CONTRIBUTING.md

Contributing

Setting up

To set up for development, create a conda environment, install lotus, and install additional dev dependencies.

conda create -n lotus python=3.10 -y
conda activate lotus
git clone [email protected]:stanford-futuredata/lotus.git
pip install -e .
pip install -r requirements-dev.txt
pre-commit install

Dev Flow

After making your changes, please make a PR to get your changes merged upstream.

Running Models

To run a model, you can use the LM class in lotus.models.LM. We use the litellm library to interface with the model. This allows you to use any model provider that is supported by litellm.

Here's an example of creating an LM object for gpt-4o

from lotus.models import LM
lm = LM(model="gpt-4o")

Here's an example of creating an LM object to use llama3.2 on Ollama

from lotus.models import LM
lm = LM(model="ollama/llama3.2")

Here's an example of creating an LM object to use Meta-Llama-3-8B-Instruct on vLLM

from lotus.models import LM
lm = LM(model='hosted_vllm/meta-llama/Meta-Llama-3-8B-Instruct',
        api_base='http://localhost:8000/v1',
        max_ctx_len=8000,
        max_tokens=1000)

Helpful Examples

For helpful examples of LOTUS operators, please refer to the examples folder, as well as the documentation.