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README.md
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title: Rag Transparency Lab
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emoji: 💻
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sdk: gradio
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sdk_version: 6.11.0
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short_description: 'See inside every step of a RAG pipeline '
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---
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title: Rag Transparency Lab
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emoji: 💻
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colorFrom: blue
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sdk: gradio
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sdk_version: 6.11.0
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short_description: 'See inside every step of a RAG pipeline '
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# 🔬 RAG Transparency Lab
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**See inside every step of a RAG pipeline — applied to scientific papers.**
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Upload any scientific PDF, ask a question, and watch the entire pipeline unfold — chunking strategies, hybrid retrieval scores, reranking decisions, filtering logic, and the exact prompt sent to the LLM.
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Built by **Zalina Dezhina, PhD** — AI Evaluation Scientist
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*RAG Education Series · Project 1 of 3*
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---
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## What this tool shows
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| Stage | What you see |
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| 📄 Chunking | All chunks with word count, sentence count, strategy comparison |
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| 🔍 Retrieval | Dense score, BM25 score, hybrid score per chunk |
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| ⚖️ Reranking | Before/after rank, filter decisions with reasons |
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| 💬 Generation | Answer with citations + full prompt transparency |
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## Stack
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`sentence-transformers` · `rank-bm25` · `pypdf` · `Anthropic API` · `Gradio`
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## RAG Education Series
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1. 🔬 **RAG Transparency Lab** ← this Space
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2. ⚡ Classic vs Advanced RAG — side-by-side
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3. 🧪 Scientific Claim Verifier
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---
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[LinkedIn](https://linkedin.com/in/zalina-dezhina) · [GitHub](https://github.com/Mioulin)
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