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Intelligent Worker Router with Expanded Steps and Quality Analysis\n\n// Define interfaces for type safety\ninterface Worker {\n name: string;\n description: string;\n bestFor: string[];\n complexity: number;\n maxTokens: number;\n}\n\ninterface WorkerMap {\n [key: string]: Worker;\n}\n\ninterface PromptAnalysis {\n length: number;\n wordCount: number;\n sentences: number;\n hasCode: boolean;\n hasTechnical: boolean;\n hasCreative: boolean;\n hasExamples: boolean;\n hasConstraints: boolean;\n hasQuestions: boolean;\n complexity: number;\n topics: string[];\n intent: string;\n}\n\ninterface PromptQuality {\n score: number;\n feedback: string[];\n}\n\ninterface FullPromptAnalysis extends PromptAnalysis {\n quality: PromptQuality;\n}\n\ninterface WorkerSelection {\n workers: string[];\n analysis: PromptAnalysis;\n reasoning: string[];\n}\n\nexport class IntelligentRouter {\n public workers: WorkerMap;\n\n constructor() {\n this.workers = {\n clarifier: { name: \"Clarifier\", description: \"Makes prompts clearer\", bestFor: [\"vague\"], complexity: 1, maxTokens: 2000 },\n condenser: { name: \"Condenser\", description: \"Removes redundancy\", bestFor: [\"verbose\"], complexity: 1, maxTokens: 1500 },\n includer: { name: \"Includer\", description: \"Adds helpful context\", bestFor: [\"brief\"], complexity: 1, maxTokens: 2500 },\n structurer: { name: \"Structurer\", description: \"Organizes prompt\", bestFor: [\"unstructured\"], complexity: 2, maxTokens: 2000 },\n technicalizer: { name: \"Technicalizer\", description: \"Adds tech specs\", bestFor: [\"technical\"], complexity: 2, maxTokens: 3000 },\n creativizer: { name: \"Creativizer\", description: \"Enhances creativity\", bestFor: [\"creative\"], complexity: 2, maxTokens: 2500 },\n contextualizer: { name: \"Contextualizer\", description: \"Adds background context\", bestFor: [\"lacks background\"], complexity: 2, maxTokens: 2500 },\n exemplifier: { name: \"Exemplifier\", description: \"Adds examples\", bestFor: [\"abstract\"], complexity: 2, maxTokens: 2000 },\n constrainer: { name: \"Constrainer\", description: \"Adds constraints\", bestFor: [\"too broad\"], complexity: 2, maxTokens: 1500 },\n validator: { name: \"Validator\", description: \"Adds validation criteria\", bestFor: [\"needs validation\"], complexity: 3, maxTokens: 2000 },\n optimizer: { name: \"Optimizer\", description: \"Optimizes for goals\", bestFor: [\"performance\"], complexity: 3, maxTokens: 2000 },\n formatter: { name: \"Formatter\", description: \"Formats output\", bestFor: [\"needs formatting\"], complexity: 1, maxTokens: 1500 },\n };\n }\n\n analyzePrompt(prompt: string): FullPromptAnalysis {\n const analysis: PromptAnalysis = {\n length: prompt.length,\n wordCount: prompt.split(/\\s+/).filter(Boolean).length,\n sentences: prompt.split(/[.!?]+/).filter(s => s.trim()).length,\n hasCode: /```|function|class|def|import|const|let|var/.test(prompt),\n hasTechnical: /API|database|algorithm|system|architecture|framework/i.test(prompt),\n hasCreative: /story|design|create|imagine|artistic|creative/i.test(prompt),\n hasExamples: /example|e\\.g\\.|for instance|such as/i.test(prompt),\n hasConstraints: /must|should|cannot|limit|maximum|minimum/i.test(prompt),\n hasQuestions: /\\?|how|what|when|where|why/.test(prompt),\n complexity: this.calculateComplexity(prompt),\n topics: this.extractTopics(prompt),\n intent: this.determineIntent(prompt),\n };\n\n const quality = this.ratePromptQuality(analysis);\n\n return { ...analysis, quality };\n }\n\n ratePromptQuality(analysis: PromptAnalysis): PromptQuality {\n let score = 100;\n const feedback: string[] = [];\n\n // Length penalties\n if (analysis.wordCount < 10) {\n score -= 30;\n feedback.push(\"Prompt is very short. Add more details and context for better results.\");\n } else if (analysis.wordCount < 25) {\n score -= 15;\n feedback.push(\"Consider elaborating on your request to provide more context.\");\n }\n if (analysis.wordCount > 300) {\n score -= 15;\n feedback.push(\"Prompt is quite long. Consider making it more concise.\");\n }\n\n // Clarity penalties\n if (analysis.hasQuestions) {\n score -= 10;\n feedback.push(\"Prompt contains questions. It's often better to state requirements directly.\");\n }\n if (analysis.sentences < 2 && analysis.wordCount > 20) {\n score -= 5;\n feedback.push(\"Breaking your prompt into multiple sentences can improve clarity.\");\n }\n\n // Specificity bonuses and penalties\n if (analysis.hasExamples) {\n score = Math.min(100, score + 15);\n } else {\n score -= 15;\n feedback.push(\"No examples found. Including an example of the desired output can significantly improve results.\");\n }\n\n if (analysis.hasConstraints) {\n score = Math.min(100, score + 10);\n } else {\n score -= 10;\n feedback.push(\"No constraints detected. Defining what to avoid or specific limits can make the output more precise.\");\n }\n\n if (analysis.intent === 'general') {\n score -= 20;\n feedback.push(\"The prompt's intent is unclear. Try using stronger action verbs like 'Create', 'Analyze', or 'Explain'.\");\n }\n\n if (feedback.length === 0) {\n feedback.push(\"This is a well-structured prompt!\");\n }\n\n return { score: Math.max(0, score), feedback };\n }\n\n calculateComplexity(prompt: string): number {\n let score = 0;\n const wordCount = prompt.split(/\\s+/).length;\n if (wordCount < 10) score += 1;\n else if (wordCount < 30) score += 3;\n else if (wordCount < 100) score += 5;\n else score += 7;\n \n if (/\\b(API|SDK|framework|architecture|algorithm)\\b/i.test(prompt)) score += 2;\n if (/\\b(async|await|promise|callback|recursion)\\b/i.test(prompt)) score += 1;\n \n const sentences = prompt.split(/[.!?]+/).filter(s => s.trim()).length;\n if (sentences > 3) score += 1;\n \n return Math.min(10, score);\n }\n\n extractTopics(prompt: string): string[] {\n const topics: string[] = [];\n if (/\\b(code|programming|software|development)\\b/i.test(prompt)) topics.push('technical');\n if (/\\b(API|REST|GraphQL|endpoint)\\b/i.test(prompt)) topics.push('api');\n if (/\\b(database|SQL|MongoDB|data)\\b/i.test(prompt)) topics.push('database');\n if (/\\b(UI|UX|interface|design|frontend)\\b/i.test(prompt)) topics.push('design');\n if (/\\b(business|market|strategy|sales)\\b/i.test(prompt)) topics.push('business');\n if (/\\b(customer|user|client|audience)\\b/i.test(prompt)) topics.push('user-focused');\n if (/\\b(story|narrative|creative|artistic)\\b/i.test(prompt)) topics.push('creative');\n if (/\\b(write|writing|content|copy)\\b/i.test(prompt)) topics.push('writing');\n if (/\\b(explain|teach|learn|understand)\\b/i.test(prompt)) topics.push('educational');\n if (/\\b(example|demonstrate|show|illustrate)\\b/i.test(prompt)) topics.push('demonstrative');\n return topics;\n }\n\n determineIntent(prompt: string): string {\n const lowerPrompt = prompt.toLowerCase();\n if (/\\b(create|build|make|develop|implement)\\b/.test(lowerPrompt)) return 'creation';\n if (/\\b(explain|describe|define|clarify)\\b/.test(lowerPrompt)) return 'explanation';\n if (/\\b(analyze|evaluate|compare|assess)\\b/.test(lowerPrompt)) return 'analysis';\n if (/\\b(fix|solve|debug|troubleshoot)\\b/.test(lowerPrompt)) return 'problem-solving';\n if (/\\b(optimize|improve|enhance|refactor)\\b/.test(lowerPrompt)) return 'optimization';\n if (/\\b(design|plan|architect|structure)\\b/.test(lowerPrompt)) return 'design';\n if (/\\b(test|validate|verify|check)\\b/.test(lowerPrompt)) return 'validation';\n return 'general';\n }\n\n selectWorkers(prompt: string, maxSteps: number = 10): WorkerSelection {\n const analysis = this.analyzePrompt(prompt);\n const selectedWorkers: string[] = [];\n const usedWorkers = new Set();\n \n if (analysis.wordCount < 5 || analysis.complexity < 3) {\n selectedWorkers.push('includer');\n usedWorkers.add('includer');\n } else if (analysis.wordCount > 100 || analysis.hasQuestions) {\n selectedWorkers.push('clarifier');\n usedWorkers.add('clarifier');\n }\n \n if (analysis.hasTechnical && !usedWorkers.has('technicalizer')) {\n selectedWorkers.push('technicalizer');\n usedWorkers.add('technicalizer');\n }\n if (analysis.hasCreative && !usedWorkers.has('creativizer')) {\n selectedWorkers.push('creativizer');\n usedWorkers.add('creativizer');\n }\n \n if (analysis.sentences > 3 && !usedWorkers.has('structurer')) {\n selectedWorkers.push('structurer');\n usedWorkers.add('structurer');\n }\n \n if (!analysis.hasExamples && analysis.complexity > 5 && !usedWorkers.has('exemplifier')) {\n selectedWorkers.push('exemplifier');\n usedWorkers.add('exemplifier');\n }\n \n if (analysis.topics.includes('technical') && !usedWorkers.has('contextualizer')) {\n selectedWorkers.push('contextualizer');\n usedWorkers.add('contextualizer');\n }\n \n if (!analysis.hasConstraints && analysis.intent === 'creation' && !usedWorkers.has('constrainer')) {\n selectedWorkers.push('constrainer');\n usedWorkers.add('constrainer');\n }\n \n if (analysis.intent === 'validation' || analysis.topics.includes('testing')) {\n if (!usedWorkers.has('validator')) {\n selectedWorkers.push('validator');\n usedWorkers.add('validator');\n }\n }\n \n if (analysis.intent === 'optimization' && !usedWorkers.has('optimizer')) {\n selectedWorkers.push('optimizer');\n usedWorkers.add('optimizer');\n }\n \n if (analysis.wordCount > 50 && !usedWorkers.has('condenser')) {\n selectedWorkers.push('condenser');\n usedWorkers.add('condenser');\n }\n \n if (analysis.topics.includes('api') || analysis.topics.includes('structured')) {\n if (!usedWorkers.has('formatter')) {\n selectedWorkers.push('formatter');\n usedWorkers.add('formatter');\n }\n }\n \n const finalWorkers = selectedWorkers.slice(0, maxSteps);\n \n if (finalWorkers.length < 3) {\n if (!usedWorkers.has('clarifier')) finalWorkers.push('clarifier');\n if (!usedWorkers.has('includer') && finalWorkers.length < 3) finalWorkers.push('includer');\n if (!usedWorkers.has('condenser') && finalWorkers.length < 3) finalWorkers.push('condenser');\n }\n \n return {\n workers: finalWorkers,\n analysis,\n reasoning: this.explainSelection(finalWorkers, analysis)\n };\n }\n\n explainSelection(workers: string[], analysis: PromptAnalysis): string[] {\n const reasons: string[] = [];\n \n workers.forEach(workerKey => {\n const workerInfo = this.workers[workerKey];\n let reason = `${workerInfo.name}: `;\n \n switch(workerKey) {\n case 'clarifier': reason += `Selected to clarify ambiguity (complexity: ${analysis.complexity}/10)`; break;\n case 'includer': reason += `Adding context (word count: ${analysis.wordCount})`; break;\n case 'condenser': reason += `Removing redundancy (${analysis.wordCount} words)`; break;\n case 'technicalizer': reason += `Adding technical specifications (technical content detected)`; break;\n case 'creativizer': reason += `Enhancing creative elements (creative intent: ${analysis.hasCreative})`; break;\n case 'structurer': reason += `Organizing content (${analysis.sentences} sentences)`; break;\n case 'exemplifier': reason += `Adding examples for clarity`; break;\n case 'contextualizer': reason += `Providing domain context (topics: ${analysis.topics.join(', ')})`; break;\n case 'constrainer': reason += `Adding boundaries and limits (intent: ${analysis.intent})`; break;\n case 'validator': reason += `Adding validation criteria`; break;\n case 'optimizer': reason += `Optimizing for efficiency`; break;\n case 'formatter': reason += `Formatting for specific output`; break;\n }\n \n reasons.push(reason);\n });\n \n return reasons;\n }\n\n getOptimalSteps(prompt: string): number {\n const analysis = this.analyzePrompt(prompt);\n if (analysis.complexity <= 3) return 3;\n if (analysis.complexity <= 5) return 5;\n if (analysis.complexity <= 7) return 7;\n return 10;\n }\n}\n\nexport default IntelligentRouter;\n","deleted","label",[170,152],"backend","permalink","https://www.val.town/x/toowired/Prompt_Improver/code/backend/intelligent_router.ts","extension","actionData","errors"]