Add jyotish oracle evidence calibration gate
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732642856
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#!/usr/bin/env python3
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"""Generate a repeatable external-oracle collection queue.
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This script turns oracle template rows into executable data-collection tasks.
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It does not compute Jyotish values and must not be used to tune production
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constants. A task is only calibration-ready after external target fields are
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filled and the status is promoted to external_verified.
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"""
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from __future__ import annotations
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import argparse
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import json
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import os
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from typing import Any
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ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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SOURCE_GUIDANCE = {
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"longitude": {
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"preferred_sources": ["VedAstro HTTP API", "JHora manual screenshot", "PyJHora black-box output"],
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"steps": [
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"Set the exact birth data, ayanamsa, node mode and timezone in the external tool.",
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"Record sidereal longitude in absolute 0-360 degree format and sign-local DMS format.",
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"Attach source metadata: tool name, version or URL, ayanamsa, node mode and capture date.",
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],
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"promotion_criteria": [
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"External source metadata is present.",
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"A numeric sidereal longitude target is filled.",
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"The value did not come from this repository's local engine output.",
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],
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},
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"dasha": {
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"preferred_sources": ["JHora manual screenshot", "PyJHora black-box output", "secondary VedAstro API check"],
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"steps": [
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"Capture Moon longitude, nakshatra, pada and Vimshottari start-boundary settings.",
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"Record Mahadasha and Antardasha boundary dates in ISO date format.",
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"Keep year-length, timezone and daylight-saving assumptions with the row.",
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],
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"promotion_criteria": [
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"At least one external Dasha boundary date is filled.",
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"Moon longitude, ayanamsa and node mode are documented beside the date.",
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"A second source or manual screenshot is attached before production tuning is considered.",
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],
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},
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"shadbala": {
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"preferred_sources": ["JHora manual screenshot", "PyJHora black-box output"],
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"steps": [
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"Capture planet-by-planet Sthana, Dig, Kala, Chesta, Naisargika and Drik Bala rows.",
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"Record Virupa and Rupa totals without applying a global scaling factor.",
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"Preserve the external tool's ayanamsa, house and node settings.",
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],
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"promotion_criteria": [
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"All six component targets are filled for the seven Shadbala planets.",
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"Totals are traceable to component sums.",
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"The row is not derived from this repository's local Shadbala output.",
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],
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},
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}
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FIELD_TO_MODULE = {
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"moon_sidereal_longitude_deg": "longitude",
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"sun_sidereal_longitude_deg": "longitude",
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"ascendant_longitude_deg": "longitude",
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"vimshottari_start_date": "dasha",
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"shadbala_components": "shadbala",
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}
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REQUIRED_EVIDENCE_METADATA_FIELDS = [
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"tool_name",
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"tool_version_or_url",
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"capture_date",
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"source_artifact",
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"ayanamsa",
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"node_mode",
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"timezone",
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"operator_note",
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]
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def _resolve_path(path: str) -> str:
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if os.path.isabs(path):
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return path
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return os.path.join(ROOT_DIR, path)
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def _load_json(path: str) -> dict[str, Any]:
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with open(_resolve_path(path), "r", encoding="utf-8") as fh:
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return json.load(fh)
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def _target_fields(value: Any, prefix: str = "target") -> list[str]:
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if prefix == "target" and isinstance(value, dict):
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return [f"{prefix}.{key}" for key in value]
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fields: list[str] = []
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if isinstance(value, dict):
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for key, child in value.items():
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fields.extend(_target_fields(child, f"{prefix}.{key}"))
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else:
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fields.append(prefix)
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return fields
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def _target_value(target: dict[str, Any], field: str) -> Any:
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value: Any = target
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for part in field.split(".")[1:]:
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if not isinstance(value, dict):
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return None
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value = value.get(part)
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return value
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def _missing_target_fields(value: Any, prefix: str = "target") -> list[str]:
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missing: list[str] = []
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if isinstance(value, dict):
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for key, child in value.items():
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missing.extend(_missing_target_fields(child, f"{prefix}.{key}"))
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elif value is None:
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missing.append(prefix)
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return missing
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def _target_modules(missing_fields: list[str]) -> list[str]:
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modules: list[str] = []
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for field in missing_fields:
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leaf = field.split(".")[-1]
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module = FIELD_TO_MODULE.get(leaf)
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if module and module not in modules:
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modules.append(module)
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return modules
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def _dedupe(items: list[str]) -> list[str]:
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seen: set[str] = set()
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result: list[str] = []
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for item in items:
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if item in seen:
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continue
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seen.add(item)
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result.append(item)
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return result
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def _evidence_packet(case: dict[str, Any], target_fields: list[str]) -> dict[str, Any]:
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case_id = case.get("id") or case.get("case_id")
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existing = case.get("evidence_packet", {})
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target = case.get("target", {})
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target_placeholders = {
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field: _target_value(target, field)
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for field in target_fields
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}
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existing_placeholders = existing.get("target_placeholders", {})
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if isinstance(existing_placeholders, dict):
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target_placeholders.update(existing_placeholders)
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return {
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"capture_id": existing.get("capture_id") or f"external_{case_id}",
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"status": existing.get("status", "draft"),
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"case_id": case_id,
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"birth": case.get("birth", {}),
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"settings": case.get("settings", {}),
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"required_metadata_fields": REQUIRED_EVIDENCE_METADATA_FIELDS,
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"metadata": existing.get("metadata", {}),
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"target_placeholders": target_placeholders,
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"integrity_checks": {
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"must_not_come_from_local_engine": True,
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"requires_external_artifact": True,
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"requires_status_external_verified_before_calibration": True,
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"reject_global_shadbala_scaling": "target.shadbala_components" in target_fields,
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},
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"promotion_status_after_fill": "external_verified",
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}
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def _task_from_template(case: dict[str, Any]) -> dict[str, Any]:
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case_id = case.get("id") or case.get("case_id")
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target = case.get("target", {})
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target_fields = _target_fields(target)
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missing_fields = _missing_target_fields(target)
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modules = _target_modules(target_fields)
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preferred_sources: list[str] = []
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collection_steps: list[str] = []
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promotion_criteria: list[str] = []
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for module in modules:
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guidance = SOURCE_GUIDANCE[module]
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preferred_sources.extend(guidance["preferred_sources"])
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collection_steps.extend(guidance["steps"])
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promotion_criteria.extend(guidance["promotion_criteria"])
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status = case.get("status", "template_only")
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ready_for_calibration = status == "external_verified" and not missing_fields
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if ready_for_calibration or missing_fields:
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blocked_reason = ""
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else:
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blocked_reason = "external_evidence_status_required"
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return {
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"task_id": f"collect_{case_id}",
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"case_id": case_id,
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"status": status,
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"source": case.get("source"),
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"privacy": case.get("privacy"),
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"birth": case.get("birth", {}),
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"settings": case.get("settings", {}),
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"target_fields": target_fields,
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"missing_target_fields": missing_fields,
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"target_modules": modules,
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"preferred_sources": _dedupe(preferred_sources),
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"collection_steps": _dedupe(collection_steps),
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"promotion_criteria": _dedupe(promotion_criteria),
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"evidence_packet": _evidence_packet(case, target_fields),
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"ready_for_collection": bool(missing_fields),
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"ready_for_calibration": ready_for_calibration,
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"blocked_reason": blocked_reason,
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"do_not_tune_production": not ready_for_calibration,
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"verification_note": case.get("verification_note", ""),
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}
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def build_queue(oracle: dict[str, Any]) -> dict[str, Any]:
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tasks = [_task_from_template(case) for case in oracle.get("template_cases", [])]
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by_status: dict[str, int] = {}
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for task in tasks:
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status = task.get("status", "unknown")
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by_status[status] = by_status.get(status, 0) + 1
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ready_for_calibration = sum(1 for task in tasks if task["ready_for_calibration"])
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return {
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"scope": "external_oracle_collection_queue",
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"schema_version": 1,
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"summary": {
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"total_tasks": len(tasks),
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"by_status": by_status,
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"ready_for_collection": sum(1 for task in tasks if task["ready_for_collection"]),
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"ready_for_calibration": ready_for_calibration,
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"production_tuning_allowed": ready_for_calibration > 0 and ready_for_calibration == len(tasks),
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"next_action": "Collect external target values, then promote individual rows to external_verified.",
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},
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"tasks": tasks,
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"boundary": (
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"Rows remain collection tasks until external targets are filled. Local engine output and "
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"template-only rows must not be used for Dasha/Shadbala production tuning."
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),
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}
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def _markdown_escape(value: Any) -> str:
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text = ", ".join(value) if isinstance(value, list) else str(value)
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return text.replace("|", "\\|")
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def render_markdown(queue: dict[str, Any]) -> str:
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summary = queue["summary"]
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lines = [
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"# Dasha/Shadbala External Oracle Collection Queue",
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"",
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f"total_tasks: `{summary['total_tasks']}`",
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f"ready_for_collection: `{summary['ready_for_collection']}`",
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f"ready_for_calibration: `{summary['ready_for_calibration']}`",
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f"production_tuning_allowed: `{str(summary['production_tuning_allowed']).lower()}`",
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"",
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"## Evidence Packet Fields",
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"",
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"Each JSON task includes an `evidence_packet.capture_id` draft packet with these required metadata fields:",
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"",
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", ".join(REQUIRED_EVIDENCE_METADATA_FIELDS),
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"",
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"| task_id | case_id | status | missing fields | preferred sources |",
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"|---|---|---|---|---|",
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]
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for task in queue["tasks"]:
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lines.append(
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"| {task_id} | {case_id} | `{status}` | {missing} | {sources} |".format(
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task_id=_markdown_escape(task["task_id"]),
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case_id=_markdown_escape(task["case_id"]),
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status=_markdown_escape(task["status"]),
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missing=_markdown_escape(task["missing_target_fields"]),
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sources=_markdown_escape(task["preferred_sources"]),
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)
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)
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lines.extend(["", queue["boundary"], ""])
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return "\n".join(lines)
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def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Generate external oracle collection tasks")
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parser.add_argument("--oracle-file", required=True, help="Path to oracle fixture JSON")
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parser.add_argument("--format", choices=["json", "markdown"], default="json")
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return parser.parse_args(argv)
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def main(argv: list[str] | None = None) -> int:
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args = parse_args(argv)
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oracle = _load_json(args.oracle_file)
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queue = build_queue(oracle)
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if args.format == "markdown":
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print(render_markdown(queue))
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else:
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print(json.dumps(queue, ensure_ascii=False, indent=2))
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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