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rag dev community skip to content navigation menu search powered by algolia search log in create account dev community close rag retrieval augmented generation or rag is an architectural approach that can improve the efficacy of large language model llm applications by leveraging custom data follow hide create post older rag posts 1 2 3 4 5 6 7 8 9 75 264 posts left menu sign in for the ability to sort posts by relevant latest or top right menu a question on discord found two bugs in my rag system fixing them found a third ankit verma ankit verma ankit verma follow sep 13 a question on discord found two bugs in my rag system fixing them found a third rag kafka ai opensource comments add comment 6 min read building a sub second enterprise rag engine with postgresql pgvector and the gemini api rohan khedekar rohan khedekar rohan khedekar follow sep 13 building a sub second enterprise rag engine with postgresql pgvector and the gemini api postgressql ai rag python comments 1 comment 4 min read agentic rag 2026 when the ai decides how it searches saaro saaro saaro follow sep 13 agentic rag 2026 when the ai decides how it searches agenticrag rag ai llm comments add comment 4 min read agentic synthetic data generation abhijeet bhale abhijeet bhale abhijeet bhale follow sep 13 agentic synthetic data generation ai datascience rag futurechallenge comments add comment 1 min read rag systems are eating the world building retrieval augmented generation in python anshul rajpal anshul rajpal anshul rajpal follow sep 12 rag systems are eating the world building retrieval augmented generation in python ai python rag 1 reaction comments add comment 3 min read build a rag legal research assistant that drafts briefs in under 10 minutes sam chen sam chen sam chen follow sep 12 build a rag legal research assistant that drafts briefs in under 10 minutes n8n python rag api comments 1 comment 8 min read rag with opensearch serverless and node js 22 build a real time ai knowledge base explained simply dinesh_gowtham dinesh_gowtham dinesh_gowtham follow sep 11 rag with opensearch serverless and node js 22 build a real time ai knowledge base explained simply opensearch node rag typescript 1 reaction comments add comment 10 min read why your rag chat is missing half the answers and how graphrag fixes it denis macpherson denis macpherson denis macpherson follow for chaos cypher sep 11 why your rag chat is missing half the answers and how graphrag fixes it graphrag rag ai selfhosted comments add comment 8 min read migrating an agentic rag app to aws serverless dmitriy trunov dmitriy trunov dmitriy trunov follow sep 11 migrating an agentic rag app to aws serverless ai aws serverless rag comments add comment 3 min read how to build rag chatbot with pinecone a full stack walkthrough sam chen sam chen sam chen follow sep 12 how to build rag chatbot with pinecone a full stack walkthrough automation python rag api 2 reactions comments add comment 8 min read blog 3 the beginning of ai learning aeron aeron aeron follow sep 11 blog 3 the beginning of ai learning ai rag beginners machinelearning comments add comment 3 min read self hosting anythingllm the three settings that decide whether your workspaces survive a redeploy great sage great sage great sage follow sep 10 self hosting anythingllm the three settings that decide whether your workspaces survive a redeploy selfhosted ai docker rag comments 1 comment 3 min read wabe labs is born and building with blueprints brett ryan brett ryan brett ryan follow sep 10 wabe labs is born and building with blueprints ai rag documentation startup comments 1 comment 5 min read building a rag powered chatbot that lets you talk to your codebase parikshit shah parikshit shah parikshit shah follow sep 9 building a rag powered chatbot that lets you talk to your codebase ai llm rag softwaredevelopment comments add comment 2 min read end to end enterprise rag pipeline with ibm docling pipelines and opensearch alain airom ayrom alain airom ayrom alain airom ayrom follow sep 9 end to end enterprise rag pipeline with ibm docling pipelines and opensearch docling opensearch rag bob 1 reaction comments add comment 7 min read sign in for the ability to sort posts by relevant latest or top trending guides resources personal context vs shared context a deep dive into how humans and organizations should feed th building an ai native second brain with multi rag knowledge graphs and mcp closer look on dynamodb vector search vs s3 vectors vector similarity search with duckdb a practical guide to the vss extension how to build a rag pipeline from pdfs using python rag explained how to give your llm a memory it can actually trust filling gpt 6 astra s 1m token window costs 10 a call building low latency semantic memory for coding agents with lancedb trustgraph 2 8 async infrastructure hybrid retrieval structured output and a plugin based wor vector search fundamentals for rag design ann hnsw distance metrics metadata filtering and bm25 length normalization why long rag chunks never rank why kimi k3 still can t do what einstein did how i built a portfolio risk return tracker with eodhd where does rag actually cost you money i decided to stop guessing when an llm response fails validation feed the error back into the retry i tested 4 rag chunking strategies everyone recommends 2 were quietly broken neo4j vs pgvector vs mongodb vs milvus vs pinecone vs faiss the complete vector database guide your gemini answer has citations is it actually grounded semantic caching in enterprise rag production architectures for faster lower cost llm systems your rag pipeline is probably failing multi hop questions here s why ai builder essentials tokens context windows and rag 101 what a production rag system actually looks like after 18 months n8n rag mcp designing an ai workflow that knows where its knowledge comes from context compression fitting more useful information into your llm s context window local embeddings vs api embeddings why i chose sentence transformers dev community a space to discuss and keep up software development and manage your software career home dev challenges reading list dev videos dev education tracks dev help advertise on dev organization accounts dev showcase about contact dev shop mlh code of conduct privacy policy terms of use built on forem the open source software that powers dev and other inclusive communities made with love and ruby on rails dev community 2016 2026 we re a place where coders share stay up to date and grow their careers log in create account