Jesse_Chen
bab0718700
Web export now calls the same full pack as the long skill report and caches an owner-only Markdown download. Appendix failure stays unavailable and does not change the main report status. Co-authored-by: Cursor <cursoragent@cursor.com>
117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
"""Public professional-reference export assembly for the Jyotish API.
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This boundary performs no writing-agent, persistence, billing, or telemetry work.
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It validates the public export request, reuses the handler's one full-reading
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calculation, and delegates packet assembly/rendering to ``jyotish_engine``.
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"""
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from __future__ import annotations
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from datetime import datetime
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from importlib import import_module
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from types import SimpleNamespace
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from typing import Any
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class ProfessionalReportReferenceInputError(ValueError):
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"""The professional-reference request is outside the public contract."""
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def _normalize_format(value: Any) -> str:
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if value is None:
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return "json"
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if not isinstance(value, str):
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raise ProfessionalReportReferenceInputError("format must be json or markdown")
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normalized = value.strip().lower()
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if normalized not in {"json", "markdown"}:
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raise ProfessionalReportReferenceInputError("format must be json or markdown")
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return normalized
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def _normalize_packs(value: Any) -> list[str]:
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if value is None:
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return []
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if isinstance(value, str):
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raw_items = value.split(",")
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elif isinstance(value, list):
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if any(not isinstance(item, str) for item in value):
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raise ProfessionalReportReferenceInputError("packs must contain only strings")
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raw_items = value
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else:
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raise ProfessionalReportReferenceInputError("packs must be a string or array of strings")
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selected: list[str] = []
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seen: set[str] = set()
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for item in raw_items:
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pack_id = item.strip()
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if pack_id and pack_id not in seen:
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selected.append(pack_id)
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seen.add(pack_id)
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return selected
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def _load_engine():
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try:
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return import_module("scripts.jyotish_engine")
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except ModuleNotFoundError: # pragma: no cover - direct scripts/ execution path
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return import_module("jyotish_engine")
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def _export_args(birth: dict[str, Any]) -> SimpleNamespace:
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today = birth.get("today") or datetime.now().strftime("%Y-%m-%d")
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raw_target = birth.get("target_year")
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if raw_target in (None, ""):
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target_year = int(str(today)[:4])
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else:
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target_year = int(raw_target)
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raw_age = birth.get("age")
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if raw_age in (None, ""):
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try:
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age = int(target_year) - int(birth["year"])
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except (TypeError, ValueError, KeyError):
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age = None
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else:
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age = int(raw_age)
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payload = {
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**birth,
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"hour": int(birth["hour"]),
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"minute": int(birth["minute"]),
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"second": int(birth.get("second", 0) or 0),
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"today": today,
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"target_year": target_year,
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"age": age,
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"visual_chart_observations": birth.get("visual_chart_observations"),
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"startrack_language_bridge": bool(birth.get("startrack_language_bridge")),
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}
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return SimpleNamespace(**payload)
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def build_professional_report_reference(handler, body: dict[str, Any], *, engine=None) -> dict[str, Any]:
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"""Build one JSON or Markdown response from one reused full-reading result."""
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if not isinstance(body, dict):
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raise ProfessionalReportReferenceInputError("request body must be an object")
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output_format = _normalize_format(body.get("format"))
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packs = _normalize_packs(body.get("packs"))
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birth = handler._high_rigor_birth_payload(body)
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full_reading = handler._compute_full_reading_for_thematic(birth)
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resolved_engine = engine or _load_engine()
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try:
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packet = resolved_engine.build_professional_report_reference_packet(
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full_reading,
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_export_args(birth),
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packs,
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)
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except ValueError as exc:
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raise ProfessionalReportReferenceInputError(str(exc)) from exc
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if output_format == "markdown":
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return {
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"format": "markdown",
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"markdown": resolved_engine.render_pl9_markdown(packet),
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}
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return {
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"format": "json",
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"report": packet,
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}
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