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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) |