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import streamlit as st
from huggingface_hub import InferenceClient
from gtts import gTTS
import base64
import os
from langdetect import detect, DetectorFactory
# To ensure consistent results from langdetect
DetectorFactory.seed = 0
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def generate_response(message, system_message, max_tokens, temperature, top_p):
messages = [{"role": "system", "content": system_message}]
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
# Generate speech from the response text using gTTS
tts = gTTS(text=response, lang='en' if detect(message) == 'en' else 'ar')
audio_file = "response.mp3"
tts.save(audio_file)
return response, audio_file
def get_base64_audio(audio_file):
with open(audio_file, "rb") as f:
audio_data = f.read()
return base64.b64encode(audio_data).decode()
st.title("A Chatbot with Voice Response")
message = st.text_input("Enter your message:")
system_message = st.text_input("System message:", value="You are a friendly Chatbot.")
max_tokens = st.slider("Max new tokens", 1, 2048, 512)
temperature = st.slider("Temperature", 0.1, 4.0, 0.7, step=0.1)
top_p = st.slider("Top-p (nucleus sampling)", 0.1, 1.0, 0.95, step=0.05)
if st.button("Generate Response"):
response, audio_file = generate_response(message, system_message, max_tokens, temperature, top_p)
st.write(response)
# Get base64 encoded audio data
audio_base64 = get_base64_audio(audio_file)
# HTML to autoplay the audio
audio_html = f"""
<audio controls autoplay>
<source src="data:audio/mp3;base64,{audio_base64}" type="audio/mp3">
Your browser does not support the audio element.
</audio>
"""
st.markdown(audio_html, unsafe_allow_html=True)
# Clean up the audio file
os.remove(audio_file)
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