Polish grounded assistant output

CHANGELOG.md

@@ -23,6 +23,9 @@
 - Provisioned the five official thematic products and the 1,159-feature DOV
   soil map into Mol's Area in the central 28-municipality workbench, removing
   the mismatch with the earlier standalone Mol project.
+- Added deterministic semantic rounding for model context and normalized model
+  Markdown to the existing plain-text renderer so hectare, population and
+  score answers remain readable without exposing raw floating-point tails.
 
 ## Sprint 213-214 Cross-domain area profile (2026-07-16)
 

backend/app/services/geo_assistant_service.py

@@ -132,6 +132,26 @@ class GeoAssistantService:
             f"{answer}"
         )
 
+    @staticmethod
+    def rounded_context_value(value: float, unit: str) -> int | float:
+        normalized_unit = unit.casefold().strip()
+        if normalized_unit in {"inwoners", "personen", "objecten", "features"}:
+            return int(round(value))
+        if "%" in normalized_unit or "ha" in normalized_unit or "km" in normalized_unit or normalized_unit == "m":
+            return round(value, 2)
+        if "score" in normalized_unit:
+            return round(value, 4)
+        return round(value, 2)
+
+    @staticmethod
+    def normalize_plain_text(answer: str) -> str:
+        lines: list[str] = []
+        for line in answer.splitlines():
+            normalized = re.sub(r"^\s*\*\s+", "- ", line.strip())
+            normalized = normalized.replace("**", "").replace("__", "").replace("`", "")
+            lines.append(normalized)
+        return "\n".join(lines).strip()
+
     def __init__(self, settings: Settings | None = None):
         self.settings = settings or get_settings()
 
@@ -386,6 +406,7 @@ class GeoAssistantService:
                     )
                     context_metrics.append(item)
                     serialized_metrics.append(item.model_dump(mode="json"))
+                    serialized_metrics[-1]["value"] = self.rounded_context_value(item.value, item.unit)
                     serialized_metrics[-1]["measurement_quality"] = (
                         "schatting" if item.is_estimate else "exact_binnen_bronrepresentatie"
                     )
@@ -428,6 +449,7 @@ class GeoAssistantService:
                     )
                     context_metrics.append(item)
                     serialized_metrics.append(item.model_dump(mode="json"))
+                    serialized_metrics[-1]["value"] = self.rounded_context_value(item.value, item.unit)
                     serialized_metrics[-1]["measurement_quality"] = "resolutiegebonden_bronmeting"
                 source_dataset_ids.append(dataset.id)
                 current_context.append(
@@ -473,6 +495,7 @@ class GeoAssistantService:
                     )
                     context_metrics.append(item)
                     serialized_metrics.append(item.model_dump(mode="json"))
+                    serialized_metrics[-1]["value"] = self.rounded_context_value(item.value, item.unit)
                     serialized_metrics[-1]["measurement_quality"] = "exacte_berekening_binnen_gemodelleerd_scenario"
                 source_dataset_ids.append(dataset.id)
                 current_context.append(
@@ -584,6 +607,8 @@ class GeoAssistantService:
             "scope.label is het exact geanalyseerde gebied; vervang dit nooit door project.name of project.region. "
             "Noem bij cijfers de bron en eenheid. Maak duidelijk onderscheid tussen exacte metingen en schattingen. "
             "Als is_estimate true is, noem de waarde verplicht een schatting en nooit exact. "
+            "Een officiële bron maakt een afgeleide gebiedswaarde niet exact; noem een schatting nooit officieel geteld. "
+            "De numerieke contextwaarden zijn al bronveilig afgerond; neem die afgeronde waarden letterlijk over. "
             "Objectaantallen zijn ondersteunend; geef betekenisvolle oppervlakte-, lengte- of bevolkingsmetriek voorrang. "
             "Wanneer de gebruiker meerdere thema's opsomt, behandel elk gevraagd thema en voeg geen ongevraagd thema toe. "
             "Houd het antwoord beknopt: groepeer de kernmetrieken per gevraagd thema en herhaal geen beperkingen. "
@@ -627,6 +652,7 @@ class GeoAssistantService:
         answer = str(message.get("content") or "").strip()
         if not answer:
             raise AppError(code="OLLAMA_EMPTY_RESPONSE", message="Ollama gaf geen antwoord terug.", status_code=502)
+        answer = self.normalize_plain_text(answer)
         answer = self.ensure_estimate_disclosure(answer, metrics)
         return AssistantQueryResponse(
             answer=answer,

backend/tests/test_sprint202_temporal_metrics_and_ollama.py

@@ -165,6 +165,25 @@ def test_geo_assistant_does_not_add_irrelevant_estimate_disclosure() -> None:
     assert answer == "De bosoppervlakte bedraagt 3.626,56 hectare."
 
 
+@pytest.mark.parametrize(
+    ("value", "unit", "expected"),
+    [
+        (36_782.6497, "inwoners", 36_783),
+        (3_638.4167, "ha", 3_638.42),
+        (31.76431, "%", 31.76),
+        (0.680612, "score", 0.6806),
+    ],
+)
+def test_geo_assistant_rounds_prompt_values_by_semantic_unit(value: float, unit: str, expected: int | float) -> None:
+    assert GeoAssistantService.rounded_context_value(value, unit) == expected
+
+
+def test_geo_assistant_normalizes_model_markdown_for_plain_text_renderer() -> None:
+    answer = GeoAssistantService.normalize_plain_text("**Bevolking**\n* 36.783 inwoners\n`Bron: Statbel`")
+
+    assert answer == "Bevolking\n- 36.783 inwoners\nBron: Statbel"
+
+
 def test_geo_assistant_sends_grounded_context_without_thinking_trace(monkeypatch) -> None:
     service = GeoAssistantService(ollama_settings())
     project_id = uuid4()
@@ -228,6 +247,8 @@ def test_geo_assistant_sends_grounded_context_without_thinking_trace(monkeypatch
     assert "Gebruik uitsluitend feiten en cijfers uit CONTEXT_JSON" in captured["payload"]["messages"][0]["content"]
     assert "scope.label is het exact geanalyseerde gebied" in captured["payload"]["messages"][0]["content"]
     assert "noem de waarde verplicht een schatting" in captured["payload"]["messages"][0]["content"]
+    assert "noem een schatting nooit officieel geteld" in captured["payload"]["messages"][0]["content"]
+    assert "contextwaarden zijn al bronveilig afgerond" in captured["payload"]["messages"][0]["content"]
     assert "verzin geen oorzaak, voorspelling, verzadiging" in captured["payload"]["messages"][0]["content"]
     assert "bereken zelf geen gemiddelde, tempo, oorzaak of afgeleide trend" in captured["payload"]["messages"][0]["content"]
     assert "zonder Markdown-symbolen" in captured["payload"]["messages"][0]["content"]

docs/CODEX_EXECUTION_LOG.md

@@ -16,6 +16,10 @@ Changed:
 - Added deterministic Dutch theme selection before GIS calculation. Explicit
   questions now calculate only named themes; general summaries and source
   inventory questions deliberately retain full context.
+- The optimized live response completed in 12.3 seconds but exposed literal
+  Markdown and raw floating-point tails in the plain-text chat renderer. Added
+  deterministic Markdown normalization and unit-aware context rounding while
+  retaining the unrounded metrics in the canonical API response.
 
 Validation evidence:
 - A read-only live production-chain probe with the 1,200-token setting
@@ -27,6 +31,8 @@ Validation evidence:
 - After deterministic theme filtering was added, the complete readiness gate
   passed 720 backend tests plus all compile, contract, Alembic, frontend and
   shell gates.
+- After plain-text normalization and semantic prompt rounding, the final
+  readiness rerun passed 725 backend tests and the same complete gate set.
 - The regional thematic operator dry-run resolved exactly 28 official
   municipality Areas. The live Mol run in `Kempen Regional Workbench` imported
   all five products with complete source coverage; the DOV operator imported