simonwillisonblog
zombodb
simonwillisonblog | zombodb | |
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28 | 23 | |
163 | 4,608 | |
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8.1 | 8.3 | |
about 17 hours ago | 21 days ago | |
JavaScript | PLpgSQL | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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simonwillisonblog
- Sandboxing Python with Win32 App Isolation
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AI for Web Devs: Addressing Bugs, Security, & Reliability
Simon Willison has pointed out several examples of prompt injection attacks and why it may never be a solved problem:
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Where Have All the Websites Gone?
I want more people to have link blogs.
I have one in the sidebar of https://simonwillison.net/ which I've been running since November 2003. You can search through all 6,836 links here: https://simonwillison.net/search/?type=blogmark
I can post things to it with a bookmarklet. It has an Atom feed.
It's such a low-friction way of publishing. A lot of https://daringfireball.net works like this too. I also like https://waxy.org/ and https://kottke.org/ for this.
I'd love to see more of these.
- Ask HN: Is it feasible to train my own LLM?
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Moving Away from Substack
My approach is to publish to my own blog at https://simonwillison.net and then copy and paste content from that into a Substack newsletter at https://simonw.substack.com a few times a month.
It's been working really well.
Substack don't have an API, but they do support copy and paste - so I built myself a tool that assembles my blog content into rich text I can copy and paste straight into the Substack editor.
I wrote about how that works here: https://simonwillison.net/2023/Apr/4/substack-observable/
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Building a Blog in Django
Hah, yeah securing something like WordPress can be a challenge, especially if you're running a bunch of plugins.
My blog is a pretty straight-forward Django setup without many other dependencies, so it's a lot less of an attack surface: https://github.com/simonw/simonwillisonblog
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Show HN: Superfunctions – AI prompt templates as an API
That specific prompt is just an example and it's pretty bad, it was the shortest and simplest prompt I could come up with that would be easily understood.
You can set response content-types (text, html, json, etc...). If you use json it will get pretty good results because I have some is some logic to attempt to pick out json or json5 objects from the text output. I dont yet have logic to support json arrays, but I'm hoping to add that soon.
But still client side validation is needed for applications with untrusted input. I dont attempt to solve prompt injection. I saw a lot of interesting posts on this topic from this blog https://simonwillison.net/. I need to find sometime to read more about it.
Try this one instead, it should be better
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Stopping at 90%
I've started to consider "commit to writing about it" as the price I have to pay for giving into the lure of another project. It's one of the main reasons I publish so much content on https://simonwillison.net/ and https://til.simonwillison.net
A project with a published write-up unlocks so much more value than one which you complete without giving others a chance of understanding what you built.
I've maintained internal blogs (sometimes just a Slack channel or Confluence area) at previous employers for this purpose too.
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Stanford A.I. Courses
I think you are asking specifically about practical LLM engineering and not the underlying science.
Honestly this is all moving so fast you can do well by reading the news, following a few reddits/substacks, and skimming the prompt engineering papers as they come out every week (!).
https://www.latent.space/p/ai-engineer provides an early manifesto for this nascent layer of the stack.
Zvi writes a good roundup (though he is concerned mostly with alignment so skip if you don’t like that angle): https://thezvi.substack.com/p/ai-18-the-great-debate-debates
Simon W has some good writeups too: https://simonwillison.net/
I strongly recommend playing with the OpenAI APIs and working with langchain in a Colab notebook to get a feel for how these all fit together. Also, the tools here are incredibly simple and easy to understand (very new) so looking at, say, https://github.com/minimaxir/simpleaichat/tree/main/simpleai... or https://github.com/smol-ai/developer and digging in to the prompts, what goes in system vs assistant roles, how you gourde the LLM, etc.
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Seeking Your Top Recommendations for Resources on ChatGPT and Generative AI
Simon Willison's Weblog
zombodb
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Introducing pgzx: create PostgreSQL extensions using Zig
And lots of interesting extensions use it, like
https://github.com/tembo-io/pgmq
https://github.com/zombodb/zombodb
https://github.com/supabase/pg_jsonschema
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Create a search engine with PostgreSQL: Postgres vs Elasticsearch
Point 2 is generally solvable via engineering effort and careful dedicated code. From the existing tools, PGSync is an open source project that aims to specifically solve this problem. ZomboDB is an interesting Postgres extension that tackles point 2 (and I think partially point 3), by controlling and querying Elasticsearch through Postgres. I haven't yet tried either of these two projects, so I can't comment on their trade-offs, but I wanted to mention them.
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Creating an advanced search engine with PostgreSQL
Curious, did you try zombodb? [https://www.zombodb.com/]
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💃🏼 Quickwit 0.6 released!🕺🏼: Elasticsearch API compatibility, Grafana plugin, and more....
What about zombodb, do you think that quickwit has all the necessary APIs?
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Write Postgres functions in Rust
No. Haha. Was just the right name for https://github.com/zombodb/zombodb at the time. Software where the only limit is yourself!
- Integrate PostgreSQL and Elasticsearch – ZomboDB
- Postgres Full Text Search vs. the Rest
- ZomboDB: Making Postgres and Elasticsearch work together like it's 2022
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Postgres Full-Text Search: A Search Engine in a Database
> The hardest part of building any search engine is keeping the index up-to-date with changes made to the underlying data store.
This deserves mention, as it solves that problem: https://github.com/zombodb/zombodb
From the README:
> ZomboDB brings powerful text-search and analytics features to Postgres by using Elasticsearch as an index type. Its comprehensive query language and SQL functions enable new and creative ways to query your relational data.
> From a technical perspective, ZomboDB is a 100% native Postgres extension that implements Postgres' Index Access Method API. As a native Postgres index type, ZomboDB allows you to CREATE INDEX ... USING zombodb on your existing Postgres tables. At that point, ZomboDB takes over and fully manages the remote Elasticsearch index and guarantees transactionally-correct text-search query results.
I find other things also hard in search engines: dealing with the plethora of human languages and all the requirements we may have to processing them. A mature solution like ES therefor is almost a must in the more demanding cases.
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State of the art for serde-compatible CBOR encoding/decoding?
You can read more about it on our GitHub repo, but basically it brings most of the power of elasticsearch’s searching and analytics abilities straight into Postgres.
What are some alternatives?
pg_cjk_parser - Postgres CJK Parser pg_cjk_parser is a fts (full text search) parser derived from the default parser in PostgreSQL 11. When a postgres database uses utf-8 encoding, this parser supports all the features of the default parser while splitting CJK (Chinese, Japanese, Korean) characters into 2-gram tokens. If the database's encoding is not utf-8, the parser behaves just like the default parser.
pg_search - pg_search builds ActiveRecord named scopes that take advantage of PostgreSQL’s full text search
pgvector - Open-source vector similarity search for Postgres
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
awesome-personal-blogs - A delightful list of personal tech blogs
noria - Fast web applications through dynamic, partially-stateful dataflow
tsv-utils - eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
squawk - 🐘 linter for PostgreSQL, focused on migrations
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
stolon - PostgreSQL cloud native High Availability and more.
knowledge - Everything I know
helium-etl-queries - A collection of SQL views used to enrich data produced by a Helium blockchain-etl