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tigergraph/graphrag
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让 AI 帮你使用轩辕镜像？ · 展开查看说明
如果你使用 DeepSeek、元宝 AI、Copilot、ChatGPT 等 AI 工具，协助配置轩辕镜像、编写 docker pull 命令、修改 Docker Compose 镜像地址、配置镜像加速、排查镜像拉取失败、分析报错日志等问题，请先让 AI 阅读并遵守轩辕镜像的规则文档。
只需在 AI 对话中先发送下面这句话即可：
请先完整阅读并严格遵守以下文档中的全部规则与要求：
https://xuanyuan.cloud/agents.md
在未充分阅读并理解该文档前，不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。查看 agents.md 用法指南与完整示范。国内用户首推 元宝 AI、DeepSeek 的深度思考模式，不推荐豆包 AI；Cursor 等编辑器可在对话 @ 该链接，或加入 User Rules。 若 AI 无法访问外链，可 打开说明文档 复制全文粘贴。文档会随站点更新，复制内容可能过期，建议定期检查。
The TigerGraph GraphRAG Docker image offers a streamlined, containerized deployment of an advanced AI assistant designed to bridge the gap between your enterprise data and Large Language Models (LLMs).
A major advantage of this architecture is its consolidated backend: the core TigerGraph database functions simultaneously as both the graph database and the vector database. By natively handling both structural data connections and semantic vector embeddings, TigerGraph serves as the single, unified resource for all of GraphRAG's operations. This eliminates the operational overhead of synchronizing disparate vector stores and graph databases.
Drawing from the project's high-level architecture, the Docker image spins up an AI assistant with two primary components running securely on top of this unified database:
- Natural Language Assistant: Converts user questions into actionable data queries, executing hybrid retrievals (combining vector search with multi-hop graph traversals) to ground LLMs in factual, context-rich data.
- Knowledge Graph Builder: A document ingestion engine that automatically extracts entities, builds ontologies, and structures raw data into an intelligent knowledge graph.
Ready to deploy? You can deploy the Docker-based instance in just a few steps. Head over to the official repository to get started: 👉 https://github.com/tigergraph/graphrag
For a comprehensive overview, prerequisites, and high-level architectural information, please reference the official https://github.com/tigergraph/graphrag/blob/main/README.md.
镜像拉取方式
您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问 标签列表页面。
轩辕镜像加速拉取命令点我查看更多 graphrag 镜像标签
docker pull docker.xuanyuan.run/tigergraph/graphrag:<标签>
DockerHub 原生拉取命令
docker pull tigergraph/graphrag:<标签>
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