Sublime
An inspiration engine for ideas
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M • 1 card
In LangChain, we first load documents through data loaders. Then we can transform them and pass these documents to a vector store as embedding. We can then query the vector store or a retriever associated with the vector store. Retrievers in LangChain can wrap the loading and vector storage into a single step.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
Communication
Mary Martin • 3 cards
Reading
Patrick Devlin • 1 card
words matter
alexi gunner • 9 cards
PDFs are satan’s file format.
Almost everyone that builds RAG needs to deal with them - and it sucks.
Solutions on the market are either too slow, too expensive or not OSS.
It should be easier. Which is why we’re open sourcing https://t.co/0gCZxzbkWu
Ishaan Kapoorx.comTo Be Formed
Melissa Oppenheim • 1 card
Reading
Blue Archer • 1 card