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@@ -30,5 +30,3 @@ Build and deploy an Agent with RAG tool and Memory | [retriever_agent_with_histo
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1. Use [`create_embeddings.py`](create_embeddings.py) to add data to your vector store.
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Learn more at [Deploying a RAG Application with Cloud SQL for Postgres to LangChain on Vertex AI](https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/reasoning-engine/tutorial_cloud_sql_pg_rag_agent.ipynb).
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