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| import gradio as gr | |
| from functools import lru_cache | |
| # Cache model loading to optimize performance | |
| def load_hf_model(model_name): | |
| return gr.load( | |
| name=f"deepseek-ai/{model_name}", | |
| src="huggingface", | |
| api_name="/chat" | |
| ) | |
| # Load all models at startup | |
| MODELS = { | |
| "DeepSeek-R1-Distill-Qwen-32B": load_hf_model("DeepSeek-R1-Distill-Qwen-32B"), | |
| "DeepSeek-R1": load_hf_model("DeepSeek-R1"), | |
| "DeepSeek-R1-Zero": load_hf_model("DeepSeek-R1-Zero") | |
| } | |
| def parse_response(response): | |
| """Handle different response formats from various models""" | |
| if isinstance(response, list): | |
| if len(response) > 0: | |
| # Handle list of messages format | |
| return response[0].get('generated_text', | |
| response[0].get('content', str(response[0]))) | |
| elif isinstance(response, dict): | |
| # Handle OpenAI-style format | |
| if 'choices' in response: | |
| return response['choices'][0]['message']['content'] | |
| # Handle standard text generation format | |
| elif 'generated_text' in response: | |
| return response['generated_text'] | |
| return f"Unsupported response format: {type(response)}" | |
| def chatbot(input_text, history, model_choice, system_message, max_new_tokens, temperature, top_p): | |
| history = history or [] | |
| model_component = MODELS[model_choice] | |
| # Construct messages with optional system message | |
| messages = [] | |
| if system_message.strip(): | |
| messages.append({"role": "system", "content": system_message}) | |
| messages.append({"role": "user", "content": input_text}) | |
| payload = { | |
| "messages": messages, | |
| "max_tokens": max_new_tokens, | |
| "temperature": temperature, | |
| "top_p": top_p | |
| } | |
| try: | |
| response = model_component(payload) | |
| assistant_response = parse_response(response) | |
| except Exception as e: | |
| assistant_response = f"Error: {str(e)}" | |
| history.append((input_text, assistant_response)) | |
| return history, history, "" | |
| # Interface setup remains the same | |
| with gr.Blocks(theme=gr.themes.Soft(), title="DeepSeek Chatbot") as demo: | |
| gr.Markdown("""# DeepSeek Chatbot""") | |
| with gr.Row(): | |
| with gr.Column(): | |
| chatbot_output = gr.Chatbot(height=500) | |
| msg = gr.Textbox(placeholder="Type your message...") | |
| with gr.Row(): | |
| submit_btn = gr.Button("Submit", variant="primary") | |
| clear_btn = gr.ClearButton([msg, chatbot_output]) | |
| with gr.Row(): | |
| with gr.Accordion("Options", open=True): | |
| model_choice = gr.Radio( | |
| choices=list(MODELS.keys()), | |
| value="DeepSeek-R1" | |
| ) | |
| with gr.Accordion("Optional Parameters", open=False): | |
| system_message = gr.Textbox( | |
| value="You are a helpful AI assistant", | |
| lines=2 | |
| ) | |
| max_new_tokens = gr.Slider(1, 4000, 200) | |
| temperature = gr.Slider(0.1, 4.0, 0.7) | |
| top_p = gr.Slider(0.1, 1.0, 0.9) | |
| chat_history = gr.State([]) | |
| submit_btn.click( | |
| chatbot, | |
| [msg, chat_history, model_choice, system_message, max_new_tokens, temperature, top_p], | |
| [chatbot_output, chat_history, msg] | |
| ) | |
| msg.submit( | |
| chatbot, | |
| [msg, chat_history, model_choice, system_message, max_new_tokens, temperature, top_p], | |
| [chatbot_output, chat_history, msg] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |