Open-source agents
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10.11.2024, 17:52
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28.03.2026, 13:50
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- AlphaEvolve: A coding agent for scientific and algorithmic discovery
- LLMs have shown promise in accelerating scientific discovery, but their ability to generate entirely novel, high-impact algorithms has been limited. This is mainly because they rely on static training data and can not refine their solutions. AlphaEvolve fixes this by creating a dynamic feedback loop where code is written, tested, criticized, and improved autonomously.
- Paper: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms
- by_cloud blog: The AI Timeline: AlphaEvolve
- Voyager
- Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager consists of three key components: 1) an automatic curriculum that maximizes exploration, 2) an ever-growing skill library of executable code for storing and retrieving complex behaviors, and 3) a new iterative prompting mechanism that incorporates environment feedback, execution errors, and self-verification for program improvement.
- Implementation:
MineDojo/Voyager
- 6.1k stars
- Paper: Voyager: An Open-Ended Embodied Agent
- 1000 citations
- 2023-10-19
- SWE-agent
- A system that facilitates LM agents to autonomously use computers to solve software engineering tasks. SWE-agent’s custom agent-computer interface (ACI) significantly enhances an agent’s ability to create and edit code files, navigate entire repositories, and execute tests and other programs
- Implementation: https://github.com/princeton-nlp/SWE-agent
- Paper:
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
- 164 citations
- Submitted on 6 May 2024
- Youtube Presentation
- Magentic-One
- A high-performing generalist agentic system designed to solve such tasks. Magentic-One employs a multi-agent architecture where a lead agent, the Orchestrator, directs four other agents to solve tasks. The Orchestrator plans, tracks progress, and re-plans to recover from errors, while directing specialized agents to perform tasks like operating a web browser, navigating local files, or writing and executing Python code.
- Implementation: https://github.com/microsoft/autogen/tree/v0.4.4/python/packages/autogen-magentic-one
- Blog: AI Frontiers blog
- Paper:
Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks
- 15 citations
- Submitted on 7 Nov 2024
- Open Deep Search
- Open-source replication of the OpenAI deep research agent by HuggingFace with the use of of smolagents library
- Implementation: https://github.com/huggingface/smolagents/tree/main/examples/open_deep_research
- Blog: Open-source DeepResearch – Freeing our search agents
- Other agents reproducing OpenAI deep research: