Awesome AI AgentsContinual Learning Agents

YunjueTech/Yunjue-Agent

⭐ 534 Python repository created 2026-01-26

Yunjue Agent is the official implementation of a self-evolving agent system from Yunjue Technology, designed for open-ended tasks that a fixed toolset cannot cover. Its premise is that an agent should not depend on tools handed to it in advance: starting from a zero-start setting with no task-specific tooling, the system decomposes a task, writes the tools it needs in situ, executes them and keeps the useful ones, so its capability grows during the run rather than only during training. The implementation is Python, requires version 3.12 and uv, and installs the Codex CLI as the execution backend, which the operator configures separately with their own API key. Configuration is split between an environment file for keys and execution limits such as worker recursion depth and maximum task execution count, and a YAML file that selects the vision and summarisation models. Reproducibility is a stated goal of the release. A dedicated reproduce branch carries the evaluation scripts and workflow, full system logs under zero-start settings are published for five benchmarks including Humanity's Last Exam, DeepSearchQA, FinSearchComp, xbench-ScienceQA and xbench-DeepSearch, and the complete traces are also distributed as a Hugging Face dataset for analysis. A technical report on arXiv covers the theory, system cost and a metric the authors call Evolutionary Generality Loss, which measures how specialising toward one task degrades general capability. Two demos ship with the code: a web demo showing tool decomposition, where the agent writes tools to search and scrape PDFs or look up stock information, and a command line skill demo. The audience is researchers working on self-improving agents, tool synthesis and deep search evaluation.

https://github.com/YunjueTech/Yunjue-Agent

agentllm-agentself-evolving-agentstool-synthesisdeep-researchbenchmarkspython

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