| import streamlit as st | |
| from transformers import pipeline | |
| from gtts import gTTS | |
| import os | |
| # Load a public, PyTorch-compatible, conversational model | |
| def load_llm(): | |
| return pipeline("text-generation", | |
| model="declare-lab/flan-alpaca-base", | |
| tokenizer="declare-lab/flan-alpaca-base", | |
| max_new_tokens=100, | |
| do_sample=True, | |
| temperature=0.7) | |
| llm = load_llm() | |
| # Text-to-speech function | |
| def speak(text, filename="response.mp3"): | |
| tts = gTTS(text) | |
| tts.save(filename) | |
| audio_file = open(filename, "rb") | |
| st.audio(audio_file.read(), format="audio/mp3") | |
| os.remove(filename) | |
| # Streamlit UI | |
| st.set_page_config(page_title="AI Learning Buddy", page_icon="🧸") | |
| st.title("🧸 AI Learning Buddy (Ages 4–7)") | |
| st.markdown("Ask anything fun or educational and hear your buddy talk!") | |
| user_input = st.text_input("What would you like to ask?") | |
| if st.button("Ask the Buddy") and user_input: | |
| prompt = f"Explain to a 5-year-old: {user_input}" | |
| result = llm(prompt)[0]["generated_text"] | |
| answer = result.split(":")[-1].strip() | |
| st.markdown(f"**AI Buddy says:** {answer}") | |
| speak(answer) | |