Skip to main content

A CLI utility and Python library for interacting with Large Language Models, including OpenAI, PaLM and local models installed on your own machine.

Project description

LLM

PyPI Documentation Changelog Tests License Discord Homebrew

A CLI utility and Python library for interacting with Large Language Models, both via remote APIs and models that can be installed and run on your own machine.

Run prompts from the command-line, store the results in SQLite, generate embeddings and more.

Full documentation: llm.datasette.io

Background on this project:

Installation

Install this tool using pip:

pip install llm

Or using pipx:

pipx install llm

Detailed installation instructions.

Getting started

If you have an OpenAI API key you can get started using the OpenAI models right away.

As an alternative to OpenAI, you can install plugins to access models by other providers, including models that can be installed and run on your own device.

Save your OpenAI API key like this:

llm keys set openai

This will prompt you for your key like so:

Enter key: <paste here>

Now that you've saved a key you can run a prompt like this:

llm "Five cute names for a pet penguin"
1. Waddles
2. Pebbles
3. Bubbles
4. Flappy
5. Chilly

Read the usage instructions for more.

Installing a model that runs on your own machine

LLM plugins can add support for alternative models, including models that run on your own machine.

To download and run Llama 2 13B locally, you can install the llm-mlc plugin:

llm install llm-mlc
llm mlc pip install --pre --force-reinstall \
  mlc-ai-nightly \
  mlc-chat-nightly \
  -f https://mlc.ai/wheels
llm mlc setup

Then download the 15GB Llama 2 13B model like this:

llm mlc download-model Llama-2-13b-chat --alias llama2

And run a prompt through it:

llm -m llama2 'difference between a llama and an alpaca'

You can also start a chat session with the model using the llm chat command:

llm chat -m llama2
Chatting with mlc-chat-Llama-2-13b-chat-hf-q4f16_1
Type 'exit' or 'quit' to exit
Type '!multi' to enter multiple lines, then '!end' to finish
> 

Using a system prompt

You can use the -s/--system option to set a system prompt, providing instructions for processing other input to the tool.

To describe how the code a file works, try this:

cat mycode.py | llm -s "Explain this code"

Help

For help, run:

llm --help

You can also use:

python -m llm --help

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llm-0.12.tar.gz (35.1 kB view details)

Uploaded Source

Built Distribution

llm-0.12-py3-none-any.whl (36.8 kB view details)

Uploaded Python 3

File details

Details for the file llm-0.12.tar.gz.

File metadata

  • Download URL: llm-0.12.tar.gz
  • Upload date:
  • Size: 35.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for llm-0.12.tar.gz
Algorithm Hash digest
SHA256 e6a3fac275b9b80a29fe018a7b8467d97871fd4194912bcd2a8c844e9aab03d1
MD5 53c6e5cfd8ffabffe71531db37b560a4
BLAKE2b-256 dd556191c46709f6aee2c80fbed7535130f868780f1b152b2e596dc81d202ebe

See more details on using hashes here.

File details

Details for the file llm-0.12-py3-none-any.whl.

File metadata

  • Download URL: llm-0.12-py3-none-any.whl
  • Upload date:
  • Size: 36.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for llm-0.12-py3-none-any.whl
Algorithm Hash digest
SHA256 8873ae105ce73030fb3e0e01379eee57cc456b58373bf17a5d7cf1b0977f5041
MD5 6849af78261abb4684b9c6ad25222adb
BLAKE2b-256 8ea6c75cc3cd35c72abd1f71f21bf232d78c17e0fa12c3872ff2ca356e5c7496

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page