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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?
Google Generative AI (Gemini API & Vertex AI)
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.
Google Cloud (Vertex AI Platform Services)
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.
Integration packages for Gemini models and the Vertex AI platform are maintained in the langchain-google repository.You can find a host of LangChain integrations with other Google APIs and services in the langchain-google-community package (listed on this page) and the googleapis GitHub organization.
Access Google Gemini models via the Gemini Developer API or Vertex AI using the unified langchain-google-genai package.
Package consolidationCertain langchain-google-vertexai classes for Gemini models are being deprecated in favor of the unified langchain-google-genai package. Please migrate to the new classes.Read the full announcement and migration guide.
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 instead of ChatVertexAI. It supports both Gemini Developer API and Vertex AI backends.The classes below focus on Vertex AI platform services that are not available in the consolidated SDK.Read the full announcement and migration guide.
Store and search vectors using Google Cloud databases and Vertex AI Vector Search.
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.
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.
Memorystore for Redis
Vector store using Memorystore for Redis
Spanner
Vector store using Cloud Spanner
Firestore (Native Mode)
Vector store using Firestore
Cloud SQL for MySQL
Vector store using Cloud SQL for MySQL
Cloud SQL for PostgreSQL
Vector store using 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.
With DataStore Backend
Vector search using Datastore for document storage.