97 items tagged “plugins”
2024
llm-gemini 0.4.
New release of my llm-gemini plugin, adding support for asynchronous models (see LLM 0.18), plus the new gemini-exp-1114 model (currently at the top of the Chatbot Arena) and a -o json_object 1 option to force JSON output.
I also released llm-claude-3 0.9 which adds asynchronous support for the Claude family of models.
django-plugin-django-debug-toolbar (via) Tom Viner built a plugin for my DJP Django plugin system that configures the excellent django-debug-toolbar debugging tool.
You can see everything it sets up for you in this Python code: it configures installed apps, URL patterns and middleware and sets the INTERNAL_IPS and DEBUG settings.
Here are Tom's running notes as he created the plugin.
llm-whisper-api. I wanted to run an experiment through the OpenAI Whisper API this morning so I knocked up a very quick plugin for LLM that provides the following interface:
llm install llm-whisper-api
llm whisper-api myfile.mp3 > transcript.txt
It uses the API key that you previously configured using the llm keys set openai command. If you haven't configured one you can pass it as --key XXX instead.
It's a tiny plugin: the source code is here.
Run a prompt to generate and execute jq programs using llm-jq
llm-jq is a brand new plugin for LLM which lets you pipe JSON directly into the llm jq command along with a human-language description of how you’d like to manipulate that JSON and have a jq program generated and executed for you on the fly.
django-plugin-datasette. I did some more work on my DJP plugin mechanism for Django at the DjangoCon US sprints today. I added a new plugin hook, asgi_wrapper(), released in DJP 0.3 and inspired by the similar hook in Datasette.
The hook only works for Django apps that are served using ASGI. It allows plugins to add their own wrapping ASGI middleware around the Django app itself, which means they can do things like attach entirely separate ASGI-compatible applications outside of the regular Django request/response cycle.
Datasette is one of those ASGI-compatible applications!
django-plugin-datasette uses that new hook to configure a new URL, /-/datasette/, which serves a full Datasette instance that scans through Django’s settings.DATABASES dictionary and serves an explore interface on top of any SQLite databases it finds there.
It doesn’t support authentication yet, so this will expose your entire database contents - probably best used as a local debugging tool only.
I did borrow some code from the datasette-mask-columns plugin to ensure that the password column in the auth_user column is reliably redacted. That column contains a heavily salted hashed password so exposing it isn’t necessarily a disaster, but I like to default to keeping hashes safe.
DJP: A plugin system for Django
DJP is a new plugin mechanism for Django, built on top of Pluggy. I announced the first version of DJP during my talk yesterday at DjangoCon US 2024, How to design and implement extensible software with plugins. I’ll post a full write-up of that talk once the video becomes available—this post describes DJP and how to use what I’ve built so far.
[... 1,664 words]datasette-checkbox. I built this fun little Datasette plugin today, inspired by a conversation I had in Datasette Office Hours.
If a user has the update-row permission and the table they are viewing has any integer columns with names that start with is_ or should_ or has_, the plugin adds interactive checkboxes to that table which can be toggled to update the underlying rows.
This makes it easy to quickly spin up an interface that allows users to review and update boolean flags in a table.
I have ambitions for a much more advanced version of this, where users can do things like add or remove tags from rows directly in that table interface - but for the moment this is a neat starting point, and it only took an hour to build (thanks to help from Claude to build an initial prototype, chat transcript here).
Announcing our DjangoCon US 2024 Talks! I'm speaking at DjangoCon in Durham, NC in September.
My accepted talk title was How to design and implement extensible software with plugins. Here's my abstract:
Plugins offer a powerful way to extend software packages. Tools that support a plugin architecture include WordPress, Jupyter, VS Code and pytest - each of which benefits from an enormous array of plugins adding all kinds of new features and expanded capabilities.
Adding plugin support to an open source project can greatly reduce the friction involved in attracting new contributors. Users can work independently and even package and publish their work without needing to directly coordinate with the project's core maintainers. As a maintainer this means you can wake up one morning and your software grew new features without you even having to review a pull request!
There's one catch: information on how to design and implement plugin support for a project is scarce.
I now have three major open source projects that support plugins, with over 200 plugins published across those projects. I'll talk about everything I've learned along the way: when and how to use plugins, how to design plugin hooks and how to ensure your plugin authors have as good an experience as possible.
I'm going to be talking about what I've learned integrating Pluggy with Datasette, LLM and sqlite-utils. I've been looking for an excuse to turn this knowledge into a talk for ages, very excited to get to do it at DjangoCon!
datasette-python.
I just released a small new plugin for Datasette to assist with debugging. It adds a python subcommand which runs a Python process in the same virtual environment as Datasette itself.
I built it initially to help debug some issues in Datasette installed via Homebrew. The Homebrew installation has its own virtual environment, and sometimes it can be useful to run commands like pip list in the same environment as Datasette itself.
Now you can do this:
brew install datasette
datasette install datasette-python
datasette python -m pip list
I built a similar plugin for LLM last year, called llm-python - it's proved useful enough that I duplicated the design for Datasette.
datasette-pins — a new Datasette plugin for pinning tables and queries. Alex Garcia built this plugin for Datasette Cloud, and as with almost every Datasette Cloud features we're releasing it as an open source package as well.
datasette-pins allows users with the right permission to "pin" tables, databases and queries to their homepage. It's a lightweight way to customize that homepage, especially useful as your Datasette instance grows to host dozens or even hundreds of tables.
llm-gpt4all. New release of my LLM plugin which builds on Nomic's excellent gpt4all Python library. I've upgraded to their latest version which adds support for Llama 3 8B Instruct, so after a 4.4GB model download this works:
llm -m Meta-Llama-3-8B-Instruct "say hi in Spanish"
datasette-import. A new plugin for importing data into Datasette. This is a replacement for datasette-paste, duplicating and extending its functionality. datasette-paste had grown beyond just dealing with pasted CSV/TSV/JSON data—it handles file uploads as well now—which inspired the new name.
llm-command-r. Cohere released Command R Plus today—an open weights (non commercial/research only) 104 billion parameter LLM, a big step up from their previous 35 billion Command R model.
Both models are fine-tuned for both tool use and RAG. The commercial API has features to expose this functionality, including a web-search connector which lets the model run web searches as part of answering the prompt and return documents and citations as part of the JSON response.
I released a new plugin for my LLM command line tool this morning adding support for the Command R models.
In addition to the two models it also adds a custom command for running prompts with web search enabled and listing the referenced documents.
llm-nomic-api-embed. My new plugin for LLM which adds API access to the Nomic series of embedding models. Nomic models can be run locally too, which makes them a great long-term commitment as there’s no risk of the models being retired in a way that damages the value of your previously calculated embedding vectors.
datasette-studio. I've been thinking for a while that it might be interesting to have a version of Datasette that comes bundled with a set of useful plugins, aimed at expanding Datasette's default functionality to cover things like importing data and editing schemas.
This morning I built the very first experimental preview of what that could look like. Install it using pipx:
pipx install datasette-studio
I recommend pipx because it will ensure datasette-studio gets its own isolated environment, independent of any other Datasette installations you might have.
Now running datasette-studio instead of datasette will get you the version with the bundled plugins.
The implementation of this is fun - it's a single pyproject.toml file defining the dependencies and setting up the datasette-studio CLI hook, which is enough to provide the full set of functionality.
Is this a good idea? I don't know yet, but it's certainly an interesting initial experiment.
Datasette 1.0a8: JavaScript plugins, new plugin hooks and plugin configuration in datasette.yaml
I just released Datasette 1.0a8. These are the annotated release notes.
[... 1,709 words]llm-sentence-transformers 0.2. I added a new --trust-remote-code option when registering an embedding model, which means LLM can now run embeddings through the new Nomic AI nomic-embed-text-v1 model.
llm-embed-onnx. I wrote a new plugin for LLM that acts as a thin wrapper around onnx_embedding_models by Benjamin Anderson, providing access to seven embedding models that can run on the ONNX model framework.
The actual plugin is around 50 lines of code, which makes for a nice example of how thin a plugin wrapper can be that adds new models to my LLM tool.
2023
datasette-plot—a new Datasette Plugin for building data visualizations. I forgot to link to this here last week: Alex Garcia released the first version of datasette-plot, a brand new Datasette visualization plugin built on top of the Observable Plot charting library. We plan to use this as the new, updated alternative to my older datasette-vega plugin.
Many options for running Mistral models in your terminal using LLM
Mistral AI is the most exciting AI research lab at the moment. They’ve now released two extremely powerful smaller Large Language Models under an Apache 2 license, and have a third much larger one that’s available via their API.
[... 2,063 words]Datasette Enrichments: a new plugin framework for augmenting your data
Today I’m releasing datasette-enrichments, a new feature for Datasette which provides a framework for applying “enrichments” that can augment your data.
[... 1,202 words]Execute Jina embeddings with a CLI using llm-embed-jina
Berlin-based Jina AI just released a new family of embedding models, boasting that they are the “world’s first open-source 8K text embedding model” and that they rival OpenAI’s text-embedding-ada-002 in quality.
Weeknotes: Embeddings, more embeddings and Datasette Cloud
Since my last weeknotes, a flurry of activity. LLM has embeddings support now, and Datasette Cloud has driven some major improvements to the wider Datasette ecosystem.
[... 2,427 words]Introducing datasette-litestream: easy replication for SQLite databases in Datasette. We use Litestream on Datasette Cloud for streaming backups of user data to S3. Alex Garcia extracted out our implementation into a standalone Datasette plugin, which bundles the Litestream Go binary (for the relevant platform) in the package you get when you run “datasette install datasette-litestream”—so now Datasette has a very robust answer to questions about SQLite disaster recovery beyond just the Datasette Cloud platform.
Datasette 1.0a4 and 1.0a5, plus weeknotes
Two new alpha releases of Datasette, plus a keynote at WordCamp, a new LLM release, two new LLM plugins and a flurry of TILs.
[... 2,709 words]Datasette Cloud, Datasette 1.0a3, llm-mlc and more
Datasette Cloud is now a significant step closer to general availability. The Datasette 1.03 alpha release is out, with a mostly finalized JSON format for 1.0. Plus new plugins for LLM and sqlite-utils and a flurry of things I’ve learned.
[... 1,690 words]Introducing datasette-write-ui: a Datasette plugin for editing, inserting, and deleting rows. Alex García is working with me on Datasette Cloud for the next few months, graciously sponsored by Fly. We will be working in public, releasing open source code and documenting how to build a multi-tenant SaaS product using Fly Machines.
Alex’s first project is datasette-write-ui, a plugin that finally lets you directly edit data stored inside Datasette. Alex wrote about the plugin on our new Datasette Cloud blog.
llm-mlc (via) My latest plugin for LLM adds support for models that use the MLC Python library—which is the first library I’ve managed to get to run Llama 2 with GPU acceleration on my M2 Mac laptop.
Weeknotes: Plugins for LLM, sqlite-utils and Datasette
The principle theme for the past few weeks has been plugins.
[... 1,203 words]Run Llama 2 on your own Mac using LLM and Homebrew
Llama 2 is the latest commercially usable openly licensed Large Language Model, released by Meta AI a few weeks ago. I just released a new plugin for my LLM utility that adds support for Llama 2 and many other llama-cpp compatible models.
[... 1,423 words]