CodeFuse
Ant Group's open-source code LLM family covering the full software development lifecycle (design, requirements, coding, testing, deployment, operations) with both pre-trained models and downstream agent products.
Description
CodeFuse is Ant Group's umbrella project for Code LLMs and coding agents spanning the full SDLC. The codefuse-ai GitHub org hosts pre-trained code models (CodeFuse-13B, -CodeLlama-34B, CodeFuse-MFT-VLM for multimodal), evaluation harnesses (CodeFuseEval), and downstream agent components (Muagent for multi-agent orchestration, ModelCache for cache, ChatBot UI). Distinct from a pure code-assistant by treating the SDLC as a coordinated multi-stage workflow rather than a single completion loop.
Solution
Multi-component stack. The base layer is a coding LLM (CodeFuse-CodeLlama-34B, etc.). Muagent layers a multi-agent orchestration (planner, coder, reviewer, executor roles) on top, with ModelCache to avoid duplicate LLM calls. Each agent runs a tool-augmented ReAct loop scoped to its SDLC stage.
Primary use cases
- open-source code LLMs for fine-tuning and research
- multi-agent SDLC orchestration (Muagent) for full lifecycle automation
- code-eval benchmark (CodeFuseEval) for in-house model evaluation
- self-hosted enterprise coding agent for Ant Group's internal products
Open the full interactive page →
Diagram, neighbourhood map, code examples, related patterns and full provenance.