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synthiaresearch

Synthia evals your AI agent against simulated users: probe it to infer who it's for, generate a synthetic scenario dataset, play the scenarios against it, and judge every rollout — locally from this SDK, or as a CI gate on every pull request.

pip install synthiaresearch   # Python ≥ 3.10; the import name is `synthia`

Quickstart

from synthia import Synthia

client = Synthia()  # reads SYNTHIA_API_KEY / SYNTHIA_BASE_URL

# One call: probe + generate (or reuse this script's dataset), play every
# scenario against your agent, judge the rollouts server-side.
def rollout_agent(transcript, sandbox):
    return my_agent.respond_with_tools(transcript, sandbox)

outcome = client.run(rollout_agent, agent_meta={"name": "my-agent"})
print(outcome.pass_rate, outcome.evaluations)

Each step — prepare(), rollouts.run(), rollouts.quality_check() — is also available individually when you need to intervene between them.

In CI

The package ships the synthia CLI (also python -m synthia): point a synthia.yaml at a module exporting agent(transcript, sandbox) -> reply and gate PRs on the pass rate —

synthia validate   # check config + entrypoint, no network
synthia run        # play the suite, judge it, gate on thresholds

— or use the GitHub Action with language: python. Setup guide: Synthia in CI.

Documentation

Mirrors the JS/TypeScript SDK (synthiaresearch on npm) — same API surface, same CLI, same yaml, byte-identical results-JSON contract. Replies and tool events are redacted by default before upload. MIT licensed.

Development

  • src/synthia/client.py — the SDK: the Synthia client, resource classes, and the local probe/rollout loops with tool-call tracing.
  • src/synthia/cli/ — the synthia CLI, a module-for-module mirror of the JS CLI (same schema, same exit codes, same report contract).
  • pyproject.toml — the synthiaresearch package definition (httpx and pyyaml as the only runtime dependencies; the import name stays synthia).

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