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import os | |
import logging | |
from io import BytesIO | |
from PIL import Image | |
import gradio as gr | |
from google import genai | |
from google.genai import types | |
# 設定 logging | |
logging.basicConfig( | |
filename='app.log', | |
level=logging.INFO, | |
format='%(asctime)s - %(levelname)s - %(message)s' | |
) | |
# 初始化 Gemini API | |
GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY") | |
client = genai.Client(api_key=GEMINI_API_KEY) | |
# 定義「圖解釋文」功能 | |
def explain_image(image: Image.Image): | |
# 將 PIL Image 轉成 Gemini 所需的格式 | |
buffered = BytesIO() | |
image.save(buffered, format="PNG") | |
image_data = buffered.getvalue() | |
# 準備輸入給 Gemini 的內容 | |
contents = [ | |
types.ContentPart.from_data(data=image_data, mime_type="image/png"), | |
types.ContentPart.text("請用繁體中文說明這張圖片的內容。") | |
] | |
# 呼叫 Gemini 模型 | |
response = client.models.generate_content( | |
model="gemini-1.5-flash", | |
contents=contents, | |
config=types.GenerateContentConfig(response_modalities=["TEXT"]) | |
) | |
# 回傳第一個回答 | |
explanation = response.candidates[0].content.parts[0].text | |
logging.info("圖片說明成功取得。") | |
return explanation | |
# Gradio 介面 | |
with gr.Blocks() as demo: | |
gr.Markdown("## 🧠 Gemini 圖片解釋器(圖 ➜ 文)") | |
image_input = gr.Image(type="pil", label="上傳圖片") | |
explain_button = gr.Button("解釋圖片") | |
output_text = gr.Textbox(label="圖片說明", lines=5) | |
explain_button.click(fn=explain_image, inputs=image_input, outputs=output_text) | |
if __name__ == "__main__": | |
demo.launch() | |