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83 lines
3 KiB
Markdown
83 lines
3 KiB
Markdown
# LLM
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[](https://pypi.org/project/llm/)
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[](https://llm.datasette.io/)
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[](https://llm.datasette.io/en/stable/changelog.html)
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[](https://github.com/simonw/llm/actions?query=workflow%3ATest)
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[](https://github.com/simonw/llm/blob/main/LICENSE)
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[](https://datasette.io/discord-llm)
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[](https://formulae.brew.sh/formula/llm)
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A CLI utility and Python library for interacting with Large Language Models, including OpenAI, PaLM and local models installed on your own machine.
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Full documentation: **[llm.datasette.io](https://llm.datasette.io/)**
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Background on this project:
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- [llm, ttok and strip-tags—CLI tools for working with ChatGPT and other LLMs](https://simonwillison.net/2023/May/18/cli-tools-for-llms/)
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- [The LLM CLI tool now supports self-hosted language models via plugins](https://simonwillison.net/2023/Jul/12/llm/)
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- [Accessing Llama 2 from the command-line with the llm-replicate plugin](https://simonwillison.net/2023/Jul/18/accessing-llama-2/)
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- [Run Llama 2 on your own Mac using LLM and Homebrew](https://simonwillison.net/2023/Aug/1/llama-2-mac/)
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- [Catching up on the weird world of LLMs](https://simonwillison.net/2023/Aug/3/weird-world-of-llms/)
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## Installation
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Install this tool using `pip`:
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```bash
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pip install llm
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```
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Or using [Homebrew](https://brew.sh/):
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```bash
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brew install llm
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```
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[Detailed installation instructions](https://llm.datasette.io/en/stable/setup.html).
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## Getting started
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If you have an [OpenAI API key](https://platform.openai.com/account/api-keys) you can get started using the OpenAI models right away.
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As an alternative to OpenAI, you can [install plugins](https://llm.datasette.io/en/stable/plugins/installing-plugins.html) to access models by other providers, including models that can be installed and run on your own device.
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Save your OpenAI API key like this:
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```bash
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llm keys set openai
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```
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This will prompt you for your key like so:
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```bash
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llm keys set openai
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```
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```
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Enter key: <paste here>
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```
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Now that you've saved a key you can run a prompt like this:
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```bash
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llm "Five cute names for a pet penguin"
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```
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```
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1. Waddles
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2. Pebbles
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3. Bubbles
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4. Flappy
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5. Chilly
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```
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Read the [usage instructions](https://llm.datasette.io/en/stable/usage.html) for more.
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## Using a system prompt
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You can use the `-s/--system` option to set a system prompt, providing instructions for processing other input to the tool.
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To describe how the code a file works, try this:
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```bash
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cat mycode.py | llm -s "Explain this code"
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```
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## Help
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For help, run:
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llm --help
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You can also use:
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python -m llm --help
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