63 lines
2.1 KiB
TypeScript
63 lines
2.1 KiB
TypeScript
import { z } from 'zod';
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import type { LlmClient } from '@/lib/ai/llm-client';
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import { GeminiLlmClient } from '@/lib/ai/gemini-client';
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import { clamp, nowIso, loadPhaseContainers, persistPhaseArtifacts } from '@/lib/server/projects';
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import type { MvpPlan } from '@/lib/types/mvp';
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const MvpPlanSchema = z.object({
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projectId: z.string(),
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coreFlows: z.array(z.string()).default([]),
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coreFeatures: z.array(z.string()).default([]),
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supportingFeatures: z.array(z.string()).default([]),
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outOfScope: z.array(z.string()).default([]),
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technicalTasks: z.array(z.string()).default([]),
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blockers: z.array(z.string()).default([]),
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overallConfidence: z.number().min(0).max(1),
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});
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export async function runMvpPlanning(projectId: string, llmClient?: LlmClient): Promise<MvpPlan> {
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const { phaseData } = await loadPhaseContainers(projectId);
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const canonical = phaseData.canonicalProductModel;
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if (!canonical) {
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throw new Error('Canonical product model missing. Run buildCanonicalProductModel first.');
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}
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const llm = llmClient ?? new GeminiLlmClient();
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const systemPrompt =
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'You are an expert SaaS product manager. Given the canonical product model, produce the smallest sellable MVP plan as strict JSON.';
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const plan = await llm.structuredCall<MvpPlan>({
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model: 'gemini',
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systemPrompt,
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messages: [
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{
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role: 'user',
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content: [
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'Canonical product model JSON:',
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'```json',
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JSON.stringify(canonical, null, 2),
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'```',
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'Respond ONLY with JSON that matches the required schema.',
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].join('\n'),
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},
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],
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schema: MvpPlanSchema,
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temperature: 0.2,
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});
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await persistPhaseArtifacts(projectId, (phaseData, phaseScores, phaseHistory) => {
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phaseData.mvpPlan = plan;
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phaseScores.mvp = {
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overallCompletion: clamp(plan.coreFeatures.length ? 0.8 : 0.5),
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overallConfidence: plan.overallConfidence,
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updatedAt: nowIso(),
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};
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phaseHistory.push({ phase: 'mvp', status: 'completed', timestamp: nowIso() });
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return { phaseData, phaseScores, phaseHistory, nextPhase: 'mvp_ready' };
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});
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return plan;
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}
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