app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
from gtts import gTTS
import torch
import os

# Load DialoGPT model for conversational style
model_name = "microsoft/DialoGPT-medium"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Set up a text generation pipeline with the conversational model
generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if torch.cuda.is_available() else -1)

# Function to generate Trump-like response
def generate_response(prompt):
    # Craft the prompt to encourage a Trump-like response
    trump_prompt = f"Imagine you are Donald Trump. Respond in your style to: {prompt}"
    
    # Generate the response
    response = generator(trump_prompt, max_length=50, num_return_sequences=1, temperature=0.6)
    return response[0]['generated_text']

# Function to convert text to audio using gTTS
def generate_audio(text):
    tts = gTTS(text=text, lang="en")
    audio_path = "output.mp3"
    tts.save(audio_path)
    return audio_path

# Streamlit app UI
st.title("Trump-like Chat Assistant")
st.write("Type in a question or statement, and receive a 'Trump-style' response in both text and audio!")

# Text input from user
user_input = st.text_input("Your message:", "Enter a message here")

if user_input:
    # Generate Trump-like response
    trump_response = generate_response(user_input)
    
    # Display text output of the response
    st.subheader("Trump-like Assistant (Text Response):")
    st.write(trump_response)  # Show the generated text directly
    
    # Convert response to audio
    audio_output_path = generate_audio(trump_response)
    
    # Ensure the file exists and can be played back
    if os.path.exists(audio_output_path):
        with open(audio_output_path, "rb") as audio_file:
            audio_bytes = audio_file.read()
            # Display audio output
            st.subheader("Trump-like Assistant (Audio Response):")
            st.audio(audio_bytes, format="audio/mp3")
    else:
        st.error("Failed to generate audio. Please try again.")