# app.py
import os
import threading
from functools import wraps
import google.generativeai as genai
from flask import Flask, request, jsonify, send_from_directory
from flask_cors import CORS
from dotenv import load_dotenv
import chromadb

# 从您的核心逻辑文件中导入类
from app_chromadb import MarkdownKnowledgeBase

# --- 初始化与配置 ---
load_dotenv()
app = Flask(__name__, static_folder='.', static_url_path='')
CORS(app)

# --- API 密钥认证配置 ---
VALID_API_KEYS_STR = os.environ.get("KNOWLEDGE_BASE_API_KEYS", "")
VALID_API_KEYS = {key.strip() for key in VALID_API_KEYS_STR.split(',') if key.strip()}
if not VALID_API_KEYS:
    print("⚠️ 警告: 未配置 KNOWLEDGE_BASE_API_KEYS。API 将对所有人开放！")

# --- ChromaDB, Gemini, SiliconFlow 实例配置 ---
try:
    CHROMA_DATA_PATH = os.path.join(os.path.dirname(os.path.realpath(__file__)), "chroma_db")
    COLLECTION_NAME = "markdown_knowledge_base_m3"
    chroma_client = chromadb.PersistentClient(path=CHROMA_DATA_PATH)
    collection = chroma_client.get_or_create_collection(name=COLLECTION_NAME)
    print(f"✅ ChromaDB 客户端已连接，数据存储在 '{CHROMA_DATA_PATH}'")
except Exception as e:
    chroma_client = None
    collection = None
    print(f"❌ 初始化 ChromaDB 失败: {e}")

try:
    GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
    genai.configure(api_key=GEMINI_API_KEY)
    gemini_model = genai.GenerativeModel('gemini-1.5-flash')
    print("✅ Gemini API 已配置。")
except Exception as e:
    gemini_model = None
    print(f"❌ Gemini API 配置失败: {e}")

try:
    SF_API_TOKEN = os.environ.get("SILICONFLOW_API_TOKEN")
    kb_instance = MarkdownKnowledgeBase(api_token=SF_API_TOKEN, chroma_collection=collection)
    print("✅ SiliconFlow 与知识库实例已配置。")
except Exception as e:
    kb_instance = None
    print(f"❌ 知识库实例配置失败: {e}")

kb_status = { "is_building": False }

# --- API 密钥认证装饰器 ---
def require_api_key(f):
    @wraps(f)
    def decorated_function(*args, **kwargs):
        if not VALID_API_KEYS: return f(*args, **kwargs)
        api_key = request.headers.get('X-API-Key')
        if api_key and api_key in VALID_API_KEYS:
            return f(*args, **kwargs)
        else:
            return jsonify({"error": "授权失败。请提供有效'X-API-Key'请求头。"}), 403
    return decorated_function

# --- 前端页面路由 ---
@app.route('/')
def serve_index():
    return send_from_directory('.', 'index.html')

# --- API 端点 ---
@app.route('/status', methods=['GET'])
def get_status():
    if collection:
        kb_status['total_items'] = collection.count()
        kb_status['is_built'] = kb_status['total_items'] > 0
        if not kb_status['is_building']:
             kb_status['message'] = f"知识库已就绪，共有 {kb_status['total_items']} 个条目。"
    else:
        kb_status['message'] = "ChromaDB 未连接。"
    return jsonify(kb_status)

@app.route('/build', methods=['POST'])
@require_api_key
def build_knowledge_base():
    if kb_status['is_building']:
        return jsonify({"error": "知识库已在构建中，请稍后。"}), 409
    
    if not kb_instance:
        return jsonify({"error": "知识库实例未初始化，无法构建。"}), 500
        
    data = request.get_json()
    clear_existing = data.get('clear_existing', False)
    
    build_params = {
        'folder_path': data.get('folder_path'),
        'chunk_size': data.get('chunk_size', 4096),
        'overlap': data.get('overlap', 400),
        'max_files': data.get('max_files', 500),
        'sample_mode': data.get('sample_mode', 'largest')
    }
    
    def build_in_background():
        global kb_status, collection
        kb_status['is_building'] = True
        kb_status['message'] = "构建任务开始..."
        try:
            if clear_existing and chroma_client:
                print(f"正在清空现有集合: {COLLECTION_NAME}")
                chroma_client.delete_collection(name=COLLECTION_NAME)
                collection = chroma_client.get_or_create_collection(name=COLLECTION_NAME)
                kb_instance.collection = collection
                print("集合已清空并重建。")

            kb_instance.build_knowledge_base(**build_params)
            kb_status['message'] = f"构建完成！知识库现有 {collection.count()} 个条目。"
        except Exception as e:
            kb_status['message'] = f"构建时出错: {e}"
            print(f"Error during build: {e}")
        finally:
            kb_status['is_building'] = False

    thread = threading.Thread(target=build_in_background)
    thread.start()
    return jsonify({"message": "知识库构建任务已在后台启动。"}), 202

@app.route('/search', methods=['GET'])
@require_api_key
def search_in_kb():
    if not (collection and collection.count() > 0):
        return jsonify({"error": "知识库为空，请先构建。"}), 400

    if not kb_instance:
        return jsonify({"error": "知识库实例未初始化，无法搜索。"}), 500

    query = request.args.get('query')
    top_k = request.args.get('top_k', default=5, type=int)
    
    if not query:
        return jsonify({"error": "必须提供 'query' 参数"}), 400

    try:
        results = kb_instance.search(query, top_k=top_k)
        return jsonify(results)
    except Exception as e:
        return jsonify({"error": f"搜索时发生错误: {e}"}), 500

@app.route('/summarize', methods=['POST'])
@require_api_key
def summarize_results():
    if not gemini_model:
        return jsonify({"error": "Gemini API 未配置或初始化失败。"}), 500
    
    data = request.get_json()
    query = data.get('query')
    search_results = data.get('results')

    if not query or not search_results:
        return jsonify({"error": "必须提供查询和搜索结果。"}), 400

    context = "\n\n---\n\n".join([item['content'] for item in search_results])
    prompt = f"""
    根据以下本地知识库中搜索到的内容，请用清晰、简洁的中文直接回答用户的问题。
    如果内容不足以回答，请说明现有信息无法直接回答。

    用户问题: "{query}"

    搜索到的内容:
    ---
    {context}
    ---

    你的回答:
    """

    try:
        print(f"正在向 Gemini 模型 '{gemini_model.model_name}' 发送请求...")
        response = gemini_model.generate_content(prompt)
        summary = response.text
        return jsonify({"summary": summary})
    except Exception as e:
        print(f"调用 Gemini API 时出错: {e}")
        return jsonify({"error": f"调用 AI 服务时出错: {e}"}), 500


if __name__ == '__main__':
    print("知识库后端服务 (最终版) 启动...")
    print("✅ 服务已启动！请在浏览器中打开 http://127.0.0.1:5000")
    # 使用生产级服务器时应移除 debug=False
    app.run(host='0.0.0.0', port=5000, debug=False)