Open Source AI Agents - Page 4
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AI-Trader
100% Fully-Automated Agent-Native Trading
AI-Trader is an open-source AI-powered quantitative trading framework designed to combine financial analysis, machine learning, and autonomous trading workflows into a unified research platform. The project integrates large language models, financial indicators, market analysis pipelines, and automated decision-making systems to support strategy generation and market prediction tasks. It is built to help researchers and developers experiment with AI-assisted trading strategies using historical and real-time financial data. The framework supports modular components for portfolio analysis, signal generation, market reasoning, and trading automation, allowing users to customize workflows for different trading styles and asset classes. AI-Trader also emphasizes extensibility for integrating external APIs, datasets, and custom models. -
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Agent S
Agent S: an open agentic framework that uses computers like a human
Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines powerful foundation models (such as GPT-5) with grounding models like UI-TARS to translate visual inputs into precise executable actions. It supports flexible deployment via CLI, SDK, or cloud, and integrates with multiple model providers including OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. With optional local code execution, reflection mechanisms, and compositional planning, Agent S provides a scalable and research-driven framework for building advanced computer-use agents. -
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E2B
Secure open source cloud runtime for AI apps & AI agents
E2B's Code Interpreter SDK allows you to add code-interpreting capabilities to your AI apps. E2B Sandbox is a secure sandboxed cloud environment made for AI agents and AI apps. Sandboxes allow AI agents and apps to have long-running cloud secure environments. In these environments, large language models can use the same tools as humans do. -
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Eliza
Autonomous agents for everyone
Build and deploy autonomous AI agents with consistent personalities across Discord, Twitter, and Telegram. Full support for voice, text, and media interactions. Built-in RAG memory system, document processing, media analysis, and autonomous trading capabilities. Supports multiple AI models including Llama, GPT-4, and Claude. Create custom actions, add new platform integrations, and extend functionality through a modular plugin system. Full TypeScript support. -
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GenericAgent
Self-evolving autonomous agent framework
The GenericAgent project is a flexible framework for building autonomous AI agents that can operate across diverse tasks and environments. It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation. It integrates with modern language models to provide planning, execution, and iterative reasoning capabilities, making it suitable for complex workflows. The project also focuses on extensibility, allowing developers to plug in custom tools or APIs and tailor agent behavior to specific use cases. By abstracting common agent patterns, it reduces the overhead of building agent systems from scratch. Overall, GenericAgent provides a foundation for scalable and reusable AI agent development. -
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Leon
Leon is your open-source personal assistant
Leon is an open-source personal AI assistant platform that lets users run a conversational agent locally or on their own servers, providing an alternative to cloud-hosted assistants with a focus on privacy, extensibility, and modular components. It’s designed to process natural language queries and perform tasks such as information retrieval, task automation, scheduling, and custom workflows defined by the user. The architecture emphasizes modularity: you can plug in different language models, intent recognizers, or action handlers to tailor Leon for specific domains like productivity, home automation, or developer tooling. Because it runs independently of third-party cloud services, Leon gives users full control over their data and system behavior, which is especially important for privacy-conscious users and organizations. -
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Maestro AI Orchestration
Agent Orchestration Command Center
Maestro is a cross-platform desktop application designed for power users to orchestrate and manage fleets of AI agents and project workflows from a keyboard-centric interface. It provides a high-performance experience for running multiple agent sessions in parallel, integrating with tools such as Claude Code, OpenAI Codex, and other agent tooling to automate tasks, perform unattended execution, and organize long-running work flows. Users can collaborate with AI to draft specifications, break tasks into playbooks, and run them sequentially or concurrently in isolated contexts, each with clean session history. Maestro includes advanced features like Git worktrees to isolate sub-agent tasks, command-line interfaces for integration into CI/CD pipelines, remote control via phone, and comprehensive session analytics. -
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React Doctor
Your agent writes bad React
React Doctor is a developer tool that scans React codebases and identifies problems that commonly appear in AI-generated or poorly maintained frontend code. It gives projects a clear health score from 0 to 100, making technical issues easier to understand, prioritize, and communicate. The scanner checks areas such as state management, effects, performance, architecture, accessibility, security, and dead code. It works across popular React environments, including Next.js, Vite, and React Native. It can also be installed into coding agents so they learn better React practices before generating new code. For teams, it supports GitHub Actions workflows that can comment on pull requests and expose scores for automated quality gates. -
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Suna
Suna - Open Source Generalist AI Agent
Suna is an open-source generalist AI agent developed by Kortix AI. Designed to assist users in accomplishing real-world tasks through natural conversation, Suna combines powerful capabilities with an intuitive interface. It serves as a digital companion for research, data analysis, and everyday challenges, integrating tools like browser automation, file management, web crawling, command-line execution, website deployment, and API integration. Suna's architecture comprises a FastAPI-based backend, a Next.js/React frontend, an agent Docker environment, and a Supabase database for state management. This modular design allows for seamless interaction and task execution through simple conversations. -
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Vibe-Trading
Vibe-Trading: Your Personal Trading Agent
Vibe-Trading is an AI-powered multi-agent financial workspace that converts natural language inputs into executable trading strategies and market analysis. It allows users to describe investment ideas in plain language, which are then translated into code, backtested, and evaluated across global markets. The platform integrates multiple data sources, including equities, crypto, and derivatives, with automatic fallback mechanisms. It features a swarm-based architecture with prebuilt expert agent teams for research, trading, and risk management. Advanced backtesting engines provide statistical validation, optimization, and performance metrics. The system also includes persistent memory, enabling it to learn from past interactions and refine strategies over time. Overall, it delivers an end-to-end AI-driven trading environment for both research and execution. -
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so many more. Add small or large files, or many files at once. We map out a knowledge graph from all the facts and relationships we extract from your data. Then, we establish graph topology and connect related knowledge clusters, enabling the LLM to "understand" the data. -
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pua
Your AI has been placed on a PIP. 30 days to show improvement
pua is a high-agency AI skill or plugin designed for use within agent-based coding environments, particularly those like Claude Code, where modular “skills” extend the behavior and capabilities of AI assistants. The project frames the AI as an underperforming senior engineer under evaluation, introducing a strong motivational and behavioral prompt layer that encourages proactive problem-solving and initiative. Rather than adding new technical capabilities, PUA focuses on shaping how the AI approaches tasks, pushing it toward more assertive, autonomous, and results-driven outputs. It is designed to influence decision-making patterns, encouraging the AI to take ownership of tasks, iterate aggressively, and prioritize delivering meaningful outcomes within constrained timeframes. -
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500+ AI Agent Projects
The 500 AI Agents Projects is a curated collection of AI agent
500 AI Agents Projects is a curated repository that aggregates hundreds of real-world AI agent use cases across multiple industries, serving as a centralized knowledge hub for developers, researchers, and businesses. Rather than being a single application, it functions as a structured index linking to open-source implementations and conceptual examples of agent-based systems. The repository highlights how AI agents can be applied in domains such as healthcare, finance, education, and retail, offering inspiration and practical entry points for building solutions. It simplifies exploration by organizing diverse projects into a single accessible location, making it easier to discover trends and patterns in agentic AI development. The project encourages collaboration and contributions, positioning itself as a living resource that evolves with the ecosystem. Its value lies in breadth, discoverability, and practical orientation toward implementation. -
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AIHawk
AIHawk aims to easy job hunt process by automating job applications
AIHawk is an AGPL‑licensed AI agent focused on automating job applications. It scrapes job listings from corporate sites (or LinkedIn in forks) and uses LLMs to generate tailored applications, streamlining the process across multiple platforms—dubbed “revolutionary” by mainstream tech outlets. -
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AgentGPT
🤖 Assemble, configure & deploy autonomous AI Agents in your browser
🤖 Assemble, configure, and deploy autonomous AI Agents in your browser. 🤖 AgentGPT allows you to configure and deploy Autonomous AI agents. Name your own custom AI and have it embark on any goal imaginable. It will attempt to reach the goal by thinking of tasks to do, executing them, and learning from the results 🚀. By sponsoring this free, open-source project, you not only have the opportunity to have your avatar/logo featured below, but also get the exclusive chance to chat with the founders!🗣️ 👉 Click here to support the project: https://github.com/sponsors/reworkd-admin -
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Agents-Flex
Agents-Flex is an elegant LLM Application Framework like LangChain
Agents-Flex includes a variety of network protocols for connecting LLMs, such as HTTP, SSE and WS. Its simple and flexible design allows developers to easily connect to various LLMs, including OpenAI, LLama, and other AI. Agents-Flex provides a rich set of development templates and Prompt Frameworks, including FEW-SHOT, CRISPE, BROKE, and ICIO. Developers can also customize their own unique prompt templates. Agents-Flex has a very flexible Function Calling component. It supports local method definitions, parsing, callbacks through LLMs, and executing local methods to obtain results. Agents-Flex offers Loader, Parser, and Splitter components for the Document. Each component has multiple implementations, making it easy to load data from the web, local files, databases, and various data types. -
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Android Use
Automate native Android apps with AI using accessibility APIs
android-action-kernel is an open source Python library designed to let AI agents control and automate native Android applications running on real devices or emulators. It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state (as XML) from the device, which is then fed to a large language model (LLM) like OpenAI’s models for decision-making, and actions are executed via the Android Debug Bridge (ADB). This approach bypasses expensive vision-based models and provides faster, cheaper automation with fine-grained interaction capabilities (for example, tapping buttons, typing text, navigating screens). -
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Antigravity Kit
AI Agent templates with Skills, Agents, and Workflows
Antigravity Kit is an AI agent capability expansion toolkit that provides structured templates, skills, and workflows designed to boost the productivity of AI assistants and autonomous agents in coding environments. It comes with an extensive library of predefined agent personas and domain-specific skills that help in performing targeted tasks such as frontend development, backend engineering, quality assurance, and more. With this kit, developers can rapidly initialize a project scaffold and gain access to specialist agents and command workflows that guide the agent through multi-step tasks and slash-command procedures. The repository follows a clear pattern for defining agents and their behaviors, making it easier to extend with new skills or tailor existing ones to your use case. Because it’s framework-agnostic at its core, the Antigravity Kit can integrate with IDEs and other development tooling for smoother AI-augmented coding. -
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BISHENG
BISHENG is an open LLM devops platform for next generation apps
BISHENG is an open LLM application DevOps platform, focusing on enterprise scenarios. It has been used by a large number of industry-leading organizations and Fortune 500 companies. "Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate. -
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ChemCrow
Chemcrow
ChemCrow is an AI-powered framework designed to assist in chemical research and discovery. It integrates AI models with chemical knowledge bases to provide intelligent recommendations for synthesis planning, reaction prediction, and material discovery. This tool helps automate and accelerate research in computational chemistry and drug development. -
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CoPaw
Your Personal AI Assistant; easy to install, deploy on local or coud
CoPaw is a personal AI assistant designed to run on your own machine or in the cloud, giving you full control over memory, models, and data. Built by the AgentScope team, it connects to multiple chat platforms—including DingTalk, Feishu, QQ, Discord, iMessage, and more—through a single unified assistant. CoPaw supports both cloud-based LLM providers and fully local models such as llama.cpp, MLX, and Ollama, allowing you to operate without API keys if preferred. It includes a browser-based Console for chatting, configuring models, managing memory, and extending capabilities with custom skills. With built-in cron scheduling, heartbeat check-ins, and extensible skill loading, CoPaw grows with your workflow over time. Easy installation options—including pip, one-line scripts, Docker, and cloud deployment—make it accessible for both developers and non-technical users. -
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GPT Researcher
LLM based autonomous agent that does online comprehensive research
Say Hello to GPT Researcher, your AI agent for rapid insights and comprehensive research. GPT Researcher is the leading autonomous agent that takes care of everything from accurate source gathering to organization of research results. -
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Inkeep
Create AI Agents in a No-Code Visual Builder or TypeScript SDK
Inkeep is an open-source framework for building and deploying AI agent workflows and interactive assistants that operate autonomously across applications, enterprise environments, and customer engagement use cases. It lets developers and non-technical users create, manage, and orchestrate multi-agent systems using both a no-code visual builder and a full TypeScript SDK, giving two ways to define agent behaviors that stay in sync with each other. Agents built with this framework can act as real-time conversational assistants — for example, handling help desk inquiries, providing internal support to teams, or driving in-app experiences — and they can be extended to automate multi-step tasks that interact with external systems like CRMs, knowledge bases, or ticketing systems. The project includes support for designing rich workflows where agents communicate with each other (agent-to-agent communication) and maintain state. -
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Letta
Letta (formerly MemGPT) is a framework for creating LLM services
Letta is an AI-powered task automation framework designed to handle workflow automation, natural language commands, and AI-driven decision-making. -
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MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs.
