zz测试18种RAG技术找到最优方案

https://zhuanlan.zhihu.com/p/31747625448

测试18种RAG技术找到最优方案

 

https://github.com/FareedKhan-dev/all-rag-techniques

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fareedkhan-dev-all-rag-techniques/
├── README.md                          <- You are here!
├── 1_simple_rag.ipynb
├── 2_semantic_chunking.ipynb
├── 3_chunk_size_selector.ipynb
├── 4_context_enriched_rag.ipynb
├── 5_contextual_chunk_headers_rag.ipynb
├── 6_doc_augmentation_rag.ipynb
├── 7_query_transform.ipynb
├── 8_reranker.ipynb
├── 9_rse.ipynb
├── 10_contextual_compression.ipynb
├── 11_feedback_loop_rag.ipynb
├── 12_adaptive_rag.ipynb
├── 13_self_rag.ipynb
├── 14_proposition_chunking.ipynb
├── 15_multimodel_rag.ipynb
├── 16_fusion_rag.ipynb
├── 17_graph_rag.ipynb
├── 18_hierarchy_rag.ipynb
├── 19_HyDE_rag.ipynb
├── 20_crag.ipynb
├── 21_rag_with_rl.ipynb
├── requirements.txt                   <- Python dependencies
└── data/
    └── val.json                       <- Sample validation data (queries and answers)
    └── AI_information.pdf             <- A sample PDF document for testing.
    └── attention_is_all_you_need.pdf  <- A sample PDF document for testing (for Multi-Modal RAG).