from gradio_client import Client, handle_file import gradio as gr import os MODELS = { "Paligemma-10B": "akhaliq/paligemma2-10b-ft-docci-448" } def create_chat_fn(client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p): def chat(message, history): text = message.get("text", "") files = message.get("files", []) processed_files = [handle_file(f) for f in files] response = client.predict( message={"text": text, "files": processed_files}, system_prompt=system_prompt, temperature=temperature, max_new_tokens=max_tokens, top_k=top_k, repetition_penalty=rep_penalty, top_p=top_p, api_name="/chat" ) return response return chat def set_client_for_session(model_name, request: gr.Request): headers = {} if request and hasattr(request, 'headers'): x_ip_token = request.headers.get('x-ip-token') if x_ip_token: headers["X-IP-Token"] = x_ip_token return Client(MODELS[model_name], headers=headers) def safe_chat_fn(message, history, client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p): if client is None: return "Error: Client not initialized. Please refresh the page." try: return create_chat_fn(client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p)(message, history) except Exception as e: print(f"Error during chat: {str(e)}") return f"Error during chat: {str(e)}" with gr.Blocks() as demo: client = gr.State() with gr.Accordion("Advanced Settings", open=False): system_prompt = gr.Textbox( value="You are a helpful AI assistant.", label="System Prompt" ) with gr.Row(): temperature = gr.Slider( minimum=0.0, maximum=2.0, value=0.7, label="Temperature" ) top_p = gr.Slider( minimum=0.0, maximum=1.0, value=0.95, label="Top P" ) with gr.Row(): top_k = gr.Slider( minimum=1, maximum=100, value=40, step=1, label="Top K" ) rep_penalty = gr.Slider( minimum=1.0, maximum=2.0, value=1.1, label="Repetition Penalty" ) max_tokens = gr.Slider( minimum=64, maximum=4096, value=1024, step=64, label="Max Tokens" ) chat_interface = gr.ChatInterface( fn=safe_chat_fn, additional_inputs=[client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p], multimodal=True ) # Initialize client on page load with default model demo.load( fn=set_client_for_session, inputs=[gr.State("Paligemma-10B")], # Using default model outputs=[client] ) # Move the API access check here, after demo is defined if hasattr(demo, 'fns'): for fn in demo.fns.values(): fn.api_name = False demo = demo