Update app.py

app.py

@@ -0,0 +1,100 @@
+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}")