fast.Order.a.sitter.order.@.2024-05-04-17-27-41.mp4
Example of ECLAIR running on a real-world nursing workflow in Epic after being given only a video recording and natural language description of the task. Note that this is sped up from actual model execution.
🤖 Multimodal foundation models (FMs) such as GPT-4 offer a promising approach for end-to-end workflow automation given their generalized reasoning and planning abilities.
⚙️ To study these capabilities we propose ECLAIR, a system to automate enterprise workflows with minimal human supervision.
📊 Our initial experiments suggest that ECLAIR can overcome the limitations of traditional automation technologies (e.g. RPA) with (1) near-human-level understanding of workflows and (2) instant set-up with minimal technical barrier.
Please note that ECLAIR is an ongoing research project and is not production-ready.
# Create virtual env
conda create -n eclair_env python=3.10 -y
conda activate eclair_env
# Install repo
git clone https://github.com/HazyResearch/eclair-agents.git
cd eclair-agents/
pip install -r requirements.txt
pip install -e .
Generate the experimental results in our paper using the dataset + scripts in this section.
- Link to Data -- Download this file into the
data/
folder and unzip it. - You should now have a folder at
data/vldb_experiments
.
export OPENAI_API_KEY=<your_openai_api_key>
# Demonstrate
bash eclair/vldb_experiments/demonstrate_experiments/run_experiments.sh
# Execute
bash eclair/vldb_experiments/execute_actions/run_experiments.sh
bash eclair/vldb_experiments/execute_grounding/run_experiments.sh # [TODO]
# Validate
bash eclair/vldb_experiments/validate_experiments/run_experiments.sh
This section contains the workflow data and scripts used to automate a real-world nursing workflow in Epic (i.e. the demo video at top of this README).
- Link to ECLAIR Demo -- Visit this folder to view the outputs of ECLAIR executing the nursing workflow in Epic.
- Please note that there are two versions of the demo video -- the raw recording as well as a 10x sped up version (labeled as
[fast]
).
- Link to Data -- Download this folder into the
data/
folder. - You should now have a folder at
data/hospital_data
.
This will run the end-to-end automation pipeline for the nursing workflow.
First, it generates an SOP from a demonstration. Second, it runs ECLAIR on the given workflow. Third, it validates that the workflow was completed successfully.
Note that this assumes you have a sandboxed instance of Epic running on your computer.
cd eclair/agent
python3 pipeline.py
Please consider citing if you found this work or code helpful!
@misc{wornow2024automating,
title={Automating the Enterprise with Foundation Models},
author={Michael Wornow and Avanika Narayan and Krista Opsahl-Ong and Quinn McIntyre and Nigam H. Shah and Christopher Re},
year={2024},
eprint={2405.03710},
archivePrefix={arXiv},
primaryClass={cs.SE}
}