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All functionality related to Google Cloud Platform and other Google products.

LLMs​

Google Generative AI​

Access GoogleAI Gemini models such as gemini-pro and gemini-pro-vision through the GoogleGenerativeAI class.

Install python package.

pip install langchain-google-genai

See a usage example.

from langchain_google_genai import GoogleGenerativeAI

Vertex AI​

Access to Gemini and PaLM LLMs (like text-bison and code-bison) via Vertex AI on Google Cloud.

We need to install langchain-google-vertexai python package.

pip install langchain-google-vertexai

See a usage example.

from langchain_google_vertexai import VertexAI

Model Garden​

Access PaLM and hundreds of OSS models via Vertex AI Model Garden on Google Cloud.

We need to install langchain-google-vertexai python package.

pip install langchain-google-vertexai

See a usage example.

from langchain_google_vertexai import VertexAIModelGarden

Chat models​

Google Generative AI​

Access GoogleAI Gemini models such as gemini-pro and gemini-pro-vision through the ChatGoogleGenerativeAI class.

pip install -U langchain-google-genai

Configure your API key.

export GOOGLE_API_KEY=your-api-key
from langchain_google_genai import ChatGoogleGenerativeAI

llm = ChatGoogleGenerativeAI(model="gemini-pro")
llm.invoke("Sing a ballad of LangChain.")

Gemini vision model supports image inputs when providing a single chat message.

from langchain_core.messages import HumanMessage
from langchain_google_genai import ChatGoogleGenerativeAI

llm = ChatGoogleGenerativeAI(model="gemini-pro-vision")

message = HumanMessage(
content=[
{
"type": "text",
"text": "What's in this image?",
}, # You can optionally provide text parts
{"type": "image_url", "image_url": "https://picsum.photos/seed/picsum/200/300"},
]
)
llm.invoke([message])

The value of image_url can be any of the following:

  • A public image URL
  • A gcs file (e.g., "gcs://path/to/file.png")
  • A local file path
  • A base64 encoded image (e.g., data:image/png;base64,abcd124)
  • A PIL image

Vertex AI​

Access PaLM chat models like chat-bison and codechat-bison via Google Cloud.

We need to install langchain-google-vertexai python package.

pip install langchain-google-vertexai

See a usage example.

from langchain_google_vertexai import ChatVertexAI

Document Loaders​

AlloyDB for PostgreSQL​

Google Cloud AlloyDB is a fully managed relational database service that offers high performance, seamless integration, and impressive scalability on Google Cloud. AlloyDB is 100% compatible with PostgreSQL.

Install the python package:

pip install langchain-google-alloydb-pg

See usage example.

from langchain_google_alloydb_pg import AlloyDBEngine, AlloyDBLoader

BigQuery​

Google Cloud BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data in Google Cloud.

We need to install google-cloud-bigquery python package.

pip install google-cloud-bigquery

See a usage example.

from langchain_community.document_loaders import BigQueryLoader

Bigtable​

Google Cloud Bigtable is Google's fully managed NoSQL Big Data database service in Google Cloud. Install the python package:

pip install langchain-google-bigtable

See Googel Cloud usage example.

from langchain_google_bigtable import BigtableLoader

Cloud SQL for MySQL​

Google Cloud SQL for MySQL is a fully-managed database service that helps you set up, maintain, manage, and administer your MySQL relational databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-mysql

See usage example.

from langchain_google_cloud_sql_mysql import MySQLEngine, MySQLDocumentLoader

Cloud SQL for SQL Server​

Google Cloud SQL for SQL Server is a fully-managed database service that helps you set up, maintain, manage, and administer your SQL Server databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-mssql

See usage example.

from langchain_google_cloud_sql_mssql import MSSQLEngine, MSSQLLoader

Cloud SQL for PostgreSQL​

Google Cloud SQL for PostgreSQL is a fully-managed database service that helps you set up, maintain, manage, and administer your PostgreSQL relational databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-pg

See usage example.

from langchain_google_cloud_sql_pg import PostgreSQLEngine, PostgreSQLLoader

Cloud Storage​

Cloud Storage is a managed service for storing unstructured data in Google Cloud.

We need to install google-cloud-storage python package.

pip install google-cloud-storage

There are two loaders for the Google Cloud Storage: the Directory and the File loaders.

See a usage example.

from langchain_community.document_loaders import GCSDirectoryLoader

See a usage example.

from langchain_community.document_loaders import GCSFileLoader

El Carro for Oracle Workloads​

Google El Carro Oracle Operator offers a way to run Oracle databases in Kubernetes as a portable, open source, community driven, no vendor lock-in container orchestration system.

pip install langchain-google-el-carro

See usage example.

from langchain_google_el_carro import ElCarroLoader

Google Drive​

Google Drive is a file storage and synchronization service developed by Google.

Currently, only Google Docs are supported.

We need to install several python packages.

pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib

See a usage example and authorization instructions.

from langchain_community.document_loaders import GoogleDriveLoader

Firestore (Native Mode)​

Google Cloud Firestore is a NoSQL document database built for automatic scaling, high performance, and ease of application development. Install the python package:

pip install langchain-google-firestore

See usage example.

from langchain_google_firestore import FirestoreLoader

Firestore (Datastore Mode)​

Google Cloud Firestore in Datastore mode is a NoSQL document database built for automatic scaling, high performance, and ease of application development. Firestore is the newest version of Datastore and introduces several improvements over Datastore. Install the python package:

pip install langchain-google-datastore

See usage example.

from langchain_google_datastore import DatastoreLoader

Memorystore for Redis​

Google Cloud Memorystore for Redis is a fully managed Redis service for Google Cloud. Applications running on Google Cloud can achieve extreme performance by leveraging the highly scalable, available, secure Redis service without the burden of managing complex Redis deployments. Install the python package:

pip install langchain-google-memorystore-redis

See usage example.

from langchain_google_memorystore_redis import MemorystoreLoader

Spanner​

Google Cloud Spanner is a fully managed, mission-critical, relational database service on Google Cloud that offers transactional consistency at global scale, automatic, synchronous replication for high availability, and support for two SQL dialects: GoogleSQL (ANSI 2011 with extensions) and PostgreSQL. Install the python package:

pip install langchain-google-spanner

See usage example.

from langchain_google_spanner import SpannerLoader

Speech-to-Text​

Google Cloud Speech-to-Text is an audio transcription API powered by Google's speech recognition models in Google Cloud.

This document loader transcribes audio files and outputs the text results as Documents.

First, we need to install the python package.

pip install google-cloud-speech

See a usage example and authorization instructions.

from langchain_community.document_loaders import GoogleSpeechToTextLoader

Document Transformers​

Document AI​

Google Cloud Document AI is a Google Cloud service that transforms 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-documentai
pip install google-cloud-documentai-toolbox

See a usage example.

from langchain_community.document_loaders.blob_loaders import Blob
from langchain_community.document_loaders.parsers import DocAIParser

Google Translate​

Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another.

The GoogleTranslateTransformer allows you to translate text and HTML with the Google Cloud Translation API.

To use it, you should have the google-cloud-translate python package installed, and a Google Cloud project with the Translation API enabled. This transformer uses the Advanced edition (v3).

First, we need to install the python package.

pip install google-cloud-translate

See a usage example and authorization instructions.

from langchain_community.document_transformers import GoogleTranslateTransformer

Vector Stores​

AlloyDB for PostgreSQL​

Google Cloud AlloyDB is a fully managed relational database service that offers high performance, seamless integration, and impressive scalability on Google Cloud. AlloyDB is 100% compatible with PostgreSQL.

Install the python package:

pip install langchain-google-alloydb-pg

See usage example.

from langchain_google_alloydb_pg import AlloyDBEngine, AlloyDBVectorStore

Google Cloud BigQuery, BigQuery is a serverless and cost-effective enterprise data warehouse in Google Cloud.

Google Cloud BigQuery Vector Search BigQuery vector search lets you use GoogleSQL to do semantic search, using vector indexes for fast but approximate results, or using brute force for exact results.

It can calculate Euclidean or Cosine distance. With LangChain, we default to use Euclidean distance.

We need to install several python packages.

pip install google-cloud-bigquery

See a usage example.

from langchain.vectorstores import BigQueryVectorSearch

Memorystore for Redis​

Google Cloud Memorystore for Redis is a fully managed Redis service for Google Cloud. Applications running on Google Cloud can achieve extreme performance by leveraging the highly scalable, available, secure Redis service without the burden of managing complex Redis deployments. Install the python package:

pip install langchain-google-memorystore-redis

See usage example.

from langchain_google_memorystore_redis import RedisVectorStore

Spanner​

Google Cloud Spanner is a fully managed, mission-critical, relational database service on Google Cloud that offers transactional consistency at global scale, automatic, synchronous replication for high availability, and support for two SQL dialects: GoogleSQL (ANSI 2011 with extensions) and PostgreSQL. Install the python package:

pip install langchain-google-spanner

See usage example.

from langchain_google_spanner import SpannerVectorStore

Cloud SQL for PostgreSQL​

Google Cloud SQL for PostgreSQL is a fully-managed database service that helps you set up, maintain, manage, and administer your PostgreSQL relational databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-pg

See usage example.

from langchain_google_cloud_sql_pg import PostgreSQLEngine, PostgresVectorStore

Google Cloud Vertex AI Vector Search from Google Cloud, formerly known as 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 langchain-google-vertexai tensorflow-hub tensorflow-text

See a usage example.

from langchain_community.vectorstores import MatchingEngine

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 scann

See a usage example.

from langchain_community.vectorstores import ScaNN

Retrievers​

Google Drive​

We need to install several python packages.

pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib

See a usage example and authorization instructions.

from langchain_googledrive.retrievers import GoogleDriveRetriever

Vertex AI Search from Google Cloud allows developers to quickly build generative AI powered search engines for customers and employees.

We need to install the google-cloud-discoveryengine python package.

pip install google-cloud-discoveryengine

See a usage example.

from langchain.retrievers import GoogleVertexAISearchRetriever

Document AI Warehouse​

Document AI Warehouse from Google Cloud allows enterprises to search, store, govern, and manage documents and their AI-extracted data and metadata in a single platform.

from langchain.retrievers import GoogleDocumentAIWarehouseRetriever
docai_wh_retriever = GoogleDocumentAIWarehouseRetriever(
project_number=...
)
query = ...
documents = docai_wh_retriever.get_relevant_documents(
query, user_ldap=...
)

Tools​

Text-to-Speech​

Google Cloud Text-to-Speech is a Google Cloud service that enables developers to synthesize natural-sounding speech with 100+ voices, available in multiple languages and variants. It applies DeepMind’s groundbreaking research in WaveNet and Google’s powerful neural networks to deliver the highest fidelity possible.

We need to install a python package.

pip install google-cloud-text-to-speech

See a usage example and authorization instructions.

from langchain.tools import GoogleCloudTextToSpeechTool

Google Drive​

We need to install several python packages.

pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib

See a usage example and authorization instructions.

from langchain_community.utilities.google_drive import GoogleDriveAPIWrapper
from langchain_community.tools.google_drive.tool import GoogleDriveSearchTool

Google Finance​

We need to install a python package.

pip install google-search-results

See a usage example and authorization instructions.

from langchain_community.tools.google_finance import GoogleFinanceQueryRun
from langchain_community.utilities.google_finance import GoogleFinanceAPIWrapper

Google Jobs​

We need to install a python package.

pip install google-search-results

See a usage example and authorization instructions.

from langchain_community.tools.google_jobs import GoogleJobsQueryRun
from langchain_community.utilities.google_finance import GoogleFinanceAPIWrapper

Google Lens​

See a usage example and authorization instructions.

from langchain_community.tools.google_lens import GoogleLensQueryRun
from langchain_community.utilities.google_lens import GoogleLensAPIWrapper

Google Places​

We need to install a python package.

pip install googlemaps

See a usage example and authorization instructions.

from langchain.tools import GooglePlacesTool

Google Scholar​

We need to install a python package.

pip install google-search-results

See a usage example and authorization instructions.

from langchain_community.tools.google_scholar import GoogleScholarQueryRun
from langchain_community.utilities.google_scholar import GoogleScholarAPIWrapper
  • Set up a Custom Search Engine, following these instructions
  • Get 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 respectively.
from langchain_community.utilities import GoogleSearchAPIWrapper

For 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_tools
tools = load_tools(["google-search"])

We need to install a python package.

pip install google-search-results

See a usage example and authorization instructions.

from langchain_community.tools.google_trends import GoogleTrendsQueryRun
from langchain_community.utilities.google_trends import GoogleTrendsAPIWrapper

Toolkits​

GMail​

Google Gmail is a free email service provided by Google. This toolkit works with emails through the Gmail API.

We need to install several python packages.

pip install google-api-python-client google-auth-oauthlib google-auth-httplib2

See a usage example and authorization instructions.

from langchain_community.agent_toolkits import GmailToolkit

Memory​

AlloyDB for PostgreSQL​

AlloyDB for PostgreSQL is a fully managed relational database service that offers high performance, seamless integration, and impressive scalability on Google Cloud. AlloyDB is 100% compatible with PostgreSQL.

Install the python package:

pip install langchain-google-alloydb-pg

See usage example.

from langchain_google_alloydb_pg import AlloyDBEngine, AlloyDBChatMessageHistory

Cloud SQL for PostgreSQL​

Cloud SQL for PostgreSQL is a fully-managed database service that helps you set up, maintain, manage, and administer your PostgreSQL relational databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-pg

See usage example.

from langchain_google_cloud_sql_pg import PostgreSQLEngine, PostgreSQLChatMessageHistory

Cloud SQL for MySQL​

Cloud SQL for MySQL is a fully-managed database service that helps you set up, maintain, manage, and administer your MySQL relational databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-mysql

See usage example.

from langchain_google_cloud_sql_mysql import MySQLEngine, MySQLChatMessageHistory

Cloud SQL for SQL Server​

Cloud SQL for SQL Server is a fully-managed database service that helps you set up, maintain, manage, and administer your SQL Server databases on Google Cloud. Install the python package:

pip install langchain-google-cloud-sql-mssql

See usage example.

from langchain_google_cloud_sql_mssql import MSSQLEngine, MSSQLChatMessageHistory

El Carro for Oracle Workloads​

Google El Carro Oracle Operator offers a way to run Oracle databases in Kubernetes as a portable, open source, community driven, no vendor lock-in container orchestration system.

pip install langchain-google-el-carro

See usage example.

from langchain_google_el_carro import ElCarroChatMessageHistory

Spanner​

Google Cloud Spanner is a fully managed, mission-critical, relational database service on Google Cloud that offers transactional consistency at global scale, automatic, synchronous replication for high availability, and support for two SQL dialects: GoogleSQL (ANSI 2011 with extensions) and PostgreSQL. Install the python package:

pip install langchain-google-spanner

See usage example.

from langchain_google_spanner import SpannerChatMessageHistory

Memorystore for Redis​

Google Cloud Memorystore for Redis is a fully managed Redis service for Google Cloud. Applications running on Google Cloud can achieve extreme performance by leveraging the highly scalable, available, secure Redis service without the burden of managing complex Redis deployments. Install the python package:

pip install langchain-google-memorystore-redis

See usage example.

from langchain_google_memorystore_redis import MemorystoreChatMessageHistory

Bigtable​

Google Cloud Bigtable is Google's fully managed NoSQL Big Data database service in Google Cloud. Install the python package:

pip install langchain-google-bigtable

See usage example.

from langchain_google_bigtable import BigtableChatMessageHistory

Firestore (Native Mode)​

Google Cloud Firestore is a NoSQL document database built for automatic scaling, high performance, and ease of application development. Install the python package:

pip install langchain-google-firestore

See usage example.

from langchain_google_firestore import FirestoreChatMessageHistory

Firestore (Datastore Mode)​

Google Cloud Firestore in Datastore mode is a NoSQL document database built for automatic scaling, high performance, and ease of application development. Firestore is the newest version of Datastore and introduces several improvements over Datastore. Install the python package:

pip install langchain-google-datastore

See usage example.

from langchain_google_datastore import DatastoreChatMessageHistory

El Carro Oracle Operator​

Google El Carro Oracle Operator offers a way to run Oracle databases in Kubernetes as a portable, open source, community driven, no vendor lock-in container orchestration system.

pip install langchain-google-el-carro

See usage example.

from langchain_google_el_carro import ElCarroChatMessageHistory

Chat Loaders​

GMail​

Gmail is a free email service provided by Google. This loader works with emails through the Gmail API.

We need to install several python packages.

pip install google-api-python-client google-auth-oauthlib google-auth-httplib2

See a usage example and authorization instructions.

from langchain_community.chat_loaders.gmail import GMailLoader

3rd Party Integrations​

SearchApi​

SearchApi provides a 3rd-party API to access Google search results, YouTube search & transcripts, and other Google-related engines.

See usage examples and authorization instructions.

from langchain_community.utilities import SearchApiAPIWrapper

SerpApi​

SerpApi provides a 3rd-party API to access Google search results.

See a usage example and authorization instructions.

from langchain_community.utilities import SerpAPIWrapper

Serper.dev​

See a usage example and authorization instructions.

from langchain_community.utilities import GoogleSerperAPIWrapper

YouTube​

YouTube Search package searches YouTube videos avoiding using their heavily rate-limited API.

It uses the form on the YouTube homepage and scrapes the resulting page.

We need to install a python package.

pip install youtube_search

See a usage example.

from langchain.tools import YouTubeSearchTool

YouTube audio​

YouTube is an online video sharing and social media platform created by Google.

Use YoutubeAudioLoader to fetch / download the audio files.

Then, use OpenAIWhisperParser to transcribe them to text.

We need to install several python packages.

pip install yt_dlp pydub librosa

See a usage example and authorization instructions.

from langchain_community.document_loaders.blob_loaders.youtube_audio import YoutubeAudioLoader
from langchain_community.document_loaders.parsers import OpenAIWhisperParser, OpenAIWhisperParserLocal

YouTube transcripts​

YouTube is an online video sharing and social media platform created by Google.

We need to install youtube-transcript-api python package.

pip install youtube-transcript-api

See a usage example.

from langchain_community.document_loaders import YoutubeLoader