Janady13/AI_Brain / tests/test_marketing_intelligence.py

1from services.seeder_api.app import ( 2 MarketingQuery, 3 marketing_diagnostics, 4 marketing_intelligence, 5 marketing_processes, 6 marketing_statistical_intelligence, 7) 8import base64 9import json 10 11from services.seeder_api.intelligence import ( 12 AmazonMarketplaceProcess, 13 AWSRevenueProcess, 14 BudgetAllocatorProcess, 15 CJAffiliateProcess, 16 CryptoMarketProcess, 17 EbayMarketplaceProcess, 18 GoogleAdsProcess, 19 MarketingCampaign, 20 MarketingIntelligenceEngine, 21 AutomationSprintPlanner, 22 LearningLoopProcess, 23 CompetitiveIntelligenceProcess, 24 ScenarioPlanningProcess, 25 StripeProcess, 26 PayPalProcess, 27 InfluencerCollaborationProcess, 28 StatisticalReasoningProcess, 29 AgenticSystemsProcess, 30) 31 32 33def test_marketing_campaign_parsing_handles_standard_format(): 34 raw = ( 35 "Campaign: social ads targeting climate tech founders leveraging video testimonial to drive product demos." 36 ) 37 campaign = MarketingCampaign.parse(raw) 38 assert campaign.channel == "social ads" 39 assert campaign.audience == "climate tech founders" 40 assert campaign.offer == "video testimonial" 41 assert campaign.objective == "drive product demos" 42 43 44def test_marketing_engine_recommendations_use_prompt_keywords(): 45 engine = MarketingIntelligenceEngine.from_file() 46 results = engine.recommend("B2B SaaS founders looking for pipeline velocity", limit=2) 47 assert len(results) == 2 48 assert any("B2B SaaS founders" in campaign.audience for campaign in results) 49 50 51def test_marketing_statistical_engine_enriches_results_with_metrics(): 52 engine = MarketingIntelligenceEngine.from_file() 53 scored = engine.recommend_statistical( 54 "Need ROI positive programs for B2B SaaS founders", limit=2 55 ) 56 assert len(scored) == 2 57 assert all(score.metrics.expected_roi > 0 for score in scored) 58 assert any(score.keyword_coverage["audience"] > 0 for score in scored) 59 60 61def test_statistical_reasoning_summary_blends_priors_and_campaigns(): 62 engine = MarketingIntelligenceEngine.from_file() 63 prompt = "Enterprise pipeline needs statistical ROI certainty" 64 ranked = engine.recommend_statistical(prompt, limit=2) 65 stock_markets = engine.stock_market_enrichment(prompt, ranked, limit=2) 66 crypto_markets = engine.crypto_market_enrichment(prompt, limit=2) 67 budget_plan = engine.budget_optimizer(prompt, ranked, limit=2) 68 69 summary = engine.statistical_reasoning_summary( 70 prompt, 71 ranked, 72 budget=budget_plan, 73 stock_markets=stock_markets, 74 crypto_markets=crypto_markets, 75 limit=2, 76 ) 77 78 assert summary.expected_roi > 0 79 assert summary.success_probability > 0 80 assert summary.evidence 81 assert summary.driver_confidence 82 assert "success" in summary.narrative.lower() 83 84 85def test_marketing_intelligence_endpoint_returns_structured_payload(): 86 payload = marketing_intelligence( 87 MarketingQuery(prompt="Need to accelerate demos for B2B SaaS founders", limit=2) 88 ) 89 assert payload.query == "Need to accelerate demos for B2B SaaS founders" 90 assert len(payload.recommendations) == 2 91 audiences = {entry.audience for entry in payload.recommendations} 92 assert any("B2B SaaS founders" in audience for audience in audiences) 93 assert "accelerate" in payload.insight.lower() 94 95 96def test_marketing_statistical_endpoint_returns_portfolio_metrics(): 97 payload = marketing_statistical_intelligence( 98 MarketingQuery(prompt="Optimize ROI for AI founders", limit=2) 99 ) 100 assert payload.query == "Optimize ROI for AI founders" 101 assert len(payload.recommendations) == 2 102 assert payload.portfolio.expected_roi > 0 103 assert payload.portfolio.confidence > 0 104 assert payload.portfolio.strongest_drivers 105 106 107def test_marketing_engine_diagnostics_detects_stage_and_focus(): 108 engine = MarketingIntelligenceEngine.from_file() 109 diagnostics = engine.diagnose("Need urgent conversion plays for enterprise SaaS founders") 110 assert diagnostics.stage in {"conversion", "consideration"} 111 assert diagnostics.urgency != "standard" 112 assert diagnostics.focus.startswith("enterprise") or "startup" in diagnostics.focus 113 assert diagnostics.recommended_kpis 114 assert diagnostics.keyword_summary["tokens"] 115 116 117def test_marketing_diagnostics_endpoint_returns_structured_analysis(): 118 payload = marketing_diagnostics( 119 MarketingQuery(prompt="Pipeline is stalled for B2B founders, need fast ROI", limit=3) 120 ) 121 assert payload.query == "Pipeline is stalled for B2B founders, need fast ROI" 122 assert payload.stage in {"conversion", "consideration"} 123 assert "pipeline" in payload.recommended_kpis[0].lower() or payload.recommended_kpis 124 assert payload.opportunities 125 assert "Performance plateau" in " ".join(payload.risk_signals) or not payload.risk_signals 126 127 128def test_marketing_engine_expansion_grid_generates_egg_experiments(): 129 engine = MarketingIntelligenceEngine.from_file() 130 scored = engine.recommend_statistical( 131 "Need urgent conversion plays for enterprise SaaS founders", limit=2 132 ) 133 experiments = engine.expansion_grid("Need urgent conversion plays for enterprise SaaS founders", scored) 134 assert experiments 135 first = experiments[0] 136 assert first.primary_metric 137 assert first.playbook 138 assert 0.2 <= first.confidence <= 0.99 139 140 141def test_marketing_engine_google_ads_fallback_without_credentials(monkeypatch): 142 monkeypatch.delenv("GOOGLE_ADS_DEVELOPER_TOKEN", raising=False) 143 monkeypatch.delenv("GOOGLE_ADS_CLIENT_ID", raising=False) 144 monkeypatch.delenv("GOOGLE_ADS_CLIENT_SECRET", raising=False) 145 monkeypatch.delenv("GOOGLE_ADS_REFRESH_TOKEN", raising=False) 146 monkeypatch.delenv("GOOGLE_ADS_CUSTOMER_ID", raising=False) 147 148 engine = MarketingIntelligenceEngine.from_file() 149 scored = engine.recommend_statistical( 150 "Need urgent conversion plays for enterprise SaaS founders", limit=2 151 ) 152 insights = engine.google_ads_enrichment( 153 "Need urgent conversion plays for enterprise SaaS founders", scored, limit=2 154 ) 155 assert len(insights) == 2 156 assert all(entry.source == "simulated" for entry in insights) 157 assert all(entry.clicks > 0 for entry in insights) 158 159 160def test_google_ads_process_loads_service_account_credentials(monkeypatch): 161 info = { 162 "type": "service_account", 163 "project_id": "test-project", 164 "private_key_id": "abc123", 165 "private_key": "-----BEGIN PRIVATE KEY-----\nabc\n-----END PRIVATE KEY-----\n", 166 "client_email": "ai-403@encoded-equator-335209.iam.gserviceaccount.com", 167 "client_id": "109575360154363072675", 168 "token_uri": "https://oauth2.googleapis.com/token", 169 } 170 encoded = base64.b64encode(json.dumps(info).encode("utf-8")).decode("utf-8") 171 172 monkeypatch.setenv("GOOGLE_ADS_DEVELOPER_TOKEN", "dev-token") 173 monkeypatch.setenv("GOOGLE_ADS_CUSTOMER_ID", "1234567890") 174 monkeypatch.setenv("GOOGLE_ADS_SERVICE_ACCOUNT_B64", encoded) 175 176 process = GoogleAdsProcess() 177 assert process._config["developer_token"] == "dev-token" 178 assert process._config["customer_id"] == "1234567890" 179 assert process._config["service_account_info"]["client_email"] == info["client_email"] 180 assert process.configured is False # without SDK the client remains unconfigured 181 182 183def test_cj_affiliate_process_catalog_fallback(monkeypatch): 184 monkeypatch.delenv("CJ_DEVELOPER_KEY", raising=False) 185 monkeypatch.delenv("CJ_WEBSITE_ID", raising=False) 186 monkeypatch.delenv("CJ_ACCOUNT_ID", raising=False) 187 188 engine = MarketingIntelligenceEngine.from_file() 189 scored = engine.recommend_statistical( 190 "Affiliate monetization ideas for AI SaaS founders", limit=3 191 ) 192 193 process = CJAffiliateProcess() 194 recommendations = process.offers( 195 "Affiliate monetization ideas for AI SaaS founders", scored, limit=2 196 ) 197 198 assert recommendations 199 assert all(entry.source == "cj_catalog" for entry in recommendations) 200 assert all(entry.projected_monthly_revenue > 0 for entry in recommendations) 201 202 203def test_cj_affiliate_process_harvests_env_configuration(monkeypatch): 204 monkeypatch.setenv("CJ_DEVELOPER_KEY", "dev-key") 205 monkeypatch.setenv("CJ_WEBSITE_ID", "site-123") 206 207 process = CJAffiliateProcess() 208 209 assert process.configured is True 210 assert process._config["developer_key"] == "dev-key" 211 assert process._config["website_id"] == "site-123" 212 213 214def test_crypto_market_process_fallback_without_requests(): 215 process = CryptoMarketProcess(allow_network=False) 216 snapshots = process.market_data("Need BTC ETH and SOL price intel", limit=3) 217 assert len(snapshots) == 3 218 assert all(snapshot.source in {"simulated", "coingecko", "coincap"} for snapshot in snapshots) 219 assert any(snapshot.asset == "bitcoin" for snapshot in snapshots) 220 221 222def test_stripe_process_generates_checkout_plans(monkeypatch): 223 monkeypatch.delenv("STRIPE_API_KEY", raising=False) 224 monkeypatch.delenv("STRIPE_ACCOUNT_ID", raising=False) 225 226 engine = MarketingIntelligenceEngine.from_file() 227 scored = engine.recommend_statistical("Launch subscription for enterprise AI", limit=2) 228 process = StripeProcess() 229 plans = process.plans("Launch subscription for enterprise AI", scored, limit=2) 230 231 assert plans 232 assert all(plan.source in {"simulated", "stripe_sdk"} for plan in plans) 233 assert plans[0].billing_interval in {"monthly", "annual", "one_time"} 234 235 236def test_paypal_process_generates_checkout_plans(monkeypatch): 237 monkeypatch.delenv("PAYPAL_CLIENT_ID", raising=False) 238 monkeypatch.delenv("PAYPAL_CLIENT_SECRET", raising=False) 239 monkeypatch.delenv("PAYPAL_MERCHANT_ID", raising=False) 240 241 engine = MarketingIntelligenceEngine.from_file() 242 scored = engine.recommend_statistical("Need to monetize community via digital products", limit=2) 243 process = PayPalProcess() 244 plans = process.plans("Need to monetize community via digital products", scored, limit=2) 245 246 assert plans 247 assert all(plan.source in {"simulated", "paypal_sdk"} for plan in plans) 248 assert plans[0].checkout_flow in {"subscription", "invoice", "one_time"} 249 assert plans[0].payout_schedule in {"daily", "weekly", "rolling"} 250 251 252def test_influencer_process_recommends_partner_reach(): 253 engine = MarketingIntelligenceEngine.from_file() 254 scored = engine.recommend_statistical("Launch AI automation suite with influencer blitz", limit=3) 255 process = InfluencerCollaborationProcess() 256 recommendations = process.recommendations( 257 "Launch AI automation suite with influencer blitz", scored, limit=2 258 ) 259 260 assert recommendations 261 assert all(rec.estimated_reach > 0 for rec in recommendations) 262 assert all(rec.projected_roi > 0 for rec in recommendations) 263 assert {rec.source for rec in recommendations}.issubset( 264 {"influencer_catalog", "influencer_api"} 265 ) 266 267 268def test_agentic_systems_process_scores_agent_workflows(monkeypatch): 269 monkeypatch.delenv("DATABASE_URL", raising=False) 270 monkeypatch.delenv("FEATURE_STORE_URL", raising=False) 271 monkeypatch.delenv("VECTOR_DB_URL", raising=False) 272 273 engine = MarketingIntelligenceEngine.from_file() 274 scored = engine.recommend_statistical( 275 "Need agent workflows orchestrating databases and trading automation", limit=3 276 ) 277 278 process = AgenticSystemsProcess() 279 plans = process.plans( 280 "Need agent workflows orchestrating databases and trading automation", scored, limit=2 281 ) 282 283 assert plans 284 assert all(plan.system_name for plan in plans) 285 assert any("database" in " ".join(plan.data_interfaces).lower() for plan in plans) 286 assert all(plan.source in {"agentic_systems_catalog", "agentic_systems_live"} for plan in plans) 287 288 289def test_amazon_marketplace_process_offline_catalog(monkeypatch): 290 monkeypatch.delenv("AMAZON_PAAPI_ACCESS_KEY", raising=False) 291 monkeypatch.delenv("AMAZON_PAAPI_SECRET_KEY", raising=False) 292 monkeypatch.delenv("AMAZON_PAAPI_PARTNER_TAG", raising=False) 293 294 engine = MarketingIntelligenceEngine.from_file() 295 scored = engine.recommend_statistical( 296 "Need retail and aws marketplace offers for ai founders", limit=3 297 ) 298 299 process = AmazonMarketplaceProcess() 300 listings = process.listings( 301 "Need retail and aws marketplace offers for ai founders", scored, limit=2 302 ) 303 304 assert listings 305 assert all(entry.source in {"amazon_catalog", "amazon_paapi"} for entry in listings) 306 assert listings[0].projected_monthly_revenue > 0 307 308 309def test_ebay_marketplace_process_offline_catalog(monkeypatch): 310 monkeypatch.delenv("EBAY_APP_ID", raising=False) 311 monkeypatch.delenv("EBAY_CERT_ID", raising=False) 312 monkeypatch.delenv("EBAY_DEV_ID", raising=False) 313 314 engine = MarketingIntelligenceEngine.from_file() 315 scored = engine.recommend_statistical( 316 "Need ecommerce partnerships and wearable funnels", limit=3 317 ) 318 319 process = EbayMarketplaceProcess() 320 listings = process.listings( 321 "Need ecommerce partnerships and wearable funnels", scored, limit=2 322 ) 323 324 assert listings 325 assert all(entry.source in {"ebay_catalog", "ebay_partner_api"} for entry in listings) 326 assert listings[0].projected_monthly_revenue > 0 327 assert listings[0].projected_profit_margin > 0 328 329 330def test_aws_revenue_process_generates_playbooks(monkeypatch): 331 monkeypatch.delenv("AWS_ACCESS_KEY_ID", raising=False) 332 monkeypatch.delenv("AWS_SECRET_ACCESS_KEY", raising=False) 333 monkeypatch.delenv("AWS_SESSION_TOKEN", raising=False) 334 335 engine = MarketingIntelligenceEngine.from_file() 336 scored = engine.recommend_statistical("Scale conversion with aws pinpoint journeys", limit=3) 337 338 process = AWSRevenueProcess() 339 programs = process.plays("Scale conversion with aws pinpoint journeys", scored, limit=2) 340 341 assert programs 342 assert all(entry.source in {"aws_playbooks", "aws_sdk"} for entry in programs) 343 assert programs[0].projected_roi > 0 344 345 346def test_budget_allocator_process_generates_plan(monkeypatch): 347 engine = MarketingIntelligenceEngine.from_file() 348 scored = engine.recommend_statistical( 349 "Deploy $45k across enterprise pipeline accelerators", limit=3 350 ) 351 352 process = BudgetAllocatorProcess() 353 plan = process.plan("Deploy $45k across enterprise pipeline accelerators", scored, limit=2) 354 355 assert plan.total_budget >= 45000 356 assert plan.allocations 357 assert abs(sum(allocation.allocation_usd for allocation in plan.allocations) - plan.total_budget) <= 1.0 358 assert plan.expected_revenue >= plan.total_budget 359 assert 0 < plan.expected_roi 360 361 362def test_automation_sprint_planner_generates_three_hour_schedule(): 363 engine = MarketingIntelligenceEngine.from_file() 364 prompt = "Need urgent conversion plays for enterprise SaaS founders" 365 scored = engine.recommend_statistical(prompt, limit=3) 366 diagnostics = engine.diagnose(prompt) 367 368 planner = AutomationSprintPlanner() 369 sprint = planner.plan(prompt, diagnostics, scored, limit=3) 370 371 assert sprint.total_minutes == 180 372 assert len(sprint.tasks) == sprint.total_minutes // 30 373 assert sprint.tasks[0].start_minute == 0 374 assert sprint.tasks[-1].end_minute == sprint.total_minutes 375 assert "automation" in sprint.summary.lower() 376 377 378def test_learning_loop_process_surfaces_closed_loop_recommendations(): 379 engine = MarketingIntelligenceEngine.from_file() 380 prompt = "Need enterprise AI pipeline recovery with stronger ROI" 381 scored = engine.recommend_statistical(prompt, limit=3) 382 diagnostics = engine.diagnose(prompt) 383 384 process = LearningLoopProcess() 385 insights = process.recommend(prompt, diagnostics, scored, limit=2) 386 387 assert insights 388 first = insights[0] 389 assert first.learning 390 assert first.next_actions 391 assert first.source == "performance_memory" 392 393 394def test_marketing_engine_automation_sprint_infers_from_prompt(): 395 engine = MarketingIntelligenceEngine.from_file() 396 sprint = engine.automation_sprint( 397 "Need urgent conversion plays for enterprise SaaS founders", limit=2 398 ) 399 400 assert sprint.stage in {"conversion", "consideration", "awareness", "retention"} 401 assert sprint.total_minutes == 180 402 assert all(task.start_minute < task.end_minute for task in sprint.tasks) 403 404 405def test_marketing_engine_learning_loop_aligns_with_prompt(): 406 engine = MarketingIntelligenceEngine.from_file() 407 insights = engine.learning_loop( 408 "Need enterprise AI pipeline recovery with stronger ROI", limit=2 409 ) 410 411 assert insights 412 assert any(insight.stage.lower() in {"conversion", "consideration"} for insight in insights) 413 assert all(insight.next_actions for insight in insights) 414 415 416def test_competitive_process_surfaces_counter_moves(): 417 engine = MarketingIntelligenceEngine.from_file() 418 prompt = "Need to outmaneuver paid search competitors for AI security buyers" 419 scored = engine.recommend_statistical(prompt, limit=2) 420 diagnostics = engine.diagnose(prompt) 421 422 process = CompetitiveIntelligenceProcess() 423 signals = process.signals(prompt, diagnostics, scored, limit=2) 424 425 assert signals 426 assert all(signal.threat_level in {"low", "medium", "high"} for signal in signals) 427 assert all(0.0 <= signal.focus_alignment <= 1.0 for signal in signals) 428 429 430def test_marketing_processes_endpoint_combines_rag_and_egg(): 431 payload = marketing_processes( 432 MarketingQuery(prompt="Need urgent conversion plays for enterprise SaaS founders", limit=2) 433 ) 434 assert payload.query == "Need urgent conversion plays for enterprise SaaS founders" 435 assert payload.rag.process == "rag" 436 assert len(payload.rag.recommendations) == 2 437 assert payload.egg 438 assert payload.egg[0].playbook 439 assert payload.google_ads 440 assert payload.google_ads[0].source in {"simulated", "google_ads_api"} 441 assert payload.cj_affiliate 442 assert payload.cj_affiliate[0].projected_monthly_revenue > 0 443 assert payload.crypto_markets 444 assert payload.crypto_markets[0].asset 445 assert payload.stock_markets 446 assert payload.stock_markets[0].symbol 447 assert payload.stripe 448 assert payload.stripe[0].product_name 449 assert payload.paypal 450 assert payload.paypal[0].checkout_flow 451 assert payload.cognitive_architecture 452 assert payload.cognitive_architecture[0].capability 453 assert payload.agentic_systems 454 assert payload.agentic_systems[0].system_name 455 assert payload.agentic_systems[0].toolchain 456 assert payload.influencer_collaborations 457 assert payload.influencer_collaborations[0].projected_roi > 0 458 assert payload.amazon_marketplace 459 assert payload.amazon_marketplace[0].estimated_monthly_sales > 0 460 assert payload.amazon_marketplace[0].fulfillment_model 461 assert payload.ebay_marketplace 462 assert payload.ebay_marketplace[0].projected_profit_margin > 0 463 assert payload.aws_cloud 464 assert payload.budget_optimizer.total_budget >= sum( 465 allocation.allocation_usd for allocation in payload.budget_optimizer.allocations 466 ) 467 assert payload.budget_optimizer.expected_revenue >= payload.budget_optimizer.total_budget 468 assert payload.automation.total_minutes == 180 469 assert payload.automation.tasks 470 assert payload.automation.tasks[0].start_minute == 0 471 assert payload.learning_loop 472 assert payload.learning_loop[0].next_actions 473 assert payload.competitive_landscape 474 assert payload.competitive_landscape[0].threat_level in {"low", "medium", "high"} 475 assert payload.excellence.maturity_level in {"emerging", "scaling", "elite", "world-class"} 476 assert 0 <= payload.excellence.excellence_index <= 100 477 assert "rag" in payload.excellence.process_coverage 478 assert "ebay_marketplace" in payload.excellence.process_coverage 479 assert "paypal" in payload.excellence.process_coverage 480 assert "influencer_collaborations" in payload.excellence.process_coverage 481 assert "stock_markets" in payload.excellence.process_coverage 482 assert "cognitive_architecture" in payload.excellence.process_coverage 483 assert "agentic_systems" in payload.excellence.process_coverage 484 assert payload.excellence.strengths 485 assert payload.excellence.watchouts 486 assert payload.executive_playbook.headline 487 assert payload.executive_playbook.directives 488 top_directive = payload.executive_playbook.directives[0] 489 assert top_directive.supporting_channels 490 assert payload.executive_playbook.north_star_metric in top_directive.supporting_metrics 491 assert top_directive.action_steps 492 assert top_directive.risk_mitigations 493 assert any(channel.startswith("Markets -") for channel in top_directive.supporting_channels) 494 assert payload.scenario_planning.headline 495 assert payload.scenario_planning.projections 496 scenario_labels = {projection.scenario for projection in payload.scenario_planning.projections} 497 assert {"optimistic", "base", "conservative"}.issubset(scenario_labels) 498 assert payload.scenario_planning.projections[0].probability > 0 499 assert payload.scenario_planning.accelerators 500 assert payload.scenario_planning.stabilizers 501 assert payload.statistical_reasoning.expected_roi > 0 502 assert payload.statistical_reasoning.success_probability > 0 503 assert payload.statistical_reasoning.evidence 504 505 506def test_marketing_engine_executive_playbook_blends_processes(): 507 engine = MarketingIntelligenceEngine.from_file() 508 prompt = "Accelerate enterprise pipeline with automation and partnerships" 509 rag_campaigns = engine.recommend(prompt, limit=3) 510 ranked = engine.recommend_statistical(prompt, limit=3) 511 egg = engine.expansion_grid(prompt, ranked) 512 google_ads = engine.google_ads_enrichment(prompt, ranked, limit=3) 513 cj_affiliate = engine.cj_affiliate_enrichment(prompt, ranked, limit=3) 514 crypto_markets = engine.crypto_market_enrichment(prompt, limit=3) 515 stock_markets = engine.stock_market_enrichment(prompt, ranked, limit=3) 516 stripe_plans = engine.stripe_checkout_enrichment(prompt, ranked, limit=3) 517 paypal_plans = engine.paypal_checkout_enrichment(prompt, ranked, limit=3) 518 influencers = engine.influencer_collaboration_enrichment(prompt, ranked, limit=3) 519 amazon = engine.amazon_marketplace_enrichment(prompt, ranked, limit=3) 520 ebay = engine.ebay_marketplace_enrichment(prompt, ranked, limit=3) 521 aws = engine.aws_cloud_enrichment(prompt, ranked, limit=3) 522 budget = engine.budget_optimizer(prompt, ranked, limit=3) 523 automation = engine.automation_sprint(prompt, ranked, limit=3) 524 learning = engine.learning_loop(prompt, ranked, limit=3) 525 competitive = engine.competitive_landscape(prompt, ranked, limit=3) 526 cognitive = engine.cognitive_architecture_enrichment(prompt, ranked, limit=3) 527 agentic = engine.agentic_system_enrichment(prompt, ranked, limit=3) 528 assert agentic 529 excellence = engine.excellence_summary( 530 prompt, 531 ranked, 532 limit=3, 533 rag=rag_campaigns, 534 egg=egg, 535 google_ads=google_ads, 536 cj_affiliate=cj_affiliate, 537 crypto_markets=crypto_markets, 538 stocks=stock_markets, 539 stripe=stripe_plans, 540 paypal=paypal_plans, 541 influencers=influencers, 542 amazon=amazon, 543 ebay=ebay, 544 aws=aws, 545 budget=budget, 546 automation=automation, 547 learning_loop=learning, 548 competitive=competitive, 549 cognitive=cognitive, 550 agentic=agentic, 551 ) 552 553 playbook = engine.executive_playbook( 554 prompt, 555 ranked, 556 limit=3, 557 rag=rag_campaigns, 558 egg=egg, 559 google_ads=google_ads, 560 cj_affiliate=cj_affiliate, 561 amazon=amazon, 562 ebay=ebay, 563 paypal=paypal_plans, 564 influencers=influencers, 565 stocks=stock_markets, 566 budget=budget, 567 automation=automation, 568 learning_loop=learning, 569 competitive=competitive, 570 excellence=excellence, 571 statistics=None, 572 cognitive=cognitive, 573 agentic=agentic, 574 ) 575 576 assert playbook.directives 577 assert playbook.north_star_metric 578 assert playbook.confidence >= 0.35 579 assert playbook.notes 580 directive = playbook.directives[0] 581 assert directive.priority == 1 582 assert directive.primary_channel in directive.supporting_channels[0] 583 assert directive.supporting_metrics 584 assert playbook.north_star_metric in directive.supporting_metrics 585 assert directive.dependencies 586 assert any("eBay" in channel for channel in directive.supporting_channels) 587 assert any("PayPal" in channel for channel in directive.supporting_channels) 588 assert any("Influencer" in channel for channel in directive.supporting_channels) 589 assert any(channel.startswith("Markets -") for channel in directive.supporting_channels) 590 assert any("Cognitive" in channel for channel in directive.supporting_channels) 591 assert any("Agentic" in channel for channel in directive.supporting_channels) 592 593 594def test_scenario_planning_process_generates_three_outcomes(): 595 engine = MarketingIntelligenceEngine.from_file() 596 prompt = "Drive enterprise conversions with integrated paid and partner motions" 597 ranked = engine.recommend_statistical(prompt, limit=3) 598 budget = engine.budget_optimizer(prompt, ranked, limit=3) 599 google_ads = engine.google_ads_enrichment(prompt, ranked, limit=3) 600 cj_affiliate = engine.cj_affiliate_enrichment(prompt, ranked, limit=3) 601 amazon = engine.amazon_marketplace_enrichment(prompt, ranked, limit=3) 602 aws = engine.aws_cloud_enrichment(prompt, ranked, limit=3) 603 stripe = engine.stripe_checkout_enrichment(prompt, ranked, limit=3) 604 paypal = engine.paypal_checkout_enrichment(prompt, ranked, limit=3) 605 crypto = engine.crypto_market_enrichment(prompt, limit=3) 606 stocks = engine.stock_market_enrichment(prompt, ranked, limit=3) 607 ebay = engine.ebay_marketplace_enrichment(prompt, ranked, limit=3) 608 influencers = engine.influencer_collaboration_enrichment(prompt, ranked, limit=3) 609 cognitive = engine.cognitive_architecture_enrichment(prompt, ranked, limit=3) 610 611 scenario = engine.scenario_planning( 612 prompt, 613 ranked, 614 limit=3, 615 budget=budget, 616 google_ads=google_ads, 617 cj_affiliate=cj_affiliate, 618 amazon=amazon, 619 ebay=ebay, 620 aws=aws, 621 stripe=stripe, 622 paypal=paypal, 623 crypto=crypto, 624 influencers=influencers, 625 stocks=stocks, 626 cognitive=cognitive, 627 ) 628 629 assert scenario.projections 630 assert len(scenario.projections) == 3 631 assert {proj.scenario for proj in scenario.projections} == {"optimistic", "base", "conservative"} 632 assert all(proj.expected_revenue > 0 for proj in scenario.projections) 633 assert scenario.accelerators 634 assert any("Equity" in accel or "market" in accel.lower() for accel in scenario.accelerators) 635 assert any("cognitive" in accel.lower() for accel in scenario.accelerators) 636 assert scenario.stabilizers 637 assert 0 < scenario.confidence <= 1 638