RL as a service SDK - Core AI functionality and tracing
Project description
Synth-AI
Docs: Synth‑AI Documentation
Fast and effective reinforcement learning for agents, via an API
Highlights
- Easily scale gpu topologies - train on 3 a10gs or 8 H100s (multi-node available upon request)
- Requires only a thin fastapi wrapper to integrate with existing agent software.
- Supports the best OSS models like Qwen3. (gpt-oss available upon request, GA soon)
- Own your trained models
Getting Started
synth-ai comes with a built-in RL example tailored for training Qwen/Qwen3-0.6B to succeed at Math.
Please create an account at Synth and Modal for the Math hello‑world test run. Then run:
uvx synth-ai demo
uvx synth-ai setup
uvx synth-ai deploy
uvx synth-ai run
To walk through kicking off your first RL run, see the Synth‑AI Documentation.
What setup does now
When you run uvx synth-ai setup (or the legacy uvx synth-ai rl_demo setup), the SDK opens your browser to the Synth dashboard for a one‑time pairing (handshake) with your signed‑in session. The SDK will automatically:
- Detect your current user and organization
- Ensure both API keys exist for that user+org
- Write the keys to your project’s
.envfile asSYNTH_API_KEYandENVIRONMENT_API_KEY
No keys are printed or requested interactively. You’ll see a confirmation like:
Connecting SDK to your browser session…
Connected to Acme Labs via browser.
If your browser isn’t already signed in, sign in when prompted and the pairing completes automatically. The dashboard’s welcome modal will reflect a successful pairing.
Environment variables:
SYNTH_CANONICAL_ORIGIN(optional): override the dashboard base URL the SDK uses for the handshake (defaults tohttps://www.usesynth.ai/dashboard).SYNTH_CANONICAL_DEV(optional): set to1,true,yes, oronto target the local dashboard athttp://localhost:3000.- Keys are stored only in your project’s
.envfile, not exported to your shell.
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