Awesome AI AgentsMulti-Agent Frameworks

ltjed/freephdlabor

⭐ 720 Python repository created 2025-10-20

freephdlabor is an open-source multiagent system for automating scientific research from hypothesis generation through experiments to a finished manuscript. A user launches it with a single task description, either a loose research direction or a detailed plan with objectives and target metrics, and a ManagerAgent orchestrates specialised workers such as an IdeationAgent that proposes research ideas, an ExperimentationAgent that runs computations and collects results, and a WriteupAgent that assembles the paper with figures and citations. The authors emphasise four design choices that separate it from earlier automated-science pipelines. Workflows are dynamic, so the system reorders and revises its plan in response to what experiments actually show instead of following a fixed sequence of stages. Agents are meant to be edited, added or removed by the user, with explicit customisation support so the same skeleton can be pointed at materials science, biology, economics or another field simply by supplying domain tools. Human feedback can be injected at any moment rather than only at predetermined checkpoints. Context management is built in so a run can sustain exploration over long horizons instead of being a single one-shot attempt. Installation uses a conda environment on Python 3.11 or later, with API keys for the chosen model providers set in a dotenv file and per-component model selection configurable in a YAML file; a CUDA-capable GPU is recommended for runs that involve real training. The repository includes an example generated paper, a demo video, a blog post explaining the intuition behind the architecture, and a technical report on arXiv. It is MIT licensed and aimed at researchers who want an always-running lab in their own field and at people studying how agent teams coordinate on open-ended work.

https://github.com/ltjed/freephdlabor

ai-agentsai4scienceautonomous-agentsmultiagent-systemsresearch-automationpythonhuman-in-the-loopmanuscript-generation

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