Project CLAI: Instrumenting the Command Line as a New Environment for AI Agents

January 31, 2020 · Entered Twilight · 🏛 arXiv.org

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Repo contents: .gitattributes, .github, .gitignore, .pylintrc, .travis.yml, AUTHORS.md, BuildDockerImage.sh, CODE_OF_CONDUCT.md, CONTRIBUTING.md, Dockerfile.CLAI, Dockerfile.CLAIServer, Dockerfile.Dev, Jenkinsfile, LICENSE.txt, Makefile, Makefile.gnu, Makefile.uss, README.md, RunDockerImage.sh, StopDockerImage.sh, anonymize.json, bin, clai, configPlugins.json, develop.py, develop.sh, docker-compose.yaml, docs, emulator.sh, install.py, install.sh, known-issues.md, my_agent, requirements.txt, requirements_dev.txt, requirements_emulator.txt, requirements_test.txt, requirements_utilities.txt, runLocalTests.sh, scripts, test, test_integration, uninstall.py, uninstall.sh, usersInstalled.json, utils

Authors Mayank Agarwal, Jorge J. Barroso, Tathagata Chakraborti, Eli M. Dow, Kshitij Fadnis, Borja Godoy, Madhavan Pallan, Kartik Talamadupula arXiv ID 2002.00762 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI Citations 9 Venue arXiv.org Repository https://github.com/IBM/clai ⭐ 493 Last Checked 29 days ago

Abstract

This whitepaper reports on Project CLAI (Command Line AI), which aims to bring the power of AI to the command line interface (CLI). The CLAI platform sets up the CLI as a new environment for AI researchers to conquer by surfacing the command line as a generic environment that researchers can interface to using a simple sense-act API, much like the traditional AI agent architecture. In this paper, we discuss the design and implementation of the platform in detail, through illustrative use cases of new end user interaction patterns enabled by this design, and through quantitative evaluation of the system footprint of a CLAI-enabled terminal. We also report on some early user feedback on CLAI's features from an internal survey.