Update app.py

app.py

@@ -1,50 +1,16 @@
-import os
-import subprocess
 import gradio as gr
-import ollama
+import spaces
+import transformers_gradio
 
-# Ensure ollama is installed via pip
-def install_ollama():
-    try:
-        import ollama
-        print("✅ Ollama is already installed.")
-    except ImportError:
-        print("🚀 Installing Ollama via pip...")
-        subprocess.run(["pip", "install", "ollama"], check=True)
-        import ollama  # Re-import after installation
-        print("✅ Ollama installed successfully!")
+demo = gr.load(name="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", src=transformers_gradio.registry)
+demo = gr.load(name="deepseek-ai/DeepSeek-R1", src=transformers_gradio.registry)
+demo = gr.load(name="deepseek-ai/DeepSeek-R1-Zero", src=transformers_gradio.registry)
 
-# Ensure model is downloaded
-MODEL_NAME = "deepseek-llm-7b"
-MODEL_PATH = f"models/{MODEL_NAME}"
 
-def download_model():
-    models = ollama.list()
-    if any(m["name"] == MODEL_NAME for m in models["models"]):
-        print(f"✅ Model '{MODEL_NAME}' is already available.")
-    else:
-        print(f"🚀 Downloading model: {MODEL_NAME} ...")
-        ollama.pull(MODEL_NAME)
-        print(f"✅ Model '{MODEL_NAME}' downloaded successfully.")
+demo.fn = spaces.GPU()(demo.fn)
 
-# Generate AI response using Ollama
-def chat_response(user_input):
-    response = ollama.chat(model=MODEL_NAME, messages=[{"role": "user", "content": user_input}])
-    return response['message']['content']
+for fn in demo.fns.values():
+    fn.api_name = False
 
-# Run setup
-install_ollama()
-download_model()
-
-# Create Gradio Interface
-iface = gr.Interface(
-    fn=chat_response,
-    inputs="text",
-    outputs="text",
-    title="DeepSeek ChatBot (Ollama)",
-    description="Chat with DeepSeek LLM 7B using Ollama."
-)
-
-# Launch Gradio App
 if __name__ == "__main__":
-    iface.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch()