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Automatically generate evals for every AI change

Project description

Parity

PyPI License: MIT Python 3.11+

Parity analyzes behavior-defining AI changes in pull requests, discovers the most relevant existing eval target, validates the real coverage gaps, and proposes native eval additions that fit the target suite.

Parity is not an eval runner. It does not create or mutate hosted evaluator infrastructure. It reuses the eval system you already have.

What Parity Does

For each PR that changes prompts, instructions, guardrails, judges, validators, or similar behavior-defining assets, Parity:

  1. Detects the behavioral change.
  2. Resolves the best matching eval target and method.
  3. Validates which gaps are actually uncovered.
  4. Synthesizes native eval additions for that target.
  5. Writes only native_ready evals after explicit approval.

Support

Path Status Notes
Promptfoo Strong Best fully native path. Assertions are row-local and writeback is straightforward.
LangSmith Strong Strong dataset discovery and writeback. Evaluator reuse is supported; evaluator mutation is out of scope.
Braintrust Supported with limitations Writeback works. Target discovery is weaker and evaluator recovery depends more on repo assets.
Arize Phoenix Supported with limitations Dataset read/write works. Evaluator discovery is weaker than Promptfoo and LangSmith.
Bootstrap mode Built in If no safe target is found, Parity proposes starter evals and abstains from unsafe writeback.

More detail: docs/platforms.md

Public Commands

These are the commands most users need:

  • parity init
  • parity doctor
  • parity run-stage 1
  • parity run-stage 2
  • parity run-stage 3
  • parity write-evals

Parity also ships lower-level operational commands for GitHub comments, run lookup, embeddings, and similarity, but those are advanced surfaces rather than the main product path.

Quick Start

pip install parity-ai
parity init

Then:

  1. Fill in the generated context/ files.
  2. Add GitHub secrets: ANTHROPIC_API_KEY, OPENAI_API_KEY, and any platform keys you use.
  3. Commit parity.yaml, .github/workflows/parity.yml, and context/.
  4. Open a PR that changes AI behavior.
  5. Add the fixed approval label parity:approve before merging if you want Parity to write approved evals back after merge.

Docs

License

MIT

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