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metadata

title: Rag Transparency Lab
emoji: 💻
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.11.0
app_file: app.py
pinned: false
license: mit
short_description: 'See inside every step of a RAG pipeline '

🔬 RAG Transparency Lab

See inside every step of a RAG pipeline — applied to scientific papers.

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.

Built by Zalina Dezhina, PhD — AI Evaluation Scientist
RAG Education Series · Project 1 of 3

What this tool shows

Stage	What you see
📄 Chunking	All chunks with word count, sentence count, strategy comparison
🔍 Retrieval	Dense score, BM25 score, hybrid score per chunk
⚖️ Reranking	Before/after rank, filter decisions with reasons
💬 Generation	Answer with citations + full prompt transparency

Stack

sentence-transformers · rank-bm25 · pypdf · Anthropic API · Gradio

RAG Education Series

🔬 RAG Transparency Lab ← this Space
⚡ Classic vs Advanced RAG — side-by-side
🧪 Scientific Claim Verifier

LinkedIn · GitHub