Simon Willison’s Weblog

q What do I title this article? (via) Christoffer Stjernlöf built this delightfully simple shell script on top of LLM. Save the following as q somewhere in your path and run chmod 755 on it:

#!/bin/sh
llm -s "Answer in as few words as possible. Use a brief style with short replies." -m claude-3.5-sonnet "$*"

The "$*" piece is the real magic here - it concatenates together all of the positional arguments passed to the script, which means you can run the command like this:

q How do I run Docker with a different entrypoint to that in the container

And get an answer back straight away in your terminal. Piping works too:

cat LICENSE | q What license is this

# 7th August 2024, 5:32 pm / llm, llms, ai, generative-ai

llm-gguf. I just released a new alpha plugin for LLM which adds support for running models from Meta's new Llama 3.1 family that have been packaged as GGUF files - it should work for other GGUF chat models too.

If you've already installed LLM the following set of commands should get you setup with Llama 3.1 8B:

llm install llm-gguf
llm gguf download-model \
  https://huggingface.co/lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf \
  --alias llama-3.1-8b-instruct --alias l31i

This will download a 4.92GB GGUF from lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF on Hugging Face and save it (at least on macOS) to your ~/Library/Application Support/io.datasette.llm/gguf/models folder.

Once installed like that, you can run prompts through the model like so:

llm -m l31i "five great names for a pet lemur"

Or use the llm chat command to keep the model resident in memory and run an interactive chat session with it:

llm chat -m l31i

I decided to ship a new alpha plugin rather than update my existing llm-llama-cpp plugin because that older plugin has some design decisions baked in from the Llama 2 release which no longer make sense, and having a fresh plugin gave me a fresh slate to adopt the latest features from the excellent underlying llama-cpp-python library by Andrei Betlen.

# 23rd July 2024, 10:18 pm / meta, llm, generative-ai, llama, projects, ai, llms

LLM 0.15. A new release of my LLM CLI tool for interacting with Large Language Models from the terminal (see this recent talk for plenty of demos).

This release adds support for the brand new GPT-4o mini:

llm -m gpt-4o-mini "rave about pelicans in Spanish"

It also sets that model as the default used by the tool if no other model is specified. This replaces GPT-3.5 Turbo, the default since the first release of LLM. 4o-mini is both cheaper and way more capable than 3.5 Turbo.

# 18th July 2024, 7:44 pm / llm, projects, generative-ai, openai, ai, llms, cli

Mistral NeMo. Released by Mistral today: "Our new best small model. A state-of-the-art 12B model with 128k context length, built in collaboration with NVIDIA, and released under the Apache 2.0 license."

Nice to see Mistral use Apache 2.0 for this, unlike their Codestral 22B release - though Codestral Mamba was Apache 2.0 as well.

Mistral's own benchmarks put NeMo slightly ahead of the smaller (but same general weight class) Gemma 2 9B and Llama 3 8B models.

It's both multi-lingual and trained for tool usage:

The model is designed for global, multilingual applications. It is trained on function calling, has a large context window, and is particularly strong in English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.

Part of this is down to the new Tekken tokenizer, which is 30% more efficient at representing both source code and most of the above listed languages.

You can try it out via Mistral's API using llm-mistral like this:

pipx install llm
llm install llm-mistral
llm keys set mistral
# paste La Plateforme API key here
llm mistral refresh # if you installed the plugin before
llm -m mistral/open-mistral-nemo 'Rave about pelicans in French'

# 18th July 2024, 4:40 pm / mistral, generative-ai, llm-tool-use, ai, llms, llm, llm-release, local-llms

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!

# 17th July 2024, 3:20 am / djangocon, python, plugins, django, speaking, sqlite-utils, llm, datasette

Codestral Mamba. New 7B parameter LLM from Mistral, released today. Codestral Mamba is "a Mamba2 language model specialised in code generation, available under an Apache 2.0 license".

This the first model from Mistral that uses the Mamba architecture, as opposed to the much more common Transformers architecture. Mistral say that Mamba can offer faster responses irrespective of input length which makes it ideal for code auto-completion, hence why they chose to specialise the model in code.

It's available to run locally with the mistral-inference GPU library, and Mistral say "For local inference, keep an eye out for support in llama.cpp" (relevant issue).

It's also available through Mistral's La Plateforme API. I just shipped llm-mistral 0.4 adding a llm -m codestral-mamba "prompt goes here" default alias for the new model.

Also released today: MathΣtral, a 7B Apache 2 licensed model "designed for math reasoning and scientific discovery", with a 32,000 context window. This one isn't available through their API yet, but the weights are available on Hugging Face.

# 16th July 2024, 4:29 pm / open-source, mistral, llm, generative-ai, ai, llms, llm-release, local-llms

llm-claude-3 0.4. LLM plugin release adding support for the new Claude 3.5 Sonnet model:

pipx install llm
llm install -U llm-claude-3
llm keys set claude
# paste AP| key here
llm -m claude-3.5-sonnet \
  'a joke about a pelican and a walrus having lunch'

# 20th June 2024, 11:04 pm / llm, anthropic, claude, generative-ai, projects, ai, llms, claude-3-5-sonnet

llm-gemini 0.1a4. A new release of my llm-gemini plugin adding support for the Gemini 1.5 Flash model that was revealed this morning at Google I/O.

I'm excited about this new model because of its low price. Flash is $0.35 per 1 million tokens for prompts up to 128K token and $0.70 per 1 million tokens for longer prompts - up to a million tokens now and potentially two million at some point in the future. That's 1/10th of the price of Gemini Pro 1.5, cheaper than GPT 3.5 ($0.50/million) and only a little more expensive than Claude 3 Haiku ($0.25/million).

# 14th May 2024, 8:32 pm / gemini, llm, generative-ai, projects, ai, google-io, llms, llm-release

LLM 0.14, with support for GPT-4o. It's been a while since the last LLM release. This one adds support for OpenAI's new model:

llm -m gpt-4o "fascinate me"

Also a new llm logs -r (or --response) option for getting back just the response from your last prompt, without wrapping it in Markdown that includes the prompt.

Plus nine new plugins since 0.13!

# 13th May 2024, 9 pm / llm, projects, generative-ai, openai, ai, llms

microsoft/Phi-3-mini-4k-instruct-gguf (via) Microsoft’s Phi-3 LLM is out and it’s really impressive. This 4,000 token context GGUF model is just a 2.2GB (for the Q4 version) and ran on my Mac using the llamafile option described in the README. I could then run prompts through it using the llm-llamafile plugin.

The vibes are good! Initial test prompts I’ve tried feel similar to much larger 7B models, despite using just a few GBs of RAM. Tokens are returned fast too—it feels like the fastest model I’ve tried yet.

And it’s MIT licensed.

# 23rd April 2024, 5:40 pm / llms, llm, generative-ai, ai, local-llms, microsoft, phi