Update app.py

app.py

@@ -1,81 +1,13 @@
 import streamlit as st
 from huggingface_hub import InferenceClient
+from gtts import gTTS
 import base64
 from pydub import AudioSegment
-from io import BytesIO
-from gtts import gTTS
-from streamlit_webrtc import webrtc_streamer, WebRtcMode
-import speech_recognition as sr
-import sounddevice as sd  
+from pydub.playback import play
 
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
-pre_prompt = ""
+pre_prompt = "tu nombre es Chaman 3.0 una IA conducual, tus principios son el trashumanísmo ecológico."
 pre_prompt_sent = False
-webrtc_ctx = None 
-
-def take_user_input():
-    r = sr.Recognizer()
-
-    def audio_callback(in_data, frame_count, time_info, status):
-        global webrtc_ctx 
-        audio = sr.AudioData(
-            in_data.tobytes(),
-            sample_rate=webrtc_ctx.audio_sample_rate,
-            sample_width=sd.default.dtype.itemsize
-        )
-
-        st.info('Reconociendo...')
-        query = transcribe_speech(audio)
-
-        if 'salir' in query or 'detener' in query:
-            speak("Hasta luego.")
-            exit()
-        return query
-
-    global webrtc_ctx 
-    webrtc_ctx = webrtc_streamer(
-        key="microphone",
-        mode=WebRtcMode.SENDRECV,
-        audio_receiver=audio_callback,
-        async_processing=True,
-    )
-
-    if not webrtc_ctx:
-        st.warning("Por favor, habilita el micrófono.")
-        return 'None'
-
-    st.info('Escuchando...')
-
-    try:
-        with sd.InputStream(callback=lambda indata, frames, time, status: None):
-            while True:
-                audio_data = webrtc_ctx.audio_receiver_stream.get()
-                if audio_data:
-                    audio = sr.AudioData(
-                        audio_data.tobytes(),
-                        sample_rate=webrtc_ctx.audio_sample_rate,
-                        sample_width=audio_data.itemsize
-                    )
-
-                    st.info('Reconociendo...')
-
-                    query = transcribe_speech(audio)
-
-                    if 'salir' in query or 'detener' in query:
-                        speak("Hasta luego.")
-                        exit()
-                    return query
-
-    except sr.UnknownValueError:
-        speak('No se ha reconocido nada. Intenta de nuevo...')
-    except sr.RequestError as e:
-        st.error(f"Error en la solicitud al reconocimiento de voz: {e}")
-
-    return 'None'
-
-
-def audio_callback(in_data, frame_count, time_info, status):
-    return in_data, webrtc_ctx.audio_sample_rate
 
 def format_prompt(message, history):
     global pre_prompt_sent
@@ -91,13 +23,24 @@ def format_prompt(message, history):
 
     prompt += f"[INST] {message} [/INST]"
     return prompt
-    
+
+def text_to_speech(text, speed=1.3):
+    tts = gTTS(text=text, lang='es')
+    audio_file_path = 'output.mp3'
+    tts.save(audio_file_path)
+    sound = AudioSegment.from_mp3(audio_file_path)
+    sound = sound.speedup(playback_speed=speed)
+    sound.export(audio_file_path, format="mp3")
+
+    return audio_file_path
+
 def generate(user_input, history, temperature=None, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
     global pre_prompt_sent
     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,
@@ -108,38 +51,30 @@ def generate(user_input, history, temperature=None, max_new_tokens=512, top_p=0.
     )
 
     formatted_prompt = format_prompt(user_input, 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
     
-    try:
-        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_bytes = text_to_speech(response)
-        return response, audio_bytes
-    except Exception as e:
-        return str(e), None
-
-def text_to_speech(text):
-    tts = gTTS(text=text, lang='es')
-    audio_stream = BytesIO()
-    tts.save(audio_stream)
-    audio_stream.seek(0)
-    return audio_stream.read()
+    response = ' '.join(response.split()).replace('</s>', '')
+
+    audio_file_path = text_to_speech(response, speed=1.3) 
+    audio_file = open(audio_file_path, 'rb')
+    audio_bytes = audio_file.read()
 
-def speak(text):
-    audio_bytes = text_to_speech(text)
-    st.audio(audio_bytes, format="audio/mp3", start_time=0, key="audio_player")
+    return response, audio_bytes
 
 if "history" not in st.session_state:
     st.session_state.history = []
 
-user_input = take_user_input()
-output, audio_bytes = generate(user_input, history=st.session_state.history)
+with st.container():
+    user_input = st.text_input(label="Usuario", value="")
+    output, audio_bytes = generate(user_input, history=st.session_state.history)
+    st.text_area("Respuesta", height=400, value=output, key="output_text", disabled=True)
 
-with st.container(width=900, height=400):
-    user_input_container = st.text_input("Tu entrada de usuario", value=user_input)
-    st.text_area("Respuesta", value=output, key="output_text", disabled=True)
+    if user_input:
+        st.session_state.history.append((user_input, output))
 
 if audio_bytes is not None:
     st.markdown(