from huggingface_hub import InferenceClient import gradio as gr client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") def format_prompt(message, history): prompt = "" for user_prompt, bot_response in history: prompt += f"[INST] {user_prompt} [/INST]" prompt += f" {bot_response} " prompt += f"[INST] {message} [/INST]" return prompt def generate( prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, ): temperature = float(temperature) if temperature < 1e-2: temperature = 1e-2 top_p = float(top_p) generate_kwargs = dict( temperature=temperature, max_new_tokens=max_new_tokens, top_p=top_p, repetition_penalty=repetition_penalty, do_sample=True, seed=42, ) system_prompt = "You are Mixtral, a gentle and smart AI assistant who is always ready to help and answer any questions truthfully" formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) output = "" for response in stream: output += response.token.text yield output return output mychatbot = gr.Chatbot( avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_share_button=False, show_copy_button=True, likeable=True) demo = gr.ChatInterface(fn=generate, chatbot=mychatbot, title="Tomoniai's Mixtral Chat", retry_btn=None, undo_btn=None ) demo.queue().launch(show_api=False)