VIBN Frontend for Coolify deployment

lib/ai/chat-extraction-types.ts

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+import { z } from 'zod';
+
+const evidenceArray = z.array(z.string()).default([]);
+const confidenceValue = z.number().min(0).max(1).default(0);
+const completionScore = z.number().min(0).max(1).default(0);
+
+const defaultWeightedString = {
+  description: null as string | null,
+  confidence: 0,
+  evidence: [] as string[],
+};
+
+const weightedStringField = z
+  .object({
+    description: z.union([z.string(), z.null()]).default(null),
+    confidence: confidenceValue.default(0),
+    evidence: evidenceArray.default([]),
+  })
+  .default(defaultWeightedString);
+
+const weightedListItem = z.object({
+  id: z.string(),
+  description: z.string(),
+  confidence: confidenceValue,
+  evidence: evidenceArray,
+});
+
+const stageEnum = z.enum([
+  'idea',
+  'prototype',
+  'mvp_in_progress',
+  'live_beta',
+  'live_paid',
+  'unknown',
+]);
+
+const severityEnum = z.enum(['low', 'medium', 'high', 'unknown']);
+const frequencyEnum = z.enum(['rare', 'occasional', 'frequent', 'constant', 'unknown']);
+const competitorTypeEnum = z.enum(['direct', 'indirect', 'alternative', 'unknown']);
+const relatedAreaEnum = z.enum(['product', 'tech', 'market', 'business_model', 'other']);
+const priorityEnum = z.enum(['high', 'medium', 'low']);
+
+export const ChatExtractionSchema = z.object({
+  project_summary: z.object({
+    working_title: z.union([z.string(), z.null()]).default(null),
+    one_liner: z.union([z.string(), z.null()]).default(null),
+    stage: stageEnum.default('unknown'),
+    overall_confidence: confidenceValue,
+    evidence: evidenceArray,
+  }),
+  product_vision: z.object({
+    problem_statement: weightedStringField,
+    target_outcome: weightedStringField,
+    founder_intent: weightedStringField,
+    completion_score: completionScore,
+  }),
+  target_users: z.object({
+    primary_segment: weightedStringField,
+    segments: z
+      .array(
+        z.object({
+          id: z.string(),
+          description: z.string(),
+          jobs_to_be_done: z.array(z.string()).default([]),
+          environment: z.union([z.string(), z.null()]),
+          confidence: confidenceValue,
+          evidence: evidenceArray,
+        }),
+      )
+      .default([]),
+    completion_score: completionScore,
+  }),
+  problems_and_pains: z.object({
+    problems: z
+      .array(
+        z.object({
+          id: z.string(),
+          description: z.string(),
+          severity: severityEnum,
+          frequency: frequencyEnum,
+          confidence: confidenceValue,
+          evidence: evidenceArray,
+        }),
+      )
+      .default([]),
+    completion_score: completionScore,
+  }),
+  solution_and_features: z.object({
+    core_solution: weightedStringField,
+    core_features: z
+      .array(
+        z.object({
+          id: z.string(),
+          name: z.string(),
+          description: z.string(),
+          is_must_have_for_v1: z.boolean(),
+          confidence: confidenceValue,
+          evidence: evidenceArray,
+        }),
+      )
+      .default([]),
+    nice_to_have_features: z
+      .array(
+        z.object({
+          id: z.string(),
+          name: z.string(),
+          description: z.string(),
+          confidence: confidenceValue,
+          evidence: evidenceArray,
+        }),
+      )
+      .default([]),
+    completion_score: completionScore,
+  }),
+  market_and_competition: z.object({
+    market_category: weightedStringField,
+    competitors: z
+      .array(
+        z.object({
+          id: z.string(),
+          name: z.string(),
+          description: z.string(),
+          type: competitorTypeEnum,
+          confidence: confidenceValue,
+          evidence: evidenceArray,
+        }),
+      )
+      .default([]),
+    differentiation_points: weightedListItem.array().default([]),
+    completion_score: completionScore,
+  }),
+  tech_and_constraints: z.object({
+    stack_mentions: weightedListItem.array().default([]),
+    constraints: weightedListItem.array().default([]),
+    completion_score: completionScore,
+  }),
+  execution_status: z.object({
+    current_stage: weightedStringField,
+    work_done: weightedListItem.array().default([]),
+    work_in_progress: weightedListItem.array().default([]),
+    blocked_items: weightedListItem.array().default([]),
+    completion_score: completionScore,
+  }),
+  goals_and_success: z.object({
+    short_term_goals: weightedListItem.array().default([]),
+    long_term_goals: weightedListItem.array().default([]),
+    success_criteria: weightedListItem.array().default([]),
+    completion_score: completionScore,
+  }),
+  unknowns_and_questions: z.object({
+    unknowns: z
+      .array(
+        z.object({
+          id: z.string(),
+          description: z.string(),
+          related_area: relatedAreaEnum,
+          evidence: evidenceArray,
+          confidence: confidenceValue,
+        }),
+      )
+      .default([]),
+    questions_to_ask_user: z
+      .array(
+        z.object({
+          id: z.string(),
+          question: z.string(),
+          priority: priorityEnum,
+        }),
+      )
+      .default([]),
+  }),
+  summary_scores: z.object({
+    overall_completion: completionScore,
+    overall_confidence: confidenceValue,
+  }),
+});
+
+export type ChatExtractionData = z.infer<typeof ChatExtractionSchema>;
+
+