January 2024 Summaries

PartyKit AI, a selection of LLMs and a vector database integrated into the PartyKit environment, is designed to make using AI models as simple as possible. It offers various AI models such as text generation, text-to-image transformation, speech-to-text conversion, and text and image classification. The integration of AI with real-time collaboration in PartyKit allows for advanced capabilities like semantic search and Retrieval-Augmented Generation (RAG). Users can connect to third-party vector databases or use alternative Large Language Models (LLMs) beyond Llama2 and Mistral. The combination of long-lived multiplayer rooms and AI models opens up a world of possibilities for building AI agents and collaborative experiences between humans and AI.

The text discusses the implementation of semantic search using AI and embedding models. It explains how to convert any string of text into a vector and store it in a vector database, where nearby vectors mean approximately the same thing. The author demonstrates building a search engine for their side project website Braggoscope, which uses an unofficial directory of BBC Radio 4's show In Our Time. They walk through setting up a vector database, embedding model, and creating a minimal PartyKit server to manage indexing and querying. The text also touches upon the use of vector databases in retrieval-augmented generation (RAG) for AI chatbots and copilot experiences.