Update app.py

app.py

@@ -39,9 +39,26 @@ def extract_text_from_pdf(pdf_stream):
 def create_vector_db(text_chunks):
     """Embeds text chunks and adds them to FAISS index"""
     global documents, index
+    
+    # Reinitialize the FAISS index
+    index = faiss.IndexFlatL2(vector_dim)
+    
     documents = text_chunks
     embeddings = embed_model.encode(text_chunks)
-    index.add(np.array(embeddings, dtype=np.float32))
+
+    # Convert embeddings to np.float32 for FAISS
+    embeddings = np.array(embeddings, dtype=np.float32)
+
+    # Ensure that embeddings have the correct shape (should be 2D, with each vector having the right dimension)
+    if embeddings.ndim == 1:  # If only one embedding, reshape it
+        embeddings = embeddings.reshape(1, -1)
+
+    # Add embeddings to the FAISS index
+    index.add(embeddings)
+
+    # Check if adding was successful (optional)
+    if index.ntotal == 0:
+        print("Error: FAISS index is empty after adding embeddings.")
 
 def search_relevant_text(query):
     """Finds the most relevant text chunk for the given query"""