mirror of
https://github.com/velocitatem/cvfs.git
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615d1bdb9e
- 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
88 lines
3.3 KiB
Python
88 lines
3.3 KiB
Python
"""Generate the static demo CV DOCX used by DEMO mode in the webapp."""
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from __future__ import annotations
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import sys
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from pathlib import Path
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from docx import Document
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from docx.shared import Pt, RGBColor
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from docx.enum.text import WD_ALIGN_PARAGRAPH
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def add_heading(doc: Document, text: str, level: int = 1) -> None:
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p = doc.add_heading(text, level=level)
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p.alignment = WD_ALIGN_PARAGRAPH.LEFT
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def add_bullet(doc: Document, text: str) -> None:
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doc.add_paragraph(text, style="List Bullet")
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def build(path: Path) -> None:
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doc = Document()
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# Name / contact
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name_para = doc.add_paragraph()
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name_para.alignment = WD_ALIGN_PARAGRAPH.CENTER
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run = name_para.add_run("Alex Rivera")
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run.bold = True
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run.font.size = Pt(18)
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contact = doc.add_paragraph()
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contact.alignment = WD_ALIGN_PARAGRAPH.CENTER
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contact.add_run("alex.rivera@email.com · linkedin.com/in/alexrivera · github.com/alexrivera")
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doc.add_paragraph() # spacer
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# Summary
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add_heading(doc, "Summary", level=2)
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doc.add_paragraph(
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"Software engineer with 5 years of experience building distributed systems and "
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"machine learning pipelines at scale. Strong background in Python, Go, and cloud-native "
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"architectures. Passionate about developer tooling and open-source contribution."
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)
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# Experience
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add_heading(doc, "Experience", level=2)
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add_heading(doc, "Senior Software Engineer — Acme Corp", level=3)
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doc.add_paragraph("Jan 2022 – Present · San Francisco, CA")
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add_bullet(doc, "Led migration of monolithic data pipeline to distributed microservices, reducing p99 latency by 40%.")
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add_bullet(doc, "Designed and shipped an internal feature flag system used by 50+ engineers across 3 teams.")
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add_bullet(doc, "Mentored 4 junior engineers and ran weekly technical design review sessions.")
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add_heading(doc, "Software Engineer — DataFlow Inc", level=3)
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doc.add_paragraph("Aug 2019 – Dec 2021 · Remote")
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add_bullet(doc, "Built real-time streaming ingestion system processing 2M events/day using Kafka and Flink.")
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add_bullet(doc, "Developed Python SDK for internal data platform, adopted by 8 product teams.")
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add_bullet(doc, "Contributed PyTorch-based anomaly detection model achieving 92% precision on production traffic.")
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# Education
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add_heading(doc, "Education", level=2)
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add_heading(doc, "B.S. Computer Science — State University", level=3)
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doc.add_paragraph("Graduated May 2019 · GPA 3.8 / 4.0")
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add_bullet(doc, "Senior thesis: Efficient approximate nearest-neighbour search for high-dimensional embeddings.")
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# Skills
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add_heading(doc, "Skills", level=2)
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skills_para = doc.add_paragraph()
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skills_para.add_run("Languages: ").bold = True
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skills_para.add_run("Python, Go, TypeScript, SQL")
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infra_para = doc.add_paragraph()
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infra_para.add_run("Infrastructure: ").bold = True
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infra_para.add_run("Kubernetes, AWS, GCP, Terraform, Docker")
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ml_para = doc.add_paragraph()
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ml_para.add_run("ML / Data: ").bold = True
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ml_para.add_run("PyTorch, scikit-learn, Spark, Kafka, dbt")
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doc.save(path)
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print(f"Saved demo CV to {path}")
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if __name__ == "__main__":
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out = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("apps/webapp/public/demo-cv.docx")
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out.parent.mkdir(parents=True, exist_ok=True)
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build(out)
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