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xlang-ai/OpenAgents

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arxiv.org/abs/2310.10634
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OpenAgents

OpenAgents is an open-source platform for deploying, managing, and interacting with language agents through a conversational interface. Agents on this platform can analyze data by generating and executing Python and SQL code, invoke external plugins, browse the web autonomously, and perform tasks like flight search, map directions, and social media posting—all driven by natural language.

What distinguishes the platform is its architecture for persistent agent lifecycle management, isolated code execution via a sandbox, multi-agent coordination for complex workflows, and automatic plugin discovery that selects the right tool for a user's request. A companion browser extension enables agents to navigate sites, fill forms, and read content autonomously. The platform also supports custom component integration, allowing developers to add new agents, language models, or tools by following structured steps.

Additional capabilities include conversational image processing, movie review summarization, dataset search, and interactive chart generation from data analysis results. Agents can be hosted and made available for others to use, with manual or automatic plugin selection for third-party services like shopping, weather, and messaging. The platform is implemented in Python.

Features

  • Conversational AI Agents - This conversational AI platform allows users to chat with language agents through a conversational interface to analyze data, invoke plugins, and browse the web.
  • Interactive Agent Chat Interfaces - Chatting with language agents to analyze data, run tools, and browse the web through a natural language interface.
  • Agent Frameworks and Platforms - Provides an open platform for deploying, managing, and interacting with language agents that can execute tools and browse the web.
  • Customizable Agent Ecosystems - Ships a platform that allows developers to add custom agents, language models, and tools through structured integration steps.

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4,710 stars·519 forks·Python·apache-2.0·30 views
  • Plugin-Based - Extends language agents with third-party plugins for automating shopping, messaging, database queries, and other external services.
  • Autonomous Web Browsing Agents - Navigates websites, reads content, and extracts information based on a user's goal, summarizing results conversationally.
  • Multi-Agent Orchestration - Coordinates multiple specialist agents to decompose and execute complex tasks like retrieving data then generating charts.
  • Web Browsing Automation - Navigates websites automatically using a browser extension to perform tasks like route planning, tweeting, and form filling.
  • Data Analysis Agents - Analyzing, visualizing, and querying data by asking natural language questions and letting agents write code or SQL.
  • Chat-Triggered Plugin Automations - Triggering external services and automating tasks like messaging, shopping, or database queries via plugin invocations from chat.
  • Conversational Data Analysis Tools - Provides a conversational interface that generates and executes Python and SQL code to analyze, visualize, and query data.
  • Natural Language Script Generators - This conversational AI platform runs Python scripts generated from natural language to clean and transform data.
  • SQL Query Executions - This conversational AI platform runs SQL queries against uploaded tables or datasets to retrieve or filter data.
  • Third-Party Service Integrations - Integrates external services and executes third-party tools through natural language commands for shopping, weather, scientific queries, and messaging.
  • Language Agent Hosting - Deploying and managing custom language agents on the platform to make them available for interactive use.
  • Agent Lifecycle Management - Deploys and maintains persistent language agent instances with state management and scaling.
  • Code Sandboxing Environments - Runs user-generated Python and SQL scripts inside isolated containers to analyze and transform data.
  • Plugin Capability Matchers - Selects the most appropriate plugin for a user request by matching intent descriptors against a plugin capability index.
  • Intent-Driven Plugin Executors - Executes external services by routing natural language commands through a plugin registry that maps intents to API calls.
  • Autonomous Browser Controllers - Controls a web browser via a companion extension, enabling autonomous page navigation and form filling.
  • Agent Model Tool Extensions - This conversational AI platform allows adding new agents, language models, or tools by following structured integration steps.
  • JSON Chart Generators - This conversational AI platform creates interactive charts by generating JSON objects from data analysis results.
  • Agent Deployment Platforms - This conversational AI platform deploys and manages language agents, making them available for others to use.
  • Manual Plugin Selection - Allows users to manually select one or more plugins to perform tasks like shopping, weather checks, data visualization, or workflow automation.
  • Automatic Plugin Invocation - Automatically selects the most appropriate plugin based on a user's natural language request without prior knowledge.
  • Agent Frameworks - Provides an open platform for interactive language-based agents.
  • Autonomous Agent Frameworks - Offers a full-stack platform for building and deploying language agents.
  • Chat Interfaces - Open-source implementation of advanced chatbot features like data analysis and web browsing.
  • Task Automation Agents - Open platform for deploying language agents in real-world scenarios.
  • Tool Use And Integration - Platform for deploying and testing language agents in the wild.
  • Web Applications - Open-source suite of AI tools including code interpretation and browsing.
  • Star history

    Star history chart for xlang-ai/openagentsStar history chart for xlang-ai/openagents

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Frequently asked questions

    What does xlang-ai/openagents do?

    OpenAgents is an open-source platform for deploying, managing, and interacting with language agents through a conversational interface. Agents on this platform can analyze data by generating and executing Python and SQL code, invoke external plugins, browse the web autonomously, and perform tasks like flight search, map directions, and social media posting—all driven by natural language.

    What are the main features of xlang-ai/openagents?

    The main features of xlang-ai/openagents are: Conversational AI Agents, Interactive Agent Chat Interfaces, Agent Frameworks and Platforms, Customizable Agent Ecosystems, Plugin-Based, Autonomous Web Browsing Agents, Multi-Agent Orchestration, Web Browsing Automation.

    Which projects share features with xlang-ai/openagents?

    Projects with overlapping indexed features include: camel-ai/camel — This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified… mervinpraison/praisonai — PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and… botpress/botpress — Botpress is a conversational AI builder and LLM agent platform used to design chatbot workflows and orchestrate agents… letta-ai/letta — Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across… modelscope/ms-agent — ms-agent is an LLM agent framework and multi-agent orchestration system designed to build autonomous entities that… strands-agents/sdk-python — This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified…

    Projects sharing features with OpenAgents

    These projects share indexed features with OpenAgents. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
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      camel-ai/camel

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      This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

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      MervinPraison/PraisonAI

      5,592View on GitHub↗

      PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo

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    • botpress/botpressbotpress avatar

      botpress/botpress

      14,748View on GitHub↗

      Botpress is a conversational AI builder and LLM agent platform used to design chatbot workflows and orchestrate agents powered by large language models. It provides a framework for managing the entire lifecycle of these agents, from initial creation through to deployment across various production environments. The platform includes a custom integration SDK for developing and publishing third-party connectors that extend agent capabilities. These tools allow for the creation of custom plugins that connect AI agents to external APIs and third-party services. The system supports both visual des

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    • letta-ai/lettaletta-ai avatar

      letta-ai/letta

      21,168View on GitHub↗

      Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

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      View on GitHub↗21,168
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