stansler

A new open source UI Toolkit to facilitate LLM-generated UIs. A2UI is built with A2A protocol and allows an A2A agent to send interactive components instead of just text, using a high level framework-agnostic format that can be rendered natively on any surface (starting with examples for web and mobile).

- Based on A2A - Streamable JSON Lines (JSONL) - Truly Framework-Agnostic

Great graphics! Cyberpunk-styled gandalf

Would be nice to have a better resolution for a sample video on YouTube (https://www.youtube.com/watch?v=FtOQddvp_U4), 64 million times sharper, but video quality is only 240p :)

Another approach is to use Database Lab (https://gitlab.com/postgres-ai/database-lab). Our tool allows deploying disposable Postgres databases in seconds using REST API, CLI, or GUI. The difference is that we provide clones with snapshots of full-sized data. For example, you may have dozens of clones of your production databases (with masked sensitive data) to use as staging servers, database migration verification, tests, and all that provisioned in a couple of seconds.

More about using full-sized Postgres clones for migration testing and why is that important: https://postgres.ai/products/database-migration-testing

Another approach is to use thin clones of Postgres to create disposable databases for fast iterations.

We've made Database Lab tool working on top of CoW file systems (ZFS, LVM) that is capable of provision multiterabyte Postgres instances in seconds. The goal is to use such clones to verify database migrations and optimize SQL queries against production-size data. See our repo: https://gitlab.com/postgres-ai/database-lab.

Joe running in Slack is indeed a way to simplify and speed-up SQL optimization workflow for developers, as it takes seconds to get initial query execution plans and optimization recommendations.

>... With a Slack interface, so you don't need to bother with connection, provisioning, credentials and decommissioning.

It's worth noticing that Joe is a use case of Database Lab (https://gitlab.com/postgres-ai/database-lab) and it's still possible to use Database Lab features like thin-clones provisioning of production-sized databases and fast data state reset with Database Lab client CLI (https://postgres.ai/docs/database-lab/6_cli_reference) for purposes of SQL optimization without Slack integration. If a user has sufficient access to the data they can provision thin-clone with Database Lab client CLI and use psql to work with the clone.

Also, we have plans to add support of recommendations and statistics in CLI and REST API to the support of various messaging platforms in the future.