@mrloldev@ctatedev it's not a port of the typescript version, and it's diverging from it in some fundamental ways. we do plan to expand _interoperability_ with it though, that's a big focus from the start
In our new blog post, Andrey shows how to use Gel’s unique features to simplify and streamline the FastAPI + Pydantic AI stack for adding long-term memory to agents.
https://t.co/LOXGxDq18a
@solarperimeter@geldata Of course! We have an entire extension dedicated to that: https://t.co/BNsGUIDX57. The embeddings bit is fully automatic, although there might be a learning curve to using it (we’re working on that)
Nothing quite as anxiety inducing as having a model edit 2000 notes you've gathered over the past few years, and just... trusting it not to mess up 🙈
https://t.co/wE2RrYAFZe
@jerryjliu0 Proud to have been a part of this! We built this to be a part of our internal RAG applications, where using @llama_index is a no-brainer. But personally I think @MathpixApp is kind of a hidden gem in this, indispensable when trying to get anything done with a LaTeX-born PDF.
Building Multimodal RAG over Scientific Papers 🔬📑
Excited to partner with the Tensorsense team (@_abuzin, Sergey, Mark) on a cookbook that shows you how to properly parse, index, and retrieve over scientific papers - this includes diagrams, figures and math equations!
1️⃣ Convert PDF to Latex with @MathpixApp
2️⃣ Process embedded objects with a multimodal model
3️⃣ Retrieve and query over a multimodal collection of items
This gives you the ability to have the LLM understand all the complex sources in your doc: text, images, and tables.
Check it out (first image is example table, second/third images are notebook screenshots): https://t.co/VmWKkkM2hB