feat(cv): Phase 2.1-b — extract Projects, Certifications, and languages-from-prose

The structured model and StructuredCvProfileJson.FromSections already map
Projects/Certifications/Languages headings, but the AI normalize prompt
never emitted them, so on the benchmark CV the entire Projects section and
the in-summary languages (English Native, Norwegian B1) were silently
dropped. This closes that gap upstream — no backend schema or data change.

ai-service (tools/summarizer/app.py):
- /cv/normalize: added # Projects and # Certifications headings; a
  languages-from-prose rule (pull "native English", "Norwegian at B1" out
  of the summary even with no Languages section; ignore programming
  languages); and skill-group prefix stripping ("Development:",
  "DevOps & Infrastructure:", "Practices:" dropped, only the skills kept).
- /cv/classify-block: Projects and Certifications added to the section
  enum + rules (fallback path).

Backend:
- LooksLikeNormalizedMarkdownCv now recognises # Projects / # Certifications
  so those CVs still take the markdown assembly path.

Tests:
- CvExtractionCoverageTests (4) lock the C# mapping of Projects,
  Certifications and Languages sections into the structured profile.
- ai-service test_classify_block_supports_projects_section (1).
426 backend tests, 17 ai-service tests pass; app.py compiles.

The LLM behaviour (prompt -> headings) needs Ollama to observe and was not
run here; the C# side that consumes the headings is proven and the prompt
change is additive. Merge-not-replace + the review screen are the next
increment (2.1-a, approved: always-review, conservative merge).

Deployment: these prompts live in the ai-service container, which
deploy.sh does not rebuild by default -- deploy with
DEPLOY_BUILD_AI_SERVICE=true or the change won't take effect.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tools/summarizer/app.py

@@ -569,6 +569,8 @@ Rules for normalized_text:
   # Work Experience
   # Education
   # Skills
+  # Projects
+  # Certifications
   # Languages
   # Interests
 - Under # Contact, put one plain value per line, no labels unless unavoidable:
@@ -591,7 +593,19 @@ Rules for normalized_text:
   Institution, Location line
   2016 - 2019 line
   - detail
-- Under # Skills and # Languages, use one bullet per item.
+- Under # Projects, for each project use this exact shape (blank line between projects):
+  Project name
+  - one short description line covering what it is and the tech used
+- Under # Certifications, one certification per line: name, then issuer and year if stated.
+- Under # Skills, use one bullet per item. If skills are grouped with a category label such as
+  "Development:", "DevOps & Infrastructure:" or "Practices:", DROP the category label and list only
+  the individual skills as separate bullets. Never keep the category word as a skill.
+- Under # Languages, one language per line as "Name: Level" (e.g. "English: Native", "Norwegian: B1").
+  IMPORTANT: languages are often stated only inside the summary or profile text (e.g. "native English
+  speaker", "Norwegian at B1"). When you see a spoken/written human language and any proficiency
+  (native, fluent, C1, B2, B1, A2, conversational, basic), add it here even if there is no dedicated
+  languages section in the source. Do NOT treat programming languages (C#, Python, JavaScript, SQL) as
+  human languages.
 - Remove OCR/layout noise.
 - Do not output placeholders like Not specified.
 - If uncertain, omit the field/line rather than invent.
@@ -619,7 +633,7 @@ async def classify_cv_block(req: CvClassifyBlockRequest):
 You classify one CV text block into structured JSON.
 Return ONLY valid JSON with this exact shape:
 {{
-  "section": "Contact|Professional Summary|Work Experience|Education|Skills|Languages|Interests|Other",
+  "section": "Contact|Professional Summary|Work Experience|Education|Skills|Projects|Certifications|Languages|Interests|Other",
   "confidence": 0.0,
   "reason": "short reason",
   "title": string|null,
@@ -636,7 +650,9 @@ Rules:
 - Preserve facts only.
 - section must be one of the listed values.
 - Use Work Experience only for job/employment blocks.
-- Use Education only for degree/course/certification blocks.
+- Use Education only for degree/diploma/course blocks.
+- Use Projects for personal/side/portfolio project blocks (put the project name in title and details in bullets).
+- Use Certifications for named certifications/licences (put the certification name in title).
 - For Contact blocks, keep title/company/start/end null and bullets/summary/skills empty.
 - For Professional Summary blocks, prefer summary for concise summary lines and keep bullets empty unless the source is already bullet-like.
 - For Skills blocks, prefer skills for normalized skill items and keep title/company/start/end null.

tools/summarizer/tests/test_app.py

@@ -134,6 +134,38 @@ def test_classify_block_returns_structured_json(monkeypatch):
     assert payload["skills"] == ["Python", "SQL"]
 
 
+def test_classify_block_supports_projects_section(monkeypatch):
+    # Phase 2.1-b: Projects and Certifications are now valid classified sections so project blocks
+    # (e.g. the benchmark CV's JobTrack/InboxIntel) are no longer dropped into "Other".
+    module = load_app_module(monkeypatch)
+
+    def fake_generate_json(prompt: str):
+        assert "Projects" in prompt  # the enum now advertises Projects to the model
+        return {
+            "section": "Projects",
+            "confidence": 0.83,
+            "reason": "project block",
+            "title": "JobTrack",
+            "company": None,
+            "location": None,
+            "start": None,
+            "end": None,
+            "bullets": ["Full-stack job-application tracker (React, ASP.NET Core, SQLite, Docker)."],
+            "summary": [],
+            "skills": [],
+        }
+
+    monkeypatch.setattr(module, "_ollama_generate_json", fake_generate_json)
+    client = TestClient(module.app)
+
+    response = client.post("/cv/classify-block", json={"block": "JobTrack - Full-stack job-application tracker (React, ASP.NET Core, SQLite, Docker)."})
+
+    assert response.status_code == 200
+    payload = response.json()
+    assert payload["section"] == "Projects"
+    assert payload["title"] == "JobTrack"
+
+
 def test_classify_block_defaults_missing_section_to_other(monkeypatch):
     module = load_app_module(monkeypatch)
     monkeypatch.setattr(module, "_ollama_generate_json", lambda prompt: {"bullets": []})