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https://github.com/langchain-ai/langchain-aws
Build LangChain Applications on AWS
https://github.com/langchain-ai/langchain-aws
aws generative-ai langchain langchain-python
Last synced: about 2 months ago
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Build LangChain Applications on AWS
- Host: GitHub
- URL: https://github.com/langchain-ai/langchain-aws
- Owner: langchain-ai
- License: mit
- Created: 2024-03-06T21:29:00.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-05-22T16:57:59.000Z (4 months ago)
- Last Synced: 2024-05-22T19:01:08.936Z (4 months ago)
- Topics: aws, generative-ai, langchain, langchain-python
- Language: Python
- Homepage:
- Size: 232 KB
- Stars: 42
- Watchers: 10
- Forks: 17
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# 🦜️🔗 LangChain 🤝 Amazon Web Services (AWS)
This repository provides LangChain components for various AWS services. It aims to replace and expand upon the existing LangChain AWS components found in the `langchain-community` package in the LangChain repository.
## Features
- **LLMs**: Includes LLM classes for AWS services like [Bedrock](https://aws.amazon.com/bedrock) and [SageMaker Endpoints](https://aws.amazon.com/sagemaker/deploy/), allowing you to leverage their language models within LangChain.
- **Retrievers**: Supports retrievers for services like [Amazon Kendra](https://aws.amazon.com/kendra/) and [KnowledgeBases for Amazon Bedrock](https://aws.amazon.com/bedrock/knowledge-bases/), enabling efficient retrieval of relevant information in your RAG applications.
- **Graphs**: Provides components for working with [AWS Neptune](https://aws.amazon.com/neptune/) graphs within LangChain.
- **More to come**: This repository will continue to expand and offer additional components for various AWS services as development progresses.
**Note**: This repository will replace all AWS integrations currently present in the `langchain-community` package. Users are encouraged to migrate to this repository as soon as possible.
## Installation
You can install the `langchain-aws` package from PyPI.
```bash
pip install langchain-aws
```
## Usage
Here's a simple example of how to use the `langchain-aws` package.
```python
from langchain_aws import BedrockLLM
# Initialize the Bedrock LLM
llm = BedrockLLM(
model_id="anthropic.claude-v2:1"
)
# Invoke the llm
response = llm.invoke("Hello! How are you today?")
print(response)
```
For more detailed usage examples and documentation, please refer to the [LangChain docs](https://python.langchain.com/docs/integrations/platforms/aws/).
## Contributing
We welcome contributions to this project! Please follow the [contribution guide](https://github.com/langchain-ai/langchain-aws/blob/main/.github/CONTRIBUTING.md) for instructions to setup the project for development and guidance on how to contribute effectively.
## License
This project is licensed under the [MIT License](LICENSE).