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langchain/templates/rag-pinecone-rerank
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Erick Friis 4b16601d33
Format Templates (#12396)
2023-10-26 19:44:30 -07:00
..
rag_pinecone_rerank Format Templates (#12396) 2023-10-26 19:44:30 -07:00
tests Cohere re-rank template (#12378) 2023-10-26 15:29:10 -07:00
LICENSE Cohere re-rank template (#12378) 2023-10-26 15:29:10 -07:00
poetry.lock Cohere re-rank template (#12378) 2023-10-26 15:29:10 -07:00
pyproject.toml Minor updates to ReRank template (#12388) 2023-10-26 16:05:17 -07:00
rag_pinecone_rerank.ipynb Minor updates to ReRank template (#12388) 2023-10-26 16:05:17 -07:00
README.md Cohere re-rank template (#12378) 2023-10-26 15:29:10 -07:00

README.md

RAG Pinecone Cohere Re-rank

This template performs RAG using Pinecone and OpenAI, with Cohere to perform re-ranking on returned documents.

Re-ranking provides a way to rank retrieved documents using specified filters or criteria.

Pinecone

This connects to a hosted Pinecone vectorstore.

Be sure that you have set a few env variables in chain.py:

  • PINECONE_API_KEY
  • PINECONE_ENV
  • index_name

LLM

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

Cohere

Be sure that COHERE_API_KEY is set in order to the ReRank endpoint.