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

scripts/gen_demo_cv.py

@@ -0,0 +1,87 @@
+"""Generate the static demo CV DOCX used by DEMO mode in the webapp."""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+from docx import Document
+from docx.shared import Pt, RGBColor
+from docx.enum.text import WD_ALIGN_PARAGRAPH
+
+
+def add_heading(doc: Document, text: str, level: int = 1) -> None:
+    p = doc.add_heading(text, level=level)
+    p.alignment = WD_ALIGN_PARAGRAPH.LEFT
+
+
+def add_bullet(doc: Document, text: str) -> None:
+    doc.add_paragraph(text, style="List Bullet")
+
+
+def build(path: Path) -> None:
+    doc = Document()
+
+    # Name / contact
+    name_para = doc.add_paragraph()
+    name_para.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    run = name_para.add_run("Alex Rivera")
+    run.bold = True
+    run.font.size = Pt(18)
+
+    contact = doc.add_paragraph()
+    contact.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    contact.add_run("alex.rivera@email.com  ·  linkedin.com/in/alexrivera  ·  github.com/alexrivera")
+
+    doc.add_paragraph()  # spacer
+
+    # Summary
+    add_heading(doc, "Summary", level=2)
+    doc.add_paragraph(
+        "Software engineer with 5 years of experience building distributed systems and "
+        "machine learning pipelines at scale. Strong background in Python, Go, and cloud-native "
+        "architectures. Passionate about developer tooling and open-source contribution."
+    )
+
+    # Experience
+    add_heading(doc, "Experience", level=2)
+
+    add_heading(doc, "Senior Software Engineer — Acme Corp", level=3)
+    doc.add_paragraph("Jan 2022 – Present  ·  San Francisco, CA")
+    add_bullet(doc, "Led migration of monolithic data pipeline to distributed microservices, reducing p99 latency by 40%.")
+    add_bullet(doc, "Designed and shipped an internal feature flag system used by 50+ engineers across 3 teams.")
+    add_bullet(doc, "Mentored 4 junior engineers and ran weekly technical design review sessions.")
+
+    add_heading(doc, "Software Engineer — DataFlow Inc", level=3)
+    doc.add_paragraph("Aug 2019 – Dec 2021  ·  Remote")
+    add_bullet(doc, "Built real-time streaming ingestion system processing 2M events/day using Kafka and Flink.")
+    add_bullet(doc, "Developed Python SDK for internal data platform, adopted by 8 product teams.")
+    add_bullet(doc, "Contributed PyTorch-based anomaly detection model achieving 92% precision on production traffic.")
+
+    # Education
+    add_heading(doc, "Education", level=2)
+    add_heading(doc, "B.S. Computer Science — State University", level=3)
+    doc.add_paragraph("Graduated May 2019  ·  GPA 3.8 / 4.0")
+    add_bullet(doc, "Senior thesis: Efficient approximate nearest-neighbour search for high-dimensional embeddings.")
+
+    # Skills
+    add_heading(doc, "Skills", level=2)
+    skills_para = doc.add_paragraph()
+    skills_para.add_run("Languages: ").bold = True
+    skills_para.add_run("Python, Go, TypeScript, SQL")
+
+    infra_para = doc.add_paragraph()
+    infra_para.add_run("Infrastructure: ").bold = True
+    infra_para.add_run("Kubernetes, AWS, GCP, Terraform, Docker")
+
+    ml_para = doc.add_paragraph()
+    ml_para.add_run("ML / Data: ").bold = True
+    ml_para.add_run("PyTorch, scikit-learn, Spark, Kafka, dbt")
+
+    doc.save(path)
+    print(f"Saved demo CV to {path}")
+
+
+if __name__ == "__main__":
+    out = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("apps/webapp/public/demo-cv.docx")
+    out.parent.mkdir(parents=True, exist_ok=True)
+    build(out)