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View on GitHubBuild LangChain Applications on AWS
Monorepo of LangChain and LangGraph integrations for AWS: Bedrock/SageMaker LLMs, AWS vector stores and retrievers for RAG, Bedrock Agents and AgentCore tools, plus DynamoDB/Valkey checkpointers and memory stores. Successor to the AWS components in langchain-community.
Use Cases
Use Bedrock and SageMaker LLMs inside LangChain chainsBuild RAG pipelines with AWS vector stores (S3 Vectors, ElastiCache, MemoryDB)Retrieve documents via Amazon Kendra and Bedrock Knowledge BasesRun Bedrock Agents and AgentCore tools from LangGraph agentsPersist LangGraph agent state with DynamoDB/Bedrock checkpointersStore long-term agent memory with AgentCore MemoryExecute sandboxed code via AgentCore Code InterpreterQuery Amazon Neptune graphs from LangChainBrowser automation tools for agents on AWS
Built With
- Language
- Python
- Frameworks
- LangChain · LangGraph · Amazon Bedrock · Bedrock AgentCore · Amazon SageMaker · Amazon Kendra · Amazon DynamoDB · ElastiCache for Valkey · Amazon Neptune · Amazon S3 Vectors · Amazon MemoryDB · Deep Agents · LangSmith
Tags
langchain · langgraph · aws · amazon-bedrock · bedrock-agentcore · vector-stores · retrievers · rag · agents · checkpointing · memory · sagemaker · kendra · dynamodb · elasticache · python