feat: created vector db and embeddings system #19
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- Created a vectordb in Pinecone, with an instance of it created in "pineconeClient.ts". - Created OpenAI client that uses embeddings API to convert text parameter into vector array. - Created 2 routes within embeddings. One route takes provided text, converts it into an embedding using the openAiClient, and then uploads it to the pinecone db. The other route takes in user provided string and retrieves the most similar results from the pinecone db.
(obviously dont want to console log an api key in prod)
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It looks like the workflow does not like that there is no provided Pinecone API key (I am grabbing it from my local env file). A potential fix to this might be to store the Pinecone and OpenAI API keys as GitHub secrets and then assign the secrets to their respective environment variables inside the workflow. |
Check your Discord DMs! |
grabbing env veariables from github secrets.
Nyumat
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Note: I am unsure if people are able to create embeddings with the base tier of openAI. If this is the case, let me know and I will look into an open source embeddings model.