aa523656718-cloud/auto-ontology

选用指南

AI 根据 README 整理 · 2026/11/5 20:16:54

使用方式

项目提供基于 Docker Compose 的 Web UI 和聊天界面，同时支持通过 Helm chart 部署到 Kubernetes，并可通过 MCP、CLI 和 API 进行访问。

查看 README 依据

- **Authentication & RBAC** —using [Better Auth](https://github.com/better-auth/better-auth). - **Web UI** for chat, analysis, data catalog, analytics, and settings. - **Flexible deployment** — Helm chart for Kubernetes or Docker Compose for a local stack. ## Software Components | Component | Technology | Role | Default port | | ------------------- | ---------------------------------------------------------------------- | ------------------------------------------ | ------------ |

systems, and exposes it to any agent harness through MCP, CLI, and API. It complements the semantic models customers already own. It enables developers to: - Discover: generate enterprise ontologies from metadata; connect existing ontologies and semantic models; build AI-ready knowledge graphs. - Ground: give agents trusted business meaning for metrics, entities, and relationships; reconcile inconsistent definitions across systems. - Validate: check generated queries against certified definitions and lineage; return provenance with every answer.

部署要求

需要 Docker 与 Compose v2 以及 NVIDIA API 密钥（`nvapi-...`），默认使用 NVIDIA NIM 端点进行推理。

查看 README 依据

left unset falls back to the matching `DEFAULT_MODELS_<FIELD>`. So the simplest setup is to fill in `DEFAULT_MODELS_*` and override per-triplet fields only where they differ (e.g. `EMBED_MODEL`, `NON_REASONING_MODEL`). `*_API_KEY` also falls back to the legacy `NVIDIA_API_KEY` for backward compatibility. ## Quickstart This runs Auto-Ontology with Docker Compose against Wide World Importers, Microsoft's sample sales database. You need Docker with Compose v2, [uv](https://docs.astral.sh/uv/), and an NVIDIA API key (`nvapi-...`) from [build.nvidia.com](https://build.nvidia.com).

- **Embeddings:** `nvidia/nemotron-3-embed-1b` - **Reranking:** `nvidia/llama-nemotron-rerank-vl-1b-v2` The endpoints and models are configured via the `DEFAULT_MODELS_ENDPOINT`, `DEFAULT_MODELS_MODEL`, `EMBED_ENDPOINT`, and `EMBED_MODEL` environment variables and require a `DEFAULT_MODELS_API_KEY`. #### Model triplets Each model role is configured by a **triplet** of environment variables — `<PREFIX>_ENDPOINT` (URL), `<PREFIX>_API_KEY`, and `<PREFIX>_MODEL`: | Prefix | Role |

已知限制

该问题无法通过现有数据解答时，Agent 会报告无法回答；本仓库目前不接受外部贡献。

查看 README 依据

advertising data, so a question about ad spend has nothing to resolve against. An agent connected through [MCP](#mcp-server) checks answerability first and asks you to clarify: ```text You: What was return on ad spend for the sushi roll flash drive in June 2015? Agent: check_answerable -> coverage 0.5; no term covers "ad spend" Agent: I can find revenue for that product, but this data has no advertising spend, so I can't compute return on ad spend. Do you want June 2015 revenue instead, or is ad spend tracked in another

[open an integration request](https://github.com/NVIDIA/auto-ontology/issues/new?template=integration.yml). The Auto-Ontology team maintains the code and doesn't accept external pull requests. Integration requests and bug reports are welcome as issues. Report security vulnerabilities through [SECURITY.md](./SECURITY.md). Maintainer workflow is in [CONTRIBUTING.md](./CONTRIBUTING.md). ## Reference | Topic | Doc |