app.py

import streamlit as st
from transformers import pipeline

# Load the pipeline from Hugging Face
@st.cache_resource
def load_pipeline():
    pipe = pipeline("text-generation", model="kshitij230/Eunoia")
    return pipe

pipe = load_pipeline()

# Streamlit page config
st.set_page_config(page_title="Eunoia 💜", layout="centered")
st.title("🫂 Eunoia - Your Emotional Support Bot")
st.markdown("Speak your heart. I'm here to listen and help 💖")

# Chat history
if "messages" not in st.session_state:
    st.session_state.messages = []

# Show history
for msg in st.session_state.messages:
    with st.chat_message(msg["role"]):
        st.markdown(msg["content"])

# Input box
user_input = st.chat_input("What's on your mind?")

if user_input:
    # Display user message
    st.chat_message("user").markdown(user_input)
    st.session_state.messages.append({"role": "user", "content": user_input})

    # Build conversation prompt
    prompt = ""
    for msg in st.session_state.messages:
        role = "User" if msg["role"] == "user" else "Bot"
        prompt += f"{role}: {msg['content']}\n"
    prompt += "Bot:"

    # Generate model response
    with st.spinner("Eunoia is listening..."):
        response = pipe(
            prompt,
            max_length=200,
            do_sample=True,
            temperature=0.7,
            top_k=50,
            top_p=0.95,
            repetition_penalty=1.2,
            pad_token_id=pipe.tokenizer.eos_token_id
        )[0]["generated_text"]

        # Remove the prompt from the response
        reply = response[len(prompt):].strip()

    # Display bot reply
    st.chat_message("assistant").markdown(reply)
    st.session_state.messages.append({"role": "assistant", "content": reply})