app.py

app.py

@@ -0,0 +1,71 @@
+import os
+import time
+
+import streamlit as st
+
+from extract import extract_text_from_pdfs
+from generate import generate_response
+from preprocess import preprocess_text
+from retrieve import create_vectorizer, retrieve
+
+# Streamlit UI
+st.title("RAG-based PDF Query System")
+
+uploaded_files = st.file_uploader("Upload PDFs", type=["pdf"], accept_multiple_files=True)
+
+if uploaded_files:
+    st.write("Processing the uploaded PDFs...")
+
+    # Initialize progress bar
+    progress_bar = st.progress(0)
+    status_text = st.empty()
+
+    # Save uploaded files to disk
+    pdf_files = []
+    for uploaded_file in uploaded_files:
+        with open(uploaded_file.name, "wb") as f:
+            f.write(uploaded_file.getbuffer())
+        pdf_files.append(uploaded_file.name)
+
+    # Extract text from PDFs with progress updates
+    num_files = len(pdf_files)
+    texts = []
+    for i, pdf_file in enumerate(pdf_files):
+        status_text.text(f"Extracting text from file {i + 1} of {num_files}...")
+        text = extract_text_from_pdfs([pdf_file])
+        texts.extend(text)
+        progress_bar.progress((i + 1) / num_files)
+        time.sleep(0.1)  # Simulate time taken for processing
+
+    # Preprocess text with progress updates
+    status_text.text("Preprocessing text...")
+    progress_bar.progress(0.5)
+    processed_texts = preprocess_text(texts)
+    time.sleep(0.1)  # Simulate time taken for processing
+
+    # Create vectorizer and transform texts
+    status_text.text("Creating vectorizer and transforming texts...")
+    progress_bar.progress(0.75)
+    vectorizer, X = create_vectorizer(processed_texts)
+    time.sleep(0.1)  # Simulate time taken for processing
+
+    # Finalize progress
+    progress_bar.progress(1.0)
+    status_text.text("Processing complete!")
+
+    query = st.text_input("Enter your query:")
+
+    if query:
+        # Retrieve relevant texts
+        top_indices = retrieve(query, X, vectorizer)
+        retrieved_texts = [texts[i] for i in top_indices]
+
+        # Generate response
+        response = generate_response(retrieved_texts, query)
+
+        st.write("Response:")
+        st.write(response)
+
+    # Clean up uploaded files
+    for pdf_file in pdf_files:
+        os.remove(pdf_file)