Update func.py

func.py

@@ -114,6 +114,37 @@ def analyze_sentiment(
     except Exception:
         return "Unknown", 0.0
 
+# ---------------------------------------------------------------------------
+# Organisation‑entity extraction helper (kept for backward compatibility)
+# ---------------------------------------------------------------------------
+
+def extract_org_entities(
+    text: str,
+    pipe=None,
+    max_entities: int = 5,
+) -> List[str]:
+    """Extract up to *max_entities* unique organisation tokens from *text*.
+
+    Uses the pre‑initialised NER pipeline unless an alternative *pipe* is
+    supplied. Tokens are upper‑cased and de‑hashed ("##") to make them ticker‑
+    friendly. The function is side‑effect free and falls back to an empty list
+    on any exception.
+    """
+    try:
+        ner_pipe = pipe or ner_pipeline
+        entities = ner_pipe(text)
+        orgs: List[str] = []
+        for ent in entities:
+            if ent.get("entity_group") == "ORG":
+                token = ent["word"].replace("##", "").strip().upper()
+                if token and token not in orgs:
+                    orgs.append(token)
+                if len(orgs) >= max_entities:
+                    break
+        return orgs
+    except Exception:
+        return []
+
 # ---------------------------------------------------------------------------
 # Aggregation logic – turning many headlines into one overall label
 # ---------------------------------------------------------------------------