Friday, June 21, 2024

JavaScript AI Chat: NLUX

The Powerful Conversational AI JavaScript Library | NLUX
✔️ AI Chat Component
✔️ React Support
✔️ Next.js Support
✔️ Hugging Face Adapter
✔️ LangChain LangServe Adapters
✔️ Custom Adapters
✔️ Assistant and User Personas
✔️ Markdown Streaming
✔️ Syntax Highlighter
✔️ Event Listeners
✔️ Conversation History
✔️ Context-Aware Conversations
✔️ Conversation Starters
✔️ Advanced Theming

AI DB: Amazon Aurora Postgres + pgvector

Amazon Aurora PostgreSQL now supports pgvector for vector storage and similarity search

Amazon Aurora PostgreSQL-Compatible Edition now supports the pgvector extension to store embeddings from machine learning (ML) models in your database and to perform efficient similarity searches. Embeddings are numerical representations (vectors) created from generative AI that capture the semantic meaning of text input into a large language model (LLM). pgvector can store and search embeddings from Amazon Bedrock, Amazon SageMaker, and more.

Open-source vector similarity search for Postgres

Store your vectors with the rest of your data. Supports:exact and approximate nearest neighbor search
single-precision, half-precision, binary, and sparse vectors
L2 distance, inner product, cosine distance, L1 distance, Hamming distance, and Jaccard distance
any language with a Postgres client

Plus ACID compliance, point-in-time recovery, JOINs, and all of the other great features of Postgres

AI tool: text => SQL: Vanna.AI

Vanna.AI - Personalized AI SQL Agent

"Let Vanna.AI write your SQL for you
The fastest way to get actionable insights from your database just by asking questions"

The Vanna Python package and the various frontend integrations are all open-source.
You can run Vanna on your own infrastructure.