Update app.py

app.py

@@ -1,4 +1,4 @@
-"""import gradio as gr
+import gradio as gr
 from huggingface_hub import InferenceClient
 
 
@@ -55,72 +55,5 @@ demo = gr.ChatInterface(
 )
 
 
-if __name__ == "__main__":
-    demo.launch()
-"""
-
-import os
-import gradio as gr
-from huggingface_hub import InferenceClient
-import json
-
-# Retrieve the API token from the environment variable
-API_TOKEN = os.getenv("HF_READ_TOKEN")
-
-# Initialize the Hugging Face Inference Client
-client = InferenceClient(
-    "mistralai/Mistral-Nemo-Instruct-2407",
-    token=API_TOKEN
-)
-
-# System prompt to define model behavior
-system_prompt = "You are a helpful assistant that provides concise and accurate answers."
-
-# Function to handle the chat completion
-def hf_chat(user_input):
-    messages = [
-        {"role": "system", "content": system_prompt},
-        {"role": "user", "content": user_input}
-    ]
-    response = ""
-    
-    try:
-        # Stream the response
-        for message in client.chat_completion(
-            messages=messages,
-            max_tokens=500,
-            stream=True,
-        ):
-            try:
-                # Parse each part of the response carefully
-                content = message.choices[0].delta.content
-                response += content
-            except (KeyError, json.JSONDecodeError) as e:
-                # Print error details for debugging
-                print(f"Error while parsing response: {e}")
-                continue  # Continue receiving the stream
-
-    except Exception as e:
-        # Catch and print any unexpected errors during the stream
-        return f"Error occurred: {str(e)}"
-    
-    return response
-
-# Gradio interface
-with gr.Blocks() as demo:
-    gr.Markdown("# mistral nemo prompt enhancer")
-    with gr.Row():
-        with gr.Column():
-            user_input = gr.Textbox(
-                label="Enter your message", 
-                placeholder="Ask me anything..."
-            )
-            submit_btn = gr.Button("Submit")
-        with gr.Column():
-            output = gr.Textbox(label="Response")
-
-    submit_btn.click(fn=hf_chat, inputs=user_input, outputs=output)
-
-# Launch Gradio app
 if __name__ == "__main__":
     demo.launch(show_api=True, share=False)