Initial RAG setup

app.py

@@ -25,3 +25,12 @@ index.add(np.array(embeddings))
 
 print("Stored embeddings in FAISS!")
 
+def search_wikipedia(query, top_k=3):
+    query_embedding = embed_model.encode([query])
+    distances, indices = index.search(np.array(query_embedding), top_k)
+    
+    results = [docs[i] for i in indices[0]]
+    return results
+
+query = "What is machine learning?"
+print("Search Results:", search_wikipedia(query))