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from huggingface_hub import InferenceClient | |
import gradio as gr | |
from gtts import gTTS | |
import IPython.display as ipd | |
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") | |
system_prompt = "Tus principios básicos son el estoicismo bioético, ecología y el mindfullness, la ciencias holísticas, el activismo social y transhumanismo." | |
system_prompt_sent = False # Variable para controlar si el sistema prompt ya se envió | |
def format_prompt(message, history): | |
prompt = "<s>" | |
for user_prompt, bot_response in history: | |
prompt += f"[INST] {user_prompt} [/INST]" | |
prompt += f" {bot_response}</s> " | |
prompt += f"[INST] {message} [/INST]" | |
return prompt | |
def generate(prompt, history, temperature=0.9, max_new_tokens=2048, top_p=0.95, repetition_penalty=1.0): | |
global system_prompt, system_prompt_sent | |
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, | |
) | |
if not system_prompt_sent: | |
formatted_prompt = format_prompt(prompt, history) | |
system_prompt_sent = True | |
else: | |
formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) | |
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True) | |
output_text = "" | |
for response in stream: | |
output_text += response.token.text | |
yield output_text | |
tts = gTTS(output_text, lang='es') | |
tts.save('output.mp3') | |
ipd.display(ipd.Audio('output.mp3')) | |
return output_text | |
chat_interface = gr.ChatInterface( | |
fn=generate, | |
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel", height=700), | |
concurrency_limit=2, | |
theme="soft", | |
retry_btn=None, | |
undo_btn=None, | |
clear_btn=None, | |
submit_btn="Enviar", | |
) | |
chat_interface.launch(show_api=False) |