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Update app.py
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app.py
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@@ -1,48 +1,19 @@
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import gradio as gr
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import requests
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import os
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#
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API_URL = "https://api-inference.huggingface.co/models/
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HF_API_TOKEN = os.getenv("HF_API_TOKEN") #
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headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
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def query(payload):
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# 呼叫 API 並處理回應
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response = requests.post(API_URL, headers=headers, json=payload)
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if response.status_code != 200:
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# 打印錯誤以進行調試
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print(f"Request failed with status code {response.status_code}")
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print(f"Error details: {response.text}")
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return f"Error: {response.status_code}, {response.text}"
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return response.content
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output = query({"inputs": description})
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# 如果回應的內容是錯誤信息,顯示錯誤
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if isinstance(output, str) and output.startswith("Error:"):
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return output # 直接返回錯誤訊息供顯示
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# 保存生成的圖像到文件
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with open("generated_image.png", "wb") as f:
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f.write(output)
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# 返回生成的圖像文件
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return "generated_image.png"
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# 創建 Gradio 介面
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interface = gr.Interface(
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fn=generate_landscape_art,
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inputs=gr.Textbox(lines=2, placeholder="輸入描述來生成山水畫..."),
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outputs="image", # 輸出圖像
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title="山水畫生成器",
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description="根據您的描述生成山水畫,請輸入如 '古代中國風格的山水畫' 的描述"
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)
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# 啟動 Gradio 應用
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interface.launch()
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import requests
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import os
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# 設置測試模型的 API URL
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API_URL = "https://api-inference.huggingface.co/models/gpt2"
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HF_API_TOKEN = os.getenv("HF_API_TOKEN") # 從環境變數讀取 API token
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headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
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def query(payload):
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response = requests.post(API_URL, headers=headers, json=payload)
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if response.status_code != 200:
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return f"Error: {response.status_code}, {response.text}"
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return response.json()
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# 測試簡單的文本生成
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output = query({"inputs": "Hello, world!"})
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# 打印結果
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print(output)
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