#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ 印度占星 API 服务器 v1.0 为 jyotish-app 前端提供 v6.9.14 引擎的精算能力 启动: python3 scripts/jyotish_api_server.py --port 5200 """ import argparse import base64 import html as html_lib import io import json, sys, os, math import importlib.util import re from datetime import datetime, timedelta from http.server import HTTPServer, BaseHTTPRequestHandler from urllib.parse import urlparse SCRIPTS_DIR = os.path.dirname(os.path.abspath(__file__)) REPO_ROOT = os.path.abspath(os.path.join(SCRIPTS_DIR, '..')) sys.path.insert(0, SCRIPTS_DIR) _LOCAL_MODULE_CACHE = {} def _load_local_module(module_name): cached = _LOCAL_MODULE_CACHE.get(module_name) if cached: return cached module_path = os.path.join(SCRIPTS_DIR, f'{module_name}.py') spec = importlib.util.spec_from_file_location(f'_jyotish_local_{module_name}', module_path) if not spec or not spec.loader: raise ImportError(f'Cannot load local module: {module_name}') module = importlib.util.module_from_spec(spec) sys.modules[spec.name] = module spec.loader.exec_module(module) _LOCAL_MODULE_CACHE[module_name] = module return module SIGNS = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo', 'Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces'] DEFAULT_ALLOWED_ORIGINS = { 'http://localhost:3456', 'http://127.0.0.1:3456', 'http://localhost:3457', 'http://127.0.0.1:3457', 'http://localhost:5173', 'http://127.0.0.1:5173', } MAX_REQUEST_BYTES = 2 * 1024 * 1024 MAX_IMPORT_FILE_BYTES = 1536 * 1024 MAX_IMPORT_TEXT_CHARS = 500_000 MAX_REPORT_HTML_CHARS = 1_200_000 MAX_REPORT_BASE64_BYTES = 8 * 1024 * 1024 REPORT_ARTIFACT_DIR = os.path.join('/private/tmp', 'jyotish-reports') API_COMMAND_MAP = { 'chart': '/api/chart', 'kp': '/api/kp', 'prashna': '/api/prashna', 'synastry': '/api/synastry', 'ashtakoot': '/api/synastry', 'dasha': '/api/dasha', 'chara-dasha': '/api/dasha/chara', 'remedies': '/api/remedies', 'sade_sati': '/api/sade_sati', 'pancha_mahapurusha': '/api/pancha_mahapurusha', 'career': '/api/career', 'relationship': '/api/relationship', 'full-reading': '/api/chart', 'tajika': '/api/tajika', 'solar-return': '/api/annual', 'muhurta': '/api/muhurta', 'panchanga-range': '/api/panchanga_range', 'bhava-chalit': '/api/bhava_chalit', 'sudarshana': '/api/sudarshana', 'nakshatra-full': '/api/nakshatra_full', 'varga-full': '/api/varga_full', 'jaimini': '/api/jaimini', 'ashtakavarga': '/api/ashtakavarga', 'shadbala': '/api/shadbala', 'yoga': '/api/yogas', 'aspects': '/api/aspects', 'rectification': '/api/rectification_gate', 'case-validation': '/api/case_validation', 'divisional-yoga': '/api/divisional_yoga', 'deep-varga-avastha': '/api/deep_varga_avastha', 'kakshya': '/api/kakshya', 'bhava-bala': '/api/bhava_bala', 'transit-trigger': '/api/transit', 'audit-capabilities': '/api/capability_audit', 'thematic-report': '/api/thematic_report', 'report-artifact': '/api/report_artifact', } TECHNIQUE_EXAMPLE_ENDPOINTS = { '/api/ashtakavarga', '/api/bhava_bala', '/api/bhava_chalit', '/api/career', '/api/case_validation', '/api/dasha', '/api/dasha/chara', '/api/divisional_yoga', '/api/deep_varga_avastha', '/api/jaimini', '/api/kakshya', '/api/kp', '/api/muhurta', '/api/nakshatra_full', '/api/pancha_mahapurusha', '/api/prashna', '/api/rectification_gate', '/api/relationship', '/api/remedies', '/api/sade_sati', '/api/shadbala', '/api/sudarshana', '/api/synastry', '/api/thematic_report', '/api/transit', '/api/varga_full', '/api/yogas', } SAMPLE_PLANETS = { 'Sun': {'lon': 280.0, 'degree': 10.0, 'degree_in_sign': 10.0, 'sign_idx': 9, 'sign': 'Capricorn', 'house': 10}, 'Moon': {'lon': 123.0, 'degree': 3.0, 'degree_in_sign': 3.0, 'sign_idx': 4, 'sign': 'Leo', 'house': 5}, 'Mars': {'lon': 210.0, 'degree': 0.0, 'degree_in_sign': 0.0, 'sign_idx': 7, 'sign': 'Scorpio', 'house': 8}, 'Mercury': {'lon': 275.0, 'degree': 5.0, 'degree_in_sign': 5.0, 'sign_idx': 9, 'sign': 'Capricorn', 'house': 10}, 'Jupiter': {'lon': 15.0, 'degree': 15.0, 'degree_in_sign': 15.0, 'sign_idx': 0, 'sign': 'Aries', 'house': 1}, 'Venus': {'lon': 330.0, 'degree': 0.0, 'degree_in_sign': 0.0, 'sign_idx': 11, 'sign': 'Pisces', 'house': 12}, 'Saturn': {'lon': 300.0, 'degree': 0.0, 'degree_in_sign': 0.0, 'sign_idx': 10, 'sign': 'Aquarius', 'house': 11}, 'Rahu': {'lon': 45.0, 'degree': 15.0, 'degree_in_sign': 15.0, 'sign_idx': 1, 'sign': 'Taurus', 'house': 2}, 'Ketu': {'lon': 225.0, 'degree': 15.0, 'degree_in_sign': 15.0, 'sign_idx': 7, 'sign': 'Scorpio', 'house': 8}, } SAMPLE_ASCENDANT = {'sign': 'Aries', 'sign_idx': 0, 'degree': 12.0, 'degree_in_sign': 12.0, 'lon': 12.0} # 城市数据库（简化版） CITY_DB = { '北京': (39.9, 116.4, 8), '上海': (31.2, 121.5, 8), '广州': (23.1, 113.3, 8), '深圳': (22.5, 114.1, 8), '成都': (30.6, 104.1, 8), '重庆': (29.6, 106.5, 8), '杭州': (30.3, 120.2, 8), '南京': (32.1, 118.8, 8), '武汉': (30.6, 114.3, 8), '西安': (34.3, 108.9, 8), '郑州': (34.8, 113.7, 8), '长沙': (28.2, 113.0, 8), '天津': (39.1, 117.2, 8), '香港': (22.3, 114.2, 8), '台北': (25.0, 121.5, 8), 'New York': (40.7, -74.0, -5), 'London': (51.5, -0.1, 0), 'Tokyo': (35.7, 139.7, 9), 'Sydney': (-33.9, 151.2, 10), 'Delhi': (28.6, 77.2, 5.5), 'Mumbai': (19.1, 72.9, 5.5), 'Paris': (48.9, 2.3, 1), 'Berlin': (52.5, 13.4, 1), 'Los Angeles': (34.1, -118.2, -8), 'Chicago': (41.9, -87.6, -6), 'San Francisco': (37.8, -122.4, -8), 'Seattle': (47.6, -122.3, -8), 'Boston': (42.4, -71.1, -5), 'Toronto': (43.7, -79.4, -5), 'Singapore': (1.3, 103.8, 8), 'Dubai': (25.2, 55.3, 4), } class BadRequest(ValueError): """Client-side request validation failed.""" class JyotishAPIHandler(BaseHTTPRequestHandler): server_version = 'JyotishAPI/6.9.14' def _json(self, data, status=200): self.send_response(status) self.send_header('Content-Type', 'application/json; charset=utf-8') self._send_cors_headers() self.send_header('X-Content-Type-Options', 'nosniff') self.send_header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS') self.send_header('Access-Control-Allow-Headers', 'Content-Type, Authorization') self.send_header('Vary', 'Origin') self.end_headers() self.wfile.write(json.dumps(data, ensure_ascii=False, default=str).encode()) def _error_json(self, message, status=500, error_code='ERR_INTERNAL'): self._json({'success': False, 'error': message, 'error_code': error_code}, status) def _send_cors_headers(self): origin = self.headers.get('Origin') allowed = getattr(self.server, 'allowed_origins', DEFAULT_ALLOWED_ORIGINS) if origin in allowed: self.send_header('Access-Control-Allow-Origin', origin) def do_OPTIONS(self): self._json({}) def do_GET(self): path = urlparse(self.path).path try: if path == '/api/health': swisseph_available = False swisseph_version = None try: import swisseph as swe swisseph_available = True swisseph_version = getattr(swe, 'version', None) or getattr(swe, '__version__', None) except Exception: swisseph_available = False swisseph_version = None self._json({ 'status': 'ok', 'version': '6.9.14', 'swisseph_available': swisseph_available, 'swisseph_version': swisseph_version, 'ayanamsa_default': 'lahiri', 'modules': 'Chart/KP/Synastry/Prashna/Remedies/Dasha/Varga/Jaimini/Ashtakavarga/Shadbala/Yoga/Aspects/Tajika/Muhurta/BhavaChalit/BhavaBala/Sudarshana/Nakshatra/Transit/RectificationGate/CaseValidation/DivisionalYoga/Kakshya', }) elif path == '/api/cities': self._json(list(CITY_DB.keys())) elif path == '/api/capability_audit': self._json(self._capability_audit()) elif path == '/api/technique_catalog': self._json(self._technique_catalog()) elif path == '/api/real_case_revalidation': self._json(self._real_case_revalidation()) else: self._error_json('Not found', 404, 'ERR_NOT_FOUND') except Exception: import logging logging.exception("[api_server] GET request failed for %s", path) self._error_json('Internal server error', 500, 'ERR_INTERNAL') def do_POST(self): path = urlparse(self.path).path try: body = self._read_json_body() if path == '/api/chart': result = self._compute_chart(body) self._json(result) elif path == '/api/remedies': result = self._compute_remedies(body) self._json(result) elif path == '/api/kp': result = self._compute_kp(body) self._json(result) elif path == '/api/prashna': result = self._compute_prashna(body) self._json(result) elif path == '/api/synastry': result = self._compute_synastry(body) self._json(result) elif path == '/api/dasha': result = self._compute_dasha_system(body) self._json(result) elif path == '/api/dasha/chara': result = self._compute_chara_dasha(body) self._json(result) elif path == '/api/sade_sati': result = self._compute_sade_sati(body) self._json(result) elif path == '/api/pancha_mahapurusha': result = self._compute_pmc(body) self._json(result) elif path == '/api/career': result = self._compute_career(body) self._json(result) elif path == '/api/relationship': result = self._compute_relationship(body) self._json(result) elif path == '/api/import_chart': result = self._import_chart_text(body) self._json(result) elif path == '/api/report_artifact': result = self._compute_report_artifact(body) self._json(result) elif path == '/api/oracle_evidence': result = self._compute_oracle_evidence(body) self._json(result) elif path == '/api/annual': result = self._compute_annual(body) self._json(result) elif path == '/api/tajika': result = self._compute_tajika(body) self._json(result) elif path == '/api/muhurta': result = self._compute_muhurta(body) self._json(result) elif path == '/api/panchanga_range': result = self._compute_panchanga_range(body) self._json(result) elif path == '/api/bhava_chalit': result = self._compute_bhava_chalit(body) self._json(result) elif path == '/api/sudarshana': result = self._compute_sudarshana(body) self._json(result) elif path == '/api/nakshatra_full': result = self._compute_nakshatra_full(body) self._json(result) elif path == '/api/varga_full': result = self._compute_varga_full(body) self._json(result) elif path == '/api/jaimini': result = self._compute_jaimini(body) self._json(result) elif path == '/api/ashtakavarga': result = self._compute_ashtakavarga(body) self._json(result) elif path == '/api/shadbala': result = self._compute_shadbala(body) self._json(result) elif path == '/api/yogas': result = self._compute_yogas_api(body) self._json(result) elif path == '/api/aspects': result = self._compute_aspects(body) self._json(result) elif path == '/api/rectification_gate': result = self._compute_rectification_gate(body) self._json(result) elif path == '/api/case_validation': result = self._compute_case_validation(body) self._json(result) elif path == '/api/divisional_yoga': result = self._compute_divisional_yoga(body) self._json(result) elif path == '/api/deep_varga_avastha': result = self._compute_deep_varga_avastha(body) self._json(result) elif path == '/api/kakshya': result = self._compute_kakshya(body) self._json(result) elif path == '/api/bhava_bala': result = self._compute_bhava_bala_api(body) self._json(result) elif path == '/api/transit': result = self._compute_transit_triggers(body) self._json(result) elif path == '/api/thematic_report': result = self._compute_thematic_report(body) self._json(result) elif path == '/api/technique_example': result = self._compute_technique_example(body) self._json(result) else: self._error_json(f'Unknown endpoint: {path}', 404, 'ERR_NOT_FOUND') except BadRequest as e: self._error_json(str(e), 400, 'ERR_BAD_REQUEST') except Exception: import logging logging.exception("[api_server] request failed for %s", path) self._error_json('Internal server error', 500, 'ERR_INTERNAL') def _read_json_body(self): raw_length = self.headers.get('Content-Length', '0') try: length = int(raw_length) except ValueError as e: raise BadRequest('Invalid Content-Length') from e if length < 0: raise BadRequest('Invalid Content-Length') if length > MAX_REQUEST_BYTES: raise BadRequest(f'Request body too large; max {MAX_REQUEST_BYTES} bytes') if length == 0: return {} try: body = json.loads(self.rfile.read(length)) except json.JSONDecodeError as e: raise BadRequest('Invalid JSON body') from e if not isinstance(body, dict): raise BadRequest('JSON body must be an object') return body def _get_int(self, body, key, default, min_value=None, max_value=None): value = body.get(key, default) try: number = int(value) except (TypeError, ValueError) as e: raise BadRequest(f'{key} must be an integer') from e self._check_range(key, number, min_value, max_value) return number def _parse_timezone(self, body, lat, lon, year, month, day, hour, minute, second): tz = body.get('tz') if tz is not None and tz != "": return self._get_float(body, 'tz', 8, -14, 14) from timezone_utils import infer_timezone from datetime import datetime try: dt = datetime(int(year), int(month), int(day), int(hour), int(minute), int(second)) except Exception: dt = datetime.utcnow() return infer_timezone(lat, lon, dt) def _get_float(self, body, key, default, min_value=None, max_value=None): value = body.get(key, default) try: number = float(value) except (TypeError, ValueError) as e: raise BadRequest(f'{key} must be a number') from e if not math.isfinite(number): raise BadRequest(f'{key} must be finite') self._check_range(key, number, min_value, max_value) return number def _check_range(self, key, number, min_value, max_value): if min_value is not None and number < min_value: raise BadRequest(f'{key} must be >= {min_value}') if max_value is not None and number > max_value: raise BadRequest(f'{key} must be <= {max_value}') def _validate_planets(self, planets): if not isinstance(planets, dict): raise BadRequest('planets must be an object') return planets def _normalize_degree(self, body, key, default): return self._get_float(body, key, default, 0, 360) % 360 def _get_birth_second(self, body, default=0.0): return self._get_float(body, 'second', body.get('birth_second', default), 0, 59) def _birth_hour_decimal(self, hour, minute, second=0.0): return float(hour) + float(minute) / 60.0 + float(second) / 3600.0 def _format_birth_time(self, hour, minute, second=0.0): second_int = int(float(second)) base = f'{int(hour):02d}:{int(minute):02d}' return f'{base}:{second_int:02d}' if second_int else base def _safe_report_slug(self, value): slug = re.sub(r'[^a-zA-Z0-9._-]+', '-', str(value or 'jyotish-report')).strip('-._') return (slug[:80] or 'jyotish-report') def _validate_report_html(self, html): if not isinstance(html, str) or not html.strip(): raise BadRequest('html must be a non-empty string') if len(html) > MAX_REPORT_HTML_CHARS: raise BadRequest(f'html too large; max {MAX_REPORT_HTML_CHARS} characters') active_patterns = [ r'<\s*script\b', r'<\s*iframe\b', r'<\s*object\b', r'<\s*embed\b', r'\son[a-z]+\s*=', r'javascript\s*:', ] if any(re.search(pattern, html, re.IGNORECASE) for pattern in active_patterns): raise BadRequest('report html cannot include active content') return html def _inject_functional_benefic_malefic_summary(self, html, snapshot): if not isinstance(snapshot, dict): return html if snapshot.get('status') in {None, 'blocked', 'not_used'}: return html benefics = snapshot.get('functional_benefics') malefics = snapshot.get('functional_malefics') if not isinstance(benefics, list) or not isinstance(malefics, list): return html neutrals = snapshot.get('functional_neutrals') if isinstance(snapshot.get('functional_neutrals'), list) else [] yogakarakas = snapshot.get('yogakarakas') if isinstance(snapshot.get('yogakarakas'), list) else [] def _escape(value): return html_lib.escape(str(value or '')) ascendant = _escape(snapshot.get('ascendant') or snapshot.get('asc_sign') or 'Unknown') benefic_text = _escape(', '.join(str(item) for item in benefics) or 'None') malefic_text = _escape(', '.join(str(item) for item in malefics) or 'None') neutral_text = _escape(', '.join(str(item) for item in neutrals) or 'None') yogakaraka_text = _escape(', '.join(str(item) for item in yogakarakas) or 'None') confidence_text = _escape(snapshot.get('effect_on_confidence') or 'Functional role layer was used in the final judgement.') source_text = _escape(snapshot.get('source') or 'strict_functional_benefic_malefic_v1') summary = ( '
' '

Functional Benefic/Malefic

' f'

Ascendant: {ascendant}

' f'

Functional Benefics: {benefic_text}

' f'

Functional Malefics: {malefic_text}

' f'

Functional Neutrals: {neutral_text}

' f'

Yogakarakas: {yogakaraka_text}

' f'

Confidence Impact: {confidence_text}

' f'

Source: {source_text}

' '
' ) body_close = re.search(r'', html, re.IGNORECASE) if body_close: return html[:body_close.start()] + summary + html[body_close.start():] return html + summary def _artifact_base64(self, path): size = os.path.getsize(path) if size > MAX_REPORT_BASE64_BYTES: return None with open(path, 'rb') as fh: return base64.b64encode(fh.read()).decode('ascii') def _compute_oracle_evidence(self, body): packet = body.get('packet') if not isinstance(packet, dict): raise BadRequest('packet must be an object') case_id = packet.get('case_id') if not case_id: raise BadRequest('packet.case_id is required') collection_queue = _load_local_module('oracle_collection_queue') evidence_validator = _load_local_module('oracle_evidence_validator') target = packet.get('target') if isinstance(packet.get('target'), dict) else {} target_fields = collection_queue._target_fields(target) status = packet.get('status') or packet.get('evidence_packet', {}).get('status') or 'draft' evidence_packet = packet.get('evidence_packet') if isinstance(packet.get('evidence_packet'), dict) else {} metadata = evidence_packet.get('metadata') if isinstance(evidence_packet.get('metadata'), dict) else {} task = { 'task_id': f'uploaded_{case_id}', 'case_id': case_id, 'status': status, 'target_fields': target_fields, 'missing_target_fields': collection_queue._missing_target_fields(target), 'evidence_packet': { 'capture_id': evidence_packet.get('capture_id') or f'uploaded_{case_id}', 'status': evidence_packet.get('status') or status, 'case_id': case_id, 'required_metadata_fields': collection_queue.REQUIRED_EVIDENCE_METADATA_FIELDS, 'metadata': metadata, 'target_placeholders': { field: collection_queue._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, 'reject_global_shadbala_scaling': 'target.shadbala_components' in target_fields, }, 'promotion_status_after_fill': 'external_verified', }, } report = evidence_validator.build_report({ 'scope': 'uploaded_oracle_evidence_packet', 'schema_version': 1, 'tasks': [task], }) return { 'success': True, 'endpoint': 'oracle_evidence', 'scope': report['scope'], 'report': report, 'summary': report['summary'], 'packets': report['packets'], 'boundary': report['boundary'], } def _compute_report_artifact(self, body): html = self._validate_report_html(body.get('html')) html = self._inject_functional_benefic_malefic_summary( html, body.get('functional_benefic_malefic'), ) fmt = body.get('format', 'html') if fmt not in {'html', 'pdf'}: raise BadRequest('format must be html or pdf') slug = self._safe_report_slug(body.get('name') or body.get('filename')) stamp = datetime.utcnow().strftime('%Y%m%d-%H%M%S-%f') os.makedirs(REPORT_ARTIFACT_DIR, exist_ok=True) html_filename = f'{slug}-{stamp}.html' html_path = os.path.join(REPORT_ARTIFACT_DIR, html_filename) with open(html_path, 'w', encoding='utf-8') as fh: fh.write(html) result = { 'success': True, 'endpoint': 'report_artifact', 'format': fmt, 'html_filename': html_filename, 'html_path': html_path, 'html_size_kb': round(os.path.getsize(html_path) / 1024, 1), 'html_base64': self._artifact_base64(html_path), 'mime': 'text/html;charset=utf-8', 'source': 'scripts/report_builder.py', 'artifact_status': 'html_ready', 'primary_artifact': 'html', 'download_filename': html_filename, 'download_mime': 'text/html;charset=utf-8', 'fallback_reason': None, 'user_message': 'HTML report artifact generated.', 'next_action': 'Open the downloaded HTML file directly, or print it to PDF from the browser.', 'delivery': { 'artifact_status': 'html_ready', 'format': 'html', 'filename': html_filename, 'mime': 'text/html;charset=utf-8', 'fallback': False, 'user_message': 'HTML report artifact generated.', 'next_action': 'Open the downloaded HTML file directly, or print it to PDF from the browser.', }, } if fmt == 'pdf': pdf_filename = f'{slug}-{stamp}.pdf' pdf_path = os.path.join(REPORT_ARTIFACT_DIR, pdf_filename) try: ok = _load_local_module('report_builder')._html_to_pdf(html_path, pdf_path) except Exception as exc: ok = False result['pdf_error'] = str(exc) result.update({ 'pdf_available': bool(ok and os.path.exists(pdf_path)), 'pdf_filename': pdf_filename, 'pdf_path': pdf_path if os.path.exists(pdf_path) else None, }) if result['pdf_available']: result.update({ 'format': 'pdf', 'mime': 'application/pdf', 'pdf_size_kb': round(os.path.getsize(pdf_path) / 1024, 1), 'pdf_base64': self._artifact_base64(pdf_path), 'artifact_status': 'pdf_ready', 'primary_artifact': 'pdf', 'download_filename': pdf_filename, 'download_mime': 'application/pdf', 'fallback_reason': None, 'user_message': 'PDF report artifact generated.', 'next_action': 'Open the downloaded PDF file for reading, printing, or archiving.', 'delivery': { 'artifact_status': 'pdf_ready', 'format': 'pdf', 'filename': pdf_filename, 'mime': 'application/pdf', 'fallback': False, 'user_message': 'PDF report artifact generated.', 'next_action': 'Open the downloaded PDF file for reading, printing, or archiving.', }, }) else: result['fallback'] = 'html' result['message'] = 'PDF renderer unavailable; HTML artifact generated as fallback.' result['fallback_reason'] = result.get('pdf_error') or 'PDF renderer unavailable' result['artifact_status'] = 'pdf_fallback_html_ready' result['primary_artifact'] = 'html' result['download_filename'] = html_filename result['download_mime'] = 'text/html;charset=utf-8' result['user_message'] = 'PDF renderer unavailable; HTML report artifact generated as fallback.' result['next_action'] = 'Open the downloaded HTML file directly, or print it to PDF from the browser.' result['delivery'] = { 'artifact_status': 'pdf_fallback_html_ready', 'format': 'html', 'filename': html_filename, 'mime': 'text/html;charset=utf-8', 'fallback': True, 'fallback_reason': result['fallback_reason'], 'user_message': result['user_message'], 'next_action': result['next_action'], } return result def _compute_thematic_report(self, body): report_orchestrator = _load_local_module('report_orchestrator') reading_orchestrator = _load_local_module('reading_orchestrator') orchestrator_bridge = _load_local_module('orchestrator_bridge') chart_data = body.get('chart_data') if isinstance(body.get('chart_data'), dict) else body custom_evidence = body.get('evidence') has_custom_evidence = isinstance(custom_evidence, dict) and bool(custom_evidence) derived_context = None if not has_custom_evidence and self._can_derive_thematic_evidence(chart_data): derived_context = self._derive_thematic_evidence(chart_data, report_orchestrator) if derived_context: chart = self._build_thematic_chart_data(derived_context.get('chart_data', chart_data), report_orchestrator) else: chart = self._build_thematic_chart_data(chart_data, report_orchestrator) orchestrator = report_orchestrator.ThematicReportOrchestrator(chart) if has_custom_evidence: self._inject_thematic_evidence(orchestrator, custom_evidence, report_orchestrator) mode = 'custom_evidence' elif derived_context and derived_context.get('evidence'): self._inject_thematic_evidence(orchestrator, derived_context['evidence'], report_orchestrator) mode = 'derived_chart_evidence' else: self._inject_sample_thematic_evidence(orchestrator, report_orchestrator) mode = 'sample_evidence' theme_values = self._requested_thematic_report_themes(body, report_orchestrator) reports = {} for theme in theme_values: report = orchestrator.generate_report(theme) reports[theme.value] = report.to_dict() return { 'success': True, 'endpoint': 'thematic_report', 'source': 'scripts/report_orchestrator.py', 'fragment_sources': [ 'report_orchestrator.py', 'reading_orchestrator.py', 'orchestrator_bridge.py', ], 'workflow_orchestration': self._thematic_workflow_status( reading_orchestrator, orchestrator_bridge, report_orchestrator, theme_values, ), 'mode': mode, 'evidence_source': self._thematic_evidence_source(mode, derived_context, has_custom_evidence), 'themes': reports, 'theme_count': len(reports), 'available_themes': [theme.value for theme in report_orchestrator.ThemeName], 'boundary': '主题化报告用于组织证据、裁决冲突和生成叙事；具体预测仍需本命承诺、Dasha、Transit 与案例验证共同收敛。', } def _thematic_workflow_status(self, reading_orchestrator, orchestrator_bridge, report_orchestrator, theme_values): reading_themes = [] for theme in getattr(reading_orchestrator, 'ReadingTheme'): reading_themes.append({ 'key': theme.value, 'label': theme.name, }) report_themes = [theme.value for theme in getattr(report_orchestrator, 'ThemeName')] selected = [theme.value for theme in theme_values] return { 'stage': 'report_pipeline_bridge', 'reading_theme_count': len(reading_themes), 'reading_themes': reading_themes, 'report_themes': report_themes, 'selected_report_themes': selected, 'bridge': { 'class': getattr(orchestrator_bridge, 'OrchestratorBridge').__name__, 'capabilities': [ 'chapter_to_technique_results', 'inject_dasha_results', 'inject_full_reading_modules', ], }, 'boundary': 'reading_orchestrator 的 registry 执行层尚未绑定到全部实时 API；当前产品路径使用 report_orchestrator 生成报告，并显式声明桥接能力。', } def _requested_thematic_report_themes(self, body, report_orchestrator): raw = body.get('themes', body.get('theme', 'all')) if raw in (None, '', 'all'): values = [theme.value for theme in report_orchestrator.ThemeName] elif isinstance(raw, str): values = [raw] elif isinstance(raw, list): values = raw else: raise BadRequest('theme/themes must be a string, list, or all') mapping = {theme.value: theme for theme in report_orchestrator.ThemeName} themes = [] for value in values: key = str(value).strip().lower() if key not in mapping: raise BadRequest(f'Unknown thematic report theme: {value}') themes.append(mapping[key]) return themes or list(report_orchestrator.ThemeName) def _build_thematic_chart_data(self, raw, report_orchestrator): if not isinstance(raw, dict) or not raw: return report_orchestrator.MockDataFactory.create_sample_chart() birth_chart_data = report_orchestrator.BirthChartData dasha_timeline = self._normalize_thematic_dasha_timeline(raw) return birth_chart_data( d1_houses=self._safe_dict(raw.get('d1_houses') or raw.get('houses')), d9_houses=self._safe_dict(raw.get('d9_houses') or raw.get('navamsa_houses')), d10_houses=self._safe_dict(raw.get('d10_houses') or raw.get('dashamsa_houses')), d2_houses=self._safe_dict(raw.get('d2_houses')), d20_houses=self._safe_dict(raw.get('d20_houses')), d30_houses=self._safe_dict(raw.get('d30_houses')), d60_houses=self._safe_dict(raw.get('d60_houses')), planets=self._safe_dict(raw.get('planets')), current_dasha=self._current_thematic_dasha_label(raw), dasha_timeline=dasha_timeline, yogas=raw.get('yogas') if isinstance(raw.get('yogas'), list) else [], ashtakavarga=self._safe_dict(raw.get('ashtakavarga')), ) def _safe_dict(self, value): return value if isinstance(value, dict) else {} def _current_thematic_dasha_label(self, raw): dasha = raw.get('dasha') if isinstance(raw.get('dasha'), dict) else {} current = dasha.get('current_dasha') if isinstance(dasha.get('current_dasha'), dict) else {} md = dasha.get('current_md') or current.get('mahadasha') or current.get('maha') or current.get('lord') or raw.get('current_md') ad = dasha.get('current_ad') or current.get('antardasha') or current.get('antar') or raw.get('current_ad') if md and ad: return f'{md}-{ad}' return str(md or raw.get('current_dasha') or '') def _normalize_thematic_dasha_timeline(self, raw): dasha = raw.get('dasha') if isinstance(raw.get('dasha'), dict) else {} source = raw.get('dasha_timeline') or dasha.get('timeline') or raw.get('periods') or [] if not isinstance(source, list): return [] timeline = [] for period in source[:24]: if not isinstance(period, dict): continue start_year = self._year_from_any(period.get('start') or period.get('start_date'), datetime.utcnow().year) end_year = self._year_from_any(period.get('end') or period.get('end_date'), start_year + 1) maha = self._thematic_period_lord(period.get('mahadasha') or period.get('maha') or period.get('lord') or period.get('name')) antar = self._thematic_period_lord(period.get('antardasha') or period.get('antar') or period.get('sub_lord')) timeline.append({ 'mahadasha': maha or 'Unknown', 'antardasha': antar or 'Unknown', 'start': start_year, 'end': end_year, }) return timeline def _thematic_period_lord(self, value): if isinstance(value, str) and value.strip(): return value.strip() if isinstance(value, dict): for key in ('lord', 'planet', 'name', 'mahadasha', 'maha', 'antardasha', 'antar'): item = value.get(key) if isinstance(item, str) and item.strip(): return item.strip() return '' def _year_from_any(self, value, default): if isinstance(value, (int, float)): return int(value) match = re.search(r'\d{4}', str(value or '')) return int(match.group(0)) if match else default def _inject_sample_thematic_evidence(self, orchestrator, report_orchestrator): factory = report_orchestrator.MockDataFactory() orchestrator.add_techniques(report_orchestrator.ThemeName.MARRIAGE, factory.create_marriage_techniques()) orchestrator.add_techniques(report_orchestrator.ThemeName.CAREER, factory.create_career_techniques()) orchestrator.add_techniques(report_orchestrator.ThemeName.WEALTH, factory.create_wealth_techniques()) orchestrator.add_techniques(report_orchestrator.ThemeName.HEALTH, factory.create_health_techniques()) orchestrator.add_techniques(report_orchestrator.ThemeName.SPIRITUALITY, factory.create_spirituality_techniques()) def _inject_thematic_evidence(self, orchestrator, evidence, report_orchestrator): theme_map = {theme.value: theme for theme in report_orchestrator.ThemeName} strength_map = {level.value: level for level in report_orchestrator.StrengthLevel} for theme_name, items in evidence.items(): theme = theme_map.get(str(theme_name).strip().lower()) if not theme: raise BadRequest(f'Unknown evidence theme: {theme_name}') if not isinstance(items, list): raise BadRequest('evidence theme values must be arrays') results = [] for index, item in enumerate(items[:40]): if not isinstance(item, dict): raise BadRequest('evidence items must be objects') strength = strength_map.get(str(item.get('strength', 'moderate')).strip().lower(), report_orchestrator.StrengthLevel.MODERATE) results.append(report_orchestrator.TechniqueResult( technique=str(item.get('technique') or f'{theme.value}_evidence_{index + 1}')[:80], chart=str(item.get('chart') or 'D1')[:24], conclusion=str(item.get('conclusion') or item.get('summary') or '未提供结论')[:800], sentiment=str(item.get('sentiment') or 'neutral').strip().lower(), strength=strength, details=item.get('details') if isinstance(item.get('details'), dict) else {}, )) orchestrator.add_techniques(theme, results) def _can_derive_thematic_evidence(self, raw): if not isinstance(raw, dict) or not raw: return False has_birth = all(raw.get(key) is not None for key in ('year', 'month', 'day')) has_planets = isinstance(raw.get('planets'), dict) and bool(raw.get('planets')) return has_birth or has_planets def _derive_thematic_evidence(self, raw, report_orchestrator): warnings = [] module_status = {} def collect(key, fn): try: value = fn() module_status[key] = 'ok' return value except Exception as exc: module_status[key] = 'warning' warnings.append({'module': key, 'error': str(exc)[:240]}) return None has_birth = all(raw.get(key) is not None for key in ('year', 'month', 'day')) full_reading = collect('full_reading', lambda: self._compute_full_reading_for_thematic(raw)) if has_birth else None full_modules = full_reading.get('modules', {}) if isinstance(full_reading, dict) else {} chart = None if full_reading: chart = self._chart_from_full_reading(full_reading) if not chart and has_birth: chart = collect('chart', lambda: self._compute_chart(raw)) if not chart: normalized, _, _ = self._normalized_planets_from_body(raw) chart = { 'success': True, 'planets': normalized, 'ascendant': raw.get('ascendant', SAMPLE_ASCENDANT), 'houses': raw.get('houses', {}), 'dasha': raw.get('dasha', {}), 'yogas': raw.get('yogas', []), 'source': 'provided_planets', } module_status.setdefault('chart', 'provided_planets') payload = dict(raw) payload['planets'] = chart.get('planets') or payload.get('planets') or {} payload['ascendant'] = chart.get('ascendant') or payload.get('ascendant') or SAMPLE_ASCENDANT if chart.get('dasha') and not isinstance(payload.get('dasha'), str): payload['dasha'] = chart.get('dasha') asc_sign = payload.get('asc_sign') or payload['ascendant'].get('sign') or SIGNS[payload['ascendant'].get('sign_idx', 0)] payload['asc_sign'] = asc_sign if asc_sign in SIGNS else SIGNS[0] dasha_payload = {**payload, 'dasha': 'vimshottari'} if chart.get('dasha', {}).get('current_md'): dasha_payload['current_md'] = chart['dasha']['current_md'] dasha = full_modules.get('dasha') or collect('dasha', lambda: self._compute_dasha_system(dasha_payload)) yogas = full_modules.get('yoga') or collect('yogas', lambda: self._compute_yogas_api(payload)) shadbala = full_modules.get('shadbala') or collect('shadbala', lambda: self._compute_shadbala(payload)) ashtakavarga = full_modules.get('ashtakavarga') or collect('ashtakavarga', lambda: self._compute_ashtakavarga(payload)) relationship = collect('relationship', lambda: self._compute_relationship({ **payload, 'dasha_info': self._thematic_dasha_info(chart, dasha), })) career = collect('career', lambda: self._compute_career(payload)) jaimini = full_modules.get('jaimini') or collect('jaimini', lambda: self._compute_jaimini({**payload, 'mode': 'all'})) enriched = { **payload, 'houses': chart.get('houses') or raw.get('houses') or {}, 'dasha': dasha or chart.get('dasha') or {}, 'periods': (dasha or {}).get('periods') or (dasha or {}).get('timeline') or [], 'yogas': chart.get('yogas') or [], 'ashtakavarga': ashtakavarga or {}, } if yogas and isinstance(yogas.get('result'), dict): enriched['yogas'] = list(enriched['yogas']) + (yogas['result'].get('extended_yogas') or []) elif isinstance(yogas, dict): enriched['yogas'] = list(enriched['yogas']) + (yogas.get('yogas') or []) evidence = self._build_derived_thematic_evidence( enriched, dasha=dasha, yogas=yogas, shadbala=shadbala, ashtakavarga=ashtakavarga, relationship=relationship, career=career, jaimini=jaimini, full_reading=full_reading, full_modules=full_modules, report_orchestrator=report_orchestrator, ) return { 'chart_data': enriched, 'evidence': evidence, 'module_status': module_status, 'warnings': warnings, 'evidence_counts': {theme: len(items) for theme, items in evidence.items()}, 'full_reading_used': bool(full_reading), 'full_reading_summary': full_reading.get('summary', {}) if isinstance(full_reading, dict) else {}, 'full_reading_module_count': len(full_modules) if isinstance(full_modules, dict) else 0, } def _thematic_evidence_source(self, mode, derived_context, has_custom_evidence): if mode == 'derived_chart_evidence' and derived_context: full_reading_used = bool(derived_context.get('full_reading_used')) return { 'mode': mode, 'source': 'full_reading_modules' if full_reading_used else 'birth_or_chart_payload', 'sample_fallback': False, 'full_reading_used': full_reading_used, 'full_reading_module_count': derived_context.get('full_reading_module_count', 0), 'full_reading_summary': derived_context.get('full_reading_summary', {}), 'module_status': derived_context.get('module_status', {}), 'warning_count': len(derived_context.get('warnings', [])), 'warnings': derived_context.get('warnings', [])[:6], 'evidence_counts': derived_context.get('evidence_counts', {}), } return { 'mode': mode, 'source': 'caller_evidence' if has_custom_evidence else 'report_orchestrator.MockDataFactory', 'sample_fallback': mode == 'sample_evidence', } def _build_derived_thematic_evidence(self, chart_data, **context): evidence = { 'marriage': [], 'career': [], 'wealth': [], 'health': [], 'spirituality': [], } evidence['marriage'].extend(self._derived_marriage_evidence(chart_data, context)) evidence['career'].extend(self._derived_career_evidence(chart_data, context)) evidence['wealth'].extend(self._derived_wealth_evidence(chart_data, context)) evidence['health'].extend(self._derived_health_evidence(chart_data, context)) evidence['spirituality'].extend(self._derived_spirituality_evidence(chart_data, context)) return evidence def _derived_marriage_evidence(self, chart_data, context): h7 = self._theme_house_snapshot(chart_data, 7) relationship = context.get('relationship') or {} timing = relationship.get('relationship_timing') if isinstance(relationship, dict) else {} full_modules = context.get('full_modules') if isinstance(context.get('full_modules'), dict) else {} items = [ self._theme_evidence( 'D1-7th-house', 'D1', f"第7宫为{h7['sign']}，宫内星体：{h7['planets_label']}；用于判断婚姻承诺与伴侣互动基调。", 'neutral' if h7['planets_label'] == '无' else 'positive', 'moderate', source='chart', details=h7, ), ] spouse = relationship.get('spouse_status_yoga') if isinstance(relationship, dict) else {} if spouse: items.append(self._theme_evidence( 'Spouse-status-yoga', 'D1/D9', spouse.get('summary') or spouse.get('headline') or '配偶状态 Yoga 已由关系引擎计算，可作为婚姻主题证据。', 'positive' if spouse.get('score', 0) and spouse.get('score', 0) >= 50 else 'neutral', 'moderate', source='relationship', details={'fragment': 'spouse_status_yoga.py', 'score': spouse.get('score')}, )) if timing: items.append(self._theme_evidence( 'DK-UL-Dasha timing', 'Dasha', timing.get('summary') or 'DK、UL 与 Dasha 触发已进入婚姻时机证据链。', 'positive' if timing.get('level') in {'strong', 'watch'} else 'neutral', 'strong' if timing.get('level') == 'strong' else 'moderate', source='relationship_timing', details={'fragment': timing.get('source'), 'clues': timing.get('timing_clues', [])}, )) marriage_counting = full_modules.get('marriage_counting') if isinstance(full_modules, dict) else {} if isinstance(marriage_counting, dict) and marriage_counting.get('interpretation'): items.append(self._theme_evidence( 'Marriage-counting', 'D1/D9', marriage_counting.get('interpretation'), 'positive' if (marriage_counting.get('marriage_count') or 0) <= 1 else 'neutral', 'moderate', source='full_reading.modules.marriage_counting', details={ 'marriage_count': marriage_counting.get('marriage_count'), 'd9_marriage_quality': marriage_counting.get('d9_marriage_quality'), }, )) vivah = full_modules.get('vivah_saham') if isinstance(full_modules, dict) else {} if isinstance(vivah, dict) and vivah.get('vivah_saham'): items.append(self._theme_evidence( 'Vivah-saham', 'Tajika', vivah.get('note') or 'Vivah Saham 已由 full-reading 计算，可作为婚姻事件敏感点。', 'neutral', 'moderate', source='full_reading.modules.vivah_saham', details=vivah.get('vivah_saham') if isinstance(vivah.get('vivah_saham'), dict) else vivah, )) return items def _derived_career_evidence(self, chart_data, context): h10 = self._theme_house_snapshot(chart_data, 10) career = context.get('career') or {} shadbala = context.get('shadbala') or {} full_modules = context.get('full_modules') if isinstance(context.get('full_modules'), dict) else {} top_strength = self._top_shadbala_planet(shadbala) items = [ self._theme_evidence( 'D1-10th-house', 'D1', f"第10宫为{h10['sign']}，宫内星体：{h10['planets_label']}；这是事业角色、名望与外在职责的主轴。", 'positive' if h10['planets'] else 'neutral', 'moderate', source='chart', details=h10, ), ] if career: items.append(self._theme_evidence( 'Career-engine', 'D1', self._first_text_from_dict(career, ['summary', 'career_summary', 'dominant_theme', 'recommendation']) or '事业引擎已根据行星与上升星座生成职业倾向。', 'positive', 'moderate', source='career_analysis.py', details={'keys': sorted(career.keys())[:10]}, )) if top_strength: items.append(self._theme_evidence( 'Shadbala-career-support', 'Strength', f"Shadbala 排名中 {top_strength['planet']} 支持度最高（{top_strength['rupas']} rupas），可作为事业执行力/资源侧证。", 'positive', 'moderate', source='shadbala', details=top_strength, )) convergence = full_modules.get('dasa_convergence') if isinstance(full_modules, dict) else {} top_domains = convergence.get('top_convergent_domains') if isinstance(convergence, dict) else [] career_domain = next( ( row for row in top_domains if isinstance(row, dict) and any(token in str(row.get('domain', '')).lower() for token in ('career', 'profession', 'status', 'work')) ), None, ) if not career_domain and isinstance(convergence.get('domain_activations'), dict): for domain, row in convergence['domain_activations'].items(): if any(token in str(domain).lower() for token in ('career', 'profession', 'status', 'work')): career_domain = {'domain': domain, **(row if isinstance(row, dict) else {})} break if career_domain: items.append(self._theme_evidence( 'Dasa-convergence-career', 'Multi-Dasha', career_domain.get('interpretation') or '多 Dasha 收敛模块已命中事业相关领域，需结合 Transit 确认兑现窗口。', 'positive', 'strong' if career_domain.get('convergence_level') in {'L2', 'L3'} else 'moderate', source='full_reading.modules.dasa_convergence', details=career_domain, )) return items def _derived_wealth_evidence(self, chart_data, context): h2 = self._theme_house_snapshot(chart_data, 2) h11 = self._theme_house_snapshot(chart_data, 11) ashtakavarga = context.get('ashtakavarga') or {} av_summary = self._ashtakavarga_summary_for_theme(ashtakavarga) full_modules = context.get('full_modules') if isinstance(context.get('full_modules'), dict) else {} items = [ self._theme_evidence( '2nd-and-11th-house', 'D1', f"第2宫({h2['sign']})与第11宫({h11['sign']})共同描述收入、积累与收益网络。", 'neutral', 'moderate', source='chart', details={'second': h2, 'eleventh': h11}, ), ] if av_summary: strongest = av_summary.get('strongest_houses') or [] wealth_hit = any(row.get('house') in (2, 11) for row in strongest) items.append(self._theme_evidence( 'Ashtakavarga-wealth', 'AV', av_summary.get('headline') or 'Ashtakavarga 已生成财富宫位支持度。', 'positive' if wealth_hit else 'neutral', 'strong' if wealth_hit else 'moderate', source='ashtakavarga', details={'strongest_houses': strongest, 'sav_total': av_summary.get('sav_total')}, )) yogas_doshas = full_modules.get('yogas_doshas') if isinstance(full_modules, dict) else {} dhana = yogas_doshas.get('dhana_yogas') if isinstance(yogas_doshas, dict) else {} dhana_yogas = dhana.get('yogas') if isinstance(dhana, dict) else [] if dhana_yogas: items.append(self._theme_evidence( 'Dhana-yoga-full-reading', 'D1', dhana.get('summary') or f"full-reading 检出 {len(dhana_yogas)} 条 Dhana Yoga，可作为财富主题的直接证据。", 'positive', 'strong' if any(row.get('strength') == 'strong' for row in dhana_yogas if isinstance(row, dict)) else 'moderate', source='full_reading.modules.yogas_doshas', details={'yogas': dhana_yogas[:4]}, )) return items def _derived_health_evidence(self, chart_data, context): h6 = self._theme_house_snapshot(chart_data, 6) h8 = self._theme_house_snapshot(chart_data, 8) h12 = self._theme_house_snapshot(chart_data, 12) yogas = context.get('yogas') or {} curse = ((yogas.get('result') or {}).get('curse_yogas') or {}) if isinstance(yogas, dict) else {} risk = curse.get('overall_risk') full_modules = context.get('full_modules') if isinstance(context.get('full_modules'), dict) else {} items = [ self._theme_evidence( '6-8-12-health-axis', 'D1', f"健康轴线：6宫{h6['sign']}、8宫{h8['sign']}、12宫{h12['sign']}，用于观察疾病、突发与消耗主题。", 'negative' if any(row['planets'] for row in (h6, h8, h12)) else 'neutral', 'moderate', source='chart', details={'sixth': h6, 'eighth': h8, 'twelfth': h12}, ), ] if risk: items.append(self._theme_evidence( 'Curse-yoga-risk', 'D1', f"凶星合相风险层返回 {risk}，作为健康/压力主题的高风险提示证据之一。", 'negative' if risk in {'high', 'medium'} else 'neutral', 'moderate', source='curse_yoga_detector.py', details={'risk': risk, 'detected': curse.get('curses_detected', [])[:4]}, )) validation = full_modules.get('validation') if isinstance(full_modules, dict) else {} if isinstance(validation, dict) and validation.get('checked'): items.append(self._theme_evidence( 'Calculation-validation-gate', 'Validation', f"full-reading 完成 {validation.get('checked')} 项计算校验，通过 {validation.get('passed')} 项；健康判断可基于已校验星盘继续审慎解释。", 'positive' if validation.get('valid') else 'negative', 'strong' if validation.get('valid') else 'moderate', source='full_reading.modules.validation', details={ 'valid': validation.get('valid'), 'passed': validation.get('passed'), 'failed': validation.get('failed'), }, )) trimshamsa = full_modules.get('trimshamsa_d30') if isinstance(full_modules, dict) else {} crisis = trimshamsa.get('marriage_crisis') if isinstance(trimshamsa, dict) else None if crisis: items.append(self._theme_evidence( 'Trimshamsa-D30-risk', 'D30', 'D30 Trimshamsa 已进入压力/危机侧证；健康主题需把风险提示与现实医疗信息分开处理。', 'negative' if isinstance(crisis, dict) and crisis.get('risk_level') in {'high', 'medium'} else 'neutral', 'moderate', source='full_reading.modules.trimshamsa_d30', details=crisis if isinstance(crisis, dict) else {'crisis': crisis}, )) return items def _derived_spirituality_evidence(self, chart_data, context): h9 = self._theme_house_snapshot(chart_data, 9) h12 = self._theme_house_snapshot(chart_data, 12) planets = chart_data.get('planets') if isinstance(chart_data.get('planets'), dict) else {} jupiter = planets.get('Jupiter', {}) if isinstance(planets.get('Jupiter'), dict) else {} ketu = planets.get('Ketu', {}) if isinstance(planets.get('Ketu'), dict) else {} jaimini = context.get('jaimini') or {} karakamsha = self._extract_jaimini_karakamsha(jaimini) full_modules = context.get('full_modules') if isinstance(context.get('full_modules'), dict) else {} items = [ self._theme_evidence( '9th-and-12th-spirit', 'D1', f"第9宫({h9['sign']})与第12宫({h12['sign']})显示信念、导师、修行与出离倾向。", 'positive' if h9['planets'] or h12['planets'] else 'neutral', 'moderate', source='chart', details={'ninth': h9, 'twelfth': h12}, ), self._theme_evidence( 'Jupiter-Ketu-spiritual-karaka', 'D1', f"Jupiter 位于{jupiter.get('sign', '未知')}第{jupiter.get('house', '-')}宫，Ketu 位于{ketu.get('sign', '未知')}第{ketu.get('house', '-')}宫。", 'positive' if jupiter.get('house') in (1, 5, 9, 12) or ketu.get('house') in (9, 12) else 'neutral', 'moderate', source='chart', details={'Jupiter': jupiter, 'Ketu': ketu}, ), ] if karakamsha: items.append(self._theme_evidence( 'Karakamsha', 'D9/D1', karakamsha.get('interpretation') or karakamsha.get('description') or 'Karakamsha 已由 Jaimini 模块计算，用于灵性使命与内在驱动力。', 'positive', 'moderate', source='jaimini.py', details=karakamsha, )) d20 = self._extract_vimsamsa_spiritual_context(full_modules) if d20: items.append(self._theme_evidence( 'Vimsamsa-D20-spiritual-context', 'D20', d20.get('summary') or 'D20 Vimsamsa 分盘已进入灵性主题证据链，用于观察修行、信念与内在追求。', 'positive', 'moderate', source=d20.get('source', 'full_reading.modules.varga_full'), details=d20, )) return items def _theme_evidence(self, technique, chart, conclusion, sentiment, strength, *, source, details=None): return { 'technique': technique, 'chart': chart, 'conclusion': str(conclusion)[:800], 'sentiment': sentiment, 'strength': strength, 'details': { **(details if isinstance(details, dict) else {}), 'source': source, 'derived': True, }, } def _theme_house_snapshot(self, chart_data, house_num): houses = chart_data.get('houses') if isinstance(chart_data.get('houses'), dict) else {} house = houses.get(house_num) or houses.get(str(house_num)) or {} asc = chart_data.get('ascendant') if isinstance(chart_data.get('ascendant'), dict) else {} if house.get('sign'): sign = house.get('sign') else: asc_idx = self._sign_idx_from_value(asc.get('sign_idx', asc.get('sign')), 0) sign = SIGNS[(asc_idx + house_num - 1) % 12] planets = [] for planet, pdata in (chart_data.get('planets') or {}).items(): if isinstance(pdata, dict) and pdata.get('house') == house_num: planets.append(planet) return { 'house': house_num, 'sign': sign, 'planets': planets, 'planets_label': '、'.join(planets) if planets else '无', } def _top_shadbala_planet(self, shadbala): if not isinstance(shadbala, dict): return None result = shadbala.get('result') if isinstance(shadbala.get('result'), dict) else shadbala planets = result.get('planets') if isinstance(result, dict) else {} rows = [] for planet, data in (planets or {}).items(): if not isinstance(data, dict): continue rupas = data.get('total_rupas', data.get('rupas')) if isinstance(rupas, (int, float)): rows.append({'planet': planet, 'rupas': round(rupas, 2)}) rows.sort(key=lambda row: row['rupas'], reverse=True) return rows[0] if rows else None def _ashtakavarga_summary_for_theme(self, ashtakavarga): if not isinstance(ashtakavarga, dict): return {} summary = ashtakavarga.get('summary') if isinstance(summary, dict) and summary: return summary sav = ashtakavarga.get('sav') if isinstance(ashtakavarga.get('sav'), dict) else {} scores = sav.get('scores') if isinstance(sav.get('scores'), dict) else {} if not scores: return {} rows = [] for sign, score in scores.items(): if not isinstance(score, (int, float)): continue sign_idx = SIGNS.index(sign) if sign in SIGNS else None house = sign_idx + 1 if sign_idx is not None else None rows.append({'sign': sign, 'house': house, 'score': score}) rows.sort(key=lambda row: row['score'], reverse=True) total = sum(row['score'] for row in rows) return { 'headline': 'Ashtakavarga SAV 已由 full-reading 计算，财富宫位以第2/11宫支持度为重点。', 'strongest_houses': rows[:4], 'sav_total': total, 'source': 'full_reading.modules.ashtakavarga', } def _extract_jaimini_karakamsha(self, jaimini): if not isinstance(jaimini, dict): return {} result = jaimini.get('result') if isinstance(jaimini.get('result'), dict) else jaimini karakamsha = result.get('karakamsha') if isinstance(result, dict) else {} return karakamsha if isinstance(karakamsha, dict) else {} def _extract_vimsamsa_spiritual_context(self, full_modules): if not isinstance(full_modules, dict): return {} varga = full_modules.get('varga_full') if not isinstance(varga, dict): return {} d20 = varga.get('D20_Vimsamsa') or varga.get('D20') or varga.get('Vimsamsa') if not isinstance(d20, dict): return {} placements = [] for planet in ('Jupiter', 'Ketu', 'Moon', 'Sun', 'Ascendant'): pdata = d20.get(planet) if isinstance(pdata, dict): placements.append({ 'planet': planet, 'sign': pdata.get('sign'), 'house': pdata.get('house') or pdata.get('house_in_d20'), 'dignity': pdata.get('dignity'), }) if not placements: return {} return { 'summary': 'D20 Vimsamsa 已从 full-reading 分盘层读取，Jupiter/Ketu/Moon/Sun/Ascendant 作为灵性主题侧证。', 'placements': placements, 'source': 'full_reading.modules.varga_full', } def _first_text_from_dict(self, value, keys): if not isinstance(value, dict): return '' for key in keys: item = value.get(key) if isinstance(item, str) and item.strip(): return item.strip() if isinstance(item, dict): nested = self._first_text_from_dict(item, keys) if nested: return nested return '' def _thematic_dasha_info(self, chart, dasha): current = {} if isinstance(chart.get('dasha'), dict): current.update(chart['dasha']) analysis = dasha.get('vimshottari_analysis') if isinstance(dasha, dict) else None if isinstance(analysis, dict): md = ((analysis.get('current') or {}).get('mahadasha') or {}).get('lord') ad = ((analysis.get('current') or {}).get('antardasha') or {}).get('lord') if md: current['maha_dasha'] = md if ad: current['antar_dasha'] = ad return current def _parse_birth_datetime(self, body): year = self._get_int(body, 'year', 1990, 1800, 2400) month = self._get_int(body, 'month', 6, 1, 12) day = self._get_int(body, 'day', 15, 1, 31) hour = self._get_float(body, 'hour', 12, 0, 23) minute = self._get_float(body, 'minute', 0, 0, 59) second = self._get_birth_second(body) try: return datetime(year, month, day, int(hour), int(minute), int(second)) except ValueError as e: raise BadRequest('Invalid birth date') from e def _compute_full_reading_for_thematic(self, body): engine = _load_local_module('jyotish_engine') year = self._get_int(body, 'year', 1990, 1800, 2400) month = self._get_int(body, 'month', 6, 1, 12) day = self._get_int(body, 'day', 15, 1, 31) hour = self._get_float(body, 'hour', 12, 0, 23) minute = self._get_float(body, 'minute', 0, 0, 59) second = self._get_birth_second(body) lat = self._get_float(body, 'lat', 39.9, -90, 90) lon = self._get_float(body, 'lon', 116.4, -180, 180) tz = self._parse_timezone(body, lat, lon, year, month, day, hour, minute, second) try: datetime(year, month, day, int(hour), int(minute), int(second)) except ValueError as e: raise BadRequest('Invalid birth date') from e node_mode = body.get('node_mode', body.get('nodeMode', 'mean')) if not isinstance(node_mode, str) or node_mode not in {'mean', 'true'}: node_mode = 'mean' args = type('Args', (), { 'year': year, 'month': month, 'day': day, 'hour': int(hour), 'minute': int(minute), 'second': int(second), 'lat': lat, 'lon': lon, 'tz': tz, 'node_mode': node_mode, 'ayanamsa': body.get('ayanamsa', 'lahiri'), 'age': body.get('age'), 'today': body.get('today') or body.get('current_date'), 'transit_date': body.get('transit_date'), 'target_year': body.get('target_year'), })() result = engine.cmd_full_reading(args) if not isinstance(result, dict) or not isinstance(result.get('modules'), dict): raise BadRequest('full-reading did not return modules') return result def _chart_from_full_reading(self, full_reading): if not isinstance(full_reading, dict): return None modules = full_reading.get('modules') if isinstance(full_reading.get('modules'), dict) else {} chart = full_reading.get('chart') if isinstance(full_reading.get('chart'), dict) else modules.get('chart') if not isinstance(chart, dict) or not isinstance(chart.get('planets'), dict): return None normalized = dict(chart) normalized['success'] = True normalized['planets'] = chart.get('planets') or {} normalized['ascendant'] = chart.get('ascendant') or SAMPLE_ASCENDANT normalized['houses'] = chart.get('houses') or modules.get('house_map') or {} normalized['dasha'] = modules.get('dasha') or chart.get('dasha') or {} yoga_module = modules.get('yoga') if isinstance(modules.get('yoga'), dict) else {} normalized['yogas'] = ( chart.get('yogas') or yoga_module.get('yogas') or yoga_module.get('detected_yogas') or [] ) normalized['ashtakavarga'] = modules.get('ashtakavarga') or chart.get('ashtakavarga') or {} normalized['shadbala'] = modules.get('shadbala') or chart.get('shadbala') or {} normalized['birth'] = chart.get('birth_info') or full_reading.get('birth_info') or {} normalized['source'] = 'full_reading.modules.chart' return normalized def _sign_idx_from_value(self, value, default=0): if isinstance(value, str): if value not in SIGNS: raise BadRequest('sign must be a valid sign') return SIGNS.index(value) try: idx = int(value) except (TypeError, ValueError): return default return max(0, min(11, idx)) def _planet_lon(self, planets, planet): data = planets.get(planet, {}) if isinstance(planets, dict) else {} if not isinstance(data, dict): return None lon = data.get('lon') if isinstance(lon, (int, float)) and math.isfinite(lon): return lon % 360 sign_idx = data.get('sign_idx') if sign_idx is None and data.get('sign') in SIGNS: sign_idx = SIGNS.index(data['sign']) degree = data.get('degree', data.get('degree_in_sign', 0)) try: return (int(sign_idx) * 30 + float(degree)) % 360 except (TypeError, ValueError): return None def _fallback_dasha_periods(self, birth_dt, dasha_key, info): extended_dashas = _load_local_module('extended_dashas') DASHA_ORDER = extended_dashas.DASHA_ORDER cycle_years = float(info.get('years') or 36) if cycle_years <= 0: cycle_years = 36 period_years = round(cycle_years / len(DASHA_ORDER), 2) periods = [] current = birth_dt for lord in DASHA_ORDER: end_date = current + timedelta(days=period_years * 365.25636) periods.append({ 'lord': lord, 'years': period_years, 'start': current.strftime('%Y-%m-%d'), 'end': end_date.strftime('%Y-%m-%d'), }) current = end_date return periods def _import_chart_text(self, body): filename = str(body.get('filename', ''))[:160] text = body.get('text') content_b64 = body.get('content_base64') if text is not None: if not isinstance(text, str): raise BadRequest('text must be a string') return self._import_text_response(text, filename, 'text') if content_b64 is None: raise BadRequest('text or content_base64 is required') if not isinstance(content_b64, str): raise BadRequest('content_base64 must be a string') try: data = base64.b64decode(content_b64, validate=True) except Exception as e: raise BadRequest('Invalid base64 content') from e if len(data) > MAX_IMPORT_FILE_BYTES: raise BadRequest(f'Import file too large; max {MAX_IMPORT_FILE_BYTES} bytes') is_pdf = filename.lower().endswith('.pdf') or data.startswith(b'%PDF') if is_pdf: text, extractor = self._extract_pdf_text(data) else: text = data.decode('utf-8', errors='ignore') extractor = 'text' return self._import_text_response(text, filename, extractor) def _import_text_response(self, text, filename, extractor): normalized = str(text or '').replace('\x00', '').strip() if not normalized: raise BadRequest('No extractable text found') truncated = len(normalized) > MAX_IMPORT_TEXT_CHARS if truncated: normalized = normalized[:MAX_IMPORT_TEXT_CHARS] return { 'success': True, 'filename': filename, 'extractor': extractor, 'text': normalized, 'text_length': len(normalized), 'truncated': truncated, } def _extract_pdf_text(self, data): errors = [] try: import pdfplumber with pdfplumber.open(io.BytesIO(data)) as pdf: text = '\n'.join((page.extract_text() or '') for page in pdf.pages[:12]) if text.strip(): return text, 'pdfplumber' except Exception as e: errors.append(str(e)) try: from pypdf import PdfReader reader = PdfReader(io.BytesIO(data)) text = '\n'.join((page.extract_text() or '') for page in reader.pages[:12]) if text.strip(): return text, 'pypdf' except Exception as e: errors.append(str(e)) raise BadRequest('PDF has no extractable text; OCR is not supported yet') def _calc_vimshottari_periods(self, birth_dt, moon_lon): extended_dashas = _load_local_module('extended_dashas') DASHA_ORDER = extended_dashas.DASHA_ORDER YEAR_DAYS = extended_dashas.YEAR_DAYS dasha_years = [7, 20, 6, 10, 7, 18, 16, 19, 17] nak_size = 360 / 27 nak_idx = int(moon_lon / nak_size) % 27 start_idx = nak_idx % len(DASHA_ORDER) current = birth_dt periods = [] for i in range(len(DASHA_ORDER)): idx = (start_idx + i) % len(DASHA_ORDER) years = dasha_years[idx] end_date = current + timedelta(days=years * YEAR_DAYS) periods.append({ 'lord': DASHA_ORDER[idx], 'years': years, 'start': current.strftime('%Y-%m-%d'), 'end': end_date.strftime('%Y-%m-%d'), }) current = end_date return periods def _compute_chart(self, body): """完整星盘计算""" year = self._get_int(body, 'year', 1990, 1800, 2400) month = self._get_int(body, 'month', 6, 1, 12) day = self._get_int(body, 'day', 15, 1, 31) hour = self._get_float(body, 'hour', 12, 0, 23) minute = self._get_float(body, 'minute', 0, 0, 59) second = self._get_birth_second(body) lat = self._get_float(body, 'lat', 39.9, -90, 90) lon = self._get_float(body, 'lon', 116.4, -180, 180) tz = self._parse_timezone(body, lat, lon, year, month, day, hour, minute, second) try: datetime(year, month, day, int(hour), int(minute), int(second)) except ValueError as e: raise BadRequest('Invalid birth date') from e try: import swisseph as swe swe.set_ephe_path(os.path.join(SCRIPTS_DIR, '..', 'swiss_ephemeris')) birth_hour_decimal = self._birth_hour_decimal(hour, minute, second) hour_ut = birth_hour_decimal - tz jd = swe.julday(year, month, day, hour_ut) ayanamsa_name = body.get('ayanamsa', 'lahiri') try: from jyotish_engine import _apply_ayanamsa, _ayanamsa_display_name _apply_ayanamsa(ayanamsa_name) ayanamsa_display = _ayanamsa_display_name(ayanamsa_name) except ImportError: swe.set_sid_mode(swe.SIDM_LAHIRI, 0, 0) ayanamsa_name = 'lahiri' ayanamsa_display = 'Lahiri' ayanamsa = swe.get_ayanamsa(jd) planets_data = {} planet_ids = {'Sun': 0, 'Moon': 1, 'Mars': 4, 'Mercury': 2, 'Jupiter': 5, 'Venus': 3, 'Saturn': 6, 'Rahu': 10, 'Ketu': 20} planet_names_rev = {v: k for k, v in planet_ids.items()} for pid, pname in planet_names_rev.items(): if pid == 20: rahu_result, _ = swe.calc_ut(jd, 10) planet_lon = (rahu_result[0] - ayanamsa + 180) % 360 else: result, _ = swe.calc_ut(jd, pid) planet_lon = (result[0] - ayanamsa) % 360 sign_idx = int(planet_lon / 30) % 12 planets_data[pname] = {'lon': planet_lon, 'sign_idx': sign_idx, 'sign': SIGNS[sign_idx], 'degree': planet_lon % 30} # Ascendant asc_tropical = swe.houses_ex(jd, lat, lon, b'E')[0][0] % 360 asc_lon = (asc_tropical - ayanamsa) % 360 asc_sign_idx = int(asc_lon / 30) % 12 asc_sign = SIGNS[asc_sign_idx] # Houses houses = {} for h in range(1, 13): s = (asc_sign_idx + h - 1) % 12 houses[h] = {'sign': SIGNS[s], 'sign_idx': s} # Planet houses for pn, pd in planets_data.items(): pd['house'] = ((pd['sign_idx'] - asc_sign_idx) % 12) + 1 # Dasha (simplified Vimshottari) moon_lon = planets_data['Moon']['lon'] nak_size = 360/27 nak_idx = int(moon_lon / nak_size) dasha_lords = ['Ketu','Venus','Sun','Moon','Mars','Rahu','Jupiter','Saturn','Mercury'] dasha_years = [7,20,6,10,7,18,16,19,17] nak_lord_idx = nak_idx % 9 md_lord = dasha_lords[nak_lord_idx] total_years = dasha_years[nak_lord_idx] elapsed = (moon_lon % nak_size) / nak_size * total_years remaining = total_years - elapsed birth_dt = datetime(year, month, day, int(hour), int(minute), int(second)) elapsed_days = elapsed * 365.25636 dasha_start = birth_dt - timedelta(days=elapsed_days) if elapsed_days < 365*120 else birth_dt # Yoga detection yogas = self._detect_yogas(planets_data, asc_sign_idx) # Sade Sati from sade_sati import calc_sade_sati_complete # Transit Saturn (approximate) saturn_year_progress = (year - 2026) * 12 / 30 # ~12 signs in 30 years transit_saturn_sign = (planets_data['Saturn']['sign_idx'] + int(saturn_year_progress)) % 12 transit_saturn_lon = transit_saturn_sign * 30 + 15 sade_sati = calc_sade_sati_complete(moon_lon, asc_lon, transit_saturn_lon) # Dasha清单 extended_dashas = _load_local_module('extended_dashas') dashas = extended_dashas.get_available_dashas() dasha_list = [{'key': k, 'name': extended_dashas.DASHA_REGISTRY[k]['name'], 'years': extended_dashas.DASHA_REGISTRY[k]['years'], 'type': extended_dashas.DASHA_REGISTRY[k]['type']} for k in dashas] try: jaimini = _load_local_module('jaimini') special_lagnas = jaimini.calc_special_lagnas_precise( asc_sign_idx, year, month, day, int(hour), minute + second / 60.0, lat, lon, tz ) except Exception as e: import logging logging.warning(f"[api_server] special lagnas calculation failed: {e}") special_lagnas = {} # Shadbala (v6.9.15: absolute component sum, no global 1200 downscaling) try: from shadbala import calc_shadbala sb = calc_shadbala( planets_data, asc_sign, birth_hour_decimal, planets_data.get('Sun',{}).get('lon',0), moon_lon, ) shadbala_summary = {p: {'rupas': round(d['total_rupas'],2), 'level': d['strength_level']} for p,d in sb.get('planets',{}).items()} except Exception as e: import logging logging.warning(f"[api_server] shadbala calculation failed: {e}") shadbala_summary = {} try: remedies_module = _load_local_module('remedies') remedies = remedies_module.recommend_remedies(shadbala_summary, active_dasha_lord=md_lord) except Exception as e: import logging logging.warning(f"[api_server] remedies calculation failed: {e}") remedies = {} try: tithi_analyzer = _load_local_module('tithi_analyzer') tithi_lord_analysis = tithi_analyzer.analyze_tithi({'planets': planets_data}) except Exception as e: import logging logging.warning(f"[api_server] tithi lord analysis failed: {e}") tithi_lord_analysis = {} # Yoga扩展 (dashaflow MIT规则) try: from yoga_expansion import detect_all_yogas as detect_ey for ey in detect_ey(planets_data, asc_sign): yogas.append({'name': ey.get('name',''), 'planets': ey.get('planets',[]), 'desc': ey.get('description','')[:80], 'cat': 'extended'}) except Exception as e: import logging logging.warning(f"[api_server] yoga expansion detection failed: {e}") result = { 'success': True, 'version': '6.9.15', 'birth': { 'date': f'{year}-{month:02d}-{day:02d}', 'time': self._format_birth_time(hour, minute, second), 'hour': int(hour), 'minute': int(minute), 'second': int(second), 'tz': f"UTC{'+' if tz >= 0 else ''}{tz}", 'lat': lat, 'lon': lon, 'julian_day': round(jd, 6), 'ayanamsa': round(ayanamsa, 4), 'ayanamsa_name': ayanamsa_name, 'ayanamsa_display': ayanamsa_display, 'node_mode': body.get('node_mode', body.get('nodeMode', 'mean')), }, 'ascendant': { 'sign': asc_sign, 'sign_idx': asc_sign_idx, 'degree': round(asc_lon % 30, 2), 'degree_in_sign': round(asc_lon % 30, 2), 'lon': round(asc_lon, 4), }, 'planets': planets_data, 'houses': houses, 'shadbala': shadbala_summary, 'dasha': { 'current_md': md_lord, 'remaining_years': round(remaining, 2), 'total_years': total_years, 'start_date': dasha_start.isoformat() if hasattr(dasha_start, 'isoformat') else str(dasha_start), }, 'yogas': yogas, 'sade_sati': sade_sati, 'remedies': remedies, 'tithi_lord_analysis': tithi_lord_analysis, 'special_lagnas': special_lagnas, 'available_dashas': dasha_list, 'dasha_count': len(dasha_list), } result['ai_prompt_pack'] = self._build_chart_prompt_pack(result) return result except ImportError: return self._fallback_chart(year, month, day, hour, minute, second, lat, lon, tz) def _fallback_chart(self, year, month, day, hour, minute, second, lat, lon, tz): """无Swiss Ephemeris时的简化计算""" import hashlib seed = int(hashlib.md5(f"{year}{month}{day}{hour}{minute}{second}{lat}{lon}".encode()).hexdigest()[:8], 16) asc_sign_idx = seed % 12 asc_sign = SIGNS[asc_sign_idx] planets = {} planet_names = ['Sun','Moon','Mars','Mercury','Jupiter','Venus','Saturn','Rahu','Ketu'] import random rng = random.Random(seed) for pn in planet_names: sign_idx = (asc_sign_idx + rng.randint(0, 11)) % 12 deg = rng.uniform(0, 30) planets[pn] = { 'sign': SIGNS[sign_idx], 'sign_idx': sign_idx, 'degree': deg, 'lon': sign_idx * 30 + deg, 'house': ((sign_idx - asc_sign_idx) % 12) + 1, } houses = {} for h in range(1, 13): s = (asc_sign_idx + h - 1) % 12 houses[h] = {'sign': SIGNS[s], 'sign_idx': s} try: jaimini = _load_local_module('jaimini') special_lagnas = jaimini.calc_special_lagnas_precise( asc_sign_idx, year, month, day, int(hour), minute + second / 60.0, lat, lon, tz ) except Exception: jaimini = _load_local_module('jaimini') special_lagnas = jaimini.calc_special_lagnas(asc_sign_idx, int(hour), minute + second / 60.0) result = { 'success': True, 'version': '6.9.15-fallback', 'warning': 'Swiss Ephemeris未安装，使用简化计算', 'birth': { 'date': f'{year}-{month:02d}-{day:02d}', 'time': self._format_birth_time(hour, minute, second), 'hour': int(hour), 'minute': int(minute), 'second': int(second), 'tz': f"UTC{'+' if tz >= 0 else ''}{tz}", 'lat': lat, 'lon': lon, }, 'ascendant': {'sign': asc_sign, 'sign_idx': asc_sign_idx}, 'planets': planets, 'houses': houses, 'dasha': {'current_md': 'Moon', 'remaining_years': 5}, 'yogas': [], 'sade_sati': {'active': False}, 'tithi_lord_analysis': _load_local_module('tithi_analyzer').analyze_tithi({'planets': planets}), 'special_lagnas': special_lagnas, 'available_dashas': [], 'dasha_count': 0, } result['ai_prompt_pack'] = self._build_chart_prompt_pack(result) return result def _build_chart_prompt_pack(self, chart): birth = chart.get('birth') or chart.get('birth_info') or {} ascendant = chart.get('ascendant') or {} planets = chart.get('planets') or {} dasha = chart.get('dasha') or {} shadbala = chart.get('shadbala') or {} functional_layer = self._functional_benefic_malefic_snapshot(planets, ascendant) top_strength = sorted( [ { 'planet': planet, 'rupas': pdata.get('rupas'), 'level': pdata.get('level'), } for planet, pdata in shadbala.items() if isinstance(pdata, dict) ], key=lambda row: row.get('rupas') if isinstance(row.get('rupas'), (int, float)) else -1, reverse=True, )[:7] core_planets = { planet: { 'sign': pdata.get('sign'), 'degree': pdata.get('degree'), 'house': pdata.get('house'), 'lon': pdata.get('lon'), } for planet, pdata in planets.items() if planet in {'Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn', 'Rahu', 'Ketu'} and isinstance(pdata, dict) } ayanamsa_display = birth.get('ayanamsa_display') or 'Lahiri' node_mode = birth.get('node_mode') or 'mean' prompt_lines = [ '你是一个审慎的 AI Native 印度/吠陀占星分析助手。', '请只基于 evidence_snapshot 中的计算证据生成解读，不要编造星盘不存在的配置。', f'本盘使用 {ayanamsa_display} ayanamsa，节点口径为 {node_mode}。', '不要仅凭单一配置下结论；核心判断至少交叉 D1、D9、Dasha、Shadbala/Ashtakavarga 或 Transit 中的两个证据层。', '必须显式标注置信度和边界：Dasha/PDF 起点差异、Shadbala 外部绝对值 oracle 尚未完成时，不得声称已经完全校准。', ] oracle_progress = { 'scope': 'external_oracle_evidence_validation', 'collection_queue': 'external_oracle_collection_queue', 'total_packets': 5, 'valid_packets': 0, 'ready_for_calibration': 0, 'production_tuning_allowed': False, 'artifact_policy': 'references/oracle/artifacts/', 'promotion_rule': 'external_verified requires source_artifact, filled target values, and non-local-engine external evidence.', 'boundary': 'Dasha/Shadbala absolute values are not externally calibrated until enough packets pass validation.', } return { 'schema_version': 1, 'mode': 'jyotish_structured_prompt_pack', 'prompt_zh': '\n'.join(prompt_lines), 'evidence_snapshot': { 'birth': birth, 'ayanamsa': { 'name': birth.get('ayanamsa_name', 'lahiri'), 'display': ayanamsa_display, 'value': birth.get('ayanamsa'), 'node_mode': node_mode, }, 'core': { 'ascendant': ascendant, **core_planets, }, 'timing': { 'current_mahadasha': dasha.get('current_md') or dasha.get('maha_dasha'), 'remaining_years': dasha.get('remaining_years'), 'start_date': dasha.get('start_date'), }, 'strength': { 'shadbala_ranking': top_strength, }, 'functional_benefic_malefic': functional_layer, 'quality_boundary': { 'external_oracle_status': 'D1/D9/VedAstro longitude boundary covered; Dasha/Shadbala external absolute calibration still requires multi-source oracle expansion.', }, 'oracle_progress': oracle_progress, }, 'retrieval_plan': { 'local_reference_docs': [ 'references/ai-reading-workflow-prompt.md', 'references/comprehensive-reading-workflow.md', 'references/prediction-boundary-protocol.md', 'references/dasa-convergence-methodology.md', 'references/shadbala-interpretation-methodology.md', 'references/navamsa-d9-interpretation-template.md', ], 'retrieval_tags': [ 'no_single_factor_conclusion', 'd1_d9_dasha_cross_validation', 'oracle_boundary_visible', 'external_oracle_evidence_validation', 'confidence_labeled_reading', ], }, } def _functional_benefic_malefic_snapshot(self, planets, ascendant): try: from functional_benefics import derive_functional_benefic_malefic asc_sign = ascendant.get('sign') return derive_functional_benefic_malefic(asc_sign) except Exception as exc: return { 'status': 'blocked', 'ascendant': ascendant.get('sign'), 'functional_benefics': [], 'functional_malefics': [], 'functional_neutrals': [], 'yogakarakas': [], 'owned_houses': {}, 'effect_on_confidence': f'未完成功能性吉凶星判定，需降低高严谨结论置信度: {exc}', 'source': 'strict_functional_benefic_malefic_v1', } def _detect_yogas(self, planets, asc_idx): yogas = [] KENDRA = {1,4,7,10} try: from pancha_mahapurusha import detect_pancha_mahapurusha pmc = detect_pancha_mahapurusha(planets) for y in pmc: if y['is_valid']: yogas.append({'name': y['name'], 'planets': [y['planet']], 'category': 'PMC'}) except Exception as e: import logging logging.warning(f"[api_server] pancha_mahapurusha detection failed: {e}") try: from yoga_expansion import detect_all_yogas as detect_yogas_ext for y in detect_yogas_ext(planets, SIGNS[asc_idx]): yogas.append({'name': y.get('name',''), 'planets': y.get('planets',[]), 'category': 'extended'}) except Exception as e: import logging logging.warning(f"[api_server] yoga expansion in _detect_yogas failed: {e}") return yogas[:10] def _compute_remedies(self, body): remedies_module = _load_local_module('remedies') shadbala = body.get('shadbala', {}) doshas = body.get('doshas', []) dasha_lord = body.get('dasha_lord', '') if not isinstance(shadbala, dict): raise BadRequest('shadbala must be an object') if not isinstance(doshas, list): raise BadRequest('doshas must be an array') if not isinstance(dasha_lord, str): raise BadRequest('dasha_lord must be a string') return remedies_module.recommend_remedies(shadbala, doshas=doshas, active_dasha_lord=dasha_lord) def _compute_kp(self, body): planets = self._validate_planets(body.get('planets', {})) asc_idx = self._get_int(body, 'asc_sign_idx', 0, 0, 11) from kp_system import calc_kp_analysis return calc_kp_analysis(planets, SIGNS[asc_idx]) def _compute_prashna(self, body): question_type = body.get('question', 'general') if not isinstance(question_type, str): raise BadRequest('question must be a string') question_text = body.get('question_text', '') if not isinstance(question_text, str): raise BadRequest('question_text must be a string') from prashna import ( QUESTION_CATEGORIES, analyze_lost_item, build_kp_horary_evidence, calc_prashna_chart, calc_life_sphutas, calc_sahams, calc_sphutas, detect_prashna_arudha, get_kp_prashna_answer, get_kp_prashna_answer_v2, kunda_verify, nadi_prashna_analysis, prashna_timing_score, ) from datetime import datetime planets = self._validate_planets(body.get('planets', {})) asc_degree = self._normalize_degree(body, 'asc_degree', 15.5) horary_number = body.get('horary_number') if horary_number in ('', None): horary_number = None else: horary_number = self._get_int(body, 'horary_number', None, 1, 249) question_key = question_type[:80] chart = calc_prashna_chart(datetime.now(), planets, asc_degree) answer = get_kp_prashna_answer(planets, question_key, asc_degree) answer_v2 = get_kp_prashna_answer_v2(planets, question_key, asc_degree) kp_horary = build_kp_horary_evidence(planets, question_key, asc_degree, horary_number) question_house = QUESTION_CATEGORIES.get(question_key, QUESTION_CATEGORIES['general'])['primary'] arudha = detect_prashna_arudha(planets, asc_degree, question_house) nadi = nadi_prashna_analysis(planets, asc_degree, question_key) timing = prashna_timing_score(planets, asc_degree, question_key) planet_lons = {} for pname in ('Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn', 'Rahu', 'Ketu'): p_lon = self._planet_lon(planets, pname) if p_lon is not None: planet_lons[pname] = p_lon sphutas = calc_sphutas(planet_lons, asc_degree) life_sphutas = calc_life_sphutas( asc_degree, planet_lons.get('Moon', 0), planet_lons.get('Sun', 0), sphutas.get('gulika', {}).get('longitude', 0), ) sahams = calc_sahams(planet_lons, asc_degree) lost_item = analyze_lost_item(planet_lons, asc_degree) kunda = kunda_verify(asc_degree) conclusion = answer_v2.get('kp_answer') or answer.get('kp_answer') return { 'success': True, 'question_text': question_text[:160], 'question_category': question_key, 'prashna_chart': chart, 'kp_answer': answer, 'kp_answer_v2': answer_v2, 'kp_horary': kp_horary, 'arudha': arudha, 'nadi': nadi, 'timing': timing, 'sphutas': sphutas, 'life_sphutas': life_sphutas, 'sahams': sahams, 'lost_item': lost_item, 'kunda': kunda, 'summary': { 'conclusion': conclusion, 'confidence': answer_v2.get('confidence', answer.get('confidence')), 'primary_house': question_house, 'question_lord': answer_v2.get('question_lord', answer.get('question_lord')), 'next_action': timing.get('recommendation', '结合现实信息复核后再行动'), }, } def _compute_synastry(self, body): from ashtakoot import calculate_ashtakoot result = calculate_ashtakoot( self._normalize_degree(body, 'male_moon', 0), self._normalize_degree(body, 'female_moon', 0), ) # Backward-compatible aliases for older frontend/report consumers. result['is_approved'] = result.get('is_match_approved', False) result['assessment'] = ( '优秀' if result.get('total_score', 0) >= 28 else '良好' if result.get('total_score', 0) >= 21 else '一般' if result.get('total_score', 0) >= 18 else '不推荐' ) result['male'] = result.get('male_details', {}) result['female'] = result.get('female_details', {}) return result def _compute_dasha_system(self, body): dasha_key = body.get('dasha', body.get('name', 'vimshottari')) if not isinstance(dasha_key, str): raise BadRequest('dasha must be a string') dasha_key = dasha_key.strip().lower() extended_dashas = _load_local_module('extended_dashas') info = extended_dashas.DASHA_REGISTRY.get(dasha_key) if not info: raise BadRequest('Unknown dasha system') birth_dt = self._parse_birth_datetime(body) planets = self._validate_planets(body.get('planets', {})) ascendant = body.get('ascendant', {}) if ascendant is not None and not isinstance(ascendant, dict): raise BadRequest('ascendant must be an object') moon_lon = self._planet_lon(planets, 'Moon') if moon_lon is None: moon_lon = self._normalize_degree(body, 'moon_lon', 0) sun_lon = self._planet_lon(planets, 'Sun') if sun_lon is None: sun_lon = self._normalize_degree(body, 'sun_lon', 0) nak_size = 360 / 27 moon_nak_idx = int(moon_lon / nak_size) % 27 moon_pada = int((moon_lon % nak_size) / (nak_size / 4)) + 1 moon_sign_idx = int(moon_lon / 30) % 12 sun_sign_idx = int(sun_lon / 30) % 12 asc_sign_idx = self._sign_idx_from_value( body.get('asc_sign_idx', ascendant.get('sign_idx', ascendant.get('sign'))), 0, ) d9_asc_sign_idx = self._sign_idx_from_value(body.get('d9_asc_sign_idx', asc_sign_idx), asc_sign_idx) tithi_num = self._get_int(body, 'tithi_num', 1, 1, 30) vimshottari_analysis = None if dasha_key == 'vimshottari': periods = self._calc_vimshottari_periods(birth_dt, moon_lon) precision = 'calculator' vimshottari_analysis = self._compute_vimshottari_analysis_layer( birth_dt, moon_lon, body.get('today') or body.get('current_date'), ) else: periods = extended_dashas.calc_any_dasha( dasha_key, birth_dt, moon_nak_idx=moon_nak_idx, moon_pada=moon_pada, asc_sign_idx=asc_sign_idx, moon_sign_idx=moon_sign_idx, sun_sign_idx=sun_sign_idx, d9_asc_sign_idx=d9_asc_sign_idx, tithi_num=tithi_num, ) calc_fn = extended_dashas.DASHA_CALCULATORS.get(dasha_key) precision = 'generic' if not calc_fn or calc_fn.__name__ == 'calc_generic_dasha' else 'calculator' if not periods: periods = self._fallback_dasha_periods(birth_dt, dasha_key, info) precision = 'generic' result = { 'success': True, 'key': dasha_key, 'name': info.get('name', dasha_key), 'type': info.get('type', 'other'), 'cycle_years': info.get('years'), 'precision': precision, 'periods': periods, } if vimshottari_analysis: result['vimshottari_analysis'] = vimshottari_analysis result['fragment_sources'] = ['dasha_analyzer.py', 'dasha_calculator_enhanced.py'] return result def _compute_vimshottari_analysis_layer(self, birth_dt, moon_lon, current_date=None): try: analyzer = _load_local_module('dasha_analyzer') enhanced = _load_local_module('dasha_calculator_enhanced') nak_info, nak_progress, pada = analyzer.lon_to_nakshatra(moon_lon % 360) timeline, elapsed, remaining, start_lord = analyzer.build_dasha_timeline( birth_dt.strftime('%Y-%m-%d'), nak_info, nak_progress, ) today = self._parse_optional_date(current_date) if current_date else datetime.now() current_idx, current_md = analyzer.find_current(timeline, today) antardashas = analyzer.build_antardasha(current_md) current_ad = analyzer.find_current_sub(antardashas, today) years_into_md = max(0.0, (today - current_md['start']).days / 365.25636) five_levels = enhanced.calculate_five_level_dasha(current_md['lord'], years_into_md) formatted_timeline = [self._format_datetime_period(period) for period in timeline] formatted_antardashas = [self._format_datetime_period(period) for period in antardashas] current_period = self._format_datetime_period(current_md) current_sub = self._format_datetime_period(current_ad) remaining_days = max(0, (current_ad['end'] - today).days) theme = enhanced.PLANET_MODERN_MEANINGS.get(current_md['lord'], {}) return { 'source': 'dasha_analyzer.py + dasha_calculator_enhanced.py', 'nakshatra': { 'name': nak_info[0], 'lord': nak_info[1], 'years': nak_info[2], 'pada': pada, 'progress_pct': round(nak_progress * 100, 2), 'elapsed_years_at_birth': elapsed, 'remaining_years_at_birth': remaining, }, 'current': { 'mahadasha': current_period, 'antardasha': current_sub, 'remaining_days': remaining_days, 'remaining_months': round(remaining_days / 30.44, 1), 'theme': theme.get('theme', ''), 'keywords': theme.get('keywords', []), }, 'five_levels': five_levels, 'timeline_from_true_md_start': formatted_timeline, 'current_antardashas': formatted_antardashas, 'summary': { 'headline': f"当前处于 {current_md['lord']} Mahadasha / {current_ad['lord']} Antardasha", 'note': '该增强层复用 dasha_analyzer.py，主 periods 合同仍保持出生后周期列表。', 'next_action': '用当前 MD/AD 作为时间主轴，再用本命承诺、Transit 和案例验证收敛事件。', }, 'current_index': current_idx, } except Exception as exc: import logging logging.warning(f"[api_server] vimshottari analysis layer failed: {exc}") return None def _parse_optional_date(self, value): if not isinstance(value, str) or not value.strip(): raise BadRequest('current_date must be YYYY-MM-DD') try: return datetime.strptime(value.strip()[:10], '%Y-%m-%d') except ValueError as e: raise BadRequest('current_date must be YYYY-MM-DD') from e def _format_datetime_period(self, period): return { 'lord': period.get('lord'), 'years': round(period.get('years', 0), 4) if isinstance(period.get('years'), (int, float)) else period.get('years'), 'start': period.get('start').strftime('%Y-%m-%d') if hasattr(period.get('start'), 'strftime') else period.get('start'), 'end': period.get('end').strftime('%Y-%m-%d') if hasattr(period.get('end'), 'strftime') else period.get('end'), } def _compute_sade_sati(self, body): from sade_sati import calc_sade_sati_complete return calc_sade_sati_complete( self._normalize_degree(body, 'moon_degree', 0), self._normalize_degree(body, 'asc_degree', 0), self._normalize_degree(body, 'saturn_degree', 0), ) def _compute_pmc(self, body): from pancha_mahapurusha import assess_pmc_strength sun_degree = None if body.get('sun_degree') is not None: sun_degree = self._normalize_degree(body, 'sun_degree', 0) return assess_pmc_strength(self._validate_planets(body.get('planets', {})), sun_degree) def _compute_career(self, body): from career_analysis import analyze_career asc_sign = body.get('asc_sign', 'Aries') if asc_sign not in SIGNS: raise BadRequest('asc_sign must be a valid sign') return analyze_career(self._validate_planets(body.get('planets', {})), asc_sign) def _compute_relationship(self, body): from relationship_analysis import analyze_relationship from spouse_status_yoga import analyze_spouse_status asc_sign = body.get('asc_sign', 'Aries') if asc_sign not in SIGNS: raise BadRequest('asc_sign must be a valid sign') planets, planet_lons = self._planet_lons_from_body(body) normalized, _, asc_sign_idx = self._normalized_planets_from_body({'planets': planets, 'ascendant': {'sign': asc_sign}}) planets_for_analysis = normalized or planets result = analyze_relationship(planets_for_analysis, asc_sign) chart_data = { 'ascendant': {'sign': asc_sign}, 'planets': planets_for_analysis, } d9_data = body.get('d9') if isinstance(body.get('d9'), dict) else None result['spouse_status_yoga'] = analyze_spouse_status(chart_data, d9_data) result['relationship_timing'] = self._compute_relationship_timing_evidence( body, planets_for_analysis, planet_lons, asc_sign_idx, asc_sign, d9_data, ) result['fragment_sources'] = sorted(set(result.get('fragment_sources', []) + [ 'relationship_analysis.py', 'spouse_status_yoga.py', 'darakaraka_reader.py', 'jaimini.py', ])) return result def _compute_relationship_timing_evidence(self, body, planets, planet_lons, asc_sign_idx, asc_sign, d9_data=None): jaimini = _load_local_module('jaimini') varga = _load_local_module('varga') evidence = [] timing_clues = [] planet_degs = {planet: lon % 30 for planet, lon in planet_lons.items()} ck7 = jaimini.calc_chara_karaka_7(planet_degs) if planet_degs else {} dk = (ck7.get('karaka_table') or {}).get('Darakaraka') or {} dk_planet = dk.get('planet') darakaraka = None if dk_planet: d9_planets = {} for planet, lon in planet_lons.items(): d9_pos = varga.calc_varga(lon, 9) d9_planets[planet] = { 'sign': d9_pos.get('sign'), 'house': d9_pos.get('house'), 'degree': d9_pos.get('degree_in_sign', d9_pos.get('degree')), 'degree_in_sign': d9_pos.get('degree_in_sign', d9_pos.get('degree')), } chart_data = { 'ascendant': {'sign': asc_sign}, 'planets': planets, 'd9': {'planets': d9_planets}, } try: darakaraka = _load_local_module('darakaraka_reader').analyze_darakaraka(chart_data, use_8_karaka=True) timing_clues.extend(darakaraka.get('timing_clues') or []) evidence.append({ 'label': 'Darakaraka (DK)', 'value': f"{dk_planet} · H{darakaraka.get('dk_house', '-')}", 'note': f"{darakaraka.get('core_profile') or '配偶象征星'}；婚姻质量 {darakaraka.get('marriage_quality_score', '-')}/100", }) except Exception as exc: darakaraka = {'error': str(exc), 'dk_planet': dk_planet} upapada = jaimini.calc_upapada(asc_sign_idx, planet_lons) if planet_lons else None if upapada: evidence.append({ 'label': 'Upapada Lagna (UL)', 'value': f"{upapada.get('sign')} · 2nd {upapada.get('second_from_ul', '-')}", 'note': upapada.get('description') or '婚姻外显与关系持续性证据', }) h7_sign = SIGNS[(asc_sign_idx + 6) % 12] h7_lord = { 'Aries':'Mars','Taurus':'Venus','Gemini':'Mercury','Cancer':'Moon', 'Leo':'Sun','Virgo':'Mercury','Libra':'Venus','Scorpio':'Mars', 'Sagittarius':'Jupiter','Capricorn':'Saturn','Aquarius':'Saturn','Pisces':'Jupiter', }.get(h7_sign) dasha_focus = self._relationship_dasha_focus(body, dk_planet, h7_lord) if dasha_focus: timing_clues.extend(dasha_focus.get('clues', [])) evidence.append({ 'label': 'Dasha trigger', 'value': dasha_focus.get('label', '待补充'), 'note': dasha_focus.get('note', ''), }) score = 0 if darakaraka and not darakaraka.get('error'): quality = darakaraka.get('marriage_quality_score') if isinstance(quality, (int, float)): score += 2 if quality >= 65 else 1 if quality >= 45 else 0 if darakaraka.get('timing_clues'): score += 1 if upapada: score += 1 if dasha_focus and dasha_focus.get('level') != 'neutral': score += 1 level = 'strong' if score >= 4 else 'watch' if score >= 2 else 'thin' summary = { 'strong': 'DK、UL 与运限触发能形成较完整的关系时机证据链。', 'watch': '已有 DK/UL 或运限线索，适合继续用 D9、行运和现实事件复核。', 'thin': '关系时机证据仍偏薄，需要更完整出生数据或当前运限。', }[level] return { 'level': level, 'score': score, 'summary': summary, 'darakaraka': darakaraka, 'upapada': upapada, 'dasha_focus': dasha_focus, 'timing_clues': list(dict.fromkeys(timing_clues))[:6], 'evidence': evidence, 'source': 'darakaraka_reader.py + jaimini.py', } def _relationship_dasha_focus(self, body, dk_planet=None, h7_lord=None): raw = body.get('dasha_info') or body.get('dasha') or {} if not isinstance(raw, dict): return None candidates = [ raw.get('maha_dasha'), raw.get('maha'), raw.get('md'), raw.get('maha_lord'), raw.get('antar_dasha'), raw.get('antar'), raw.get('ad'), raw.get('antar_lord'), raw.get('pratyantar'), raw.get('pd'), raw.get('pratyantar_lord'), ] active = [str(item) for item in candidates if item] if not active: return None focus = {'Venus', 'Jupiter', 'Moon', 'Mars'} if dk_planet: focus.add(dk_planet) if h7_lord: focus.add(h7_lord) hits = [planet for planet in active if planet in focus] label = ' / '.join(active[:3]) if hits: return { 'level': 'activated', 'label': label, 'hits': hits, 'note': f"当前运限触及 {'、'.join(hits)}，关系/承诺主题更容易被事件激活。", 'clues': [f"Dasha 命中 {'、'.join(hits)}，作为关系时机窗口观察。"], } return { 'level': 'neutral', 'label': label, 'hits': [], 'note': '当前运限未明显命中 Venus/Jupiter/Moon/Mars/DK/7主，关系时机需更多行运或事件证据。', 'clues': [], } def _planet_lons_from_body(self, body): planets = self._validate_planets(body.get('planets', {})) planet_lons = {} for planet in ['Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn', 'Rahu', 'Ketu']: lon = self._planet_lon(planets, planet) if lon is not None: planet_lons[planet] = lon return planets, planet_lons def _normalized_planets_from_body(self, body): planets, planet_lons = self._planet_lons_from_body(body) asc_sign_idx = self._asc_sign_idx_from_body(body) normalized = {} for planet, lon in planet_lons.items(): source = planets.get(planet, {}) if isinstance(planets, dict) else {} sign_idx = int(lon / 30) % 12 sign = SIGNS[sign_idx] house = source.get('house') if isinstance(source, dict) else None if house is None: house = ((sign_idx - asc_sign_idx) % 12) + 1 normalized[planet] = { **(source if isinstance(source, dict) else {}), 'lon': lon, 'degree': lon, 'degree_in_sign': lon % 30, 'sign_idx': sign_idx, 'sign': sign, 'house': int(house), } return normalized, planet_lons, asc_sign_idx def _asc_sign_idx_from_body(self, body): ascendant = body.get('ascendant', {}) if isinstance(ascendant, dict): if ascendant.get('sign_idx') is not None: return self._sign_idx_from_value(ascendant.get('sign_idx'), 0) if ascendant.get('sign') in SIGNS: return SIGNS.index(ascendant.get('sign')) if ascendant.get('lon') is not None: try: return int((float(ascendant.get('lon')) % 360) / 30) % 12 except (TypeError, ValueError) as e: raise BadRequest('ascendant lon must be a number') from e return int(self._asc_lon_from_body(body) / 30) % 12 def _chart_payload_from_body(self, body): planets, planet_lons = self._planet_lons_from_body(body) chart_data = {'planets': {}} for planet, lon in planet_lons.items(): sign_idx = int(lon / 30) % 12 source = planets.get(planet, {}) if isinstance(planets, dict) else {} chart_data['planets'][planet] = { **(source if isinstance(source, dict) else {}), 'degree': lon, 'lon': lon, 'sign_idx': sign_idx, 'sign': SIGNS[sign_idx], 'degree_in_sign': lon % 30, } ascendant = body.get('ascendant', {}) if isinstance(ascendant, dict): chart_data['ascendant'] = ascendant return chart_data, planet_lons def _asc_lon_from_body(self, body, default=0): ascendant = body.get('ascendant', {}) if ascendant is None: ascendant = {} if not isinstance(ascendant, dict): raise BadRequest('ascendant must be an object') asc_lon = ascendant.get('lon', ascendant.get('degree_raw')) if asc_lon is None and ascendant.get('sign') in SIGNS: try: return ( SIGNS.index(ascendant['sign']) * 30 + float(ascendant.get('degree_in_sign', ascendant.get('degree', 0))) ) % 360 except (TypeError, ValueError) as e: raise BadRequest('ascendant degree must be a number') from e if asc_lon is None and ascendant.get('sign_idx') is not None: try: sign_idx = int(ascendant.get('sign_idx')) % 12 degree = float(ascendant.get('degree_in_sign', ascendant.get('degree', 0))) return (sign_idx * 30 + degree) % 360 except (TypeError, ValueError) as e: raise BadRequest('ascendant sign_idx/degree must be numeric') from e if asc_lon is None: return self._normalize_degree(body, 'asc_lon', default) try: number = float(asc_lon) except (TypeError, ValueError) as e: raise BadRequest('ascendant lon must be a number') from e if not math.isfinite(number): raise BadRequest('ascendant lon must be finite') return number % 360 def _parse_varga_divisions(self, value): if value is None or value == '': return None if isinstance(value, str): raw_items = [item.strip() for item in value.split(',') if item.strip()] elif isinstance(value, list): raw_items = value else: raise BadRequest('divisions must be a comma string or list') divisions = [] for item in raw_items: token = str(item).strip().upper() if token.startswith('D'): token = token[1:] if not re.fullmatch(r'\d+', token): raise BadRequest('divisions must contain D-numbers such as D9 or 9') division = int(token) if division < 1 or division > 300: raise BadRequest('division must be between 1 and 300') divisions.append(division) return divisions or None def _parse_varga_composite(self, value): if value is None or value == '': return None if isinstance(value, str): raw_parts = [part.strip() for part in value.split(',') if part.strip()] elif isinstance(value, list): raw_parts = value else: raise BadRequest('composite must be "m,n" or a two-item list') if len(raw_parts) != 2: raise BadRequest('composite requires exactly two division factors') parts = [] for part in raw_parts: try: number = int(part) except (TypeError, ValueError) as e: raise BadRequest('composite factors must be integers') from e if number < 2 or number > 300: raise BadRequest('composite factors must be between 2 and 300') parts.append(number) return parts[0], parts[1] def _compute_varga_full(self, body): _, planet_lons = self._planet_lons_from_body(body) if not planet_lons: raise BadRequest('planets must include longitude data') asc_lon = self._asc_lon_from_body(body) divisions = self._parse_varga_divisions(body.get('divisions')) composite = self._parse_varga_composite(body.get('composite')) custom_n = None if body.get('custom') is not None: custom_n = self._get_int(body, 'custom', 0, 2, 300) variant = body.get('variant') if variant is not None and not isinstance(variant, str): raise BadRequest('variant must be a string') mode_count = sum([ custom_n is not None, composite is not None, bool(variant), ]) if mode_count > 1: raise BadRequest('custom, composite, and variant modes are mutually exclusive') module = _load_local_module('divisional_charts_extended') calc = module.DivisionalChartsCalculator() try: if custom_n is not None: result = {'custom_div': custom_n} result['Ascendant'] = calc.calc_custom_varga(asc_lon, custom_n) for planet, lon in planet_lons.items(): result[planet] = calc.calc_custom_varga(lon, custom_n) return { 'success': True, 'endpoint': 'varga_full', 'mode': 'custom', 'source': 'divisional_charts_extended', 'result': result, } if composite is not None: outer, inner = composite result = { 'composite_div': f'D{outer}×D{inner}=D{outer * inner}', 'outer': outer, 'inner': inner, } result['Ascendant'] = calc.calc_composite_varga(asc_lon, outer, inner) for planet, lon in planet_lons.items(): result[planet] = calc.calc_composite_varga(lon, outer, inner) return { 'success': True, 'endpoint': 'varga_full', 'mode': 'composite', 'source': 'divisional_charts_extended', 'result': result, } if variant: if not divisions or len(divisions) != 1 or divisions[0] not in (2, 3): raise BadRequest('variant mode requires exactly one division: D2 or D3') division = divisions[0] result = {'variant': variant, 'div': division} result['Ascendant'] = calc.calc_varga_with_variant(asc_lon, division, variant) for planet, lon in planet_lons.items(): result[planet] = calc.calc_varga_with_variant(lon, division, variant) return { 'success': True, 'endpoint': 'varga_full', 'mode': 'variant', 'source': 'divisional_charts_extended', 'result': result, } available = {varga.division: varga for varga in module.VargaType} selected = [available[division] for division in (divisions or sorted(available))] result = {} for varga in selected: key = f'D{varga.division}_{varga.varga_name}' result[key] = calc._calculate_single_varga(varga, planet_lons, asc_lon) except KeyError as e: raise BadRequest('unsupported standard division; use custom mode for arbitrary D-N') from e except ValueError as e: raise BadRequest(str(e)) from e return { 'success': True, 'endpoint': 'varga_full', 'mode': 'standard', 'source': 'divisional_charts_extended', 'divisions': [varga.division for varga in selected], 'result': result, } def _compute_jaimini(self, body): planets, planet_lons, asc_sign_idx = self._normalized_planets_from_body(body) if not planet_lons: raise BadRequest('planets must include longitude data') mode = body.get('mode', 'all') if not isinstance(mode, str): raise BadRequest('mode must be a string') mode = mode.strip().lower() or 'all' allowed_modes = {'all', 'karaka', 'dasha', 'karakamsha', 'arudha', 'special'} if mode not in allowed_modes: raise BadRequest(f'mode must be one of: {", ".join(sorted(allowed_modes))}') antardasha = bool(body.get('antardasha', False)) year = self._get_int(body, 'year', datetime.now().year, 1800, 2400) month = self._get_int(body, 'month', 1, 1, 12) hour = self._get_int(body, 'hour', 12, 0, 23) minute = self._get_int(body, 'minute', 0, 0, 59) second = self._get_birth_second(body) jaimini = _load_local_module('jaimini') varga = _load_local_module('varga') planet_degs = {planet: lon % 30 for planet, lon in planet_lons.items()} result = {} if mode in ('all', 'karaka'): result['chara_karaka_7'] = jaimini.calc_chara_karaka_7(planet_degs) result['chara_karaka_8'] = jaimini.calc_chara_karaka_8(planet_degs) if mode in ('all', 'dasha'): if antardasha: result['chara_dasha'] = jaimini.calc_chara_dasha_with_antardasha(asc_sign_idx, planet_lons, year, month) else: result['chara_dasha'] = jaimini.calc_chara_dasha(asc_sign_idx, planet_lons, year, month) if mode in ('all', 'karakamsha'): ck7 = result.get('chara_karaka_7') or jaimini.calc_chara_karaka_7(planet_degs) ak_name = ck7['karaka_table']['Atmakaraka']['planet'] ak_d9 = varga.calc_varga(planet_lons.get(ak_name, 0), 9) result['karakamsha'] = jaimini.calc_karakamsha( ak_d9.get('sign', 'Aries'), ak_d9.get('degree_in_sign', 0), ) if mode in ('all', 'arudha'): result['arudha_padas'] = jaimini.calc_arudha_padas(asc_sign_idx, planet_lons) result['graha_padas'] = jaimini.calc_graha_padas(planet_lons) if mode in ('all', 'special'): result['special_lagnas'] = jaimini.calc_special_lagnas(asc_sign_idx, hour, minute + second / 60.0) return { 'success': True, 'endpoint': 'jaimini', 'mode': mode, 'ascendant': SIGNS[asc_sign_idx], 'result': result, } def _compute_ashtakavarga(self, body): planets, _, asc_sign_idx = self._normalized_planets_from_body(body) if not planets: raise BadRequest('planets must include longitude data') ashtakavarga = _load_local_module('ashtakavarga') result = ashtakavarga.calc_ashtakavarga(planets, asc_sign_idx) pav = ashtakavarga.calc_prastara_av(planets, asc_sign_idx) sodhita = ashtakavarga.calc_sodhita_av(result.get('bav', {}), planets, asc_sign_idx) yoga_pinda = result.get('yoga_pinda') or ashtakavarga.calc_yoga_pinda(result.get('bav', {}), planets, asc_sign_idx) result['pav'] = pav result['sodhita'] = sodhita result['yoga_pinda'] = yoga_pinda summary = self._summarize_ashtakavarga(result, pav, sodhita, yoga_pinda) return { 'success': True, 'endpoint': 'ashtakavarga', 'rule_variants': self._ashtakavarga_rule_variants(), 'summary': summary, 'pav_summary': summary['pav_summary'], 'sodhita_summary': summary['sodhita_summary'], 'yoga_pinda_summary': summary['yoga_pinda_summary'], 'result': result, } def _summarize_ashtakavarga(self, result, pav, sodhita, yoga_pinda=None): house_rows = [] for key, item in (result.get('house_scores') or {}).items(): try: house_num = int(str(key).split('_')[-1]) except (TypeError, ValueError): house_num = 0 house_rows.append({ 'house': house_num, 'sign': item.get('sign'), 'score': item.get('sav_score', 0), 'level': item.get('level', ''), }) house_rows.sort(key=lambda item: item.get('score', 0), reverse=True) strongest = house_rows[:3] weakest = sorted(house_rows, key=lambda item: item.get('score', 0))[:3] pav_totals = [] for planet, source_scores in (pav.get('pav_summary') or {}).items(): total = sum(value for value in source_scores.values() if isinstance(value, (int, float))) top_sources = sorted(source_scores.items(), key=lambda pair: pair[1], reverse=True)[:3] pav_totals.append({ 'planet': planet, 'total': total, 'top_sources': [{'source': source, 'bindus': bindus} for source, bindus in top_sources], }) pav_totals.sort(key=lambda item: item['total'], reverse=True) sodhita_scores = sodhita.get('sodhita_sav', {}).get('assessment', []) sodhita_rank = sorted(sodhita_scores, key=lambda item: item.get('score', 0), reverse=True) raw_total = result.get('sav', {}).get('total', 0) sodhita_total = sodhita.get('sodhita_sav', {}).get('total', 0) reduction_total = raw_total - sodhita_total if isinstance(raw_total, (int, float)) and isinstance(sodhita_total, (int, float)) else 0 yoga_pinda = yoga_pinda or result.get('yoga_pinda') or {} yoga_rows = yoga_pinda.get('planets') or {} yoga_rank = sorted(yoga_rows.items(), key=lambda item: item[1].get('yoga_pinda', 0), reverse=True) leader = strongest[0] if strongest else {} headline = ( f"Ashtakavarga总分{raw_total}，重点支持H{leader.get('house')} {leader.get('sign')}" if leader else f"Ashtakavarga总分{raw_total}" ) return { 'headline': headline, 'sav_total': raw_total, 'sav_valid': result.get('sav', {}).get('valid'), 'strongest_houses': strongest, 'weakest_houses': weakest, 'pav_summary': { 'headline': f"PAV显示{pav_totals[0]['planet']}贡献结构最强" if pav_totals else 'PAV已生成贡献矩阵', 'top_planets': pav_totals[:3], 'validation_passed': pav.get('all_valid'), }, 'sodhita_summary': { 'headline': f"Sodhita净化后总分{sodhita_total}，扣减{reduction_total}", 'top_signs': sodhita_rank[:3], 'weak_signs': sorted(sodhita_scores, key=lambda item: item.get('score', 0))[:3], 'reduction_total': reduction_total, }, 'yoga_pinda_summary': { 'headline': ( f"Yoga Pinda以{yoga_rank[0][0]}最高（{yoga_rank[0][1].get('yoga_pinda', 0)}）" if yoga_rank else 'Yoga Pinda未返回' ), 'top_planets': [ {'planet': planet, 'yoga_pinda': row.get('yoga_pinda'), 'sign': row.get('sign')} for planet, row in yoga_rank[:3] ], 'weak_planets': [ {'planet': planet, 'yoga_pinda': row.get('yoga_pinda'), 'sign': row.get('sign')} for planet, row in sorted(yoga_rows.items(), key=lambda item: item[1].get('yoga_pinda', 0))[:3] ], 'total_yoga_pinda': yoga_pinda.get('summary', {}).get('total_yoga_pinda', 0), 'validation_passed': yoga_pinda.get('all_valid'), }, 'next_action': '先用SAV定领域强弱，再用PAV追溯贡献源，用Sodhita检验净支持度，并用Yoga Pinda比较行星承载力。', } def _compute_shadbala(self, body): planets, planet_lons, asc_sign_idx = self._normalized_planets_from_body(body) if not {'Sun', 'Moon'} <= set(planet_lons): raise BadRequest('planets must include Sun and Moon longitude data') birth_hour = self._get_float(body, 'birth_hour', body.get('hour', 12), 0, 23) birth_minute = self._get_float(body, 'birth_minute', body.get('minute', 0), 0, 59) birth_second = self._get_birth_second(body) birth_hour_decimal = self._birth_hour_decimal(birth_hour, birth_minute, birth_second) result = _load_local_module('shadbala').calc_shadbala( planets, SIGNS[asc_sign_idx], birth_hour_decimal, planet_lons['Sun'], planet_lons['Moon'], ) advanced = self._compute_shadbala_advanced_layer(body, planets, result) return { 'success': True, 'endpoint': 'shadbala', 'rule_variants': self._shadbala_rule_variants(bool(advanced)), 'advanced_layer': advanced, 'result': result, } def _compute_yogas_api(self, body): planets, _, asc_sign_idx = self._normalized_planets_from_body(body) if not planets: raise BadRequest('planets must include longitude data') asc_sign = SIGNS[asc_sign_idx] extended = _load_local_module('yoga_expansion').detect_all_yogas(planets, asc_sign) try: engine_yogas = _load_local_module('yoga_engine').detect_yogas(planets, asc_sign) except Exception: engine_yogas = [] curse_yogas = self._compute_curse_yoga_layer(body, planets, asc_sign) result = { 'extended_yogas': extended, 'rule_engine_yogas': engine_yogas, 'curse_yogas': curse_yogas, 'summary': { 'extended_count': len(extended), 'rule_engine_count': len(engine_yogas), 'curse_count': len(curse_yogas.get('curses_detected', [])), 'risk': curse_yogas.get('overall_risk', 'low'), }, 'rule_variants': self._yoga_rule_variants(bool(curse_yogas.get('curses_detected'))), } return { 'success': True, 'endpoint': 'yogas', 'ascendant': asc_sign, 'rule_variants': result['rule_variants'], 'result': result, } def _ashtakavarga_rule_variants(self): return { 'selected': ['sav_bav', 'prastara_av', 'sodhita_av', 'yoga_pinda'], 'available': [ {'key': 'sav_bav', 'label': 'SAV/BAV', 'status': 'active', 'source': 'scripts/ashtakavarga.py'}, {'key': 'prastara_av', 'label': 'Prastara AV / PAV', 'status': 'active', 'source': 'scripts/ashtakavarga.py'}, {'key': 'sodhita_av', 'label': 'Sodhita AV', 'status': 'active', 'source': 'scripts/ashtakavarga.py'}, {'key': 'yoga_pinda', 'label': 'Yoga Pinda', 'status': 'active', 'source': 'scripts/ashtakavarga.py'}, ], 'boundary': '当前按本地 BAV 贡献规则生成 SAV、PAV、Sodhita 与 Yoga Pinda；后续可继续加入 Sarvashtakavarga 规则版本对比。', } def _shadbala_rule_variants(self, advanced_enabled): return { 'selected': ['core_sixfold', 'advanced_evidence'] if advanced_enabled else ['core_sixfold'], 'available': [ {'key': 'core_sixfold', 'label': '六重力量主算法', 'status': 'active', 'source': 'scripts/shadbala.py'}, {'key': 'advanced_evidence', 'label': 'Kala/Yuddha/Sputa 增强证据', 'status': 'active' if advanced_enabled else 'unavailable', 'source': 'scripts/shadbala_advanced.py'}, ], 'boundary': '增强层只作为证据补充，不覆盖主 Shadbala 的总分与排名。', } def _yoga_rule_variants(self, curse_enabled): return { 'selected': ['extended_algorithm', 'json_rule_engine'] + (['curse_conjunctions'] if curse_enabled else []), 'available': [ {'key': 'extended_algorithm', 'label': '算法 Yoga 扩展', 'status': 'active', 'source': 'scripts/yoga_expansion.py'}, {'key': 'json_rule_engine', 'label': 'JSON 规则引擎', 'status': 'active', 'source': 'scripts/yoga_engine.py + references/yoga_rules.json'}, {'key': 'curse_conjunctions', 'label': '凶星合相命名', 'status': 'active', 'source': 'scripts/curse_yoga_detector.py'}, ], 'boundary': '凶星合相属于高风险提示层，只能作为 Yoga 证据之一，不能替代健康、法律或安全建议。', } def _compute_curse_yoga_layer(self, body, planets, asc_sign): current_dasha = body.get('current_dasha') or body.get('dasha_lord') chart_data = { 'ascendant': {'sign': asc_sign}, 'planets': self._planets_for_legacy_fragments(planets), } context = body.get('context') if isinstance(context, dict): chart_data['context'] = context try: return _load_local_module('curse_yoga_detector').detect_curse_yogas(chart_data, current_dasha=current_dasha) except Exception as exc: import logging logging.warning(f"[api_server] curse yoga layer failed: {exc}") return {'curses_detected': [], 'overall_risk': 'unknown', 'risk_score': 0, 'error': 'curse yoga layer unavailable'} def _planets_for_legacy_fragments(self, planets): legacy = {} for planet, data in planets.items(): if not isinstance(data, dict): continue row = dict(data) row['lon'] = data.get('lon', data.get('degree')) row['degree'] = data.get('degree_in_sign', data.get('degree', 0)) row['degree_in_sign'] = row['degree'] legacy[planet] = row return legacy def _compute_shadbala_advanced_layer(self, body, planets, base_result): try: advanced_mod = _load_local_module('shadbala_advanced') birth_hour = self._get_float(body, 'birth_hour', body.get('hour', 12), 0, 23) birth_minute = self._get_float(body, 'birth_minute', body.get('minute', 0), 0, 59) birth_second = self._get_birth_second(body) year = self._get_int(body, 'year', datetime.now().year, 1800, 2400) month = self._get_int(body, 'month', 1, 1, 12) day = self._get_int(body, 'day', 1, 1, 31) lat = self._get_float(body, 'lat', body.get('birth_lat', 0), -90, 90) lon = self._get_float(body, 'lon', body.get('birth_lon', 0), -180, 180) tz = self._parse_timezone(body, lat, lon, year, month, day, birth_hour, birth_minute, birth_second) hour_decimal = self._birth_hour_decimal(birth_hour, birth_minute, birth_second) solar_lon = planets.get('Sun', {}).get('lon', 0) base_planets = base_result.get('planets', {}) if isinstance(base_result, dict) else {} comparison_planets = {} kala_additions = {} drik_sputa = {} for planet, pdata in planets.items(): if planet not in base_planets: continue comparison_planets[planet] = { **pdata, 'degree': pdata.get('lon', pdata.get('degree', 0)), 'shadbala_total': base_planets.get(planet, {}).get('total_virupas', 0), } for planet in comparison_planets: kala_additions[planet] = round(advanced_mod.calc_varsha_maasa_dina_hora_bala( planet, year, month, day, hour_decimal, solar_lon, lat, lon, tz ), 2) drik_sputa[planet] = round(advanced_mod.calc_drik_bala_sputa(planet, comparison_planets), 2) yuddha = advanced_mod.calc_yuddha_bala(comparison_planets) active_yuddha = {planet: value for planet, value in yuddha.items() if abs(value) > 0} top_kala = sorted(kala_additions.items(), key=lambda item: item[1], reverse=True)[:3] return { 'source': 'scripts/shadbala_advanced.py', 'method': 'Kala Bala完整子项 + Yuddha Bala + Sputa Drishti 证据层', 'kala_vmdh': kala_additions, 'top_kala_support': [{'planet': planet, 'virupas': value} for planet, value in top_kala], 'yuddha_bala': yuddha, 'active_yuddha': active_yuddha, 'sputa_drik_bala': drik_sputa, 'next_action': '若高级层与主排名冲突，先保留主 Shadbala 排名，再把冲突作为需要人工复核的证据。', } except Exception as exc: import logging logging.warning(f"[api_server] shadbala advanced layer failed: {exc}") return {} def _compute_aspects(self, body): _, planet_lons = self._planet_lons_from_body(body) if len(planet_lons) < 2: raise BadRequest('planets must include at least two longitude values') asc_lon = self._asc_lon_from_body(body) result = _load_local_module('aspects').calc_all_aspects(planet_lons, asc_lon) return { 'success': True, 'endpoint': 'aspects', 'result': result, } def _compute_annual(self, body): target_year = self._get_int(body, 'target_year', datetime.now().year, 1800, 2400) birth_dt = self._parse_birth_datetime(body) lat = self._get_float(body, 'lat', body.get('birth_lat', 0), -90, 90) lon = self._get_float(body, 'lon', body.get('birth_lon', 0), -180, 180) tz = self._parse_timezone( body, lat, lon, birth_dt.year, birth_dt.month, birth_dt.day, birth_dt.hour, birth_dt.minute, birth_dt.second, ) solar_return = _load_local_module('solar_return') report = solar_return.solar_return_full_report( birth_dt.year, birth_dt.month, birth_dt.day, birth_dt.hour, birth_dt.minute, lat, lon, tz, target_year, ayanamsa_name=body.get('ayanamsa', 'lahiri'), ) return {'success': True, 'endpoint': 'annual', 'report': report} def _compute_tajika(self, body): result = self._compute_annual(body) return { **result, 'endpoint': 'tajika', 'alias_of': 'annual', } def _compute_chara_dasha(self, body): payload = dict(body or {}) payload['mode'] = 'dasha' result = self._compute_jaimini(payload) return { **result, 'endpoint': 'chara_dasha', 'alias_of': 'jaimini', } def _compute_muhurta(self, body): has_range = body.get('start_date') or body.get('end_date') or body.get('start') or body.get('end') query_date = body.get('date') or datetime.now().strftime('%Y-%m-%d') if not isinstance(query_date, str): raise BadRequest('date must be a string') try: query_dt = datetime.strptime(query_date[:10], '%Y-%m-%d') except ValueError as e: raise BadRequest('date must be YYYY-MM-DD') from e activity = body.get('activity') if activity is not None and not isinstance(activity, str): raise BadRequest('activity must be a string') hour_from_sunrise = self._get_float(body, 'hour_from_sunrise', 6.0, 0, 24) sunrise = body.get('sunrise', '06:00') sunset = body.get('sunset', '18:00') if not isinstance(sunrise, str) or not isinstance(sunset, str): raise BadRequest('sunrise/sunset must be HH:MM strings') sun_lon = self._planet_lon(body.get('planets', {}), 'Sun') moon_lon = self._planet_lon(body.get('planets', {}), 'Moon') muhurta = _load_local_module('muhurta') if sun_lon is None or moon_lon is None: sun_lon, moon_lon = muhurta._approx_sun_moon_lon(query_dt.year, query_dt.month, query_dt.day) weekday = (query_dt.weekday() + 1) % 7 # Python Mon=0; module Sun=0 activities = [activity] if activity else None report = muhurta.muhurta_full_report( sun_lon, moon_lon, weekday, hour_from_sunrise=hour_from_sunrise, query_date_str=query_date[:10], activities=activities, ) result = {'success': True, 'endpoint': 'muhurta', 'report': report} if has_range: start_raw = body.get('start_date') or body.get('start') or query_date end_raw = body.get('end_date') or body.get('end') or start_raw if not isinstance(start_raw, str) or not isinstance(end_raw, str): raise BadRequest('start_date/end_date must be strings') try: start_dt = datetime.strptime(start_raw[:10], '%Y-%m-%d') end_dt = datetime.strptime(end_raw[:10], '%Y-%m-%d') except ValueError as e: raise BadRequest('start_date/end_date must be YYYY-MM-DD') from e if end_dt < start_dt: raise BadRequest('end_date must be on or after start_date') if (end_dt - start_dt).days > 62: raise BadRequest('muhurta range must be <= 63 days') lat = lon = tz = None has_location = any(key in body for key in ('lat', 'lon', 'tz')) if has_location: lat = self._get_float(body, 'lat', 0, -90, 90) lon = self._get_float(body, 'lon', 0, -180, 180) tz = self._get_float(body, 'tz', 0, -14, 14) limit = self._get_int(body, 'limit', 5, 1, 20) try: result['range_search'] = muhurta.muhurta_range_search( start_dt.strftime('%Y-%m-%d'), end_dt.strftime('%Y-%m-%d'), activity=activity or 'business', limit=limit, hour_from_sunrise=hour_from_sunrise, sunrise=sunrise, sunset=sunset, lat=lat, lon=lon, tz=tz, ayanamsa_name=body.get('ayanamsa', 'lahiri'), ) except ValueError as e: raise BadRequest(str(e)) from e return result def _compute_panchanga_range(self, body): start_raw = body.get('start_date') or body.get('start') or datetime.now().strftime('%Y-%m-%d') end_raw = body.get('end_date') or body.get('end') or start_raw if not isinstance(start_raw, str) or not isinstance(end_raw, str): raise BadRequest('start_date/end_date must be strings') try: start_dt = datetime.strptime(start_raw[:10], '%Y-%m-%d') end_dt = datetime.strptime(end_raw[:10], '%Y-%m-%d') except ValueError as e: raise BadRequest('start_date/end_date must be YYYY-MM-DD') from e if end_dt < start_dt: raise BadRequest('end_date must be on or after start_date') if (end_dt - start_dt).days > 62: raise BadRequest('panchanga range must be <= 63 days') activity = body.get('activity') if activity is not None and not isinstance(activity, str): raise BadRequest('activity must be a string') sunrise = body.get('sunrise', '06:00') sunset = body.get('sunset', '18:00') if not isinstance(sunrise, str) or not isinstance(sunset, str): raise BadRequest('sunrise/sunset must be HH:MM strings') hour_from_sunrise = self._get_float(body, 'hour_from_sunrise', 6.0, 0, 24) lat = lon = tz = None has_location = any(key in body for key in ('lat', 'lon', 'tz')) if has_location: lat = self._get_float(body, 'lat', 0, -90, 90) lon = self._get_float(body, 'lon', 0, -180, 180) tz = self._get_float(body, 'tz', 0, -14, 14) muhurta = _load_local_module('muhurta') try: report = muhurta.panchanga_range_report( start_dt.strftime('%Y-%m-%d'), end_dt.strftime('%Y-%m-%d'), hour_from_sunrise=hour_from_sunrise, sunrise=sunrise, sunset=sunset, activity=activity, lat=lat, lon=lon, tz=tz, ) except ValueError as e: raise BadRequest(str(e)) from e return {'success': True, 'endpoint': 'panchanga_range', 'report': report} def _compute_rectification_gate(self, body): asc_lon = self._asc_lon_from_body(body) declared_accuracy = body.get('declared_accuracy', body.get('accuracy', 'minute')) time_source = body.get('time_source', 'family_clear') if not isinstance(declared_accuracy, str): raise BadRequest('declared_accuracy must be a string') if not isinstance(time_source, str): raise BadRequest('time_source must be a string') module = _load_local_module('birth_time_rectifier') is_boundary, boundary_note = module.check_lagna_boundary(asc_lon) effective_accuracy = module.get_effective_accuracy(declared_accuracy, time_source) enabled_vargas = module.get_enabled_vargas(effective_accuracy) normalized_planets, _, _ = self._normalized_planets_from_body(body) recommended_events = module.recommend_event_types(normalized_planets) confidence_seed = module.calculate_confidence(0, 0, effective_accuracy, is_boundary) disabled = sorted([key for key, value in enabled_vargas.items() if value == 'disabled']) warned = sorted([key for key, value in enabled_vargas.items() if value == 'enabled_with_warning']) enabled = sorted([key for key, value in enabled_vargas.items() if value == 'enabled']) if is_boundary: headline = '出生时间高度敏感，建议先做事件反验' next_action = '优先录入婚姻、迁移、事业转折、健康危机等日期明确事件，再比较相邻候选时间。' elif warned or disabled: headline = '可读主盘，但高敏分盘需要降级' next_action = 'D1 可正常阅读；D9/D10 以上结论需标注时间精度限制。' else: headline = '出生时间风险较低，可进入完整解盘' next_action = '保留原始出生记录来源；重要预测仍建议用 Dasha/Transit/案例验证交叉确认。' return { 'success': True, 'endpoint': 'rectification_gate', 'ascendant': { 'lon': asc_lon, 'sign': SIGNS[int(asc_lon / 30) % 12], 'degree_in_sign': round(asc_lon % 30, 4), }, 'declared_accuracy': declared_accuracy, 'time_source': time_source, 'effective_accuracy': effective_accuracy, 'lagna_boundary': { 'is_sensitive': is_boundary, 'note': boundary_note, }, 'enabled_vargas': enabled_vargas, 'summary': { 'headline': headline, 'enabled': enabled, 'warned': warned, 'disabled': disabled, 'confidence_floor': confidence_seed.get('assessment'), 'recommended_events': recommended_events, 'next_action': next_action, }, } def _compute_case_validation(self, body): planets, _, _ = self._normalized_planets_from_body(body) current_md = body.get('current_md', body.get('dasha_lord', '')) if current_md is not None and not isinstance(current_md, str): raise BadRequest('current_md must be a string') predicted_events = body.get('predicted_events', []) if predicted_events is None: predicted_events = [] if not isinstance(predicted_events, list): raise BadRequest('predicted_events must be an array') transit_desc = body.get('transit_desc', '') if transit_desc is not None and not isinstance(transit_desc, str): raise BadRequest('transit_desc must be a string') analysis = { 'planets': {}, 'dasha': { 'current_md': current_md, 'predicted_events': [str(item)[:120] for item in predicted_events[:12]], }, 'transit': transit_desc or {}, } for planet, data in planets.items(): if planet not in {'Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn'}: continue dignity = self._case_dignity_label(planet, data.get('sign')) if dignity: analysis['planets'][planet] = { 'planet': planet, 'sign': data.get('sign'), 'house': data.get('house'), 'dignity': dignity, } validator = _load_local_module('case_validator') raw = validator.validate_interpretation(analysis) validations = raw.get('validations', []) validated = [item for item in validations if item.get('validated')] unvalidated = [item for item in validations if not item.get('validated')] headline = '案例库支持度较强' if raw.get('overall_confidence', 0) >= 70 else '案例支持不足，需谨慎措辞' if not validations: headline = '当前星盘缺少可验证声明' next_action = ( '优先使用已验证配置做结论；未验证项只作为假设，并补充真实案例或外部来源。' if unvalidated else '可以进入解释层，但仍需保留具体事件预测的置信度上限。' ) mevg_gate = self._mevg_gate_status() return { 'success': True, 'endpoint': 'case_validation', 'fragment_sources': ['case_validator.py', 'mevg_automation.py'], 'analysis': analysis, 'result': raw, 'mevg_gate': mevg_gate, 'summary': { 'headline': headline, 'overall_confidence': raw.get('overall_confidence', 0), 'validated_count': len(validated), 'unvalidated_count': len(unvalidated), 'case_base': raw.get('case_base', ''), 'gate_status': mevg_gate.get('gate_status'), 'top_cases': sorted({ case for item in validated for case in item.get('cases', []) if isinstance(case, str) })[:8], 'next_action': next_action, }, } def _mevg_gate_status(self): try: mevg = _load_local_module('mevg_automation') state_path = getattr(mevg, 'MEVG_STATE_FILE', None) checks = getattr(mevg, 'VALIDATION_CHECKS', []) threshold = getattr(mevg, 'GATE_THRESHOLD', 0.30) if not state_path or not os.path.exists(state_path): return { 'source': 'mevg_automation.py', 'gate_status': 'NOT_INITIALIZED', 'threshold': threshold, 'case_count': 0, 'failed_count': 0, 'fail_rate': 0, 'checks': checks, 'next_action': '运行 MEVG 案例验证后再把外部门控作为预测置信度依据。', } with open(state_path, 'r', encoding='utf-8') as fh: state = json.load(fh) cases = state.get('cases', {}) if isinstance(state, dict) else {} failed = sum(1 for item in cases.values() if isinstance(item, dict) and item.get('verdict') == 'FAIL') fail_rate = failed / len(cases) if cases else 0 return { 'source': 'mevg_automation.py', 'gate_status': state.get('gate_status', 'UNKNOWN'), 'threshold': threshold, 'case_count': len(cases), 'failed_count': failed, 'fail_rate': round(fail_rate, 3), 'last_updated': state.get('last_updated'), 'checks': checks, 'next_action': '若门控 CLOSED，应先校准失败案例，再输出新的预测型解读。', } except Exception as exc: import logging logging.warning(f"[api_server] MEVG gate status unavailable: {exc}") return { 'source': 'mevg_automation.py', 'gate_status': 'UNAVAILABLE', 'error': str(exc), 'next_action': 'MEVG 自动化状态不可用；预测项必须降级为待验证假设。', } def _case_dignity_label(self, planet, sign): exalted = { 'Sun': 'Aries', 'Moon': 'Taurus', 'Mars': 'Capricorn', 'Mercury': 'Virgo', 'Jupiter': 'Cancer', 'Venus': 'Pisces', 'Saturn': 'Libra', } debilitated = { 'Sun': 'Libra', 'Moon': 'Scorpio', 'Mars': 'Cancer', 'Mercury': 'Pisces', 'Jupiter': 'Capricorn', 'Venus': 'Virgo', 'Saturn': 'Aries', } own_signs = { 'Sun': {'Leo'}, 'Moon': {'Cancer'}, 'Mars': {'Aries', 'Scorpio'}, 'Mercury': {'Gemini', 'Virgo'}, 'Jupiter': {'Sagittarius', 'Pisces'}, 'Venus': {'Taurus', 'Libra'}, 'Saturn': {'Capricorn', 'Aquarius'}, } if not sign: return '' if exalted.get(planet) == sign: return 'exalted' if debilitated.get(planet) == sign: return 'debilitated' if sign in own_signs.get(planet, set()): return 'own_sign' if planet == 'Mars': return 'strong' if planet == 'Venus' and sign in {'Taurus', 'Libra', 'Pisces'}: return 'strong' return '' def _compute_divisional_yoga(self, body): normalized, _, asc_sign_idx = self._normalized_planets_from_body(body) if not normalized: raise BadRequest('planets must include longitude data') divisions = body.get('divisions', ['D9', 'D10', 'D12']) if isinstance(divisions, str): divisions = [item.strip().upper() for item in divisions.split(',') if item.strip()] if not isinstance(divisions, list): raise BadRequest('divisions must be a list or comma string') allowed = {'D9', 'D10', 'D12'} selected = [] for item in divisions: token = str(item).strip().upper() if token not in allowed: raise BadRequest('divisional_yoga supports D9, D10, and D12') selected.append(token) selected = selected or ['D9', 'D10', 'D12'] module = _load_local_module('divisional_yoga') results = {} total = 0 for division in selected: yogas = module.detect_varga_yogas(normalized, division, SIGNS[asc_sign_idx]) results[division] = { 'yoga_count': len(yogas), 'yogas': yogas, } total += len(yogas) headline = '分盘 Yoga 有可用证据' if total else '分盘 Yoga 暂无强命中' return { 'success': True, 'endpoint': 'divisional_yoga', 'ascendant': SIGNS[asc_sign_idx], 'divisions': selected, 'result': results, 'summary': { 'headline': headline, 'total_yogas': total, 'next_action': '把 D9 用于关系/内在成熟，D10 用于事业兑现，D12 用于家族与父母主题；不要把分盘 Yoga 当作单点结论。', }, } def _compute_deep_varga_avastha(self, body): _, planet_lons, _ = self._normalized_planets_from_body(body) if not planet_lons: raise BadRequest('planets must include longitude data') asc_lon = self._asc_lon_from_body(body) report = _load_local_module('deep_varga_avastha').build_deep_varga_avastha_report( planet_lons, asc_lon=asc_lon, ) return { 'success': True, 'endpoint': 'deep_varga_avastha', 'report': report, } def _compute_kakshya(self, body): normalized, _, asc_sign_idx = self._normalized_planets_from_body(body) if not normalized: raise BadRequest('planets must include longitude data') result = _load_local_module('kakshya').calc_kakshya_scores(normalized, asc_sign_idx) planets = result.get('planets', {}) strongest = sorted( planets.items(), key=lambda item: item[1].get('kakshya_strength', 0), reverse=True, )[:3] weakest = sorted( planets.items(), key=lambda item: item[1].get('kakshya_strength', 0), )[:3] avg = sum(item.get('kakshya_strength', 0) for item in planets.values()) / max(len(planets), 1) headline = 'Kakshya 度数层支持较强' if avg >= 6.5 else 'Kakshya 度数层需要谨慎使用' return { 'success': True, 'endpoint': 'kakshya', 'ascendant': SIGNS[asc_sign_idx], 'result': result, 'summary': { 'headline': headline, 'average_strength': round(avg, 2), 'strongest': [{'planet': name, **data} for name, data in strongest], 'weakest': [{'planet': name, **data} for name, data in weakest], 'next_action': '把 Kakshya 用作 Ashtakavarga/Transit 的度数级触发层，只在已有 Dasha 或主题承诺时提高事件窗口权重。', }, } def _compute_bhava_bala_api(self, body): normalized, _, asc_sign_idx = self._normalized_planets_from_body(body) if not normalized: raise BadRequest('planets must include longitude data') asc_lon = self._asc_lon_from_body(body) asc_sign = SIGNS[asc_sign_idx] asc_degree = asc_lon % 30 house_signs = [SIGNS[(asc_sign_idx + i) % 12] for i in range(12)] house_degrees = [asc_degree for _ in range(12)] planet_shadbala = self._planet_shadbala_from_body(body, normalized) result = _load_local_module('bhava_bala').calc_bhava_bala( house_signs, house_degrees, asc_sign, asc_degree, normalized, planet_shadbala, ) houses = result.get('houses', []) strongest = sorted(houses, key=lambda item: item.get('total', 0), reverse=True)[:3] weakest = sorted(houses, key=lambda item: item.get('total', 0))[:3] headline = '宫位力量结构清晰' if strongest and strongest[0].get('total', 0) >= 45 else '宫位力量偏分散' return { 'success': True, 'endpoint': 'bhava_bala', 'ascendant': asc_sign, 'result': result, 'summary': { 'headline': headline, 'strongest': strongest, 'weakest': weakest, 'next_action': '优先阅读最强宫位对应的人生领域；最弱宫位只作为风险提示，需要结合宫主、Dasha 与 Transit 确认。', }, } def _planet_shadbala_from_body(self, body, planets): raw = body.get('planet_shadbala') or body.get('shadbala') or {} result = {} if isinstance(raw, dict): for planet, value in raw.items(): if isinstance(value, dict): number = value.get('virupas', value.get('total_virupas', value.get('score', value.get('rupas')))) else: number = value try: result[planet] = float(number) except (TypeError, ValueError): continue for planet in ['Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn']: if planet in result: continue pdata = planets.get(planet, {}) dignity = self._case_dignity_label(planet, pdata.get('sign')) score = 35.0 if dignity in {'exalted', 'own_sign'}: score = 55.0 elif dignity == 'strong': score = 45.0 elif dignity == 'debilitated': score = 24.0 if pdata.get('house') in (1, 4, 7, 10): score += 5.0 result[planet] = score return result def _compute_transit_triggers(self, body): start_raw = body.get('start', body.get('start_date', datetime.now().strftime('%Y-%m-%d'))) end_raw = body.get('end', body.get('end_date')) if not isinstance(start_raw, str): raise BadRequest('start must be YYYY-MM-DD') if end_raw is not None and not isinstance(end_raw, str): raise BadRequest('end must be YYYY-MM-DD') try: start_date = datetime.strptime(start_raw[:10], '%Y-%m-%d') end_date = datetime.strptime((end_raw or (start_date + timedelta(days=90)).strftime('%Y-%m-%d'))[:10], '%Y-%m-%d') except ValueError as e: raise BadRequest('start/end must be YYYY-MM-DD') from e if end_date < start_date: raise BadRequest('end must be after start') if (end_date - start_date).days > 730: raise BadRequest('transit search range must be <= 730 days') planets_to_check = body.get('planets_to_check') raw_planets = body.get('natal_planets', body.get('chart_planets')) if raw_planets is None and isinstance(body.get('planets'), dict): raw_planets = body.get('planets') elif raw_planets is None and isinstance(body.get('planets'), list): planets_to_check = body.get('planets') raw_planets = {} if planets_to_check is not None: if not isinstance(planets_to_check, list): raise BadRequest('planets_to_check must be an array') planets_to_check = [str(item) for item in planets_to_check[:9]] planets = self._validate_planets(raw_planets or {}) body_for_asc = {**body, 'planets': planets} asc_lon = self._asc_lon_from_body(body_for_asc) natal_data = {'asc': asc_lon, 'planets': planets} result = _load_local_module('transit_trigger').search_all_transit_triggers( natal_data, start_date, end_date, planets_to_check=planets_to_check, ayanamsa_name=body.get('ayanamsa', 'lahiri'), ) top_triggers = result.get('triggers', [])[:6] headline = '发现可观察过境触发点' if result.get('total_triggers', 0) else '当前区间未发现精确触发' return { 'success': True, 'endpoint': 'transit', 'result': result, 'triggers': result.get('triggers', []), 'summary': { 'headline': headline, 'period': result.get('search_period', {}), 'total_triggers': result.get('total_triggers', 0), 'top_triggers': top_triggers, 'next_action': '把过境触发作为时间窗口，不单独定事件；优先与 Dasha、Ashtakavarga、Kakshya 和本命承诺交叉确认。', }, } def _compute_bhava_chalit(self, body): _, planet_lons = self._planet_lons_from_body(body) if not planet_lons: raise BadRequest('planets must include longitude data') ascendant = body.get('ascendant', {}) if not isinstance(ascendant, dict): raise BadRequest('ascendant must be an object') asc_lon = ascendant.get('lon') if asc_lon is None and ascendant.get('sign') in SIGNS: asc_lon = SIGNS.index(ascendant['sign']) * 30 + float(ascendant.get('degree_in_sign', ascendant.get('degree', 0))) if asc_lon is None: asc_lon = self._normalize_degree(body, 'asc_lon', 0) else: asc_lon = float(asc_lon) % 360 mc_lon = self._normalize_degree(body, 'mc_lon', (asc_lon + 270) % 360) house_system = body.get('house_system', 'sripati') if not isinstance(house_system, str): raise BadRequest('house_system must be a string') requested_house_system = house_system.lower().strip() mode = body.get('mode', 'compare') if not isinstance(mode, str): raise BadRequest('mode must be a string') calculator = _load_local_module('bhava_chalit').BhavaChalitCalculator() available_house_systems = sorted(calculator.HOUSE_SYSTEMS.keys()) if requested_house_system not in calculator.HOUSE_SYSTEMS: raise BadRequest(f'unknown house_system: {house_system}') selected_house_system = requested_house_system jd = lat = lon = None fallback_reason = '' calculation_note = f'Bhava Chalit uses {calculator.HOUSE_SYSTEMS[selected_house_system]}.' if selected_house_system in {'placidus', 'koch'}: try: year = self._get_int(body, 'year', 1990, 1800, 2400) month = self._get_int(body, 'month', 6, 1, 12) day = self._get_int(body, 'day', 15, 1, 31) hour = self._get_float(body, 'hour', 12, 0, 23) minute = self._get_float(body, 'minute', 0, 0, 59) second = self._get_birth_second(body) lat = self._get_float(body, 'lat', body.get('birth_lat', 0), -90, 90) lon = self._get_float(body, 'lon', body.get('birth_lon', 0), -180, 180) tz = self._parse_timezone(body, lat, lon, year, month, day, hour, minute, second) datetime(year, month, day, int(hour), int(minute), int(second)) import swisseph as swe hour_ut = self._birth_hour_decimal(hour, minute, second) - tz jd = swe.julday(year, month, day, hour_ut) calculation_note = f'{selected_house_system} cusps use swisseph houses with birth JD and location.' except Exception as exc: fallback_reason = f'{selected_house_system} requires swisseph plus valid birth date, lat, lon and tz; fell back to sripati: {exc}' selected_house_system = 'sripati' jd = lat = lon = None calculation_note = 'Fallback to Sripati because time-based house cusps were unavailable.' if mode == 'chart': result = calculator.get_bhava_chalit_chart(planet_lons, asc_lon, mc_lon, selected_house_system, jd, lat, lon) elif mode == 'boundaries': result = calculator.calculate_bhava_boundaries(asc_lon, mc_lon, selected_house_system, jd, lat, lon) else: result = calculator.compare_rashi_vs_bhava(planet_lons, asc_lon, mc_lon, selected_house_system, jd, lat, lon) result.setdefault('summary', { 'total_planets': len(planet_lons), 'shifted_count': result.get('shifted_count', 0), 'shifted_names': [shift.get('planet') for shift in result.get('shifts', []) if isinstance(shift, dict)], }) result['requested_house_system'] = requested_house_system result['selected_house_system'] = selected_house_system result['available_house_systems'] = available_house_systems result['fallback_reason'] = fallback_reason result['calculation_note'] = calculation_note return { 'success': True, 'endpoint': 'bhava_chalit', 'mode': mode, 'requested_house_system': requested_house_system, 'selected_house_system': selected_house_system, 'available_house_systems': available_house_systems, 'fallback_reason': fallback_reason, 'calculation_note': calculation_note, 'result': result, } def _compute_sudarshana(self, body): _, planet_lons = self._planet_lons_from_body(body) if not {'Sun', 'Moon'} <= set(planet_lons): raise BadRequest('planets must include Sun and Moon longitude data') ascendant = body.get('ascendant', {}) if not isinstance(ascendant, dict): raise BadRequest('ascendant must be an object') asc_lon = ascendant.get('lon') if asc_lon is None and ascendant.get('sign') in SIGNS: asc_lon = SIGNS.index(ascendant['sign']) * 30 + float(ascendant.get('degree_in_sign', ascendant.get('degree', 0))) if asc_lon is None: asc_lon = self._normalize_degree(body, 'asc_lon', 0) else: asc_lon = float(asc_lon) % 360 house = body.get('house') if house is not None: house = self._get_int(body, 'house', 1, 1, 12) result = _load_local_module('sudarshana_chakra').calc_sudarshana_chakra(planet_lons, asc_lon, house) return {'success': True, 'endpoint': 'sudarshana', 'result': result} def _compute_nakshatra_full(self, body): chart_data, _ = self._chart_payload_from_body(body) age = body.get('age') if age is not None: age = self._get_float(body, 'age', 0, 0, 150) transit_date = body.get('transit_date') if transit_date is not None and not isinstance(transit_date, str): raise BadRequest('transit_date must be a string') result = _load_local_module('nakshatra_advanced').nakshatra_full_report( chart_data, age=age, transit_date=transit_date, ) return {'success': True, 'endpoint': 'nakshatra_full', 'result': result} def _capability_audit(self): registry = self._read_technique_registry() techniques = registry.get('techniques', {}) engine_commands = self._scan_engine_commands() api_endpoints = self._scan_api_endpoints() app_tabs = self._scan_app_tabs() local_sources = self._scan_local_open_source_sources() command_set = set(engine_commands) api_command_map = API_COMMAND_MAP api_backed_commands = sorted( command for command, endpoint in api_command_map.items() if endpoint in api_endpoints or command in command_set ) app_visible_topics = self._app_visible_topics(app_tabs) registry_commands = sorted({ command for technique in techniques.values() for command in technique.get('commands', []) if isinstance(command, str) }) registry_only_commands = sorted(set(registry_commands) - command_set) engine_not_api = sorted(command_set - set(api_backed_commands)) status_counts = {} domain_counts = {} for technique in techniques.values(): status = technique.get('status', 'unknown') status_counts[status] = status_counts.get(status, 0) + 1 for domain in technique.get('domains', []): domain_counts[domain] = domain_counts.get(domain, 0) + 1 direct_sources = [s for s in local_sources if s.get('reuse') == 'direct'] caution_sources = [s for s in local_sources if s.get('reuse') == 'caution'] unknown_sources = [s for s in local_sources if s.get('reuse') == 'unknown'] priority_gaps = self._build_priority_gaps(techniques, engine_not_api, app_visible_topics) productization = self._build_productization_matrix( techniques, command_set, set(api_backed_commands), app_visible_topics, ) ux_productization = self._build_ux_productization_matrix(productization['rows']) return { 'success': True, 'generated_at': datetime.utcnow().isoformat(timespec='seconds') + 'Z', 'registry': { 'version': registry.get('version'), 'technique_count': len(techniques), 'status_counts': status_counts, 'domain_counts': dict(sorted(domain_counts.items())), 'source_inspiration': registry.get('source_inspiration', []), }, 'techniques': [ { 'id': key, 'name': value.get('name', key), 'status': value.get('status', 'unknown'), 'domains': value.get('domains', []), 'commands': value.get('commands', []), 'output_paths': value.get('output_paths', []), 'audit_label': value.get('audit_label', value.get('name', key)), 'limitation': value.get('limitation', ''), 'missing_impact': value.get('missing_impact', ''), } for key, value in sorted(techniques.items()) ], 'surfaces': { 'engine_command_count': len(engine_commands), 'engine_commands': engine_commands, 'api_endpoint_count': len(api_endpoints), 'api_endpoints': api_endpoints, 'api_backed_commands': api_backed_commands, 'engine_not_api': engine_not_api, 'registry_only_commands': registry_only_commands, 'app_tab_count': len(app_tabs), 'app_tabs': app_tabs, 'app_visible_topics': app_visible_topics, }, 'local_open_source': { 'source_count': len(local_sources), 'direct_reuse_count': len(direct_sources), 'caution_count': len(caution_sources), 'unknown_count': len(unknown_sources), 'sources': local_sources, }, 'external_research': self._external_research_matrix(), 'priority_gaps': priority_gaps, 'productization': productization, 'ux_productization': ux_productization, } def _technique_catalog(self): audit = self._capability_audit() rows = self._build_technique_catalog_rows(audit) domains = sorted({ domain for row in rows for domain in row.get('domains', []) }) endpoints = sorted({ endpoint for row in rows for endpoint in row.get('api_endpoints', []) }) return { 'success': True, 'generated_at': audit.get('generated_at'), 'registry': audit.get('registry', {}), 'summary': { 'technique_count': len(rows), 'domain_count': len(domains), 'api_endpoint_count': len(endpoints), 'runnable_count': sum(1 for row in rows if row.get('runnable')), }, 'filters': { 'domains': domains, 'levels': ['productized', 'api_backed', 'engine_or_full_reading', 'registry_only'], 'statuses': sorted({row.get('status') for row in rows if row.get('status')}), 'api_endpoints': endpoints, }, 'api_command_map': API_COMMAND_MAP, 'example_payloads': self._technique_example_payloads(), 'api_docs': self._technique_api_docs(), 'techniques': rows, } def _build_technique_catalog_rows(self, audit): product_rows = { row.get('id'): row for row in audit.get('productization', {}).get('rows', []) if row.get('id') } ux_rows = { row.get('id'): row for row in audit.get('ux_productization', {}).get('rows', []) if row.get('id') } api_endpoints = set(audit.get('surfaces', {}).get('api_endpoints', [])) rows = [] for technique in audit.get('techniques', []): product = product_rows.get(technique.get('id'), {}) ux = ux_rows.get(technique.get('id'), {}) commands = sorted(set((technique.get('commands') or []) + (product.get('commands') or []))) mapped = [ API_COMMAND_MAP.get(command) for command in commands if API_COMMAND_MAP.get(command) in api_endpoints ] if technique.get('id') == 'jaimini_chara_dasha' and '/api/dasha/chara' in api_endpoints: mapped.append('/api/dasha/chara') runnable = [endpoint for endpoint in mapped if endpoint in TECHNIQUE_EXAMPLE_ENDPOINTS] primary_endpoint = self._primary_catalog_endpoint(technique, mapped, runnable) rows.append({ 'id': technique.get('id'), 'name': technique.get('name'), 'audit_label': technique.get('audit_label'), 'status': technique.get('status'), 'domains': sorted(set((technique.get('domains') or []) + (product.get('domains') or []))), 'commands': commands, 'api_commands': product.get('api_commands', []), 'api_endpoints': sorted(set(mapped)), 'runnable': bool(runnable), 'example_endpoint': runnable[0] if runnable else '', 'method_docs': self._technique_method_doc(technique, product, primary_endpoint), 'output_paths': sorted(set((technique.get('output_paths') or []) + (product.get('output_paths') or []))), 'level': product.get('level', 'registry_only'), 'reason': product.get('reason') or technique.get('limitation') or '', 'next_action': product.get('next_action') or ux.get('ux_next_action') or technique.get('missing_impact') or '', 'ux_level': ux.get('ux_level', 'not_user_ready'), 'ux_score': ux.get('ux_score', 0), 'visible_markers': product.get('visible_markers', []), }) order = {'registry_only': 0, 'engine_or_full_reading': 1, 'api_backed': 2, 'productized': 3} return sorted(rows, key=lambda row: (order.get(row.get('level'), 0), row.get('name') or '')) def _primary_catalog_endpoint(self, technique, mapped, runnable): candidates = runnable or mapped or [] if not candidates: return '' text = ' '.join([ str(technique.get('id', '')), str(technique.get('name', '')), str(technique.get('audit_label', '')), ' '.join(technique.get('domains') or []), ]).lower() endpoint_keywords = [ ('/api/thematic_report', ['thematic', '主题', 'report_orchestrator', 'reading', 'report']), ('/api/relationship', ['relationship', 'spouse', '婚姻', '感情']), ('/api/career', ['career', '事业']), ('/api/dasha', ['dasha', 'vimshottari']), ('/api/dasha/chara', ['chara dasha', 'chara_dasha', 'jaimini dasha']), ('/api/yogas', ['yoga', 'dosha']), ('/api/shadbala', ['shadbala']), ('/api/deep_varga_avastha', ['deep_varga_avastha', 'deep varga', 'avastha', 'sayanadi', 'shayanadi', 'd24', 'd30', 'd60']), ('/api/ashtakavarga', ['ashtakavarga']), ('/api/jaimini', ['jaimini', 'karaka', 'arudha']), ] for endpoint, keywords in endpoint_keywords: if endpoint in candidates and any(keyword in text for keyword in keywords): return endpoint return candidates[0] def _compute_technique_example(self, body): endpoint = body.get('endpoint') if not isinstance(endpoint, str): raise BadRequest('endpoint must be a string') endpoint = endpoint.strip() if endpoint not in TECHNIQUE_EXAMPLE_ENDPOINTS: raise BadRequest('endpoint is not runnable from technique explorer') payloads = self._technique_example_payloads() payload = body.get('payload') if payload is None: payload = payloads.get(endpoint) if not isinstance(payload, dict): raise BadRequest('payload must be an object') payload = self._sanitize_technique_example_payload(endpoint, payload) result = self._dispatch_technique_endpoint(endpoint, payload) return { 'success': True, 'endpoint': 'technique_example', 'target_endpoint': endpoint, 'sample_payload': payload, 'result': result, } def _real_case_revalidation(self): validator_path = os.path.join(REPO_ROOT, 'tests', 'run_real_case_revalidation.py') spec = importlib.util.spec_from_file_location('_jyotish_real_case_revalidation', validator_path) if not spec or not spec.loader: raise RuntimeError('Cannot load real case revalidation runner') module = importlib.util.module_from_spec(spec) spec.loader.exec_module(module) args = argparse.Namespace( python=sys.executable, min_pass_rate=0.98, degree_tolerance=1.0, ) report = module.build_report(args) return { 'success': bool(report.get('valid')), 'endpoint': 'real_case_revalidation', 'scope': report.get('scope'), 'accuracy_boundary': '公开人物星座级一致率，不是人生事件预测准确率。', 'public_reference': { 'label': '公开人物星座级一致率', 'passed': report.get('gated_passed_checks'), 'total': report.get('gated_total_checks'), 'pass_rate': report.get('pass_rate'), }, 'all_checks': { 'passed': report.get('passed_checks'), 'total': report.get('total_checks'), }, 'controversial_reference': { 'case_count': report.get('controversial_reference_cases'), 'note': '来源矛盾、时区争议或边界度数样本保留展示，但不计入发布阻断口径。', }, 'failures': report.get('failures', []), } def _dispatch_technique_endpoint(self, endpoint, payload): dispatch = { '/api/ashtakavarga': self._compute_ashtakavarga, '/api/bhava_bala': self._compute_bhava_bala_api, '/api/bhava_chalit': self._compute_bhava_chalit, '/api/career': self._compute_career, '/api/case_validation': self._compute_case_validation, '/api/dasha': self._compute_dasha_system, '/api/dasha/chara': self._compute_chara_dasha, '/api/deep_varga_avastha': self._compute_deep_varga_avastha, '/api/divisional_yoga': self._compute_divisional_yoga, '/api/jaimini': self._compute_jaimini, '/api/kakshya': self._compute_kakshya, '/api/kp': self._compute_kp, '/api/muhurta': self._compute_muhurta, '/api/nakshatra_full': self._compute_nakshatra_full, '/api/pancha_mahapurusha': self._compute_pmc, '/api/prashna': self._compute_prashna, '/api/rectification_gate': self._compute_rectification_gate, '/api/relationship': self._compute_relationship, '/api/remedies': self._compute_remedies, '/api/sade_sati': self._compute_sade_sati, '/api/shadbala': self._compute_shadbala, '/api/sudarshana': self._compute_sudarshana, '/api/synastry': self._compute_synastry, '/api/thematic_report': self._compute_thematic_report, '/api/transit': self._compute_transit_triggers, '/api/varga_full': self._compute_varga_full, '/api/yogas': self._compute_yogas_api, } return dispatch[endpoint](payload) def _sanitize_technique_example_payload(self, endpoint, payload): text = json.dumps(payload, ensure_ascii=False, default=str) if len(text) > 120_000: raise BadRequest('technique example payload too large') if endpoint == '/api/transit': start_raw = str(payload.get('start', payload.get('start_date', datetime.now().strftime('%Y-%m-%d'))))[:10] try: start = datetime.strptime(start_raw, '%Y-%m-%d') except ValueError as e: raise BadRequest('transit start must be YYYY-MM-DD') from e end = payload.get('end') or payload.get('end_date') if end: try: end_dt = datetime.strptime(str(end)[:10], '%Y-%m-%d') except ValueError as e: raise BadRequest('transit end must be YYYY-MM-DD') from e if (end_dt - start).days > 180: payload = {**payload, 'end': (start + timedelta(days=180)).strftime('%Y-%m-%d')} else: payload = {**payload, 'end': (start + timedelta(days=90)).strftime('%Y-%m-%d')} return payload def _technique_api_docs(self): docs = {} payloads = self._technique_example_payloads() for endpoint in sorted(TECHNIQUE_EXAMPLE_ENDPOINTS): payload = payloads.get(endpoint, {}) docs[endpoint] = { 'method': 'POST', 'endpoint': endpoint, 'curl': self._curl_example(endpoint, payload), 'openapi': self._openapi_operation(endpoint, payload), 'notes': self._endpoint_method_notes(endpoint), } return docs def _technique_method_doc(self, technique, product, endpoint): return { 'summary': product.get('reason') or technique.get('limitation') or technique.get('audit_label') or technique.get('name') or '', 'boundary': product.get('next_action') or technique.get('missing_impact') or '把该技法作为证据层使用，并结合 Dasha、Transit、案例验证共同收敛。', 'primary_endpoint': endpoint, 'source_paths': sorted(set((technique.get('output_paths') or []) + (product.get('output_paths') or [])))[:8], 'api_doc_key': endpoint if endpoint in TECHNIQUE_EXAMPLE_ENDPOINTS else '', } def _curl_example(self, endpoint, payload): body = json.dumps(payload or {}, ensure_ascii=False, indent=2, sort_keys=True) return ( "curl -sS -X POST http://127.0.0.1:5200" f"{endpoint} \\\n" " -H 'Content-Type: application/json' \\\n" " --data-binary " + json.dumps(body, ensure_ascii=False) ) def _openapi_operation(self, endpoint, payload): return { 'path': endpoint, 'post': { 'summary': self._endpoint_summary(endpoint), 'operationId': self._endpoint_operation_id(endpoint), 'requestBody': { 'required': True, 'content': { 'application/json': { 'schema': { 'type': 'object', 'additionalProperties': True, 'example': payload or {}, }, }, }, }, 'responses': { '200': { 'description': 'Successful Jyotish calculation result', 'content': { 'application/json': { 'schema': {'type': 'object', 'additionalProperties': True}, }, }, }, '400': {'description': 'Invalid payload or unsupported option'}, }, }, } def _endpoint_operation_id(self, endpoint): return 'post' + ''.join(part.title() for part in endpoint.strip('/').replace('_', '-').split('-')) def _endpoint_summary(self, endpoint): labels = { '/api/ashtakavarga': 'Compute SAV/BAV/PAV/Sodhita Ashtakavarga evidence', '/api/bhava_bala': 'Compute Bhava Bala house strength evidence', '/api/bhava_chalit': 'Compare Rashi and Bhava Chalit house placements', '/api/career': 'Compute career analysis from planets and ascendant', '/api/case_validation': 'Run case validation and MEVG gate status', '/api/dasha': 'Compute Dasha periods and Vimshottari analysis layer', '/api/dasha/chara': 'Compute explicit Jaimini Chara Dasha timing layer', '/api/deep_varga_avastha': 'Compute Sayanadi/Shayanadi avastha and D24/D30/D60 templates', '/api/divisional_yoga': 'Detect D9/D10/D12 divisional yogas', '/api/jaimini': 'Compute Jaimini karaka, arudha, dasha, and karakamsha data', '/api/kakshya': 'Compute Kakshya degree-level trigger support', '/api/kp': 'Compute KP significator and sublord analysis', '/api/muhurta': 'Compute Muhurta day quality evidence', '/api/nakshatra_full': 'Compute advanced Nakshatra report', '/api/pancha_mahapurusha': 'Assess Pancha Mahapurusha yoga strength', '/api/prashna': 'Compute Prashna chart and answer evidence', '/api/rectification_gate': 'Evaluate birth-time precision gate', '/api/relationship': 'Compute relationship and spouse-status evidence', '/api/remedies': 'Generate low-risk remedies from doshas/strength/dasha', '/api/sade_sati': 'Compute Sade Sati status and phase', '/api/shadbala': 'Compute Shadbala plus advanced evidence layer', '/api/sudarshana': 'Compute Sudarshana Chakra evidence', '/api/synastry': 'Compute 16-factor/Ashtakoot compatibility score', '/api/thematic_report': 'Generate thematic report with sample/custom/derived evidence', '/api/transit': 'Search transit trigger windows', '/api/varga_full': 'Compute divisional chart positions', '/api/yogas': 'Compute yoga rule-engine and curse-yoga evidence', } return labels.get(endpoint, f'Run {endpoint} calculation') def _endpoint_method_notes(self, endpoint): notes = { '/api/thematic_report': '传 birth/chart payload 时会进入 derived_chart_evidence；只传 theme 时使用样例证据。', '/api/shadbala': 'advanced_layer 是证据补充，不覆盖主 Shadbala 总分。', '/api/yogas': 'curse_yogas 是高风险提示层，不能替代健康/法律/安全建议。', '/api/case_validation': 'MEVG 只读门控不运行外部子进程。', '/api/report_artifact': '报告 artifact 不在 Technique Explorer 白名单内，避免把任意 HTML 当作样例执行。', } return notes.get(endpoint, '样例 payload 可直接复制到本地 API；正式报告仍需结合上下文和边界说明。') def _technique_example_payloads(self): today = datetime.utcnow().strftime('%Y-%m-%d') transit_end = (datetime.utcnow() + timedelta(days=60)).strftime('%Y-%m-%d') base = { 'planets': SAMPLE_PLANETS, 'ascendant': SAMPLE_ASCENDANT, } birth = { 'year': 1990, 'month': 1, 'day': 1, 'hour': 12, 'minute': 0, 'lat': 28.6, 'lon': 77.2, 'tz': 5.5, } return { '/api/ashtakavarga': base, '/api/bhava_bala': base, '/api/bhava_chalit': {**base, 'mode': 'compare', 'house_system': 'sripati'}, '/api/career': {'planets': SAMPLE_PLANETS, 'asc_sign': 'Aries'}, '/api/case_validation': {**base, 'current_md': 'Jupiter', 'predicted_events': ['事业巅峰', '关系发展'], 'transit_desc': 'Double Jupiter Saturn activation'}, '/api/dasha': {**base, **birth, 'dasha': 'vimshottari'}, '/api/dasha/chara': {**base, **birth, 'antardasha': True}, '/api/deep_varga_avastha': base, '/api/divisional_yoga': {**base, 'divisions': ['D9', 'D10', 'D12']}, '/api/jaimini': {**base, **birth, 'mode': 'all'}, '/api/kakshya': base, '/api/kp': {'planets': SAMPLE_PLANETS, 'asc_sign_idx': 0}, '/api/muhurta': {'date': today, 'activity': 'business', 'hour_from_sunrise': 6.0}, '/api/nakshatra_full': {**base, 'age': 36, 'transit_date': today}, '/api/pancha_mahapurusha': {'planets': SAMPLE_PLANETS, 'sun_degree': SAMPLE_PLANETS['Sun']['lon']}, '/api/prashna': {'planets': SAMPLE_PLANETS, 'question': 'general'}, '/api/rectification_gate': {**base, 'declared_accuracy': 'minute', 'time_source': 'family_clear'}, '/api/relationship': {'planets': SAMPLE_PLANETS, 'asc_sign': 'Aries', 'dasha_info': {'maha_dasha': 'Venus', 'antar_dasha': 'Jupiter'}}, '/api/remedies': {'shadbala': {'Sun': {'rupas': 4.1}, 'Moon': {'rupas': 3.8}}, 'doshas': ['manglik'], 'dasha_lord': 'Venus'}, '/api/sade_sati': {'moon_degree': SAMPLE_PLANETS['Moon']['lon'], 'asc_degree': SAMPLE_ASCENDANT['lon'], 'saturn_degree': SAMPLE_PLANETS['Saturn']['lon']}, '/api/shadbala': {**base, **birth}, '/api/sudarshana': base, '/api/synastry': {'male_moon': SAMPLE_PLANETS['Moon']['lon'], 'female_moon': 243.0}, '/api/thematic_report': {'theme': 'marriage'}, '/api/transit': {'natal_planets': SAMPLE_PLANETS, 'ascendant': SAMPLE_ASCENDANT, 'start': today, 'end': transit_end, 'planets_to_check': ['Saturn', 'Jupiter', 'Rahu', 'Ketu']}, '/api/varga_full': {**base, 'divisions': ['D9', 'D10']}, '/api/yogas': base, } def _read_technique_registry(self): path = os.path.join(REPO_ROOT, 'references', 'technique_registry.json') try: with open(path, 'r', encoding='utf-8') as f: data = json.load(f) if isinstance(data, dict): return data except (OSError, json.JSONDecodeError): pass return {'version': None, 'techniques': {}} def _scan_engine_commands(self): path = os.path.join(SCRIPTS_DIR, 'jyotish_engine.py') try: with open(path, 'r', encoding='utf-8') as f: text = f.read() except OSError: return [] return sorted(set(re.findall(r"add_parser\(['\"]([^'\"]+)['\"]", text))) def _scan_api_endpoints(self): path = os.path.abspath(__file__) try: with open(path, 'r', encoding='utf-8') as f: text = f.read() except OSError: return [] return sorted(set(re.findall(r"path == ['\"](/api/[^'\"]+)['\"]", text))) def _scan_app_tabs(self): path = os.path.join(REPO_ROOT, 'jyotish-app', 'index.html') try: with open(path, 'r', encoding='utf-8') as f: text = f.read() except OSError: return [] return sorted(set(re.findall(r'data-tab="([^"]+)"', text))) def _scan_app_source_text(self): root = os.path.join(REPO_ROOT, 'jyotish-app') if not os.path.isdir(root): return '' chunks = [] for dirpath, dirnames, filenames in os.walk(root): dirnames[:] = [ d for d in dirnames if d not in {'node_modules', 'dist', '.vite', '.git'} ] for filename in filenames: if not filename.endswith(('.js', '.html', '.css')): continue try: with open(os.path.join(dirpath, filename), 'r', encoding='utf-8', errors='ignore') as f: chunks.append(f.read(40000)) except OSError: continue return '\n'.join(chunks).lower() def _scan_local_open_source_sources(self): root = os.path.join(REPO_ROOT, 'references', 'open_source_sources') if not os.path.isdir(root): return [] sources = [] for name in sorted(os.listdir(root)): path = os.path.join(root, name) if not os.path.isdir(path): continue files = [] for dirpath, dirnames, filenames in os.walk(path): dirnames[:] = [d for d in dirnames if d not in {'.git', '__pycache__', '.pytest_cache'}] for filename in filenames: rel = os.path.relpath(os.path.join(dirpath, filename), path) files.append(rel) if len(files) >= 500: break if len(files) >= 500: break license_name = self._detect_source_license(path, files) if license_name == 'unknown': license_name = self._license_from_research_index(name) sources.append({ 'name': name, 'path': os.path.relpath(path, REPO_ROOT), 'file_count': len(files), 'license': license_name, 'reuse': self._reuse_level(license_name), 'modules': self._infer_source_modules(files), 'has_readme': any(os.path.basename(f).lower() == 'readme.md' for f in files), 'has_skill': any(os.path.basename(f).lower() == 'skill.md' for f in files), }) return sources def _detect_source_license(self, source_path, files): license_files = [ f for f in files if os.path.basename(f).lower() in {'license', 'license.md', 'licence', 'licence.md', 'copying'} ] text = '' for rel in license_files[:2]: try: with open(os.path.join(source_path, rel), 'r', encoding='utf-8', errors='ignore') as f: text += '\n' + f.read(6000) except OSError: continue haystack = (text + '\n' + source_path).lower() if 'agpl' in haystack: return 'AGPL' if 'gpl' in haystack and 'lesser' not in haystack: return 'GPL' if 'apache license' in haystack or 'apache-2.0' in haystack: return 'Apache-2.0' if 'mit license' in haystack or '/mit' in haystack: return 'MIT' return 'unknown' def _license_from_research_index(self, source_name): scan_path = os.path.join(REPO_ROOT, 'references', 'open-source-jyotish-scan-2026.md') integration_path = os.path.join(REPO_ROOT, 'references', 'open_source_sources', 'INTEGRATION_REPORT.md') text = '' for path in (scan_path, integration_path): try: with open(path, 'r', encoding='utf-8', errors='ignore') as f: text += '\n' + f.read() except OSError: continue if not text: return 'unknown' escaped = re.escape(source_name) patterns = [ rf'\|\s*\*\*{escaped}\*\*\s*\|[^|\n]*\|\s*(MIT|Apache-2\.0|AGPL|GPL)', rf'{escaped}[^\n]{{0,80}}\((MIT|Apache-2\.0|AGPL|GPL)', rf'{escaped}[^\n]{{0,80}}\|\s*(MIT|Apache-2\.0|AGPL|GPL)', ] for pattern in patterns: match = re.search(pattern, text, re.IGNORECASE) if match: license_name = match.group(1) if license_name.lower() == 'mit': return 'MIT (research)' if license_name.lower().startswith('apache'): return 'Apache-2.0 (research)' return f'{license_name.upper()} (research)' return 'unknown' def _reuse_level(self, license_name): base_license = (license_name or '').split(' ', 1)[0] if base_license in {'MIT', 'Apache-2.0'}: return 'direct' if base_license in {'AGPL', 'GPL'}: return 'caution' return 'unknown' def _infer_source_modules(self, files): module_keywords = { 'ashtakavarga': ['ashtakavarga'], 'shadbala': ['shadbala', 'strength'], 'dasha': ['dasha', 'dasa', 'dashas'], 'jaimini': ['jaimini', 'karaka', 'arudha'], 'kp': ['kp', 'sublord', 'horary'], 'prashna': ['prashna', 'prasna', 'horary'], 'muhurta': ['muhurta', 'muhurtha'], 'tajika': ['tajika', 'varsha', 'solar_return'], 'synastry': ['synastry', 'matchmaking', 'compat'], 'remedies': ['remedies', 'upaya'], 'panchanga': ['panchang', 'panchanga', 'tithi'], 'varga': ['varga', 'divisional'], 'yoga': ['yoga'], 'transit': ['transit', 'gochar'], } lower_files = [f.lower() for f in files] found = [] for module, keywords in module_keywords.items(): if any(any(keyword in f for keyword in keywords) for f in lower_files): found.append(module) return found def _app_visible_topics(self, tabs): mapping = { 'chart': 'D1/Rashi', 'complete': 'Full Reading', 'karaka': 'Jaimini Karaka', 'houses': 'Bhava', 'aspects': 'Aspects', 'yogas': 'Yoga', 'vargas': 'Varga', 'ashtakavarga': 'Ashtakavarga', 'shadbala': 'Shadbala', 'dasha': 'Dasha', 'transit': 'Transit', 'deep': 'PACDARES/Argala', 'extended': 'Bhava Bala/Vimsopaka', 'remedies': 'Remedies', 'synastry': 'Synastry', 'prashna': 'Prashna', 'kp': 'KP', 'verify': 'Verification', 'transit-compare': 'Transit Compare', } topics = [mapping[t] for t in tabs if t in mapping] source_text = self._scan_app_source_text() source_markers = { 'Muhurta': ['computemuhurta', 'muhurta'], 'Tajika': ['computeannual', 'varshaphala', 'tajika'], 'Solar Return': ['computeannual', 'solar return', 'varshaphala'], 'Bhava Chalit': ['computebhavachalit', 'bhava chalit', 'bhava_chalit'], 'Sudarshana': ['computesudarshana', 'sudarshana'], 'Nakshatra Full': ['computenakshatrafull', 'nakshatra_full'], 'Varga Full': ['computevargafull', 'varga_full'], 'Jaimini': ['computejaimini', '/api/jaimini'], 'Ashtakavarga': ['computeashtakavarga', '/api/ashtakavarga'], 'Shadbala': ['computeshadbala', '/api/shadbala'], 'Yoga': ['computeyogas', '/api/yogas'], 'Aspects': ['computeaspects', '/api/aspects'], 'Birth Rectification': ['computerectificationgate', '/api/rectification_gate', 'rectification', 'rect-prompt'], 'Case Validation': ['computecasevalidation', '/api/case_validation', 'case validation', 'mevg'], 'Deep Varga Avastha': ['deepvargaavastha', '/api/deep_varga_avastha', 'sayanadi/shayanadi', 'd24/d30/d60'], 'Divisional Yoga': ['computedivisionalyoga', '/api/divisional_yoga', 'divisional yoga'], 'Kakshya': ['computekakshya', '/api/kakshya', 'kakshya'], 'Career': ['computecareer', '/api/career', 'career analysis', '事业分析'], 'Relationship': ['computerelationship', '/api/relationship', 'relationship analysis', '感情分析'], 'KP System': ['computekp', '/api/kp', 'kp sublord', 'kp分析'], 'Prashna': ['computeprashna', '/api/prashna', 'prashna', '问事'], 'Synastry 16-factor': ['computesynastry', '/api/synastry', 'ashtakoot', '合盘'], 'Bhava Bala': ['computebhavabala', '/api/bhava_bala', 'bhava bala'], 'Transit Trigger': ['computetransittriggers', '/api/transit', 'transit trigger', '过境触发'], 'Thematic Report': ['computethematicreport', '/api/thematic_report', 'thematic report', '主题化报告'], } for topic, markers in source_markers.items(): if any(marker in source_text for marker in markers) and topic not in topics: topics.append(topic) return topics def _build_priority_gaps(self, techniques, engine_not_api, app_visible_topics): api_gap_commands = {'varga-full', 'bhava-chalit', 'sudarshana', 'tajika', 'solar-return', 'muhurta', 'nakshatra-full', 'audit-capabilities'} gaps = [] for command in sorted(api_gap_commands & set(engine_not_api)): related = [ value.get('name', key) for key, value in techniques.items() if command in value.get('commands', []) ][:4] gaps.append({ 'kind': 'engine_not_api', 'command': command, 'priority': 'high', 'reason': '引擎已有命令，但 Web API/用户端未直接承载完整工作流。', 'related_techniques': related, }) visible_lower = ' '.join(app_visible_topics).lower() for topic in ['muhurta', 'tajika', 'solar return', 'bhava chalit', 'sudarshana']: if topic not in visible_lower: gaps.append({ 'kind': 'app_visibility', 'topic': topic, 'priority': 'medium', 'reason': '前端缺少独立入口或专题化展示，用户不容易发现已有能力。', }) return gaps[:12] def _build_productization_matrix(self, techniques, engine_commands, api_backed_commands, app_visible_topics): app_text = ' '.join(app_visible_topics).lower() productized_markers = { 'd1': ['d1', 'rashi', 'chart', '本命盘'], 'd9': ['d9', 'navamsa', 'varga', '分盘'], 'd10': ['d10', 'dasamsa', 'varga'], 'varga': ['varga', '分盘'], 'jaimini': ['jaimini', 'karaka', 'arudha'], 'karaka': ['karaka', 'jaimini'], 'arudha': ['arudha', 'jaimini'], 'ashtakavarga': ['ashtakavarga'], 'shadbala': ['shadbala'], 'yoga': ['yoga', '格局'], 'dosha': ['dosha', 'remedies'], 'dasha': ['dasha'], 'nakshatra': ['nakshatra'], 'muhurta': ['muhurta'], 'tajika': ['tajika', 'solar return', 'varshaphala'], 'annual': ['tajika', 'solar return', 'varshaphala'], 'bhava': ['bhava'], 'bhava-bala': ['bhava bala', 'bhava'], 'transit': ['transit'], 'transit-trigger': ['transit trigger', 'transit', '过境触发'], 'kp': ['kp'], 'prashna': ['prashna'], 'synastry': ['synastry'], 'relationship': ['relationship', 'synastry'], 'remedies': ['remedies'], 'aspects': ['aspects'], 'sudarshana': ['sudarshana'], 'career': ['career'], 'marriage': ['navamsa', 'synastry', 'relationship'], 'birth': ['birth rectification', 'rectification', '生时校正'], 'rectification': ['birth rectification', 'rectification', '生时校正'], 'case': ['case validation', 'mevg', '验证'], 'validation': ['case validation', 'mevg', '验证'], 'misconceptions': ['case validation', 'mevg', '验证'], 'muhurtha': ['muhurta'], 'varshaphala': ['tajika', 'solar return', 'varshaphala'], 'deep-varga-avastha': ['deep varga avastha', 'deep varga', 'd24/d30/d60'], 'avastha': ['deep varga avastha', 'sayanadi/shayanadi'], 'd24': ['d24/d30/d60'], 'd30': ['d24/d30/d60'], 'd60': ['d24/d30/d60'], 'divisional': ['divisional yoga', 'varga', '分盘'], 'kakshya': ['kakshya', 'ashtakavarga'], } api_only_commands = sorted(api_backed_commands - {'chart', 'full-reading'}) rows = [] summary = { 'productized': 0, 'api_backed': 0, 'engine_or_full_reading': 0, 'registry_only': 0, } for key, technique in sorted(techniques.items()): commands = [c for c in technique.get('commands', []) if isinstance(c, str)] domains = [d for d in technique.get('domains', []) if isinstance(d, str)] output_paths = technique.get('output_paths', []) inferred_commands = self._inferred_commands_for_technique(key, technique) all_commands = sorted(set(commands + inferred_commands)) api_commands = [command for command in commands if command in api_backed_commands] api_commands = sorted(set(api_commands + [command for command in inferred_commands if command in api_backed_commands])) engine_hits = [command for command in all_commands if command in engine_commands] marker_terms = [] for token in [key, *domains, *all_commands]: token_lower = token.lower() marker_terms.extend(productized_markers.get(token_lower, [])) marker_terms.append(token_lower.replace('-', ' ')) marker_terms.append(token_lower.replace('_', ' ')) visible_markers = sorted({ marker for marker in marker_terms if marker and marker in app_text }) if visible_markers and (api_commands or 'full-reading' in commands or output_paths): level = 'productized' reason = '前端已有可见入口，并且有 API/full-reading/输出路径承载。' elif api_commands: level = 'api_backed' reason = '已有 Web API，但用户端需要更明确的专题解释或引导。' elif engine_hits or 'full-reading' in commands or output_paths: level = 'engine_or_full_reading' reason = '引擎、完整解盘或输出路径已覆盖，但缺少独立产品化入口。' else: level = 'registry_only' reason = '注册表中存在，但未自动识别到命令/API/前端入口。' summary[level] += 1 rows.append({ 'id': key, 'name': technique.get('name', key), 'level': level, 'reason': reason, 'domains': domains, 'commands': all_commands, 'api_commands': api_commands, 'output_paths': output_paths, 'visible_markers': visible_markers[:6], 'status': technique.get('status', 'unknown'), 'next_action': self._productization_next_action(level, all_commands, api_commands, visible_markers), }) next_queue = [ row for row in rows if row['level'] in {'api_backed', 'engine_or_full_reading', 'registry_only'} ] priority_order = {'api_backed': 0, 'engine_or_full_reading': 1, 'registry_only': 2} next_queue.sort(key=lambda row: (priority_order[row['level']], row['name'])) return { 'summary': summary, 'rows': rows, 'next_queue': next_queue[:18], 'api_only_commands': api_only_commands, } def _inferred_commands_for_technique(self, key, technique): domains = set(technique.get('domains') or []) name = str(technique.get('name', '')).lower() path_text = ' '.join(str(path).lower() for path in technique.get('output_paths', [])) inferred = [] if key == 'career_engine' or 'career_analysis.py' in path_text or 'career' in domains: inferred.append('career') if key == 'relationship_engine' or 'relationship_analysis.py' in path_text or 'relationship' in domains: inferred.append('relationship') if key == 'kp_system' or 'kp_system.py' in path_text or 'kp' in domains: inferred.append('kp') if key == 'prashna' or 'prashna.py' in path_text or 'prashna' in domains: inferred.append('prashna') if key == 'synastry_16factor' or 'synastry.py' in path_text or 'synastry' in domains: inferred.append('synastry') if key == 'remedies' or 'remedies.py' in path_text or 'remedies' in domains: inferred.append('remedies') if key == 'bhava_bala' or 'bhava_bala.py' in path_text: inferred.append('bhava-bala') if key == 'transit_trigger' or 'transit_trigger.py' in path_text: inferred.append('transit-trigger') if key == 'thematic_report_orchestrator' or 'report_orchestrator.py' in path_text or {'report', 'reading'} & domains: inferred.append('thematic-report') if key == 'divisional_yoga' or 'divisional_yoga.py' in path_text: inferred.append('divisional-yoga') if key == 'deep_varga_avastha' or 'deep_varga_avastha.py' in path_text: inferred.append('deep-varga-avastha') if key == 'birth_time_rectifier' or 'birth_time_rectifier.py' in path_text: inferred.append('rectification') if key == 'case_validator' or 'case_validator.py' in path_text: inferred.append('case-validation') if key == 'kakshya' or 'kakshya.py' in path_text: inferred.append('kakshya') if key == 'muhurtha' or 'muhurtha' in domains or 'muhurtha_election.py' in path_text: inferred.append('muhurta') if key == 'varshaphala' or 'varshaphala' in domains or 'varshaphala.py' in path_text: inferred.append('solar-return') if 'ashtakavarga' in domains and 'prastara' in name: inferred.append('ashtakavarga') if 'ashtakavarga' in domains and 'sodhita' in name: inferred.append('ashtakavarga') if key == 'bhrigu_bindu' or 'calc_bhrigu_bindu' in path_text: inferred.append('full-reading') inferred.append('varga-full') return sorted(set(inferred)) def _productization_next_action(self, level, commands, api_commands, visible_markers): if level == 'api_backed': return '把 API 结果转成结论卡、证据卡和交叉验证提示。' if level == 'engine_or_full_reading': if any(command in {'transit', 'narayana-dasha', 'nakshatra-dasha', 'vivah-saham', 'transit-ll7l'} for command in commands): return '优先 API 化，并加入高级技法工作台或专题 Tab。' return '梳理到完整解盘主流程，补用户可见入口。' if level == 'registry_only': return '确认是否仍是有效技法；若有效，补命令/API/输出路径。' if visible_markers: return '继续优化解释层和移动端可读性。' return '保持监控。' def _build_ux_productization_matrix(self, product_rows): rows = [] summary = { 'excellent': 0, 'usable': 0, 'thin': 0, 'not_user_ready': 0, } criteria_keys = [ 'clear_entry', 'human_readable_conclusion', 'evidence_chain', 'next_action', 'json_hidden', 'mobile_scannable', ] for row in product_rows: criteria = self._ux_criteria_for_row(row) score = sum(1 for key in criteria_keys if criteria.get(key)) if score >= 5: ux_level = 'excellent' elif score >= 4: ux_level = 'usable' elif score >= 2: ux_level = 'thin' else: ux_level = 'not_user_ready' summary[ux_level] += 1 missing = [key for key in criteria_keys if not criteria.get(key)] rows.append({ **row, 'ux_score': score, 'ux_level': ux_level, 'criteria': criteria, 'missing_ux': missing, 'ux_next_action': self._ux_next_action(ux_level, missing, row), }) queue = [row for row in rows if row['ux_level'] != 'excellent'] level_order = {'not_user_ready': 0, 'thin': 1, 'usable': 2, 'excellent': 3} queue.sort(key=lambda row: (level_order[row['ux_level']], -row['ux_score'], row['name'])) return { 'criteria': criteria_keys, 'summary': summary, 'rows': rows, 'next_queue': queue[:18], } def _ux_criteria_for_row(self, row): level = row.get('level') commands = set(row.get('commands') or []) api_commands = set(row.get('api_commands') or []) domains = set(row.get('domains') or []) visible_markers = set(row.get('visible_markers') or []) name = row.get('name', '').lower() row_id = row.get('id', '').lower() has_api = bool(api_commands - {'full-reading'}) or any( command in api_commands for command in {'dasha', 'jaimini', 'ashtakavarga', 'shadbala', 'yoga', 'muhurta', 'solar-return', 'sudarshana', 'nakshatra-full', 'varga-full', 'rectification', 'case-validation', 'deep-varga-avastha', 'divisional-yoga', 'kakshya', 'career', 'relationship', 'kp', 'prashna', 'synastry', 'remedies', 'bhava-bala', 'transit-trigger', 'thematic-report'} ) source_backed = level == 'productized' and bool(row.get('output_paths')) clear_entry = level == 'productized' and bool(visible_markers) human_readable = bool( source_backed or commands & {'full-reading', 'chart', 'dasha', 'jaimini', 'ashtakavarga', 'muhurta', 'solar-return', 'sudarshana', 'rectification', 'case-validation', 'deep-varga-avastha', 'divisional-yoga', 'kakshya', 'career', 'relationship', 'kp', 'prashna', 'synastry', 'remedies', 'bhava-bala', 'transit-trigger', 'thematic-report'} or domains & {'core', 'relationship', 'marriage', 'career', 'remedies', 'muhurta', 'muhurtha', 'tajika', 'varshaphala', 'birth', 'case', 'misconceptions', 'divisional', 'kakshya', 'kp', 'prashna', 'synastry', 'ashtakavarga', 'bhava', 'transit', 'avastha', 'd24', 'd30', 'd60'} or any(token in name for token in ['reading', 'analysis', 'report']) ) evidence_chain = bool( has_api or source_backed or commands & {'full-reading', 'varga-full', 'ashtakavarga', 'shadbala', 'jaimini', 'yoga', 'dasha', 'case-validation', 'deep-varga-avastha', 'divisional-yoga', 'kakshya', 'career', 'relationship', 'kp', 'prashna', 'synastry', 'remedies', 'bhava-bala', 'transit-trigger', 'thematic-report'} or domains & {'strength', 'timing', 'varga', 'dasha', 'jaimini', 'ashtakavarga', 'remedies', 'birth', 'case', 'misconceptions', 'divisional', 'kakshya', 'kp', 'prashna', 'synastry', 'bhava', 'transit', 'avastha', 'd24', 'd30', 'd60'} ) next_action = bool( domains & {'remedies', 'muhurta', 'muhurtha', 'career', 'relationship', 'marriage', 'timing', 'event', 'birth', 'case', 'varshaphala', 'divisional', 'kakshya', 'kp', 'prashna', 'synastry', 'bhava', 'transit', 'avastha', 'd24', 'd30', 'd60'} or row.get('next_action') ) hidden_json_rows = { 'bhava_bala', 'birth_time_rectifier', 'career_engine', 'case_validator', 'deep_varga_avastha', 'divisional_yoga', 'kakshya', 'misconceptions', 'relationship_engine', 'remedies', 'transit_trigger', 'full_reading_strict', } json_hidden = level == 'productized' and ( bool(api_commands) or row_id in hidden_json_rows or (not row_id.endswith('_engine') and '.py' not in name) ) mobile_scannable = clear_entry and (human_readable or evidence_chain) return { 'clear_entry': clear_entry, 'human_readable_conclusion': human_readable, 'evidence_chain': evidence_chain, 'next_action': next_action, 'json_hidden': json_hidden, 'mobile_scannable': mobile_scannable, } def _ux_next_action(self, ux_level, missing, row): if ux_level == 'excellent': return '保持现有入口，继续做文案和移动端微调。' if 'human_readable_conclusion' in missing: return '把计算结果转成用户可读结论卡，并说明它支持哪个判断。' if 'clear_entry' in missing: return '补清晰入口或把该技法合并进完整解盘主流程。' if 'evidence_chain' in missing: return '补证据链：引用具体行星、宫位、分盘、Dasha 或相位。' if 'json_hidden' in missing: return '默认隐藏 JSON，只保留展开查看；主视图展示摘要。' if 'mobile_scannable' in missing: return '重排移动端卡片密度，保证三分钟内能读到结论。' return row.get('next_action') or '补用户体验解释层。' def _external_research_matrix(self): return [ { 'name': 'PyJHora', 'url': 'https://github.com/naturalstupid/PyJHora', 'license': 'AGPL-3.0', 'reuse': 'benchmark_only', 'notes': '最强传统算法对标；许可证不适合直接复制进 MIT 仓库。', 'best_for': ['Dasha族', '分盘变体', 'Ashtakavarga高级层', 'JHora口径校准'], }, { 'name': 'dashaflow', 'url': 'https://github.com/adarshj322/dashaflow', 'license': 'MIT', 'reuse': 'direct', 'notes': '本地已有源码；适合复用 Ashtakavarga、Shadbala、Jaimini、合盘、Muhurta 的轻量实现。', 'best_for': ['Ashtakavarga', 'Shadbala', 'Jaimini', 'Synastry', 'Muhurta'], }, { 'name': 'jyotishganit', 'url': 'https://github.com/northtara/jyotishganit', 'license': 'MIT', 'reuse': 'direct', 'notes': '高精度结构化计算与 JSON-LD 输出思路，适合用于数据层校准。', 'best_for': ['D1-D60', 'Panchanga', 'Shadbala', 'JSON-LD'], }, { 'name': 'VedicAstro', 'url': 'https://github.com/diliprk/VedicAstro', 'license': 'unspecified/readme badge', 'reuse': 'review_before_copy', 'notes': 'KP 与 Horary 很有价值，但复制前必须确认许可证文件。', 'best_for': ['KP Sublord', 'ABCD Significators', 'Horary'], }, { 'name': 'VedAstro', 'url': 'https://github.com/VedAstro/VedAstro', 'license': 'MIT', 'reuse': 'direct_or_port', 'notes': 'C# API 平台范式，可参考 Web/API 产品化结构。', 'best_for': ['API Platform', 'Muhurta', 'Panchanga', 'AI Astrologer'], }, { 'name': 'xalen-ephemeris', 'url': 'https://github.com/vedika-io/xalen-ephemeris', 'license': 'Apache-2.0', 'reuse': 'direct_or_port', 'notes': 'Rust 高精度星历与多传统系统，适合未来替代/补强天文底座。', 'best_for': ['Ephemeris', 'Ayanamsa', 'House Systems', 'KP/Jaimini/Tajika'], }, ] def _parse_allowed_origins(value): if not value: return DEFAULT_ALLOWED_ORIGINS return {item.strip() for item in value.split(',') if item.strip()} def start_server(port=5200, host='127.0.0.1', allowed_origins=None): server = HTTPServer((host, port), JyotishAPIHandler) server.allowed_origins = allowed_origins or DEFAULT_ALLOWED_ORIGINS print(f'Jyotish API v6.9.14 running on http://{host}:{port}') print(f' CORS origins: {", ".join(sorted(server.allowed_origins))}') print(f' POST /api/chart — 完整星盘计算') print(f' POST /api/remedies — 补救建议') print(f' POST /api/kp — KP分析') print(f' POST /api/prashna — 卜卦') print(f' POST /api/synastry — 合盘') print(f' POST /api/dasha — 单Dasha时间线') print(f' POST /api/sade_sati — 土星周期') print(f' POST /api/pancha_mahapurusha — 五王瑜伽') print(f' POST /api/career — 事业分析') print(f' POST /api/relationship — 感情分析') print(f' POST /api/annual — 年运/Tajika') print(f' POST /api/muhurta — 择日') print(f' POST /api/panchanga_range — Panchanga日期范围') print(f' POST /api/bhava_chalit — Bhava Chalit') print(f' POST /api/sudarshana — Sudarshana Chakra') print(f' POST /api/nakshatra_full — Nakshatra深层报告') print(f' POST /api/varga_full — BPHS扩展分盘/变体/自定义/复合') print(f' POST /api/jaimini — Jaimini Karaka/Arudha/Chara Dasha') print(f' POST /api/ashtakavarga — Ashtakavarga SAV/BAV') print(f' POST /api/shadbala — Shadbala六重力量') print(f' POST /api/yogas — Yoga格局检测') print(f' POST /api/aspects — 精确相位') print(f' POST /api/report_artifact — HTML/PDF报告工件生成') print(f' POST /api/thematic_report — 主题化报告/冲突裁决') print(f' GET /api/health — 健康检查') print(f' GET /api/cities — 城市列表') print(f' GET /api/capability_audit — 能力审计') server.serve_forever() if __name__ == '__main__': parser = argparse.ArgumentParser(description='Jyotish API server') parser.add_argument('--port', type=int, default=5200) parser.add_argument('--host', default=os.environ.get('JYOTISH_API_HOST', '127.0.0.1')) parser.add_argument( '--allow-origin', action='append', default=[], help='Allowed browser origin; may be repeated. Defaults to local Vite origins.', ) args = parser.parse_args() env_origins = _parse_allowed_origins(os.environ.get('JYOTISH_ALLOWED_ORIGINS')) cli_origins = set(args.allow_origin) start_server(args.port, host=args.host, allowed_origins=cli_origins or env_origins)