# datawhalechina/all-in-rag

<https://repo.masters-masters.com/en/repos/datawhalechina/all-in-rag>

[Home](https://repo.masters-masters.com/en) › [datawhalechina](https://repo.masters-masters.com/en/owners/datawhalechina) › [all-in-rag](https://repo.masters-masters.com/en/repos/datawhalechina/all-in-rag)

datawhalechina/all-in-rag has 12,857 stars on GitHub. Its RepoMasters card: Stable tier. 🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in…

| Field | Value |
| --- | --- |
| Owner | [datawhalechina](https://repo.masters-masters.com/en/owners/datawhalechina) |
| Stars | 12,857 |
| Forks | 6,524 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2025 |
| Topics | embedding, kimi-k2, langchain, llama-index, llm, milvus, multimodal, rag, ai, neo4j |
| Tier | [Stable (5,000 to 19,999 ★)](https://repo.masters-masters.com/en/ranks/cult) |
| View on GitHub | [datawhalechina/all-in-rag](https://github.com/datawhalechina/all-in-rag) |

## Repository

🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/

The tier for repos with 5,000 to 19,999 ★. Published odds per card pulled: 0.9%. Rarity: Very rare.

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