constants.py
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"""Paths and shared constants for search evaluation."""
from pathlib import Path
_PKG_DIR = Path(__file__).resolve().parent
_SCRIPTS_EVAL_DIR = _PKG_DIR.parent
PROJECT_ROOT = _SCRIPTS_EVAL_DIR.parents[1]
# Canonical English labels (must match LLM prompt output in prompts._CLASSIFY_TEMPLATE_EN)
RELEVANCE_EXACT = "Exact Match"
RELEVANCE_HIGH = "High Relevant"
RELEVANCE_LOW = "Low Relevant"
RELEVANCE_IRRELEVANT = "Irrelevant"
VALID_LABELS = frozenset({RELEVANCE_EXACT, RELEVANCE_HIGH, RELEVANCE_LOW, RELEVANCE_IRRELEVANT})
# Precision / MAP "positive" set (all non-irrelevant tiers)
RELEVANCE_NON_IRRELEVANT = frozenset({RELEVANCE_EXACT, RELEVANCE_HIGH, RELEVANCE_LOW})
_LEGACY_LABEL_MAP = {
"Exact": RELEVANCE_EXACT,
"Partial": RELEVANCE_HIGH,
}
def normalize_stored_label(label: str) -> str:
"""Map legacy 3-way SQLite labels to current 4-way strings; pass through canonical labels."""
s = str(label).strip()
if s in VALID_LABELS:
return s
return _LEGACY_LABEL_MAP.get(s, s)
DEFAULT_ARTIFACT_ROOT = PROJECT_ROOT / "artifacts" / "search_evaluation"
DEFAULT_QUERY_FILE = _SCRIPTS_EVAL_DIR / "queries" / "queries.txt"
# Judge LLM (eval_framework only; override via CLI --judge-model / constructor kwargs)
DEFAULT_JUDGE_MODEL = "qwen3.5-flash"
DEFAULT_JUDGE_ENABLE_THINKING = True
DEFAULT_JUDGE_DASHSCOPE_BATCH = False
DEFAULT_JUDGE_BATCH_COMPLETION_WINDOW = "24h"
DEFAULT_JUDGE_BATCH_POLL_INTERVAL_SEC = 10.0
# Rebuild annotation pool (build --force-refresh-labels): search recall + full-corpus rerank + LLM batches
DEFAULT_SEARCH_RECALL_TOP_K = 500
DEFAULT_RERANK_HIGH_THRESHOLD = 0.5
DEFAULT_RERANK_HIGH_SKIP_COUNT = 1000
DEFAULT_REBUILD_LLM_BATCH_SIZE = 50
DEFAULT_REBUILD_MIN_LLM_BATCHES = 20
DEFAULT_REBUILD_MAX_LLM_BATCHES = 40
DEFAULT_REBUILD_IRRELEVANT_STOP_RATIO = 0.92
DEFAULT_REBUILD_IRRELEVANT_STOP_STREAK = 3