ProvidersGoogleOn this pageGoogleAll functionality related to Google Cloud PlatformLLMs​Vertex AI​Access PaLM LLMs like text-bison and code-bison via Google Cloud.from langchain.llms import VertexAIModel Garden​Access PaLM and hundreds of OSS models via Vertex AI Model Garden.from langchain.llms import VertexAIModelGardenChat models​Vertex AI​Access PaLM chat models like chat-bison and codechat-bison via Google Cloud.from langchain.chat_models import ChatVertexAIDocument Loader​Google BigQuery​Google BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
BigQuery is a part of the Google Cloud Platform.First, we need to install google-cloud-bigquery python package.pip install google-cloud-bigquerySee a usage example.from langchain.document_loaders import BigQueryLoaderGoogle Cloud Storage​Google Cloud Storage is a managed service for storing unstructured data.First, we need to install google-cloud-storage python package.pip install google-cloud-storageThere are two loaders for the Google Cloud Storage: the Directory and the File loaders.See a usage example.from langchain.document_loaders import GCSDirectoryLoaderSee a usage example.from langchain.document_loaders import GCSFileLoaderGoogle Drive​Google Drive is a file storage and synchronization service developed by Google.Currently, only Google Docs are supported.First, we need to install several python package.pip install google-api-python-client google-auth-httplib2 google-auth-oauthlibSee a usage example and authorizing instructions.from langchain.document_loaders import GoogleDriveLoaderVector Store​Google Vertex AI MatchingEngine​Google Vertex AI Matching Engine provides
the industry's leading high-scale low latency vector database. These vector databases are commonly
referred to as vector similarity-matching or an approximate nearest neighbor (ANN) service.We need to install several python packages.pip install tensorflow google-cloud-aiplatform tensorflow-hub tensorflow-textSee a usage example.from langchain.vectorstores import MatchingEngineGoogle ScaNN​Google ScaNN
(Scalable Nearest Neighbors) is a python package.ScaNN is a method for efficient vector similarity search at scale.ScaNN includes search space pruning and quantization for Maximum Inner
Product Search and also supports other distance functions such as
Euclidean distance. The implementation is optimized for x86 processors
with AVX2 support. See its Google Research github
for more details.We need to install scann python package.pip install scannSee a usage example.from langchain.vectorstores import ScaNNRetrievers​Vertex AI Search​Google Cloud Vertex AI Search
allows developers to quickly build generative AI powered search engines for customers and employees.First, you need to install the google-cloud-discoveryengine Python package.pip install google-cloud-discoveryengineSee a usage example.from langchain.retrievers import GoogleVertexAISearchRetrieverTools​Google Search​Install requirements with pip install google-api-python-clientSet up a Custom Search Engine, following these instructionsGet an API Key and Custom Search Engine ID from the previous step, and set them as environment variables GOOGLE_API_KEY and GOOGLE_CSE_ID respectivelyThere exists a GoogleSearchAPIWrapper utility which wraps this API. To import this utility:from langchain.utilities import GoogleSearchAPIWrapperFor a more detailed walkthrough of this wrapper, see this notebook.We can easily load this wrapper as a Tool (to use with an Agent). We can do this with:from langchain.agents import load_toolstools = load_tools(["google-search"])Document Transformer​Google Document AI​Document AI is a Google Cloud Platform
service to transform unstructured data from documents into structured data, making it easier
to understand, analyze, and consume.  We need to set up a GCS bucket and create your own OCR processor
The GCS_OUTPUT_PATH should be a path to a folder on GCS (starting with gs://)
and a processor name should look like projects/PROJECT_NUMBER/locations/LOCATION/processors/PROCESSOR_ID.
We can get it either programmatically or copy from the Prediction endpoint section of the Processor details
tab in the Google Cloud Console.pip install google-cloud-documentaipip install google-cloud-documentai-toolboxSee a usage example.from langchain.document_loaders.blob_loaders import Blobfrom langchain.document_loaders.parsers import DocAIParserPreviousAWSNextMicrosoftLLMsVertex AIModel GardenChat modelsVertex AIDocument LoaderGoogle BigQueryGoogle Cloud StorageGoogle DriveVector StoreGoogle Vertex AI MatchingEngineGoogle ScaNNRetrieversVertex AI SearchToolsGoogle SearchDocument TransformerGoogle Document AI