diff --git a/app/analyzer.py b/app/analyzer.py
index 6f0dc67..648d3b9 100644
--- a/app/analyzer.py
+++ b/app/analyzer.py
@@ -246,6 +246,11 @@ async def analyze_antrag(text: str, bundesland: str = "NRW", model: str = "qwen-
                 text, fraktionen, bundesland=bundesland, top_k_per_partei=2,
             )
             quotes_context = format_quotes_for_prompt(semantic_quotes)
+        except (NameError, AttributeError, TypeError, KeyError):
+            # Programmierfehler (z.B. der partei_upper-Refactor-Rest aus
+            # #55/eb045d0, der zu Issue #60 führte) sollen hart fehlschlagen
+            # statt still auf den schwächeren Keyword-Pfad zurückzufallen.
+            raise
         except Exception:
             logger.exception("Semantic search failed, falling back to keyword search")
             quotes = find_relevant_quotes(text, fraktionen, bundesland=bundesland)
diff --git a/app/embeddings.py b/app/embeddings.py
index c8cfd26..8d4594a 100644
--- a/app/embeddings.py
+++ b/app/embeddings.py
@@ -525,7 +525,7 @@ def get_relevant_quotes_for_antrag(
         )
 
         if wahl_chunks or partei_chunks:
-            results[partei_upper] = {
+            results[partei_lookup] = {
                 "wahlprogramm": wahl_chunks,
                 "parteiprogramm": partei_chunks,
             }
diff --git a/tests/test_embeddings.py b/tests/test_embeddings.py
index 48ee6b5..5c48123 100644
--- a/tests/test_embeddings.py
+++ b/tests/test_embeddings.py
@@ -21,7 +21,12 @@ if "openai" not in sys.modules:
     openai_stub.OpenAI = lambda **kw: None
     sys.modules["openai"] = openai_stub
 
-from app.embeddings import _chunk_source_label, format_quotes_for_prompt
+from app import embeddings as embeddings_mod
+from app.embeddings import (
+    _chunk_source_label,
+    format_quotes_for_prompt,
+    get_relevant_quotes_for_antrag,
+)
 
 
 # ─────────────────────────────────────────────────────────────────────────────
@@ -131,6 +136,51 @@ class TestFormatQuotesForPrompt:
         assert "**Wahlprogramm:**" in out
         assert "**Grundsatzprogramm:**" in out
 
+    def test_get_relevant_quotes_for_antrag_populates_results(self, monkeypatch):
+        """Regression for the partei_upper NameError (Phase B / #55 / eb045d0):
+
+        The dict-write line still referenced ``partei_upper`` after the
+        rest of the function had been renamed to ``partei_lookup``. The
+        result was that ``get_relevant_quotes_for_antrag`` raised
+        ``NameError`` on every call, was silently swallowed by the
+        ``except Exception`` in ``analyzer.run_analysis``, and silently
+        downgraded *every* assessment to keyword search — which then
+        caused the LLM hallucinations tracked in #60.
+
+        Test strategy: monkeypatch ``find_relevant_chunks`` so we don't
+        need real embeddings, then call the wrapper and assert it
+        actually returns a populated dict instead of crashing.
+        """
+        def fake_find_relevant_chunks(query, parteien=None, typ=None,
+                                      bundesland=None, top_k=3,
+                                      min_similarity=0.5):
+            return [{
+                "programm_id": "gruene-nrw-2022",
+                "partei": parteien[0] if parteien else "GRÜNE",
+                "typ": typ or "wahlprogramm",
+                "seite": 58,
+                "text": "Wahlalter ab 16",
+                "similarity": 0.7,
+            }]
+
+        monkeypatch.setattr(embeddings_mod, "find_relevant_chunks",
+                            fake_find_relevant_chunks)
+
+        result = get_relevant_quotes_for_antrag(
+            antrag_text="Wahlalter ab 16",
+            fraktionen=["GRÜNE"],
+            bundesland="NRW",
+            top_k_per_partei=2,
+        )
+        assert result, "Expected a non-empty result dict, got empty"
+        # The keys are canonical party names; either GRÜNE itself or
+        # whatever the canonical mapper returns for it.
+        assert any("GR" in k.upper() for k in result.keys())
+        # And the structure must be the {wahlprogramm, parteiprogramm} dict
+        first = next(iter(result.values()))
+        assert "wahlprogramm" in first
+        assert "parteiprogramm" in first
+
     def test_text_truncated_at_500_chars(self):
         long_chunk = {
             "FDP": {