README.md

# Safetensors Studio & Bench

> **Run, test, and benchmark local Safetensors models with surgical VRAM observability.**

[![Next.js](https://img.shields.io/badge/Next.js-14-black?logo=next.js)](https://nextjs.org/)
[![FastAPI](https://img.shields.io/badge/FastAPI-0.110-009688?logo=fastapi)](https://fastapi.tiangolo.com/)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](./LICENSE)
[![Hugging Face](https://img.shields.io/badge/🤗-Hugging%20Face-FFD21E)](./docs/HUGGINGFACE.md)

**Safetensors Studio & Bench** is a full-stack, local-first platform to **load any `*.safetensors` + `config.json` + `tokenizer.json` folder, stream chat with real TPS/TTFT, run automated benchmarks (Reasoning/Coding/Arabic/Summarization), and profile GPU/CPU/RAM live** — no cloud required.

📖 **Arabic README:** [`README_AR.md`](./README_AR.md) | 📚 **Docs:** [`docs/`](./docs/) | 🤝 **Contribute:** [`CONTRIBUTING.md`](./CONTRIBUTING.md)

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## ✨ Key Features

| Area | What you get |
|------|--------------|
| **Safetensors Loader** | Local folder picker • `Float16 / Bfloat16 / Float32` • `4-bit NF4 / 8-bit` via `bitsandbytes` • `device_map: auto / balanced / cpu / cuda:0` + offloading |
| **Live Playground** | Token Streaming (SSE) • Real `Tokens/sec` & `TTFT` • Temperature / Top-P / Max Tokens • Copy & clear |
| **Automated Benchmark** | 15 preset tasks: Reasoning (4), Coding (4), Arabic Quality (4), Summarization (3) • `Exact / Regex / LLM-as-Judge` • **Custom datasets:** drop any folder with `.csv/.json/.jsonl/.txt/.md` → auto-detects language (Arabic/English) & category |
| **Hardware Profiling** | `pynvml + psutil` → live VRAM/CPU/RAM/Power via `Recharts` • VRAM peak timeline • TPS vs VRAM scatter • 600-point history |
| **Reports & Sharing** | Export `PDF (Arabic-capable)` / `JSON` / `CSV` • Shareable link `/share/{token}` • Full tables + `by_category` insights |

---

## 🌍 Supported Languages

| Language | Coverage |
|----------|----------|
| **English** | UI, prompts, docs, code, benchmarks (`Reasoning`, `Coding`, `Summarization`) |
| **Arabic (العربية)** | Full UI RTL, benchmarks (`Arabic Quality`, `Summarization`), PDF with `tahoma.ttf` + `arabic-reshaper`, auto-detection `\u0600-\u06FF` for custom datasets |
| **Mixed** | Auto `language_counts: {ar, en}` per folder, per report |

> Add a new language: add prompts to `backend/app/benchmark.py:14` and categories to `dataset_parser.py:11`. See [`SUPPORTED_LANGUAGES.md`](./SUPPORTED_LANGUAGES.md).

---

## 🚀 Quick Start

### 1. Requirements
- Node 22+ / Python 3.12+
- 8GB RAM minimum (CPU mode), 12GB+ VRAM recommended for 7B models on GPU

### 2. Backend
```bash
cd backend
pip install -r requirements.txt          # torch CPU + transformers are included
# optional GPU: pip install torch --index-url https://download.pytorch.org/whl/cu121
uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
# → http://localhost:8000/docs
```

### 3. Frontend
```bash
cd frontend
npm install
npm run dev
# → http://localhost:3000
# env: frontend/.env.local → NEXT_PUBLIC_API_URL=http://localhost:8000
```

### 4. Docker (alternative)
```bash
docker compose up --build
# frontend http://localhost:3000  backend http://localhost:8000
```

### 5. Load a model
- Place a HF-style folder anywhere, e.g. `C:\models\mistral-7b` containing `model.safetensors`, `config.json`, `tokenizer.json`
- In UI `/` or `/models` or **new:** top bar of `/benchmark` → paste path → `Validate` → `Load`
- Or via API: `POST /api/model/load {"model_path":"C:\\models\\my-model","dtype":"float16","quantization":"4bit","device_map":"auto"}`

> **No GPU?** The platform auto-enters **Demo Mode** (simulated generation) so you can still test all features.

---

## 📁 Project Structure

```
backend/app/
  main.py                 # FastAPI + CORS + routers
  model_manager.py        # Safetensors loader (torch dtype/quant/device_map)
  telemetry.py            # pynvml/psutil + 600-point history
  benchmark.py            # 15 tasks + evaluate_answer()
  dataset_parser.py       # CSV/JSON/JSONL/TXT/MD → BenchmarkTask + lang detect
  schemas.py
  routers/{model,inference,telemetry,benchmark,custom_benchmark,share,export}.py
frontend/src/
  app/{page, playground, benchmark, hardware, models, share/[token]}
  components/{ModelLoader, ModelPathSelector, Playground, BenchmarkPanel, CustomDatasetPanel, TelemetryCharts}
  lib/{api.ts, utils.ts}
example_dataset/          # 9-task mixed sample (AR/EN)
docs/                     # English developer docs
```

---

## 🔌 API Reference (core)

| Method | Path | Description |
|--------|------|-------------|
| `POST` | `/api/model/load` | Load Safetensors folder |
| `GET`  | `/api/model/status` | Loaded info |
| `GET`  | `/api/model/validate?path=` | Check `*.safetensors + config.json` |
| `POST` | `/api/generate` (SSE) | Stream tokens with `ttft_ms`, `tokens_per_sec` |
| `GET`  | `/api/telemetry/` | Snapshot (VRAM/GPU/CPU/RAM) |
| `WS`   | `/ws/telemetry` | Live push (fallback to HTTP polling) |
| `POST` | `/api/benchmark/run` | Sync benchmark (blocking) |
| `POST` | `/api/benchmark/run-stream` | **SSE progress** (`type: progress/task_done/done`) |
| `POST` | `/api/benchmark/custom/scan?folder_path=` | Scan custom folder |
| `POST` | `/api/benchmark/custom/run-from-folder` | Run on custom folder |
| `POST` | `/api/benchmark/custom/upload` | Multipart upload |
| `POST` | `/api/share/{report_id}` | Create share token |
| `GET`  | `/api/share/{token}` | Fetch shared report |
| `GET`  | `/api/export/{json,csv,pdf}?report_id=` | Export |

Full spec: http://localhost:8000/docs

---

## 🧪 Benchmark Suites

| Suite | Tasks | Judge |
|-------|-------|-------|
| `reasoning` | arithmetic, sequence, logic puzzle, fraction | Regex `\b7\b` |
| `coding` | fibonacci, loop output, reverse_string, sorted | Regex `def\s+` |
| `arabic` | spelling, synonym, i'rab, summarization | Regex `ذهبت`, `فرح` |
| `summarization` | tech text, Transformer, bullet points | Regex `7 مليار` |

Custom folder example (`CSV`):
```
prompt,expected,expected_regex,category,name
"ما مرادف سعيد؟",فرح,فرح,arabic,syn
```

---

## 📊 Hardware Profiling

- `telemetry.py:19` polls `pynvml.nvmlDeviceGetMemoryInfo` + `psutil.virtual_memory` every 1.2s
- `Recharts` Area/Line/Scatter: VRAM timeline, CPU/RAM %, Power vs VRAM, TPS vs VRAM
- `vram_peak_mb` tracked per task and globally

---

## 📄 Export & Sharing

- **PDF:** Unicode via `tahoma.ttf` + `arabic-reshaper` + `python-bidi` (fallback to `?` sanitization)
- **Share:** in-memory `share_store[token]=report_id` → `/share/{token}` page

---

## 🛠️ Development

See [`docs/DEVELOPMENT.md`](./docs/DEVELOPMENT.md) and [`docs/ARCHITECTURE.md`](./docs/ARCHITECTURE.md).

```bash
# Frontend
npm run build   # production
npm run lint

# Backend
python -m pytest  # (add tests)
pip install -r requirements.txt
```

---

## 🤗 Hugging Face

- Use any HF model: download `snapshots` and point `model_path` to it.
- Model card template: [`docs/HUGGINGFACE.md`](./docs/HUGGINGFACE.md)
- Dataset parser auto-handles HF `datasets` exported as JSONL/CSV.

---

## 🤝 Contributing

Please read [`CONTRIBUTING.md`](./CONTRIBUTING.md) and [`CODE_OF_CONDUCT.md`](./CODE_OF_CONDUCT.md). PRs for new languages, benchmarks, and quant backends are welcome!

## 🔒 Security

See [`SECURITY.md`](./SECURITY.md).

## 📝 License

MIT — see [`LICENSE`](./LICENSE).

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