app.py

import os
import json
import random
import time
import requests
from flask import Flask, render_template, request, jsonify, send_from_directory
from flask_cors import CORS
from werkzeug.utils import secure_filename

app = Flask(__name__)
CORS(app)

# Configuration
app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB
app.config['JSON_AS_ASCII'] = False
app.config['UPLOAD_FOLDER'] = 'uploads'

# Ensure upload folder exists
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)

# API Key Configuration
# In production, use environment variables: os.environ.get("SILICONFLOW_API_KEY")
SILICONFLOW_API_KEY = os.environ.get("SILICONFLOW_API_KEY", "sk-vimuseiptfbomzegyuvmebjzooncsqbyjtlddrfodzcdskgi")
SILICONFLOW_API_URL = "https://api.siliconflow.cn/v1/chat/completions"

# Global context to store uploaded data or latest traffic state
traffic_context = {}

# Mock Data Generator
def generate_traffic_data():
    """Generate mock traffic data for the dashboard (Chinese)."""
    districts = ["市中心", "北区", "科技园", "港口区", "西区"]
    data = {
        "timestamp": time.strftime("%H:%M:%S"),
        "congestion_index": round(random.uniform(1.0, 9.9), 1),
        "avg_speed": round(random.uniform(15, 60), 1),
        "active_incidents": random.randint(0, 5),
        "district_status": []
    }
    
    for district in districts:
        status_map = {
            "Smooth": "畅通",
            "Moderate": "缓行",
            "Congested": "拥堵",
            "Heavy Congestion": "严重拥堵"
        }
        raw_status = random.choice(list(status_map.keys()))
        data["district_status"].append({
            "name": district,
            "flow": random.randint(500, 3000), # vehicles per hour
            "status": raw_status,
            "status_cn": status_map[raw_status]
        })
    
    # Update global context
    global traffic_context
    traffic_context = data
    return data

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/api/traffic-data', methods=['GET'])
def get_traffic_data():
    return jsonify(generate_traffic_data())

@app.route('/api/upload', methods=['POST'])
def upload_file():
    if 'file' not in request.files:
        return jsonify({"error": "没有文件部分"}), 400
    file = request.files['file']
    if file.filename == '':
        return jsonify({"error": "未选择文件"}), 400
    
    if file:
        filename = secure_filename(file.filename)
        filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
        try:
            file.save(filepath)
        except Exception as e:
            return jsonify({"error": f"保存文件失败: {str(e)}"}), 500
        
        # Simple processing logic
        msg = f"文件 {filename} 上传成功。"
        if filename.lower().endswith('.json'):
            try:
                with open(filepath, 'r', encoding='utf-8') as f:
                    data = json.load(f)
                    # Try to merge into context if structure matches
                    if 'congestion_index' in data:
                        global traffic_context
                        traffic_context.update(data)
                        msg += " 交通数据已更新。"
            except Exception as e:
                msg += f" 但解析JSON失败: {str(e)}"
                
        return jsonify({"message": msg, "filename": filename})

@app.route('/api/chat', methods=['POST'])
def chat():
    data = request.json
    user_message = data.get('message', '')
    # Use global context if available, else client provided context
    context_data = traffic_context if traffic_context else data.get('context', {})
    
    if not user_message:
        return jsonify({"error": "No message provided"}), 400

    # System Prompt with Context (Chinese)
    system_prompt = f"""你是一个名为'Urban Flow'的智慧城市交通管理AI专家。
    当前交通状况:
    - 拥堵指数: {context_data.get('congestion_index', 'N/A')}
    - 平均车速: {context_data.get('avg_speed', 'N/A')} km/h
    - 活跃事件: {context_data.get('active_incidents', 'N/A')}
    
    你的角色是分析交通状况，提出信号优化策略和出行建议。
    请保持专业、简洁，并用数据说话。使用Markdown格式回复。
    如果被问及'优化信号灯'，请提出具体的调整建议（例如：'建议将市中心主干道的绿灯时间延长15秒'）。
    """

    payload = {
        "model": "Qwen/Qwen2.5-7B-Instruct",
        "messages": [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_message}
        ],
        "temperature": 0.7,
        "max_tokens": 512
    }

    headers = {
        "Authorization": f"Bearer {SILICONFLOW_API_KEY}",
        "Content-Type": "application/json"
    }

    try:
        # Mock Mode Fallback logic (Network resilience)
        try:
            response = requests.post(SILICONFLOW_API_URL, json=payload, headers=headers, timeout=5)
            response.raise_for_status()
            ai_response = response.json()['choices'][0]['message']['content']
        except Exception as e:
            print(f"API Error: {e}. Switching to Mock Mode.")
            # Fallback Mock Response
            time.sleep(1) # Simulate delay
            ai_response = f"""**[模拟模式已激活]** 网络连接不可用。
            
            根据当前拥堵指数 **{context_data.get('congestion_index', 'N/A')}**，我的分析如下：
            
            1. **信号优化**: 建议延长 **市中心** 区域绿灯时长 20%。
            2. **路线建议**: 建议重型货车绕行外环路。
            3. **事件响应**: 派遣无人机巡查西区路口。
            
            *注意: 请检查网络连接和API密钥以获取实时AI分析。*"""

        return jsonify({"response": ai_response})

    except Exception as e:
        return jsonify({"error": str(e)}), 500

@app.errorhandler(413)
def request_entity_too_large(error):
    return jsonify({"error": "文件太大，超过限制 (16MB)"}), 413

@app.errorhandler(404)
def page_not_found(e):
    return jsonify({"error": "未找到该资源 (404)"}), 404

@app.errorhandler(500)
def internal_server_error(e):
    return jsonify({"error": "服务器内部错误 (500)"}), 500

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=True)