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--- |
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title: Thoracic Radiology RAG System |
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emoji: 👀 |
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colorFrom: green |
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colorTo: red |
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sdk: gradio |
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sdk_version: 6.1.0 |
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app_file: app.py |
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pinned: false |
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license: mit |
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short_description: 'Ask questions about thoracic radiology and get answers with ' |
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--- |
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## Overview |
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This repository contains a **Hugging Face Spaces-ready** RAG (Retrieval-Augmented Generation) demo for thoracic radiology Q&A. |
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- **Default index (prebuilt)**: `ZhangNy/radiology-index-qwen3-embedding-0.6b` |
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- **Raw public dataset**: `ZhangNy/radiology-dataset` |
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- **No image rendering in UI**: references link to original pages where images can be viewed. |
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The Space uses **external APIs** for Embeddings / Reranker / LLM via **Secrets**. |
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## Run (local) |
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```bash |
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cd LangGraphAgent/rebuild_1219 |
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pip install -r requirements.txt |
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export EMBED_API_KEY="..." |
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export LLM_API_KEY="..." |
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# optional: |
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export RERANK_API_KEY="..." |
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python app.py --config config/default_config.yaml --host 0.0.0.0 --port 7860 |
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``` |
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Open `http://localhost:7860`. |
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## Required Hugging Face Space Secrets |
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### Required |
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- **`EMBED_API_KEY`**: embedding API key (OpenAI-compatible) |
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- **`LLM_API_KEY`**: LLM API key (OpenAI-compatible) |
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### Recommended |
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- **`RERANK_API_KEY`**: reranker API key (OpenAI-compatible `/rerank` endpoint) |
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### Optional (override defaults) |
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- **`EMBED_API_BASE_URL`**, **`EMBED_MODEL_NAME`** |
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- **`RERANK_API_BASE_URL`**, **`RERANK_MODEL_NAME`** |
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- **`LLM_BASE_URL`**, **`LLM_MODEL_NAME`** |
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- **`RAG_INDEX_REPO_ID`** (default: `ZhangNy/radiology-index-qwen3-embedding-0.6b`) |
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- **`RAG_STORAGE_DIR`** (default: `/data/radiology_rag` if `/data` exists, else `./storage`) |
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## Advanced: rebuild your own index (offline) |
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Install dev deps: |
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```bash |
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pip install -r requirements-dev.txt |
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``` |
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The `scripts/` folder (to be used locally) will support: |
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- Downloading `ZhangNy/radiology-dataset` to `./hf_dataset_prepared` |
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- Building a new index with a different embedding model |
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- Publishing that index as a Hugging Face dataset repo |
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### Fast path (no rebuild): publish your existing local index |
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If you already have a built index locally (e.g. `rebuild_1217/storage` contains `chroma_db/` + `doc_store.db`), |
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you can **package it without images** and upload it: |
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```bash |
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python scripts/package_existing_storage.py \ |
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--storage /home/zny/codes/radioagent_prepare/LangGraphAgent/rebuild_1217/storage \ |
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--output-dir ./index_out \ |
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--overwrite |
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python scripts/publish_index_to_hf.py \ |
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--repo ZhangNy/radiology-index-qwen3-embedding-0.6b \ |
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--folder ./index_out \ |
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--token $HF_TOKEN |
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``` |
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## Notes |
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- **Do not commit API keys**. This repo is configured to read them from environment variables / Space Secrets. |
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- **Index compatibility**: query-time embedding model should match the index embedding model for best retrieval quality. |
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