Update wait_for_docs_in_index

Author: NoahStapp

pymongo_vectorsearch_utils/index.py

@@ -269,7 +269,10 @@ def wait_for_docs_in_index(
         embedding_field (str): The name of the document field containing embeddings.
         n_docs (int): The number of documents to expect in the index.
     """
-    index = collection.list_search_indexes(index_name).to_list()[0]
+    indexes = collection.list_search_indexes(index_name).to_list()
+    if len(indexes) == 0:
+        raise ValueError(f"Index {index_name} does not exist in collection {collection.name}")
+    index = indexes[0]
     num_dimensions = index["latestDefinition"]["fields"][0]["numDimensions"]
     field = index["latestDefinition"]["fields"][0]["path"]
 

tests/test_operation.py

@@ -298,7 +298,7 @@ def vector_search_index(self, client):
         drop_vector_search_index(collection=coll, index_name=VECTOR_INDEX_NAME)
 
     @pytest.fixture(scope="class", autouse=True)
-    def sample_docs(self, preserved_collection: Collection):
+    def sample_docs(self, preserved_collection: Collection, vector_search_index):
         texts = ["apple fruit", "banana fruit", "car vehicle", "bike vehicle"]
         metadatas = [
             {"category": "fruit", "color": "red"},