Zeige die echten Produktwerte aus der Trefferliste und vermeide doppelte RAM/Speicher-Schluessel.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/app/discovery/attributes.py

@@ -0,0 +1,51 @@
+from __future__ import annotations
+
+from typing import Any
+
+SPEC_ALIASES = {
+    "ram_gb": ("ram", "arbeitsspeicher"),
+    "storage_gb": ("speicher", "ssd", "festplatte"),
+    "weight_kg": ("gewicht",),
+}
+
+
+def merge_observation_attributes(
+    raw_attributes: dict[str, Any],
+    normalized_attributes: dict[str, Any],
+) -> list[dict[str, Any]]:
+    items: list[dict[str, Any]] = []
+    used_norm: set[str] = set()
+    for name, raw_value in raw_attributes.items():
+        if raw_value is None or str(raw_value).strip() == "":
+            continue
+        fold = str(name).casefold().rstrip(":")
+        norm_key = next((key for key, aliases in SPEC_ALIASES.items() if fold in aliases), None)
+        norm_value = normalized_attributes.get(norm_key) if norm_key else None
+        if norm_key:
+            used_norm.add(norm_key)
+        items.append(
+            {
+                "attribute_key": norm_key or fold.replace(" ", "_"),
+                "raw_name": str(name).rstrip(":"),
+                "raw_value": raw_value,
+                "normalized_value": norm_value,
+            }
+        )
+    for key, value in normalized_attributes.items():
+        if key in used_norm or value is None:
+            continue
+        items.append(
+            {
+                "attribute_key": key,
+                "raw_name": key,
+                "raw_value": None,
+                "normalized_value": value,
+            }
+        )
+    return items
+
+
+def is_derived_duplicate(name: str, present: set[str]) -> bool:
+    fold = name.casefold()
+    aliases = SPEC_ALIASES.get(fold)
+    return bool(aliases and present.intersection(aliases))

backend/app/services/discovery_service.py

@@ -9,6 +9,7 @@ from sqlalchemy import select
 from sqlalchemy.orm import Session
 
 from app.clock import now_utc
+from app.discovery.attributes import is_derived_duplicate, merge_observation_attributes
 from app.discovery.definitions import get_definition, get_definition_by_key, upsert_definition
 from app.discovery.diff import diff_run, next_lifecycle
 from app.discovery.enums import (
@@ -1447,7 +1448,7 @@ def _attribute_map(session: Session, observation_id: UUID) -> dict[str, Any]:
         key = row.attribute_key
         if definition is not None and definition.scoring_attribute_key:
             key = definition.scoring_attribute_key
-        mapped[key] = row.normalized_value
+        mapped[key] = row.normalized_value if row.normalized_value is not None else row.raw_value
     return mapped
 
 
@@ -1457,16 +1458,29 @@ def _dynamic_attributes(session: Session, observation_id: UUID) -> list[dict[str
             ProductObservationAttributeRecord.observation_id == observation_id
         )
     ).all()
-    return [
+    present = {(row.raw_name or row.attribute_key or "").casefold() for row in rows}
+    items: list[dict[str, Any]] = []
+    for row in rows:
+        name = row.raw_name or row.attribute_key or ""
+        if is_derived_duplicate(row.attribute_key or "", present) or is_derived_duplicate(name, present):
+            continue
+        raw = row.raw_value
+        normalized = row.normalized_value
+        if (raw is None or raw == "") and normalized is None:
+            continue
+        definition = (
+            None if row.criterion_definition_id is None else session.get(CriterionDefinitionRecord, row.criterion_definition_id)
+        )
+        items.append(
             {
                 "criterion_definition_id": row.criterion_definition_id,
-            "raw_name": row.raw_name or row.attribute_key,
-            "raw_value": row.raw_value,
-            "normalized_value": row.normalized_value,
+                "raw_name": (definition.label if definition is not None else None) or name,
+                "raw_value": raw,
+                "normalized_value": normalized if normalized is not None else raw,
                 "unit": row.unit,
             }
-        for row in rows
-    ]
+        )
+    return items
 
 
 def _store_observation_attributes(
@@ -1475,30 +1489,34 @@ def _store_observation_attributes(
     raw_attributes: dict[str, Any],
     normalized_attributes: dict[str, Any],
 ) -> None:
-    keys = set(raw_attributes) | set(normalized_attributes)
-    definitions = {
-        row.scoring_attribute_key or row.key: row
-        for row in session.scalars(select(CriterionDefinitionRecord)).all()
-        if row.scoring_attribute_key or row.key
-    }
+    definitions = list(session.scalars(select(CriterionDefinitionRecord)))
+    by_score = {row.scoring_attribute_key: row for row in definitions if row.scoring_attribute_key}
+    by_key = {row.key: row for row in definitions}
+    by_label = {row.label.casefold(): row for row in definitions if row.label}
     attr_maps = {
-        row.raw_name: row
+        row.raw_name.casefold(): row
         for row in session.scalars(select(SourceAttributeMappingRecord)).all()
     }
-    for key in keys:
-        mapping = attr_maps.get(key)
+    for item in merge_observation_attributes(raw_attributes, normalized_attributes):
+        raw_name = str(item["raw_name"])
+        attribute_key = str(item["attribute_key"])
+        mapping = attr_maps.get(raw_name.casefold())
         definition = None if mapping is None else session.get(CriterionDefinitionRecord, mapping.criterion_definition_id)
         if definition is None:
-            definition = definitions.get(key)
+            definition = (
+                by_label.get(raw_name.casefold())
+                or by_score.get(attribute_key)
+                or by_key.get(attribute_key)
+            )
         session.add(
             ProductObservationAttributeRecord(
                 id=uuid4(),
                 observation_id=observation_id,
                 criterion_definition_id=None if definition is None else definition.id,
-                attribute_key=key,
-                raw_name=key,
-                raw_value=raw_attributes.get(key),
-                normalized_value=normalized_attributes.get(key),
+                attribute_key=attribute_key,
+                raw_name=raw_name,
+                raw_value=item["raw_value"],
+                normalized_value=item["normalized_value"],
                 unit=None if definition is None else definition.unit,
             )
         )

backend/app/sources/geizhals/result_parser.py

@@ -168,9 +168,11 @@ def _definition_list(node: Any) -> dict[str, str]:
                 if isinstance(child, str):
                     continue
                 if child.tag == "dt":
-                    pending = re.sub(r"\s+", " ", node_text(child)).strip()
+                    pending = re.sub(r"\s+", " ", node_text(child)).strip().rstrip(":")
                 elif child.tag == "dd" and pending:
-                    pairs[pending] = re.sub(r"\s+", " ", node_text(child)).strip()
+                    value = re.sub(r"\s+", " ", node_text(child)).strip()
+                    if value:
+                        pairs[pending] = value
                     pending = None
             return
         for child in current.children:

backend/tests/unit/test_observation_attributes.py

@@ -0,0 +1,28 @@
+from app.discovery.attributes import is_derived_duplicate, merge_observation_attributes
+
+
+def test_merge_keeps_product_values_and_drops_alias_duplicates() -> None:
+    items = merge_observation_attributes(
+        {
+            "CPU": "Apple M5 - 10 Core CPU",
+            "Display": '14.2" (3024x1964)',
+            "RAM": "16GB LPDDR5X",
+            "Speicher": "512GB SSD",
+            "Grafik": "",
+        },
+        {"ram_gb": 16, "storage_gb": 512},
+    )
+    by_name = {item["raw_name"]: item for item in items}
+    assert "ram_gb" not in by_name
+    assert "storage_gb" not in by_name
+    assert by_name["CPU"]["raw_value"] == "Apple M5 - 10 Core CPU"
+    assert by_name["Display"]["raw_value"] == '14.2" (3024x1964)'
+    assert by_name["RAM"]["normalized_value"] == 16
+    assert by_name["RAM"]["attribute_key"] == "ram_gb"
+    assert by_name["Speicher"]["normalized_value"] == 512
+    assert "Grafik" not in by_name
+
+
+def test_derived_duplicate_is_detected() -> None:
+    assert is_derived_duplicate("ram_gb", {"ram", "cpu"})
+    assert not is_derived_duplicate("cpu", {"ram", "cpu"})

frontend/src/api.ts

@@ -141,7 +141,12 @@ export type Candidate = {
   source_url?: string | null;
   current_best_price?: string | null;
   currency?: string | null;
-  current_dynamic_attributes?: { raw_name: string; normalized_value: unknown; unit?: string | null }[];
+  current_dynamic_attributes?: {
+    raw_name: string;
+    raw_value?: unknown;
+    normalized_value: unknown;
+    unit?: string | null;
+  }[];
   product_score?: number | null;
   product_eligibility?: string | null;
   ranking_status: string;
@@ -160,7 +165,7 @@ export type Observation = {
   currency?: string | null;
   availability?: string | null;
   seller_count?: number | null;
-  dynamic_attributes?: { raw_name: string; normalized_value: unknown }[];
+  dynamic_attributes?: { raw_name: string; raw_value?: unknown; normalized_value: unknown }[];
 };
 export type Source = { id: string; name: string };
 export type SourceCategory = {

frontend/src/pages/CandidateDetailPage.tsx

@@ -32,11 +32,15 @@ export function CandidateDetailPage() {
       </div>
       <div className="card">
         <h2>Attribute</h2>
-        {(Array.isArray(item.current_dynamic_attributes) ? item.current_dynamic_attributes : []).map((attr) => (
+        {(Array.isArray(item.current_dynamic_attributes) ? item.current_dynamic_attributes : []).map((attr) => {
+          const value = attr.raw_value ?? attr.normalized_value;
+          if (value == null || value === "") return null;
+          return (
             <p key={attr.raw_name}>
-            {attr.raw_name}: {String(attr.normalized_value ?? "")} {attr.unit || ""}
+              {attr.raw_name}: {String(value)} {attr.unit || ""}
             </p>
-        ))}
+          );
+        })}
       </div>
       <div className="card">
         <h2>Historie</h2>