hep-data-llm 1.0.0b3

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hep-data-llm

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Table of Contents

• Installation
• License

Installation

To run out of the box you'll need to do the following once:

Prerequisites:

1. You'll need to have docker installed on your machine
2. Build the docker image that is used to run servicex, awkward, and friends: docker build -t atlasplotagent:latest Docker
3. If you are running a servicex workflow, get an access token. Make sure the servicex.yaml file is either in your home directory or your current working directory.
4. You'll need token(s) to access the LLM. Here is what the .env looks like. Please create this either in your local directory or your home directory. Make sure only you can read it: this is access to a paid service!

api_openai_com_API_KEY=<openai-key>
api_together_xyz_API_KEY=<together.ai key>
openrouter_ai_API_KEY=<openrouter-key>

Running in a local python environment

pip install hep-data-llm
hep-data-llm plot "Plot the ETmiss of all events in the rucio dataset mc23_13p6TeV:mc23_13p6TeV.801167.Py8EG_A14NNPDF23LO_jj_JZ2.deriv.DAOD_PHYSLITE.e8514_e8528_a911_s4114_r15224_r15225_p6697." output.md

The output will be in output.md - view in a markdown rendering problem (I use vscode). A img directory will be created and it will contain the plot (hopefully).

Use hep-data-llm plot --help to see all the options you can give it. It defaults to using gpt-5, the most successful model in tests.

Running with uvx

This is great if you want to just run once or twice.

uvx hep-data-llm plot "Plot the ETmiss of all events in the rucio dataset mc23_13p6TeV:mc23_13p6TeV.801167.Py8EG_A14NNPDF23LO_jj_JZ2.deriv.DAOD_PHYSLITE.e8514_e8528_a911_s4114_r15224_r15225_p6697." output.md

This uses the uvx tool to install a temporary environment. If you want to keep this around to use, you can use uv tool install hep-data-llm. Do remember to update it every now and then!

License

hep-data-llm is distributed under the terms of the MIT license.