README.md

---
title: Arabic Sign Language NLP API
emoji: 🤟
colorFrom: green
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
---

# Arabic Sign Language NLP API

Translates Arabic text (Fus-ha and Ammiya) into sign animation sequences.

## Endpoints

| Method | Path | Description |
|--------|------|-------------|
| GET | `/` | Health check — returns model info and sign count |
| POST | `/translate` | Translate Arabic text (JSON body) |
| GET | `/translate?text=...` | Quick translate via URL param |
| GET | `/signs` | List all signs in the database |
| GET | `/sequence-file` | Read the last saved sequence file |

## POST /translate

```json
{
  "text": "انا عايز اروح المدرسة",
  "save_sequence": false
}
```

**Response:**
```json
{
  "status": "success",
  "input_text": "انا عايز اروح المدرسة",
  "sequence": ["انا", "يريد", "يذهب", "مدرسة"],
  "total_steps": 4,
  "sign_count": 4,
  "letter_count": 0,
  "missing_keypoint_files": [],
  "detailed_plan": [...]
}
```

## Setup

1. Upload your `arabic_sign_lang_features.csv` to the Space files.
2. (Optional) Upload your `keypoints/` folder for `.npy` validation.
3. Set `CSV_PATH` env variable if your CSV has a different name.

## Environment Variables

| Variable | Default | Description |
|----------|---------|-------------|
| `CSV_PATH` | `arabic_sign_lang_features.csv` | Path to sign label CSV |
| `KEYPOINTS_FOLDER` | `keypoints` | Folder with .npy files |
| `SIMILARITY_THRESHOLD` | `0.72` | AraBERT match threshold |

## Interactive Docs

Visit `/docs` for the Swagger UI.