#!/usr/bin/env python3

"""
AI Review Service

基于 DeepSeek + RAG 的 AI 内容审核微服务。
接收纯文本字符串，返回结构化审核结果。
"""

from flask import Flask, request, jsonify
from flask_cors import CORS
from waitress import serve
from dotenv import load_dotenv
import hashlib
import os
import sys

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
load_dotenv(os.path.join(os.path.dirname(os.path.abspath(__file__)), ".env"))

from agent.review_agent import ReviewAgent

app = Flask(__name__)
CORS(app)

review_agent = ReviewAgent()


@app.route('/review', methods=['POST'])
def review():
    """
    审核接口
    Request:  {"content": "待审核的字符串"}
    Response: {"invalid": "true"}  或  {"invalid": "false"}
    """
    data = request.get_json()

    if not data or 'content' not in data:
        return jsonify({"error": "content is required"}), 400

    content = data.get('content', '').strip()

    if not content:
        return jsonify({"error": "content cannot be empty"}), 400

    result = review_agent.review(content)
    return jsonify(result), 200


@app.route('/rag/feedback', methods=['POST'])
def rag_feedback():
    """
    人工纠偏反馈接口 —— AI 审核结果与人工判断不一致时调用。

    Request:  {"content": "被误判的文本", "correct_type": "violation"}
    correct_type: "violation" — AI 漏判了（AI 通过但实际违规）
                  "safe"      — AI 误杀了（AI 拦截但实际安全）

    Response: {"added": true, "id": "v_xxx", "md5": "xxx"}
              {"added": false, "reason": "duplicate"}
    """
    data = request.get_json()

    if not data or 'content' not in data:
        return jsonify({"error": "content is required"}), 400

    content = data.get('content', '').strip()
    correct_type = data.get('correct_type', 'violation').strip()

    if not content:
        return jsonify({"error": "content cannot be empty"}), 400

    if correct_type not in ("violation", "safe"):
        return jsonify({"error": "correct_type must be 'violation' or 'safe'"}), 400

    md5_hash = hashlib.md5(content.encode("utf-8")).hexdigest()
    entry_id = f"{correct_type[:1]}_{md5_hash[:12]}"
    category = "human_feedback"

    added = review_agent.rag.add_example(entry_id, content, correct_type, category)

    return jsonify({
        "added": added,
        "id": entry_id if added else None,
        "md5": md5_hash,
        "reason": None if added else "duplicate",
    }), 200


@app.route('/health', methods=['GET'])
def health():
    return jsonify({"status": "ok"}), 200


@app.route('/rag/list', methods=['GET'])
def rag_list():
    """返回 RAG 库中所有条目。"""
    entries = review_agent.rag.list_all()
    return jsonify({"total": len(entries), "entries": entries}), 200


ADDR = os.getenv("AI_REVIEW_HOST", "127.0.0.1")
PORT = int(os.getenv("AI_REVIEW_PORT", "8007"))

if __name__ == "__main__":
    print(f'AI Review Service listening at http://{ADDR}:{PORT}')
    serve(app, host=ADDR, port=PORT)