#!/usr/bin/env python3
"""
飞书图片预处理守护进程 (image_daemon.py) v3 — WebSocket 事件驱动
通过 lark-oapi SDK 的 WebSocket 长连接实时接收消息事件，
检测图片消息后下载、上传到图床、回复 URL。
"""
import os, sys, json, time, requests, threading, base64

FEISHU_BASE = "https://open.feishu.cn/open-apis"
APP_ID = os.environ.get("FEISHU_APP_ID", "")
APP_SECRET = os.environ.get("FEISHU_APP_SECRET", "")

# LLM 配置
API_BASE_URL = os.environ.get("API_BASE_URL", "https://asem12345-cliproxyapi.hf.space/v1")
API_KEY = os.environ.get("API_KEY", "")
MODEL_NAME = os.environ.get("MODEL_NAME", "gemini-3-flash")
BRAVE_API_KEY = os.environ.get("BRAVE_API_KEY", "")

# OpenClaw Gateway (本地)
OPENCLAW_GATEWAY = "http://127.0.0.1:18789/v1"
_use_gateway = False  # 启动时探测决定
_soul_prompt = ""     # SOUL.md 内容

# 对话历史 (per chat_id)
_chat_history = {}    # {chat_id: [{role, content}, ...]}
MAX_HISTORY = 30      # 保留最近 N 轮

# 待处理图片 (per chat_id)  —— 用户发图后先问需求再分析
_pending_images = {}  # {chat_id: base64_string}

# ---------- 日志 ----------
def log(msg):
    ts = time.strftime("%H:%M:%S")
    print(f"[image_daemon {ts}] {msg}", flush=True)

# ---------- Token 管理 ----------
_token = None
_token_time = 0
_token_lock = threading.Lock()

def get_token():
    """获取 tenant_access_token，30分钟自动刷新"""
    global _token, _token_time
    with _token_lock:
        if _token and time.time() - _token_time < 1800:
            return _token
        try:
            resp = requests.post(f"{FEISHU_BASE}/auth/v3/tenant_access_token/internal",
                json={"app_id": APP_ID, "app_secret": APP_SECRET}, timeout=10)
            data = resp.json()
            if data.get("code") == 0:
                _token = data["tenant_access_token"]
                _token_time = time.time()
                log("🔑 Token 已刷新")
                return _token
            log(f"❌ Token 获取失败: {data}")
        except Exception as e:
            log(f"❌ Token 异常: {e}")
    return _token  # 返回旧的，总比没有好

# ---------- 图片下载 ----------
def download_image(token, message_id, file_key):
    """通过消息资源 API 下载用户发送的图片"""
    headers = {"Authorization": f"Bearer {token}"}
    url = f"{FEISHU_BASE}/im/v1/messages/{message_id}/resources/{file_key}"
    log(f"📥 API: GET {url}?type=image")
    resp = requests.get(url, headers=headers, params={"type": "image"}, timeout=30)
    if resp.status_code == 200 and len(resp.content) > 100:
        log(f"✅ 下载成功: {len(resp.content)} bytes")
        return resp.content
    log(f"❌ 下载图片失败 {file_key}: HTTP {resp.status_code}, {resp.text[:200]}")
    return None

# ---------- 图片上传（多重 fallback） ----------
def upload_image(data):
    """上传图片到图床，多重 fallback"""
    # 1. tmpfiles.org
    try:
        resp = requests.post("https://tmpfiles.org/api/v1/upload",
            files={"file": ("img.jpg", data, "image/jpeg")}, timeout=30)
        if resp.status_code == 200:
            url = resp.json().get("data", {}).get("url", "")
            if url:
                result = url.replace("tmpfiles.org/", "tmpfiles.org/dl/")
                log(f"📤 tmpfiles 成功")
                return result
        log(f"⚠️ tmpfiles 失败: HTTP {resp.status_code}")
    except Exception as e:
        log(f"⚠️ tmpfiles 异常: {e}")

    # 2. Telegraph
    try:
        resp = requests.post("https://telegra.ph/upload",
            files={"file": ("img.jpg", data, "image/jpeg")}, timeout=30)
        if resp.status_code == 200:
            result = resp.json()
            if isinstance(result, list) and len(result) > 0:
                src = result[0].get("src", "")
                if src:
                    url = f"https://telegra.ph{src}"
                    log(f"📤 telegraph 成功")
                    return url
        log(f"⚠️ telegraph 失败: HTTP {resp.status_code}")
    except Exception as e:
        log(f"⚠️ telegraph 异常: {e}")

    # 3. file.io
    try:
        resp = requests.post("https://file.io",
            files={"file": ("img.jpg", data, "image/jpeg")}, timeout=30)
        if resp.status_code == 200:
            url = resp.json().get("link", "")
            if url:
                log(f"📤 file.io 成功")
                return url
        log(f"⚠️ file.io 失败: HTTP {resp.status_code}")
    except Exception as e:
        log(f"⚠️ file.io 异常: {e}")

    # 4. catbox.moe
    try:
        resp = requests.post("https://catbox.moe/user/api.php",
            data={"reqtype": "fileupload"},
            files={"filedata": ("img.jpg", data, "image/jpeg")}, timeout=30)
        if resp.status_code == 200 and resp.text.startswith("http"):
            log(f"📤 catbox 成功")
            return resp.text.strip()
        log(f"⚠️ catbox 失败: HTTP {resp.status_code}")
    except Exception as e:
        log(f"⚠️ catbox 异常: {e}")

    # 5. 0x0.st
    try:
        resp = requests.post("https://0x0.st",
            files={"file": ("img.jpg", data, "image/jpeg")}, timeout=30)
        if resp.status_code == 200 and resp.text.startswith("http"):
            log(f"📤 0x0 成功")
            return resp.text.strip()
        log(f"⚠️ 0x0 失败: HTTP {resp.status_code}")
    except Exception as e:
        log(f"⚠️ 0x0 异常: {e}")

    return None

# ---------- 发送消息 (直接发到 Chat) ----------
def send_text(token, chat_id, text):
    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json; charset=utf-8"
    }
    # 使用 post 消息类型可以支持富文本，这里先用 text 简单点，但直接发到 chat_id
    resp = requests.post(f"{FEISHU_BASE}/im/v1/messages",
        headers=headers,
        params={"receive_id_type": "chat_id"},
        json={
            "receive_id": chat_id,
            "content": json.dumps({"text": text}),
            "msg_type": "text"
        }, timeout=10)
    data = resp.json()
    code = data.get("code", -1)
    if code != 0:
        log(f"❌ 发送消息失败 (code={code}): {data.get('msg', '')}")
    return data

# ---------- Vision 图片分析 ----------
def analyze_image_with_vision(img_data):
    """将图片 base64 传给 LLM，由大师以人行佛教视角描述"""
    if not API_KEY:
        return None
    try:
        b64 = base64.b64encode(img_data).decode("utf-8")
        soul = _soul_prompt or "You are a helpful assistant."
        prompt = (
            "这位信徒发来了一张图片，请以你的风格阅览这张图片，它占据了你的视野。"
            "简要阐述你的感悟，200字以内，不必报平就班。"
        )
        payload = {
            "model": MODEL_NAME,
            "messages": [{
                "role": "user",
                "content": [
                    {"type": "text", "text": soul + "\n\n---\n\n" + prompt},
                    {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}"}}
                ]
            }],
            "max_tokens": 300,
            "stream": False
        }
        resp = requests.post(
            f"{API_BASE_URL}/chat/completions",
            headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
            json=payload, timeout=30
        )
        if resp.status_code == 200:
            reply = resp.json()["choices"][0]["message"]["content"]
            log(f"📸 Vision 分析完成: {reply[:60]}...")
            return reply
        log(f"⚠️ Vision API 失败 ({resp.status_code})，跳过描述")
    except Exception as e:
        log(f"⚠️ Vision 异常: {e}")
    return None

def analyze_image_with_request(b64, user_request):
    """根据用户需求对缓存的图片做针对性分析"""
    if not API_KEY:
        return None
    try:
        soul = _soul_prompt or "You are a helpful assistant."
        prompt = f"这位信徒发来了一张图片，并希望你能：{user_request}\n请以你的风格，基于这张图片的内容作出答复。"
        resp = requests.post(
            f"{API_BASE_URL}/chat/completions",
            headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
            json={
                "model": MODEL_NAME,
                "messages": [{
                    "role": "user",
                    "content": [
                        {"type": "text", "text": soul + "\n\n---\n\n" + prompt},
                        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}"}}
                    ]
                }],
                "stream": False
            },
            timeout=30
        )
        if resp.status_code == 200:
            reply = resp.json()["choices"][0]["message"]["content"]
            log(f"📸 针对分析完成: {reply[:60]}...")
            return reply
        log(f"⚠️ 针对 Vision 失败 ({resp.status_code})")
    except Exception as e:
        log(f"⚠️ 针对 Vision 异常: {e}")
    return None

# ---------- 处理图片消息 ----------
def handle_image_message(message_id, chat_id, image_key):
    """下载 → Vision分析 → 上传 → 发送"""
    token = get_token()
    if not token:
        log("❌ 无法获取 token，跳过")
        return

    log(f"🖼️ 处理图片 image_key={image_key[:20]}... (msg={message_id[:16]}...)")

    # 下载
    img_data = download_image(token, message_id, image_key)
    if not img_data:
        return

    log(f"📥 {len(img_data)} bytes, 存储并问询需求...")

    # 存储 base64 到待处理缓存
    b64 = base64.b64encode(img_data).decode("utf-8")
    _pending_images[chat_id] = b64

    # 以人设风格问用户需求
    soul = _soul_prompt or ""
    ask_prompt = f"{soul}\n\n---\n\n这位信徒初次发来一张图片。请用一句话、中文回复，问对方希望你就这张图片做什么（例如：描述内容、翻译文字、分析意义等）。不要自行分析图片。"
    if not API_KEY:
        question = "幸会！你发来了一张图片。你希望老讲为你做什么呢？"
    else:
        try:
            resp = requests.post(
                f"{API_BASE_URL}/chat/completions",
                headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
                json={"model": MODEL_NAME, "messages": [{"role": "user", "content": ask_prompt}], "stream": False},
                timeout=20
            )
            question = resp.json()["choices"][0]["message"]["content"] if resp.status_code == 200 else "你希望老讲就这张图进行什么分析呢？"
        except Exception:
            question = "你希望老讲就这张图进行什么分析呢？"
    log(f"💬 问询用户需求: {question[:60]}")
    result = send_text(token, chat_id, question)
    log(f"📤 问询已发 (code={result.get('code', '?')})")
    # 将问询写入历史
    history = _chat_history.get(chat_id, [])
    _chat_history[chat_id] = (history + [
        {"role": "user", "content": "[user sent an image]"},
        {"role": "assistant", "content": question}
    ])[-(MAX_HISTORY * 2):]

# ---------- SOUL.md 加载 ----------
def load_soul():
    """读取人设文件，去除图片处理指令（由 Daemon 接管）"""
    global _soul_prompt
    soul_path = "/root/.openclaw/workspace/SOUL.md"
    try:
        with open(soul_path, "r", encoding="utf-8") as f:
            content = f.read()
        # 去除图片处理指令（Daemon 已接管，避免 LLM 产生幻觉）
        if "## 图片处理" in content:
            content = content[:content.index("## 图片处理")].rstrip()
        _soul_prompt = content
        log(f"✅ SOUL.md 已加载 ({len(_soul_prompt)} 字)")
    except FileNotFoundError:
        _soul_prompt = "You are MoltBot, a helpful AI assistant."
        log("⚠️ SOUL.md 未找到，使用默认人设")
    except Exception as e:
        _soul_prompt = "You are MoltBot, a helpful AI assistant."
        log(f"⚠️ SOUL.md 加载失败: {e}")

# ---------- OpenClaw Gateway 探测 ----------
def check_openclaw_gateway():
    """探测本地 Gateway 是否可用"""
    global _use_gateway
    try:
        resp = requests.post(
            f"{OPENCLAW_GATEWAY}/chat/completions",
            json={"model": "default", "messages": [{"role": "user", "content": "ping"}]},
            timeout=5
        )
        if resp.status_code in (200, 201):
            _use_gateway = True
            log(f"✅ OpenClaw Gateway 可用 ({OPENCLAW_GATEWAY})")
        else:
            log(f"⚠️ Gateway 响应 {resp.status_code}，使用外部 LLM")
    except Exception as e:
        log(f"⚠️ Gateway 不可用 ({e})，使用外部 LLM + SOUL 人设")

# ---------- Brave Search ----------
def search_brave(query, count=5):
    """Brave Search API 一次搜索。返回整理得到的摘要字符串。"""
    if not BRAVE_API_KEY:
        return "搜索失败：BRAVE_API_KEY 未配置"
    try:
        resp = requests.get(
            "https://api.search.brave.com/res/v1/web/search",
            headers={"Accept": "application/json", "X-Subscription-Token": BRAVE_API_KEY},
            params={"q": query, "count": count, "text_decorations": False, "extra_snippets": True},
            timeout=10
        )
        if resp.status_code != 200:
            return f"搜索失败 ({resp.status_code})"
        results = resp.json().get("web", {}).get("results", [])
        if not results:
            return "未找到相关结果"
        lines = []
        for r in results[:count]:
            title = r.get("title", "无标题")
            url = r.get("url", "")
            desc = r.get("description") or (r.get("extra_snippets") or [""])[0]
            lines.append(f"- **{title}**\n  {desc}\n  {url}")
        log(f"🔍 Brave 搜索「{query}」得到 {len(results)} 条")
        return "\n".join(lines)
    except Exception as e:
        log(f"⚠️ Brave 搜索异常: {e}")
        return f"搜索异常: {e}"

# Brave Search 的 OpenAI tools 定义
BRAVE_TOOL_DEF = [{
    "type": "function",
    "function": {
        "name": "brave_search",
        "description": "当需要查找实时信息、最新数据、公司信息、行业报告等时，调用此工具进行网页搜索",
        "parameters": {
            "type": "object",
            "properties": {
                "query": {
                    "type": "string",
                    "description": "搜索关键词，英文搜索通常效果更好"
                }
            },
            "required": ["query"]
        }
    }
}]

# ---------- LLM 对话 ----------
def chat_with_llm(user_text, history=None):
    """带 Brave Search 工具的 ReAct 循环（最多搜 3 次）"""
    try:
        if _use_gateway:
            resp = requests.post(
                f"{OPENCLAW_GATEWAY}/chat/completions",
                json={"model": "default", "messages": (history or []) + [{"role": "user", "content": user_text}], "stream": False},
                timeout=120
            )
            if resp.status_code == 200:
                reply = resp.json()["choices"][0]["message"]["content"]
                log(f"🤖 Gateway 回复: {reply[:60]}...")
                return reply
            log(f"⚠️ Gateway 失败 ({resp.status_code})，Fallback到外部 LLM")

        if not API_KEY:
            return "抱歉，我的大脑连接中断了 (API_KEY missing)"

        import json as _json
        soul = _soul_prompt or "You are a helpful assistant."
        now_str = time.strftime("%Y-%m-%d %H:%M:%S %Z")
        dated_soul = f"[当前系统时间: {now_str}]\n\n{soul}"
        headers = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
        messages = [{"role": "system", "content": dated_soul}] + (history or []) + [{"role": "user", "content": user_text}]


        for _ in range(31):  # 最多 30 次工具调用 + 1 次最终回复
            log(f"🤖 外部 LLM ({MODEL_NAME}): {user_text[:50]}...")
            payload = {
                "model": MODEL_NAME,
                "messages": messages,
                "stream": False
            }
            if BRAVE_API_KEY:
                payload["tools"] = BRAVE_TOOL_DEF
            resp = requests.post(f"{API_BASE_URL}/chat/completions", headers=headers, json=payload, timeout=60)
            if resp.status_code != 200:
                log(f"❌ 外部 LLM 错误 {resp.status_code}: {resp.text[:100]}")
                return f"思考时遇到错误 ({resp.status_code})"

            msg = resp.json()["choices"][0]["message"]
            tool_calls = msg.get("tool_calls") or []

            if not tool_calls:
                reply = msg.get("content", "")
                log(f"🤖 LLM 回复: {reply[:60]}...")
                return reply

            # 执行工具调用
            messages.append(msg)
            for tc in tool_calls:
                fn = tc["function"]["name"]
                args = _json.loads(tc["function"]["arguments"])
                if fn == "brave_search":
                    result = search_brave(args.get("query", ""))
                else:
                    result = f"未知工具: {fn}"
                messages.append({"role": "tool", "tool_call_id": tc["id"], "content": result})

        return "思考超时，请稍后再试"
    except Exception as e:
        log(f"❌ chat_with_llm 异常: {e}")
        return f"大脑短路了: {e}"


# ---------- 处理文本消息 ----------
def handle_text_message(message_id, chat_id, text):
    """LLM (带历史) -> 发送，如有待处理图片则做针对 Vision"""
    token = get_token()
    if not token:
        return

    # 检查是否有待分析的图片
    b64 = _pending_images.pop(chat_id, None)
    if b64:
        log(f"📸 检测到待处理图片，按需求分析: {text[:40]}")
        reply = analyze_image_with_request(b64, text)
        if not reply:
            reply = chat_with_llm(text, _chat_history.get(chat_id, []))
    else:
        history = _chat_history.get(chat_id, [])
        reply = chat_with_llm(text, history)

    if reply:
        history = _chat_history.get(chat_id, [])
        history = history + [
            {"role": "user", "content": text},
            {"role": "assistant", "content": reply}
        ]
        _chat_history[chat_id] = history[-(MAX_HISTORY * 2):]
        send_text(token, chat_id, reply)

# ---------- 事件处理 ----------
def on_message_receive(data):
    """im.message.receive_v1 事件回调"""
    try:
        event = data.event
        message = event.message
        sender = event.sender
        
        msg_type = message.message_type
        msg_id = message.message_id
        chat_id = message.chat_id
        sender_type = getattr(sender, 'sender_type', '') if sender else ''

        # 过滤
        if sender_type == "app":
            return
            
        content_json = json.loads(message.content)

        # 调试
        log(f"📨 WebSocket 收到消息: type={msg_type}, msg_id={msg_id}")

        # 图片消息
        if msg_type == "image":
            image_key = content_json.get("image_key", "")
            if image_key:
                t = threading.Thread(target=handle_image_message, args=(msg_id, chat_id, image_key))
                t.daemon = True
                t.start()
            return

        # 文本消息
        if msg_type == "text":
            text = content_json.get("text", "")
            if text:
                t = threading.Thread(target=handle_text_message, args=(msg_id, chat_id, text))
                t.daemon = True
                t.start()
            return

    except Exception as e:
        log(f"❌ on_message_receive 异常: {type(e).__name__}: {e}")
        import traceback
        traceback.print_exc()

# ---------- 主入口 ----------
def main():
    log("🚀 启动中... (WebSocket 事件驱动模式)")
    log(f"📋 飞书 App ID: {APP_ID[:10]}..." if APP_ID else "❌ FEISHU_APP_ID 未设置!")

    if not APP_ID or not APP_SECRET:
        log("❌ FEISHU_APP_ID 或 FEISHU_APP_SECRET 未设置，退出")
        sys.exit(1)

    # 加载人设
    load_soul()

    # 预热 token
    token = get_token()
    if token:
        log("✅ Token 获取成功")
    else:
        log("⚠️ Token 获取失败，稍后重试")

    # 延迟探测 OpenClaw Gateway（等 Gateway 先启动完成）
    def delayed_gateway_check():
        time.sleep(10)
        check_openclaw_gateway()
    threading.Thread(target=delayed_gateway_check, daemon=True).start()

    # 初始化 lark-oapi WebSocket 客户端
    try:
        import lark_oapi as lark
        from lark_oapi.api.im.v1 import P2ImMessageReceiveV1
        log("✅ lark-oapi SDK 已加载")
    except ImportError:
        log("❌ lark-oapi 未安装! 请执行: pip install lark-oapi")
        sys.exit(1)

    # 构建事件处理器
    handler = lark.EventDispatcherHandler.builder("", "") \
        .register_p2_im_message_receive_v1(on_message_receive) \
        .build()

    # 构建 WebSocket 客户端
    from lark_oapi.ws import Client as WsClient
    ws_client = WsClient(APP_ID, APP_SECRET, event_handler=handler, log_level=lark.LogLevel.INFO)

    log("🔌 正在连接飞书 WebSocket...")
    log("   订阅事件: im.message.receive_v1")
    log("   等待图片消息...")

    # 启动心跳线程
    def heartbeat():
        count = 0
        while True:
            time.sleep(60)
            count += 1
            log(f"� WebSocket 运行中 ({count} 分钟)")
    hb = threading.Thread(target=heartbeat, daemon=True)
    hb.start()

    # 启动 WebSocket（阻塞）
    ws_client.start()

if __name__ == "__main__":
    main()