Update app.py

app.py

@@ -1,25 +1,15 @@
 import faiss
-import numpy as np
-from sentence_transformers import SentenceTransformer
+import os
 
-# 🔹 Load FAISS Index
-FAISS_PATH = "asa_faiss.index"
-faiss_index = faiss.read_index(FAISS_PATH)
-
-# 🔹 Load Embedding Model
-embedder = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
-
-# 🔹 Test Query
-test_query = "Where is ASA Microfinance located?"
-query_embedding = embedder.encode([test_query], convert_to_tensor=True).cpu().numpy()
+# 🔹 Define FAISS File Path
+FAISS_FILE = "asa_faiss.index"  # This should be inside your space files
+LOCAL_FAISS_PATH = os.path.join(os.getcwd(), FAISS_FILE)
 
-# 🔹 Search FAISS
-distances, indices = faiss_index.search(query_embedding, 3)  # Retrieve top 3 matches
+# 🔹 Check if FAISS File Exists
+if not os.path.exists(LOCAL_FAISS_PATH):
+    raise FileNotFoundError(f"❌ FAISS index file '{FAISS_FILE}' not found! Make sure it's uploaded to your Space.")
 
-# 🔹 Print Results
-print("🔹 FAISS Search Results:")
-for idx in indices[0]:
-    print(f"Index: {idx}")
-
-print("🔹 FAISS Distances:")
-print(distances)
+# 🔹 Load FAISS Index
+print(f"Loading FAISS index from {LOCAL_FAISS_PATH}...")
+faiss_index = faiss.read_index(LOCAL_FAISS_PATH)
+print("✅ FAISS index loaded successfully!")