77cf56e54a
* Embeddings plugin hook + OpenAI implementation * llm.get_embedding_model(name) function * llm embed command, for returning embeddings or saving them to SQLite * Tests using an EmbedDemo embedding model * llm embed-models list and emeb-models default commands * llm embed-db path and llm embed-db collections commands |
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| Justfile | ||
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| MANIFEST.in | ||
| mypy.ini | ||
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LLM
A CLI utility and Python library for interacting with Large Language Models, including OpenAI, PaLM and local models installed on your own machine.
Full documentation: llm.datasette.io
Background on this project:
- llm, ttok and strip-tags—CLI tools for working with ChatGPT and other LLMs
- The LLM CLI tool now supports self-hosted language models via plugins
- Accessing Llama 2 from the command-line with the llm-replicate plugin
- Run Llama 2 on your own Mac using LLM and Homebrew
- Catching up on the weird world of LLMs
Installation
Install this tool using pip:
pip install llm
Or using Homebrew:
brew 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:
llm keys set openai
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.
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