Fix AI assignment returning nothing: cap tokens, optimize prompt, show errors
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- Cap maxTokens at 12000 (was unlimited dynamic calc that could exceed model limits) - Replace massive EXISTING array with compact CURRENT_JUROR_LOAD counts and ALREADY_ASSIGNED per-project map (keeps prompt small across batches) - Add coverage gap-filler: algorithmically fills projects below required reviews - Show error state inline on page when AI fails (red banner with message) - Add server-side logging for debugging assignment flow - Reduce batch size to 10 projects Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -186,7 +186,8 @@ export default function RoundDetailPage() {
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})
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},
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onError: (err) => {
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toast.error(`AI generation failed: ${err.message}`)
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toast.error(`AI generation failed: ${err.message}`, { duration: 15000 })
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console.error('[AI Assignment]', err)
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},
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})
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const [exportOpen, setExportOpen] = useState(false)
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@@ -1725,6 +1726,19 @@ export default function RoundDetailPage() {
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</div>
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</div>
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)}
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{aiAssignmentMutation.error && !aiAssignmentMutation.isPending && (
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<div className="flex items-center gap-3 p-3 rounded-lg bg-red-50 border border-red-200 dark:bg-red-950/20 dark:border-red-800">
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<AlertTriangle className="h-5 w-5 text-red-600 shrink-0" />
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<div className="flex-1">
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<p className="text-sm font-medium text-red-800 dark:text-red-200">
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AI generation failed
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</p>
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<p className="text-xs text-red-600 dark:text-red-400">
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{aiAssignmentMutation.error.message}
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</p>
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</div>
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</div>
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)}
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{aiAssignmentMutation.data && !aiAssignmentMutation.isPending && (
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<div className="flex items-center gap-3 p-3 rounded-lg bg-emerald-50 border border-emerald-200 dark:bg-emerald-950/20 dark:border-emerald-800">
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<CheckCircle2 className="h-5 w-5 text-emerald-600 shrink-0" />
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@@ -152,6 +152,7 @@ export const roundAssignmentRouter = router({
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}
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// Call AI service
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console.log(`[AI Assignment Router] Starting for ${projects.length} projects, ${jurors.length} jurors, ${input.requiredReviews} reviews/project, max ${maxPerJuror}/juror`)
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const result = await generateAIAssignments(
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jurors,
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projects,
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@@ -159,6 +160,7 @@ export const roundAssignmentRouter = router({
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ctx.user.id,
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input.roundId,
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)
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console.log(`[AI Assignment Router] Got ${result.suggestions.length} suggestions, success=${result.success}, fallback=${result.fallbackUsed}`)
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// Filter out COI pairs and already-assigned pairs
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const existingPairSet = new Set(existingAssignments.map((a) => `${a.userId}:${a.projectId}`))
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@@ -173,9 +173,9 @@ async function processAssignmentBatch(
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try {
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// Calculate maxTokens based on expected assignments
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// ~150 tokens per assignment JSON object
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// ~150 tokens per assignment JSON object, capped at 12000
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const expectedAssignments = batchProjects.length * constraints.requiredReviewsPerProject
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const estimatedTokens = Math.max(4000, expectedAssignments * 200 + 500)
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const estimatedTokens = Math.min(12000, Math.max(4000, expectedAssignments * 200 + 500))
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const params = buildCompletionParams(model, {
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messages: [
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@@ -359,13 +359,33 @@ function buildBatchPrompt(
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const expectedTotal = projects.length * constraints.requiredReviewsPerProject
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// Instead of full existing assignment list, send per-juror current load counts
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// This keeps the prompt shorter as batches accumulate
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const jurorCurrentLoad: Record<string, number> = {}
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for (const a of constraints.existingAssignments) {
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const anonId = jurorIdMap.get(a.jurorId)
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if (anonId) jurorCurrentLoad[anonId] = (jurorCurrentLoad[anonId] || 0) + 1
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}
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// Also track which projects in this batch already have assignments
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const projectExistingReviewers: Record<string, string[]> = {}
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for (const a of constraints.existingAssignments) {
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const anonProjectId = projectIdMap.get(a.projectId)
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const anonJurorId = jurorIdMap.get(a.jurorId)
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if (anonProjectId && anonJurorId) {
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if (!projectExistingReviewers[anonProjectId]) projectExistingReviewers[anonProjectId] = []
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projectExistingReviewers[anonProjectId].push(anonJurorId)
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}
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}
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return `JURORS: ${JSON.stringify(jurors)}
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PROJECTS: ${JSON.stringify(projects)}
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REVIEWS_PER_PROJECT: ${constraints.requiredReviewsPerProject} (each project MUST get exactly ${constraints.requiredReviewsPerProject} different jurors)
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MAX_PER_JUROR: ${constraints.maxAssignmentsPerJuror || 'unlimited'} (HARD LIMIT — never exceed)${jurorLimitsStr}${targetStr}
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EXISTING: ${JSON.stringify(anonymousExisting)}
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EXPECTED_OUTPUT_SIZE: approximately ${expectedTotal} assignment objects (${projects.length} projects × ${constraints.requiredReviewsPerProject} reviewers each)
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IMPORTANT: Every project must appear ${constraints.requiredReviewsPerProject} times with ${constraints.requiredReviewsPerProject} DIFFERENT juror_ids. Pick the least-loaded jurors first. Never exceed a juror's max.
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CURRENT_JUROR_LOAD: ${JSON.stringify(jurorCurrentLoad)} (add these to currentAssignmentCount to get true total)
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ALREADY_ASSIGNED: ${JSON.stringify(projectExistingReviewers)} (do NOT assign these juror-project pairs again)
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EXPECTED_OUTPUT: ${expectedTotal} assignment objects (${projects.length} projects × ${constraints.requiredReviewsPerProject} reviewers)
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IMPORTANT: Every project must appear ${constraints.requiredReviewsPerProject} times with ${constraints.requiredReviewsPerProject} DIFFERENT juror_ids. Pick the least-loaded jurors first.
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Return JSON: {"assignments": [...]}`
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}
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