import os
import io
import re
import requests
import faiss
import numpy as np
import streamlit as st
from PyPDF2 import PdfReader
from sentence_transformers import SentenceTransformer
from groq import Groq

# ============ CONFIG ============ #
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
if not GROQ_API_KEY:
    st.error("❌ GROQ_API_KEY environment variable not found.")
    st.stop()

client = Groq(api_key=GROQ_API_KEY)
embedder = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")

# Google Drive file links (shared by you)
GDRIVE_LINKS = [
    "https://drive.google.com/file/d/1aBFrAktgTIFwYxNDiY75Gj-4gwqoUJbm/view?usp=sharing",
    "https://drive.google.com/file/d/1boqYWdtFqYagnVk7oeh6hRZb5Um2W9zC/view?usp=sharing"
]

# ============ UTILS ============ #
def gdrive_to_direct(link):
    match = re.search(r"drive\.google\.com\/file\/d\/([^/]+)", link)
    if match:
        file_id = match.group(1)
        return f"https://drive.google.com/uc?export=download&id={file_id}"
    return None

def fetch_pdf(url):
    response = requests.get(url, timeout=30)
    response.raise_for_status()
    return response.content

def read_pdf_bytes(data):
    reader = PdfReader(io.BytesIO(data))
    text = ""
    for page in reader.pages:
        extracted = page.extract_text()
        if extracted:
            text += extracted
    return text

def chunk_text(text, max_length=500):
    words = text.split()
    return [' '.join(words[i:i + max_length]) for i in range(0, len(words), max_length)]

def create_faiss_index(chunks):
    embeddings = embedder.encode(chunks)
    dim = embeddings.shape[1]
    index = faiss.IndexFlatL2(dim)
    index.add(np.array(embeddings))
    return index, chunks

def search_index(index, query, chunks, top_k=3):
    query_embedding = embedder.encode([query])
    D, I = index.search(np.array(query_embedding), top_k)
    return [chunks[i] for i in I[0]]

# ============ STREAMLIT UI ============ #
st.set_page_config(page_title="🧠 RAG Chat from Cloud PDFs", layout="wide")
st.title("📄 Chat with 2 Google Drive PDFs (Auto-loaded)")

with st.spinner("📥 Downloading and processing PDF documents..."):
    combined_text = ""
    for link in GDRIVE_LINKS:
        direct_url = gdrive_to_direct(link)
        if direct_url:
            try:
                pdf_bytes = fetch_pdf(direct_url)
                combined_text += read_pdf_bytes(pdf_bytes)
            except Exception as e:
                st.error(f"❌ Error fetching PDF from: {link}\n\n{e}")
                st.stop()
        else:
            st.error(f"❌ Invalid Google Drive link format: {link}")
            st.stop()

    chunks = chunk_text(combined_text)
    index, stored_chunks = create_faiss_index(chunks)

st.success("✅ PDFs loaded and indexed. Ask your questions below!")

# Input box for queries
query = st.text_input("Ask a question based on the documents:")
if query:
    with st.spinner("🔍 Searching and generating response..."):
        context = search_index(index, query, stored_chunks)
        prompt = "\n".join(context) + f"\n\nQuestion: {query}"
        response = client.chat.completions.create(
            model="llama-3.3-70b-versatile",
            messages=[{"role": "user", "content": prompt}]
        )
        answer = response.choices[0].message.content.strip()
    st.markdown(f"**Answer:** {answer}")