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Basic Information

OpenAgents is an open platform that provides code and runnable examples to host, run, and extend language-based agents for real-world tasks. The repository implements and documents three ready agents — a Data Agent for code-driven data analysis, a Plugins Agent that integrates with a large collection of third-party tools, and a Web Agent that automates browsing via a Chrome extension. The project supplies a full-stack reference implementation including a Flask backend, a Next.js/React frontend with a chat web UI, adapters and memory modules, and guidance for local and Docker deployment. It targets both general users who want interactive agent demos and developers or researchers who want a modular foundation to build, evaluate, and deploy new language agents and components.

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Features
The repo bundles several concrete agent capabilities and extensible infrastructure. Data Agent supports searching, acquisition, manipulation, code execution and visualization for Python and SQL workflows. Plugins Agent ships with over 200 plugins, combined plugin usage and an auto plugin selection mechanism. Web Agent uses a Chrome extension to automate tasks like map navigation, form filling and social posts. The codebase includes backend REST APIs, streaming response rendering, a memory module, adapter components, a clear folder-per-agent layout, frontend React components and a Webot Chrome extension. Deployment aids include a Docker compose setup, a one-click backend setup script, examples for registering new LLMs, and templates for adding new plugins and tools.
Use Cases
OpenAgents helps non-experts interact with language agents through an optimized chat UI and hosted demos while giving engineers a reproducible codebase to build upon. For end users it provides ready agents for data analysis, tool-driven workflows and autonomous web browsing to automate routine tasks. For developers and researchers it provides modular adapters, a clear extension path for adding new agents, tools and LLM backends, instructions for registering models and plugins, and deployment options via source or Docker. The project also includes documentation, contribution guidelines, example use cases and an accompanying paper to support evaluation and further development.

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