ZucchettiAI / app.py
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from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
def format_prompt(message, history):
prompt = "<s>"
with open('Manuale.txt', 'r') as file:
manual_content = file.read()
prompt += f"[INST]Leggi questo MANUALE dopo ti farò delle domande ***INIZIO_MANUALE***: [/INST] {manual_content} [INST] ***FINE_MANUALE***[/INST]"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt += f"[INST]Tu sei Zucchetti AI, il mio assistente personale di AdHoc e... io ho un problema in AdHoc, rispondi proponendo SOLO con soluzione relativa al problmea a partire dal manuale (testo tra ***INIZIO_MANUALE*** e ***FINE_MANUALE***): {message} [/INST]"
return prompt
def generate(
prompt, history, temperature=0.2, max_new_tokens=300, 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,
)
formatted_prompt = format_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", "./LogoAHR.jpg"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,value=[[None, "Ciao sono Zucchetti AI il tuo assistente personale per AdHoc Revolution…"]], )
demo = gr.ChatInterface(fn=generate,
chatbot=mychatbot,
title="Zucchetti AI",
textbox=gr.Textbox(placeholder="Descrivi il tuo problema..."),
theme="gradio/base",
submit_btn="Invia",
retry_btn=None,
undo_btn=None,
clear_btn="🗑️ Cancella"
)
demo.queue().launch(show_api=True)