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docs(docs): update RAG tutorials link across multiple vector store docs (AstraDB, DatabricksVectorSearch, FAISS, Redis, etc.) (#32301)
## **Description:** This PR updates the internal documentation link for the RAG tutorials to reflect the updated path. Previously, the link pointed to the root `/docs/tutorials/`, which was generic. It now correctly routes to the RAG-specific tutorial page for the following vector store docs. 1. AstraDBVectorStore 2. Clickhouse 3. CouchbaseSearchVectorStore 4. DatabricksVectorSearch 5. ElasticsearchStore 6. FAISS 7. Milvus 8. MongoDBAtlasVectorSearch 9. openGauss 10. PGVector 11. PGVectorStore 12. PineconeVectorStore 13. QdrantVectorStore 14. Redis 15. SQLServer ## **Issue:** N/A ## **Dependencies:** None ## **Twitter handle:** N/A
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docs/docs/integrations/vectorstores/astradb.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/clickhouse.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/couchbase.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/databricks_vector_search.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/elasticsearch.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/faiss.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/milvus.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/mongodb_atlas.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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docs/docs/integrations/vectorstores/opengauss.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval/)"
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docs/docs/integrations/vectorstores/pgvector.ipynb

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"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
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"- [Tutorials](/docs/tutorials/)\n",
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"- [Tutorials](/docs/tutorials/rag)\n",
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"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
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"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
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