Migrate to a managed db

app.py

@@ -120,7 +120,9 @@ def index_repo(textbox: str, dropdown: str) -> Response:
                 embedding_function=embeddings,
                 token=os.environ['ACTIVELOOP_TOKEN'],
                 read_only=True,
-                num_workers=10)
+                num_workers=12,
+                runtime = {"tensor_db": True}
+            )
         # NOTE: read_only=False because we want to ingest documents
         # NOTE: This will raise a `deeplake.util.exceptions.LockedException` if dataset is already locked
         # NOTE: change it to read_only=True when querying the dataset
@@ -149,7 +151,10 @@ def index_repo(textbox: str, dropdown: str) -> Response:
                 db = DeepLake(dataset_path=dataset_path,
                         embedding_function=embeddings,
                         token=os.environ['ACTIVELOOP_TOKEN'],
-                        read_only=False)
+                        read_only=False,
+                        num_workers=12,
+                        runtime = {"tensor_db": True}
+                )
                 # Do this in chunks to avoid hitting the ratelimit immediately
                 for i in range(0, len(texts), 500):
                     print("Adding documents " + str(i))