app.py

import gradio as gr
from huggingface_hub import InferenceClient, InferenceTimeoutError
import logging

# Set up logging
logging.basicConfig(level=logging.INFO)

# Initialize client with timeout
client = InferenceClient("hackergeek/gemma-finetuned", timeout=30)

def respond(
    message: str,
    history: list[tuple[str, str]],
    system_message: str,
    max_tokens: int,
    temperature: float,
    top_p: float,
):
    """
    Handles chat responses with error handling and validation
    """
    try:
        # Validate system message
        if not system_message.strip():
            system_message = "You are a helpful AI assistant."

        # Build message history
        messages = [{"role": "system", "content": system_message}]
        
        for user_msg, assistant_msg in history:
            if user_msg:
                messages.append({"role": "user", "content": user_msg})
            if assistant_msg:
                messages.append({"role": "assistant", "content": assistant_msg})
        
        messages.append({"role": "user", "content": message})

        response = ""
        
        # Stream the response
        for chunk in client.chat_completion(
            messages,
            max_tokens=max_tokens,
            stream=True,
            temperature=temperature,
            top_p=top_p,
        ):
            if chunk.choices and chunk.choices[0].delta.content:
                token = chunk.choices[0].delta.content
                response += token
                yield response

    except InferenceTimeoutError:
        logging.error("API request timed out")
        yield "Error: Request timed out. Please try again."
    except Exception as e:
        logging.error(f"API error: {str(e)}")
        yield f"Error: {str(e)}. Please check your input and try again."

# Custom CSS for better appearance
custom_css = """
#chatbot { min-height: 400px; }
.dark #chatbot { font-size: 14px !important; }
footer { visibility: hidden; }
"""

# Configure interface
with gr.Blocks(css=custom_css, title="Gemma Chatbot") as demo:
    gr.Markdown("# 🚀 Gemma Fine-Tuned Chatbot")
    gr.Markdown("Chat with the fine-tuned Gemma AI assistant!")
    
    with gr.Accordion("⚙️ Advanced Settings", open=False):
        system_input = gr.Textbox(
            value="You are a helpful AI assistant.",
            label="System Role",
            info="Initial instructions for the AI"
        )
        max_tokens = gr.Slider(
            minimum=32, maximum=2048, value=512,
            step=32, label="Max Response Length"
        )
        temperature = gr.Slider(
            minimum=0.1, maximum=2.0, value=0.7,
            step=0.1, label="Creativity (Temperature)"
        )
        top_p = gr.Slider(
            minimum=0.1, maximum=1.0, value=0.95,
            step=0.05, label="Focus (Top-p)"
        )
    
    chat_interface = gr.ChatInterface(
        respond,
        additional_inputs=[
            system_input,
            max_tokens,
            temperature,
            top_p
        ],
        examples=[
            ["Explain quantum computing in simple terms"],
            ["What's the weather like in Paris?"],
            ["Write a poem about artificial intelligence"]
        ],
        retry_btn=None,
        undo_btn=None,
        clear_btn="✨ New Chat",
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)