# Deploying ProBas RAG Assistant to Hugging Face Spaces

The Space ships the **prebuilt index** and loads it directly on startup — no
re-embedding, and the 1.2 GB raw dataset does **not** need to be uploaded. The
app's `load_any_bundle()` fallback loads any bundle present under
`indexes/probas_rag/` even when the raw `probas_processes_by_classification_rag_json/`
directory is absent.

At query time the app still calls the API for the query embedding and the chat
completion, so the Space needs `OPENAI_API_KEY` set as a **secret**.

## What gets uploaded

| File | Purpose | Size |
|------|---------|------|
| `app.py` | the app | small |
| `requirements.txt` | deps | small |
| `README.md` | includes the Space metadata header | small |
| `.gitattributes` | LFS rules for the index | small |
| `check_progress.py` | optional build monitor | small |
| `indexes/probas_rag/bundle_v3_*.json` | record/BM25 bundle | ~489 MB (LFS) |
| `indexes/probas_rag/bundle_embeddings_v3_*.npy` | embeddings | ~227 MB (LFS) |

Do **not** upload `.env`, the raw dataset folder, or `.venv`.

## Steps

Assuming you cloned the Space already:

```bash
git clone https://huggingface.co/spaces/IPTS-PRODDEV/ProBas_RAG_Assistant
cd ProBas_RAG_Assistant
```

1. Copy the app files in. From this project directory:

   ```bash
   SRC="/media/mohamed/New Volume/Leuphana_cousres/SA_Projects/Probas RAG Assistant"
   DST="/media/mohamed/New Volume/Leuphana_cousres/SA_Projects/Probas RAG Assistant/ProBas_RAG_Assistant"   # the HF clone

   cp "$SRC/app.py" "$SRC/requirements.txt" "$SRC/README.md" \
      "$SRC/.gitattributes" "$SRC/check_progress.py" "$DST/"

   mkdir -p "$DST/indexes/probas_rag"
   cp "$SRC/indexes/probas_rag/bundle_v3_"*.json   "$DST/indexes/probas_rag/"
   cp "$SRC/indexes/probas_rag/bundle_embeddings_v3_"*.npy "$DST/indexes/probas_rag/"
   ```

2. Make sure the Space does not ignore the index. Create `$DST/.gitignore` with:

   ```gitignore
   .env
   __pycache__/
   *.pyc
   .venv/
   # NOTE: indexes/ is intentionally NOT ignored — the prebuilt bundle ships with the Space.
   ```

3. Enable LFS and stage the large files (the `.gitattributes` already tracks
   `*.npy` and `indexes/probas_rag/*.json`):

   ```bash
   cd "$DST"
   git lfs install
   git add .gitattributes
   git add app.py requirements.txt README.md check_progress.py .gitignore
   git add indexes/probas_rag/bundle_v3_*.json indexes/probas_rag/bundle_embeddings_v3_*.npy
   git lfs ls-files   # confirm both large files are LFS-tracked
   ```

4. Set the API key as a **Space secret** (Settings → Variables and secrets →
   New secret), name `OPENAI_API_KEY`. Optionally also set `OPENAI_BASE_URL`
   and `PROBAS_EMBEDDING_MODEL` as variables if you want to override the defaults.

5. Commit and push:

   ```bash
   git commit -m "Deploy ProBas RAG Assistant with prebuilt index"
   git push
   ```

The Space will build, install requirements, and on boot load the prebuilt bundle
(~15 s) instead of embedding. The first chat request warms the API connection.

## Hardware note

The bundle holds 23,172 records and a (23172, 2560) float32 embedding matrix
(~237 MB in RAM) plus the BM25 token lists. The free CPU Space tier (16 GB) is
sufficient. If startup is killed for memory, upgrade to a larger CPU tier.

## Security

Rotate the API key that was previously committed to git history in this project
before reusing it as a Space secret.