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Documentation Index

Fetch the complete documentation index at: https://docs.langchain.com/llms.txt

Use this file to discover all available pages before exploring further.

This page covers all LangChain integrations with Google Gemini, Google Cloud, and other Google products (such as Google Maps, YouTube, and more).
Unified SDK & package consolidationAs of langchain-google-genai 4.0.0, this package uses the consolidated google-genai SDK and now supports both the Gemini Developer API and Vertex AI backends.The langchain-google-vertexai package remains supported for Vertex AI platform-specific features (Model Garden, Vector Search, evaluation services, etc.).Read the full announcement and migration guide.
Not sure which package to use?
Access Google Gemini models via the Gemini Developer API or Vertex AI. The backend is selected automatically based on your configuration.
  • Gemini Developer API: Quick setup with API key, ideal for individual developers and rapid prototyping
  • Vertex AI: Enterprise features with Google Cloud integration (requires GCP project)
Use the langchain-google-genai package for chat models, LLMs, and embeddings.See integrations.
Access Vertex AI platform-specific services beyond Gemini models: Model Garden (Llama, Mistral, Anthropic), evaluation services, and specialized vision models.Use the langchain-google-vertexai package for platform services and specific packages (e.g., langchain-google-community, langchain-google-cloud-sql-pg) for other cloud services like databases and storage.See integrations.
See Google’s guide on migrating from the Gemini API to Vertex AI for more details on the differences.

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Google Generative AI

Access Google Gemini models via the Gemini Developer API or Vertex AI using the unified langchain-google-genai package.

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Chat models

ChatGoogleGenerativeAI

Google Gemini chat models via Gemini Developer API or Vertex AI.

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LLMs

GoogleGenerativeAI

Gemini models using the (legacy) LLM text completion interface.

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Embedding models

GoogleGenerativeAIEmbeddings

Gemini embedding models via Gemini Developer API or Vertex AI.

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Google Cloud

Access Vertex AI platform-specific services including Model Garden (Llama, Mistral, Anthropic), Vector Search, evaluation services, and specialized vision models.
For Gemini models, use ChatGoogleGenerativeAI from langchain-google-genai. The classes below focus on Vertex AI platform services not available in the consolidated SDK.

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Chat models

ChatAnthropicVertex

Anthropic on Vertex AI Model Garden
Deprecated—Use ChatGoogleGenerativeAI for Gemini models instead.
from langchain_google_vertexai import ChatVertexAI
Llama on Vertex AI Model Garden
from langchain_google_vertexai.model_garden_maas.llama import VertexModelGardenLlama
Mistral on Vertex AI Model Garden
from langchain_google_vertexai.model_garden_maas.mistral import VertexModelGardenMistral
Local Gemma model loaded from HuggingFace.
from langchain_google_vertexai.gemma import GemmaChatLocalHF
Local Gemma model loaded from Kaggle.
from langchain_google_vertexai.gemma import GemmaChatLocalKaggle
Gemma on Vertex AI Model Garden
from langchain_google_vertexai.gemma import GemmaChatVertexAIModelGarden
Image captioning model as a chat interface.
from langchain_google_vertexai.vision_models import VertexAIImageCaptioningChat
Edit images given a prompt. Currently supports mask-free editing only.
from langchain_google_vertexai.vision_models import VertexAIImageEditorChat
Generate images from a prompt.
from langchain_google_vertexai.vision_models import VertexAIImageGeneratorChat
Visual question answering model as a chat interface.
from langchain_google_vertexai.vision_models import VertexAIVisualQnAChat

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LLMs

(Legacy) string-in, string-out LLM interface.

VertexAIModelGarden

Hundreds of OSS models via Vertex AI Model Garden.
Deprecated—Use GoogleGenerativeAI for Gemini models instead.
from langchain_google_vertexai import VertexAI
Local Gemma model loaded from HuggingFace.
from langchain_google_vertexai.gemma import GemmaLocalHF
Local Gemma model loaded from Kaggle.
from langchain_google_vertexai.gemma import GemmaLocalKaggle

from langchain_google_vertexai.gemma import GemmaVertexAIModelGarden
Image captioning model as an LLM interface.
from langchain_google_vertexai.vision_models import VertexAIImageCaptioning

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Embedding models

Deprecated—Use GoogleGenerativeAIEmbeddings instead.
from langchain_google_vertexai import VertexAIEmbeddings

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Document loaders

AlloyDB for PostgreSQL

PostgreSQL-compatible database on Google Cloud.

BigQuery

Serverless data warehouse.

Bigtable

Key-value and wide-column store for structured and semi-structured data.

Cloud SQL for MySQL

Managed MySQL database.

Cloud SQL for SQL Server

Managed SQL Server database.

Cloud SQL for PostgreSQL

Managed PostgreSQL database.

Cloud Storage (directory)

Load documents from a GCS bucket directory.

Cloud Storage (file)

Load a single document from GCS.

El Carro for Oracle Workloads

Oracle databases on Kubernetes via El Carro.

Firestore (Native Mode)

NoSQL document database.

Firestore (Datastore Mode)

Firestore in Datastore mode.

Memorystore for Redis

Managed Redis service.

Spanner

Globally distributed relational database.

Speech-to-Text

Transcribe audio files.
Load data using Google Cloud Vision API.
from langchain_google_community.vision import CloudVisionLoader

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Document transformers

Document AI

Extract structured data from unstructured documents.

Google Translate

Translate text and HTML via Cloud Translation API.

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Vector stores

Store and search vectors using Google Cloud databases and Vertex AI Vector Search.

AlloyDB for PostgreSQL

PostgreSQL-compatible vector store on AlloyDB.

BigQuery Vector Search

Semantic search using GoogleSQL with vector indexes.

Memorystore for Redis

Vector store on Memorystore for Redis.

Spanner

Vector store on Cloud Spanner.

Bigtable

Vector store on Cloud Bigtable.

Firestore (Native Mode)

Vector store on Firestore.

Cloud SQL for MySQL

Vector store on Cloud SQL for MySQL.

Cloud SQL for PostgreSQL

Vector store on Cloud SQL for PostgreSQL.

Vertex AI Vector Search

Formerly known as Vertex AI Matching Engine, provides a low latency vector database. These vector databases are commonly referred to as vector similarity-matching or an approximate nearest neighbor (ANN) service.

Vertex AI Vector Search + Datastore

Vector search with Datastore for document storage.

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Retrievers

Vertex AI Search

Generative AI powered search via Vertex AI Search.

Document AI Warehouse

Search, store, and manage documents using Document AI Warehouse.
Other retrievers
from langchain_google_community import VertexAIMultiTurnSearchRetriever
from langchain_google_community import VertexAISearchRetriever
from langchain_google_community import VertexAISearchSummaryTool

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Tools

Integrate agents with various Google Cloud services.

Text-to-Speech

Synthesize natural-sounding speech with 100+ voices.

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Callbacks

Track LLM/Chat model usage.
Track VertexAI usage info.
from langchain_google_vertexai.callbacks import VertexAICallbackHandler
See the documentation for more details.
from langchain_google_community.callbacks.bigquery_callback import BigQueryCallbackHandler

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Evaluators

Evaluate model outputs using Vertex AI.
Pair-wise evaluation using Vertex AI models.
from langchain_google_vertexai.evaluators.evaluation import VertexPairWiseStringEvaluator
Single prediction evaluation using Vertex AI models.
from langchain_google_vertexai.evaluators.evaluation import VertexStringEvaluator

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Other Google products

Integrations with various Google services beyond the core Cloud Platform.

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Document loaders

Google Drive

Load files from Google Drive. Currently supports Google Docs.

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Retrievers

Google Drive

Retrieve documents from Google Drive.

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Tools

Google Search

Web search via Google Custom Search Engine (CSE).

Google Drive

Interact with Google Drive.

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MCP

MCP Toolbox

Connect to databases including Cloud SQL and AlloyDB.

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Toolkits

Gmail

Create, search, and send emails via the Gmail API.

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3rd party integrations

Access Google services via unofficial third-party APIs.

cloro

Google Search results with AI Overview support.
Connect these docs to Claude, VSCode, and more via MCP for real-time answers.
Edit this page on GitHub or file an issue.