After always ending up north of 500 browser tabs open with (mostly) LLM-related content i try to migrate the links into this repo. This allows also for a better organisation and commentary. I try to add comments per link/topic. The content here is (currently) mainly used to help me to remember certain information, which i found along the way. This page focuses on LLM topics. Other topics are covered on dedicated pages.
Fuck You, Show Me The Prompt. In this blog post, I’ll show you how you can intercept API calls w/prompts for any tool, without having to fumble through docs or read source code. I’ll show you how to setup and operate mitmproxy with examples from the LLM the tools I previously mentioned. Lots of interesting details about prompts and ways of how to analyze whats going on.
Vector DB Comparison is a very handy site, listing a lot of database and comparing features.
VectorIO. This library uses a universal format for vector datasets to easily export and import data from all vector databases.
VectorFlow. Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably
Site with docs and demo video
Building Generative AI Applications Using MongoDB: Harnessing the Power of Atlas Vector Search and Open Source Models. Nice intro into using MongoDB as a VectorDB. Easy to follow examples
Multimodal Vector-Search Using CLIP on MongoDB. This notebook demonstrates how SuperDuperDB can perform multimodal searches using the VectorIndex. It highlights SuperDuperDB's flexibility in integrating different models for vectorizing diverse queries during search and inference. In this example, we utilize the CLIP multimodal architecture.
MongoDB joins Cassandra, PostgreSQL and SingleStore in implementing AI-friendly features https://www.theregister.com/2023/07/11/vector_databases/ Lightweight backgrounder, mentioning MongoDB
5 Best Courses on Vector Database https://analyticsindiamag.com/5-best-courses-on-vector-database/
Vector store and query engine for video recordings. This demo helps you build a vector database using your recordings using LlamaIndex and Chroma.
Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search. Learn how to use vector search and embeddings to easily combine your data with large language models like GPT-4. You will first learn the concepts and then create three projects.
Zeta Alpha Trends in AI. Monthly updates lasting around one hour.