("message", "").strip()
+    system_type = data.get("system_type", "general_assistant")
+    conversation_key = data.get("conversation_key", "default")
+    
+    if not user_input:
+        return jsonify({"error": "请输入内容"}), 400
+    
+    if conversation_key not in session:
+        session[conversation_key] = []
+    
+    conversation_history = session[conversation_key]
+    
+    try:
+        result = deepseek_service.chat(
+            user_input=user_input,
+            conversation_history=conversation_history,
+            system_type=system_type
+        )
+        
+        conversation_history.append({"role": "user", "content": user_input})
+        conversation_history.append(result)
+        session[conversation_key] = conversation_history[-20:]
+        
+        return jsonify({"response": result["content"]})
+    
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+
+@app.route("/api/resume/optimize", methods=["POST"])
+def optimize_resume():
+    data = request.json
+    resume_content = data.get("resume_content", "").strip()
+    target_position = data.get("target_position", "").strip()
+    
+    if not resume_content:
+        return jsonify({"error": "请提供简历内容"}), 400
+    
+    try:
+        result = deepseek_service.optimize_resume(resume_content, target_position)
+        return jsonify(result)
+    
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+
+@app.route("/api/interview/start", methods=["POST"])
+def start_interview():
+    data = request.json
+    job_position = data.get("job_position", "").strip()
+    difficulty = data.get("difficulty", "intermediate")
+    
+    if not job_position:
+        return jsonify({"error": "请选择目标岗位"}), 400
+    
+    interview_id = str(uuid.uuid4())
+    
+    session[f"interview_{interview_id}"] = {
+        "job_position": job_position,
+        "difficulty": difficulty,
+        "current_phase": "intro",
+        "question_count": 0,
+        "conversation_history": [],
+        "is_active": True
+    }
+    
+    first_question = deepseek_service.generate_interview_question(
+        job_position=job_position,
+        difficulty=difficulty,
+        phase="intro"
+    )
+    
+    session[f"interview_{interview_id}"]["conversation_history"].append({
+        "role": "assistant",
+        "content": f"你好！我是面试官，现在开始针对{job_position}岗位的面试。\n\n{first_question}"
+    })
+    
+    return jsonify({
+        "interview_id": interview_id,
+        "job_position": job_position,
+        "difficulty": difficulty,
+        "question": first_question,
+        "phase": "intro"
+    })
+
+
+@app.route("/api/interview/answer", methods=["POST"])
+def answer_question():
+    data = request.json
+    interview_id = data.get("interview_id", "").strip()
+    user_answer = data.get("answer", "").strip()
+    request_feedback = data.get("request_feedback", False)
+    
+    if not interview_id:
+        return jsonify({"error": "无效的面试ID"}), 400
+    
+    interview_key = f"interview_{interview_id}"
+    if interview_key not in session:
+        return jsonify({"error": "面试不存在或已结束"}), 400
+    
+    interview_data = session[interview_key]
+    
+    if not interview_data["is_active"]:
+        return jsonify({"error": "面试已结束"}), 400
+    
+    if not user_answer:
+        return jsonify({"error": "请输入你的回答"}), 400
+    
+    conversation_history = interview_data["conversation_history"]
+    
+    if request_feedback:
+        last_question = ""
+        for msg in reversed(conversation_history):
+            if msg["role"] == "assistant" and "？" in msg["content"]:
+                last_question = msg["content"]
+                break
+        
+        if last_question:
+            try:
+                feedback = deepseek_service.chat_with_feedback(
+                    user_input=last_question,
+                    user_answer=user_answer,
+                    conversation_history=conversation_history[:-1]
+                )
+                conversation_history.append({"role": "user", "content": user_answer})
+                conversation_history.append(feedback)
+                
+                return jsonify({
+                    "feedback": feedback["content"],
+                    "ended": False
+                })
+            except Exception as e:
+                return jsonify({"error": f"生成反馈失败：{str(e)}"}), 500
+    
+    conversation_history.append({"role": "user", "content": user_answer})
+    
+    interview_data["question_count"] += 1
+    current_phase = interview_data["current_phase"]
+    phase_order = ["intro", "professional", "scenario", "career", "closing"]
+    
+    current_index = phase_order.index(current_phase)
+    questions_in_phase = QUESTION_COUNTS.get(current_phase, 1)
+    
+    next_question = None
+    
+    if interview_data["question_count"] >= questions_in_phase:
+        if current_index < len(phase_order) - 1:
+            next_phase = phase_order[current_index + 1]
+            interview_data["current_phase"] = next_phase
+            interview_data["question_count"] = 0
+            
+            if next_phase == "closing":
+                conversation_history.append({
+                    "role": "assistant",
+                    "content": "面试结束！感谢你的参与。点击下方按钮获取本次面试的详细反馈。"
+                })
+                interview_data["is_active"] = False
+                
+                return jsonify({
+                    "question": None,
+                    "feedback": "面试结束",
+                    "ended": True,
+                    "conversation_history": conversation_history[-10:]
+                })
+            else:
+                phase_names = {
+                    "intro": "自我介绍",
+                    "professional": "专业能力",
+                    "scenario": "情景假设",
+                    "career": "职业规划"
+                }
+                
+                try:
+                    next_question = deepseek_service.generate_interview_question(
+                        job_position=interview_data["job_position"],
+                        difficulty=interview_data["difficulty"],
+                        conversation_history=conversation_history[:-1],
+                        phase=next_phase
+                    )
+                    conversation_history.append({
+                        "role": "assistant",
+                        "content": f"（{phase_names.get(next_phase, next_phase)}阶段）\n\n{next_question}"
+                    })
+                except Exception as e:
+                    return jsonify({"error": f"生成问题失败：{str(e)}"}), 500
+    else:
+        try:
+            next_question = deepseek_service.generate_interview_question(
+                job_position=interview_data["job_position"],
+                difficulty=interview_data["difficulty"],
+                conversation_history=conversation_history[:-1],
+                phase=current_phase
+            )
+            conversation_history.append({"role": "assistant", "content": next_question})
+        except Exception as e:
+            return jsonify({"error": f"生成问题失败：{str(e)}"}), 500
+    
+    session[interview_key] = interview_data
+    
+    return jsonify({
+        "question": next_question,
+        "feedback": None,
+        "ended": False,
+        "phase": interview_data["current_phase"]
+    })
+
+
+@app.route("/api/interview/feedback", methods=["POST"])
+def get_interview_feedback():
+    data = request.json
+    interview_id = data.get("interview_id", "").strip()
+    conversation_history = data.get("conversation_history", [])
+    
+    if not interview_id:
+        return jsonify({"error": "无效的面试ID"}), 400
+    
+    system_prompt = """作为一位专业的面试评估专家，请对整场面试进行全面评估。
+
+请提供：
+1. 整体表现评分（0-100分）和评级（优秀/良好/一般/需改进）
+2. 各轮回答的详细分析
+3.  strengths（优势）
+4. areas_for_improvement（需要改进的方面）
+5. 具体的准备建议
+
+请用中文回复，格式清晰、结构化。"""
+    
+    conversation_text = "\n\n".join([
+        f"{msg['role']}：{msg['content']}" 
+        for msg in conversation_history[-30:]
+    ])
+    
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"请分析以下面试对话并给出综合反馈：\n\n{conversation_text}"}
+    ]
+    
+    try:
+        response = deepseek_service._call_api(messages)
+        feedback = response["choices"][0]["message"]["content"]
+        
+        return jsonify({"feedback": feedback})
+    
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+
+if __name__ == "__main__":
+    app.run(
+        host=Config.APP_HOST,
+        port=Config.APP_PORT,
+        debug=Config.DEBUG
+    )
diff --git a/config.py b/config.py
new file mode 100644
index 0000000..422bd95
--- /dev/null
+++ b/config.py
@@ -0,0 +1,93 @@
+import os
+from typing import Optional
+
+class Config:
+    DEEPSEEK_API_KEY: str = "sk-9f449a2d06f644d082e32863d7c2d37c"
+    DEEPSEEK_API_BASE: str = "https://api.deepseek.com"
+    MODEL_NAME: str = "deepseek-chat"
+    
+    MAX_TOKENS: int = 2000
+    TEMPERATURE: float = 0.7
+    
+    APP_HOST: str = "0.0.0.0"
+    APP_PORT: int = 5000
+    DEBUG: bool = True
+
+def get_api_key() -> str:
+    api_key = os.getenv("DEEPSEEK_API_KEY")
+    if not api_key:
+        api_key = Config.DEEPSEEK_API_KEY
+    return api_key
+
+SYSTEM_PROMPTS = {
+    "resume_optimization": """你是一位专业的简历优化顾问和面试辅导专家。你的任务是帮助用户优化简历，提供专业的求职建议。
+
+工作流程：
+1. 分析用户提供的简历内容或求职意向
+2. 针对目标岗位评估简历的匹配度
+3. 提供具体的优化建议：
+   - 关键词补充（ATS系统友好）
+   - 表述方式改进（STAR法则）
+   - 内容结构优化
+   - 量化成果强调
+4. 用专业、鼓励的语气回复
+
+请确保：
+- 回复简洁有力，重点突出
+- 每次只针对一个具体问题给出建议
+- 提供可操作的改进方案，而不是泛泛而谈
+- 如果信息不足，主动询问用户需要补充的内容""",
+    
+    "interview_simulation": """你是一位经验丰富的面试官，负责进行模拟面试。你的任务是扮演目标岗位的面试官，向候选人提问并评估其回答。
+
+工作流程：
+1. 根据用户选择的岗位和级别，准备针对性的面试问题
+2. 从基础问题开始，逐步深入
+3. 每轮只问一个问题，等待用户回答
+4. 根据用户回答，决定：
+   - 进入下一个问题
+   - 追问细节
+   - 给出反馈（如果用户要求结束面试）
+
+面试问题类型：
+- 自我介绍（1-2轮）
+- 岗位专业能力（3-5轮）
+- 情景假设（1-2轮）
+- 职业规划（1轮）
+
+注意事项：
+- 问题要真实、典型、有挑战性
+- 语气专业但友好
+- 适当追问以深入了解
+- 严格遵守用户选择的岗位和级别""",
+    
+    "answer_feedback": """你是一位专业的面试辅导专家，负责评估用户的面试回答并提供改进建议。
+
+评估维度：
+1. 内容完整性（0-25分）：是否覆盖问题要点
+2. 逻辑清晰度（0-25分）：结构是否清晰，论证是否严密
+3. 专业匹配度（0-25分）：是否展示岗位所需的专业能力
+4. 表达流畅度（0-25分）：语言是否流畅自然
+
+反馈格式：
+- 整体评分（X/100）和星级（★☆☆☆☆）
+- 每个维度的具体得分和评价
+- 具体的改进建议（3-5条）
+- 参考回答示例（可选，用来说明好的回答应该是什么样的）
+
+要求：
+- 评价客观中肯，既要指出不足也要肯定优点
+- 建议要具体可操作，不是泛泛而谈
+- 语言要鼓励性强，帮助用户建立信心
+- 如果回答已经很优秀，可以简短肯定并进入下一题""",
+    
+    "general_assistant": """你是一位智能求职助手，专门帮助求职者解决求职相关问题。
+
+你可以帮助用户：
+- 解答简历制作和优化问题
+- 提供面试技巧和建议
+- 分析岗位要求和匹配度
+- 分享行业知识和职业发展建议
+
+请用专业、友好、鼓励的语气与用户交流。回复要简洁有用，避免冗长。"""
+}
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..d8903a4
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,4 @@
+flask>=2.3.0
+requests>=2.31.0
+python-dotenv>=1.0.0
+gunicorn>=21.0.0
diff --git a/services/__pycache__/deepseek_service.cpython-312.pyc b/services/__pycache__/deepseek_service.cpython-312.pyc
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HcmV?d00001

diff --git a/services/deepseek_service.py b/services/deepseek_service.py
new file mode 100644
index 0000000..cfbf38e
--- /dev/null
+++ b/services/deepseek_service.py
@@ -0,0 +1,126 @@
+import requests
+import json
+from typing import List, Dict, Optional, Generator
+from config import Config, SYSTEM_PROMPTS, get_api_key
+
+
+class DeepSeekService:
+    def __init__(self):
+        self.api_key = get_api_key()
+        self.api_base = Config.DEEPSEEK_API_BASE
+        self.model = Config.MODEL_NAME
+        self.max_tokens = Config.MAX_TOKENS
+        self.temperature = Config.TEMPERATURE
+    
+    def _get_headers(self) -> Dict[str, str]:
+        return {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json"
+        }
+    
+    def _build_messages(self, system_prompt: str, conversation_history: List[Dict[str, str]], 
+                        user_input: str) -> List[Dict[str, str]]:
+        messages = [{"role": "system", "content": system_prompt}]
+        messages.extend(conversation_history)
+        messages.append({"role": "user", "content": user_input})
+        return messages
+    
+    def _call_api(self, messages: List[Dict[str, str]], stream: bool = False) -> Dict:
+        payload = {
+            "model": self.model,
+            "messages": messages,
+            "max_tokens": self.max_tokens,
+            "temperature": self.temperature,
+            "stream": stream
+        }
+        
+        response = requests.post(
+            f"{self.api_base}/chat/completions",
+            headers=self._get_headers(),
+            json=payload,
+            timeout=30
+        )
+        
+        if response.status_code != 200:
+            error_msg = f"API调用失败：状态码 {response.status_code}"
+            try:
+                error_detail = response.json().get("error", {})
+                error_msg += f"，错误信息：{error_detail.get('message', '未知错误')}"
+            except:
+                error_msg += f"，响应内容：{response.text}"
+            raise Exception(error_msg)
+        
+        return response.json()
+    
+    def chat(self, user_input: str, conversation_history: List[Dict[str, str]] = None,
+             system_type: str = "general_assistant") -> Dict[str, str]:
+        if conversation_history is None:
+            conversation_history = []
+        
+        system_prompt = SYSTEM_PROMPTS.get(system_type, SYSTEM_PROMPTS["general_assistant"])
+        messages = self._build_messages(system_prompt, conversation_history, user_input)
+        
+        response = self._call_api(messages)
+        assistant_message = response["choices"][0]["message"]["content"]
+        
+        return {"role": "assistant", "content": assistant_message}
+    
+    def chat_with_feedback(self, user_input: str, user_answer: str,
+                          conversation_history: List[Dict[str, str]] = None) -> Dict[str, str]:
+        if conversation_history is None:
+            conversation_history = []
+        
+        feedback_prompt = SYSTEM_PROMPTS["answer_feedback"]
+        
+        context = f"面试问题：{user_input}\n\n候选人回答：{user_answer}"
+        messages = self._build_messages(feedback_prompt, conversation_history, context)
+        
+        response = self._call_api(messages)
+        feedback_content = response["choices"][0]["message"]["content"]
+        
+        return {"role": "assistant", "content": feedback_content}
+    
+    def generate_interview_question(self, job_position: str, difficulty: str,
+                                    conversation_history: List[Dict[str, str]] = None,
+                                    phase: str = "intro") -> str:
+        if conversation_history is None:
+            conversation_history = []
+        
+        system_prompt = SYSTEM_PROMPTS["interview_simulation"]
+        
+        context = f"""
+目标岗位：{job_position}
+难度级别：{difficulty}
+面试阶段：{phase}
+
+请根据以上信息，提出一个针对性的面试问题。
+"""
+        messages = self._build_messages(system_prompt, conversation_history, context)
+        
+        response = self._call_api(messages)
+        question = response["choices"][0]["message"]["content"]
+        
+        return question
+    
+    def optimize_resume(self, resume_content: str, target_position: str = None) -> Dict[str, str]:
+        system_prompt = SYSTEM_PROMPTS["resume_optimization"]
+        
+        if target_position:
+            user_input = f"目标岗位：{target_position}\n\n简历内容：\n{resume_content}"
+        else:
+            user_input = f"请分析以下简历内容，提供优化建议：\n\n{resume_content}"
+        
+        messages = [{"role": "system", "content": system_prompt}]
+        messages.append({"role": "user", "content": user_input})
+        
+        response = self._call_api(messages)
+        optimization_suggestions = response["choices"][0]["message"]["content"]
+        
+        return {
+            "resume_content": resume_content,
+            "target_position": target_position,
+            "suggestions": optimization_suggestions
+        }
+
+
+deepseek_service = DeepSeekService()
diff --git a/static/css/style.css b/static/css/style.css
new file mode 100644
index 0000000..47afb9b
--- /dev/null
+++ b/static/css/style.css
@@ -0,0 +1,537 @@
+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+
+body {
+    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    min-height: 100vh;
+    color: #333;
+}
+
+.container {
+    max-width: 1200px;
+    margin: 0 auto;
+    padding: 20px;
+    min-height: 100vh;
+    display: flex;
+    flex-direction: column;
+}
+
+.header {
+    text-align: center;
+    padding: 40px 20px;
+    color: white;
+}
+
+.logo {
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    gap: 15px;
+    margin-bottom: 15px;
+}
+
+.logo-icon {
+    font-size: 48px;
+}
+
+.logo h1 {
+    font-size: 48px;
+    font-weight: 700;
+    text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
+}
+
+.tagline {
+    font-size: 18px;
+    opacity: 0.9;
+}
+
+.main-content {
+    flex: 1;
+    padding: 20px 0;
+}
+
+.feature-section {
+    display: grid;
+    grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
+    gap: 25px;
+    margin-bottom: 30px;
+}
+
+.feature-card {
+    background: white;
+    border-radius: 16px;
+    padding: 35px 30px;
+    text-align: center;
+    cursor: pointer;
+    transition: all 0.3s ease;
+    box-shadow: 0 10px 30px rgba(0,0,0,0.1);
+}
+
+.feature-card:hover {
+    transform: translateY(-8px);
+    box-shadow: 0 15px 40px rgba(0,0,0,0.15);
+}
+
+.feature-icon {
+    font-size: 56px;
+    margin-bottom: 20px;
+}
+
+.feature-card h3 {
+    font-size: 24px;
+    color: #333;
+    margin-bottom: 12px;
+}
+
+.feature-card p {
+    color: #666;
+    font-size: 15px;
+    line-height: 1.6;
+}
+
+.tool-section {
+    background: white;
+    border-radius: 16px;
+    padding: 35px;
+    box-shadow: 0 10px 30px rgba(0,0,0,0.1);
+}
+
+.section-header {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    margin-bottom: 30px;
+    padding-bottom: 20px;
+    border-bottom: 2px solid #f0f0f0;
+}
+
+.section-header h2 {
+    font-size: 26px;
+    color: #333;
+}
+
+.back-btn {
+    background: #f5f5f5;
+    color: #666;
+    border: none;
+    padding: 10px 20px;
+    border-radius: 8px;
+    cursor: pointer;
+    font-size: 14px;
+    transition: all 0.2s;
+}
+
+.back-btn:hover {
+    background: #e0e0e0;
+}
+
+.input-group {
+    margin-bottom: 25px;
+}
+
+.input-group label {
+    display: block;
+    font-size: 15px;
+    font-weight: 600;
+    color: #333;
+    margin-bottom: 10px;
+}
+
+.input-group input[type="text"],
+.input-group textarea {
+    width: 100%;
+    padding: 14px 18px;
+    border: 2px solid #e0e0e0;
+    border-radius: 10px;
+    font-size: 15px;
+    transition: border-color 0.2s;
+    font-family: inherit;
+}
+
+.input-group input[type="text"]:focus,
+.input-group textarea:focus {
+    outline: none;
+    border-color: #667eea;
+}
+
+.input-group textarea {
+    resize: vertical;
+    min-height: 150px;
+}
+
+.difficulty-options {
+    display: flex;
+    gap: 20px;
+}
+
+.radio-label {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    cursor: pointer;
+    font-size: 15px;
+}
+
+.radio-label input[type="radio"] {
+    width: 18px;
+    height: 18px;
+    cursor: pointer;
+}
+
+.submit-btn {
+    width: 100%;
+    padding: 16px;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    border: none;
+    border-radius: 10px;
+    font-size: 17px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: transform 0.2s, box-shadow 0.2s;
+}
+
+.submit-btn:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 5px 20px rgba(102, 126, 234, 0.4);
+}
+
+.submit-btn:active {
+    transform: translateY(0);
+}
+
+.result-box {
+    margin-top: 30px;
+    padding: 25px;
+    background: #f8f9ff;
+    border-radius: 12px;
+    border-left: 4px solid #667eea;
+}
+
+.result-box h3 {
+    font-size: 18px;
+    color: #333;
+    margin-bottom: 15px;
+}
+
+.suggestions-content {
+    font-size: 15px;
+    line-height: 1.8;
+    color: #444;
+}
+
+.suggestions-content h4 {
+    color: #667eea;
+    margin: 15px 0 8px;
+}
+
+.interview-setup {
+    max-width: 600px;
+    margin: 0 auto;
+}
+
+.interview-active {
+    display: flex;
+    flex-direction: column;
+    height: calc(100vh - 300px);
+    min-height: 500px;
+}
+
+.interview-info {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    padding: 15px 20px;
+    background: #f5f5f5;
+    border-radius: 10px;
+    margin-bottom: 20px;
+}
+
+#current-position {
+    font-weight: 600;
+    color: #333;
+}
+
+.phase-badge {
+    background: #667eea;
+    color: white;
+    padding: 5px 15px;
+    border-radius: 20px;
+    font-size: 13px;
+}
+
+.interview-messages {
+    flex: 1;
+    overflow-y: auto;
+    padding: 20px;
+    background: #fafafa;
+    border-radius: 12px;
+    margin-bottom: 20px;
+    max-height: 400px;
+}
+
+.message {
+    margin-bottom: 20px;
+    padding: 15px 20px;
+    border-radius: 12px;
+    max-width: 85%;
+    line-height: 1.6;
+    font-size: 15px;
+}
+
+.message.interviewer {
+    background: #667eea;
+    color: white;
+    margin-right: auto;
+}
+
+.message.candidate {
+    background: #e8f5e9;
+    color: #333;
+    margin-left: auto;
+}
+
+.message.feedback {
+    background: #fff3e0;
+    color: #333;
+    border-left: 4px solid #ff9800;
+    margin: 20px 0;
+}
+
+.interview-input-area {
+    margin-bottom: 15px;
+}
+
+.interview-input-area textarea {
+    width: 100%;
+    padding: 14px 18px;
+    border: 2px solid #e0e0e0;
+    border-radius: 10px;
+    font-size: 15px;
+    resize: none;
+    font-family: inherit;
+}
+
+.interview-input-area textarea:focus {
+    outline: none;
+    border-color: #667eea;
+}
+
+.input-actions {
+    display: flex;
+    gap: 15px;
+    margin-top: 12px;
+}
+
+.action-btn {
+    flex: 1;
+    padding: 14px;
+    border: none;
+    border-radius: 10px;
+    font-size: 15px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: all 0.2s;
+}
+
+.action-btn.primary {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+}
+
+.action-btn.secondary {
+    background: #f5f5f5;
+    color: #666;
+}
+
+.action-btn:hover {
+    transform: translateY(-2px);
+}
+
+.interview-controls {
+    text-align: center;
+}
+
+.control-btn {
+    background: #ff6b6b;
+    color: white;
+    border: none;
+    padding: 12px 30px;
+    border-radius: 8px;
+    font-size: 14px;
+    cursor: pointer;
+    transition: all 0.2s;
+}
+
+.control-btn:hover {
+    background: #ee5a5a;
+}
+
+.interview-feedback {
+    padding: 25px;
+    background: #f8f9ff;
+    border-radius: 12px;
+}
+
+.interview-feedback h3 {
+    font-size: 22px;
+    color: #333;
+    margin-bottom: 20px;
+}
+
+.feedback-content {
+    font-size: 15px;
+    line-height: 1.8;
+    color: #444;
+    margin-bottom: 25px;
+}
+
+.chat-container {
+    display: flex;
+    flex-direction: column;
+    height: calc(100vh - 350px);
+    min-height: 400px;
+}
+
+.chat-messages {
+    flex: 1;
+    overflow-y: auto;
+    padding: 20px;
+    background: #fafafa;
+    border-radius: 12px;
+    margin-bottom: 20px;
+}
+
+.chat-message {
+    margin-bottom: 15px;
+    padding: 12px 18px;
+    border-radius: 12px;
+    max-width: 85%;
+    line-height: 1.6;
+    font-size: 15px;
+}
+
+.chat-message.assistant {
+    background: #e3f2fd;
+    color: #333;
+    margin-right: auto;
+}
+
+.chat-message.user {
+    background: #f3e5f5;
+    color: #333;
+    margin-left: auto;
+}
+
+.chat-input-area {
+    display: flex;
+    gap: 15px;
+}
+
+.chat-input-area input {
+    flex: 1;
+    padding: 14px 18px;
+    border: 2px solid #e0e0e0;
+    border-radius: 10px;
+    font-size: 15px;
+}
+
+.chat-input-area input:focus {
+    outline: none;
+    border-color: #667eea;
+}
+
+.send-btn {
+    padding: 14px 28px;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    border: none;
+    border-radius: 10px;
+    font-size: 15px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: all 0.2s;
+}
+
+.send-btn:hover {
+    transform: translateY(-2px);
+}
+
+.footer {
+    text-align: center;
+    padding: 25px;
+    color: rgba(255,255,255,0.8);
+    font-size: 14px;
+}
+
+.loading-overlay {
+    position: fixed;
+    top: 0;
+    left: 0;
+    width: 100%;
+    height: 100%;
+    background: rgba(0,0,0,0.5);
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    justify-content: center;
+    z-index: 1000;
+}
+
+.loading-spinner {
+    width: 50px;
+    height: 50px;
+    border: 4px solid rgba(255,255,255,0.3);
+    border-top-color: white;
+    border-radius: 50%;
+    animation: spin 1s linear infinite;
+}
+
+@keyframes spin {
+    to { transform: rotate(360deg); }
+}
+
+.loading-overlay p {
+    color: white;
+    margin-top: 15px;
+    font-size: 15px;
+}
+
+@media (max-width: 768px) {
+    .container {
+        padding: 15px;
+    }
+    
+    .header {
+        padding: 30px 15px;
+    }
+    
+    .logo h1 {
+        font-size: 36px;
+    }
+    
+    .feature-section {
+        grid-template-columns: 1fr;
+    }
+    
+    .tool-section {
+        padding: 25px 20px;
+    }
+    
+    .difficulty-options {
+        flex-direction: column;
+        gap: 12px;
+    }
+    
+    .message {
+        max-width: 95%;
+    }
+    
+    .input-actions {
+        flex-direction: column;
+    }
+}
diff --git a/static/js/main.js b/static/js/main.js
new file mode 100644
index 0000000..1ca8eca
--- /dev/null
+++ b/static/js/main.js
@@ -0,0 +1,402 @@
+let currentFeature = null;
+let interviewId = null;
+let conversationKey = 'default';
+
+function showFeature(feature) {
+    document.querySelectorAll('.tool-section').forEach(section => {
+        section.style.display = 'none';
+    });
+    
+    document.querySelectorAll('.feature-card').forEach(card => {
+        card.style.transform = '';
+        card.style.boxShadow = '';
+    });
+    
+    if (feature === null) {
+        currentFeature = null;
+        return;
+    }
+    
+    const featureCard = document.querySelector(`.feature-card[onclick="showFeature('${feature}')"]`);
+    if (featureCard) {
+        featureCard.style.transform = 'translateY(-5px)';
+        featureCard.style.boxShadow = '0 10px 30px rgba(102, 126, 234, 0.3)';
+    }
+    
+    currentFeature = feature;
+    
+    const sectionMap = {
+        'resume': 'resume-section',
+        'interview': 'interview-section',
+        'feedback': 'interview-section'
+    };
+    
+    const targetSection = sectionMap[feature];
+    if (targetSection) {
+        document.getElementById(targetSection).style.display = 'block';
+        
+        if (feature === 'interview' || feature === 'feedback') {
+            resetInterview();
+        } else if (feature === 'resume') {
+            document.getElementById('resume-result').style.display = 'none';
+        }
+    }
+}
+
+function showLoading(show) {
+    document.getElementById('loading-overlay').style.display = show ? 'flex' : 'none';
+}
+
+async function optimizeResume() {
+    const targetPosition = document.getElementById('target-position').value.trim();
+    const resumeContent = document.getElementById('resume-content').value.trim();
+    
+    if (!resumeContent) {
+        alert('请输入简历内容');
+        return;
+    }
+    
+    showLoading(true);
+    
+    try {
+        const response = await fetch('/api/resume/optimize', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                resume_content: resumeContent,
+                target_position: targetPosition
+            })
+        });
+        
+        const data = await response.json();
+        
+        if (data.error) {
+            alert(data.error);
+            return;
+        }
+        
+        const suggestionsDiv = document.getElementById('resume-suggestions');
+        suggestionsDiv.innerHTML = formatSuggestions(data.suggestions);
+        document.getElementById('resume-result').style.display = 'block';
+        
+    } catch (error) {
+        alert('优化失败：' + error.message);
+    } finally {
+        showLoading(false);
+    }
+}
+
+function formatSuggestions(text) {
+    if (!text) return '<p>未能生成优化建议，请重试。</p>';
+    
+    let html = text
+        .replace(/\n\n/g, '</p><p>')
+        .replace(/\n/g, '<br>');
+    
+    return '<p>' + html + '</p>';
+}
+
+async function startInterview() {
+    const jobPosition = document.getElementById('job-position').value.trim();
+    
+    if (!jobPosition) {
+        alert('请输入目标岗位');
+        return;
+    }
+    
+    const difficulty = document.querySelector('input[name="difficulty"]:checked').value;
+    
+    showLoading(true);
+    
+    try {
+        const response = await fetch('/api/interview/start', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                job_position: jobPosition,
+                difficulty: difficulty
+            })
+        });
+        
+        const data = await response.json();
+        
+        if (data.error) {
+            alert(data.error);
+            return;
+        }
+        
+        interviewId = data.interview_id;
+        
+        document.getElementById('interview-setup').style.display = 'none';
+        document.getElementById('interview-active').style.display = 'flex';
+        
+        document.getElementById('current-position').textContent = '目标岗位：' + data.job_position;
+        updatePhaseBadge(data.phase);
+        
+        const messagesContainer = document.getElementById('interview-messages');
+        messagesContainer.innerHTML = '';
+        
+        addInterviewMessage(data.question, 'interviewer');
+        
+    } catch (error) {
+        alert('开始面试失败：' + error.message);
+    } finally {
+        showLoading(false);
+    }
+}
+
+function updatePhaseBadge(phase) {
+    const phaseMap = {
+        'intro': '自我介绍',
+        'professional': '专业能力',
+        'scenario': '情景假设',
+        'career': '职业规划',
+        'closing': '面试结束'
+    };
+    
+    document.getElementById('current-phase').textContent = phaseMap[phase] || phase;
+}
+
+function addInterviewMessage(content, type) {
+    if (!content) return;
+    
+    const messagesContainer = document.getElementById('interview-messages');
+    const messageDiv = document.createElement('div');
+    messageDiv.className = 'message ' + type;
+    messageDiv.textContent = content;
+    messagesContainer.appendChild(messageDiv);
+    messagesContainer.scrollTop = messagesContainer.scrollHeight;
+}
+
+async function submitAnswer() {
+    const answerInput = document.getElementById('answer-input');
+    const answer = answerInput.value.trim();
+    
+    if (!answer) {
+        alert('请输入你的回答');
+        return;
+    }
+    
+    addInterviewMessage(answer, 'candidate');
+    answerInput.value = '';
+    
+    showLoading(true);
+    
+    try {
+        const response = await fetch('/api/interview/answer', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                interview_id: interviewId,
+                answer: answer,
+                request_feedback: false
+            })
+        });
+        
+        const data = await response.json();
+        
+        if (data.error) {
+            alert(data.error);
+            return;
+        }
+        
+        if (data.ended) {
+            showFinalFeedback(data.conversation_history);
+        } else if (data.question) {
+            addInterviewMessage(data.question, 'interviewer');
+            updatePhaseBadge(data.phase);
+        }
+        
+    } catch (error) {
+        alert('提交回答失败：' + error.message);
+    } finally {
+        showLoading(false);
+    }
+}
+
+async function requestFeedback() {
+    const answerInput = document.getElementById('answer-input');
+    const answer = answerInput.value.trim();
+    
+    if (!answer) {
+        alert('请先输入你的回答');
+        return;
+    }
+    
+    addInterviewMessage(answer, 'candidate');
+    answerInput.value = '';
+    
+    showLoading(true);
+    
+    try {
+        const response = await fetch('/api/interview/answer', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                interview_id: interviewId,
+                answer: answer,
+                request_feedback: true
+            })
+        });
+        
+        const data = await response.json();
+        
+        if (data.error) {
+            alert(data.error);
+            return;
+        }
+        
+        if (data.feedback) {
+            addInterviewMessage(data.feedback, 'feedback');
+        }
+        
+    } catch (error) {
+        alert('获取反馈失败：' + error.message);
+    } finally {
+        showLoading(false);
+    }
+}
+
+async function endInterview() {
+    const messages = [];
+    document.querySelectorAll('.interview-messages .message').forEach(msg => {
+        messages.push({
+            role: msg.classList.contains('interviewer') ? 'assistant' : 'user',
+            content: msg.textContent
+        });
+    });
+    
+    showLoading(true);
+    
+    try {
+        const response = await fetch('/api/interview/feedback', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                interview_id: interviewId,
+                conversation_history: messages
+            })
+        });
+        
+        const data = await response.json();
+        
+        if (data.error) {
+            alert(data.error);
+            return;
+        }
+        
+        showFinalFeedback(data.feedback);
+        
+    } catch (error) {
+        alert('获取反馈失败：' + error.message);
+    } finally {
+        showLoading(false);
+    }
+}
+
+function showFinalFeedback(feedbackData) {
+    document.getElementById('interview-active').style.display = 'none';
+    document.getElementById('interview-feedback').style.display = 'block';
+    
+    const feedbackContent = document.getElementById('feedback-content');
+    
+    if (typeof feedbackData === 'string') {
+        feedbackContent.innerHTML = formatSuggestions(feedbackData);
+    } else {
+        let html = '<h4>面试综合评估</h4>';
+        feedbackData.forEach(msg => {
+            html += `<p><strong>${msg.role === 'assistant' ? '面试官' : '你'}：</strong>${msg.content}</p>`;
+        });
+        feedbackContent.innerHTML = html;
+    }
+}
+
+function resetInterview() {
+    interviewId = null;
+    document.getElementById('interview-setup').style.display = 'block';
+    document.getElementById('interview-active').style.display = 'none';
+    document.getElementById('interview-feedback').style.display = 'none';
+    document.getElementById('interview-messages').innerHTML = '';
+    document.getElementById('answer-input').value = '';
+    document.getElementById('job-position').value = '';
+}
+
+async function sendChatMessage() {
+    const chatInput = document.getElementById('chat-input');
+    const message = chatInput.value.trim();
+    
+    if (!message) {
+        return;
+    }
+    
+    const messagesContainer = document.getElementById('chat-messages');
+    
+    const userMessageDiv = document.createElement('div');
+    userMessageDiv.className = 'chat-message user';
+    userMessageDiv.textContent = message;
+    messagesContainer.appendChild(userMessageDiv);
+    
+    chatInput.value = '';
+    messagesContainer.scrollTop = messagesContainer.scrollHeight;
+    
+    showLoading(true);
+    
+    try {
+        const response = await fetch('/api/chat', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                message: message,
+                system_type: 'general_assistant',
+                conversation_key: conversationKey
+            })
+        });
+        
+        const data = await response.json();
+        
+        if (data.error) {
+            alert(data.error);
+            return;
+        }
+        
+        const assistantMessageDiv = document.createElement('div');
+        assistantMessageDiv.className = 'chat-message assistant';
+        assistantMessageDiv.textContent = data.response;
+        messagesContainer.appendChild(assistantMessageDiv);
+        
+        messagesContainer.scrollTop = messagesContainer.scrollHeight;
+        
+    } catch (error) {
+        alert('发送消息失败：' + error.message);
+    } finally {
+        showLoading(false);
+    }
+}
+
+document.addEventListener('DOMContentLoaded', function() {
+    document.getElementById('chat-input').addEventListener('keypress', function(e) {
+        if (e.key === 'Enter' && !e.shiftKey) {
+            e.preventDefault();
+            sendChatMessage();
+        }
+    });
+    
+    document.getElementById('answer-input').addEventListener('keypress', function(e) {
+        if (e.key === 'Enter' && !e.shiftKey) {
+            e.preventDefault();
+            submitAnswer();
+        }
+    });
+});
diff --git a/templates/index.html b/templates/index.html
new file mode 100644
index 0000000..829c523
--- /dev/null
+++ b/templates/index.html
@@ -0,0 +1,154 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>面试官 - AI面试助手</title>
+    <link rel="stylesheet" href="/static/css/style.css">
+</head>
+<body>
+    <div class="container">
+        <header class="header">
+            <div class="logo">
+                <span class="logo-icon">👔</span>
+                <h1>面试官</h1>
+            </div>
+            <p class="tagline">AI驱动的智能面试助手，帮助你轻松应对面试</p>
+        </header>
+        
+        <main class="main-content">
+            <section class="feature-section">
+                <div class="feature-card" onclick="showFeature('resume')">
+                    <div class="feature-icon">📄</div>
+                    <h3>简历优化</h3>
+                    <p>AI分析简历，提供针对性优化建议，让你的简历脱颖而出</p>
+                </div>
+                
+                <div class="feature-card" onclick="showFeature('interview')">
+                    <div class="feature-icon">🎯</div>
+                    <h3>模拟面试</h3>
+                    <p>模拟真实面试场景，AI扮演面试官进行问答练习</p>
+                </div>
+                
+                <div class="feature-card" onclick="showFeature('feedback')">
+                    <div class="feature-icon">💡</div>
+                    <h3>反馈建议</h3>
+                    <p>实时评估回答质量，提供具体改进建议和参考范例</p>
+                </div>
+            </section>
+            
+            <section id="resume-section" class="tool-section" style="display: none;">
+                <div class="section-header">
+                    <h2>📄 简历优化助手</h2>
+                    <button class="back-btn" onclick="showFeature(null)">返回</button>
+                </div>
+                
+                <div class="input-group">
+                    <label for="target-position">目标岗位（选填）</label>
+                    <input type="text" id="target-position" placeholder="例如：产品经理、Java开发工程师">
+                </div>
+                
+                <div class="input-group">
+                    <label for="resume-content">简历内容</label>
+                    <textarea id="resume-content" rows="10" placeholder="请粘贴你的简历内容，或描述你的工作经验和技能..."></textarea>
+                </div>
+                
+                <button class="submit-btn" onclick="optimizeResume()">开始优化</button>
+                
+                <div id="resume-result" class="result-box" style="display: none;">
+                    <h3>优化建议</h3>
+                    <div id="resume-suggestions" class="suggestions-content"></div>
+                </div>
+            </section>
+            
+            <section id="interview-section" class="tool-section" style="display: none;">
+                <div class="section-header">
+                    <h2>🎯 模拟面试</h2>
+                    <button class="back-btn" onclick="showFeature(null)">返回</button>
+                </div>
+                
+                <div id="interview-setup" class="interview-setup">
+                    <div class="input-group">
+                        <label for="job-position">目标岗位</label>
+                        <input type="text" id="job-position" placeholder="例如：产品经理、数据分析师" required>
+                    </div>
+                    
+                    <div class="input-group">
+                        <label>难度级别</label>
+                        <div class="difficulty-options">
+                            <label class="radio-label">
+                                <input type="radio" name="difficulty" value="junior" checked>
+                                <span>初级</span>
+                            </label>
+                            <label class="radio-label">
+                                <input type="radio" name="difficulty" value="intermediate">
+                                <span>中级</span>
+                            </label>
+                            <label class="radio-label">
+                                <input type="radio" name="difficulty" value="senior">
+                                <span>高级</span>
+                            </label>
+                        </div>
+                    </div>
+                    
+                    <button class="submit-btn" onclick="startInterview()">开始面试</button>
+                </div>
+                
+                <div id="interview-active" class="interview-active" style="display: none;">
+                    <div class="interview-info">
+                        <span id="current-position"></span>
+                        <span id="current-phase" class="phase-badge"></span>
+                    </div>
+                    
+                    <div id="interview-messages" class="interview-messages"></div>
+                    
+                    <div class="interview-input-area">
+                        <textarea id="answer-input" rows="3" placeholder="请输入你的回答..."></textarea>
+                        <div class="input-actions">
+                            <button class="action-btn secondary" onclick="requestFeedback()">请求反馈</button>
+                            <button class="action-btn primary" onclick="submitAnswer()">提交回答</button>
+                        </div>
+                    </div>
+                    
+                    <div class="interview-controls">
+                        <button class="control-btn" onclick="endInterview()">结束面试</button>
+                    </div>
+                </div>
+                
+                <div id="interview-feedback" class="interview-feedback" style="display: none;">
+                    <h3>面试反馈</h3>
+                    <div id="feedback-content" class="feedback-content"></div>
+                    <button class="submit-btn" onclick="resetInterview()">重新开始</button>
+                </div>
+            </section>
+            
+            <section id="chat-section" class="tool-section" style="display: none;">
+                <div class="section-header">
+                    <h2>💬 求职问答</h2>
+                    <button class="back-btn" onclick="showFeature(null)">返回</button>
+                </div>
+                
+                <div class="chat-container">
+                    <div id="chat-messages" class="chat-messages"></div>
+                    
+                    <div class="chat-input-area">
+                        <input type="text" id="chat-input" placeholder="输入你的问题，例如：如何准备产品经理面试？">
+                        <button class="send-btn" onclick="sendChatMessage()">发送</button>
+                    </div>
+                </div>
+            </section>
+        </main>
+        
+        <footer class="footer">
+            <p>Powered by DeepSeek AI</p>
+        </footer>
+    </div>
+    
+    <div id="loading-overlay" class="loading-overlay" style="display: none;">
+        <div class="loading-spinner"></div>
+        <p>AI思考中，请稍候...</p>
+    </div>
+    
+    <script src="/static/js/main.js"></script>
+</body>
+</html>