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r/Rag is a subreddit with 38k members. Its distinguishing qualities are that the community is large in size, and has high activity.
Welcome to r/Rag, the community for everything Retrieval-Augmented Generation (RAG)! RAG combines retrieval systems with generative models to create more accurate responses, enhancing applications like customer support and research. Join us to discuss RAG techniques, projects, and tools. Whether you're a researcher, developer, or AI enthusiast, you'll find tips, tutorials, and support to innovate with RAG!
Popular Themes in r/Rag
#1
Solution Requests
: "What’s the best RAG tech stack these days? From chunking and embedding to retrieval and reranking"
19 posts
#2
Advice Requests
: "A free goldmine of tutorials for the components you need to create production-level agents"
16 posts
#3
Ideas
: "GraphRAG with Neo4j, Langchain and Gemini is amazing!"
6 posts
#4
Money Talk
: "I made 60K+ building RAG projects in 3 months. Here's exactly how I did it (technical + business breakdown)"
3 posts
#5
Self-Promotion
: "I built a Cursor for PDFs"
3 posts
Popular Topics in r/Rag
#1
Rag
: "I made 60K+ building Rag projects in 3 months. Here's exactly how I did it (technical + business breakdown)"
126 posts
#2
Ai
: "I scraped 1M+ job openings, here’s where Ai Company are actually hiring"
39 posts
#3
Llm
: "Tried Neo4j with Llms for RAG -surprisingly effective combo"
13 posts
#4
Graph
: "GraphRAG Stack: What actually works, and when to use it"
12 posts
#5
: "For anyone struggling with Pdf extraction for textbooks (Math, Chem), you have to try MinerU."
11 posts
#6
Document
: "Document Parsing - What I've Learned So Far"
8 posts
#7
Data
: "Multimodal Data Ingestion in RAG: A Practical Guide"
8 posts
#8
Chatbot
: "RAG Chatbot using Ollama & langflow. All local, quantized models."
7 posts
#9
Vector
: "S3 is a Vector DB now!"
7 posts
#10
Metadata
: "Started getting my hands on this one - felt like a complete Agents book, Any thoughts?"
7 posts
Member Growth in r/Rag
Yearly
+35k members(1023.8%)
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