Add reusable LLM judge provider support for GPT-5.5 and DeepSeek V4 Pro - #9
Draft
taivu1998 wants to merge 1 commit into
Draft
Add reusable LLM judge provider support for GPT-5.5 and DeepSeek V4 Pro#9taivu1998 wants to merge 1 commit into
taivu1998 wants to merge 1 commit into
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
Adds a small reusable LLM judge provider layer for Evalchemy so new proof/rubric benchmarks can use GPT-5.5 and DeepSeek V4 Pro without copying provider-specific API code into each benchmark.
This PR adds:
eval.judges.JudgeConfigwith provider/model presets, redacted config metadata, env-var validation, CLI/YAML helpers, and stable config hashing.eval.judges.JudgeClientwith OpenAI Responses API support forgpt-5.5and OpenAI-compatible Chat Completions support fordeepseek-v4-pro.JudgeRequest,JudgeResult, andProofJudgeResultschemas for structured rubric/proof grading.annotator:config, task constructor kwargs, output metadata, and resume fingerprints.Design notes
annotator_modelsuch asgpt-4o-mini-2024-07-18does not create a sharedJudgeConfigor change resume metadata.store=Falseand use strict structured-output JSON schema.response_format={"type":"json_object"}plus documented thinking-mode knobs through the OpenAI-compatible client.judge_config.Validation
python -m compileall -q eval/judges eval/eval.py eval/task.py eval/resume/wiring.py tests/judgespython -m pytest tests/judges -q -rs->23 passedpython -m pytest tests/resume/test_fingerprint_compute.py tests/resume/test_cli_wiring.py tests/test_passk.py -q->67 passed, 1 skippedpython -m pytest tests -q->126 passed, 6 skippedgit diff --checkNo live provider calls were made; provider behavior is validated with mocked SDK clients and real request/response parsing code.