update app.py

app.py

@@ -1,38 +1,13 @@
-import gradio as gr
-import os
-import requests
 from llama_cpp import Llama
 
-# 确保模型文件夹存在
-model_dir = "/home/user/models"
-os.makedirs(model_dir, exist_ok=True)
-
-# GGUF 模型文件名
-model_name = "unsloth.Q8_0.gguf"
-model_path = os.path.join(model_dir, model_name)
-
-# 如果模型文件不存在，则从 Hugging Face 下载
-hf_model_url = "https://huggingface.co/YLX1965/medical-model/resolve/main/unsloth.Q8_0.gguf"
-
-if not os.path.exists(model_path):
-    print(f"Downloading model from {hf_model_url}...")
-    response = requests.get(hf_model_url, stream=True)
-    with open(model_path, "wb") as f:
-        for chunk in response.iter_content(chunk_size=8192):
-            f.write(chunk)
-    print("Download complete.")
+# 直接从 Hugging Face 加载模型（避免存储问题）
+llm = Llama.from_pretrained("YLX1965/medical-model", filename="unsloth.Q8_0.gguf")
 
-# 加载 GGUF 模型
-llm = Llama(model_path=model_path)
-
-# 定义聊天函数
 def chat(prompt):
     output = llm(prompt, max_tokens=200)
     return output["choices"][0]["text"]
 
-# 创建 Gradio 界面
-interface = gr.Interface(fn=chat, inputs="text", outputs="text",
-                         title="Medical Chatbot",
-                         description="使用 GGUF 量化模型进行医疗文本生成")
-
+# 运行 Gradio
+import gradio as gr
+interface = gr.Interface(fn=chat, inputs="text", outputs="text")
 interface.launch()