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‚ÄãVertex AI Search‚ÄãGoogle 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 GoogleVertexAISearchRetrieverDocument AI Warehouse‚ÄãGoogle Cloud Document AI Warehouse
allows enterprises to search, store, govern, and manage documents and their AI-extracted
data and metadata in a single platform. Documents should be uploaded outside of Langchain,from langchain.retrievers import GoogleDocumentAIWarehouseRetrieverdocai_wh_retriever = GoogleDocumentAIWarehouseRetriever(    project_number=...)query = ...documents = docai_wh_retriever.get_relevant_documents(    query, user_ldap=...)Tools‚ÄãGoogle Search‚ÄãInstall 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‚ÄãGoogle Document AI‚ÄãDocument 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
All functionality related to Google Cloud Platform
All functionality related to Google Cloud Platform ->: 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‚ÄãVertex AI Search‚ÄãGoogle 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 GoogleVertexAISearchRetrieverDocument AI Warehouse‚ÄãGoogle Cloud Document AI Warehouse
allows enterprises to search, store, govern, and manage documents and their AI-extracted
data and metadata in a single platform. Documents should be uploaded outside of Langchain,from langchain.retrievers import GoogleDocumentAIWarehouseRetrieverdocai_wh_retriever = GoogleDocumentAIWarehouseRetriever(    project_number=...)query = ...documents = docai_wh_retriever.get_relevant_documents(    query, user_ldap=...)Tools‚ÄãGoogle Search‚ÄãInstall 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‚ÄãGoogle Document AI‚ÄãDocument 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