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e726170 dc54127 e726170 5ab38b4 e726170 5ab38b4 e726170 dc54127 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 | """Single-article MVP classification orchestration."""
from __future__ import annotations
import logging
import time
from datetime import datetime, timezone
from typing import Any
from gcmd_classifier.classification import (
ClassificationCandidate,
TermBranchSeed,
candidate_from_terminal_outcome,
candidate_from_topic_stop,
remove_redundant_classifications,
route_terms,
route_topics,
validate_candidates,
)
from gcmd_classifier.config import ModelSettings
from gcmd_classifier.llm.base import ModelClient
from gcmd_classifier.logging_config import get_logger, log_event
from gcmd_classifier.models import (
ArticleClassificationOutcome,
ArticleProcessingStatus,
ArticleRecord,
ArticleResult,
ClassificationRecord,
OutputError,
OutputWarning,
ProcessingMetadata,
ReviewStatus,
)
from gcmd_classifier.persistence.cache import article_fingerprint, configuration_hash
from gcmd_classifier.pipeline.review import flag_review_risk
from gcmd_classifier.vocabulary.index import VocabularyIndex
APPLICATION_VERSION = "0.1.0"
def classify_article(
*,
article: ArticleRecord,
vocabulary: VocabularyIndex,
model_client: ModelClient,
settings: ModelSettings,
run_id: str | None = None,
application_version: str = APPLICATION_VERSION,
relevant_config: dict[str, Any] | None = None,
logger: logging.Logger | None = None,
) -> ArticleResult:
"""Classify one valid article through the current MVP pipeline."""
active_logger = logger or get_logger(__name__)
started_at = _now_iso()
started = time.perf_counter()
model_calls_before = _model_request_count(model_client)
log_event(active_logger, "article_started", DOI=article.DOI, stage="pipeline")
candidates: list[ClassificationCandidate] = []
warnings: list[OutputWarning] = []
errors: list[OutputError] = []
no_classification_reason: str | None = None
try:
topic_result = route_topics(
article=article,
vocabulary=vocabulary,
model_client=model_client,
settings=settings,
)
if topic_result.is_no_topic:
no_classification_reason = (
topic_result.no_selection_reason or "No GCMD Topic was supported by the article."
)
for topic_branch in topic_result.branches:
try:
term_result = route_terms(
article=article,
topic_branch=topic_branch,
vocabulary=vocabulary,
model_client=model_client,
settings=settings,
)
except Exception as exc:
errors.append(_error_from_exception(exc, stage="term_routing", DOI=article.DOI))
log_event(
active_logger,
"branch_failed",
DOI=article.DOI,
stage="term_routing",
branch_id=topic_branch.branch_id,
error_code=exc.__class__.__name__,
)
continue
if term_result.stop_at_topic is not None:
candidates.append(candidate_from_topic_stop(term_result.stop_at_topic))
for term_branch in term_result.term_branches:
_process_term_branch(
article=article,
term_branch=term_branch,
vocabulary=vocabulary,
model_client=model_client,
settings=settings,
candidates=candidates,
warnings=warnings,
errors=errors,
logger=active_logger,
)
except Exception as exc:
errors.append(_error_from_exception(exc, stage="topic_routing", DOI=article.DOI))
log_event(
active_logger,
"article_failed",
DOI=article.DOI,
stage="topic_routing",
error_code=exc.__class__.__name__,
)
validation_result = validate_candidates(candidates, vocabulary)
for rejected in validation_result.rejected:
errors.extend(rejected.deterministic_validation.errors)
redundancy_result = remove_redundant_classifications(validation_result.accepted, vocabulary)
warnings.extend(redundancy_result.warnings)
classifications = flag_review_risk(redundancy_result.classifications)
result = _article_result(
article=article,
classifications=classifications,
warnings=tuple(warnings),
errors=tuple(errors),
no_classification_reason=no_classification_reason,
started_at=started_at,
duration_seconds=time.perf_counter() - started,
model_calls=_model_calls_used(model_client, model_calls_before),
run_id=run_id,
vocabulary=vocabulary,
settings=settings,
application_version=application_version,
relevant_config=relevant_config,
)
log_event(
active_logger,
"article_finished",
DOI=article.DOI,
stage="pipeline",
processing_status=result.processing_status.value,
classification_outcome=None
if result.classification_outcome is None
else result.classification_outcome.value,
classifications=len(result.classifications),
errors=len(result.errors),
)
return result
def _process_term_branch(
*,
article: ArticleRecord,
term_branch: TermBranchSeed,
vocabulary: VocabularyIndex,
model_client: ModelClient,
settings: ModelSettings,
candidates: list[ClassificationCandidate],
warnings: list[OutputWarning],
errors: list[OutputError],
logger: logging.Logger,
) -> None:
from gcmd_classifier.classification import descend_variables
try:
descent_result = descend_variables(
article=article,
term_branch=term_branch,
vocabulary=vocabulary,
model_client=model_client,
settings=settings,
)
except Exception as exc:
errors.append(_error_from_exception(exc, stage="variable_descent", DOI=article.DOI))
log_event(
logger,
"branch_failed",
DOI=article.DOI,
stage="variable_descent",
branch_id=term_branch.branch_id,
error_code=exc.__class__.__name__,
)
return
candidates.extend(
candidate_from_terminal_outcome(terminal) for terminal in descent_result.terminals
)
warnings.extend(descent_result.warnings)
errors.extend(descent_result.diagnostics)
for branch_error in descent_result.errors:
errors.append(
OutputError(
code=branch_error.code,
message=branch_error.message,
stage="variable_descent",
DOI=article.DOI,
details={
"branch_id": branch_error.branch_id,
"parent_branch_id": branch_error.parent_branch_id,
"parent_uuid": branch_error.parent_uuid,
"parent_level": branch_error.parent_level,
},
)
)
def _article_result(
*,
article: ArticleRecord,
classifications: tuple[ClassificationRecord, ...],
warnings: tuple[OutputWarning, ...],
errors: tuple[OutputError, ...],
no_classification_reason: str | None,
started_at: str,
duration_seconds: float,
model_calls: int | None,
run_id: str | None,
vocabulary: VocabularyIndex,
settings: ModelSettings,
application_version: str,
relevant_config: dict[str, Any] | None,
) -> ArticleResult:
metadata = _metadata(
article=article,
started_at=started_at,
duration_seconds=duration_seconds,
model_calls=model_calls,
run_id=run_id,
vocabulary=vocabulary,
settings=settings,
application_version=application_version,
relevant_config=relevant_config,
)
if classifications:
status = ArticleProcessingStatus.PARTIAL if errors else ArticleProcessingStatus.COMPLETED
return ArticleResult(
DOI=article.DOI,
Title=article.Title,
Year=article.Year,
Abstract=article.Abstract,
processing_status=status,
classification_outcome=ArticleClassificationOutcome.CLASSIFIED,
classifications=classifications,
review_status=ReviewStatus.NOT_REQUIRED,
warnings=warnings,
errors=errors,
processing_metadata=metadata,
)
if errors:
return ArticleResult(
DOI=article.DOI,
Title=article.Title,
Year=article.Year,
Abstract=article.Abstract,
processing_status=ArticleProcessingStatus.FAILED,
classification_outcome=None,
classifications=(),
review_status=ReviewStatus.NOT_REQUIRED,
warnings=warnings,
errors=errors,
processing_metadata=metadata,
)
return ArticleResult(
DOI=article.DOI,
Title=article.Title,
Year=article.Year,
Abstract=article.Abstract,
processing_status=ArticleProcessingStatus.COMPLETED,
classification_outcome=ArticleClassificationOutcome.NOT_CLASSIFIED,
classifications=(),
no_classification_reason=no_classification_reason
or "No defensible GCMD classification was supported.",
review_status=ReviewStatus.NOT_REQUIRED,
warnings=warnings,
errors=errors,
processing_metadata=metadata,
)
def failed_article_result(
*,
article: ArticleRecord,
error: OutputError,
vocabulary: VocabularyIndex,
settings: ModelSettings,
run_id: str | None = None,
application_version: str = APPLICATION_VERSION,
relevant_config: dict[str, Any] | None = None,
) -> ArticleResult:
"""Build and return a persisted failed article result for batch-level failures."""
started_at = _now_iso()
return ArticleResult(
DOI=article.DOI,
Title=article.Title,
Year=article.Year,
Abstract=article.Abstract,
processing_status=ArticleProcessingStatus.FAILED,
classification_outcome=None,
classifications=(),
review_status=ReviewStatus.NOT_REQUIRED,
errors=(error,),
processing_metadata=_metadata(
article=article,
started_at=started_at,
duration_seconds=0.0,
model_calls=None,
run_id=run_id,
vocabulary=vocabulary,
settings=settings,
application_version=application_version,
relevant_config=relevant_config,
),
)
def _metadata(
*,
article: ArticleRecord,
started_at: str,
duration_seconds: float,
model_calls: int | None,
run_id: str | None,
vocabulary: VocabularyIndex,
settings: ModelSettings,
application_version: str,
relevant_config: dict[str, Any] | None,
) -> ProcessingMetadata:
completed_at = _now_iso()
return ProcessingMetadata(
run_id=run_id,
started_at=started_at,
completed_at=completed_at,
processed_at=completed_at,
model_provider=settings.provider,
model_name=settings.model_name,
model_parameters={
"temperature": settings.temperature,
"timeout_seconds": settings.timeout_seconds,
"max_retries": settings.max_retries,
},
prompt_versions={
"topic": settings.prompt_version_topic,
"term": settings.prompt_version_term,
"variable": settings.prompt_version_variable,
},
vocabulary_version=vocabulary.vocabulary_version,
vocabulary_hash=vocabulary.vocabulary_version,
application_version=application_version,
configuration_hash=configuration_hash(relevant_config),
article_fingerprint=article_fingerprint(article),
cache_used=False,
processing_time_seconds=duration_seconds,
model_calls=model_calls,
title_available=bool(article.Title),
abstract_available=bool(article.Abstract),
)
def _error_from_exception(exc: Exception, *, stage: str, DOI: str | None = None) -> OutputError:
retry_count = getattr(exc, "retry_count", None)
return OutputError(
code=exc.__class__.__name__,
message=str(exc),
stage=stage,
DOI=DOI,
retry_count=retry_count if isinstance(retry_count, int) else None,
)
def _model_request_count(model_client: ModelClient) -> int | None:
requests = getattr(model_client, "requests", None)
return len(requests) if isinstance(requests, list) else None
def _model_calls_used(model_client: ModelClient, before: int | None) -> int | None:
after = _model_request_count(model_client)
if before is None or after is None:
return None
return after - before
def _now_iso() -> str:
return datetime.now(timezone.utc).isoformat() # noqa: UP017
|