Skip to main content

Serverless Posttraining for Agents - Core AI functionality and tracing

Project description

Synth

Python PyPI Crates.io License

Build systems for OOMs more complexity.

Continual and offline optimization for prompts, context, skills, and long-horizon memory.

Use the SDK in Python (uv add synth-ai) and Rust (beta) (cargo add synth-ai), or call Synth endpoints from any language.

Synth Style

Synth is built for frontier builders first. We:

  • push interface complexity inward (strong server contracts, simpler app surfaces)
  • design online/offline parity with pause/resume as first-class controls
  • meet production code where it is (no forced lock-in or rewrites)
  • build general algorithmic foundations, then layer targeted affordances

For engineering principles and coding standards, see specs/README.md.

Bar chart comparing baseline vs GEPA-optimized prompt performance across GPT-4.1 Nano, GPT-4o Mini, and GPT-5 Nano.

Average accuracy on LangProBe prompt optimization benchmarks.

Demo Walkthroughs

Benchmark and demo runner source files live in the Benchmarking repo (../Benchmarking in a sibling checkout).

Product Focus

  • Continual Learning Sessions (MIPRO + GEPA): run online sessions that update prompts from reward feedback during live traffic, with first-class pause/resume/cancel controls.
  • Discrete GEPA Optimization (Prompt + Context): run offline GEPA jobs for controlled batch optimization, compare artifacts, and promote the best candidates.
  • Voyager for Skills + Long-Term Memory: optimize skill/context surfaces and use durable memory with retrieval and summarization for long-horizon agent systems.
  • One Canonical Runtime Surface: use shared systems, offline, and online primitives across SDK and HTTP APIs.
  • Agent Infrastructure Built In: run with pools, containers, and tunnels for local or managed rollouts without forcing app rewrites.
  • Graph + Verifier Workflows: train GraphGen pipelines and rubric-based verifiers for domain-specific evaluation loops.

Getting Started

Python SDK

uv add synth-ai
# or
pip install synth-ai==0.9.3

Rust SDK (beta)

cargo add synth-ai

API (any language)

Use your SYNTH_API_KEY and call Synth HTTP endpoints directly.

Docs: docs.usesynth.ai

Project details


Release history Release notifications | RSS feed

This version

0.9.3

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

synth_ai-0.9.3.tar.gz (692.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

synth_ai-0.9.3-cp311-cp311-macosx_11_0_arm64.whl (10.3 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

File details

Details for the file synth_ai-0.9.3.tar.gz.

File metadata

  • Download URL: synth_ai-0.9.3.tar.gz
  • Upload date:
  • Size: 692.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.6

File hashes

Hashes for synth_ai-0.9.3.tar.gz
Algorithm Hash digest
SHA256 914de81e6933d3ba5e0801c1fadaf9ed35ec1bccf08f899ac3881b8bdf497c2d
MD5 979b8a817c591b94a1e213654e2e1c07
BLAKE2b-256 502cb706e27421901250adc87874efcf4eaa3d6808894562b33607d80f9c66d1

See more details on using hashes here.

File details

Details for the file synth_ai-0.9.3-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for synth_ai-0.9.3-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1751df2d3b798397a69a0f1c9033cc465eef40c547f568e5b7579b1ac8ba09cc
MD5 26a5678cced2a0b65daef96aa36d5bc8
BLAKE2b-256 6beb792348d31d341449334517ed2695ba94331c796fc22d9dc295a2ceecfae5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page