import gradio as gr from huggingface_hub import InferenceClient """ For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference """ #client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") client = InferenceClient("unsloth/Llama-3.2-1B-Instruct") def respond( message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p, ): messages = [{"role": "system", "content": system_message}] for val in history: if val[0]: messages.append({"role": "user", "content": val[0]}) if val[1]: messages.append({"role": "assistant", "content": val[1]}) messages.append({"role": "user", "content": message}) response = "" try: for message in client.chat_completion( messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p, ): # Ensure the message has a valid structure if not message or not isinstance(message, dict): continue try: # Extract content and finish reason content = message.choices[0].delta.content finish_reason = message.choices[0].finish_reason # Check if the content is empty if content.strip() == "": # If the finish reason is 'stop', it's expected and we can break the loop if finish_reason == "stop": print("Stream ended normally.") break else: print("Received unexpected empty content, skipping...") continue response += content yield response except (AttributeError, IndexError, KeyError) as e: print(f"Error processing message: {e}") continue except Exception as e: print(f"Unexpected error: {e}") yield "An error occurred while generating the response." # Final check if the response is empty if response.strip() == "": yield "No response generated. Please try again or adjust the settings." """ For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface """ demo = gr.ChatInterface( respond, additional_inputs=[ gr.Textbox(value="You are a friendly Chatbot. Your name is Juninho.", label="System message"), gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), gr.Slider( minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)", ), ], ) if __name__ == "__main__": demo.launch()