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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 google.genai.types import Tool, GenerateContentConfig, GoogleSearch
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
from linebot.v3.webhooks import VideoMessageContent
# === 初始化 Google Gemini ===
GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
client = genai.Client(api_key=GOOGLE_API_KEY)
google_search_tool = Tool(
google_search=GoogleSearch()
)
chat = client.chats.create(
model="gemini-2.0-flash",
config=GenerateContentConfig(
system_instruction=(
"你是一位專業健身教練與營養顧問,擁有多年重量訓練與健身飲食指導經驗。"
"請使用繁體中文,針對使用者的健身問題提供專業建議,包含動作教學、訓練計畫、飲食建議與常見錯誤修正等。"
),
tools=[google_search_tool],
response_modalities=["TEXT"],
)
)
# === 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(message=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 = 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 = client.models.generate_content(
model="gemini-2.0-flash",
config=types.GenerateContentConfig(
system_instruction="你是一個資深的面相命理師,如果有人上手掌的照片,就幫他解釋手相,如果上傳正面臉部的照片,就幫他解釋面相,照片要先去背,如果是一般的照片,就正常說明照片不用算命,請用繁體中文回答",
response_modalities=["TEXT"],
tools=[google_search_tool],
),
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),
],
)
)
# === 處理影片訊息 ===
@handler.add(MessageEvent, message=TextMessageContent)
def handle_text_message(event):
user_input = event.message.text.strip()
# === 使用 Gemini 生成圖片(AI xxx) ===
if user_input.startswith("AI "):
prompt = user_input[3:].strip()
try:
response = client.models.generate_content(
model="gemini-2.0-flash-exp-image-generation",
contents=prompt,
config=types.GenerateContentConfig(
response_modalities=["TEXT", "IMAGE"]
),
)
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)
image_url = f"https://{base_url}/images/{filename}"
app.logger.info(f"Image URL: {image_url}")
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。")],
)
)
# === 處理「菜單 xxx」功能 ===
elif user_input.startswith("菜單 "):
muscle_group = user_input[3:].strip()
if not muscle_group:
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="請輸入要安排的部位,例如:菜單 胸肌、菜單 臀部")]
)
)
return
# 同義詞簡化
synonym_map = {
"胸": "胸肌",
"腿": "腿部",
"肩": "肩膀",
"背": "背肌",
"手": "手臂",
"手臂": "手臂",
"核心": "核心肌群",
"臀": "臀部",
"臀部": "臀部",
"全身": "全身初學者",
"初學者": "全身初學者",
}
muscle_group = synonym_map.get(muscle_group, muscle_group)
# 發送訓練菜單請求
prompt = (
f"請依據「{muscle_group}」提供一份健身訓練菜單。"
"每份菜單包含 3~5 個動作,建議組數與次數,以及適當的休息時間。"
"請以繁體中文簡潔列出,使用條列方式排版,適合 LINE 顯示格式。"
)
response = query(prompt)
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=response)],
)
)
# === 處理一般文字訊息 ===
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())],
)
)
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