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import io
import base64
import webrtcvad
import threading
import numpy as np
from gtts import gTTS
import streamlit as st
import sounddevice as sd
import speech_recognition as sr
from huggingface_hub import InferenceClient
devices = sd.query_devices()
print(devices)
if "history" not in st.session_state:
st.session_state.history = []
if "pre_prompt_sent" not in st.session_state:
st.session_state.pre_prompt_sent = False
gatherUsageStats = "false"
pre_prompt_text = "eres una IA conductual, tus respuestas ser谩n breves."
def recognize_speech(audio_data, show_messages=True):
recognizer = sr.Recognizer()
audio_recording = sr.AudioFile(audio_data)
with audio_recording as source:
audio = recognizer.record(source)
try:
audio_text = recognizer.recognize_google(audio, language="es-ES")
if show_messages:
st.subheader("Texto Reconocido:")
st.write(audio_text)
st.success("Reconocimiento de voz completado.")
except sr.UnknownValueError:
st.warning("No se pudo reconocer el audio. 驴Intentaste grabar algo?")
audio_text = ""
except sr.RequestError:
st.error("Hablame para comenzar!")
audio_text = ""
return audio_text
def format_prompt(message, history):
prompt = "<s>"
if not st.session_state.pre_prompt_sent:
prompt += f"[INST]{pre_prompt_text}[/INST]"
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(audio_text, history, temperature=None, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
temperature = float(temperature) if temperature is not None else 0.9
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(audio_text, history)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
response = ""
for response_token in stream:
response += response_token.token.text
response = ' '.join(response.split()).replace('</s>', '')
audio_file = text_to_speech(response, speed=1.3)
return response, audio_file
def text_to_speech(text, speed=1.3):
tts = gTTS(text=text, lang='es')
audio_fp = io.BytesIO()
tts.write_to_fp(audio_fp)
audio_fp.seek(0)
return audio_fp
def audio_play(audio_fp):
st.audio(audio_fp.read(), format="audio/mp3", start_time=0)
def display_recognition_result(audio_text, output, audio_file):
if audio_text:
st.session_state.history.append((audio_text, output))
if audio_file is not None:
st.markdown(
f"""<audio autoplay="autoplay" controls="controls" src="data:audio/mp3;base64,{base64.b64encode(audio_file.read()).decode()}" type="audio/mp3" id="audio_player"></audio>""",
unsafe_allow_html=True)
def voice_activity_detection(audio_data):
return vad.is_speech(audio_data, sample_rate)
def audio_callback(indata, frames, time, status):
assert frames == block_size
audio_data = indata[::downsample, mapping]
audio_data = map(lambda x: (x + 1) / 2, audio_data)
audio_data = np.fromiter(audio_data, np.float16)
audio_data = audio_data.tobytes()
detection = voice_activity_detection(audio_data)
print(detection)
def start_stream():
stream.start()
class Threader(threading.Thread):
def __init__(self, *args, **kwargs):
threading.Thread.__init__(self, *args, **kwargs)
self.start()
def run(self):
if self.name == 'mythread':
print("Started mythread")
start_stream()
if __name__ == "__main__":
vad = webrtcvad.Vad(1)
channels = [1]
mapping = [c - 1 for c in channels]
device_info = sd.query_devices(16, 'input')
sample_rate = int(device_info['default_samplerate'])
interval_size = 10
downsample = 1
block_size = int(sample_rate * interval_size / 1000)
Threader(name='mythread')
st.button("Detener Stream")
st.text("Esperando entrada de voz...")
st.text("Puedes detener el stream manualmente usando el bot贸n 'Detener Stream'.")
st.text("Nota: El c贸digo actual imprime los resultados de VAD en la consola.")
st.text("Puedes personalizar la l贸gica de VAD seg煤n tus necesidades.")
st.text("La transcripci贸n de voz y la generaci贸n de texto se manejar谩n una vez que se detecte actividad de voz.")
st.text("Inicia la grabaci贸n y espera a que aparezcan los resultados.") |