File size: 8,690 Bytes
734b5b4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 | from __future__ import annotations
from dataclasses import dataclass, field
from pathlib import Path
from typing import Callable
from src.core.models import JobConfig, JobResult, dataclass_to_dict
from src.core.toolbox import PDFToolbox
from src.services.local_logger import LocalLogger
from src.utils.file_utils import ensure_dir, stage_file
@dataclass
class PipelineContext:
job_config: JobConfig
job_dir: Path
log_file: Path
logger: LocalLogger
toolbox: PDFToolbox
current_pdf: Path
stages: list = field(default_factory=list)
errors: list = field(default_factory=list)
state: dict = field(default_factory=dict)
def make_stage_path(self, prefix: str, suffix: str = ".pdf") -> Path:
return stage_file(self.job_dir, prefix, suffix=suffix)
def finish_success(self, final_pdf: Path, manifest: Path) -> JobResult:
self.logger.log("orchestrator", "info", "Job finished", success=True)
return JobResult(
self.job_config.job_id,
True,
final_pdf,
self.log_file,
manifest,
self.stages,
self.errors,
)
def finish_failure(self) -> JobResult:
return JobResult(
self.job_config.job_id,
False,
None,
self.log_file,
self.job_dir / "manifest.json",
self.stages,
self.errors,
)
@dataclass
class PipelineStep:
name: str
action: Callable[[PipelineContext], None]
enabled: Callable[[PipelineContext], bool] | None = None
def should_run(self, context: PipelineContext) -> bool:
if self.enabled is None:
return True
return self.enabled(context)
@dataclass
class PDFPipeline:
name: str
description: str
steps: list[PipelineStep]
def run(self, context: PipelineContext) -> PipelineContext:
context.logger.log(
"orchestrator",
"info",
"Pipeline started",
pipeline=self.name,
job_id=context.job_config.job_id,
)
for step in self.steps:
if step.should_run(context):
step.action(context)
return context
def create_pipeline_context(
job_config: JobConfig, toolbox: PDFToolbox, work_dir: Path
) -> PipelineContext:
job_config.output_dir = ensure_dir(job_config.output_dir)
job_dir = ensure_dir(job_config.output_dir / f"job-{job_config.job_id}")
log_file = job_dir / "pipeline.jsonl"
logger = LocalLogger(log_file)
logger.log("orchestrator", "info", "Job started", job_id=job_config.job_id)
return PipelineContext(
job_config=job_config,
job_dir=job_dir,
log_file=log_file,
logger=logger,
toolbox=toolbox,
current_pdf=job_config.input_pdf,
state={"work_dir": str(work_dir)},
)
def _inspect_step(context: PipelineContext) -> None:
report = context.toolbox.inspect(context.current_pdf)
buckets = context.toolbox.bucket_operations(context.job_config.operations)
context.state["inspection_report"] = report
context.state["operation_buckets"] = buckets
context.stages.append({"stage": "inspect", "report": dataclass_to_dict(report)})
context.logger.log(
"inspect",
"info",
"Done",
ocr_pages=report.ocr_required_pages,
edit_operations=len(buckets.edit),
annotation_operations=len(buckets.annotate),
)
def _needs_ocr(context: PipelineContext) -> bool:
report = context.state.get("inspection_report")
if report is None:
return context.job_config.force_ocr or context.job_config.run_ocr
return (
context.job_config.force_ocr
or context.job_config.run_ocr
or bool(report.ocr_required_pages)
)
def _ocr_step(context: PipelineContext) -> None:
output = context.make_stage_path("02-ocr")
context.current_pdf = context.toolbox.run_ocr(
context.current_pdf, output, context.job_config.ocr_language
)
context.stages.append({"stage": "ocr", "output": str(context.current_pdf)})
context.logger.log("ocr", "info", "Done", output=str(context.current_pdf))
def _has_edit_ops(context: PipelineContext) -> bool:
buckets = context.state.get("operation_buckets")
return bool(buckets and buckets.edit)
def _edit_step(context: PipelineContext) -> None:
buckets = context.state["operation_buckets"]
output = context.make_stage_path("03-edit")
context.current_pdf = context.toolbox.edit_pdf(
context.current_pdf, output, buckets.edit
)
context.stages.append(
{
"stage": "edit",
"output": str(context.current_pdf),
"count": len(buckets.edit),
}
)
context.logger.log("edit", "info", "Done", count=len(buckets.edit))
def _has_annotation_ops(context: PipelineContext) -> bool:
buckets = context.state.get("operation_buckets")
return bool(buckets and buckets.annotate)
def _annotate_step(context: PipelineContext) -> None:
buckets = context.state["operation_buckets"]
output = context.make_stage_path("04-annotate")
context.current_pdf = context.toolbox.annotate_pdf(
context.current_pdf, output, buckets.annotate
)
context.stages.append(
{
"stage": "annotate",
"output": str(context.current_pdf),
"count": len(buckets.annotate),
}
)
context.logger.log("annotate", "info", "Done", count=len(buckets.annotate))
def _validate_step(context: PipelineContext) -> None:
output = context.make_stage_path("05-validated")
context.current_pdf, report = context.toolbox.validate_pdf(
context.current_pdf, output
)
context.state["validation_report"] = report
context.stages.append(
{"stage": "validate", "output": str(context.current_pdf), "report": report}
)
context.logger.log("validate", "info", "Done", **report)
def _export_step(context: PipelineContext) -> None:
final_pdf, manifest = context.toolbox.export_job(
context.current_pdf,
context.job_config,
context.stages,
context.log_file,
)
context.state["final_pdf"] = final_pdf
context.state["manifest"] = manifest
context.stages.append(
{"stage": "export", "output": str(final_pdf), "manifest": str(manifest)}
)
context.logger.log("export", "info", "Done", final=str(final_pdf))
def build_pipeline_catalog(toolbox: PDFToolbox) -> dict[str, PDFPipeline]:
inspect = PipelineStep("inspect", _inspect_step)
ocr = PipelineStep("ocr", _ocr_step, enabled=_needs_ocr)
edit = PipelineStep("edit", _edit_step, enabled=_has_edit_ops)
annotate = PipelineStep("annotate", _annotate_step, enabled=_has_annotation_ops)
validate = PipelineStep("validate", _validate_step)
export = PipelineStep("export", _export_step)
return {
"full_document": PDFPipeline(
name="full_document",
description="Inspects the document, runs OCR if needed, applies edits and annotations, validates, then exports.",
steps=[inspect, ocr, edit, annotate, validate, export],
),
"text_edit": PDFPipeline(
name="text_edit",
description="Runs the edit-oriented document pipeline without annotation steps.",
steps=[inspect, ocr, edit, validate, export],
),
"annotation_review": PDFPipeline(
name="annotation_review",
description="Applies annotation and review operations on top of the current PDF, then validates and exports.",
steps=[inspect, annotate, validate, export],
),
"page_restructure": PDFPipeline(
name="page_restructure",
description="Handles page-level editing operations like rotate, delete, and reorder before validation and export.",
steps=[inspect, edit, validate, export],
),
"ocr_preflight": PDFPipeline(
name="ocr_preflight",
description="Runs inspection and OCR preparation only, then validates and exports an OCR-ready PDF.",
steps=[inspect, ocr, validate, export],
),
}
def list_available_pipeline_names(toolbox: PDFToolbox | None = None) -> list[str]:
resolved_toolbox = toolbox or PDFToolbox()
return list(build_pipeline_catalog(resolved_toolbox).keys())
|