runrl 0.2.1

Official Python SDK for the RunRL API

RunRL Python SDK (v0.2.0)

The RunRL Python SDK provides a friendly, fully typed interface to the RunRL REST API. It supports both synchronous and asynchronous workflows and introduces a principled futures system inspired by distributed ML orchestration platforms. Use the SDK to automate training runs, monitor progress, manipulate files, deploy checkpoints, and integrate RunRL into your ML pipelines.

Installation

pip install runrl

Quick Start

from runrl import RunRLClient

client = RunRLClient(api_key="rl_your_api_key")

# Upload a reward function
reward = client.files.create_from_content(
    name="latency_reward",
    content="""def reward_fn(prompt, response):\n    return 1 - response['latency']""",
    file_type="reward_function",
)

# Launch a training run (returns a Future immediately)
future = client.runs.create(
    model="Qwen/Qwen3-8B",
    prompt_file_id="PROMPT_UUID",
    reward_file_id=reward.id,
    completion_length=1024,
)

# Wait for completion (polls RunRL behind the scenes)
run = future.result()
print(run.status)
print(run.metrics_url)

Features

• Unified Client – simple configuration, automatic retries, pagination helpers.
• Futures System – wait for long-running operations with rich status metadata.
• Sync & Async – mirrored APIs for both paradigms (RunRLClient / AsyncRunRLClient).
• Typed Models – Pydantic models to validate API responses and guide development.
• Extensive Docs – tutorials, futures guide, and endpoint-level reference in docs/.

See docs/index.md for the full documentation set.