"""Procesamiento de ingestas individuales desde la app desktop."""
from __future__ import annotations

import logging
from typing import Any

from domain.normalizer import normalize_to_schema
from domain.profiles import get_profile
from domain.prompts import PromptBuilder
from domain.service import InvoiceProcessingService
from infrastructure.database import ExtractionRow, Task, utcnow
from infrastructure.serialization import flatten_extraction_result
from sqlalchemy.orm import Session

logger = logging.getLogger(__name__)


def _paths_for_type(fields: list[str], doc_type: str | None) -> list[str]:
  if not doc_type:
    return list(fields or [])
  prefix = f"{doc_type}/"
  return [path.split("/", 1)[1] for path in fields if path.startswith(prefix)]


def _expected_doc_types_for_radicado(request: dict[str, Any], radicado: str) -> set[str]:
  expected: set[str] = set()
  for item in request.get("documents") or []:
    if str(item.get("radicado") or "") != radicado:
      continue
    doc_type = str(item.get("doc_type") or item.get("docType") or "").strip()
    if doc_type:
      expected.add(doc_type)
  return expected


def _finalize_radicado_if_ready(
  session: Session,
  *,
  task: Task,
  batch_id: str,
  radicado: str,
  request: dict[str, Any],
  fields: list[str],
  alias_map: dict[str, str],
) -> bool:
  partials = dict((task.result or {}).get("partials") or {})
  radicado_partials = dict(partials.get(radicado) or {})
  expected = _expected_doc_types_for_radicado(request, radicado)
  if expected and not expected.issubset(set(radicado_partials.keys())):
    return False

  fused: dict[str, Any] = {"radicado": radicado, **radicado_partials}
  source_pdf = None
  for item in request.get("documents") or []:
    if str(item.get("radicado") or "") == radicado:
      source_pdf = item.get("filename")
      break
  if source_pdf:
    fused["_source_pdf"] = source_pdf

  row_index = int((task.result or {}).get("row_count") or 0)
  for row in flatten_extraction_result(fused, fields, alias_map):
    row_index += 1
    session.add(
      ExtractionRow(
        batch_id=batch_id,
        radicado=radicado,
        source_pdf=source_pdf,
        row_index=row_index,
        row_json=row,
        raw_json=fused,
      )
    )

  partials.pop(radicado, None)
  result = dict(task.result or {})
  result["partials"] = partials
  result["row_count"] = row_index
  result["processed"] = int(result.get("processed") or 0) + 1
  task.result = result
  task.updated_at = utcnow()
  return True


def _service_for_model(base_service: InvoiceProcessingService, model: str | None) -> InvoiceProcessingService:
  """Devuelve un servicio con el modelo solicitado; reutiliza base_service si coincide."""
  if not model:
    return base_service
  current_model = getattr(base_service.extractor, "model", None)
  if current_model == model:
    return base_service
  from domain.strategies import OpenAICompatibleExtractor
  from domain.batch_processor import BatchProcessor
  from domain.estimator import Estimator
  extractor = OpenAICompatibleExtractor(model=model)
  return InvoiceProcessingService(
    extractor,
    batch_processor_factory=lambda s: BatchProcessor(s),
    estimator_factory=lambda s: Estimator(s),
  )


def process_desktop_ingest(
  service: InvoiceProcessingService,
  session: Session,
  *,
  task: Task,
  batch_id: str,
  temp_path: str,
  radicado: str,
  filename: str,
  doc_type: str | None,
  instruction: str | None,
  tiff_page_range: tuple[int, int] | None,
  model: str | None = None,
) -> dict[str, Any]:
  service = _service_for_model(service, model)
  request = dict(task.request or {})
  fields = list(request.get("fields") or [])
  alias_map = dict(request.get("alias_map") or {})
  structure_mode = str(request.get("structure_mode") or "radicados")
  doc_types = list(request.get("doc_types") or [])
  prof = get_profile("invoice")

  selected_paths = _paths_for_type(fields, doc_type if structure_mode == "radicados" and doc_types else None)
  if doc_type and structure_mode == "radicados" and doc_types:
    try:
      prompt = PromptBuilder.build_for_type(doc_type, selected_paths, {}, profile_name=prof.get("name", "invoice"))
    except Exception:
      prompt = PromptBuilder.build(selected_paths, {}, profile_name=prof.get("name", "invoice"))
  else:
    prompt = instruction or PromptBuilder.build(selected_paths, {}, profile_name=prof.get("name", "invoice"))

  data, _usage = service.extract_full_from_pdf(
    temp_path,
    instruction=prompt,
    tiff_page_range=tiff_page_range,
  )
  raw_data = data if isinstance(data, dict) else {"data": data}
  if isinstance(data, dict):
    data["radicado"] = radicado
  else:
    data = {"radicado": radicado, "data": data}

  norm = normalize_to_schema(
    data,
    paths=selected_paths,
    profile_name=prof.get("name", "invoice"),
  )
  normalized_obj = data
  if isinstance(norm, dict):
    normalized_obj = norm.get("normalized") or data

  result = dict(task.result or {})
  errors = list(result.get("errors") or [])

  if structure_mode == "radicados" and doc_types and doc_type:
    partials = dict(result.get("partials") or {})
    radicado_partials = dict(partials.get(radicado) or {})
    radicado_partials[doc_type] = normalized_obj or {}
    partials[radicado] = radicado_partials
    result["partials"] = partials
    task.result = result
    session.flush()
    finalized = _finalize_radicado_if_ready(
      session,
      task=task,
      batch_id=batch_id,
      radicado=radicado,
      request=request,
      fields=fields,
      alias_map=alias_map,
    )
    return {
      "radicado": radicado,
      "filename": filename,
      "doc_type": doc_type,
      "finalized": finalized,
      "processed": int((task.result or {}).get("processed") or 0),
      "total": int((task.result or {}).get("total") or 0),
    }

  fused = {"radicado": radicado, "_source_pdf": filename}
  if doc_type:
    fused[doc_type] = normalized_obj or {}
  else:
    fused.update(normalized_obj if isinstance(normalized_obj, dict) else {"data": normalized_obj})

  row_index = int(result.get("row_count") or 0)
  for row in flatten_extraction_result(fused, fields, alias_map):
    row_index += 1
    session.add(
      ExtractionRow(
        batch_id=batch_id,
        radicado=radicado,
        source_pdf=filename,
        row_index=row_index,
        row_json=row,
        raw_json=fused,
      )
    )

  result["row_count"] = row_index
  result["processed"] = int(result.get("processed") or 0) + 1
  task.result = result
  task.updated_at = utcnow()
  session.flush()

  return {
    "radicado": radicado,
    "filename": filename,
    "doc_type": doc_type,
    "finalized": True,
    "processed": int(result.get("processed") or 0),
    "total": int(result.get("total") or 0),
  }


def mark_task_completed_if_done(session: Session, task: Task, batch_id: str) -> None:
  result = dict(task.result or {})
  processed = int(result.get("processed") or 0)
  total = int(result.get("total") or 0)
  partials = dict(result.get("partials") or {})
  if processed < total or partials:
    return

  from infrastructure.database import ExtractionBatch

  task.status = "completed"
  task.finished_at = utcnow()
  task.updated_at = utcnow()
  batch = session.get(ExtractionBatch, batch_id)
  if batch is not None:
    batch.status = "completed"
    batch.updated_at = utcnow()