# Deploying the GDScript Assistant (Colab-built jina index)

The 280 MB jina index is built on a **free Colab GPU** and pushed straight to the
Space, so it never moves over your local connection. You only push the app +
`chunks.jsonl` (~90 MB) once.

## 0. Prerequisites
- HuggingFace account + **write token** (https://huggingface.co/settings/tokens).
- `git`, `git-lfs`, `pip install huggingface_hub`.
- `data/chunks.jsonl` is already staged in this folder.

## Phase 1 — Push the app + corpus (your machine)
The app tolerates a missing index (it answers without retrieval until the index
is added), so deploy first:
```bash
huggingface-cli login            # write token
huggingface-cli repo create gdscript-assistant --type space --space_sdk gradio
cd hf-space/gdscript-assistant
git init && git lfs install
git add . && git commit -m "GDScript RAG assistant (app + corpus)"
git remote add origin https://huggingface.co/spaces/<user>/gdscript-assistant
git push -u origin main           # ~90MB: chunks.jsonl (LFS) + code
```
Then in **Space → Settings → Hardware → select "ZeroGPU"**.

## Phase 2 — Build the jina index on Colab (free GPU, ~10 min)
1. Open https://colab.research.google.com → new notebook →
   **Runtime → Change runtime type → T4 GPU**.
2. Cell 1 (install):
   ```python
   !pip install -q "transformers<5" sentence-transformers einops faiss-cpu huggingface_hub
   ```
3. Cell 2: paste the contents of **`colab_build_index.py`**, set at the top:
   ```python
   SPACE_REPO = "<user>/gdscript-assistant"
   HF_TOKEN   = "hf_...your_write_token..."
   ```
   Run it. It pulls `chunks.jsonl` from the Space, embeds 91,720 chunks with
   `jina-embeddings-v2-base-code` on the GPU, builds the FAISS index, and
   **uploads `data/embeddings.faiss` + `data/id_map.json` back to the Space**.
4. The Space auto-restarts and now answers with full RAG + sources.

## Phase 3 — Verify on the Space
- Ask *"Write a CharacterBody2D top-down movement script"* → GDScript answer, a
  **✅ gdtoolkit validation** badge, and a **📚 Retrieved sources** list.
- Force a mistake to see the **🔧 auto-correct** path.
- Hitting ZeroGPU quota? HF **PRO** ($9/mo) gives much more GPU time.

## Notes
- Index format is built to match `rag.py` exactly (cosine `IndexIDMap2`,
  `faiss_id == chunk id`; `id_map.json` keyed by `str(id)`).
- `requirements.txt` pins `transformers~=4.45` so jina (query embedding) and
  Qwen2.5-Coder both load with no patches.
- Validation checks **syntax + style** (gdtoolkit), not runtime/scene semantics.
- Fallback (local build): if you ever build the index locally
  (`python crawl_gdscript.py embed`), run `bash stage_index.sh` then push — but
  jina on this CPU is ~50h, so Colab is strongly preferred.