mirror of
https://github.com/velocitatem/cvfs.git
synced 2026-05-31 08:43:37 +00:00
feat: NLP patch insights + standalone demo mode
- dlib/ai/insights.py: pure-Python NLP analysis that correlates accepted AI suggestion operations/keywords/sections with submission outcomes (pending_review / published = positive, archived = negative) - Backend: GET /api/v1/insights route + service + Pydantic schema - Frontend: InsightsPanel component with bar charts for operation impact, section impact, and keyword signal lift scores - Insights tab added to the version panel; compact preview on doc overview - NEXT_PUBLIC_DEMO=true makes the webapp fully standalone: loads DEMO_DOCUMENTS / DEMO_SUBMISSIONS / DEMO_INSIGHTS from demo-data.ts, disables all mutating actions, shows a DEMO badge in the top bar - apps/webapp/public/demo-cv.docx: static dummy CV (Alex Rivera) for demo - scripts/gen_demo_cv.py: script to regenerate the demo DOCX - .env.example: document NEXT_PUBLIC_DEMO flag https://claude.ai/code/session_01LWxu2qrwY6BRjUFXXn7NiM
This commit is contained in:
Claude
BIN
apps/webapp/public/demo-cv.docx
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apps/webapp/public/demo-cv.docx
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apps/webapp/src/app/dashboard/demo-data.ts
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apps/webapp/src/app/dashboard/demo-data.ts
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@@ -0,0 +1,165 @@
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import type { Document, Submission, InsightsResult } from '@/libs/api';
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const NOW = new Date().toISOString();
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const D = (daysAgo: number) => new Date(Date.now() - daysAgo * 86_400_000).toISOString();
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const ROOT_VERSION_ID = 'demo-v1';
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const ML_VERSION_ID = 'demo-v2';
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const BACKEND_VERSION_ID = 'demo-v3';
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export const DEMO_DOC_ID = 'demo-doc-1';
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export const DEMO_DOCUMENTS: Document[] = [
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{
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id: DEMO_DOC_ID,
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title: 'Alex Rivera — Software Engineer',
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description: 'Main CV, ATS-safe baseline',
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owner_id: 'demo-user',
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root_version_id: ROOT_VERSION_ID,
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created_at: D(45),
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updated_at: D(3),
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versions: [
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{
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id: ROOT_VERSION_ID,
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branch_name: 'root',
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version_label: 'v1.0 baseline',
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parent_version_id: null,
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structured_blocks: [
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{ path: 'heading[1]', block_type: 'heading', text: 'Alex Rivera', keywords: [] },
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{ path: 'summary[1]', block_type: 'summary', text: 'Software engineer with 5 years of experience building distributed systems and ML pipelines at scale.', keywords: ['distributed', 'systems', 'machine', 'learning'] },
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{ path: 'heading[2]', block_type: 'heading', text: 'Experience', keywords: [] },
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{ path: 'bullet[1]', block_type: 'bullet', text: 'Led migration of monolithic data pipeline to distributed microservices, reducing p99 latency by 40%.', keywords: ['distributed', 'microservices', 'latency', 'pipeline'] },
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{ path: 'bullet[2]', block_type: 'bullet', text: 'Designed feature flag system used by 50+ engineers across 3 teams.', keywords: ['system', 'design', 'engineers'] },
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{ path: 'heading[3]', block_type: 'heading', text: 'Skills', keywords: [] },
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{ path: 'skills[1]', block_type: 'skills', text: 'Python, Go, TypeScript, SQL, Kubernetes, AWS, PyTorch', keywords: ['python', 'go', 'typescript', 'pytorch', 'kubernetes'] },
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],
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artifact_docx_key: 'demo/demo-cv.docx',
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patches: [],
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public_assets: [],
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created_at: D(45),
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updated_at: D(45),
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},
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{
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id: ML_VERSION_ID,
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branch_name: 'ml-engineer',
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version_label: 'ML-focused variant',
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parent_version_id: ROOT_VERSION_ID,
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structured_blocks: [
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{ path: 'heading[1]', block_type: 'heading', text: 'Alex Rivera', keywords: [] },
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{ path: 'summary[1]', block_type: 'summary', text: 'ML engineer specialising in large-scale PyTorch training pipelines, distributed inference, and production-grade MLOps.', keywords: ['pytorch', 'distributed', 'mlops', 'inference'] },
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{ path: 'heading[2]', block_type: 'heading', text: 'Experience', keywords: [] },
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{ path: 'bullet[1]', block_type: 'bullet', text: 'Contributed PyTorch anomaly detection model achieving 92% precision on production traffic at 2M events/day.', keywords: ['pytorch', 'machine learning', 'production', 'precision'] },
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{ path: 'bullet[2]', block_type: 'bullet', text: 'Built streaming data ingestion system (Kafka + Flink) powering real-time ML feature store.', keywords: ['kafka', 'flink', 'streaming', 'feature store'] },
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{ path: 'heading[3]', block_type: 'heading', text: 'Skills', keywords: [] },
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{ path: 'skills[1]', block_type: 'skills', text: 'PyTorch, Python, Go, Kubernetes, Spark, dbt, AWS SageMaker', keywords: ['pytorch', 'python', 'kubernetes', 'spark', 'sagemaker'] },
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],
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artifact_docx_key: 'demo/demo-cv.docx',
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patches: [
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{ id: 'dp1', target_path: 'summary[1]', operation: 'replace_text', old_value: 'Software engineer…', new_value: 'ML engineer specialising…', created_at: D(30) },
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{ id: 'dp2', target_path: 'skills[1]', operation: 'boost_keyword', old_value: null, new_value: 'PyTorch', created_at: D(30) },
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],
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public_assets: [{
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id: 'demo-asset-1', slug: 'alex-ml', artifact_key: 'public/alex-ml.docx',
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is_public: true, url: '/demo-cv.docx', version_id: ML_VERSION_ID, submission_id: null, created_at: D(20),
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}],
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created_at: D(30),
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updated_at: D(3),
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},
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{
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id: BACKEND_VERSION_ID,
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branch_name: 'backend-engineer',
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version_label: 'Backend-focused variant',
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parent_version_id: ROOT_VERSION_ID,
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structured_blocks: [
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{ path: 'heading[1]', block_type: 'heading', text: 'Alex Rivera', keywords: [] },
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{ path: 'summary[1]', block_type: 'summary', text: 'Backend engineer focused on high-throughput API design, distributed systems, and reliability engineering.', keywords: ['backend', 'api', 'distributed', 'reliability'] },
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{ path: 'bullet[1]', block_type: 'bullet', text: 'Led migration to microservices, reducing p99 latency by 40% under 10k RPS sustained load.', keywords: ['microservices', 'latency', 'rps', 'distributed'] },
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{ path: 'skills[1]', block_type: 'skills', text: 'Go, Python, PostgreSQL, Redis, gRPC, Kubernetes, AWS', keywords: ['go', 'postgresql', 'redis', 'grpc', 'kubernetes'] },
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],
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artifact_docx_key: 'demo/demo-cv.docx',
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patches: [
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{ id: 'dp3', target_path: 'summary[1]', operation: 'replace_text', old_value: 'Software engineer…', new_value: 'Backend engineer…', created_at: D(25) },
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],
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public_assets: [],
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created_at: D(25),
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updated_at: D(10),
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},
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],
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},
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];
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export const DEMO_SUBMISSIONS: Submission[] = [
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{
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id: 'ds1', version_id: ML_VERSION_ID, company_name: 'Anthropic', role_title: 'ML Research Engineer',
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job_url: null, job_description: null, status: 'pending_review', created_at: D(18),
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suggestions: [
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{ id: 's1', target_path: 'summary[1]', operation: 'boost_keyword', proposed_text: 'constitutional ai', rationale: 'Highlight alignment research experience', accepted: true, metadata_json: { confidence: 0.82 } },
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{ id: 's2', target_path: 'bullet[1]', operation: 'replace_text', proposed_text: 'Built distributed PyTorch training pipeline handling constitutional AI fine-tuning at scale.', rationale: 'Align with Anthropic stack', accepted: true, metadata_json: { confidence: 0.74 } },
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],
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},
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{
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id: 'ds2', version_id: ML_VERSION_ID, company_name: 'Google DeepMind', role_title: 'Senior ML Engineer',
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job_url: null, job_description: null, status: 'pending_review', created_at: D(14),
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suggestions: [
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{ id: 's3', target_path: 'skills[1]', operation: 'boost_keyword', proposed_text: 'JAX', rationale: 'DeepMind uses JAX heavily', accepted: true, metadata_json: { confidence: 0.71 } },
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{ id: 's4', target_path: 'bullet[2]', operation: 'replace_text', proposed_text: 'Built large-scale streaming pipeline underpinning real-time feature store for JAX model serving.', rationale: 'Add JAX context', accepted: true, metadata_json: { confidence: 0.68 } },
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],
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},
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{
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id: 'ds3', version_id: ML_VERSION_ID, company_name: 'OpenAI', role_title: 'Research Engineer',
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job_url: null, job_description: null, status: 'published', created_at: D(10),
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suggestions: [
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{ id: 's5', target_path: 'summary[1]', operation: 'replace_text', proposed_text: 'ML engineer with track record in large-scale training infrastructure and RLHF pipelines.', rationale: 'OpenAI focus on RLHF', accepted: true, metadata_json: { confidence: 0.77 } },
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],
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},
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{
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id: 'ds4', version_id: ML_VERSION_ID, company_name: 'Meta AI', role_title: 'ML Infrastructure Engineer',
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job_url: null, job_description: null, status: 'archived', created_at: D(22),
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suggestions: [
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{ id: 's6', target_path: 'bullet[1]', operation: 'boost_keyword', proposed_text: 'PyTorch', rationale: 'Meta maintains PyTorch', accepted: true, metadata_json: { confidence: 0.55 } },
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{ id: 's7', target_path: 'summary[1]', operation: 'suppress_block', proposed_text: null, rationale: 'Summary too generic', accepted: false, metadata_json: { confidence: 0.3 } },
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],
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},
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{
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id: 'ds5', version_id: BACKEND_VERSION_ID, company_name: 'Stripe', role_title: 'Senior Backend Engineer',
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job_url: null, job_description: null, status: 'pending_review', created_at: D(8),
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suggestions: [
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{ id: 's8', target_path: 'bullet[1]', operation: 'replace_text', proposed_text: 'Led migration to microservices achieving 99.99% uptime across Stripe-scale payment processing.', rationale: 'Emphasise reliability', accepted: true, metadata_json: { confidence: 0.79 } },
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],
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},
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{
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id: 'ds6', version_id: BACKEND_VERSION_ID, company_name: 'Cloudflare', role_title: 'Staff Engineer',
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job_url: null, job_description: null, status: 'archived', created_at: D(20),
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suggestions: [
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{ id: 's9', target_path: 'skills[1]', operation: 'boost_keyword', proposed_text: 'Rust', rationale: 'Cloudflare uses Rust', accepted: true, metadata_json: { confidence: 0.4 } },
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],
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},
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];
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export const DEMO_INSIGHTS: InsightsResult = {
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total_submissions: 6,
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positive_count: 4,
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positive_rate: 0.667,
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has_data: true,
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operation_impact: [
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{ operation: 'replace_text', total: 5, positive: 4, rate: 0.8 },
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{ operation: 'boost_keyword', total: 5, positive: 3, rate: 0.6 },
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{ operation: 'suppress_block', total: 1, positive: 0, rate: 0.0 },
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],
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top_positive_keywords: [
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{ keyword: 'pytorch', positive_count: 4, negative_count: 1, lift: 4.0 },
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{ keyword: 'distributed', positive_count: 3, negative_count: 0, lift: 3.0 },
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{ keyword: 'pipeline', positive_count: 3, negative_count: 1, lift: 3.0 },
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{ keyword: 'scale', positive_count: 3, negative_count: 1, lift: 3.0 },
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{ keyword: 'reliability', positive_count: 2, negative_count: 0, lift: 2.0 },
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{ keyword: 'inference', positive_count: 2, negative_count: 0, lift: 2.0 },
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],
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top_negative_keywords: [
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{ keyword: 'generic', positive_count: 0, negative_count: 2, lift: 0.0 },
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{ keyword: 'suppress', positive_count: 0, negative_count: 1, lift: 0.0 },
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],
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section_impact: [
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{ section: 'summary', positive_rate: 0.83, count: 6 },
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{ section: 'bullet', positive_rate: 0.75, count: 4 },
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{ section: 'skills', positive_rate: 0.5, count: 4 },
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],
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};
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@@ -3,12 +3,15 @@
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import { useEffect, useRef, useState } from 'react';
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import CVTree from '@/components/cv/CVTree';
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import DiffViewer from '@/components/cv/DiffViewer';
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import InsightsPanel from '@/components/cv/InsightsPanel';
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import Link from 'next/link';
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import {
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appendPatches,
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createBranch, createSubmission, deleteDocument, deleteVersion,
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Document, downloadVersionUrl,
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fetchDocuments, fetchSubmissions, fetchPublicAssetAnalytics, getPublicPdfUrl,
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fetchDocuments, fetchInsights, fetchSubmissions, fetchPublicAssetAnalytics, getPublicPdfUrl,
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InsightsResult,
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IS_DEMO,
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publishVersion, PublicAsset, PublicAssetAnalytics,
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requestAiSuggestions,
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Submission,
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@@ -20,6 +23,9 @@ import {
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uploadDocument,
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Version,
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} from '@/libs/api';
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import {
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DEMO_DOCUMENTS, DEMO_DOC_ID, DEMO_INSIGHTS, DEMO_SUBMISSIONS,
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} from './demo-data';
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// ── helpers ───────────────────────────────────────────────────────────────────
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@@ -548,7 +554,7 @@ function SubmissionsTab({
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// ── main dashboard ────────────────────────────────────────────────────────────
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type Modal = 'upload' | 'branch' | 'submission' | 'publish' | null;
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type Tab = 'content' | 'patches' | 'submissions';
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type Tab = 'content' | 'patches' | 'submissions' | 'insights';
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export default function Dashboard() {
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const [docs, setDocs] = useState<Document[]>([]);
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@@ -568,8 +574,17 @@ export default function Dashboard() {
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const [docHovered, setDocHovered] = useState<string | null>(null);
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const [applyLoading, setApplyLoading] = useState(false);
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const [applyError, setApplyError] = useState('');
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const [insights, setInsights] = useState<InsightsResult | null>(null);
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useEffect(() => {
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if (IS_DEMO) {
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setDocs(DEMO_DOCUMENTS);
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setAllSubmissions(DEMO_SUBMISSIONS);
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setSelectedDocId(DEMO_DOC_ID);
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setInsights(DEMO_INSIGHTS);
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setLoading(false);
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return;
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}
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Promise.all([fetchDocuments(), fetchSubmissions().catch(() => [])])
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.then(([d, allSubs]) => {
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setDocs(d);
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@@ -580,6 +595,11 @@ export default function Dashboard() {
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.finally(() => setLoading(false));
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}, []);
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useEffect(() => {
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if (IS_DEMO || !selectedDocId) return;
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fetchInsights().then(setInsights).catch(() => setInsights(null));
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}, [selectedDocId]);
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useEffect(() => {
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setPendingEdits(new Map());
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setApplyError('');
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@@ -691,6 +711,7 @@ export default function Dashboard() {
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};
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const handleDeleteDoc = async (docId: string) => {
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if (IS_DEMO) return;
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if (!confirm('Delete this CV and all its branches? This cannot be undone.')) return;
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try {
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await deleteDocument(docId);
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@@ -706,6 +727,7 @@ export default function Dashboard() {
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};
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const handleDeleteVersion = async (versionId: string) => {
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if (IS_DEMO) return;
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const hasChildren = selectedDoc?.versions.some(v => v.parent_version_id === versionId);
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const msg = hasChildren
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? 'Delete this branch and all its sub-branches? This cannot be undone.'
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@@ -758,12 +780,21 @@ export default function Dashboard() {
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</Link>
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</div>
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<div style={{ display: 'flex', gap: 8, alignItems: 'center' }}>
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<button className="btn btn-primary" style={{ padding: '4px 10px', fontSize: 12 }} onClick={() => setModal('upload')}>
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+ Upload CV
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</button>
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<button className="btn btn-ghost" style={{ padding: '4px 10px', fontSize: 12 }} onClick={logout}>
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Sign out
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</button>
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{IS_DEMO && (
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<span style={{ fontSize: 11, padding: '2px 10px', background: '#7c3aed', color: '#fff', borderRadius: 9999, fontWeight: 600, letterSpacing: '0.04em' }}>
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DEMO
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</span>
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)}
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{!IS_DEMO && (
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<button className="btn btn-primary" style={{ padding: '4px 10px', fontSize: 12 }} onClick={() => setModal('upload')}>
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+ Upload CV
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</button>
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)}
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{!IS_DEMO && (
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<button className="btn btn-ghost" style={{ padding: '4px 10px', fontSize: 12 }} onClick={logout}>
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Sign out
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</button>
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)}
|
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</div>
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</div>
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@@ -900,6 +931,13 @@ export default function Dashboard() {
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onSelect={selectVersion}
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/>
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</div>
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||||
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{insights?.has_data && (
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<div style={{ marginTop: 10 }}>
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<div className="label" style={{ marginBottom: 8 }}>NLP insights</div>
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<InsightsPanel data={insights} />
|
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</div>
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||||
)}
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</div>
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) : (
|
||||
<div style={{ paddingTop: 60, textAlign: 'center', color: 'var(--text-faint)', fontSize: 13 }}>
|
||||
@@ -938,10 +976,15 @@ export default function Dashboard() {
|
||||
|
||||
{/* action buttons */}
|
||||
<div className="action-buttons">
|
||||
<button className="btn btn-ghost" onClick={() => setModal('branch')}>Branch</button>
|
||||
<button className="btn btn-ghost" onClick={() => { setModal('submission'); }}>Submit</button>
|
||||
<button className="btn btn-ghost" onClick={() => setModal('publish')}>Publish</button>
|
||||
{selectedVersion.artifact_docx_key && selectedDoc && (
|
||||
{!IS_DEMO && <button className="btn btn-ghost" onClick={() => setModal('branch')}>Branch</button>}
|
||||
{!IS_DEMO && <button className="btn btn-ghost" onClick={() => { setModal('submission'); }}>Submit</button>}
|
||||
{!IS_DEMO && <button className="btn btn-ghost" onClick={() => setModal('publish')}>Publish</button>}
|
||||
{IS_DEMO && (
|
||||
<a href="/demo-cv.docx" download="alex-rivera-cv.docx" className="btn btn-ghost">
|
||||
↓ DOCX
|
||||
</a>
|
||||
)}
|
||||
{!IS_DEMO && selectedVersion.artifact_docx_key && selectedDoc && (
|
||||
<a href={downloadVersionUrl(selectedDoc.id, selectedVersion.id)} download className="btn btn-ghost">
|
||||
↓ DOCX
|
||||
</a>
|
||||
@@ -1044,7 +1087,7 @@ export default function Dashboard() {
|
||||
|
||||
{/* tabs */}
|
||||
<div style={{ display: 'flex', gap: 0, borderBottom: '1px solid var(--border)', overflowX: 'auto' }}>
|
||||
{(['content', 'patches', 'submissions'] as Tab[]).map(t => (
|
||||
{(['content', 'patches', 'submissions', 'insights'] as Tab[]).map(t => (
|
||||
<button
|
||||
key={t}
|
||||
onClick={() => setActiveTab(t)}
|
||||
@@ -1076,13 +1119,21 @@ export default function Dashboard() {
|
||||
)}
|
||||
{activeTab === 'submissions' && (
|
||||
<SubmissionsTab
|
||||
submissions={submissions}
|
||||
submissions={IS_DEMO
|
||||
? DEMO_SUBMISSIONS.filter(s => {
|
||||
const doc = DEMO_DOCUMENTS.find(d => d.id === selectedDocId);
|
||||
return doc?.versions.some(v => v.id === s.version_id);
|
||||
})
|
||||
: submissions}
|
||||
loading={subsLoading}
|
||||
onNewSubmission={() => setModal('submission')}
|
||||
onRefresh={refreshSubs}
|
||||
onNewSubmission={() => !IS_DEMO && setModal('submission')}
|
||||
onRefresh={() => !IS_DEMO && refreshSubs()}
|
||||
onStatusChange={handleSubmissionStatusChange}
|
||||
/>
|
||||
)}
|
||||
{activeTab === 'insights' && (
|
||||
<InsightsPanel data={insights} />
|
||||
)}
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
|
||||
134
apps/webapp/src/components/cv/InsightsPanel.tsx
Normal file
134
apps/webapp/src/components/cv/InsightsPanel.tsx
Normal file
@@ -0,0 +1,134 @@
|
||||
'use client';
|
||||
|
||||
import type { InsightsResult } from '@/libs/api';
|
||||
|
||||
function Bar({ rate, positive }: { rate: number; positive?: boolean }) {
|
||||
return (
|
||||
<div style={{ flex: 1, height: 6, background: 'var(--border)', borderRadius: 3, overflow: 'hidden' }}>
|
||||
<div style={{
|
||||
width: `${Math.round(rate * 100)}%`,
|
||||
height: '100%',
|
||||
background: positive === false ? '#ef4444' : rate >= 0.6 ? '#22c55e' : rate >= 0.4 ? '#f59e0b' : '#94a3b8',
|
||||
borderRadius: 3,
|
||||
transition: 'width 0.3s',
|
||||
}} />
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
function Pct({ v }: { v: number }) {
|
||||
return <span style={{ fontVariantNumeric: 'tabular-nums', fontSize: 12, fontWeight: 600, color: v >= 0.6 ? '#16a34a' : v >= 0.4 ? '#d97706' : '#6b7280' }}>{Math.round(v * 100)}%</span>;
|
||||
}
|
||||
|
||||
export default function InsightsPanel({ data }: { data: InsightsResult | null }) {
|
||||
if (!data) return (
|
||||
<div style={{ padding: '24px 0', color: 'var(--text-faint)', fontSize: 13, textAlign: 'center' }}>
|
||||
Loading insights…
|
||||
</div>
|
||||
);
|
||||
|
||||
if (!data.has_data) return (
|
||||
<div style={{ padding: '24px 0', color: 'var(--text-faint)', fontSize: 13 }}>
|
||||
Not enough data yet. Submit applications and mark outcomes to unlock insights.
|
||||
</div>
|
||||
);
|
||||
|
||||
return (
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 20 }}>
|
||||
{/* headline numbers */}
|
||||
<div style={{ display: 'grid', gridTemplateColumns: 'repeat(3, 1fr)', gap: 8 }}>
|
||||
{[
|
||||
{ label: 'Total submissions', value: data.total_submissions },
|
||||
{ label: 'Passed screening', value: data.positive_count },
|
||||
{ label: 'Screening rate', value: `${Math.round(data.positive_rate * 100)}%` },
|
||||
].map(({ label, value }) => (
|
||||
<div key={label} style={{ border: '1px solid var(--border)', borderRadius: 6, padding: '8px 10px', background: 'var(--surface)' }}>
|
||||
<div className="label" style={{ marginBottom: 3 }}>{label}</div>
|
||||
<div style={{ fontSize: 18, fontWeight: 600 }}>{value}</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
|
||||
{/* operation impact */}
|
||||
{data.operation_impact.length > 0 && (
|
||||
<section>
|
||||
<div className="label" style={{ marginBottom: 8 }}>Patch operation impact</div>
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 6 }}>
|
||||
{data.operation_impact.map(op => (
|
||||
<div key={op.operation} style={{ display: 'flex', alignItems: 'center', gap: 10 }}>
|
||||
<span style={{ fontFamily: 'var(--font-mono)', fontSize: 11, width: 140, flexShrink: 0, color: 'var(--text-muted)' }}>
|
||||
{op.operation}
|
||||
</span>
|
||||
<Bar rate={op.rate} />
|
||||
<Pct v={op.rate} />
|
||||
<span style={{ fontSize: 11, color: 'var(--text-faint)', width: 50, textAlign: 'right' }}>
|
||||
{op.positive}/{op.total}
|
||||
</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
<p style={{ fontSize: 11, color: 'var(--text-faint)', marginTop: 6 }}>
|
||||
% of accepted patches of this type in submissions that passed screening.
|
||||
</p>
|
||||
</section>
|
||||
)}
|
||||
|
||||
{/* section impact */}
|
||||
{data.section_impact.length > 0 && (
|
||||
<section>
|
||||
<div className="label" style={{ marginBottom: 8 }}>CV section impact</div>
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 6 }}>
|
||||
{data.section_impact.map(s => (
|
||||
<div key={s.section} style={{ display: 'flex', alignItems: 'center', gap: 10 }}>
|
||||
<span style={{ fontFamily: 'var(--font-mono)', fontSize: 11, width: 80, flexShrink: 0, color: 'var(--text-muted)' }}>
|
||||
{s.section}
|
||||
</span>
|
||||
<Bar rate={s.positive_rate} />
|
||||
<Pct v={s.positive_rate} />
|
||||
<span style={{ fontSize: 11, color: 'var(--text-faint)', width: 50, textAlign: 'right' }}>
|
||||
{s.count} edits
|
||||
</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</section>
|
||||
)}
|
||||
|
||||
{/* keyword signals */}
|
||||
{(data.top_positive_keywords.length > 0 || data.top_negative_keywords.length > 0) && (
|
||||
<section>
|
||||
<div className="label" style={{ marginBottom: 8 }}>Keyword signals</div>
|
||||
<div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: 12 }}>
|
||||
<div>
|
||||
<div style={{ fontSize: 11, color: '#16a34a', fontWeight: 600, marginBottom: 6 }}>Positive signals</div>
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 4 }}>
|
||||
{data.top_positive_keywords.map(k => (
|
||||
<div key={k.keyword} style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center' }}>
|
||||
<span style={{ fontSize: 12, fontFamily: 'var(--font-mono)', color: 'var(--text)' }}>{k.keyword}</span>
|
||||
<span style={{ fontSize: 11, color: '#16a34a' }}>+{k.positive_count} ({k.lift}×)</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
<div>
|
||||
<div style={{ fontSize: 11, color: '#dc2626', fontWeight: 600, marginBottom: 6 }}>Negative signals</div>
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 4 }}>
|
||||
{data.top_negative_keywords.length === 0
|
||||
? <span style={{ fontSize: 12, color: 'var(--text-faint)' }}>None yet</span>
|
||||
: data.top_negative_keywords.map(k => (
|
||||
<div key={k.keyword} style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center' }}>
|
||||
<span style={{ fontSize: 12, fontFamily: 'var(--font-mono)', color: 'var(--text)' }}>{k.keyword}</span>
|
||||
<span style={{ fontSize: 11, color: '#dc2626' }}>{k.negative_count}×</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<p style={{ fontSize: 11, color: 'var(--text-faint)', marginTop: 6 }}>
|
||||
Keywords extracted from accepted AI suggestions, split by outcome.
|
||||
</p>
|
||||
</section>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -1,4 +1,5 @@
|
||||
const API = "";
|
||||
export const IS_DEMO = process.env.NEXT_PUBLIC_DEMO === 'true';
|
||||
|
||||
export type StructuredBlock = {
|
||||
path: string;
|
||||
@@ -87,6 +88,21 @@ export type PublicAssetAnalytics = {
|
||||
last_viewed_at?: string | null;
|
||||
};
|
||||
|
||||
export type OperationImpact = { operation: string; total: number; positive: number; rate: number };
|
||||
export type KeywordSignal = { keyword: string; positive_count: number; negative_count: number; lift: number };
|
||||
export type SectionImpact = { section: string; positive_rate: number; count: number };
|
||||
|
||||
export type InsightsResult = {
|
||||
total_submissions: number;
|
||||
positive_count: number;
|
||||
positive_rate: number;
|
||||
operation_impact: OperationImpact[];
|
||||
top_positive_keywords: KeywordSignal[];
|
||||
top_negative_keywords: KeywordSignal[];
|
||||
section_impact: SectionImpact[];
|
||||
has_data: boolean;
|
||||
};
|
||||
|
||||
// reads OIDC bearer token from client-readable cookie (set by /api/auth/callback)
|
||||
function getAuthHeader(): Record<string, string> {
|
||||
if (typeof document === 'undefined') return {};
|
||||
@@ -238,6 +254,9 @@ export async function deleteDocument(documentId: string): Promise<void> {
|
||||
}
|
||||
}
|
||||
|
||||
export const fetchInsights = (): Promise<InsightsResult> =>
|
||||
req<InsightsResult>('/api/v1/insights');
|
||||
|
||||
export async function deleteVersion(versionId: string): Promise<void> {
|
||||
const res = await fetch(`${API}/api/v1/versions/${versionId}`, {
|
||||
method: 'DELETE',
|
||||
|
||||
Reference in New Issue
Block a user