Update app.py

app.py

@@ -31,7 +31,7 @@ embedder = SentenceTransformer('paraphrase-MiniLM-L6-v2')
 dataset_embeddings = embedder.encode(train_dataset['question'], convert_to_tensor=True)
 index = faiss.IndexFlatL2(dataset_embeddings.shape[1])  # Create an index based on L2 distance
 index.add(dataset_embeddings.cpu().numpy())  # Add the embeddings to the index
-
+api_key = os.getenv("api_key") 
 # Set up Groq API with direct API key
 
 client = Groq(api_key=api_key)