| """Configuration dataclasses for pipeline stages.""" |
|
|
| from __future__ import annotations |
|
|
| import logging |
| import os |
| from dataclasses import dataclass, field |
| from pathlib import Path |
| from typing import Any, Dict, Optional, Type, TypeVar |
|
|
| LOGGER = logging.getLogger(__name__) |
|
|
| T = TypeVar("T") |
|
|
|
|
| def env(key: str, default: T = None, cast: Type[T] = str) -> T: |
| """Read environment variable with type casting.""" |
| raw = os.environ.get(key) |
| if raw is None: |
| return default |
| try: |
| return cast(raw) |
| except (TypeError, ValueError): |
| LOGGER.warning("Invalid %s=%s, using default=%s", key, raw, default) |
| return default |
|
|
|
|
| @dataclass |
| class FigureMetadata: |
| """Metadata for an extracted figure (image stored in dataset, not as file).""" |
|
|
| figure_id: str |
| label: str |
| bounding_box_pixels: Dict[str, int] |
| description: Optional[str] = None |
|
|
|
|
| @dataclass |
| class InferenceSettings: |
| """Settings for batch inference.""" |
|
|
| batch_size: int = 4 |
| max_concurrency: int = 4 |
| request_timeout: int = 120 |
| max_retries: int = 3 |
| retry_backoff: float = 2.0 |
|
|
| @classmethod |
| def from_env(cls, prefix: str = "") -> InferenceSettings: |
| """Load from environment with optional prefix (e.g., 'EXTRACT_').""" |
| p = f"{prefix}_" if prefix else "" |
| return cls( |
| batch_size=max(1, env(f"{p}BATCH_SIZE", 4, int)), |
| max_concurrency=max(1, env(f"{p}MAX_CONCURRENCY", 4, int)), |
| request_timeout=max(1, env(f"{p}REQUEST_TIMEOUT", 120, int)), |
| max_retries=max(0, env(f"{p}MAX_RETRIES", 3, int)), |
| retry_backoff=max(0.1, env(f"{p}RETRY_BACKOFF", 2.0, float)), |
| ) |
|
|
|
|
| @dataclass |
| class HubSettings: |
| """Settings for HuggingFace Hub upload.""" |
|
|
| repo_id: Optional[str] = None |
| path_in_repo: str = "" |
| branch: Optional[str] = None |
| commit_message: Optional[str] = None |
|
|
| @classmethod |
| def from_env(cls, prefix: str = "HF") -> HubSettings: |
| """Load from environment with prefix (e.g., 'HF_' -> HF_REPO_ID).""" |
| p = f"{prefix}_" if prefix else "" |
| return cls( |
| repo_id=env(f"{p}REPO_ID") or env(f"{p}REPO"), |
| path_in_repo=env(f"{p}PATH_IN_REPO", ""), |
| branch=env(f"{p}BRANCH"), |
| commit_message=env(f"{p}COMMIT_MESSAGE"), |
| ) |
|
|
|
|
| @dataclass |
| class ExtractSettings: |
| """Settings for the extract stage.""" |
|
|
| dataset_name: str |
| dataset_config: str |
| dataset_split: str |
| output_dir: Path |
| client: Any |
| prompt: str = "<image>\n<|grounding|>Convert this document to Markdown." |
| max_tokens: int = 2048 |
| temperature: float = 0.0 |
| max_samples: Optional[int] = None |
| stream_dataset: bool = True |
| inference: InferenceSettings = field(default_factory=InferenceSettings) |
| hub: HubSettings = field(default_factory=HubSettings) |
|
|
| @classmethod |
| def from_env(cls, client: Any) -> ExtractSettings: |
| """Load settings from environment variables.""" |
| return cls( |
| dataset_name=env("DATASET_NAME", "HuggingFaceM4/FineVision"), |
| dataset_config=env("DATASET_CONFIG", "olmOCR-mix-0225-documents"), |
| dataset_split=env("DATASET_SPLIT", "train"), |
| output_dir=Path(env("OUTPUT_DIR", "./outputs/extract")), |
| client=client, |
| prompt=env( |
| "DOC_PROMPT", "<image>\n<|grounding|>Convert this document to Markdown." |
| ), |
| max_tokens=env("DOC_MAX_TOKENS", 2048, int), |
| temperature=env("DOC_TEMPERATURE", 0.0, float), |
| max_samples=env("MAX_SAMPLES", None, int), |
| stream_dataset=env("STREAM_DATASET", "true").lower() == "true", |
| inference=InferenceSettings.from_env("EXTRACT"), |
| hub=HubSettings.from_env("HF"), |
| ) |
|
|
|
|
| @dataclass |
| class DescribeSettings: |
| """Settings for the describe stage.""" |
|
|
| output_dir: Path |
| client: Any |
| source_repo_id: Optional[str] = None |
| prompt: str = "<image>\nDescribe this image in detail" |
| max_tokens: int = 512 |
| temperature: float = 0.0 |
| inference: InferenceSettings = field(default_factory=InferenceSettings) |
| hub: HubSettings = field(default_factory=HubSettings) |
|
|
| @classmethod |
| def from_env(cls, client: Any) -> DescribeSettings: |
| """Load settings from environment variables.""" |
| return cls( |
| output_dir=Path(env("OUTPUT_DIR", "./outputs/describe")), |
| client=client, |
| source_repo_id=env("SOURCE_REPO_ID") or env("HF_REPO_ID"), |
| prompt=env("FIGURE_PROMPT", "<image>\nDescribe this image in detail"), |
| max_tokens=env("FIGURE_MAX_TOKENS", 512, int), |
| temperature=env("FIGURE_TEMPERATURE", 0.0, float), |
| inference=InferenceSettings.from_env("DESCRIBE"), |
| hub=HubSettings.from_env("HF"), |
| ) |
|
|
|
|
| @dataclass |
| class AssembleSettings: |
| """Settings for the assemble stage.""" |
|
|
| source_repo_id: Optional[str] = None |
| hub: HubSettings = field(default_factory=HubSettings) |
|
|
| @classmethod |
| def from_env(cls) -> AssembleSettings: |
| """Load settings from environment variables.""" |
| return cls( |
| source_repo_id=env("SOURCE_REPO_ID") or env("HF_REPO_ID"), |
| hub=HubSettings.from_env("HF"), |
| ) |
|
|
