Hello World! This is CodeFuse!
CodeFuse aims to develop Code Large Language Models (Code LLMs) to support and enhance full-lifecycle AI native software development, covering crucial stages such as design requirements, coding, testing, building, deployment, operations, and insight analysis.
[TMLR] A curated list of language modeling researches for code (and other software engineering activities), plus related datasets.
An intelligent assistant serving the entire software development lifecycle, powered by a Multi-Agent Framework, working with DevOps Toolkits, Code&Doc Repo RAG, etc.
A LLM semantic caching system aiming to enhance user experience by reducing response time via cached query-result pairs.
An Innovative Agent Framework Driven by KG Engine
Industrial-first evaluation benchmark for LLMs in the DevOps/AIOps domain.
[TMLR] A curated list of language modeling researches for code (and other software engineering activities), plus related datasets.
CodeFuse-CommitEval is the first benchmark tailored to commit Message-Code Inconsistency (MCI) detection with large language models (LLMs).
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