langchain/templates/rag-conversation/README.md

# Conversational RAG

This template performs [conversational](https://python.langchain.com/docs/expression_language/cookbook/retrieval#conversational-retrieval-chain) [retrieval](https://python.langchain.com/docs/use_cases/question_answering/), which is one of the most popular LLM use-cases.

It passes both a conversation history and retrieved documents into an LLM for synthesis.

##  LLM

Be sure that `OPENAI_API_KEY` is set in order to use the OpenAI models.

##  Pinecone

This template uses Pinecone as a vectorstore and requires that `PINECONE_API_KEY`, `PINECONE_ENVIRONMENT`, and `PINECONE_INDEX` are set.
Allow index name customization via env var in rag-conversation (#12315) 11 months ago			`# Conversational RAG`
Templates (#12294) Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Lance Martin <lance@langchain.dev> Co-authored-by: Jacob Lee <jacoblee93@gmail.com> 11 months ago
			`This template performs [conversational](https://python.langchain.com/docs/expression_language/cookbook/retrieval#conversational-retrieval-chain) [retrieval](https://python.langchain.com/docs/use_cases/question_answering/), which is one of the most popular LLM use-cases.`

			`It passes both a conversation history and retrieved documents into an LLM for synthesis.`

			`## LLM`

			Be sure that `OPENAI_API_KEY` is set in order to use the OpenAI models.

			`## Pinecone`

Add template for Pinecone + Multi-Query (#12353) 11 months ago			This template uses Pinecone as a vectorstore and requires that `PINECONE_API_KEY`, `PINECONE_ENVIRONMENT`, and `PINECONE_INDEX` are set.