app.py

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 chat_inf(system_prompt,prompt,history,client_choice):
    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=0.9,
        max_new_tokens=10480,
        top_p=0.95,
        repetition_penalty=1.0,
        do_sample=True,
        seed=seed,
    )
        
    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

with gr.Blocks() as app:
    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)")
                btn = gr.Button("Chat")
                
            with gr.Column(scale=1):
                with gr.Group():
                    stop_btn=gr.Button("Stop")
                    clear_btn=gr.Button("Clear")
        client_choice=gr.Dropdown(label="Models",type='index',choices=[c for c in models],value=models[0],interactive=True)
    btn.click(chat_inf,[sys_inp,inp,chat_b,client_choice],chat_b)
app.launch()