Delete benchmarks/search/config.py

benchmarks/search/config.py

@@ -1,96 +0,0 @@
-from __future__ import annotations
-
-import os
-from dataclasses import dataclass
-from pathlib import Path
-
-from dotenv import load_dotenv
-
-BENCHMARKS_ROOT = Path(__file__).resolve().parent.parent
-DATA_DIR = BENCHMARKS_ROOT / "data"
-RUNS_DIR = BENCHMARKS_ROOT / "runs"
-DEFAULT_DATASET_PATH = DATA_DIR / "search_toy.jsonl"
-DEFAULT_BRAIN_ID = "searchbenchsmoke"
-REQUIRED_PREFIX = "searchbench"
-FORBIDDEN_BRAINS = frozenset(
-    {
-        "beam1m1clean",
-        "demorecsys",
-        "locomoconv26",
-        "locomoconv26clean",
-        "locomoconv26nostorm",
-    }
-)
-FORBIDDEN_PREFIXES = (
-    "beam",
-    "demorecsys",
-    "lme",
-    "locomoconv",
-    "longmemeval",
-)
-FROZEN_STRUCTURED_BRAINS = frozenset(
-    {
-        "searchbenchwands",
-        "searchbenchesci74",
-        "searchbenchescies",
-        "searchbenchesciltr2",
-    }
-)
-TERMINAL_TASK_STATUSES = frozenset({"completed", "failed", "partial_failed"})
-
-
-def validate_brain_id(brain_id: str) -> str:
-    bid = (brain_id or "").strip()
-    if not bid:
-        raise SystemExit("brain_id is required.")
-    lowered = bid.lower()
-    forbidden = {item.lower() for item in FORBIDDEN_BRAINS}
-    if lowered in forbidden or lowered.startswith(FORBIDDEN_PREFIXES):
-        raise SystemExit(
-            f"Refusing brain_id={bid!r}. Use a dedicated searchbench* brain "
-            f"(default {DEFAULT_BRAIN_ID}). Never wipe eval memory or recsys brains."
-        )
-    if not lowered.startswith(REQUIRED_PREFIX):
-        raise SystemExit(
-            f"Refusing brain_id={bid!r}. Search eval brains must start with "
-            f"{REQUIRED_PREFIX!r} (default {DEFAULT_BRAIN_ID})."
-        )
-    return bid
-
-
-@dataclass
-class Settings:
-    brainapi_url: str
-    brainpat_token: str
-    dataset_path: Path
-    runs_dir: Path
-    brain_id: str
-
-    @classmethod
-    def load(cls, env_file: Path | None = None) -> "Settings":
-        if env_file is None:
-            env_file = BENCHMARKS_ROOT / ".env"
-        if env_file.exists():
-            load_dotenv(env_file, override=False)
-        else:
-            load_dotenv(override=False)
-
-        brain_id = validate_brain_id(
-            os.getenv("SEARCH_BRAIN_ID", DEFAULT_BRAIN_ID) or DEFAULT_BRAIN_ID
-        )
-        return cls(
-            brainapi_url=os.getenv("BRAINAPI_URL", "http://localhost:8000").rstrip("/"),
-            brainpat_token=os.getenv("BRAINPAT_TOKEN", ""),
-            dataset_path=Path(
-                os.getenv("SEARCH_DATASET_PATH", str(DEFAULT_DATASET_PATH))
-            ),
-            runs_dir=Path(os.getenv("BENCH_RUNS_DIR", str(RUNS_DIR))),
-            brain_id=brain_id,
-        )
-
-    def require_brainapi(self) -> None:
-        if not self.brainpat_token:
-            raise SystemExit(
-                "BRAINPAT_TOKEN is required. Copy benchmarks/.env.example to "
-                "benchmarks/.env and set it."
-            )