Initial video AI analysis project
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yangyl
278
video_ai_analysis_poc/config.py
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278
video_ai_analysis_poc/config.py
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from __future__ import annotations
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import ast
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from pathlib import Path
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from typing import Any
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from .paths import resolve_path, validate_output_dir
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DEFAULT_CONFIG_PATH = Path(__file__).resolve().parent.parent / "config" / "local_batch.yaml"
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def load_config(
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config_path: str | Path = DEFAULT_CONFIG_PATH,
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*,
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input_dir: str | Path | None = None,
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output_dir: str | Path | None = None,
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) -> dict[str, Any]:
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path = Path(config_path).expanduser().resolve(strict=False)
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raw_config = _parse_simple_yaml(path)
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config = _with_defaults(raw_config)
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base_dir = path.parent.parent if path.parent.name == "config" else path.parent
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if input_dir is not None:
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config["input"]["dir"] = str(input_dir)
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if output_dir is not None:
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config["output"]["dir"] = str(output_dir)
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config["input"]["dir"] = str(resolve_path(config["input"]["dir"], base_dir=base_dir))
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config["output"]["dir"] = str(
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resolve_path(config["output"]["dir"], base_dir=base_dir)
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)
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validate_output_dir(config["input"]["dir"], config["output"]["dir"])
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extensions = config["input"].get("extensions", [])
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config["input"]["extensions"] = _normalize_extensions(extensions)
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config["input"]["recursive"] = bool(config["input"].get("recursive", True))
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config.setdefault("ffprobe", {})
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config["ffprobe"]["timeout_seconds"] = int(
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config["ffprobe"].get("timeout_seconds", 30)
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)
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return config
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def _with_defaults(config: dict[str, Any]) -> dict[str, Any]:
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merged: dict[str, Any] = {
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"input": {
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"dir": "./videos",
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"recursive": True,
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"extensions": [".mp4", ".mov", ".mkv", ".avi", ".flv", ".ts", ".m4v"],
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},
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"output": {
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"dir": "./outputs/local-batch",
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"overwrite": False,
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"resume": True,
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"keep_frames": True,
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},
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"source": {"mode": "local"},
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"hik_cloud": {
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"api_base_url": "https://api2.hik-cloud.com",
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"download_path": "/v1/carrier/cstorage/open/play/download",
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"access_token": None,
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"access_token_env": "HIK_CLOUD_ACCESS_TOKEN",
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"devices": [],
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"time_ranges": [],
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"chunk_seconds": 600,
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"timeout_seconds": 60,
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"download_timeout_seconds": 600,
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},
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"ffprobe": {"timeout_seconds": 30},
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"ffmpeg": {
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"prefer_nvdec": True,
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"allow_cpu_fallback": False,
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"hwaccel": "cuda",
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"codec_decoders": {"h264": "h264_cuvid", "hevc": "hevc_cuvid"},
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"frame_fps": 1,
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"frame_width": 640,
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"jpeg_quality": 4,
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"timeout_seconds_per_video": 3600,
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},
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"clip": {
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"length_seconds": 10,
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"stride_seconds": 10,
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"frames_per_clip": 8,
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"min_frames_per_clip": 4,
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},
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"vlm": {
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"api_base_url": "http://localhost:8679",
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"chat_completions_path": "/v1/chat/completions",
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"model": "memai-zhengxin-v3-20260413",
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"timeout_seconds": 120,
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"max_tokens": 512,
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"temperature": 0,
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"batch_size": 1,
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"image_transport": "data_uri",
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"retries": 1,
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},
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"prompt": {
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"system": "You are a store video analysis assistant. Return strict JSON only.",
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"user": "Analyze this clip. Return events and screen_time. If no event, return events: [].",
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},
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"schema": {
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"version": "local-batch-v1",
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"event_types": [
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"customer_enter",
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"customer_leave",
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"queue_detected",
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"staff_absent",
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"staff_present",
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"area_crowded",
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"abnormal_behavior",
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"unknown",
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],
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"require_strict_json": True,
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"parse_retry": 1,
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"merge_gap_seconds": 30,
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},
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"runtime": {"timezone": "Asia/Shanghai", "log_level": "INFO"},
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}
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for section, values in config.items():
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if isinstance(values, dict) and isinstance(merged.get(section), dict):
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merged[section].update(values)
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else:
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merged[section] = values
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return merged
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def _normalize_extensions(extensions: list[str]) -> list[str]:
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normalized = []
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for extension in extensions:
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value = str(extension).lower()
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if not value.startswith("."):
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value = f".{value}"
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normalized.append(value)
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return normalized
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def _parse_simple_yaml(path: Path) -> dict[str, Any]:
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if not path.exists():
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raise FileNotFoundError(f"config file not found: {path}")
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root: dict[str, Any] = {}
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stack: list[tuple[int, dict[str, Any] | list[Any]]] = [(-1, root)]
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lines = path.read_text(encoding="utf-8").splitlines()
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index = 0
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while index < len(lines):
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raw_line = lines[index].rstrip()
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stripped = raw_line.strip()
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if not stripped or raw_line.lstrip().startswith("#"):
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index += 1
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continue
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indent = len(raw_line) - len(raw_line.lstrip(" "))
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while indent <= stack[-1][0]:
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stack.pop()
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parent = stack[-1][1]
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if stripped.startswith("- "):
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if not isinstance(parent, list):
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raise ValueError(f"list item without list parent: {raw_line}")
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item = stripped[2:].strip()
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if ":" in item:
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key, value = item.split(":", 1)
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mapping: dict[str, Any] = {}
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parent.append(mapping)
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key = key.strip()
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value = value.strip()
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if not value:
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next_stripped = _next_stripped(lines, index)
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child: dict[str, Any] | list[Any]
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child = [] if next_stripped and next_stripped.startswith("- ") else {}
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mapping[key] = child
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stack.append((indent, mapping))
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stack.append((indent + 2, child))
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else:
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mapping[key] = _parse_scalar(value)
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stack.append((indent, mapping))
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else:
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parent.append(_parse_scalar(item))
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index += 1
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continue
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if not isinstance(parent, dict):
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raise ValueError(f"mapping entry inside list is not supported: {raw_line}")
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if ":" not in stripped:
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raise ValueError(f"unsupported config line: {raw_line}")
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key, value = stripped.split(":", 1)
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key = key.strip()
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value = value.strip()
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if _is_block_scalar(value):
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parent[key], index = _parse_block_scalar(lines, index, indent, value)
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continue
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if not value:
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next_stripped = _next_stripped(lines, index)
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child: dict[str, Any] | list[Any]
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child = [] if next_stripped and next_stripped.startswith("- ") else {}
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parent[key] = child
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stack.append((indent, child))
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else:
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parent[key] = _parse_scalar(value)
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index += 1
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return root
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def _next_stripped(lines: list[str], current_index: int) -> str | None:
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for raw_line in lines[current_index + 1 :]:
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stripped = raw_line.strip()
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if stripped and not raw_line.lstrip().startswith("#"):
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return stripped
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return None
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def _is_block_scalar(value: str) -> bool:
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return value in {">", ">-", "|", "|-"}
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def _parse_block_scalar(
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lines: list[str],
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start_index: int,
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parent_indent: int,
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marker: str,
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) -> tuple[str, int]:
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content_lines: list[str] = []
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content_indent: int | None = None
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index = start_index + 1
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while index < len(lines):
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raw_line = lines[index].rstrip()
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stripped = raw_line.strip()
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if not stripped:
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content_lines.append("")
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index += 1
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continue
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indent = len(raw_line) - len(raw_line.lstrip(" "))
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if indent <= parent_indent:
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break
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if content_indent is None:
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content_indent = indent
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content_lines.append(raw_line[content_indent:])
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index += 1
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if marker.endswith("-"):
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while content_lines and content_lines[-1] == "":
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content_lines.pop()
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return "\n".join(content_lines), index
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def _parse_scalar(value: str) -> Any:
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lower = value.lower()
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if lower == "true":
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return True
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if lower == "false":
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return False
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if lower in {"null", "none"}:
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return None
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if value.startswith("[") and value.endswith("]"):
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parsed = ast.literal_eval(value)
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if not isinstance(parsed, list):
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raise ValueError(f"expected list value: {value}")
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return parsed
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if (value.startswith('"') and value.endswith('"')) or (
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value.startswith("'") and value.endswith("'")
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):
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return ast.literal_eval(value)
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try:
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return int(value)
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except ValueError:
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pass
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try:
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return float(value)
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except ValueError:
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return value
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