From b19405b29642cba223ec36d580b720b9225c590f Mon Sep 17 00:00:00 2001 From: Vadym Barda Date: Sun, 4 May 2025 17:03:05 -0400 Subject: [PATCH] docs: hide old RAG tutorials (#4525) --- docs/docs/tutorials/index.md | 6 ------ 1 file changed, 6 deletions(-) diff --git a/docs/docs/tutorials/index.md b/docs/docs/tutorials/index.md index 483956621..a63315acc 100644 --- a/docs/docs/tutorials/index.md +++ b/docs/docs/tutorials/index.md @@ -30,12 +30,6 @@ Explore practical implementations tailored for specific scenarios: ### RAG - [Agentic RAG](rag/langgraph_agentic_rag.ipynb): Use an agent to figure out how to retrieve the most relevant information before using the retrieved information to answer the user's question. -- [Adaptive RAG](rag/langgraph_adaptive_rag.ipynb): Adaptive RAG is a strategy for RAG that unites (1) query analysis with (2) active / self-corrective RAG. Implementation of: https://arxiv.org/abs/2403.14403 - - For a version that uses a local LLM: [Adaptive RAG using local LLMs](rag/langgraph_adaptive_rag_local.ipynb) -- [Corrective RAG](rag/langgraph_crag.ipynb): Uses an LLM to grade the quality of the retrieved information from the given source, and if the quality is low, it will try to retrieve the information from another source. Implementation of: https://arxiv.org/pdf/2401.15884.pdf - - For a version that uses a local LLM: [Corrective RAG using local LLMs](rag/langgraph_crag_local.ipynb) -- [Self-RAG](rag/langgraph_self_rag.ipynb): Self-RAG is a strategy for RAG that incorporates self-reflection / self-grading on retrieved documents and generations. Implementation of https://arxiv.org/abs/2310.11511. - - For a version that uses a local LLM: [Self-RAG using local LLMs](rag/langgraph_self_rag_local.ipynb) - [SQL Agent](sql-agent.ipynb): Build a SQL agent that can answer questions about a SQL database.