Handle FastEmbed generator results

backend/app/embeddings.py

@@ -86,8 +86,15 @@ def embed_text(text: str) -> List[float]:
         return [0.0] * get_embedding_size()
     
     model = get_embedding_model()
-    embedding = model.embed([text])
-    return embedding[0].tolist()
+    embeddings = iter(model.embed([text]))
+    try:
+        embedding = next(embeddings)
+    except StopIteration as exc:
+        raise RuntimeError("Embedding model returned no vector") from exc
+
+    if hasattr(embedding, "tolist"):
+        return embedding.tolist()
+    return list(embedding)
 
 
 def embed_texts(texts: List[str]) -> List[List[float]]: