Upload app.py

app.py

@@ -0,0 +1,124 @@
+
+import re
+import json
+import requests
+import gradio as gr
+
+HF_TOKEN = "hf_你的Token這邊要換掉"
+
+task_options = ["重點整理", "問答", "翻譯"]
+
+MODEL_URLS = {
+    "重點整理": {
+        "翻譯": "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-zh",
+        "摘要": "https://api-inference.huggingface.co/models/csebuetnlp/mT5_multilingual_XLSum"
+    },
+    "問答": "https://api-inference.huggingface.co/models/luhua/chinese_pretrain_mrc_roberta_wwm_ext_large",
+    "翻譯": "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-zh"
+}
+
+def clean_rtf(text):
+    text = re.sub(r"\'.", "", text)
+    text = re.sub(r"\[a-z]+[0-9]* ?", "", text)
+    text = re.sub(r"[{}]", "", text)
+    return text.strip()
+
+def run_model(task, text, question=None):
+    headers = {
+        "Authorization": f"Bearer {HF_TOKEN}",
+        "Content-Type": "application/json"
+    }
+
+    if task == "重點整理":
+        translation_payload = {"inputs": text}
+        translation_url = MODEL_URLS["重點整理"]["翻譯"]
+        translation_response = requests.post(translation_url, headers=headers, json=translation_payload)
+
+        if translation_response.status_code != 200:
+            return "❌ 翻譯失敗：" + translation_response.text
+
+        try:
+            translated_text = translation_response.json()[0]['translation_text']
+        except Exception as e:
+            return f"❌ 翻譯結果解析錯誤：{str(e)}"
+
+        summarization_payload = {"inputs": f"summarize: {translated_text}"}
+        summarization_url = MODEL_URLS["重點整理"]["摘要"]
+        summarization_response = requests.post(summarization_url, headers=headers, json=summarization_payload)
+
+        if summarization_response.status_code != 200:
+            return "❌ 摘要失敗：" + summarization_response.text
+
+        try:
+            summary_text = summarization_response.json()[0]['summary_text']
+        except Exception as e:
+            return f"❌ 摘要結果解析錯誤：{str(e)}"
+
+        return summary_text
+
+    elif task == "問答":
+        if not question:
+            return "❌ 請輸入問題"
+
+        qa_payload = {
+            "inputs": {
+                "question": question,
+                "context": text
+            }
+        }
+        qa_url = MODEL_URLS["問答"]
+        qa_response = requests.post(qa_url, headers=headers, json=qa_payload)
+
+        if qa_response.status_code != 200:
+            return "❌ 問答失敗：" + qa_response.text
+
+        try:
+            answer = qa_response.json().get("answer", "⚠️ 找不到答案")
+            trans_payload = {"inputs": answer}
+            trans_url = MODEL_URLS["翻譯"]
+            trans_response = requests.post(trans_url, headers=headers, json=trans_payload)
+            if trans_response.status_code == 200:
+                return trans_response.json()[0]['translation_text']
+            else:
+                return answer
+        except Exception as e:
+            return f"❌ 回答解析錯誤：{str(e)}"
+
+    elif task == "翻譯":
+        translation_payload = {"inputs": text}
+        translation_url = MODEL_URLS["翻譯"]
+        translation_response = requests.post(translation_url, headers=headers, json=translation_payload)
+
+        if translation_response.status_code != 200:
+            return "❌ 翻譯失敗：" + translation_response.text
+
+        try:
+            return translation_response.json()[0]['translation_text']
+        except Exception as e:
+            return f"❌ 翻譯結果解析錯誤：{str(e)}"
+
+    else:
+        return "❌ 不支援的任務"
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🌐 多功能語言處理器（繁體中文）\n支援：重點整理（英文→中）、問答、翻譯（英翻中）")
+
+    with gr.Row():
+        task = gr.Dropdown(choices=task_options, label="請選擇任務")
+
+    with gr.Row():
+        text_input = gr.Textbox(lines=10, label="輸入文章 / 內容")
+
+    with gr.Row():
+        question_input = gr.Textbox(label="問題（問答任務用）", placeholder="選擇問答任務時必填")
+
+    with gr.Row():
+        output = gr.Textbox(lines=5, label="輸出結果")
+
+    with gr.Row():
+        run_button = gr.Button("執行")
+
+    run_button.click(fn=run_model, inputs=[task, text_input, question_input], outputs=output)
+
+if __name__ == "__main__":
+    demo.launch()