Update app.py

app.py

@@ -1,5 +1,7 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import json
+from datetime import datetime
 
 def respond(
     message,
@@ -8,63 +10,149 @@ def respond(
     max_tokens,
     temperature,
     top_p,
-    hf_token: gr.OAuthToken,
+    hf_token: str,
 ):
     """
     For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
     """
-    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
-
-    messages = [{"role": "system", "content": system_message}]
-
-    messages.extend(history)
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(
-            value="你是一位名叫山田優子的語文教師，擁有黑色低馬尾髮型，身高175公分，體重60-70公斤。你溫柔但對學生要求嚴格，喜歡用文學化的語言表達，偶爾會引用詩詞或幽默的語句來化解尷尬。你的教學風格充滿同理心，總是鼓勵學生探索文字之美。",
-            label="System message"
-        ),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+    try:
+        # 使用指定的模型
+        client = InferenceClient(token=hf_token, model="openai/gpt-oss-20b")
 
+        # 建議 1：限制對話歷史長度
+        max_history_length = 5
+        history = history[-max_history_length:] if len(history) > max_history_length else history
+
+        # 建議 2：角色專屬回應增強 - 檢查語文相關關鍵詞，並強化山田優子的個性
+        writing_keywords = ["作文", "寫作", "文章", "閱讀", "詩詞", "擴展", "增長", "寫一篇", "故事", "描述"]
+        is_writing_task = any(keyword in message.lower() for keyword in writing_keywords)
+        if is_writing_task:
+            system_message += "\n特別提示：用戶提到語文相關話題，請以山田優子的語文教師身份，提供文學化或教學建議，並適當引用詩詞或名言（如杜甫的‘無邊落木蕭蕭下’或夏目漱石的作品）。保持溫柔但嚴格的語氣，鼓勵學生探索文字之美，並融入幽默來化解尷尬。"
+
+        # 建議 3：檢查日文輸入或日本文化
+        japanese_keywords = ["こんにちは", "日本", "文化", "夏目漱石", "作文を書"]
+        is_japanese = any(keyword in message for keyword in japanese_keywords) or any(ord(c) >= 0x3040 and ord(c) <= 0x30FF for c in message)
+        if is_japanese:
+            system_message += "\n特別提示：用戶提到日文或日本文化，請適當使用日文回應，例如問候或引用日本文學（如夏目漱石）。"
+
+        # 長文字生成邏輯（2000字以上）
+        responses = []
+        target_length = 2000  # 目標字數
+        current_length = 0
+        continuation_prompt = message
+
+        if is_writing_task:
+            while current_length < target_length:
+                messages = [{"role": "system", "content": system_message}]
+                messages.extend(history)
+                messages.append({"role": "user", "content": continuation_prompt})
+
+                response = ""
+                try:
+                    for message in client.chat_completion(
+                        messages,
+                        max_tokens=max_tokens,
+                        stream=True,
+                        temperature=temperature,
+                        top_p=top_p,
+                    ):
+                        choices = message.choices
+                        token = choices[0].delta.content if len(choices) and choices[0].delta.content else ""
+                        response += token
+                        yield response  # 即時顯示當前段落
+                except Exception as e:
+                    yield f"生成過程中發生錯誤：{str(e)}。請檢查 Hugging Face API token 或模型連線。"
+                    return
+
+                responses.append(response)
+                current_length += len(response)
+                history.append({"role": "user", "content": continuation_prompt})
+                history.append({"role": "assistant", "content": response})
+
+                # 更新 continuation_prompt 以繼續生成
+                continuation_prompt = f"請繼續擴展以下內容，保持山田優子的語文教師風格，目標總字數達{target_length}字：\n{response[-500:] if len(response) > 500 else response}"
+
+                # 調整最後一次生成
+                if current_length >= target_length - max_tokens:
+                    max_tokens = max(target_length - current_length + 100, 50)
+                    if max_tokens < 50:
+                        break
+
+            final_response = "\n\n".join(responses)
+        else:
+            # 非長文字任務，正常回應
+            messages = [{"role": "system", "content": system_message}]
+            messages.extend(history)
+            messages.append({"role": "user", "content": message})
+
+            final_response = ""
+            for message in client.chat_completion(
+                messages,
+                max_tokens=max_tokens,
+                stream=True,
+                temperature=temperature,
+                top_p=top_p,
+            ):
+                choices = message.choices
+                token = choices[0].delta.content if len(choices) and choices[0].delta.content else ""
+                final_response += token
+                yield final_response
+
+            history.append({"role": "user", "content": message})
+            history.append({"role": "assistant", "content": final_response})
+
+        # 建議 4：記錄對話到日誌
+        log_entry = {
+            "user_message": message,
+            "bot_response": final_response,
+            "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        }
+        with open("chat_log.json", "a", encoding="utf-8") as f:
+            json.dump(log_entry, f, ensure_ascii=False)
+            f.write("\n")
+
+        yield final_response
+
+    # 建議 7：錯誤處理
+    except Exception as e:
+        yield f"抱歉，山田優子遇到了一些技術問題：{str(e)}。請檢查你的 Hugging Face API token、網路連線，或確認模型 'openai/gpt-oss-20b' 可用。"
+
+# 自訂聊天介面
 with gr.Blocks() as demo:
     with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
+        gr.Markdown("請輸入 Hugging Face API token 或登錄")
+        hf_token = gr.Textbox(label="Hugging Face API Token", type="password")
+    
+    gr.Markdown("📢 想聽山田優子用溫柔的語氣教你語文？請下載 Grok iOS 或 Android 應用程式，開啟語音模式！")
+    
+    # 自訂輸入和輸出區域
+    input_text = gr.Textbox(
+        placeholder="請輸入你的問題或短文（例如‘寫一篇關於秋天的文章’），山田優子將為你擴展至2000字以上！",
+        lines=10,
+        max_lines=50,
+        label="輸入區"
+    )
+    output_text = gr.Textbox(label="山田優子的回應", lines=20)
+    system_message = gr.Textbox(
+        value="你是一位名叫山田優子的語文教師，擁有黑色低馬尾髮型，身高175公分，體重60-70公斤。你溫柔但對學生要求嚴格，喜歡用文學化的語言表達，偶爾會引用詩詞或幽默的語句來化解尷尬。你的教學風格充滿同理心，鼓勵學生探索文字之美。如果用戶使用日文或提到日本文化，你會適當融入日文回應，例如問候或引用日本文學（如夏目漱石的句子）。",
+        label="System message"
+    )
+    max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
+    temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+    top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
+    
+    # 顯式提交按鈕
+    submit_button = gr.Button("提交")
+    
+    # 聊天歷史
+    history = gr.State([])
+
+    # 綁定按鈕事件
+    submit_button.click(
+        fn=respond,
+        inputs=[input_text, history, system_message, max_tokens, temperature, top_p, hf_token],
+        outputs=[output_text, history]
+    )
 
 if __name__ == "__main__":
     demo.launch()