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| title: README | |
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| ## RAG-Experiments | |
| Exploring Retrieval-Augmented Generation (RAG) methods with practical, reproducible experiments. | |
| We focus on building lightweight APIs, model comparisons, and exploratory demos around RAG, vector databases, embeddings, and evaluation. | |
| ## What We Do | |
| Minimal RAG APIs (FastAPI + FAISS + embeddings). | |
| Comparative experiments: Markov chains vs. LLMs, chunking strategies, rerankers. | |
| End-to-end Spaces for testing retrieval and generation workflows. | |
| Educational, open, and reproducible — for the community. | |
| ## Projects | |
| Minimal RAG API | |
| Chunking, reranking, and persistence strategies (ongoing) | |
| ## Contributors | |
| This org is developed and maintained by: | |
| Naga Adithya Kaushik — ML Engineer, GenAI enthusiast. | |
| ## Join the Journey | |
| All experiments are open-source and community-friendly. | |
| Check out the Spaces, fork projects, and share feedback! |