Ross ROSS = Recommend OSS · open-source software intelligence for agents

iDC-NEU/YiGraph

YiGraph is an LLM-driven agent for autonomous Graph Data Analytics based on Analytics-Augmented Generation. 易图(YiGraph)是一套基于 AAG(分析增强生成)框架构建的图分析智能体系统,致力于挖掘数据之间的关联关系,释放数据价值。 observed · 2026-08-28

github.com/iDC-NEU/YiGraph · Python observed · 2026-08-28

Health v2 · maintenance only

61/100

  • Activity 94
  • Release rhythm 35
  • Longevity 30

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 425
  • days_rel: n/a
  • days_push: 40
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1227 stars · 96 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

YiGraph is an LLM-driven agent system for autonomous graph data analytics built on the Analytics-Augmented Generation (AAG) framework. It extracts entities and relationships from raw data sources like logs, documents, and tables to build graph data, then answers natural-language business questions by planning and executing verifiable graph computations and generating interpretable analysis reports.

Use cases

  • analyze relationships in complex data with natural language questions
  • extract entities and relations from documents and logs into a knowledge graph
  • financial anti-money-laundering graph analysis
  • generate interpretable analysis reports from graph data
  • run graph algorithms via an LLM agent without writing queries
  • turn business questions into executable graph analysis workflows

When to choose

  • you need natural-language-driven analysis over relational/graph data
  • you want LLM answers grounded in verifiable graph computations rather than free-form chat
  • you need automated entity and relationship extraction from heterogeneous raw data
  • you need traceable, reviewable analysis reports for domains like finance or fraud detection

When to avoid

  • you need a simple chatbot without graph analytics
  • your data has no meaningful relational structure
  • you require a permissively licensed dependency - the repository lists no license
  • you need a lightweight tool without LLM infrastructure

Facets

application · maturity active

agent-framework rag nlp machine-learning data-science analytics chatbot artificial-intelligence large-language-models data-science analytics graph-processing python cross-platform graph-analytics analytics-augmented-generation llm-agent knowledge-graph graph-database natural-language-analysis anti-money-laundering report-generation ai-agents natural-language-processing

1 source

Member repositories

RepositoryRoleHealth v2
iDC-NEU/YiGraphmain61

For agents

markdown · JSON · MCP: product_card(name="iDC-NEU/YiGraph")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem