https://github.com/rustsbi/agent
RustSBI Specialized Domain Knowledge Quiz LLM
https://github.com/rustsbi/agent
Last synced: about 1 year ago
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RustSBI Specialized Domain Knowledge Quiz LLM
- Host: GitHub
- URL: https://github.com/rustsbi/agent
- Owner: rustsbi
- License: mit
- Created: 2024-09-20T06:29:59.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-30T05:09:56.000Z (about 1 year ago)
- Last Synced: 2025-03-30T06:19:04.100Z (about 1 year ago)
- Language: Python
- Size: 19.2 MB
- Stars: 101
- Watchers: 6
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Agent
RustSBI Specialized Domain Knowledge Quiz LLM
## Demos
[GPTs Demo 入口](https://chatgpt.com/g/g-ubp707Cke-rustsbi-development-expert-test)
[QAnything Demo 入口](https://ai.youdao.com/saas/qanything/#/bots/129B009D611B4051/share)
## Domain Knowledge Sources
> Sources of Knowledge in the Knowledge Base. Our agent's domain knowledge will be extracted from the documents listed below.
Rust Documentation: https://doc.rust-lang.org/stable/std/
RISC-V Documentation: https://github.com/riscv/riscv-isa-manual
Bouffalo Docs: https://github.com/bouffalolab/bl_docs
Bouffalo SDK: https://github.com/bouffalolab/bouffalo_sdk
Xiangshan Docs: https://github.com/openxiangshan/xiangshan
## LLM Prompt Engineering
> Introduction to Prompt Engineering, including documentation and high-quality articles.
Prompt Engineering Guide: https://www.promptingguide.ai/zh
Prompt Engineering Tools: https://learnprompting.org/docs/tooling/tools
## RAG Engineering
> Introduction to RAG Engineering, including documentation and high-quality articles.
RAG Beginner's Guide (Chinese): https://53ai.com/news/RAG/2024081636147.html
RAG Beginner's Guide (English): https://www.singlestore.com/blog/a-guide-to-retrieval-augmented-generation-rag/
> Existing projects about RAG.
Easy-RAG: [A RAG system implementation](https://github.com/yuntianhe2014/Easy-RAG)
RAGFlow: [Another RAG implementation](https://github.com/infiniflow/ragflow)
WikiChat: [A LLM system with knowledge from Wikipedia](https://github.com/stanford-oval/WikiChat)