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ElizaOS

Agent Frameworks

Open-source multi-agent simulation framework for building autonomous AI agents with persistent memory and character-driven interactions.

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At a Glance

Pricing

Open Source

Free and open-source under MIT license

Engagement

Available On

Windows
macOS
Linux
SDK

Resources

WebsiteDocsGitHubllms.txt

Topics

Agent FrameworksMulti-agent SystemsConversational Agents

About ElizaOS

ElizaOS is an open-source multi-agent simulation framework designed for creating, deploying, and managing autonomous AI agents. Built with TypeScript, it provides developers with a comprehensive toolkit for building AI agents that can interact across multiple platforms while maintaining consistent personalities and persistent memory.

The framework enables developers to create sophisticated AI agents that can engage in natural conversations, execute complex tasks, and integrate with various services and platforms. ElizaOS supports multiple AI model providers and offers extensive customization options for agent behavior and capabilities.

  • Multi-Agent Architecture allows developers to deploy and manage multiple AI agents simultaneously, each with unique personalities and capabilities, enabling complex multi-agent simulations and interactions.

  • Persistent Memory System provides agents with long-term memory capabilities, allowing them to remember past interactions, learn from conversations, and maintain context across sessions for more coherent and personalized responses.

  • Character-Driven Design enables the creation of agents with distinct personalities, backgrounds, and communication styles through customizable character files that define agent behavior and traits.

  • Platform Connectors support integration with Discord, Twitter, Telegram, and other platforms, allowing agents to operate seamlessly across multiple communication channels from a single codebase.

  • Extensible Plugin System offers a modular architecture where developers can add custom actions, evaluators, and providers to extend agent capabilities and integrate with external services.

  • Model Provider Flexibility supports multiple AI backends including OpenAI, Anthropic, Llama, and other providers, giving developers freedom to choose the best model for their use case.

  • RAG Knowledge Integration enables agents to access and utilize external knowledge bases, documents, and data sources to provide informed and contextually relevant responses.

To get started with ElizaOS, clone the repository from GitHub, install dependencies using npm or pnpm, configure your environment variables with API keys for your chosen model providers, and create character files to define your agent's personality. The framework includes comprehensive documentation and example configurations to help developers quickly build and deploy their first AI agents.

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Pricing

OPEN SOURCE

Open Source

Free and open-source under MIT license

  • Full framework access
  • Multi-agent support
  • All platform connectors
  • Plugin system
  • Community support
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Capabilities

Key Features

  • Multi-agent simulation framework
  • Persistent memory system
  • Character-driven agent design
  • Discord integration
  • Twitter integration
  • Telegram integration
  • Extensible plugin architecture
  • Multiple AI model provider support
  • RAG knowledge integration
  • Custom action creation
  • Evaluator system
  • Provider system
  • TypeScript-based development
  • Cross-platform deployment
  • Long-term memory storage
  • Context management

Integrations

Discord
Twitter
Telegram
OpenAI
Anthropic
Llama
PostgreSQL
SQLite

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Developer

ElizaOS Team

ElizaOS develops an open-source multi-agent simulation framework for building autonomous AI agents. The project provides developers with tools to create AI agents with persistent memory, character-driven personalities, and cross-platform deployment capabilities. The framework supports multiple AI model providers and offers an extensible plugin architecture for custom integrations.

Read more about ElizaOS Team
WebsiteGitHubX / Twitter
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