text: Sentence Encoder as an Embedderâ€‹# Load the Universal Sentence Encoder modulemodule_url = "https://tfhub.dev/google/universal-sentence-encoder-multilingual/3"model = hub.load(module_url)# Generate embeddings for each wordembeddings = model(["banana"])Inserting a test embeddingâ€‹initial_config = {    "id": "banana_id",    "embedding": [float(x) for x in list(embeddings.numpy()[0])],}with open("data.json", "w") as f:    json.dump(initial_config, f)gsutil cp data.json {EMBEDDING_DIR}/file.jsonaiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=BUCKET_URI)Creating Indexâ€‹my_index = aiplatform.MatchingEngineIndex.create_tree_ah_index(    display_name=DISPLAY_NAME,    contents_delta_uri=EMBEDDING_DIR,    dimensions=DIMENSIONS,    approximate_neighbors_count=150,    distance_measure_type="DOT_PRODUCT_DISTANCE",)Creating Endpointâ€‹my_index_endpoint = aiplatform.MatchingEngineIndexEndpoint.create(    display_name=f"{DISPLAY_NAME}-endpoint",    network=VPC_NETWORK_FULL,)Deploy Indexâ€‹my_index_endpoint = my_index_endpoint.deploy_index(    index=my_index, deployed_index_id=DEPLOYED_INDEX_ID)my_index_endpoint.deployed_indexesPreviousMarqoNextMilvusCreate VectorStore from textsCreate Index and deploy it to an EndpointImports, Constants and ConfigsUsing Tensorflow Universal Sentence Encoder as an EmbedderInserting a test embeddingCreating IndexCreating EndpointDeploy IndexCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.