Motor de Infográfico Orientado por Pesquisa

Grade 2x2, 16:9, faça pesquisa sobre isso para o custo do iPhone 18 e 3 outros tópicos virais: class ResearchDrivenInfographicEngine: def __init__(self, topic): self.topic = topic self.research = conduct_research( topic, source_types=[ "official data", "academic papers", "industry reports", "primary sources", "credible journalism", "technical documentation" ] ) self.topic_structure = infer_topic_structure(topic, self.research) self.visual_layout = choose_best_layout(self.topic_structure) self.dimensions = infer_dimensions(topic, self.research) self.metrics = infer_metrics(topic, self.research) self.tradeoffs = infer_tradeoffs(topic, self.research) self.insights = derive_key_insights(topic, self.research) def choose_layout(self): return best_fit_layout( topic_structure=self.topic_structure, candidates=[ "exploded teardown", "timeline", "map", "network", "flow diagram", "matrix", "scorecard", "anatomy", "supply chain", "stakeholder grid", "lifecycle curve", "layered stack", "comparison dashboard" ] ) def poster_modules(self): return { "headline": derive_headline(self.topic, self.insights), "subtitle": derive_explanatory_subtitle(self.topic), "main_visual": self.visual_layout, "dimension_legend": self.dimensions, "metric_blocks": self.metrics, "tradeoff_box": self.tradeoffs, "score_panel": infer_score_if_useful(self.topic), "methodology": summarize_methodology(self.research), "source_footer": cite_sources(self.research) } def render(self): return """ Render a premium vertical editorial infographic. Use the layout chosen by the structure of the topic. Include researched metrics, source notes, dimensions, insight boxes, and a clear explanatory visual hierarchy. """