root/Jyotisha
1
0
Fork 0
Code Issues 1 Pull Requests 1 Actions Packages Projects Releases Wiki Activity

feat(benchmark): add tajika annual oracle dashboard

Browse Source
This commit is contained in:
732642856
2026-06-26 17:29:47 +08:00
parent cba4e85d05
commit 3e606e5fe8
8 changed files with 740 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+19
View File
@@ -214,6 +214,25 @@ python3 scripts/public_benchmark_dashboard.py \
当前看板固定输出 `can_claim_global_first: false`，直到外部 oracle 样本、差异审计和长期公开 benchmark 都达到生产调参标准。
Tajika/Sahams 年运系统使用独立的外部 oracle 队列，专门追踪 Varshaphala、太阳回归、Muntha、Year Lord、Mudda Dasha、Sahams 与 Tajika Yogas 的外部验证状态：
```bash
python3 scripts/tajika_annual_oracle_queue.py \
--oracle-file references/oracle/tajika_annual_oracle_cases.json \
--format markdown
```
公开年运看板可这样生成：
```bash
python3 scripts/tajika_annual_benchmark_dashboard.py \
--oracle-file references/oracle/tajika_annual_oracle_cases.json \
--format markdown \
--output docs/benchmark/tajika_sahams_annual_benchmark_dashboard.md
```
当前 Tajika/Sahams 看板固定输出 `can_claim_tajika_sahams_closure: false`：本地 skill 已有年运计算与解释骨架，但太阳回归精确时刻、Varsha Lagna、Muntha、Mudda Dasha、Punya/Rajya/Vivah Saham 和 Tajika Yogas 仍需 JHora/PyJHora/书例级外部证据后，才能宣称年运闭环。
`full-reading` 也会输出 `ai_prompt_pack`：这是给网页/app、skill 或后端 AI 代理使用的结构化 Prompt/RAG 上下文包。它不会硬编码断语，而是携带 D1/D9/Dasha/Shadbala/Ashtakavarga 的证据快照、推荐检索文档和边界提示，要求大模型基于计算证据交叉验证，避免单一配置下结论。
### Prerequisites
docs/benchmark/tajika_sahams_annual_benchmark_dashboard.json
+25
View File
@@ -0,0 +1,25 @@
{
"scope": "tajika_sahams_annual_benchmark_dashboard",
"schema_version": 1,
"generated_at": "2026-06-26T09:27:54.639600+00:00",
"summary": {
"total_tasks": 5,
"ready_for_collection": 5,
"ready_for_calibration": 0,
"production_tuning_allowed": false,
"by_status": {
"template_only": 5
}
},
"annual_claim": {
"can_claim_tajika_sahams_closure": false,
"reason": "Do not claim annual-chart closure until every template row is promoted to external_verified with human-reviewable artifacts."
},
"remaining_gap": "Solar return exact time, Varsha Lagna, Muntha, Year Lord, Mudda Dasha first lord, Sahams and Tajika Yogas still need external JHora/PyJHora/book-example evidence before the Jyotish skill can claim Tajika/Sahams annual closure.",
"next_actions": [
"Fill one Steve Jobs annual evidence packet from JHora or PyJHora.",
"Add solar return datetime and Varsha Lagna tolerance checks after the first external row exists.",
"Add Saham-specific tolerance checks for Punya, Rajya and Vivah Saham.",
"Expand the annual benchmark with at least one printed Varshaphala example."
]
}
docs/benchmark/tajika_sahams_annual_benchmark_dashboard.md
+26
View File
@@ -0,0 +1,26 @@
# Tajika/Sahams Annual Benchmark Dashboard
Generated: `2026-06-26T09:27:55.462154+00:00`
## Annual Oracle Readiness
- total_tasks: `5`
- ready_for_collection: `5`
- ready_for_calibration: `0`
- production_tuning_allowed: `false`
## Annual Closure Claim
- can_claim_tajika_sahams_closure: `false`
- reason: Do not claim annual-chart closure until every template row is promoted to external_verified with human-reviewable artifacts.
## Remaining Gap
Solar return exact time, Varsha Lagna, Muntha, Year Lord, Mudda Dasha first lord, Sahams and Tajika Yogas still need external JHora/PyJHora/book-example evidence before the Jyotish skill can claim Tajika/Sahams annual closure.
## Next Actions
- Fill one Steve Jobs annual evidence packet from JHora or PyJHora.
- Add solar return datetime and Varsha Lagna tolerance checks after the first external row exists.
- Add Saham-specific tolerance checks for Punya, Rajya and Vivah Saham.
- Expand the annual benchmark with at least one printed Varshaphala example.
references/oracle/tajika_annual_oracle_cases.json
+201
View File
@@ -0,0 +1,201 @@
{
"schema_version": 1,
"scope": "external_tajika_sahams_annual_oracle_cases",
"notes": [
"These rows collect external annual-chart evidence for the Jyotish skill, not web/app UI fixtures.",
"Do not tune Tajika, Varshaphala, Muntha, Mudda Dasha, Sahams or yoga rules from template-only rows.",
"JHora, PyJHora, printed Varshaphala examples or documented black-box outputs may be used as external behavior references. Do not port incompatible licensed code."
],
"template_cases": [
{
"id": "template_steve_jobs_varshaphala_1984_lahiri",
"status": "template_only",
"source": "JHora Varshaphala screenshot / PyJHora black-box annual output / printed example",
"privacy": "public_figure_template",
"birth": {
"year": 1955,
"month": 2,
"day": 24,
"hour": 19,
"minute": 15,
"second": 0,
"lat": 37.7749,
"lon": -122.4194,
"tz": -8
},
"settings": {
"ayanamsa": "lahiri",
"node_mode": "true",
"annual_system": "varshaphala",
"target_year": 1984
},
"target": {
"solar_return_datetime": null,
"varsha_lagna_deg": null,
"muntha_sign": null,
"year_lord": null,
"mudda_dasha_first_lord": null,
"sahams": {
"punya_saham": null,
"rajya_saham": null,
"vivah_saham": null
},
"tajika_yogas": null,
"source_artifact": null
},
"verification_note": "Fill only from external annual-chart output. Local scripts/varshaphala.py output is not valid evidence."
},
{
"id": "template_einstein_varshaphala_1905_lahiri",
"status": "template_only",
"source": "JHora Varshaphala screenshot / PyJHora black-box annual output / printed example",
"privacy": "public_figure_template",
"birth": {
"year": 1879,
"month": 3,
"day": 14,
"hour": 11,
"minute": 30,
"second": 0,
"lat": 48.3984,
"lon": 9.9916,
"tz": 0.883333
},
"settings": {
"ayanamsa": "lahiri",
"node_mode": "mean",
"annual_system": "varshaphala",
"target_year": 1905
},
"target": {
"solar_return_datetime": null,
"varsha_lagna_deg": null,
"muntha_sign": null,
"year_lord": null,
"mudda_dasha_first_lord": null,
"sahams": {
"punya_saham": null,
"rajya_saham": null,
"vivah_saham": null
},
"tajika_yogas": null,
"source_artifact": null
},
"verification_note": "Historical timezone and source convention must be documented beside the external annual output."
},
{
"id": "template_marilyn_monroe_varshaphala_1962_lahiri",
"status": "template_only",
"source": "JHora Varshaphala screenshot / PyJHora black-box annual output / printed example",
"privacy": "public_figure_template",
"birth": {
"year": 1926,
"month": 6,
"day": 1,
"hour": 9,
"minute": 30,
"second": 0,
"lat": 34.0522,
"lon": -118.2437,
"tz": -8
},
"settings": {
"ayanamsa": "lahiri",
"node_mode": "true",
"annual_system": "varshaphala",
"target_year": 1962
},
"target": {
"solar_return_datetime": null,
"varsha_lagna_deg": null,
"muntha_sign": null,
"year_lord": null,
"mudda_dasha_first_lord": null,
"sahams": {
"punya_saham": null,
"rajya_saham": null,
"vivah_saham": null
},
"tajika_yogas": null,
"source_artifact": null
},
"verification_note": "Annual reading evidence must include exact solar return convention and visible source metadata."
},
{
"id": "template_historical_dst_london_varshaphala_1943_lahiri",
"status": "template_only",
"source": "JHora Varshaphala screenshot / PyJHora black-box annual output / printed example",
"privacy": "synthetic_historical_dst_template",
"birth": {
"year": 1910,
"month": 4,
"day": 15,
"hour": 12,
"minute": 0,
"second": 0,
"lat": 51.5074,
"lon": -0.1278,
"tz": 0
},
"settings": {
"ayanamsa": "lahiri",
"node_mode": "mean",
"annual_system": "varshaphala",
"target_year": 1943
},
"target": {
"solar_return_datetime": null,
"varsha_lagna_deg": null,
"muntha_sign": null,
"year_lord": null,
"mudda_dasha_first_lord": null,
"sahams": {
"punya_saham": null,
"rajya_saham": null,
"vivah_saham": null
},
"tajika_yogas": null,
"source_artifact": null
},
"verification_note": "This row exists to force historical DST documentation before annual-chart accuracy claims."
},
{
"id": "template_synthetic_extreme_latitude_varshaphala_kp",
"status": "template_only",
"source": "JHora Varshaphala screenshot / PyJHora black-box annual output / printed example",
"privacy": "synthetic_extreme_latitude_template",
"birth": {
"year": 2000,
"month": 6,
"day": 21,
"hour": 0,
"minute": 0,
"second": 0,
"lat": 65.0,
"lon": 15.0,
"tz": 1
},
"settings": {
"ayanamsa": "kp",
"node_mode": "true",
"annual_system": "varshaphala",
"target_year": 2024
},
"target": {
"solar_return_datetime": null,
"varsha_lagna_deg": null,
"muntha_sign": null,
"year_lord": null,
"mudda_dasha_first_lord": null,
"sahams": {
"punya_saham": null,
"rajya_saham": null,
"vivah_saham": null
},
"tajika_yogas": null,
"source_artifact": null
},
"verification_note": "High-latitude annual chart row; external source must document house and ascendant assumptions."
}
]
}
scripts/tajika_annual_benchmark_dashboard.py
+123
View File
@@ -0,0 +1,123 @@
#!/usr/bin/env python3
"""Generate a Tajika/Sahams annual benchmark dashboard for the Jyotish skill."""
from __future__ import annotations
import argparse
import json
import subprocess
import sys
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
ROOT = Path(__file__).resolve().parents[1]
PYTHON = sys.executable
def _run_json(command: list[str]) -> dict[str, Any]:
completed = subprocess.run(
command,
cwd=ROOT,
text=True,
capture_output=True,
timeout=60,
check=False,
)
if completed.returncode != 0:
raise RuntimeError(completed.stderr.strip() or completed.stdout.strip())
return json.loads(completed.stdout)
def build_dashboard(oracle_file: str) -> dict[str, Any]:
queue = _run_json([PYTHON, "scripts/tajika_annual_oracle_queue.py", "--oracle-file", oracle_file, "--format", "json"])
summary = queue["summary"]
can_claim_closure = bool(summary["production_tuning_allowed"] and summary["ready_for_calibration"] == summary["total_tasks"])
remaining_gap = (
"Solar return exact time, Varsha Lagna, Muntha, Year Lord, Mudda Dasha first lord, "
"Sahams and Tajika Yogas still need external JHora/PyJHora/book-example evidence before "
"the Jyotish skill can claim Tajika/Sahams annual closure."
)
return {
"scope": "tajika_sahams_annual_benchmark_dashboard",
"schema_version": 1,
"generated_at": datetime.now(timezone.utc).isoformat(),
"summary": {
"total_tasks": summary["total_tasks"],
"ready_for_collection": summary["ready_for_collection"],
"ready_for_calibration": summary["ready_for_calibration"],
"production_tuning_allowed": summary["production_tuning_allowed"],
"by_status": summary["by_status"],
},
"annual_claim": {
"can_claim_tajika_sahams_closure": can_claim_closure,
"reason": (
"Do not claim annual-chart closure until every template row is promoted to "
"external_verified with human-reviewable artifacts."
),
},
"remaining_gap": remaining_gap,
"next_actions": [
"Fill one Steve Jobs annual evidence packet from JHora or PyJHora.",
"Add solar return datetime and Varsha Lagna tolerance checks after the first external row exists.",
"Add Saham-specific tolerance checks for Punya, Rajya and Vivah Saham.",
"Expand the annual benchmark with at least one printed Varshaphala example.",
],
}
def render_markdown(report: dict[str, Any]) -> str:
summary = report["summary"]
claim = report["annual_claim"]
lines = [
"# Tajika/Sahams Annual Benchmark Dashboard",
"",
f"Generated: `{report['generated_at']}`",
"",
"## Annual Oracle Readiness",
"",
f"- total_tasks: `{summary['total_tasks']}`",
f"- ready_for_collection: `{summary['ready_for_collection']}`",
f"- ready_for_calibration: `{summary['ready_for_calibration']}`",
f"- production_tuning_allowed: `{str(summary['production_tuning_allowed']).lower()}`",
"",
"## Annual Closure Claim",
"",
f"- can_claim_tajika_sahams_closure: `{str(claim['can_claim_tajika_sahams_closure']).lower()}`",
f"- reason: {claim['reason']}",
"",
"## Remaining Gap",
"",
report["remaining_gap"],
"",
"## Next Actions",
"",
]
lines.extend(f"- {item}" for item in report["next_actions"])
lines.append("")
return "\n".join(lines)
def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Generate Tajika/Sahams annual benchmark dashboard")
parser.add_argument("--oracle-file", default="references/oracle/tajika_annual_oracle_cases.json")
parser.add_argument("--format", choices=["json", "markdown"], default="json")
parser.add_argument("--output", help="Optional output path")
return parser.parse_args(argv)
def main(argv: list[str] | None = None) -> int:
args = parse_args(argv)
report = build_dashboard(args.oracle_file)
text = json.dumps(report, ensure_ascii=False, indent=2) if args.format == "json" else render_markdown(report)
if args.output:
output = Path(args.output)
output.parent.mkdir(parents=True, exist_ok=True)
output.write_text(text, encoding="utf-8")
print(text)
return 0
if __name__ == "__main__":
raise SystemExit(main())
scripts/tajika_annual_oracle_queue.py
+231
View File
@@ -0,0 +1,231 @@
#!/usr/bin/env python3
"""Generate Tajika/Sahams annual external-oracle collection tasks.
This is skill-level verification infrastructure. It does not compute annual
chart values and must not be used to tune production rules from template rows.
"""
from __future__ import annotations
import argparse
import json
import os
from typing import Any
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
REQUIRED_EVIDENCE_METADATA_FIELDS = [
"tool_name",
"tool_version_or_url",
"capture_date",
"source_artifact",
"ayanamsa",
"node_mode",
"timezone",
"annual_system",
"target_year",
"operator_note",
]
SOURCE_GUIDANCE = {
"preferred_sources": [
"JHora Varshaphala screenshot",
"PyJHora black-box annual output",
"Printed Tajika/Varshaphala example",
],
"collection_steps": [
"Set the exact birth data, ayanamsa, node mode, timezone and target year in the external annual-chart tool.",
"Record solar return datetime, Varsha Lagna, Muntha sign, Year Lord and first Mudda Dasha lord.",
"Record Punya Saham, Rajya Saham and Vivah Saham in absolute 0-360 degree format.",
"Record visible Tajika Yogas without translating them through this repository's interpretation layer.",
"Attach a redacted screenshot, stdout snippet or book-example citation under references/oracle/artifacts/.",
],
"promotion_criteria": [
"All target fields are filled from a documented external annual-chart source.",
"The source artifact is external evidence, not scripts/varshaphala.py or this repository's local output.",
"Solar return and timezone/DST conventions are documented before promotion to external_verified.",
"At least one human-reviewable artifact path is preserved in target.source_artifact.",
],
}
def _resolve_path(path: str) -> str:
if os.path.isabs(path):
return path
return os.path.join(ROOT_DIR, path)
def _load_json(path: str) -> dict[str, Any]:
with open(_resolve_path(path), "r", encoding="utf-8") as fh:
return json.load(fh)
def _target_fields(value: Any, prefix: str = "target") -> list[str]:
if prefix == "target" and isinstance(value, dict):
fields: list[str] = []
for key, child in value.items():
fields.extend(_target_fields(child, f"{prefix}.{key}"))
return fields
if isinstance(value, dict):
fields = []
for key, child in value.items():
fields.extend(_target_fields(child, f"{prefix}.{key}"))
return fields
return [prefix]
def _target_value(target: dict[str, Any], field: str) -> Any:
value: Any = target
for part in field.split(".")[1:]:
if not isinstance(value, dict):
return None
value = value.get(part)
return value
def _missing_target_fields(value: Any, prefix: str = "target") -> list[str]:
missing: list[str] = []
if isinstance(value, dict):
for key, child in value.items():
missing.extend(_missing_target_fields(child, f"{prefix}.{key}"))
elif value is None or value == "" or value == [] or value == {}:
missing.append(prefix)
return missing
def _evidence_packet(case: dict[str, Any], target_fields: list[str]) -> dict[str, Any]:
case_id = case.get("id") or case.get("case_id")
target = case.get("target", {})
settings = case.get("settings", {})
metadata = {
"tool_name": "",
"tool_version_or_url": "",
"capture_date": "",
"source_artifact": "references/oracle/artifacts/",
"ayanamsa": settings.get("ayanamsa", ""),
"node_mode": settings.get("node_mode", ""),
"timezone": case.get("birth", {}).get("tz", ""),
"annual_system": settings.get("annual_system", "varshaphala"),
"target_year": settings.get("target_year", ""),
"operator_note": "",
}
return {
"capture_id": f"external_{case_id}",
"status": "draft",
"case_id": case_id,
"birth": case.get("birth", {}),
"settings": settings,
"required_metadata_fields": REQUIRED_EVIDENCE_METADATA_FIELDS,
"metadata": metadata,
"target_placeholders": {field: _target_value(target, field) for field in target_fields},
"integrity_checks": {
"must_not_come_from_local_engine": True,
"requires_external_artifact": True,
"requires_status_external_verified_before_calibration": True,
"requires_solar_return_convention": True,
},
"promotion_status_after_fill": "external_verified",
}
def _task_from_template(case: dict[str, Any]) -> dict[str, Any]:
case_id = case.get("id") or case.get("case_id")
target = case.get("target", {})
target_fields = _target_fields(target)
missing_fields = _missing_target_fields(target)
status = case.get("status", "template_only")
ready_for_calibration = status == "external_verified" and not missing_fields
return {
"task_id": f"collect_{case_id}",
"case_id": case_id,
"status": status,
"source": case.get("source"),
"privacy": case.get("privacy"),
"birth": case.get("birth", {}),
"settings": case.get("settings", {}),
"target_fields": target_fields,
"missing_target_fields": missing_fields,
"preferred_sources": SOURCE_GUIDANCE["preferred_sources"],
"collection_steps": SOURCE_GUIDANCE["collection_steps"],
"promotion_criteria": SOURCE_GUIDANCE["promotion_criteria"],
"evidence_packet": _evidence_packet(case, target_fields),
"ready_for_collection": bool(missing_fields),
"ready_for_calibration": ready_for_calibration,
"blocked_reason": "" if ready_for_calibration else "external_annual_evidence_required",
"do_not_tune_production": not ready_for_calibration,
"verification_note": case.get("verification_note", ""),
}
def build_queue(oracle: dict[str, Any]) -> dict[str, Any]:
tasks = [_task_from_template(case) for case in oracle.get("template_cases", [])]
by_status: dict[str, int] = {}
for task in tasks:
status = task.get("status", "unknown")
by_status[status] = by_status.get(status, 0) + 1
ready_for_calibration = sum(1 for task in tasks if task["ready_for_calibration"])
return {
"scope": "tajika_sahams_annual_oracle_collection_queue",
"schema_version": 1,
"summary": {
"total_tasks": len(tasks),
"by_status": by_status,
"ready_for_collection": sum(1 for task in tasks if task["ready_for_collection"]),
"ready_for_calibration": ready_for_calibration,
"production_tuning_allowed": ready_for_calibration > 0 and ready_for_calibration == len(tasks),
"next_action": "Collect external Varshaphala target values, then promote rows to external_verified.",
},
"tasks": tasks,
"boundary": (
"Rows remain collection tasks until external solar return, Muntha, Year Lord, Mudda Dasha, "
"Sahams and Tajika Yogas targets are filled. Local annual-chart output and template-only rows "
"must not be used for production tuning."
),
}
def render_markdown(queue: dict[str, Any]) -> str:
summary = queue["summary"]
lines = [
"# Tajika/Sahams Annual External Oracle Collection Queue",
"",
f"total_tasks: `{summary['total_tasks']}`",
f"ready_for_collection: `{summary['ready_for_collection']}`",
f"ready_for_calibration: `{summary['ready_for_calibration']}`",
f"production_tuning_allowed: `{str(summary['production_tuning_allowed']).lower()}`",
"",
"## Required Evidence",
"",
"Solar return datetime, Varsha Lagna, Muntha, Year Lord, Mudda Dasha, Punya Saham, Rajya Saham, Vivah Saham and Tajika Yogas.",
"",
"| task_id | status | missing fields | preferred sources |",
"|---|---|---|---|",
]
for task in queue["tasks"]:
lines.append(
f"| {task['task_id']} | `{task['status']}` | {', '.join(task['missing_target_fields'])} | {', '.join(task['preferred_sources'])} |"
)
lines.extend(["", queue["boundary"], ""])
return "\n".join(lines)
def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Generate Tajika/Sahams annual oracle collection tasks")
parser.add_argument("--oracle-file", required=True)
parser.add_argument("--format", choices=["json", "markdown"], default="json")
return parser.parse_args(argv)
def main(argv: list[str] | None = None) -> int:
args = parse_args(argv)
queue = build_queue(_load_json(args.oracle_file))
if args.format == "markdown":
print(render_markdown(queue))
else:
print(json.dumps(queue, ensure_ascii=False, indent=2))
return 0
if __name__ == "__main__":
raise SystemExit(main())
tests/test_tajika_annual_benchmark_dashboard.py
+57
View File
@@ -0,0 +1,57 @@
#!/usr/bin/env python3
"""Tests for the Tajika/Sahams annual benchmark dashboard."""
from __future__ import annotations
import json
import subprocess
import sys
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
ORACLE_FILE = "references/oracle/tajika_annual_oracle_cases.json"
def run_dashboard(*args: str) -> subprocess.CompletedProcess[str]:
return subprocess.run(
[
sys.executable,
"scripts/tajika_annual_benchmark_dashboard.py",
"--oracle-file",
ORACLE_FILE,
*args,
],
cwd=ROOT,
text=True,
capture_output=True,
timeout=60,
check=False,
)
def test_tajika_annual_dashboard_outputs_stable_json_summary() -> None:
completed = run_dashboard("--format", "json")
assert completed.returncode == 0, completed.stderr or completed.stdout
report = json.loads(completed.stdout)
assert report["scope"] == "tajika_sahams_annual_benchmark_dashboard"
assert report["schema_version"] == 1
assert report["summary"]["total_tasks"] == 5
assert report["summary"]["ready_for_calibration"] == 0
assert report["summary"]["production_tuning_allowed"] is False
assert report["annual_claim"]["can_claim_tajika_sahams_closure"] is False
assert "Solar return" in report["remaining_gap"]
assert "Sahams" in report["remaining_gap"]
def test_tajika_annual_dashboard_outputs_markdown_and_can_write_file(tmp_path: Path) -> None:
output = tmp_path / "tajika_dashboard.md"
completed = run_dashboard("--format", "markdown", "--output", str(output))
assert completed.returncode == 0, completed.stderr or completed.stdout
assert output.exists()
markdown = output.read_text(encoding="utf-8")
assert "# Tajika/Sahams Annual Benchmark Dashboard" in markdown
assert "can_claim_tajika_sahams_closure: `false`" in markdown
assert "production_tuning_allowed: `false`" in markdown
tests/test_tajika_annual_oracle_queue.py
+58
View File
@@ -0,0 +1,58 @@
#!/usr/bin/env python3
"""Tests for the Tajika/Sahams annual external-oracle collection queue."""
from __future__ import annotations
import json
import subprocess
import sys
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
ORACLE_FILE = "references/oracle/tajika_annual_oracle_cases.json"
def run_queue(*args: str) -> subprocess.CompletedProcess[str]:
return subprocess.run(
[sys.executable, "scripts/tajika_annual_oracle_queue.py", "--oracle-file", ORACLE_FILE, *args],
cwd=ROOT,
text=True,
capture_output=True,
timeout=60,
check=False,
)
def test_tajika_annual_queue_outputs_collection_tasks() -> None:
completed = run_queue("--format", "json")
assert completed.returncode == 0, completed.stderr or completed.stdout
queue = json.loads(completed.stdout)
assert queue["scope"] == "tajika_sahams_annual_oracle_collection_queue"
assert queue["schema_version"] == 1
assert queue["summary"]["total_tasks"] == 5
assert queue["summary"]["ready_for_calibration"] == 0
assert queue["summary"]["production_tuning_allowed"] is False
assert "solar return" in queue["boundary"].lower()
first = queue["tasks"][0]
assert first["task_id"].startswith("collect_")
assert first["status"] == "template_only"
assert first["ready_for_collection"] is True
assert first["ready_for_calibration"] is False
assert "target.solar_return_datetime" in first["target_fields"]
assert "target.sahams.punya_saham" in first["missing_target_fields"]
assert "JHora Varshaphala screenshot" in first["preferred_sources"]
assert first["evidence_packet"]["integrity_checks"]["requires_external_artifact"] is True
def test_tajika_annual_queue_markdown_lists_sahams_and_yogas() -> None:
completed = run_queue("--format", "markdown")
assert completed.returncode == 0, completed.stderr or completed.stdout
markdown = completed.stdout
assert "# Tajika/Sahams Annual External Oracle Collection Queue" in markdown
assert "Punya Saham" in markdown
assert "Tajika Yogas" in markdown
assert "production_tuning_allowed: `false`" in markdown