# codefuse-ai/codefuse-chatbot

An intelligent assistant serving the entire software development lifecycle, powered by a Multi-Agent Framework, working with DevOps Toolkits, Code&Doc Repo RAG,  etc.

Repository: https://github.com/codefuse-ai/codefuse-chatbot
Canonical: https://ross.abutalabs.com/products/codefuse-chatbot
Language: Python
License: NOASSERTION
License Family: other
Topics: multi-agent, tool-learning, aiops, code-repo-analysis, code-repo-generation, devops, gpt, knowledge-graph, rag, chatbot, langchain
Last push: 2024-07-01T09:16:47+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 76
- inputs: {"age_days": 1071, "days_push": 793, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1290, forks 148 (observed 2026-08-28T04:04:15.452619+00:00)

## What it is
CodeFuse-ChatBot is an open-source AI assistant for the software development lifecycle, combining a multi-agent scheduling framework with DevOps toolkits, code and documentation repo RAG, knowledge graphs, and sandboxed execution. It supports offline private deployment with open-source LLMs and embeddings, as well as OpenAI API access.

## Use cases
- build a devops ai assistant over private docs
- chat with my code repository
- run a multi-agent llm workflow for development tasks
- self-host a rag chatbot with local llms
- analyze a codebase and generate code with llm
- build a devops knowledge base with knowledge graph retrieval

## When to choose
- you want a privately deployed devops assistant combining code repo RAG, doc RAG, and multi-agent orchestration
- you need offline/on-premise LLM usage with open-source models
- you want an AIOps-oriented assistant with tool learning and sandbox execution

## When to avoid
- you need a lightweight general-purpose chatbot without devops focus
- you want a production-proven product with a permissive license (license is non-standard)
- you need a simple single-agent Q&A setup without multi-agent complexity

## Facets
- artifact type: application
- maturity: active
- function: chatbot, rag, agent-framework, llm-inference, web-scraping, search-engine, nlp
- domain: large-language-models, chatbots, developer-tools
- platform: python, self-hosted
- tags: multi-agent, devops-assistant, code-repo-rag, knowledge-graph, aiops, tool-learning, private-deployment, langchain, ai-agents, retrieval-augmented-generation, devops, natural-language-processing, docker, web-server

## Member repositories
- codefuse-ai/codefuse-chatbot (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:15.452619+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:55:23.208724+00:00, confidence not recorded.
  - readme: https://github.com/codefuse-ai/codefuse-chatbot (fetched 2026-08-28T04:04:15.452619+00:00, sha d4be1ee09055)
- Data as of 2026-08-30T08:39:29.467469+00:00.