app.py

import os
import tempfile
import gc
import logging
import streamlit as st
from groq import Groq, APIError
from langchain_community.document_loaders import PyPDFLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import Chroma
import torch

# ---------------- CONFIGURATION ----------------
logging.basicConfig(level=logging.INFO)

# Load API key from Hugging Face secrets
GROQ_API_KEY = st.secrets.get("GROQ_API_KEY", os.environ.get("GROQ_API_KEY"))
GROQ_MODEL = "llama-3.1-8b-instant"

# Initialize Groq client
client = None
if GROQ_API_KEY:
    try:
        client = Groq(api_key=GROQ_API_KEY)
        logging.info("✅ Groq client initialized successfully.")
    except Exception as e:
        st.error(f"❌ Failed to initialize Groq client: {e}")
        client = None
else:
    st.warning("⚠️ GROQ_API_KEY not found. Please add it to Hugging Face secrets.")

# ---------------- STREAMLIT UI SETUP ----------------
st.set_page_config(page_title="PDF Assistant", page_icon="📘", layout="wide")

# ---------------- CSS ----------------
st.markdown("""
<style>
/* 1. GLOBAL RESET & SCROLL LOCK */
html, body {
    overflow: hidden;
    height: 100%;
    margin: 0;
}

/* 2. HIDE DEFAULT STREAMLIT ELEMENTS */
header[data-testid="stHeader"] {
    display: none;
}
footer {
    display: none;
}

/* 3. SIDEBAR STYLING (INDEPENDENT LEFT PANEL SCROLL) */
[data-testid="stSidebar"] {
    position: fixed;
    top: 0;
    left: 0;
    height: 100vh;
    width: 20rem;
    overflow-y: auto !important;
    z-index: 99999;
}
[data-testid="stSidebar"]::-webkit-scrollbar {
    width: 6px;
}
[data-testid="stSidebar"]::-webkit-scrollbar-thumb {
    background: #2d3748;
    border-radius: 3px;
}

/* 4. FIXED HEADER STYLING */
.fixed-header {
    position: fixed;
    top: 0;
    left: 0;
    width: 100%;
    height: 6rem;
    background-color: #0e1117; 
    z-index: 99998;
    display: flex;
    flex-direction: column;
    justify-content: center;
    align-items: center;
    border-bottom: 1px solid rgba(255, 255, 255, 0.1);
}

/* 5. MAIN CONTENT SCROLLING (INDEPENDENT RIGHT PANEL SCROLL) */
.main .block-container {
    margin-top: 6rem;
    height: calc(100vh - 6rem);
    overflow-y: auto;
    padding-top: 1rem;
    padding-bottom: 5rem;
}
.main .block-container::-webkit-scrollbar {
    width: 8px;
}
.main .block-container::-webkit-scrollbar-thumb {
    background: #2d3748;
    border-radius: 4px;
}

/* 6. SIDEBAR BUTTON STYLING */
[data-testid="stSidebar"] .stButton button {
    width: 100%;
    border-radius: 8px;
    font-weight: 600;
    margin-bottom: 6px;
}

/* 7. HIDE UPLOADED FILE LIST & NAME */
[data-testid='stFileUploaderFile'] {
    display: none;
}
section[data-testid="stFileUploader"] ul {
    display: none;
}
section[data-testid="stFileUploader"] small {
    display: none;
}

/* 8. CHAT BUBBLES */
.chat-user {
    background: #2d3748;
    padding: 12px;
    border-radius: 10px 10px 2px 10px;
    margin: 6px 0 6px auto;
    max-width: 85%;
    text-align: right;
    color: #f0f2f6;
}
.chat-bot {
    background: #1e3a8a;
    padding: 12px;
    border-radius: 10px 10px 10px 2px;
    margin: 6px auto 6px 0;
    max-width: 85%;
    text-align: left;
    color: #ffffff;
}
/* Sources CSS removed/hidden as it is no longer used */
.sources {
    display: none; 
}

/* 9. TITLE TEXT */
.title-text {
    font-size: 2.5rem;
    font-weight: 800;
    margin: 0;
    line-height: 1.2;
}
.creator-text {
    font-size: 1rem;
    font-weight: 500;
    color: #cccccc;
}
.creator-text a {
    color: #4da6ff;
    text-decoration: none;
}

/* 10. INPUT FORM STYLING */
[data-testid="stForm"] {
    border: none;
    padding: 0;
}
</style>
""", unsafe_allow_html=True)

# ---------------- FIXED HEADER ----------------
st.markdown("""
<div class="fixed-header">
    <div class="title-text">📘 PDF Assistant</div>
    <div class="creator-text">
        by <a href="https://www.linkedin.com/in/abhishek-iitr/" target="_blank">Abhishek Saxena</a>
    </div>
</div>
""", unsafe_allow_html=True)


# ---------------- SESSION STATE ----------------
if "chat" not in st.session_state:
    st.session_state.chat = []

if "vectorstore" not in st.session_state:
    st.session_state.vectorstore = None

if "retriever" not in st.session_state:
    st.session_state.retriever = None

if "uploaded_file_name" not in st.session_state:
    st.session_state.uploaded_file_name = None

if "uploader_key" not in st.session_state:
    st.session_state.uploader_key = 0

# ---------------- FUNCTIONS ----------------
def clear_chat_history():
    st.session_state.chat = []

def clear_memory():
    st.session_state.vectorstore = None
    st.session_state.retriever = None
    st.session_state.uploaded_file_name = None
    st.session_state.uploader_key += 1
    gc.collect()
    if torch.cuda.is_available():
        torch.cuda.empty_cache()

def process_pdf(uploaded_file):
    try:
        with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
            tmp.write(uploaded_file.getvalue())
            path = tmp.name
        
        loader = PyPDFLoader(path)
        docs = loader.load()
        
        splitter = RecursiveCharacterTextSplitter(chunk_size=800, chunk_overlap=60)
        chunks = splitter.split_documents(docs)
        
        embeddings = HuggingFaceEmbeddings(
            model_name="sentence-transformers/all-MiniLM-L6-v2",
            model_kwargs={"device": "cpu"},
            encode_kwargs={"normalize_embeddings": True}
        )
        
        vectorstore = Chroma.from_documents(chunks, embeddings)
        retriever = vectorstore.as_retriever(search_kwargs={"k": 5})
        
        st.session_state.vectorstore = vectorstore
        st.session_state.retriever = retriever
        
        if os.path.exists(path):
            os.unlink(path)
        
        return len(chunks)
    except Exception as e:
        st.error(f"Error processing PDF: {str(e)}")
        return None

def ask_question(question):
    if not client:
        return None, 0, "Groq client is not initialized."
    if not st.session_state.retriever:
        return None, 0, "Upload PDF first."
    
    try:
        docs = st.session_state.retriever.invoke(question)
        context = "\n\n".join(d.page_content for d in docs)
        
        prompt = f"""
You are a strict RAG Q&A assistant.
Summarize the context based on user question and return best answer. If the answer is not found, reply: "I cannot find this in the PDF."
 CONTEXT = {context}
QUESTION = {question}

Answer on your behalf, don't say based on the context...
"""
        
        response = client.chat.completions.create(
            model=GROQ_MODEL,
            messages=[
                {"role": "system", "content": "Use only the PDF content."},
                {"role": "user", "content": prompt}
            ],
            temperature=0.1
        )
        return response.choices[0].message.content.strip(), len(docs), None
    except Exception as e:
        return None, 0, f"Error: {str(e)}"

# ---------------- SIDEBAR ----------------
with st.sidebar:
    st.write("") 
    if st.button("🗑️ Clear Chat History", use_container_width=True):
        clear_chat_history()
    if st.button("🔥 Clear PDF Memory", on_click=clear_memory, use_container_width=True):
         st.success("Memory Cleared!")

    st.markdown("---")
    
    upload_label = "✅ PDF Uploaded!" if st.session_state.uploaded_file_name else "Upload PDF"
    uploaded = st.file_uploader(
        upload_label, type=["pdf"], key=st.session_state.uploader_key, label_visibility="collapsed"
    )

    if uploaded:
        if uploaded.name != st.session_state.uploaded_file_name:
            st.session_state.uploaded_file_name = None
            st.session_state.chat = []
            with st.spinner(f"Processing '{uploaded.name}'..."):
                chunks = process_pdf(uploaded)
                if chunks:
                    st.session_state.uploaded_file_name = uploaded.name
                    st.success("✅ PDF Processed!") 
                else:
                    st.error("❌ Failed.")
        else:
            st.success(f"✅ **Active:** `{uploaded.name}`")
    else:
        st.warning("⬆️ Upload a PDF to start chatting!")

# ---------------- INPUT AREA ----------------
disabled_input = st.session_state.uploaded_file_name is None or client is None

# Input Form
with st.form(key='chat_form', clear_on_submit=True):
    col_input, col_btn = st.columns([0.85, 0.15], gap="small")
    with col_input:
        user_question = st.text_input(
            "Ask a question", 
            placeholder="Ask a question about the loaded PDF...",
            label_visibility="collapsed",
            disabled=disabled_input
        )
    with col_btn:
        submit_btn = st.form_submit_button("➤", disabled=disabled_input, use_container_width=True)

if submit_btn and user_question:
    st.session_state.chat.append(("user", user_question))
    with st.spinner("Thinking..."):
        answer, sources, error = ask_question(user_question)
        if answer:
            # CHANGED: Removed the 'Context Chunks Used' HTML from the message
            bot_msg = answer
            st.session_state.chat.append(("bot", bot_msg))
        else:
            st.session_state.chat.append(("bot", f"🔴 **Error:** {error}"))
    st.rerun()

# ---------------- CHAT HISTORY (REVERSED) ----------------
if st.session_state.chat:
    st.markdown("---")
    for role, msg in reversed(st.session_state.chat):
        if role == "user":
            st.markdown(f"<div class='chat-user'>{msg}</div>", unsafe_allow_html=True)
        else:
            st.markdown(f"<div class='chat-bot'>{msg}</div>", unsafe_allow_html=True)