Tutorials & How‑Tos Build and deploy a RAG app with Pinecone Serverless
Deploy a production RAG application using Pinecone Serverless, LangServe, and LangSmith observability following the template repo.
Deploy a production RAG application using Pinecone Serverless, LangServe, and LangSmith observability following the template repo.
Summary
Pinecone Serverless launches unlimited index capacity via cloud object storage and introduces usage‑based pricing, eliminating the need to provision a dedicated index or pay a fixed monthly fee. The article explains how LangServe maps LCEL chain methods to HTTP endpoints, enabling rapid deployment of any chain as a production web service. LangSmith observability integrates seamlessly with Hosted LangServe, providing real‑time monitoring of inputs and outputs. A template repo demonstrates connecting a Pinecone Serverless index to a RAG chain that uses Cohere embeddings for similarity search and GPT‑4 for answer synthesis. The demo shows how to convert the chain into a web service with LangServe, deploy it with Hosted LangServe, and monitor it with LangSmith. The article includes a video and a GitHub repo (https://github.com/langchain-ai/pinecone-serverless). It addresses pain points such as provisioning your own Pinecone index and fixed monthly pricing, and shows how Pinecone Serverless reduces cost to serve. The piece was published on January 16, 2024 and highlights the synergy between Pinecone Serverless, LangServe, and LangSmith for production RAG applications.
Key changes
- Pinecone Serverless offers unlimited index capacity via cloud object storage and usage‑based pricing
- Addresses pain points of provisioning own Pinecone index and fixed monthly pricing
- LangServe maps LCEL chain methods to HTTP endpoints for production deployment
- LangSmith provides observability for LangServe services
- Template repo demonstrates connecting Pinecone Serverless with Cohere embeddings and GPT‑4 for RAG
- Hosted LangServe enables rapid deployment of RAG chains as web services
- Pinecone Serverless reduces cost to serve, allowing pay‑for‑what‑you‑use
- Article includes a video and a GitHub repo (https://github.com/langchain-ai/pinecone-serverless)