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llm-anyscale-endpoints's Introduction

llm-anyscale-endpoints

PyPI Changelog Tests License

LLM plugin for models hosted by Anyscale Endpoints

Installation

First, install the LLM command-line utility.

Now install this plugin in the same environment as LLM.

llm install llm-anyscale-endpoints

Configuration

You will need an API key from Anyscale Endpoints. You can obtain one here.

You can set that as an environment variable called LLM_ANYSCALE_ENDPOINTS_KEY, or add it to the llm set of saved keys using:

llm keys set anyscale-endpoints
Enter key: <paste key here>

Usage

To list available models, run:

llm models list

You should see a list that looks something like this:

AnyscaleEndpoints: meta-llama/Llama-2-7b-chat-hf
AnyscaleEndpoints: meta-llama/Llama-2-13b-chat-hf
AnyscaleEndpoints: mistralai/Mixtral-8x7B-Instruct-v0.1
AnyscaleEndpoints: mistralai/Mistral-7B-Instruct-v0.1
AnyscaleEndpoints: meta-llama/Llama-2-70b-chat-hf
AnyscaleEndpoints: meta-llama/Llama-3-8b-chat-hf
AnyscaleEndpoints: meta-llama/Llama-3-70b-chat-hf
AnyscaleEndpoints: codellama/CodeLlama-70b-Instruct-hf
AnyscaleEndpoints: mistralai/Mixtral-8x22B-Instruct-v0.1
AnyscaleEndpoints: mlabonne/NeuralHermes-2.5-Mistral-7B
AnyscaleEndpoints: google/gemma-7b-it

To run a prompt against a model, pass its full model ID to the -m option, like this:

llm -m mistralai/Mixtral-8x22B-Instruct-v0.1 \
  'Five strident names for a pet walrus' \
  --system 'You love coming up with creative names for pets'

You can set a shorter alias for a model using the llm aliases command like so:

llm aliases set mix22b mistralai/Mixtral-8x22B-Instruct-v0.1

Now you can prompt Mixtral-8x22B-Instruct-v0.1 using the alias mix22b:

cat llm_anyscale_endpoints.py | \
  llm -m mix22b -s 'explain this code'

You can refresh the list of models by running:

llm anyscale-endpoints refresh

This will fetch the latest list of models from Anyscale Endpoints and story it in a local cache file.

Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

cd llm-anyscale-endpoints
python3 -m venv venv
source venv/bin/activate

Now install the dependencies and test dependencies:

pip install -e '.[test]'

To run the tests:

pytest

llm-anyscale-endpoints's People

Contributors

simonw avatar nikitajz avatar

Stargazers

Jeff Fan avatar  avatar Anubhav avatar Alex Kwiatkowski avatar Christopher Carroll Smith avatar Daniel Martinez avatar Umar Hansa avatar 爱可可-爱生活 avatar Tiberiu Ichim avatar Devon 'fire' Adkisson avatar Michael Warkentin avatar John D. Pope avatar Alexander Cohen @capitolmuckrakr avatar Josh Mize avatar Artur Shlyapnikov avatar SJ avatar Martin Amm avatar  avatar  avatar Erin Lee avatar Tim Kersey avatar  avatar Nick Dhima avatar Shyam Sudhakaran avatar Christopher Peisert avatar Patrick Lima avatar  avatar  avatar Vincent avatar Hussein Lezzaik avatar Ivandir avatar  avatar

Watchers

 avatar Sam Hahn avatar  avatar

llm-anyscale-endpoints's Issues

Automatically add all models

The model list is hard-coded at the moment:

MODELS = (
"meta-llama/Llama-2-7b-chat-hf",
"meta-llama/Llama-2-13b-chat-hf",
"meta-llama/Llama-2-70b-chat-hf",
"codellama/CodeLlama-34b-Instruct-hf",
"mistralai/Mistral-7B-Instruct-v0.1",
"mistralai/Mixtral-8x7B-Instruct-v0.1",
"Open-Orca/Mistral-7B-OpenOrca",
"HuggingFaceH4/zephyr-7b-beta",
)

Looks like there's an undocumented API endpoint at /v1/models that could be used to get the models dynamically instead.

codellama/CodeLlama-34b-Instruct-hf

Code Llama is now available as codellama/CodeLlama-34b-Instruct-hf

It looks like you can't link directly to the documentation page, so here's a screenshot:

Supported models > codellama/CodeLlama-34b-Instruct-hf codellama/CodeLlama-34b-Instruct-hf © INFO Refer to the Hugging Face model page for more model details. About this model Model name to use in API calls: codellama/CodeLlama-34b-Instruct-hf Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the 34B parameter version, fine tuned for instructions. This model is designed for general code synthesis and understanding. Links to other models can be found in the index at the bottom.

Include Llama 3 models

These are currently available if you know to run llm anyscale-endpoints refresh but it would be better if they came out of the box.

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