Update app.py

app.py

@@ -10,26 +10,27 @@ model = AutoModelForCausalLM.from_pretrained(
     trust_remote_code=True
 )
 
-# 创建聊天管道
+# 创建文本生成管道（替换原有的 conversational 管道）
 chat_pipeline = pipeline(
-    "conversational",
+    "text-generation",
     model=model,
-    tokenizer=tokenizer
+    tokenizer=tokenizer,
+    max_new_tokens=100  # 限制回复长度，避免过长
 )
 
 # 聊天函数
 def chat_with_model(message, history):
-    # 把历史对话转换成模型需要的格式
-    history_transformer_format = []
+    # 构建对话历史
+    prompt = ""
     for user_msg, bot_msg in history:
-        history_transformer_format.append({"role": "user", "content": user_msg})
-        history_transformer_format.append({"role": "assistant", "content": bot_msg})
-    # 添加当前用户消息
-    history_transformer_format.append({"role": "user", "content": message})
+        prompt += f"用户：{user_msg}\n助手：{bot_msg}\n"
+    prompt += f"用户：{message}\n助手："
     
     # 获取模型回复
-    response = chat_pipeline(history_transformer_format)
-    return response[-1]["content"]
+    response = chat_pipeline(prompt, temperature=0.7)[0]["generated_text"]
+    # 提取助手的回复
+    bot_response = response.split("助手：")[-1].strip()
+    return bot_response
 
 # 启动Gradio聊天界面
 if __name__ == "__main__":