Metadata-Version: 2.4
Name: sstudio
Version: 0.0.1
Summary: SmartStudio Post-Training SDK — Python client and CLI for the SmartStudio platform.
Author-email: SmartStudio <sdk@smartstudio.com>
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Typing :: Typed
Requires-Python: >=3.8
Requires-Dist: click>=8.0
Requires-Dist: httpx>=0.25.0
Requires-Dist: pydantic>=2.0
Requires-Dist: pyyaml>=6.0
Description-Content-Type: text/markdown

# sstudio

`sstudio` is the Python SDK and command-line client for the **SmartStudio**
post-training platform. It wraps the platform's HTTP APIs behind a small, stable
Python surface and an `sstudio` CLI — handling authentication, request
normalization, and unified job tracking.

## Install

```bash
pip install sstudio
```

## Authenticate

```bash
sstudio login --api-key sk-xxxx
sstudio whoami
```

Or from Python:

```python
from sstudio import SmartStudioClient

with SmartStudioClient(api_key="sk-xxxx") as client:
    print(client.me())
```

## Configure

Project settings live in `sstudio.yaml` (base model, platform endpoint, storage
paths, …). Values are resolved with the precedence
*command-line flag > `SSTUDIO_*` env var > `sstudio.yaml` > built-in default*.

```bash
sstudio config validate
sstudio config show
```

## Scope

The SDK is organized around the post-training workflow:

| Module  | Purpose |
| ------- | ------- |
| `data`  | Document parsing and training/eval dataset generation |
| `train` | SFT-LoRA / SFT-Full / SFT-Plus / DPO / GKD fine-tuning |
| `eval`  | Benchmark scoring and LLM/VLM-as-judge evaluation |
| `serve` | Model deployment |
| `job`   | Unified async job status, logs and results |

## Requirements

Python 3.8+

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