Update app.py

app.py

@@ -2,7 +2,7 @@ from datasets import load_dataset
 from sentence_transformers import SentenceTransformer
 import faiss
 import numpy as np
-
+import gradio as gr
 
 # Load a small subset (10,000 rows)
 dataset = load_dataset("wiki40b", "en", split="train[:10000]")
@@ -25,12 +25,20 @@ index.add(np.array(embeddings))
 
 print("Stored embeddings in FAISS!")
 
+# Search function
 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))
+    return "\n\n".join(results)
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=search_wikipedia, 
+    inputs="text", 
+    outputs="text", 
+    title="Wikipedia Search RAG",
+    description="Enter a query and retrieve relevant Wikipedia passages."
+)
+
+iface.launch()