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from flask import Flask, render_template, request, jsonify, session
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import json
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import requests
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import os
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from datetime import datetime
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app = Flask(__name__)
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app.secret_key = 'your-secret-key-here'
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# 大模型API配置
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LLM_CONFIG = {
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"deepseek": {
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"api_key": os.getenv("DEEPSEEK_API_KEY", "your-deepseek-api-key"),
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"base_url": "https://api.deepseek.com/v1"
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}
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}
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@app.route('/')
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def index():
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return render_template('index.html')
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@app.route('/ai')
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def ai():
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return render_template('ai.html')
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# 新增：大模型行程规划API
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@app.route('/api/generate_itinerary', methods=['POST'])
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def generate_itinerary():
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try:
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data = request.json
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user_input = {
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"destination": data.get('destination'),
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"days": data.get('days'),
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"trip_type": data.get('trip_type'),
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"travelers": data.get('travelers'),
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"budget": data.get('budget'),
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"special_needs": data.get('special_needs', '')
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}
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# 调用大模型生成行程
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itinerary = call_llm_for_itinerary(user_input)
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return jsonify({
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"success": True,
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"itinerary": itinerary,
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"title": f"{user_input['destination']}{user_input['days']}日{user_input['trip_type']}之旅"
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})
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except Exception as e:
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return jsonify({
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"success": False,
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"error": str(e)
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}), 500
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# 新增：语音对话API
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@app.route('/api/voice_chat', methods=['POST'])
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def voice_chat():
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try:
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data = request.json
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user_message = data.get('message')
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conversation_history = data.get('history', [])
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# 调用大模型进行对话
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response = call_llm_for_chat(user_message, conversation_history)
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return jsonify({
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"success": True,
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"response": response
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})
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except Exception as e:
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return jsonify({
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"success": False,
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"error": str(e)
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}), 500
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def call_llm_for_itinerary(user_input):
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"""调用大模型生成行程"""
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prompt = f"""
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作为专业的旅行规划专家，请为以下需求生成详细的旅行行程：
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目的地：{user_input['destination']}
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天数：{user_input['days']}天
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旅行类型：{user_input['trip_type']}
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人数：{user_input['travelers']}
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预算：{user_input['budget']}
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特殊需求：{user_input['special_needs']}
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请按以下格式回复：
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## 行程概览
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- 总天数：{user_input['days']}天
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- 主题特色：{user_input['trip_type']}
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## 每日详细安排
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**第1天**
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- 🕘 上午：[活动1] + [详细说明] + [时长]
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- 🕐 下午：[活动2] + [详细说明] + [时长]
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- 🕖 晚上：[活动3] + [详细说明] + [时长]
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- 🍽 餐饮推荐：[餐厅1] [特色] [预算]
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## 实用贴士
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- 交通建议
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- 注意事项
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- 省钱技巧
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请确保行程合理，考虑景点开放时间、交通距离、体力分配等因素。
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"""
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# 实际项目中调用大模型API
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# 这里先用模拟数据
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return generate_mock_itinerary(user_input)
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def call_llm_for_chat(message, history):
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"""调用大模型进行对话"""
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# 构建对话上下文
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messages = [
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{"role": "system", "content": "你是一个专业的旅行助手，帮助用户规划行程、推荐目的地、提供旅行建议。回复要友好、专业、简洁。"}
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]
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# 添加历史对话
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for msg in history[-6:]: # 只保留最近6轮对话
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messages.append(msg)
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# 添加当前消息
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messages.append({"role": "user", "content": message})
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# 实际项目中调用大模型API
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# 这里先用模拟回复
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return generate_mock_chat_response(message)
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def generate_mock_itinerary(user_input):
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"""生成模拟行程数据"""
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# 这里可以扩展更多目的地和行程类型
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base_itineraries = {
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'日本东京': [
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{
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'day': 1,
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'title': '抵达东京 - 浅草寺与东京塔',
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'schedule': [
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{'time': '上午', 'content': '抵达成田机场，乘坐成田特快到市区，办理酒店入住', 'duration': '09:00-12:00'},
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{'time': '中午', 'content': '浅草寺周边午餐，推荐尝试天妇罗或荞麦面', 'duration': '12:30-14:00'},
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{'time': '下午', 'content': '参观浅草寺，仲见世商店街购买纪念品', 'duration': '14:30-17:00'},
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{'time': '晚上', 'content': '登上东京塔，欣赏夜景并拍照', 'duration': '18:30-20:30'}
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]
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}
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]
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}
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destination = user_input['destination']
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days = int(user_input['days'])
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# 获取基础行程或默认行程
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itinerary = base_itineraries.get(destination, base_itineraries['日本东京'])
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# 补充不足的天数
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while len(itinerary) < days:
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day_index = len(itinerary) + 1
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itinerary.append({
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'day': day_index,
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'title': f'自由探索 - 深度体验{destination}',
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'schedule': [
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{'time': '上午', 'content': '根据兴趣自由安排，推荐前往当地小众景点', 'duration': '09:00-12:00'},
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{'time': '中午', 'content': '尝试当地特色美食，建议询问民宿老板推荐', 'duration': '12:30-14:00'},
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{'time': '下午', 'content': '休闲活动（如咖啡馆看书、河边散步）', 'duration': '14:30-17:00'}
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]
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})
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return itinerary[:days] # 只返回所需天数的行程
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def generate_mock_chat_response(message):
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"""生成模拟聊天回复"""
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responses = {
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'推荐': '根据您的喜好，我推荐以下几个目的地：\n\n1. **日本京都** - 适合文化体验，有丰富的寺庙和传统建筑\n2. **泰国清迈** - 适合美食和放松，物价相对较低\n3. **云南丽江** - 国内首选，自然风光和纳西文化都很棒',
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'预算': '预算规划建议：\n\n- **经济型** (¥3000以下)：选择青旅、当地交通、街边小吃\n- **舒适型** (¥3000-8000)：商务酒店、部分出租车、餐厅用餐\n- **豪华型** (¥8000以上)：星级酒店、包车、高端餐厅',
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'天气': '请告诉我具体的目的地和出行时间，我可以为您查询当地的天气情况和最佳旅行季节。',
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'签证': '签证信息因目的地而异：\n\n- **泰国**：落地签或提前办理\n- **日本**：需要提前办理签证\n- **欧洲**：申根签证，需要较长时间准备材料'
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}
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# 简单的关键词匹配
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for keyword, response in responses.items():
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if keyword in message:
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return response
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return '我主要专注于旅行规划相关的问题，比如目的地推荐、行程安排、预算规划、签证信息等。如果您有具体的旅行问题，我很乐意为您提供帮助！'
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if __name__ == '__main__':
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app.run(debug=True, port=5000)
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from flask import Flask, render_template, request, jsonify, session, redirect, url_for, flash
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import json
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import os
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import requests
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from datetime import datetime
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from config import Config
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app = Flask(__name__)
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app.config.from_object(Config)
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# 确保上传目录存在
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os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
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# 模拟用户数据（实际项目中使用数据库）
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users = {
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'test@example.com': {
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'password': '123456',
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'username': '测试用户',
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'avatar': 'https://picsum.photos/id/1005/200/200'
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}
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}
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# 主页路由
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@app.route('/')
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def index():
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return render_template('index.html')
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# 登录页路由
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@app.route('/login', methods=['GET', 'POST'])
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def login():
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if request.method == 'POST':
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email = request.form.get('email')
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password = request.form.get('password')
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user = users.get(email)
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if user and user['password'] == password:
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session['user'] = {
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'email': email,
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'username': user['username'],
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'avatar': user['avatar']
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}
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flash('登录成功！', 'success')
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return redirect(url_for('index'))
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else:
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flash('邮箱或密码错误', 'error')
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return render_template('login.html')
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# 注册页路由
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@app.route('/register', methods=['GET', 'POST'])
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def register():
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if request.method == 'POST':
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email = request.form.get('email')
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password = request.form.get('password')
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confirm_password = request.form.get('confirm_password')
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if password != confirm_password:
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flash('两次输入的密码不一致', 'error')
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elif email in users:
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flash('该邮箱已被注册', 'error')
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else:
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users[email] = {
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'password': password,
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'username': email.split('@')[0],
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'avatar': 'https://picsum.photos/id/1005/200/200'
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}
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flash('注册成功，请登录', 'success')
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return redirect(url_for('login'))
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return render_template('register.html')
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# 退出登录
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@app.route('/logout')
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def logout():
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session.pop('user', None)
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flash('已退出登录', 'info')
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return redirect(url_for('index'))
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# 个人中心
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@app.route('/profile')
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def profile():
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if 'user' not in session:
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flash('请先登录', 'error')
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return redirect(url_for('login'))
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return render_template('profile.html')
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# AI行程规划页
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@app.route('/ai')
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def ai():
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return render_template('ai.html')
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# 打卡页面
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@app.route('/checkin')
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def checkin():
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if 'user' not in session:
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flash('请先登录', 'error')
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return redirect(url_for('login'))
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return render_template('checkin.html')
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# 发表笔记页面
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@app.route('/postnote')
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def postnote():
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if 'user' not in session:
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flash('请先登录', 'error')
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return redirect(url_for('login'))
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return render_template('postnote.html')
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# API路由 - 生成行程
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@app.route('/api/generate_itinerary', methods=['POST'])
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def generate_itinerary():
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try:
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data = request.json
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user_input = {
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"destination": data.get('destination'),
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"days": data.get('days'),
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"trip_type": data.get('trip_type'),
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"travelers": data.get('travelers'),
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"budget": data.get('budget'),
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"special_needs": data.get('special_needs', '')
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}
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# 调用大模型生成行程
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itinerary = call_llm_for_itinerary(user_input)
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return jsonify({
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"success": True,
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"itinerary": itinerary,
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"title": f"{user_input['destination']}{user_input['days']}日{user_input['trip_type']}之旅"
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})
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except Exception as e:
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return jsonify({
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"success": False,
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"error": str(e)
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}), 500
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# API路由 - AI对话
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@app.route('/api/ai_chat', methods=['POST'])
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def ai_chat():
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try:
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data = request.json
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user_message = data.get('message')
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# 调用大模型进行对话
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response = call_llm_for_chat(user_message)
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return jsonify({
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"success": True,
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"response": response
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})
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except Exception as e:
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return jsonify({
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"success": False,
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"error": str(e)
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}), 500
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# 大模型调用函数
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def call_llm_for_itinerary(user_input):
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"""调用大模型生成行程"""
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# 这里使用模拟数据，实际项目中调用真实API
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return generate_mock_itinerary(user_input)
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def call_llm_for_chat(message):
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"""调用大模型进行对话"""
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# 这里使用模拟回复，实际项目中调用真实API
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return generate_mock_chat_response(message)
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def generate_mock_itinerary(user_input):
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"""生成模拟行程数据"""
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destination = user_input['destination']
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days = int(user_input['days'])
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base_itineraries = {
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'日本东京': [
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{
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'day': 1,
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'title': '抵达东京 - 浅草寺与东京塔',
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'schedule': [
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{'time': '上午', 'content': '抵达成田机场，乘坐成田特快到市区，办理酒店入住', 'duration': '09:00-12:00'},
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{'time': '中午', 'content': '浅草寺周边午餐，推荐尝试天妇罗或荞麦面', 'duration': '12:30-14:00'},
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{'time': '下午', 'content': '参观浅草寺，仲见世商店街购买纪念品', 'duration': '14:30-17:00'},
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{'time': '晚上', 'content': '登上东京塔，欣赏夜景并拍照', 'duration': '18:30-20:30'}
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]
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},
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{
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'day': 2,
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'title': '上野公园 - 秋叶原动漫体验',
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'schedule': [
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{'time': '上午', 'content': '上野公园散步，参观东京国立博物馆', 'duration': '09:30-12:30'},
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{'time': '中午', 'content': '上野公园周边鳗鱼饭午餐', 'duration': '13:00-14:30'},
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{'time': '下午', 'content': '秋叶原电器街体验动漫文化，逛免税店', 'duration': '15:00-18:00'}
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]
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}
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],
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'云南丽江': [
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{
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'day': 1,
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'title': '抵达丽江 - 古城初体验',
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'schedule': [
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{'time': '上午', 'content': '抵达丽江三义机场，乘车到古城，办理民宿入住', 'duration': '09:00-12:00'},
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{'time': '中午', 'content': '古城内尝试纳西族特色菜（腊排骨火锅）', 'duration': '12:30-14:00'},
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{'time': '下午', 'content': '丽江古城石板路漫步，参观四方街、大水车', 'duration': '14:30-17:30'},
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{'time': '晚上', 'content': '古城酒吧街体验民谣演出', 'duration': '19:00-21:00'}
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]
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}
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]
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}
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# 获取基础行程或默认行程
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itinerary = base_itineraries.get(destination, base_itineraries['日本东京'])
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# 补充不足的天数
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while len(itinerary) < days:
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day_index = len(itinerary) + 1
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itinerary.append({
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'day': day_index,
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'title': f'自由探索 - 深度体验{destination}',
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'schedule': [
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{'time': '上午', 'content': '根据兴趣自由安排，推荐前往当地小众景点', 'duration': '09:00-12:00'},
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{'time': '中午', 'content': '尝试当地特色美食，建议询问民宿老板推荐', 'duration': '12:30-14:00'},
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{'time': '下午', 'content': '休闲活动（如咖啡馆看书、河边散步）', 'duration': '14:30-17:00'}
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]
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})
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return itinerary[:days]
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def generate_mock_chat_response(message):
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"""生成模拟聊天回复"""
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responses = {
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'推荐': '根据您的喜好，我推荐以下几个目的地：\n\n1. **日本京都** - 适合文化体验，有丰富的寺庙和传统建筑\n2. **泰国清迈** - 适合美食和放松，物价相对较低\n3. **云南丽江** - 国内首选，自然风光和纳西文化都很棒',
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'预算': '预算规划建议：\n\n- **经济型** (¥3000以下)：选择青旅、当地交通、街边小吃\n- **舒适型** (¥3000-8000)：商务酒店、部分出租车、餐厅用餐\n- **豪华型** (¥8000以上)：星级酒店、包车、高端餐厅',
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'天气': '请告诉我具体的目的地和出行时间，我可以为您查询当地的天气情况和最佳旅行季节。',
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'签证': '签证信息因目的地而异：\n\n- **泰国**：落地签或提前办理\n- **日本**：需要提前办理签证\n- **欧洲**：申根签证，需要较长时间准备材料'
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}
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# 简单的关键词匹配
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for keyword, response in responses.items():
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if keyword in message:
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return response
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return '我主要专注于旅行规划相关的问题，比如目的地推荐、行程安排、预算规划、签证信息等。如果您有具体的旅行问题，我很乐意为您提供帮助！'
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if __name__ == '__main__':
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app.run(debug=True, host='0.0.0.0', port=5000)
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