Janady13/AI_Brain / services/seeder_api/app.py

1#!/usr/bin/env python3 2import os 3import time 4from fastapi import FastAPI 5from pydantic import BaseModel 6 7from .intelligence import ( 8 AmazonProductRecommendation, 9 AWSRevenueRecommendation, 10 AutomationSprint, 11 AutomationTask, 12 BudgetPlan, 13 CampaignMetrics, 14 CampaignScore, 15 CJAffiliateRecommendation, 16 CryptoMarketSnapshot, 17 CognitiveCapabilityPlan, 18 AgenticSystemPlan, 19 EbayRevenuePlay, 20 GrowthExperiment, 21 GoogleCampaignPerformance, 22 CompetitiveSignal, 23 InfluencerRecommendation, 24 LearningLoopRecommendation, 25 ExcellenceSummary, 26 ExecutivePlaybook, 27 StrategicDirective, 28 ScenarioAnalysis, 29 ScenarioProjection, 30 StockMarketForecast, 31 StatisticalReasoningSummary, 32 StatisticalEvidence, 33 MarketingIntelligenceEngine, 34 MarketingCampaign, 35 PromptDiagnostics, 36 StripeMonetizationPlan, 37 PayPalMonetizationPlan, 38 PaymentIntegrationPlan, 39 InvestingPlan, 40 KnowledgeWorkflowPlan, 41 LanguageCapabilityPlan, 42 CodeAutomationPlan, 43 MixtureOfExpertsPlan, 44 ExpertActivation, 45 AgenticLoopPlan, 46 QuantumStressTestPlan, 47 PhysicsEconomicsPlan, 48 default_marketing_engine, 49) 50 51APP_NAME = os.getenv("APP_NAME", "HiveSeedAPI") 52START_TS = time.time() 53 54app = FastAPI(title=APP_NAME) 55 56class Health(BaseModel): 57 status: str 58 uptime_seconds: float 59 60class Ready(BaseModel): 61 ready: bool 62 reason: str | None = None 63 64 65class MarketingQuery(BaseModel): 66 prompt: str 67 limit: int = 3 68 69 70class MarketingInsight(BaseModel): 71 channel: str 72 audience: str 73 offer: str 74 objective: str 75 rationale: str 76 77 78class MarketingResponse(BaseModel): 79 query: str 80 recommendations: list[MarketingInsight] 81 insight: str 82 83 84class StatisticalInsight(BaseModel): 85 channel: str 86 audience: str 87 offer: str 88 objective: str 89 expected_roi: float 90 expected_ctr: float 91 confidence: float 92 rationale: str 93 drivers: dict[str, float] 94 95 96class StatisticalEvidenceInsight(BaseModel): 97 feature: str 98 feature_type: str 99 posterior_roi: float 100 posterior_ctr: float 101 confidence: float 102 lift_vs_benchmark: float 103 sample_size: int 104 weight: float 105 rationale: str 106 107 108class StatisticalReasoningInsight(BaseModel): 109 expected_roi: float 110 expected_revenue: float 111 confidence: float 112 success_probability: float 113 volatility_adjustment: float 114 scenario_spread: dict[str, float] 115 driver_confidence: dict[str, float] 116 evidence: list[StatisticalEvidenceInsight] 117 narrative: str 118 source: str 119 notes: str | None = None 120 121 122class PortfolioInsight(BaseModel): 123 expected_roi: float 124 expected_ctr: float 125 confidence: float 126 rationale: str 127 strongest_drivers: dict[str, float] 128 129 130class StatisticalResponse(BaseModel): 131 query: str 132 recommendations: list[StatisticalInsight] 133 portfolio: PortfolioInsight 134 135 136class DiagnosticResponse(BaseModel): 137 query: str 138 stage: str 139 urgency: str 140 focus: str 141 confidence: float 142 recommended_kpis: list[str] 143 opportunities: list[str] 144 risk_signals: list[str] 145 keyword_summary: dict[str, list[str]] 146 147 148class ProcessRun(BaseModel): 149 process: str 150 recommendations: list[MarketingInsight] 151 summary: str 152 153 154class ExperimentInsight(BaseModel): 155 name: str 156 hypothesis: str 157 primary_metric: str 158 secondary_metrics: list[str] 159 playbook: list[str] 160 confidence: float 161 162 163class LearningLoopInsight(BaseModel): 164 play_name: str 165 stage: str 166 audience_focus: str 167 channel: str 168 learning: str 169 wins: list[str] 170 losses: list[str] 171 next_actions: list[str] 172 kpi_focus: list[str] 173 confidence: float 174 source: str 175 notes: str | None = None 176 177 178class CompetitiveLandscapeInsight(BaseModel): 179 competitor: str 180 channel: str 181 summary: str 182 strengths: list[str] 183 weaknesses: list[str] 184 recommended_play: str 185 share_of_voice: float 186 signal_intensity: float 187 threat_level: str 188 focus_alignment: float 189 source: str 190 notes: str | None = None 191 192 193class ExcellenceInsight(BaseModel): 194 excellence_index: float 195 maturity_level: str 196 headline: str 197 strengths: list[str] 198 watchouts: list[str] 199 process_coverage: dict[str, float] 200 notes: str | None = None 201 202 203class StrategicDirectiveInsight(BaseModel): 204 name: str 205 priority: int 206 objective: str 207 primary_channel: str 208 supporting_channels: list[str] 209 investment_usd: float | None 210 expected_revenue_usd: float | None 211 confidence: float 212 time_horizon_hours: int 213 north_star_metric: str 214 supporting_metrics: list[str] 215 action_steps: list[str] 216 dependencies: list[str] 217 risk_mitigations: list[str] 218 inspiration: str 219 source: str 220 notes: str | None = None 221 222 223class ExecutivePlaybookInsight(BaseModel): 224 headline: str 225 focus: str 226 urgency: str 227 north_star_metric: str 228 total_budget_usd: float | None 229 expected_revenue_usd: float | None 230 confidence: float 231 directives: list[StrategicDirectiveInsight] 232 summary: str 233 notes: str | None = None 234 235 236class ScenarioProjectionInsight(BaseModel): 237 scenario: str 238 expected_revenue: float 239 expected_roi: float 240 probability: float 241 confidence: float 242 accelerators: list[str] 243 stabilizers: list[str] 244 watchouts: list[str] 245 source: str 246 notes: str | None = None 247 248 249class ScenarioPlanningInsight(BaseModel): 250 headline: str 251 summary: str 252 projections: list[ScenarioProjectionInsight] 253 confidence: float 254 accelerators: list[str] 255 stabilizers: list[str] 256 source: str 257 notes: str | None = None 258 259 260class MarketingProcessesResponse(BaseModel): 261 query: str 262 rag: ProcessRun 263 egg: list[ExperimentInsight] 264 google_ads: list["GoogleAdsInsight"] 265 cj_affiliate: list["CJAffiliateInsight"] 266 crypto_markets: list["CryptoMarketInsight"] 267 stock_markets: list["StockMarketInsight"] 268 stripe: list["StripePlanInsight"] 269 paypal: list["PayPalPlanInsight"] 270 payment_integrations: list["PaymentIntegrationInsight"] 271 investing: list["InvestingInsight"] 272 cognitive_architecture: list["CognitiveArchitectureInsight"] 273 agentic_systems: list["AgenticSystemInsight"] 274 rag_workflows: list["KnowledgeWorkflowInsight"] 275 knowledge_graphs: list["KnowledgeWorkflowInsight"] 276 language_intelligence: list["LanguageCapabilityInsight"] 277 code_automation: list["CodeAutomationInsight"] 278 mixture_of_experts: list["MixtureOfExpertsInsight"] 279 agentic_loops: list["AgenticLoopInsight"] 280 quantum_simulation: list["QuantumSimulationInsight"] 281 physics_economics: list["PhysicsEconomicsInsight"] 282 stripe: list["StripePlanInsight"] 283 paypal: list["PayPalPlanInsight"] 284 influencer_collaborations: list["InfluencerInsight"] 285 amazon_marketplace: list["AmazonMarketplaceInsight"] 286 ebay_marketplace: list["EbayMarketplaceInsight"] 287 aws_cloud: list["AWSRevenueInsight"] 288 budget_optimizer: "BudgetPlanInsight" 289 automation: "AutomationSprintInsight" 290 learning_loop: list["LearningLoopInsight"] 291 competitive_landscape: list["CompetitiveLandscapeInsight"] 292 excellence: "ExcellenceInsight" 293 executive_playbook: "ExecutivePlaybookInsight" 294 scenario_planning: "ScenarioPlanningInsight" 295 statistical_reasoning: "StatisticalReasoningInsight" 296 297 298class GoogleAdsInsight(BaseModel): 299 campaign_name: str 300 clicks: int 301 impressions: int 302 conversions: float 303 cost_micros: int 304 ctr: float 305 cpc: float 306 roas: float 307 source: str 308 notes: str | None = None 309 310 311class CJAffiliateInsight(BaseModel): 312 program_name: str 313 advertiser_id: str 314 category: str 315 commission_rate: float 316 epc: float 317 seven_day_epc: float 318 projected_epc: float 319 projected_monthly_revenue: float 320 network_rank: int 321 payout_terms: str 322 landing_url: str 323 rationale: str 324 source: str 325 notes: str | None = None 326 327 328class CryptoMarketInsight(BaseModel): 329 asset: str 330 price_usd: float | None 331 change_24h: float | None 332 market_cap: float | None 333 volume_24h: float | None 334 source: str 335 notes: str | None = None 336 337 338class StockMarketInsight(BaseModel): 339 symbol: str 340 name: str 341 region: str 342 focus: str 343 current_price: float 344 trend: str 345 forecast_return_30d: float 346 forecast_return_90d: float 347 forecast_revenue_multiplier: float 348 volatility: float 349 confidence: float 350 signal_summary: str 351 source: str 352 notes: str | None = None 353 354 355class StripePlanInsight(BaseModel): 356 product_name: str 357 price_usd: float 358 billing_interval: str 359 currency: str 360 rationale: str 361 setup_steps: list[str] 362 source: str 363 notes: str | None = None 364 365 366class PayPalPlanInsight(BaseModel): 367 product_name: str 368 price_usd: float 369 checkout_flow: str 370 payout_schedule: str 371 rationale: str 372 setup_steps: list[str] 373 source: str 374 notes: str | None = None 375 376 377class PaymentIntegrationInsight(BaseModel): 378 provider: str 379 maturity: str 380 description: str 381 reasoning: str 382 integration_focus: list[str] 383 docs: list[str] 384 sdks: list[str] 385 setup: list[str] 386 troubleshooting: list[str] 387 codefix: list[str] 388 marketing_plays: list[str] 389 source: str 390 notes: str | None = None 391 392 393class InvestingInsight(BaseModel): 394 provider: str 395 category: str 396 maturity: str 397 description: str 398 reasoning: str 399 asset_classes: list[str] 400 monetization: list[str] 401 onboarding: list[str] 402 tools: list[str] 403 risk_controls: list[str] 404 revenue_programs: list[str] 405 kpis: list[str] 406 source: str 407 notes: str | None = None 408 409 410class CognitiveArchitectureInsight(BaseModel): 411 capability: str 412 pillar: str 413 maturity: str 414 description: str 415 reasoning: str 416 prompt_strategy: str 417 frameworks: list[str] 418 tooling: list[str] 419 metrics: list[str] 420 knowledge_assets: list[str] 421 orchestration_steps: list[str] 422 source: str 423 424 425class AgenticSystemInsight(BaseModel): 426 system_name: str 427 domain: str 428 controller: str 429 maturity: str 430 reasoning: str 431 orchestration_steps: list[str] 432 toolchain: list[str] 433 data_interfaces: list[str] 434 knowledge_sources: list[str] 435 revenue_programs: list[str] 436 risk_controls: list[str] 437 metrics: list[str] 438 source: str 439 notes: str | None = None 440 441 442class KnowledgeWorkflowInsight(BaseModel): 443 name: str 444 category: str 445 maturity: str 446 description: str 447 reasoning: str 448 indexing_plan: list[str] 449 retrieval_plan: list[str] 450 vector_store: str 451 embedding_models: list[str] 452 tooling: list[str] 453 evaluation: list[str] 454 governance: list[str] 455 caching: list[str] 456 source: str 457 458 459class LanguageCapabilityInsight(BaseModel): 460 capability: str 461 category: str 462 maturity: str 463 description: str 464 reasoning: str 465 pipeline_components: list[str] 466 tooling: list[str] 467 datasets: list[str] 468 evaluation_metrics: list[str] 469 revenue_programs: list[str] 470 orchestration_steps: list[str] 471 source: str 472 notes: str | None = None 473 474 475class CodeAutomationInsight(BaseModel): 476 capability: str 477 category: str 478 maturity: str 479 description: str 480 reasoning: str 481 automation_stages: list[str] 482 tooling: list[str] 483 platforms: list[str] 484 metrics: list[str] 485 revenue_programs: list[str] 486 guardrails: list[str] 487 orchestration_steps: list[str] 488 source: str 489 notes: str | None = None 490 491 492class ExpertActivationInsight(BaseModel): 493 name: str 494 provider: str 495 role: str 496 confidence: float 497 reasoning: str 498 outputs: list[str] 499 metrics: list[str] 500 fallback: str 501 source: str 502 503 504class MixtureOfExpertsInsight(BaseModel): 505 router_summary: str 506 maturity: str 507 activations: list[ExpertActivationInsight] 508 evaluation_metrics: list[str] 509 notes: str 510 source: str 511 512 513class AgenticLoopStageInsight(BaseModel): 514 stage: str 515 objective: str 516 actions: list[str] 517 tools: list[str] 518 signals: list[str] 519 outputs: list[str] 520 metrics: list[str] 521 522 523class AgenticLoopInsight(BaseModel): 524 name: str 525 goal_focus: str 526 summary: str 527 maturity: str 528 reasoning: str 529 stages: list[AgenticLoopStageInsight] 530 guardrails: list[str] 531 source: str 532 533 534class QuantumStressScenarioInsight(BaseModel): 535 name: str 536 domain: str 537 objective: str 538 stressors: list[str] 539 metrics: list[str] 540 gate_sequence: list[str] 541 measurement_probability: float 542 stability_index: float 543 integration_points: list[str] 544 recommended_actions: list[str] 545 notes: str | None = None 546 547 548class QuantumSimulationInsight(BaseModel): 549 simulator: str 550 provider: str 551 maturity: str 552 description: str 553 reasoning: str 554 training_focus: list[str] 555 stress_tests: list[QuantumStressScenarioInsight] 556 orchestration_steps: list[str] 557 metrics: list[str] 558 dependencies: list[str] 559 docs: list[str] 560 coverage_ratio: float 561 domain_stability: dict[str, float] 562 source: str 563 notes: str | None = None 564 565 566class PhysicsEconomicsInsight(BaseModel): 567 capability: str 568 domain: str 569 maturity: str 570 description: str 571 rationale: str 572 marketing_algorithms: list[str] 573 physics_principles: list[str] 574 quantum_strategies: list[str] 575 economic_models: list[str] 576 hardware_strategies: list[str] 577 data_compression: list[str] 578 risk_controls: list[str] 579 metrics: list[str] 580 orchestration_steps: list[str] 581 docs: list[str] 582 source: str 583 notes: str | None = None 584 585 586class InfluencerInsight(BaseModel): 587 name: str 588 platform: str 589 niche: str 590 collab_format: str 591 audience_size: int 592 engagement_rate: float 593 estimated_reach: int 594 projected_cpm: float 595 projected_leads: int 596 projected_revenue: float 597 projected_roi: float 598 rationale: str 599 source: str 600 notes: str | None = None 601 602 603class AmazonMarketplaceInsight(BaseModel): 604 asin: str 605 title: str 606 category: str 607 price_usd: float 608 commission_rate: float 609 rating: float 610 reviews: int 611 estimated_monthly_sales: int 612 buy_box_share: float 613 prime_eligible: bool 614 fulfillment_model: str 615 projected_monthly_revenue: float 616 rationale: str 617 url: str 618 source: str 619 notes: str | None = None 620 621 622class EbayMarketplaceInsight(BaseModel): 623 item_id: str 624 title: str 625 category: str 626 price_usd: float 627 affiliate_rate: float 628 seller_level: str 629 seller_rating: float 630 conversion_rate: float 631 sold_per_month: int 632 projected_monthly_revenue: float 633 projected_profit_margin: float 634 shipping_days: int 635 rationale: str 636 url: str 637 source: str 638 notes: str | None = None 639 640 641class AWSRevenueInsight(BaseModel): 642 program_name: str 643 focus: str 644 description: str 645 revenue_motion: str 646 primary_service: str 647 secondary_services: list[str] 648 automation_play: str 649 projected_roi: float 650 source: str 651 notes: str | None = None 652 653 654class BudgetAllocationInsight(BaseModel): 655 channel: str 656 audience_focus: str 657 offer: str 658 objective: str 659 allocation_usd: float 660 allocation_weight: float 661 expected_leads: float 662 expected_revenue: float 663 rationale: str 664 source: str 665 notes: str | None = None 666 667 668class BudgetPlanInsight(BaseModel): 669 total_budget: float 670 expected_revenue: float 671 expected_roi: float 672 payback_period_weeks: float 673 summary: str 674 allocations: list[BudgetAllocationInsight] 675 676 677class AutomationTaskInsight(BaseModel): 678 start_minute: int 679 end_minute: int 680 activity: str 681 outcome: str 682 tooling: list[str] 683 kpis: list[str] 684 automation_level: str 685 source: str 686 687 688class AutomationSprintInsight(BaseModel): 689 total_minutes: int 690 stage: str 691 focus: str 692 summary: str 693 notes: str | None = None 694 tasks: list[AutomationTaskInsight] 695 source: str 696 697 698try: # Pydantic v2 699 GoogleAdsInsight.model_rebuild() 700 CJAffiliateInsight.model_rebuild() 701 CryptoMarketInsight.model_rebuild() 702 StockMarketInsight.model_rebuild() 703 StripePlanInsight.model_rebuild() 704 PayPalPlanInsight.model_rebuild() 705 CognitiveArchitectureInsight.model_rebuild() 706 StripePlanInsight.model_rebuild() 707 PayPalPlanInsight.model_rebuild() 708 InfluencerInsight.model_rebuild() 709 AmazonMarketplaceInsight.model_rebuild() 710 EbayMarketplaceInsight.model_rebuild() 711 AWSRevenueInsight.model_rebuild() 712 BudgetAllocationInsight.model_rebuild() 713 BudgetPlanInsight.model_rebuild() 714 AutomationTaskInsight.model_rebuild() 715 AutomationSprintInsight.model_rebuild() 716 QuantumSimulationInsight.model_rebuild() 717 PhysicsEconomicsInsight.model_rebuild() 718 LearningLoopInsight.model_rebuild() 719 CompetitiveLandscapeInsight.model_rebuild() 720 ExcellenceInsight.model_rebuild() 721 StrategicDirectiveInsight.model_rebuild() 722 ExecutivePlaybookInsight.model_rebuild() 723 ScenarioProjectionInsight.model_rebuild() 724 ScenarioPlanningInsight.model_rebuild() 725 StatisticalEvidenceInsight.model_rebuild() 726 StatisticalReasoningInsight.model_rebuild() 727 MarketingProcessesResponse.model_rebuild() 728except AttributeError: # pragma: no cover - pydantic v1 fallback 729 MarketingProcessesResponse.update_forward_refs( 730 GoogleAdsInsight=GoogleAdsInsight, 731 CJAffiliateInsight=CJAffiliateInsight, 732 CryptoMarketInsight=CryptoMarketInsight, 733 StockMarketInsight=StockMarketInsight, 734 StripePlanInsight=StripePlanInsight, 735 PayPalPlanInsight=PayPalPlanInsight, 736 CognitiveArchitectureInsight=CognitiveArchitectureInsight, 737 StripePlanInsight=StripePlanInsight, 738 PayPalPlanInsight=PayPalPlanInsight, 739 InfluencerInsight=InfluencerInsight, 740 AmazonMarketplaceInsight=AmazonMarketplaceInsight, 741 EbayMarketplaceInsight=EbayMarketplaceInsight, 742 AWSRevenueInsight=AWSRevenueInsight, 743 BudgetAllocationInsight=BudgetAllocationInsight, 744 BudgetPlanInsight=BudgetPlanInsight, 745 AutomationTaskInsight=AutomationTaskInsight, 746 AutomationSprintInsight=AutomationSprintInsight, 747 QuantumSimulationInsight=QuantumSimulationInsight, 748 PhysicsEconomicsInsight=PhysicsEconomicsInsight, 749 LearningLoopInsight=LearningLoopInsight, 750 CompetitiveLandscapeInsight=CompetitiveLandscapeInsight, 751 ExcellenceInsight=ExcellenceInsight, 752 StrategicDirectiveInsight=StrategicDirectiveInsight, 753 ExecutivePlaybookInsight=ExecutivePlaybookInsight, 754 ScenarioProjectionInsight=ScenarioProjectionInsight, 755 ScenarioPlanningInsight=ScenarioPlanningInsight, 756 StatisticalEvidenceInsight=StatisticalEvidenceInsight, 757 StatisticalReasoningInsight=StatisticalReasoningInsight, 758 ) 759 760 761@app.get("/healthz", response_model=Health) 762def healthz() -> Health: 763 return Health(status="ok", uptime_seconds=time.time() - START_TS) 764 765@app.get("/readyz", response_model=Ready) 766def readyz() -> Ready: 767 # Minimal readiness: enumerations exist or DRY_RUN enabled 768 base = os.path.join(os.path.dirname(__file__), "..", "..", "daemon", "enumerations") 769 files = [ 770 os.path.join(base, "math_model_500.txt"), 771 os.path.join(base, "agent_500.txt"), 772 os.path.join(base, "language_500.txt"), 773 os.path.join(base, "prophecy_500.txt"), 774 os.path.join(base, "marketing_500.txt"), 775 ] 776 if all(os.path.isfile(p) for p in files): 777 return Ready(ready=True) 778 if os.getenv("DRY_RUN", "0") in {"1", "true", "TRUE", "yes", "on"}: 779 return Ready(ready=True, reason="DRY_RUN enabled") 780 return Ready(ready=False, reason="Enumerations missing; run make enumerations") 781 782 783def _campaign_to_insight(engine: MarketingIntelligenceEngine, query: str, campaign: MarketingCampaign) -> MarketingInsight: 784 tokens = engine.keywords(query) 785 matches: list[str] = [] 786 normalized = { 787 "channel": campaign.channel.lower(), 788 "audience": campaign.audience.lower(), 789 "offer": campaign.offer.lower(), 790 "objective": campaign.objective.lower(), 791 } 792 for token in tokens: 793 for feature, text in normalized.items(): 794 if token in text and feature not in matches: 795 matches.append(feature) 796 rationale = "Matched: " + ", ".join(matches) if matches else "General fit from curated library" 797 return MarketingInsight( 798 channel=campaign.channel, 799 audience=campaign.audience, 800 offer=campaign.offer, 801 objective=campaign.objective, 802 rationale=rationale, 803 ) 804 805 806def _campaign_to_statistical_insight( 807 engine: MarketingIntelligenceEngine, 808 query: str, 809 scored: CampaignScore, 810) -> StatisticalInsight: 811 matches: list[str] = [] 812 for feature, count in scored.keyword_coverage.items(): 813 if count: 814 matches.append(feature) 815 816 if matches: 817 rationale = f"Matched {', '.join(sorted(matches))} intent with statistical lift." 818 else: 819 rationale = "Benchmark-driven pick from marketing corpus." 820 821 strongest = sorted(scored.metrics.drivers.items(), key=lambda item: item[1], reverse=True) 822 if strongest: 823 rationale += f" Top driver: {strongest[0][0]} ROI {strongest[0][1]:.2f}." 824 825 return StatisticalInsight( 826 channel=scored.campaign.channel, 827 audience=scored.campaign.audience, 828 offer=scored.campaign.offer, 829 objective=scored.campaign.objective, 830 expected_roi=round(scored.metrics.expected_roi, 2), 831 expected_ctr=round(scored.metrics.expected_ctr, 4), 832 confidence=round(scored.metrics.confidence, 2), 833 rationale=rationale, 834 drivers={key: round(value, 2) for key, value in scored.metrics.drivers.items()}, 835 ) 836 837 838def _portfolio_to_insight(query: str, portfolio: CampaignMetrics, tokens: list[str]) -> PortfolioInsight: 839 highlights = ", ".join(sorted(set(tokens))) or "broad" 840 strongest = sorted(portfolio.drivers.items(), key=lambda item: item[1], reverse=True) 841 driver_text = strongest[0][0] if strongest else "channel" 842 rationale = ( 843 f"Statistical blend for '{query}' optimized for {highlights} focus; strongest lift from {driver_text}." 844 ) 845 return PortfolioInsight( 846 expected_roi=round(portfolio.expected_roi, 2), 847 expected_ctr=round(portfolio.expected_ctr, 4), 848 confidence=round(portfolio.confidence, 2), 849 rationale=rationale, 850 strongest_drivers={key: round(value, 2) for key, value in portfolio.drivers.items()}, 851 ) 852 853 854@app.post("/intelligence/marketing", response_model=MarketingResponse) 855def marketing_intelligence(query: MarketingQuery) -> MarketingResponse: 856 engine = default_marketing_engine() 857 campaigns = engine.recommend(query.prompt, query.limit) 858 insights = [_campaign_to_insight(engine, query.prompt, campaign) for campaign in campaigns] 859 narrative = engine.summarize(query.prompt, campaigns) 860 return MarketingResponse(query=query.prompt, recommendations=insights, insight=narrative) 861 862 863@app.post("/intelligence/marketing/statistical", response_model=StatisticalResponse) 864def marketing_statistical_intelligence(query: MarketingQuery) -> StatisticalResponse: 865 engine = default_marketing_engine() 866 ranked = engine.recommend_statistical(query.prompt, query.limit) 867 insights = [ 868 _campaign_to_statistical_insight(engine, query.prompt, scored) for scored in ranked 869 ] 870 tokens = engine.keywords(query.prompt) 871 portfolio_metrics = engine.portfolio(query.prompt, ranked) 872 portfolio = _portfolio_to_insight(query.prompt, portfolio_metrics, tokens) 873 return StatisticalResponse(query=query.prompt, recommendations=insights, portfolio=portfolio) 874 875 876def _diagnostics_payload(query: str, diagnostics: PromptDiagnostics) -> DiagnosticResponse: 877 return DiagnosticResponse( 878 query=query, 879 stage=diagnostics.stage, 880 urgency=diagnostics.urgency, 881 focus=diagnostics.focus, 882 confidence=diagnostics.confidence, 883 recommended_kpis=diagnostics.recommended_kpis, 884 opportunities=diagnostics.opportunities, 885 risk_signals=diagnostics.risk_signals, 886 keyword_summary=diagnostics.keyword_summary, 887 ) 888 889 890def _experiment_payload(experiment: GrowthExperiment) -> ExperimentInsight: 891 return ExperimentInsight( 892 name=experiment.name, 893 hypothesis=experiment.hypothesis, 894 primary_metric=experiment.primary_metric, 895 secondary_metrics=experiment.secondary_metrics, 896 playbook=experiment.playbook, 897 confidence=experiment.confidence, 898 ) 899 900 901def _google_ads_payload(performance: GoogleCampaignPerformance) -> "GoogleAdsInsight": 902 return GoogleAdsInsight( 903 campaign_name=performance.campaign_name, 904 clicks=performance.clicks, 905 impressions=performance.impressions, 906 conversions=performance.conversions, 907 cost_micros=performance.cost_micros, 908 ctr=performance.ctr, 909 cpc=performance.cpc, 910 roas=performance.roas, 911 source=performance.source, 912 notes=performance.notes, 913 ) 914 915 916def _cj_affiliate_payload(recommendation: CJAffiliateRecommendation) -> "CJAffiliateInsight": 917 return CJAffiliateInsight( 918 program_name=recommendation.program_name, 919 advertiser_id=recommendation.advertiser_id, 920 category=recommendation.category, 921 commission_rate=recommendation.commission_rate, 922 epc=recommendation.epc, 923 seven_day_epc=recommendation.seven_day_epc, 924 projected_epc=recommendation.projected_epc, 925 projected_monthly_revenue=recommendation.projected_monthly_revenue, 926 network_rank=recommendation.network_rank, 927 payout_terms=recommendation.payout_terms, 928 landing_url=recommendation.landing_url, 929 rationale=recommendation.rationale, 930 source=recommendation.source, 931 notes=recommendation.notes, 932 ) 933 934 935def _crypto_market_payload(snapshot: CryptoMarketSnapshot) -> "CryptoMarketInsight": 936 return CryptoMarketInsight( 937 asset=snapshot.asset, 938 price_usd=snapshot.price_usd, 939 change_24h=snapshot.change_24h, 940 market_cap=snapshot.market_cap, 941 volume_24h=snapshot.volume_24h, 942 source=snapshot.source, 943 notes=snapshot.notes, 944 ) 945 946 947def _stock_market_payload(forecast: StockMarketForecast) -> "StockMarketInsight": 948 return StockMarketInsight( 949 symbol=forecast.symbol, 950 name=forecast.name, 951 region=forecast.region, 952 focus=forecast.focus, 953 current_price=forecast.current_price, 954 trend=forecast.trend, 955 forecast_return_30d=forecast.forecast_return_30d, 956 forecast_return_90d=forecast.forecast_return_90d, 957 forecast_revenue_multiplier=forecast.forecast_revenue_multiplier, 958 volatility=forecast.volatility, 959 confidence=forecast.confidence, 960 signal_summary=forecast.signal_summary, 961 source=forecast.source, 962 notes=forecast.notes, 963 ) 964 965 966def _statistical_evidence_payload(evidence: StatisticalEvidence) -> StatisticalEvidenceInsight: 967 return StatisticalEvidenceInsight( 968 feature=evidence.feature, 969 feature_type=evidence.feature_type, 970 posterior_roi=evidence.posterior_roi, 971 posterior_ctr=evidence.posterior_ctr, 972 confidence=evidence.confidence, 973 lift_vs_benchmark=evidence.lift_vs_benchmark, 974 sample_size=evidence.sample_size, 975 weight=evidence.weight, 976 rationale=evidence.rationale, 977 ) 978 979 980def _statistical_reasoning_payload( 981 summary: StatisticalReasoningSummary, 982) -> StatisticalReasoningInsight: 983 return StatisticalReasoningInsight( 984 expected_roi=summary.expected_roi, 985 expected_revenue=summary.expected_revenue, 986 confidence=summary.confidence, 987 success_probability=summary.success_probability, 988 volatility_adjustment=summary.volatility_adjustment, 989 scenario_spread=summary.scenario_spread, 990 driver_confidence=summary.driver_confidence, 991 evidence=[_statistical_evidence_payload(item) for item in summary.evidence], 992 narrative=summary.narrative, 993 source=summary.source, 994 notes=summary.notes, 995 ) 996 997 998def _stripe_plan_payload(plan: StripeMonetizationPlan) -> "StripePlanInsight": 999 return StripePlanInsight( 1000 product_name=plan.product_name, 1001 price_usd=plan.price_usd, 1002 billing_interval=plan.billing_interval, 1003 currency=plan.currency, 1004 rationale=plan.rationale, 1005 setup_steps=plan.setup_steps, 1006 source=plan.source, 1007 notes=plan.notes, 1008 ) 1009 1010 1011def _paypal_plan_payload(plan: PayPalMonetizationPlan) -> "PayPalPlanInsight": 1012 return PayPalPlanInsight( 1013 product_name=plan.product_name, 1014 price_usd=plan.price_usd, 1015 checkout_flow=plan.checkout_flow, 1016 payout_schedule=plan.payout_schedule, 1017 rationale=plan.rationale, 1018 setup_steps=plan.setup_steps, 1019 source=plan.source, 1020 notes=plan.notes, 1021 ) 1022 1023 1024def _payment_integration_payload(plan: PaymentIntegrationPlan) -> "PaymentIntegrationInsight": 1025 return PaymentIntegrationInsight( 1026 provider=plan.provider, 1027 maturity=plan.maturity, 1028 description=plan.description, 1029 reasoning=plan.reasoning, 1030 integration_focus=plan.integration_focus, 1031 docs=plan.docs, 1032 sdks=plan.sdks, 1033 setup=plan.setup, 1034 troubleshooting=plan.troubleshooting, 1035 codefix=plan.codefix, 1036 marketing_plays=plan.marketing_plays, 1037 source=plan.source, 1038 notes=plan.notes, 1039 ) 1040 1041 1042def _investing_payload(plan: InvestingPlan) -> "InvestingInsight": 1043 return InvestingInsight( 1044 provider=plan.provider, 1045 category=plan.category, 1046 maturity=plan.maturity, 1047 description=plan.description, 1048 reasoning=plan.reasoning, 1049 asset_classes=plan.asset_classes, 1050 monetization=plan.monetization, 1051 onboarding=plan.onboarding, 1052 tools=plan.tools, 1053 risk_controls=plan.risk_controls, 1054 revenue_programs=plan.revenue_programs, 1055 kpis=plan.kpis, 1056 source=plan.source, 1057 notes=plan.notes, 1058 ) 1059 1060 1061def _cognitive_architecture_payload( 1062 plan: CognitiveCapabilityPlan, 1063) -> "CognitiveArchitectureInsight": 1064 return CognitiveArchitectureInsight( 1065 capability=plan.capability, 1066 pillar=plan.pillar, 1067 maturity=plan.maturity, 1068 description=plan.description, 1069 reasoning=plan.reasoning, 1070 prompt_strategy=plan.prompt_strategy, 1071 frameworks=list(plan.frameworks), 1072 tooling=list(plan.tooling), 1073 metrics=list(plan.metrics), 1074 knowledge_assets=list(plan.knowledge_assets), 1075 orchestration_steps=list(plan.orchestration_steps), 1076 source=plan.source, 1077 ) 1078 1079 1080def _agentic_system_payload(plan: AgenticSystemPlan) -> "AgenticSystemInsight": 1081 return AgenticSystemInsight( 1082 system_name=plan.system_name, 1083 domain=plan.domain, 1084 controller=plan.controller, 1085 maturity=plan.maturity, 1086 reasoning=plan.reasoning, 1087 orchestration_steps=list(plan.orchestration_steps), 1088 toolchain=list(plan.toolchain), 1089 data_interfaces=list(plan.data_interfaces), 1090 knowledge_sources=list(plan.knowledge_sources), 1091 revenue_programs=list(plan.revenue_programs), 1092 risk_controls=list(plan.risk_controls), 1093 metrics=list(plan.metrics), 1094 source=plan.source, 1095 notes=plan.notes, 1096 ) 1097 1098 1099def _knowledge_workflow_payload(plan: KnowledgeWorkflowPlan) -> "KnowledgeWorkflowInsight": 1100 return KnowledgeWorkflowInsight( 1101 name=plan.name, 1102 category=plan.category, 1103 maturity=plan.maturity, 1104 description=plan.description, 1105 reasoning=plan.reasoning, 1106 indexing_plan=list(plan.indexing_plan), 1107 retrieval_plan=list(plan.retrieval_plan), 1108 vector_store=plan.vector_store, 1109 embedding_models=list(plan.embedding_models), 1110 tooling=list(plan.tooling), 1111 evaluation=list(plan.evaluation), 1112 governance=list(plan.governance), 1113 caching=list(plan.caching), 1114 source=plan.source, 1115 ) 1116 1117 1118def _language_capability_payload( 1119 plan: LanguageCapabilityPlan, 1120) -> "LanguageCapabilityInsight": 1121 return LanguageCapabilityInsight( 1122 capability=plan.capability, 1123 category=plan.category, 1124 maturity=plan.maturity, 1125 description=plan.description, 1126 reasoning=plan.reasoning, 1127 pipeline_components=list(plan.pipeline_components), 1128 tooling=list(plan.tooling), 1129 datasets=list(plan.datasets), 1130 evaluation_metrics=list(plan.evaluation_metrics), 1131 revenue_programs=list(plan.revenue_programs), 1132 orchestration_steps=list(plan.orchestration_steps), 1133 source=plan.source, 1134 notes=plan.notes, 1135 ) 1136 1137 1138def _code_automation_payload(plan: CodeAutomationPlan) -> "CodeAutomationInsight": 1139 return CodeAutomationInsight( 1140 capability=plan.capability, 1141 category=plan.category, 1142 maturity=plan.maturity, 1143 description=plan.description, 1144 reasoning=plan.reasoning, 1145 automation_stages=list(plan.automation_stages), 1146 tooling=list(plan.tooling), 1147 platforms=list(plan.platforms), 1148 metrics=list(plan.metrics), 1149 revenue_programs=list(plan.revenue_programs), 1150 guardrails=list(plan.guardrails), 1151 orchestration_steps=list(plan.orchestration_steps), 1152 source=plan.source, 1153 notes=plan.notes, 1154 ) 1155 1156 1157def _expert_activation_payload(activation: ExpertActivation) -> "ExpertActivationInsight": 1158 return ExpertActivationInsight( 1159 name=activation.name, 1160 provider=activation.provider, 1161 role=activation.role, 1162 confidence=activation.confidence, 1163 reasoning=activation.reasoning, 1164 outputs=list(activation.outputs), 1165 metrics=list(activation.metrics), 1166 fallback=activation.fallback, 1167 source=activation.source, 1168 ) 1169 1170 1171def _mixture_of_experts_payload(plan: MixtureOfExpertsPlan) -> "MixtureOfExpertsInsight": 1172 return MixtureOfExpertsInsight( 1173 router_summary=plan.router_summary, 1174 maturity=plan.maturity, 1175 activations=[_expert_activation_payload(act) for act in plan.activations], 1176 evaluation_metrics=list(plan.evaluation_metrics), 1177 notes=plan.notes, 1178 source=plan.source, 1179 ) 1180 1181 1182def _agentic_loop_payload(plan: AgenticLoopPlan) -> "AgenticLoopInsight": 1183 return AgenticLoopInsight( 1184 name=plan.name, 1185 goal_focus=plan.goal_focus, 1186 summary=plan.summary, 1187 maturity=plan.maturity, 1188 reasoning=plan.reasoning, 1189 stages=[ 1190 AgenticLoopStageInsight( 1191 stage=stage.stage, 1192 objective=stage.objective, 1193 actions=list(stage.actions), 1194 tools=list(stage.tools), 1195 signals=list(stage.signals), 1196 outputs=list(stage.outputs), 1197 metrics=list(stage.metrics), 1198 ) 1199 for stage in plan.stages 1200 ], 1201 guardrails=list(plan.guardrails), 1202 source=plan.source, 1203 ) 1204 1205 1206def _quantum_simulation_payload(plan: QuantumStressTestPlan) -> "QuantumSimulationInsight": 1207 return QuantumSimulationInsight( 1208 simulator=plan.simulator, 1209 provider=plan.provider, 1210 maturity=plan.maturity, 1211 description=plan.description, 1212 reasoning=plan.reasoning, 1213 training_focus=list(plan.training_focus), 1214 stress_tests=[ 1215 QuantumStressScenarioInsight( 1216 name=test.name, 1217 domain=test.domain, 1218 objective=test.objective, 1219 stressors=list(test.stressors), 1220 metrics=list(test.metrics), 1221 gate_sequence=list(test.gate_sequence), 1222 measurement_probability=test.measurement_probability, 1223 stability_index=test.stability_index, 1224 integration_points=list(test.integration_points), 1225 recommended_actions=list(test.recommended_actions), 1226 notes=test.notes, 1227 ) 1228 for test in plan.stress_tests 1229 ], 1230 orchestration_steps=list(plan.orchestration_steps), 1231 metrics=list(plan.metrics), 1232 dependencies=list(plan.dependencies), 1233 docs=list(plan.docs), 1234 coverage_ratio=plan.coverage_ratio, 1235 domain_stability=dict(plan.domain_stability), 1236 source=plan.source, 1237 notes=plan.notes, 1238 ) 1239 1240 1241def _physics_economics_payload( 1242 plan: PhysicsEconomicsPlan, 1243) -> "PhysicsEconomicsInsight": 1244 return PhysicsEconomicsInsight( 1245 capability=plan.capability, 1246 domain=plan.domain, 1247 maturity=plan.maturity, 1248 description=plan.description, 1249 rationale=plan.rationale, 1250 marketing_algorithms=list(plan.marketing_algorithms), 1251 physics_principles=list(plan.physics_principles), 1252 quantum_strategies=list(plan.quantum_strategies), 1253 economic_models=list(plan.economic_models), 1254 hardware_strategies=list(plan.hardware_strategies), 1255 data_compression=list(plan.data_compression), 1256 risk_controls=list(plan.risk_controls), 1257 metrics=list(plan.metrics), 1258 orchestration_steps=list(plan.orchestration_steps), 1259 docs=list(plan.docs), 1260 source=plan.source, 1261 notes=plan.notes, 1262 ) 1263 1264 1265def _influencer_payload( 1266 recommendation: InfluencerRecommendation, 1267) -> "InfluencerInsight": 1268 return InfluencerInsight( 1269 name=recommendation.name, 1270 platform=recommendation.platform, 1271 niche=recommendation.niche, 1272 collab_format=recommendation.collab_format, 1273 audience_size=recommendation.audience_size, 1274 engagement_rate=recommendation.engagement_rate, 1275 estimated_reach=recommendation.estimated_reach, 1276 projected_cpm=recommendation.projected_cpm, 1277 projected_leads=recommendation.projected_leads, 1278 projected_revenue=recommendation.projected_revenue, 1279 projected_roi=recommendation.projected_roi, 1280 rationale=recommendation.rationale, 1281 source=recommendation.source, 1282 notes=recommendation.notes, 1283 ) 1284 1285 1286def _amazon_listing_payload( 1287 recommendation: AmazonProductRecommendation, 1288) -> "AmazonMarketplaceInsight": 1289 return AmazonMarketplaceInsight( 1290 asin=recommendation.asin, 1291 title=recommendation.title, 1292 category=recommendation.category, 1293 price_usd=recommendation.price_usd, 1294 commission_rate=recommendation.commission_rate, 1295 rating=recommendation.rating, 1296 reviews=recommendation.reviews, 1297 estimated_monthly_sales=recommendation.estimated_monthly_sales, 1298 buy_box_share=recommendation.buy_box_share, 1299 prime_eligible=recommendation.prime_eligible, 1300 fulfillment_model=recommendation.fulfillment_model, 1301 projected_monthly_revenue=recommendation.projected_monthly_revenue, 1302 rationale=recommendation.rationale, 1303 url=recommendation.url, 1304 source=recommendation.source, 1305 notes=recommendation.notes, 1306 ) 1307 1308 1309def _ebay_listing_payload(recommendation: EbayRevenuePlay) -> "EbayMarketplaceInsight": 1310 return EbayMarketplaceInsight( 1311 item_id=recommendation.item_id, 1312 title=recommendation.title, 1313 category=recommendation.category, 1314 price_usd=recommendation.price_usd, 1315 affiliate_rate=recommendation.affiliate_rate, 1316 seller_level=recommendation.seller_level, 1317 seller_rating=recommendation.seller_rating, 1318 conversion_rate=recommendation.conversion_rate, 1319 sold_per_month=recommendation.sold_per_month, 1320 projected_monthly_revenue=recommendation.projected_monthly_revenue, 1321 projected_profit_margin=recommendation.projected_profit_margin, 1322 shipping_days=recommendation.shipping_days, 1323 rationale=recommendation.rationale, 1324 url=recommendation.url, 1325 source=recommendation.source, 1326 notes=recommendation.notes, 1327 ) 1328 1329 1330def _aws_revenue_payload(recommendation: AWSRevenueRecommendation) -> "AWSRevenueInsight": 1331 return AWSRevenueInsight( 1332 program_name=recommendation.program_name, 1333 focus=recommendation.focus, 1334 description=recommendation.description, 1335 revenue_motion=recommendation.revenue_motion, 1336 primary_service=recommendation.primary_service, 1337 secondary_services=recommendation.secondary_services, 1338 automation_play=recommendation.automation_play, 1339 projected_roi=recommendation.projected_roi, 1340 source=recommendation.source, 1341 notes=recommendation.notes, 1342 ) 1343 1344 1345def _budget_plan_payload(plan: BudgetPlan) -> "BudgetPlanInsight": 1346 allocations = [ 1347 BudgetAllocationInsight( 1348 channel=allocation.channel, 1349 audience_focus=allocation.audience_focus, 1350 offer=allocation.offer, 1351 objective=allocation.objective, 1352 allocation_usd=allocation.allocation_usd, 1353 allocation_weight=allocation.allocation_weight, 1354 expected_leads=allocation.expected_leads, 1355 expected_revenue=allocation.expected_revenue, 1356 rationale=allocation.rationale, 1357 source=allocation.source, 1358 notes=allocation.notes, 1359 ) 1360 for allocation in plan.allocations 1361 ] 1362 1363 return BudgetPlanInsight( 1364 total_budget=plan.total_budget, 1365 expected_revenue=plan.expected_revenue, 1366 expected_roi=plan.expected_roi, 1367 payback_period_weeks=plan.payback_period_weeks, 1368 summary=plan.summary, 1369 allocations=allocations, 1370 ) 1371 1372 1373def _automation_task_payload(task: AutomationTask) -> AutomationTaskInsight: 1374 return AutomationTaskInsight( 1375 start_minute=task.start_minute, 1376 end_minute=task.end_minute, 1377 activity=task.activity, 1378 outcome=task.outcome, 1379 tooling=task.tooling, 1380 kpis=task.kpis, 1381 automation_level=task.automation_level, 1382 source=task.source, 1383 ) 1384 1385 1386def _automation_sprint_payload(sprint: AutomationSprint) -> AutomationSprintInsight: 1387 return AutomationSprintInsight( 1388 total_minutes=sprint.total_minutes, 1389 stage=sprint.stage, 1390 focus=sprint.focus, 1391 summary=sprint.summary, 1392 notes=sprint.notes, 1393 tasks=[_automation_task_payload(task) for task in sprint.tasks], 1394 source=sprint.source, 1395 ) 1396 1397 1398def _learning_loop_payload(recommendation: LearningLoopRecommendation) -> "LearningLoopInsight": 1399 return LearningLoopInsight( 1400 play_name=recommendation.play_name, 1401 stage=recommendation.stage, 1402 audience_focus=recommendation.audience_focus, 1403 channel=recommendation.channel, 1404 learning=recommendation.learning, 1405 wins=recommendation.wins, 1406 losses=recommendation.losses, 1407 next_actions=recommendation.next_actions, 1408 kpi_focus=recommendation.kpi_focus, 1409 confidence=recommendation.confidence, 1410 source=recommendation.source, 1411 notes=recommendation.notes, 1412 ) 1413 1414 1415def _competitive_signal_payload(signal: CompetitiveSignal) -> "CompetitiveLandscapeInsight": 1416 return CompetitiveLandscapeInsight( 1417 competitor=signal.competitor, 1418 channel=signal.channel, 1419 summary=signal.summary, 1420 strengths=signal.strengths, 1421 weaknesses=signal.weaknesses, 1422 recommended_play=signal.recommended_play, 1423 share_of_voice=signal.share_of_voice, 1424 signal_intensity=signal.signal_intensity, 1425 threat_level=signal.threat_level, 1426 focus_alignment=signal.focus_alignment, 1427 source=signal.source, 1428 notes=signal.notes, 1429 ) 1430 1431 1432def _excellence_payload(summary: ExcellenceSummary) -> ExcellenceInsight: 1433 return ExcellenceInsight( 1434 excellence_index=summary.excellence_index, 1435 maturity_level=summary.maturity_level, 1436 headline=summary.headline, 1437 strengths=summary.strengths, 1438 watchouts=summary.watchouts, 1439 process_coverage=summary.process_coverage, 1440 notes=summary.notes, 1441 ) 1442 1443 1444def _directive_payload(directive: StrategicDirective) -> StrategicDirectiveInsight: 1445 return StrategicDirectiveInsight( 1446 name=directive.name, 1447 priority=directive.priority, 1448 objective=directive.objective, 1449 primary_channel=directive.primary_channel, 1450 supporting_channels=directive.supporting_channels, 1451 investment_usd=directive.investment_usd, 1452 expected_revenue_usd=directive.expected_revenue_usd, 1453 confidence=directive.confidence, 1454 time_horizon_hours=directive.time_horizon_hours, 1455 north_star_metric=directive.north_star_metric, 1456 supporting_metrics=directive.supporting_metrics, 1457 action_steps=directive.action_steps, 1458 dependencies=directive.dependencies, 1459 risk_mitigations=directive.risk_mitigations, 1460 inspiration=directive.inspiration, 1461 source=directive.source, 1462 notes=directive.notes, 1463 ) 1464 1465 1466def _playbook_payload(playbook: ExecutivePlaybook) -> ExecutivePlaybookInsight: 1467 return ExecutivePlaybookInsight( 1468 headline=playbook.headline, 1469 focus=playbook.focus, 1470 urgency=playbook.urgency, 1471 north_star_metric=playbook.north_star_metric, 1472 total_budget_usd=playbook.total_budget_usd, 1473 expected_revenue_usd=playbook.expected_revenue_usd, 1474 confidence=playbook.confidence, 1475 directives=[_directive_payload(directive) for directive in playbook.directives], 1476 summary=playbook.summary, 1477 notes=playbook.notes, 1478 ) 1479 1480 1481def _scenario_projection_payload(projection: ScenarioProjection) -> ScenarioProjectionInsight: 1482 return ScenarioProjectionInsight( 1483 scenario=projection.scenario, 1484 expected_revenue=projection.expected_revenue, 1485 expected_roi=projection.expected_roi, 1486 probability=projection.probability, 1487 confidence=projection.confidence, 1488 accelerators=projection.accelerators, 1489 stabilizers=projection.stabilizers, 1490 watchouts=projection.watchouts, 1491 source=projection.source, 1492 notes=projection.notes, 1493 ) 1494 1495 1496def _scenario_planning_payload(analysis: ScenarioAnalysis) -> ScenarioPlanningInsight: 1497 return ScenarioPlanningInsight( 1498 headline=analysis.headline, 1499 summary=analysis.summary, 1500 projections=[_scenario_projection_payload(proj) for proj in analysis.projections],