Closed tsibg closed 3 months ago
Thank you @tsibg both for engaging and also for the PR. Let's get it merged in.
Thanks for merging it.
Just a few ideas for future implementations:
Closing this issue as my use case is fully covered with the merge. Thanks again for the fast collab!
Published new version 0.0.72
with merged changes.
I like the idea of natively supporting multimodal. RAG is still useful in a multimodal setup. I will start a discussion thread on the best way to go ahead with support for this in the library.
I am interested in support for Gemini models, preferably on VertexAI by Google Cloud Platform. The Gemini 1.5 Pro supports up to 1M Context, which could open a bunch of possibilities for grounding and RAG. Further more it is multimodal (text, images, audio, PDFs, code, videos).
Resources for the integration:
LLM and Embedding models on VertexAI:
Langchain LLM support for VertexAI and all Gemini models:
Langchain Embeddings on VertexAI (Expirimental): Supports both
textembedding-gecko
andmultimodalembedding@001
I'm currently working on the integration, it looks pretty straight forward. Will also submit a PR, if the authors are interested.
P.S. Thanks for creating this library, well structured and easy to use.