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# ===東吳大學資料系 2025 年 LINEBOT ===
import logging
import os
import tempfile
import uuid
from io import BytesIO

import markdown
from bs4 import BeautifulSoup
from flask import Flask, abort, request, send_from_directory
from google import genai
from google.genai import types
from linebot.v3 import WebhookHandler
from linebot.v3.exceptions import InvalidSignatureError
from linebot.v3.messaging import (
    ApiClient,
    Configuration,
    ImageMessage,
    MessagingApi,
    MessagingApiBlob,
    ReplyMessageRequest,
    TextMessage,
)
from linebot.v3.webhooks import ImageMessageContent, MessageEvent, TextMessageContent
from PIL import Image

# === 初始化 Google Gemini ===
GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
google_client = genai.Client(api_key=GOOGLE_API_KEY)
text_system_prompt = "你是一個中文的AI助手,請用繁體中文回答"
chat = google_client.chats.create(model="gemini-2.0-flash")

# === 初始設定 ===
static_tmp_path = tempfile.gettempdir()
os.makedirs(static_tmp_path, exist_ok=True)
base_url = os.getenv("SPACE_HOST")  # e.g., "your-space-name.hf.space"

# === Flask 應用初始化 ===
app = Flask(__name__)
logging.basicConfig(
    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
)
app.logger.setLevel(logging.INFO)

channel_secret = os.environ.get("YOUR_CHANNEL_SECRET")
channel_access_token = os.environ.get("YOUR_CHANNEL_ACCESS_TOKEN")

configuration = Configuration(access_token=channel_access_token)
handler = WebhookHandler(channel_secret)


# === AI Query 包裝 ===
def query(payload):
    response = chat.send_message(f"{text_system_prompt}{payload}")
    return response.text

# === 靜態圖檔路由 ===
@app.route("/images/<filename>")
def serve_image(filename):
    return send_from_directory(static_tmp_path, filename)


# === LINE Webhook 接收端點 ===
@app.route("/")
def home():
    return {"message": "Line Webhook Server"}


@app.route("/", methods=["POST"])
def callback():
    signature = request.headers.get("X-Line-Signature")
    body = request.get_data(as_text=True)
    app.logger.info(f"Request body: {body}")

    try:
        handler.handle(body, signature)
    except InvalidSignatureError:
        app.logger.warning("Invalid signature. Please check channel credentials.")
        abort(400)

    return "OK"


# === 處理文字訊息 ===
@handler.add(MessageEvent, message=TextMessageContent)
def handle_text_message(event):
    user_input = event.message.text.strip()
    if user_input.startswith("AI "):
        prompt = user_input[3:].strip()
        try:
            # 使用 Gemini 生成圖片
            response = google_client.models.generate_content(
                model="gemini-2.0-flash-exp-image-generation",
                contents=prompt,
                config=types.GenerateContentConfig(
                    response_modalities=["TEXT", "IMAGE"]
                ),
            )

            # 處理回應中的圖片
            for part in response.candidates[0].content.parts:
                if part.inline_data is not None:
                    image = Image.open(BytesIO(part.inline_data.data))
                    filename = f"{uuid.uuid4().hex}.png"
                    image_path = os.path.join(static_tmp_path, filename)
                    image.save(image_path)

                    # 建立圖片的公開 URL
                    image_url = f"https://{base_url}/images/{filename}"
                    app.logger.info(f"Image URL: {image_url}")

                    # 回傳圖片給 LINE 使用者
                    with ApiClient(configuration) as api_client:
                        line_bot_api = MessagingApi(api_client)
                        line_bot_api.reply_message(
                            ReplyMessageRequest(
                                reply_token=event.reply_token,
                                messages=[
                                    ImageMessage(
                                        original_content_url=image_url,
                                        preview_image_url=image_url,
                                    )
                                ],
                            )
                        )
                    
        except Exception as e:
            app.logger.error(f"Gemini API error: {e}")
            with ApiClient(configuration) as api_client:
                line_bot_api = MessagingApi(api_client)
                line_bot_api.reply_message(
                    ReplyMessageRequest(
                        reply_token=event.reply_token,
                        messages=[TextMessage(text="抱歉,生成圖片時發生錯誤。")],
                    )
                )
    else:
        with ApiClient(configuration) as api_client:
            line_bot_api = MessagingApi(api_client)
            response = query(event.message.text)
            html_msg = markdown.markdown(response)
            soup = BeautifulSoup(html_msg, "html.parser")

            line_bot_api.reply_message_with_http_info(
                ReplyMessageRequest(
                    reply_token=event.reply_token,
                    messages=[TextMessage(text=soup.get_text())],
                )
            )


# === 處理圖片訊息 ===
@handler.add(MessageEvent, message=ImageMessageContent)
def handle_image_message(event):
    # === 以下是處理圖片回傳部分 === #
    with ApiClient(configuration) as api_client:
        blob_api = MessagingApiBlob(api_client)
        content = blob_api.get_message_content(message_id=event.message.id)

    # Step 4:將圖片存到本地端
    with tempfile.NamedTemporaryFile(
        dir=static_tmp_path, suffix=".jpg", delete=False
    ) as tf:
        tf.write(content)
        filename = os.path.basename(tf.name)

    image_url = f"https://{base_url}/images/{filename}"

    app.logger.info(f"Image URL: {image_url}")

    # === 以下是解釋圖片 === #
    image = Image.open(tf.name)
    response = google_client.models.generate_content(
        model="gemini-2.0-flash",
        contents=[image, "用繁體中文描述這張圖片"],
    )
    app.logger.info(response.text)

    # === 以下是回傳圖片部分 === #

    with ApiClient(configuration) as api_client:
        line_bot_api = MessagingApi(api_client)
        line_bot_api.reply_message(
            ReplyMessageRequest(
                reply_token=event.reply_token,
                messages=[
                    ImageMessage(
                        original_content_url=image_url, preview_image_url=image_url
                    ),
                    TextMessage(text=response.text),
                ],
            )
        )
'''
@handler.add(MessageEvent, message=ImageMessageContent)
def handle_image_message(event):

    # === 以下是處理圖片回傳部分 === #

    with ApiClient(configuration) as api_client:
        blob_api = MessagingApiBlob(api_client)
        content = blob_api.get_message_content(message_id=event.message.id)
        image_bytes = content

    # Step 2:轉成 base64 字串
    base64_string = base64.b64encode(image_bytes).decode("utf-8")

    # Step 3:組成 OpenAI 的 data URI 格式
    data_uri = f"data:image/png;base64,{base64_string}"
    app.logger.info(f"Data URI: {data_uri}")

    # Step 4:將圖片存到本地端
    with tempfile.NamedTemporaryFile(
        dir=static_tmp_path, suffix=".jpg", delete=False
    ) as tf:
        tf.write(content)
        filename = os.path.basename(tf.name)

    image_url = f"https://{base_url}/images/{filename}"

    app.logger.info(f"Image URL: {image_url}")

    # === 以下是處理解釋圖片部分 === #
    response = client.responses.create(
        model="gpt-4.1-nano",
        input=[
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_text",
                        "text": "describe the image in traditional chinese",
                    },
                    {
                        "type": "input_image",
                        "image_url": data_uri,
                    },
                ],
            }
        ],
    )
    app.logger.info(response.output_text)

    # === 以下是回傳圖片部分 === #

    with ApiClient(configuration) as api_client:
        line_bot_api = MessagingApi(api_client)
        line_bot_api.reply_message(
            ReplyMessageRequest(
                reply_token=event.reply_token,
                messages=[
                    ImageMessage(
                        original_content_url=image_url, preview_image_url=image_url
                    ),
                    TextMessage(text=response.output_text),
                ],
            )
        )
'''