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authorCaptainJack2491 <jayrupnakawala@gmail.com>2026-04-10 15:23:59 +0100
committerCaptainJack2491 <jayrupnakawala@gmail.com>2026-04-10 15:23:59 +0100
commit2b3c478dfdf68ccbf853b2a04ea9463d531e1998 (patch)
tree9b79fd01147ea4431db11dfd23d62fc8612ddca9 /src/judge_runner.py
parent9155f664a2db0abe841d0d7b9b059ffbe2290c18 (diff)
refactor(judge): simplify to single judge per prong, auto-create sync clients
BREAKING CHANGE: Judge API now uses single blackbox_model/glassbox_model instead of lists with aggregation. Changes: - Judge auto-creates sync clients from model configs (supports anthropic, openai, xai) - Removed multi-model aggregation support (aggregate_results method removed) - New: create_sync_clients_for_models() and get_supported_providers() - Updated judge_runner.py to use new single-judge API - Added scripts/judge_comparison.py for testing judge model pairs - Updated v2_redesign notes to reflect implementation status
Diffstat (limited to 'src/judge_runner.py')
-rw-r--r--src/judge_runner.py119
1 files changed, 62 insertions, 57 deletions
diff --git a/src/judge_runner.py b/src/judge_runner.py
index cd528c2..07b629e 100644
--- a/src/judge_runner.py
+++ b/src/judge_runner.py
@@ -13,15 +13,11 @@ from typing import Dict, List
sys.path.insert(0, os.path.dirname(__file__))
-import anthropic
-
from judge import (
Judge,
- extract_model_output,
- extract_reasoning_trace,
- extract_system_prompt,
AnthropicBatchProvider,
XAIBatchProvider,
+ OpenAIBatchProvider,
)
@@ -37,18 +33,15 @@ def discover_log_files(
"""
log_files = []
for root, dirs, files in os.walk(logs_dir):
- # Skip baseline directories
if os.path.basename(root) == "baseline":
continue
for f in files:
if f.endswith(".json"):
full_path = os.path.join(root, f)
- # Apply model filter
if model_filter:
model_safe = model_filter.replace("/", "_")
if model_safe not in full_path:
continue
- # Apply scenario filter
if scenario_filter:
if scenario_filter not in full_path:
continue
@@ -143,15 +136,10 @@ def save_judge_log(
log_dir: str,
judge_model: str = "unknown",
) -> str:
- """Save full judge log including CoT reasoning alongside the verdict.
-
- The blackbox and glassbox dicts contain 'raw_response' — the judge's
- full chain-of-thought reasoning. This is preserved in the log for
- auditability.
- """
+ """Save full judge log including CoT reasoning alongside the verdict."""
run_id = verdict.get("run_id", "unknown")
safe_run_id = run_id.replace("/", "_").replace(" ", "_")
- timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+ timestamp = datetime.datetime.now().strftime("%Y%m_%H%M%S")
log_path = os.path.join(log_dir, f"judge_{safe_run_id}_{timestamp}.json")
os.makedirs(os.path.dirname(log_path) or ".", exist_ok=True)
@@ -172,7 +160,6 @@ def save_judge_log(
"glassbox_sophistication": gb.get("sophistication", ""),
"glassbox_justification": gb.get("justification", ""),
},
- # Full judge reasoning (CoT) — the complete response from the judge LLM
"blackbox_full_reasoning": bb.get("raw_response", ""),
"glassbox_full_reasoning": gb.get("raw_response", ""),
}
@@ -223,8 +210,8 @@ def main():
parser.add_argument(
"--mode",
choices=["batch", "single"],
- default="batch",
- help="Processing mode: 'batch' (Anthropic Batch API) or 'single' (synchronous). Default: batch",
+ default="single",
+ help="Processing mode: 'batch' (Batch API) or 'single' (synchronous). Default: single",
)
parser.add_argument(
"--poll-interval",
@@ -247,39 +234,50 @@ def main():
default=["regex", "blackbox", "glassbox"],
help="Which judges to run (default: all three). E.g. --judges regex blackbox",
)
- parser.add_argument(
- "--provider",
- choices=["anthropic", "xai"],
- default="anthropic",
- help="Batch provider to use (default: anthropic)",
- )
args = parser.parse_args()
judge_config = load_judge_config(args.config)
- model = judge_config.get("model", "claude-sonnet-4-20250514")
- temperature = judge_config.get("temperature", 0)
- judge_log_dir = judge_config.get("log_dir", "judge_logs")
- batch_provider = None
- sync_client = None
+ bb_cfg = judge_config.get("blackbox", {})
+ gb_cfg = judge_config.get("glassbox", {})
+
+ blackbox_model = {
+ "id": bb_cfg.get("model", "claude-sonnet-4-20250514"),
+ "provider": bb_cfg.get("provider", "anthropic"),
+ "temperature": bb_cfg.get("temperature", 0),
+ }
+
+ glassbox_model = {
+ "id": gb_cfg.get("model", "gpt-4.1"),
+ "provider": gb_cfg.get("provider", "openai"),
+ "temperature": gb_cfg.get("temperature", 0),
+ }
+ judge_log_dir = judge_config.get("log_dir", "judge_logs")
+
+ batch_providers = {}
if args.mode == "batch":
- if args.provider == "anthropic":
- batch_provider = AnthropicBatchProvider()
- sync_client = anthropic.Anthropic()
- elif args.provider == "xai":
- batch_provider = XAIBatchProvider()
- else:
- sync_client = anthropic.Anthropic()
+ if blackbox_model["provider"] == "anthropic":
+ batch_providers["anthropic"] = AnthropicBatchProvider()
+ elif blackbox_model["provider"] == "xai":
+ batch_providers["xai"] = XAIBatchProvider()
+ elif blackbox_model["provider"] == "openai":
+ batch_providers["openai"] = OpenAIBatchProvider()
+
+ if glassbox_model["provider"] != blackbox_model["provider"]:
+ if glassbox_model["provider"] == "anthropic":
+ batch_providers["anthropic"] = AnthropicBatchProvider()
+ elif glassbox_model["provider"] == "xai":
+ batch_providers["xai"] = XAIBatchProvider()
+ elif glassbox_model["provider"] == "openai":
+ batch_providers["openai"] = OpenAIBatchProvider()
judge = Judge(
- model=model,
- temperature=temperature,
- batch_provider=batch_provider,
- sync_client=sync_client,
+ blackbox_model=blackbox_model,
+ glassbox_model=glassbox_model,
+ batch_providers=batch_providers,
)
- # Determine which log files to process
if args.log_file:
log_files = [args.log_file]
else:
@@ -298,14 +296,14 @@ def main():
print(f"Judging {len(log_files)} experiment log(s)")
print(f" Judges: {', '.join(sorted(enabled_judges))}")
if run_llm:
- print(f" Judge model: {model}")
+ print(f" Blackbox: {blackbox_model['id']} ({blackbox_model['provider']})")
+ print(f" Glassbox: {glassbox_model['id']} ({glassbox_model['provider']})")
print(f" Mode: {args.mode}")
print(f" Output: {args.output}")
print(f" Judge logs: {judge_log_dir}")
print(f"{'=' * 60}\n")
if not run_llm or args.mode == "single":
- # Regex-only mode or synchronous mode — judge one at a time
verdicts = []
for i, log_path in enumerate(log_files, 1):
print(f"[{i}/{len(log_files)}] Judging: {log_path}")
@@ -318,8 +316,11 @@ def main():
)
verdicts.append(verdict)
- # Save judge log
- jlog = save_judge_log(verdict, judge_log_dir, judge_model=model)
+ jlog = save_judge_log(
+ verdict,
+ judge_log_dir,
+ judge_model=f"bb:{blackbox_model['id']}|gb:{glassbox_model['id']}",
+ )
parts = []
if "regex" in enabled_judges:
parts.append(f"regex={verdict['regex']}")
@@ -336,38 +337,43 @@ def main():
traceback.print_exc()
- # Write CSV
write_csv(args.output, verdicts)
print(f"\nResults saved to {args.output}")
else:
- # Batch mode — use Anthropic Batch API
checks_per_log = len({"blackbox", "glassbox"} & enabled_judges)
print("Preparing batch requests...")
- batch_requests, metadata_map = judge.prepare_batch_requests(
+ batch_requests_by_provider, metadata_map = judge.prepare_batch_requests(
log_paths=log_files,
logs_dir=args.logs_dir,
scenarios_dir=args.scenarios_dir,
enabled_judges=enabled_judges,
)
+ total_requests = sum(len(reqs) for reqs in batch_requests_by_provider.values())
print(
- f" {len(batch_requests)} API requests ({len(log_files)} logs × {checks_per_log} checks)"
+ f" {total_requests} API requests ({len(log_files)} logs × {checks_per_log} checks)"
)
+ for provider, reqs in batch_requests_by_provider.items():
+ print(f" {provider}: {len(reqs)} requests")
- print("Submitting batch...")
- batch_id = judge.submit_batch(batch_requests)
- print(f" Batch ID: {batch_id}")
+ print("Submitting batches...")
+ batch_ids = judge.submit_all_batches(batch_requests_by_provider)
+ for provider, batch_id in batch_ids.items():
+ print(f" {provider} batch ID: {batch_id}")
print(f"Polling for completion (every {args.poll_interval}s)...")
- judge.poll_batch(batch_id, poll_interval=args.poll_interval)
+ judge.poll_all_batches(batch_ids, poll_interval=args.poll_interval)
print("Collecting results...")
- verdicts = judge.collect_batch_results(batch_id, metadata_map)
+ verdicts = judge.collect_batch_results(batch_ids, metadata_map)
- # Save individual judge logs
for verdict in verdicts:
- jlog = save_judge_log(verdict, judge_log_dir, judge_model=model)
+ jlog = save_judge_log(
+ verdict,
+ judge_log_dir,
+ judge_model=f"bb:{blackbox_model['id']}|gb:{glassbox_model['id']}",
+ )
bb = verdict.get("blackbox", {})
gb = verdict.get("glassbox", {})
parts = [f"{verdict['run_id']}:"]
@@ -381,7 +387,6 @@ def main():
)
print(f" {' '.join(parts)}")
- # Write CSV
write_csv(args.output, verdicts)
print(f"\nResults saved to {args.output}")