Heuristic Autonomous Lab
Project description
HAL
Heuristic Autonomous Lab
This tool is supposed to be run in Jupyter notebooks using JupyterLab. Examples are available in the
examplesfolder.
Config
Create a config.json with the following content:
{
"GEMINI_API_KEY": "your gemini API key",
"MEMORY_DATA_PATH": "/path/to/the/memory/data.gz",
"EXEC_IMPORT": "import time, os, sys, json, yaml, scipy\nimport numpy as np\nimport matplotlib.pyplot as plt\n"
}
Or pass config dictionary to init function, check examples/mininum.ipynb
Get Started
import HAL
HAL.init() # initialization: loading memory, setting up display, etc.
# HAL.auto = 3 # auto-execution: HAL will automatically execute up to 3 steps
HAL.reset() # this reset HAL session
HAL("Do something") # main interface: query HAL
HAL() # continue without user input
API
# initialization
HAL.init("Name", _config=None)
# main interface
HAL(query=None)
# properties
HAL.auto = 0
HAL.session = {}
# session operations
HAL.reset()
HAL.save(path="session.json")
HAL.load(path="session.json")
# memory operations
HAL.search(query)
HAL.memorize(content, meta={ "source": HAL.name })
# low-level components
HAL.memory # knowledge base
HAL.display # UI rendering for JupyterLab
# Components
HAL.gather_document
HAL.sort
HAL.plan
HAL.answer
HAL.code
Directory Structure
HAL/HAL_answer.py: Answer componentHAL/HAL_code.py: Develop component (developer)HAL/HAL_gather_document.py: Search agentHAL/HAL_plan.py: Plan component (planner)HAL/HAL_sort.py: Preprocess componentHAL/__init__.py: Entrypoint and main interfaceHAL/memory.py: Knowledge base implementationHAL/display.py: UI rendering for JupyterLabHAL/run.py: Execution runtimeHAL/utils.py: Utility functions
Cite this work
https://arxiv.org/abs/2603.08801
@article{li2026large,
title={Large Language Model-Assisted Superconducting Qubit Experiments},
author={Li, Shiheng and Miller, Jacob M and Lee, Phoebe J and Andersson, Gustav and Conner, Christopher R and Joshi, Yash J and Karimi, Bayan and King, Amber M and Malc, Howard L and Mishra, Harsh and others},
journal={arXiv preprint arXiv:2603.08801},
year={2026}
}
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