73a8314ed9
Major refactoring of worksheet parsing to use centralized state management: New architecture: - WorksheetParsingContext: React context provider for parsing state - state-machine.ts: Typed reducer with actions for streaming lifecycle - sse-parser.ts: Shared SSE parsing utility for OpenAI Responses API - usePartialJsonParser.ts: Progressive JSON extraction during streaming Streaming UI improvements: - ParsingProgressOverlay: Dark overlay on photo tile during parsing - ParsingProgressPanel: Collapsible reasoning text panel - ProgressiveHighlightOverlay: Problem boxes light up as LLM parses - New streaming API routes: /parse/stream and /parse-selected/stream Bug fixes during testing: - Fix TypeScript error: cast event.response for id access in sse-parser - Fix reparse reasoning display: preserve "processing" status for reparse - Fix concurrent parsing: revert previous attachment status when switching - Fix problem count: track dispatched problems to prevent duplicates Components updated to use context: - SummaryClient: Wrapped with WorksheetParsingProvider - OfflineWorkSection: Uses context instead of local streaming state - PhotoViewerEditor: Uses context for coordinated parsing 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
102 lines
2.7 KiB
TypeScript
102 lines
2.7 KiB
TypeScript
#!/usr/bin/env tsx
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/**
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* Test script for GPT-5 worksheet grading
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*
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* Usage:
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* npx tsx scripts/testGrading.ts path/to/worksheet.jpg
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*
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* This will:
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* 1. Call GPT-5 vision API to grade the worksheet
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* 2. Validate the response
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* 3. Print the results (score, feedback, suggested step)
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*/
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import { gradeWorksheetWithVision } from "../src/lib/ai/gradeWorksheet";
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import { join } from "path";
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async function main() {
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const args = process.argv.slice(2);
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if (args.length === 0) {
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console.error(
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"Usage: npx tsx scripts/testGrading.ts path/to/worksheet.jpg",
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);
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console.error("\nExample:");
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console.error(
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" npx tsx scripts/testGrading.ts data/uploads/test-worksheet.jpg",
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);
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process.exit(1);
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}
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const imagePath = args[0];
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const absolutePath = imagePath.startsWith("/")
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? imagePath
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: join(process.cwd(), imagePath);
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console.log("🔍 Testing GPT-5 Worksheet Grading");
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console.log("━".repeat(60));
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console.log(`Image: ${absolutePath}`);
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console.log("━".repeat(60));
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console.log();
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try {
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console.log("📤 Calling GPT-5 vision API...");
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const startTime = Date.now();
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const result = await gradeWorksheetWithVision(absolutePath);
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const duration = ((Date.now() - startTime) / 1000).toFixed(1);
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console.log(`✅ Grading complete in ${duration}s`);
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console.log();
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// Print results
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console.log("📊 GRADING RESULTS");
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console.log("━".repeat(60));
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console.log(
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`Score: ${result.correctCount}/${result.totalProblems} (${(result.accuracy * 100).toFixed(1)}%)`,
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);
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console.log();
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console.log("🤖 AI Feedback:");
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console.log(result.feedback);
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console.log();
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console.log("🏷️ Error Patterns:");
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if (result.errorPatterns.length === 0) {
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console.log(" None detected");
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} else {
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result.errorPatterns.forEach((pattern) => {
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console.log(` • ${pattern}`);
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});
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}
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console.log();
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console.log("📈 Progression:");
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console.log(` Current estimate: ${result.currentStepEstimate}`);
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console.log(` Suggested step: ${result.suggestedStepId}`);
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console.log();
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console.log("🧮 Problem Breakdown:");
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console.log("━".repeat(60));
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result.problems.forEach((p) => {
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const status = p.isCorrect ? "✓" : "✗";
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const answer = p.studentAnswer !== null ? p.studentAnswer : "blank";
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console.log(
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`#${p.index + 1}: ${p.operandA} + ${p.operandB} = ${p.correctAnswer} ` +
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`(student: ${answer}) ${status}`,
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);
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});
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console.log();
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console.log("💭 AI Reasoning:");
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console.log(result.reasoning);
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console.log();
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} catch (error) {
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console.error("❌ Grading failed:");
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console.error(error);
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process.exit(1);
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}
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}
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main();
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