import streamlit as st from huggingface_hub import InferenceClient from gtts import gTTS import os 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') audio_file = "response.mp3" tts.save(audio_file) return response, audio_file st.title("Hi (:") 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) # Add HTML to autoplay the audio audio_html = f""" """ st.markdown(audio_html, unsafe_allow_html=True)