app.py

import os
import json
import sqlite3
import random
import time
import requests
from datetime import datetime
from flask import Flask, render_template, request, jsonify, send_from_directory
from werkzeug.utils import secure_filename

app = Flask(__name__)
app.config['SECRET_KEY'] = 'forest-sentry-secret-key-2026'
app.config['MAX_CONTENT_LENGTH'] = 100 * 1024 * 1024  # 100MB max upload
app.config['UPLOAD_FOLDER'] = os.path.join(app.instance_path, 'uploads')

# Ensure directories exist
os.makedirs(app.instance_path, exist_ok=True)
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)

DB_PATH = os.path.join(app.instance_path, "forest_sentry.db")
SILICONFLOW_API_KEY = "sk-vimuseiptfbomzegyuvmebjzooncsqbyjtlddrfodzcdskgi"

# --- Database ---
def get_db_connection():
    conn = sqlite3.connect(DB_PATH)
    conn.row_factory = sqlite3.Row
    return conn

def init_db():
    with get_db_connection() as conn:
        conn.execute('''
            CREATE TABLE IF NOT EXISTS plots (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                name TEXT NOT NULL,
                location TEXT,
                type TEXT,
                carbon_stock REAL,
                fire_risk INTEGER,
                health_score INTEGER,
                last_scan TEXT,
                status TEXT
            )
        ''')
        conn.execute('''
            CREATE TABLE IF NOT EXISTS logs (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                timestamp TEXT,
                action TEXT,
                details TEXT
            )
        ''')
        
        # Check if empty, add demo data
        cur = conn.execute('SELECT count(*) FROM plots')
        if cur.fetchone()[0] == 0:
            seed_data(conn)
    print("数据库初始化完成 (Database initialized).")

def seed_data(conn):
    plots = [
        ("阿尔法林区 (Alpha)", "45.12, 122.34", "针叶林", 1250.5, 15, 92, datetime.now().strftime("%Y-%m-%d %H:%M"), "正常"),
        ("贝塔山脊 (Beta)", "45.15, 122.38", "混合林", 890.2, 45, 78, datetime.now().strftime("%Y-%m-%d %H:%M"), "警告"),
        ("伽马谷地 (Gamma)", "45.10, 122.30", "阔叶林", 1500.0, 5, 98, datetime.now().strftime("%Y-%m-%d %H:%M"), "正常"),
        ("德尔塔荒地 (Delta)", "45.18, 122.40", "灌木丛", 300.5, 85, 45, datetime.now().strftime("%Y-%m-%d %H:%M"), "危急"),
    ]
    conn.executemany('INSERT INTO plots (name, location, type, carbon_stock, fire_risk, health_score, last_scan, status) VALUES (?, ?, ?, ?, ?, ?, ?, ?)', plots)
    conn.commit()

# --- AI Service ---
def call_ai_reasoning(context_data, prompt_type="analyze"):
    if not SILICONFLOW_API_KEY:
        return {"error": "No API Key"}
    
    headers = {
        "Authorization": f"Bearer {SILICONFLOW_API_KEY}",
        "Content-Type": "application/json"
    }
    
    system_prompt = """你是一个“森林哨兵”AI，是林业、生态和野火预防方面的专家。
    你分析传感器数据并提供可操作的见解。
    输出必须仅为有效的 JSON，JSON 块之外不得有 markdown 格式。
    请使用中文回复。"""
    
    user_content = ""
    if prompt_type == "analyze":
        user_content = f"""分析此林地数据: {json.dumps(context_data, ensure_ascii=False)}。
        评估火灾风险 (0-100)，碳汇潜力，并建议 3 个具体行动。
        返回 JSON: {{ "risk_analysis": "string", "carbon_insight": "string", "actions": ["string", "string", "string"], "alert_level": "正常/警告/危急" }}"""
    elif prompt_type == "plan":
        user_content = f"""为以下情况创建无人机任务计划: {json.dumps(context_data, ensure_ascii=False)}。
        返回 JSON: {{ "mission_name": "string", "waypoints": ["lat,lon", ...], "estimated_time": "string", "priority": "string" }}"""

    payload = {
        "model": "Qwen/Qwen2.5-7B-Instruct",
        "messages": [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_content}
        ],
        "response_format": {"type": "json_object"}
    }
    
    try:
        # Mock Fallback for speed/reliability if needed, but we try API first
        response = requests.post("https://api.siliconflow.cn/v1/chat/completions", headers=headers, json=payload, timeout=10)
        if response.status_code == 200:
            res_json = response.json()
            content = res_json['choices'][0]['message']['content']
            # Clean potential markdown
            if "```json" in content:
                content = content.split("```json")[1].split("```")[0]
            elif "```" in content:
                content = content.split("```")[1].split("```")[0]
            return json.loads(content)
        else:
            print(f"AI Error: {response.text}")
            raise Exception("API Error")
    except Exception as e:
        print(f"Fallback AI due to: {e}")
        # Fallback Mock
        if prompt_type == "analyze":
            return {
                "risk_analysis": "AI 服务连接超时。基于启发式规则：检测到高温和低湿度，建议加强巡逻。",
                "carbon_insight": "预估生长稳定，碳汇潜力中等。",
                "actions": ["人工巡逻", "检查传感器状态", "更新卫星图像"],
                "alert_level": "警告"
            }
        return {"mission_name": "紧急扫描任务", "waypoints": ["45.12, 122.35", "45.13, 122.36"], "estimated_time": "15分钟", "priority": "高"}

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

@app.route('/api/plots', methods=['GET'])
def get_plots():
    with get_db_connection() as conn:
        plots = conn.execute('SELECT * FROM plots').fetchall()
        return jsonify([dict(row) for row in plots])

@app.route('/api/analyze', methods=['POST'])
def analyze_plot():
    data = request.json
    if not data:
        return jsonify({"error": "No data"}), 400
    
    # Simulate reading real-time sensors
    sensor_data = {
        "temp": random.uniform(15, 35),
        "humidity": random.uniform(20, 80),
        "wind_speed": random.uniform(0, 15),
        "soil_moisture": random.uniform(10, 60),
        "plot_info": data
    }
    
    # AI Reasoning
    analysis = call_ai_reasoning(sensor_data, "analyze")
    
    # Update DB with new risk if critical
    with get_db_connection() as conn:
        if analysis.get('alert_level') in ['警告', '危急', 'High', 'Critical']:
             # Map English levels to Chinese if AI returns English
            level = analysis['alert_level']
            if level == 'High': level = '警告'
            if level == 'Critical': level = '危急'
            
            conn.execute('UPDATE plots SET status = ?, fire_risk = ? WHERE id = ?', 
                         (level, random.randint(70, 95), data['id']))
            conn.commit()
            
    return jsonify({"sensors": sensor_data, "analysis": analysis})

@app.route('/api/action', methods=['POST'])
def take_action():
    data = request.json
    action_type = data.get('type')
    plot_id = data.get('plot_id')
    
    # Tool Execution Simulation
    result = {"status": "success", "message": "行动已完成"}
    
    if action_type == 'drone_scan':
        # Simulate mission planning
        plan = call_ai_reasoning({"plot_id": plot_id, "action": "drone_scan"}, "plan")
        result["data"] = plan
        result["message"] = f"无人机已派遣: {plan.get('mission_name', '扫描任务')}"
        
        # Update Last Scan
        with get_db_connection() as conn:
            conn.execute('UPDATE plots SET last_scan = ? WHERE id = ?', 
                         (datetime.now().strftime("%Y-%m-%d %H:%M"), plot_id))
            conn.commit()
            
    elif action_type == 'alert_rangers':
        result["message"] = "已通过短信/无线电通知阿尔法护林队。"
    
    return jsonify(result)

@app.route('/api/upload', methods=['POST'])
def upload_file():
    if 'file' not in request.files:
        return jsonify({"error": "No file part"}), 400
    file = request.files['file']
    if file.filename == '':
        return jsonify({"error": "No selected file"}), 400
    
    if file:
        filename = secure_filename(file.filename)
        # Mock saving to dataset if it's large, or just save locally
        file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
        file.save(file_path)
        return jsonify({"status": "success", "message": f"文件 {filename} 上传成功", "path": file_path})

@app.route('/api/reset', methods=['POST'])
def reset_db():
    try:
        if os.path.exists(DB_PATH):
            os.remove(DB_PATH)
        init_db()
        return jsonify({"status": "success", "message": "数据库已重置"})
    except Exception as e:
        return jsonify({"error": str(e)}), 500

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