Petri is an open-source alignment auditing agent that lets researchers rapidly test concrete safety hypotheses against target models using realistic, multi-turn scenarios. Instead of building bespoke evals, Petri automatically generates audit environments from seed “special instructions,” orchestrates an auditor model to probe a target model, and simulates tool use and rollbacks to surface risky behaviors. Each interaction transcript is then scored by a judge model using a consistent rubric so results are comparable across runs and models. The system supports major model APIs and comes with starter seeds and judge dimensions, enabling minutes-to-insight workflows for questions like reward hacking, self-preservation, or eval awareness. Petri is designed for parallel exploration: it spins many audits in flight, aggregates findings, and highlights transcripts that deserve human review.

Features

  • Scenario generator that turns seed instructions into realistic audit setups
  • Multi-turn auditor orchestration with simulated tool use and rollbacks
  • Judge model that scores transcripts via a consistent safety rubric
  • Parallel execution to explore many hypotheses and surface the riskiest traces first
  • Built-in starters for seeds and judge dimensions plus guidance for customization
  • API support for popular model providers with reproducible runs and reports

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Categories

AI Agents

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python AI Agents

Registered

2 days ago