File size: 12,192 Bytes
887f465
 
9949813
887f465
096d13f
2b0943a
7431696
9949813
 
 
f3ead48
b8e6e12
 
f3ead48
 
9949813
 
 
 
 
 
 
 
 
 
 
f3ead48
 
 
 
 
 
b8e6e12
f3ead48
9949813
887f465
 
f3ead48
 
 
 
 
 
 
79d4f9b
f3ead48
2b0943a
 
 
 
 
f3ead48
 
 
 
887f465
 
 
 
 
 
 
 
 
f3ead48
 
887f465
 
 
9949813
 
 
 
 
 
 
887f465
 
f3ead48
887f465
 
f3ead48
887f465
 
 
 
 
 
 
 
 
9949813
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7431696
f3ead48
7431696
 
 
b8e6e12
 
9949813
7431696
 
 
 
 
096d13f
7431696
 
 
 
 
096d13f
b8e6e12
096d13f
7431696
 
 
 
 
 
 
 
 
 
 
9949813
7431696
f3ead48
9949813
7431696
9949813
 
 
 
 
7431696
9949813
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b8e6e12
9949813
 
ce94612
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f3ead48
ce94612
f3ead48
 
 
 
 
ce94612
 
46b7c78
ce94612
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9949813
f3ead48
9949813
2b0943a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9949813
c806d24
 
 
 
 
2b0943a
c806d24
 
9949813
2b0943a
 
 
 
 
 
 
9949813
2b0943a
 
 
 
 
9949813
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
# ===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())],
                )
            )