fixed refactored code

src/embeddingbuddy/data/parser.py

@@ -16,11 +16,26 @@ class NDJSONParser:
     @staticmethod
     def parse_text(text_content: str) -> List[Document]:
         documents = []
-        for line in text_content.strip().split("\n"):
+        for line_num, line in enumerate(text_content.strip().split("\n"), 1):
             if line.strip():
-                doc_dict = json.loads(line)
-                doc = NDJSONParser._dict_to_document(doc_dict)
-                documents.append(doc)
+                try:
+                    doc_dict = json.loads(line)
+                    doc = NDJSONParser._dict_to_document(doc_dict)
+                    documents.append(doc)
+                except json.JSONDecodeError as e:
+                    raise json.JSONDecodeError(
+                        f"Invalid JSON on line {line_num}: {e.msg}",
+                        e.doc,
+                        e.pos
+                    )
+                except KeyError as e:
+                    raise KeyError(
+                        f"Missing required field {e} on line {line_num}"
+                    )
+                except (TypeError, ValueError) as e:
+                    raise ValueError(
+                        f"Invalid data format on line {line_num}: {str(e)}"
+                    )
         return documents
 
     @staticmethod
@@ -28,10 +43,29 @@ class NDJSONParser:
         if "id" not in doc_dict:
             doc_dict["id"] = str(uuid.uuid4())
 
+        # Validate required fields
+        if "text" not in doc_dict:
+            raise KeyError("'text'")
+        if "embedding" not in doc_dict:
+            raise KeyError("'embedding'")
+
+        # Validate embedding format
+        embedding = doc_dict["embedding"]
+        if not isinstance(embedding, list):
+            raise ValueError(f"Embedding must be a list, got {type(embedding).__name__}")
+        
+        if not embedding:
+            raise ValueError("Embedding cannot be empty")
+        
+        # Check that all embedding values are numbers
+        for i, val in enumerate(embedding):
+            if not isinstance(val, (int, float)) or val != val:  # NaN check
+                raise ValueError(f"Embedding contains invalid value at index {i}: {val}")
+
         return Document(
             id=doc_dict["id"],
             text=doc_dict["text"],
-            embedding=doc_dict["embedding"],
+            embedding=embedding,
             category=doc_dict.get("category"),
             subcategory=doc_dict.get("subcategory"),
             tags=doc_dict.get("tags"),