app.py

import streamlit as st
#from transformers import AutoTokenizer
from llama_cpp import Llama
from transformers import pipeline
#from peft import PeftModel, PeftConfig
#from transformers import AutoModelForCausalLM
from datasets import load_dataset

# Replace with the direct image URL
flower_image_url = "https://i.postimg.cc/hG2FG85D/2.png"

# Inject custom CSS for the background with a centered and blurred image
st.markdown(
    f"""
    <style>
    /* Container for background */
    html, body {{
        margin: 0;
        padding: 0;
        overflow: hidden;
    }}
    [data-testid="stAppViewContainer"] {{
        position: relative;
        z-index: 1; /* Ensure UI elements are above the background */
    }}
    /* Blurred background image */
    .blurred-background {{
        position: fixed;
        top: 0;
        left: 0;
        width: 100%;
        height: 100%;
        z-index: -1; /* Send background image behind all UI elements */
        background-image: url("{flower_image_url}");
        background-size: cover;
        background-position: center;
        filter: blur(10px); /* Adjust blur ratio here */
        opacity: 0.8; /* Optional: Add slight transparency for a subtle effect */
    }}
    </style>
    """,
    unsafe_allow_html=True
)

# Add the blurred background div
st.markdown('<div class="blurred-background"></div>', unsafe_allow_html=True)

#"""""""""""""""""""""""""   Application Code Starts here   """""""""""""""""""""""""""""""""""""""""""""

# Path to the GGUF model file
MODEL_PATH = "QuantFactory/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2-GGUF/model.gguf"

# Load Llama model
@st.cache_resource
def load_llama_model():
    try:
        return Llama(model_path=MODEL_PATH, n_threads=8)  # Adjust `n_threads` based on your system
    except Exception as e:
        st.error(f"Error loading model: {e}")
        return None

llama_model = load_llama_model()

# Load counseling dataset
@st.cache_resource
def load_counseling_dataset():
    return load_dataset("Amod/mental_health_counseling_conversations")

dataset = load_counseling_dataset()

# Streamlit App
st.title("Mental Health Counseling Chat")
st.markdown("""
Welcome to the **Mental Health Counseling Chat Application**.  
This platform is designed to provide **supportive, positive, and encouraging responses** based on mental health counseling expertise.
""")

# Check if the model loaded correctly
if llama_model is None:
    st.error("The text generation model could not be loaded. Please check your configuration.")
else:
    # Explore dataset for additional context or resources (optional)
    if st.checkbox("Show Example Questions and Answers from Dataset"):
        sample = dataset["train"].shuffle(seed=42).select(range(3))  # Display 3 random samples
        for example in sample:
            st.markdown(f"**Question:** {example.get('context', 'N/A')}")
            st.markdown(f"**Answer:** {example.get('response', 'N/A')}")
            st.markdown("---")

    # User input for mental health concerns
    user_input = st.text_area("Your question or concern:", placeholder="Type your question here...")

    if st.button("Get Supportive Response"):
        if user_input.strip():
            try:
                # Generate response using Llama
                prompt = f"User: {user_input}\nCounselor:"
                response = llama_model(prompt, max_tokens=200, stop=["\n", "User:"])
                
                # Extract and display the response
                st.subheader("Counselor's Response:")
                st.write(response["choices"][0]["text"].strip())
            except Exception as e:
                st.error(f"An error occurred while generating the response: {e}")
        else:
            st.error("Please enter a question or concern to receive a response.")

    # Sidebar resources
    st.sidebar.header("Additional Mental Health Resources")
    st.sidebar.markdown("""
    - [Mental Health Foundation](https://www.mentalhealth.org)
    - [Mind](https://www.mind.org.uk)
    - [National Suicide Prevention Lifeline](https://suicidepreventionlifeline.org)
    """)

    st.sidebar.info("This application is not a replacement for professional counseling. If you are in crisis, please seek professional help immediately.")