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开篇介绍🌈\n\n检索增强生成（RAG）技术正在革新我们对信息检索和生成式人工智能的结合方式。这个系列教程汇集了一系列精选的高级技术，它们将为您的RAG系统注入新动力，使其能够生成更精准、更贴近需求、更全面的答案。\n\n致力于成为研究人员和实践者探索RAG技术潜力的宝贵资源。通过营造一个协作的环境，希望加速这一激动人心领域的创新步伐。\n\n## RAG课程🌱\n\n| 序号 | 课程名称 | 课程简介 | 链接 |\n| -- | -- | -- | -- |\n| 01 | 基础简单的RAG | 适合新手的基本RAG技术 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/01_base_rag.ipynb) |\n| 02 | 丰富上下文 | 通过检索到单个块扩展到相邻块提高检索效率 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/02_context_enrichment_window.ipynb) |\n| 03 | 融合检索 | 结合了基于向量的相似性检索和关键词的BM25检索方法优化结果 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/03_fusion_retrieval.ipynb) |\n| 04 | 智能重新排序 | 使用大模型对检索块的相关性进行评分重新排序 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/04_reranking_01.ipynb) |\n| 05 | 智能重新排序 | 使用Reranker Model对检索块的相关性进行评分重新排序 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/05_reranking_02.ipynb) |\n| 06 | CSV文件RAG | 基于CSV文件的RAG系统 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/06_csv_rag.ipynb) |\n| 07 | 更加可靠的检索 | 通过检查文档相关性和防止幻觉确保准确性和相关性 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/07_reliable_rag.ipynb) |\n| 08 | 查询语句转换技术  | 查询语句重写 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/08_query_rewriting.ipynb) |\n| 09 | 查询语句转换技术 | Step-back提示 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/09_step_back_prompting.ipynb) |\n| 10 | 查询语句转换技术 | 子查询分解 | [链接](https://github.com/justinzm/RAG_course/blob/main/course/10_sub_query.ipynb) |\n| -- | -- | -- |\n\n## License 许可证\nThis project is licensed under the Apache License 2.0 - see the [LICENSE](https://github.com/justinzm/RAG_course/blob/main/LICENSE) file for details.\n\n⭐️ ️如果你觉得这个仓库有帮助，请考虑给它一个星星！\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjustinzm%2Frag_course","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjustinzm%2Frag_course","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjustinzm%2Frag_course/lists"}