docs/SHIP.md

# Shippable build — `dynamic-finetuned`

This branch **is** the shippable product: one container = FastAPI backend +
built React frontend + Tesseract OCR + the dynamic-baseline risk engine, running
on the zero-shot DeBERTa classifier (MIT) by default. Verified end-to-end in
deployment mode (backend serves the SPA + full API; uploads, risks, dynamic
baseline, exports, portfolio, traceability all pass).

## Deploy (one command)
```bash
APP_PASSWORD=choose-a-password docker compose up -d --build
# app -> http://<server>:8000   (PostgreSQL + zero-shot classifier + OCR, no model downloads at runtime)
```
The image bakes the zero-shot DeBERTa weights, so it runs **air-gapped** — no
calls to huggingface.co. SQLite single-container fallback:
`DATABASE_URL=sqlite:////app/data/contracts.db`.

## Defaults (the safe, clean ship config)
| Setting | Default | Meaning |
|---|---|---|
| `CLASSIFIER` | `auto` | zero-shot DeBERTa (0.61, MIT) if weights present → rules. **Clean licence.** |
| `CORE_LLM_BACKEND` | `auto` | Ollama if reachable → rules. Extraction works with or without an LLM. |
| `CORE_LLM_MODEL_OLLAMA` | `qwen2.5:7b` | the extraction LLM (swap to your trained model — see below) |

## Plugging in the trained Ollama model (when ready)
1. Create it in Ollama (e.g. from your GGUF + Modelfile):
   `ollama create contract-llm -f Modelfile`
2. Point the app at it:
   `CORE_LLM_MODEL_OLLAMA=contract-llm CORE_LLM_BACKEND=ollama docker compose up -d`
No code change — the extraction layer reads the model name from the env var.

## Optional: the fine-tuned classifier (accuracy upgrade)
Default ships on zero-shot (clean licence, robust). To run the fine-tuned
fusion classifier, drop the model dir in and set one env var — see
`docs/ACTIVATE_FINETUNED.md`. Deploy on **DeBERTa 0.67 (MIT)**, not LegalBERT
(CC-BY-SA).

## Verify a deployment
```bash
curl -fsS http://<server>:8000/api/health         # {"status":"ok", ...}
cd backend && ../.venv/bin/python tests/test_risk_golden.py   # golden test OK
```

## Accuracy (for the slide)
rules 0.50 → zero-shot DeBERTa **0.61 (shipped default)** → fine-tuned fusion
**0.68** (measured, optional upgrade). The dynamic baseline — computed from 510
CUAD contracts — runs on top of any of them.

## Status
Shippable now on zero-shot + dynamic baseline. Open/optional: trained Ollama
model (hook ready above), DeBERTa-0.67 classifier weights (clean-licence
accuracy upgrade), merge to `main`.