Update app.py

app.py

@@ -13,9 +13,10 @@ from dotenv import load_dotenv
 from flask import jsonify
 
 load_dotenv()
-
-API_URL_EMBEDDINGS = f"https://e4e5-196-96-202-255.ngrok-free.app/embeddings"
-API_URL_METADATA = f"https://e4e5-196-96-202-255.ngrok-free.app/metadata"
+API_URL = "https://e4e5-196-96-202-255.ngrok-free.app"
+API_URL_FILES = f"{API_URL}/file"
+API_URL_EMBEDDINGS = f"{API_URL}/embeddings"
+API_URL_METADATA = f"{API_URL}/metadata"
 
 # FAISS index setup
 DIM = 768  # Adjust based on the embedding model
@@ -81,8 +82,12 @@ def retrieve_document(query):
     query_embedding = embedding_model.encode([query]).astype(np.float32)
 
     # Search for the closest document in FAISS index
+    index = faiss.read_index(embeddings_file)
     _, closest_idx = index.search(query_embedding, 1)
 
+    with open(metadata_file, "r") as f:
+        metadata = [json.loads(line) for line in f]
+
     # Check if a relevant document was found
     if closest_idx[0][0] == -1 or str(closest_idx[0][0]) not in metadata:
         print("No relevant document found")
@@ -91,6 +96,8 @@ def retrieve_document(query):
     # Retrieve the document file path
     filename = metadata[str(closest_idx[0][0])]
 
+    pdf_file = requests.get(API_URL_FILES, filename)
+
     # Read and return the document content
     with open(filename, "r", encoding="utf-8") as f:
         return f.read()