18ce7e57cf
- Replace 6 compound Likert questions with 12 atomic ones grouped by dimension (syntax, expressiveness, data/IO, errors, overall); drop free-form question. Responses now stored as ints, not strings. - Back-compat layer maps legacy keys to new dimensions so existing results still render. - Parallelize run-all with ThreadPoolExecutor (configurable workers) and add a thread-safe min-request-interval rate limiter to the Anthropic provider. - Add new tasks: path_normalizer, todo_manager, currency_converter, locale_weather_url, network_info_parser, url_normalizer.
42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
from __future__ import annotations
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import tomllib
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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@dataclass
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class Config:
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lush_binary: Path
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max_retries: int = 3
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timeout_seconds: float = 10.0
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normalize_whitespace: bool = True
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output_dir: Path = Path("results")
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max_workers: int = 4
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provider_configs: dict[str, dict[str, Any]] = field(default_factory=dict)
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@classmethod
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def load(cls, path: Path | None = None) -> Config:
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if path is None:
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path = Path(__file__).parent.parent / "config.toml"
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raw = tomllib.loads(path.read_text())
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lush = raw.get("lush", {})
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agent = raw.get("agent", {})
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results = raw.get("results", {})
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# Collect provider configs (any top-level section not in known keys)
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known_sections = {"lush", "agent", "results"}
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provider_configs = {k: v for k, v in raw.items() if k not in known_sections and isinstance(v, dict)}
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return cls(
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lush_binary=Path(lush["binary"]),
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max_retries=agent.get("max_retries", 3),
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timeout_seconds=agent.get("timeout_seconds", 10.0),
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normalize_whitespace=agent.get("normalize_whitespace", True),
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output_dir=Path(results.get("output_dir", "results")),
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max_workers=agent.get("max_workers", 4),
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provider_configs=provider_configs,
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)
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