docs: Update deployments.md to include a BentoML example (#2661)

Add a new deployment example with BentoML, see more
https://github.com/ssheng/BentoChain.
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Sean Sheng 2023-04-10 14:57:32 -07:00 committed by GitHub
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@ -40,3 +40,7 @@ This includes: production ready endpoints, horizontal scaling across dependencie
## [Langchain-serve](https://github.com/jina-ai/langchain-serve) ## [Langchain-serve](https://github.com/jina-ai/langchain-serve)
This repository allows users to serve local chains and agents as RESTful, gRPC, or Websocket APIs thanks to [Jina](https://docs.jina.ai/). Deploy your chains & agents with ease and enjoy independent scaling, serverless and autoscaling APIs, as well as a Streamlit playground on Jina AI Cloud. This repository allows users to serve local chains and agents as RESTful, gRPC, or Websocket APIs thanks to [Jina](https://docs.jina.ai/). Deploy your chains & agents with ease and enjoy independent scaling, serverless and autoscaling APIs, as well as a Streamlit playground on Jina AI Cloud.
## [BentoML](https://github.com/ssheng/BentoChain)
This repository provides an example of how to deploy a LangChain application with [BentoML](https://github.com/bentoml/BentoML). BentoML is a framework that enables the containerization of machine learning applications as standard OCI images. BentoML also allows for the automatic generation of OpenAPI and gRPC endpoints. With BentoML, you can integrate models from all popular ML frameworks and deploy them as microservices running on the most optimal hardware and scaling independently.