import gradio as gr from huggingface_hub import InferenceClient import random models=[ "google/gemma-7b", "google/gemma-7b-it", "google/gemma-2b", "google/gemma-2b-it" ] clients=[ InferenceClient(models[0]), InferenceClient(models[1]), InferenceClient(models[2]), InferenceClient(models[3]), ] def format_prompt(message, history): prompt = "" if history: #userHow does the brain work?model for user_prompt, bot_response in history: prompt += f"user{user_prompt}" prompt += f"model{bot_response}" prompt += f"user{message}model" return prompt def chat_inf(system_prompt,prompt,history,client_choice,seed,temp,tokens,top_p,rep_p): #token max=8192 client=clients[int(client_choice)-1] if not history: history = [] hist_len=0 if history: hist_len=len(history) print(hist_len) #seed = random.randint(1,1111111111111111) generate_kwargs = dict( temperature=temp, max_new_tokens=tokens, top_p=top_p, repetition_penalty=rep_p, do_sample=True, seed=seed, ) #formatted_prompt=prompt 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 [(prompt,output)] history.append((prompt,output)) yield history def clear_fn(): return None,None,None rand_val=random.randint(1,1111111111111111) def check_rand(inp,val): if inp==True: return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=random.randint(1,1111111111111111)) else: return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val)) with gr.Blocks() as app: gr.HTML("""

Google Gemma Models


running on Huggingface Inference Client


EXPERIMENTAL""") with gr.Group(): chat_b = gr.Chatbot() with gr.Row(): with gr.Column(scale=3): inp = gr.Textbox(label="Prompt") sys_inp = gr.Textbox(label="System Prompt (optional)") client_choice=gr.Dropdown(label="Models",type='index',choices=[c for c in models],value=models[0],interactive=True) with gr.Row(): with gr.Column(scale=2): btn = gr.Button("Chat") with gr.Column(scale=1): with gr.Group(): stop_btn=gr.Button("Stop") clear_btn=gr.Button("Clear") with gr.Column(scale=1): with gr.Group(): rand = gr.Checkbox(label="Random", value=True) seed=gr.Slider(label="Seed", minimum=1, maximum=1111111111111111,step=1, value=rand_val) tokens = gr.Slider(label="Max new tokens",value=6400,minimum=0,maximum=8000,step=64,interactive=True, visible=True,info="The maximum number of tokens") temp=gr.Slider(label="Temperature",step=0.01, minimum=0.01, maximum=1.0, value=0.9) top_p=gr.Slider(label="Top-P",step=0.01, minimum=0.01, maximum=1.0, value=0.9) rep_p=gr.Slider(label="Repetition Penalty",step=0.1, minimum=0.1, maximum=2.0, value=1.0) go=btn.click(check_rand,[rand,seed],seed).then(chat_inf,[sys_inp,inp,chat_b,client_choice,seed,temp,tokens,top_p,rep_p],chat_b) stop_btn.click(None,None,None,cancels=go) clear_btn.click(clear_fn,None,[inp,sys_inp,chat_b]) app.queue(default_concurrency_limit=10).launch()