RAG
Embeddings & Chunks
Use the Panora API to retrieve your documents embedding sand chunks for your LLMs.
Once we’ve synced documents across File Storage systems, we embed and chunk them so you can power your RAG applications and enable advanced retrieval search.
Step 1: Import the code snippet
Use the SDK
Congrats ! You should be able to get back your embeddings and chunks for the query !
If you selfhost, please make sure to do step 2 or directly fill these env vars in your .env here!
By default, for embedding we use OpenAI ADA-002 model and Pinecone managed vector database for storing the chunks.
Step 2 (Optional): Choose your own Vector DB + Embedding Model
In Configuration page, choose the RAG settings page and provide your own credentials for vector database and embedding model.
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