AutoLabs

AutoLabs is a Streamlit-based application for designing, simulating, and evaluating laboratory experiments using AI-powered agents and tagging systems. It supports multi-agent and single-agent workflows, experiment step tagging, and evaluation management.

Manuscript: AutoLabs: Cognitive Multi-Agent Systems with Self-Correction for Autonomous Chemical Experimentation

Features

• Interactive experiment design via chat and forms
• Multi-agent and single-agent graph options
• AI-powered query rewriting and step suggestion
• Tagging system for experiment steps (dispensing, processing, etc.)
• Optional tag selection based on experiment context
• Saving and downloading experiment history, steps, and evaluation results
• Generation of LSR (Lab Step Representation) files for experiments
• Downloadable zipped evaluation results

Main Components

• app.py: Main Streamlit app, UI, and workflow logic
• src/: Core logic, agents, tagging utilities, configuration, and experiment graph modules

Getting Started

1. Install dependencies:

   • Python 3.11+
   • Install with pip install -r requirements.txt (create this file if missing)

2. Set up environment variables:

   • Create a .env file with your API keys:

         OPENAI_API_KEY=""
         OPENAI_BASE_URL=""
         OPENAI_API_VERSION=""
         MODEL=""
     

3. Run the app:

   streamlit run app.py
   

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Disclaimer

This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor Battelle, nor any of their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights.

Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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                            for the
               UNITED STATES DEPARTMENT OF ENERGY
                under Contract DE-AC05-76RL01830