app.py

import streamlit as st
import PyPDF2
import requests
import json
from sentence_transformers import SentenceTransformer
import numpy as np
from sklearn.metrics.pairwise import cosine_similarity
import os
from datetime import datetime

# Page configuration
st.set_page_config(
    page_title="🚨 First Aid Emergency Assistant",
    page_icon="🚨",
    layout="wide",
    initial_sidebar_state="collapsed"
)

# Custom CSS for ChatGPT-like interface
st.markdown("""
<style>
    .stApp {
        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
    }
    
    .main-header {
        text-align: center;
        padding: 1rem 0;
        background: rgba(255, 255, 255, 0.1);
        border-radius: 15px;
        margin-bottom: 2rem;
        backdrop-filter: blur(10px);
        border: 1px solid rgba(255, 255, 255, 0.2);
    }
    
    .chat-container {
        background: white;
        border-radius: 15px;
        padding: 1rem;
        margin: 1rem 0;
        box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1);
        border: 1px solid rgba(255, 255, 255, 0.2);
        max-height: 500px;
        overflow-y: auto;
    }
    
    .user-message {
        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        color: white;
        padding: 12px 16px;
        border-radius: 18px 18px 5px 18px;
        margin: 8px 0 8px 20%;
        max-width: 80%;
        float: right;
        clear: both;
        box-shadow: 0 2px 10px rgba(102, 126, 234, 0.3);
    }
    
    .bot-message {
        background: #f8f9fa;
        color: #333;
        padding: 12px 16px;
        border-radius: 18px 18px 18px 5px;
        margin: 8px 20% 8px 0;
        max-width: 80%;
        float: left;
        clear: both;
        border: 1px solid #e9ecef;
        box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
    }
    
    .input-container {
        position: sticky;
        bottom: 0;
        background: white;
        padding: 1rem;
        border-radius: 15px;
        margin-top: 2rem;
        box-shadow: 0 -4px 20px rgba(0, 0, 0, 0.1);
    }
    
    .warning-box {
        background: linear-gradient(135deg, #ff9a9e 0%, #fecfef 100%);
        padding: 1rem;
        border-radius: 10px;
        margin: 1rem 0;
        border-left: 4px solid #ff6b6b;
    }
    
    .stTextInput input {
        border-radius: 25px !important;
        border: 2px solid #e9ecef !important;
        padding: 12px 20px !important;
        font-size: 16px !important;
    }
    
    .stTextInput input:focus {
        border-color: #667eea !important;
        box-shadow: 0 0 0 0.2rem rgba(102, 126, 234, 0.25) !important;
    }
    
    .stButton button {
        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
        color: white !important;
        border: none !important;
        border-radius: 25px !important;
        padding: 12px 30px !important;
        font-weight: 600 !important;
        transition: all 0.3s ease !important;
    }
    
    .stButton button:hover {
        transform: translateY(-2px) !important;
        box-shadow: 0 5px 15px rgba(102, 126, 234, 0.4) !important;
    }
    
    .sidebar-info {
        background: rgba(255, 255, 255, 0.1);
        padding: 1rem;
        border-radius: 10px;
        margin: 1rem 0;
    }
</style>
""", unsafe_allow_html=True)

# Initialize GROQ API

@st.cache_resource
def setup_groq():
    os.getenv("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")
    if not groq_api_key:
        st.error("⚠️ GROQ API key not found! Please add it to your Hugging Face secrets.")
        st.stop()
    return groq_api_key

# Load and process PDF
@st.cache_resource
def load_pdf():
    try:
        with open("First-Aid.pdf", "rb") as file:
            pdf_reader = PyPDF2.PdfReader(file)
            text = ""
            for page in pdf_reader.pages:
                text += page.extract_text() + "\n"
        return text
    except FileNotFoundError:
        st.error("📄 First-Aid.pdf not found! Please upload the PDF file to your space.")
        st.stop()
    except Exception as e:
        st.error(f"❌ Error loading PDF: {str(e)}")
        st.stop()

# Setup embeddings and knowledge base
@st.cache_resource
def setup_knowledge_base():
    # Load PDF content
    pdf_text = load_pdf()
    
    # Split text into chunks
    chunks = []
    sentences = pdf_text.split('\n')
    current_chunk = ""
    
    for sentence in sentences:
        if len(current_chunk + sentence) < 1000:
            current_chunk += sentence + "\n"
        else:
            if current_chunk.strip():
                chunks.append(current_chunk.strip())
            current_chunk = sentence + "\n"
    
    if current_chunk.strip():
        chunks.append(current_chunk.strip())
    
    # Load sentence transformer model
    model = SentenceTransformer('all-MiniLM-L6-v2')
    
    # Create embeddings for chunks
    chunk_embeddings = model.encode(chunks)
    
    return chunks, chunk_embeddings, model

def find_relevant_context(query, chunks, chunk_embeddings, model, top_k=3):
    """Find most relevant chunks for the query"""
    query_embedding = model.encode([query])
    similarities = cosine_similarity(query_embedding, chunk_embeddings)[0]
    top_indices = np.argsort(similarities)[-top_k:][::-1]
    
    relevant_chunks = [chunks[i] for i in top_indices]
    return "\n\n".join(relevant_chunks)

def query_groq(prompt, api_key):
    """Query GROQ API"""
    url = "https://api.groq.com/openai/v1/chat/completions"
    
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json"
    }
    
    data = {
        "model": "mixtral-8x7b-32768",
        "messages": [
            {
                "role": "system",
                "content": """You are a First Aid Emergency Assistant. You provide clear, step-by-step first aid guidance based on the provided medical manual context. 

IMPORTANT RULES:
1. Only answer questions related to first aid, medical emergencies, and health safety
2. If asked about non-medical topics, politely redirect to first aid topics
3. For serious emergencies, always remind users to call emergency services first
4. Provide clear, numbered steps when giving instructions
5. Keep responses focused and practical

If the question is not related to first aid or medical emergencies, respond with: "🚨 I'm specialized in First Aid emergencies only! Please ask me about medical emergencies, CPR, wounds, burns, fractures, or other first aid topics."
"""
            },
            {
                "role": "user",
                "content": prompt
            }
        ],
        "temperature": 0.3,
        "max_tokens": 1000
    }
    
    try:
        response = requests.post(url, headers=headers, json=data, timeout=30)
        response.raise_for_status()
        return response.json()["choices"][0]["message"]["content"]
    except requests.exceptions.RequestException as e:
        return f"❌ Error connecting to GROQ API: {str(e)}"
    except Exception as e:
        return f"❌ Error processing response: {str(e)}"

# Initialize session state
if "messages" not in st.session_state:
    st.session_state.messages = [
        {
            "role": "assistant", 
            "content": "🚨 **Hello! I'm your First Aid Emergency Assistant.**\n\nI can help you with:\n• CPR procedures\n• Bleeding control\n• Burns treatment\n• Choking response\n• Fracture management\n• Poisoning emergencies\n• And much more!\n\n💡 **Ask me anything about first aid emergencies!**"
        }
    ]

if "knowledge_base" not in st.session_state:
    with st.spinner("🔄 Loading First Aid knowledge base..."):
        chunks, embeddings, model = setup_knowledge_base()
        st.session_state.knowledge_base = {
            "chunks": chunks,
            "embeddings": embeddings,
            "model": model
        }

if "groq_api_key" not in st.session_state:
    st.session_state.groq_api_key = setup_groq()

# Header
st.markdown("""
<div class="main-header">
    <h1>🚨 First Aid Emergency Assistant</h1>
    <p style="margin: 0; font-size: 18px; opacity: 0.9;">Your AI-powered emergency response guide</p>
</div>
""", unsafe_allow_html=True)

# Warning disclaimer
st.markdown("""
<div class="warning-box">
    <strong>⚠️ IMPORTANT MEDICAL DISCLAIMER:</strong><br>
    This chatbot provides general first aid guidance only. In real emergencies, always call emergency services immediately. 
    This tool is not a substitute for professional medical advice, diagnosis, or treatment.
</div>
""", unsafe_allow_html=True)

# Chat container
chat_container = st.container()

with chat_container:
    st.markdown('<div class="chat-container">', unsafe_allow_html=True)
    
    # Display chat messages
    for message in st.session_state.messages:
        if message["role"] == "user":
            st.markdown(f"""
            <div class="user-message">
                <strong>You:</strong> {message["content"]}
            </div>
            <div style="clear: both;"></div>
            """, unsafe_allow_html=True)
        else:
            st.markdown(f"""
            <div class="bot-message">
                <strong>🤖 First Aid Assistant:</strong><br>
                {message["content"]}
            </div>
            <div style="clear: both;"></div>
            """, unsafe_allow_html=True)
    
    st.markdown('</div>', unsafe_allow_html=True)

# Input section
st.markdown('<div class="input-container">', unsafe_allow_html=True)

col1, col2 = st.columns([4, 1])

with col1:
    user_input = st.text_input(
        "",
        placeholder="Ask me about first aid emergencies... (e.g., 'How to treat burns?')",
        key="user_input",
        label_visibility="collapsed"
    )

with col2:
    send_button = st.button("Send 🚀", key="send_button")

st.markdown('</div>', unsafe_allow_html=True)

# Process user input
if send_button and user_input.strip():
    # Add user message to chat
    st.session_state.messages.append({"role": "user", "content": user_input})
    
    # Get bot response
    with st.spinner("🤔 Thinking..."):
        try:
            # Find relevant context from PDF
            kb = st.session_state.knowledge_base
            context = find_relevant_context(
                user_input, 
                kb["chunks"], 
                kb["embeddings"], 
                kb["model"]
            )
            
            # Create enhanced prompt with context
            enhanced_prompt = f"""
Based on the following first aid manual content, answer this question: {user_input}

Context from First Aid Manual:
{context}

Please provide a clear, helpful response based on this information. If this is a serious emergency, remind the user to call emergency services first.
"""
            
            # Query GROQ API
            response = query_groq(enhanced_prompt, st.session_state.groq_api_key)
            
            # Enhance response with emergency reminder for serious cases
            serious_keywords = ['heart attack', 'stroke', 'unconscious', 'not breathing', 'severe bleeding', 'poisoning', 'choking']
            if any(keyword in user_input.lower() for keyword in serious_keywords):
                response = f"🚨 **CALL EMERGENCY SERVICES IMMEDIATELY!**\n\n{response}"
                
        except Exception as e:
            response = f"❌ Sorry, I encountered an error: {str(e)}. Please try asking your question differently."
    
    # Add bot response to chat
    st.session_state.messages.append({"role": "assistant", "content": response})
    
    # Rerun to show new message
    st.rerun()

# Sidebar with helpful information
with st.sidebar:
    st.markdown("## 📋 Quick Emergency Numbers")
    st.markdown("""
    <div class="sidebar-info">
    <strong>🚨 Emergency Services:</strong><br>
    • General Emergency: 911<br>
    • Poison Control: 1-800-222-1222<br>
    • Mental Health Crisis: 988
    </div>
    """, unsafe_allow_html=True)
    
    st.markdown("## 🎯 What I Can Help With")
    st.markdown("""
    <div class="sidebar-info">
    • CPR and rescue breathing<br>
    • Wound care and bleeding<br>
    • Burns and scalds<br>
    • Fractures and sprains<br>
    • Choking procedures<br>
    • Poisoning emergencies<br>
    • Heart attack signs<br>
    • Snake and animal bites<br>
    • Drowning response<br>
    • And much more!
    </div>
    """, unsafe_allow_html=True)
    
    st.markdown("## ℹ️ How to Use")
    st.markdown("""
    <div class="sidebar-info">
    1. Type your first aid question<br>
    2. Get instant step-by-step guidance<br>
    3. Follow instructions carefully<br>
    4. Seek professional help for serious emergencies
    </div>
    """, unsafe_allow_html=True)

# Footer
st.markdown("---")
st.markdown("""
<div style="text-align: center; opacity: 0.7; padding: 1rem;">
    🤖 First Aid Emergency Assistant | Powered by GROQ AI | Always consult medical professionals for serious emergencies
</div>
""", unsafe_allow_html=True)