ref: Use TypeError instead of ValueError when relevant (TRY004) (#4045)

Use TypeError instead of ValueError when relevant (TRY004)

src/backend/base/langflow/base/io/chat.py

@@ -61,7 +61,7 @@ class ChatComponent(Component):
         iterator = message.text
         if not isinstance(iterator, AsyncIterator | Iterator):
             msg = "The message must be an iterator or an async iterator."
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         if isinstance(iterator, AsyncIterator):
             return run_until_complete(self._handle_async_iterator(iterator, message, message_id))

src/backend/base/langflow/components/helpers/MessageToData.py

@@ -27,7 +27,7 @@ class MessageToDataComponent(Component):
         try:
             if not isinstance(self.message, Message):
                 msg = "Input must be a Message object"
-                raise ValueError(msg)
+                raise TypeError(msg)
 
             # Convert Message to Data
             data = Data(data=self.message.data)

src/backend/base/langflow/components/prototypes/RunnableExecutor.py

@@ -119,7 +119,7 @@ class RunnableExecComponent(Component):
         input_dict, status = self.get_input_dict(self.runnable, self.input_key, self.input_value)
         if not isinstance(self.runnable, AgentExecutor):
             msg = "The runnable must be an AgentExecutor"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         if self.use_stream:
             return self.astream_events(input_dict)

src/backend/base/langflow/components/retrievers/SelfQueryRetriever.py

@@ -67,7 +67,7 @@ class SelfQueryRetrieverComponent(Component):
             input_text = self.query
         else:
             msg = f"Query type {type(self.query)} not supported."
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         documents = self_query_retriever.invoke(input=input_text, config={"callbacks": self.get_langchain_callbacks()})
         data = [Data.from_document(document) for document in documents]

src/backend/base/langflow/components/tools/PythonREPLTool.py

@@ -55,7 +55,7 @@ class PythonREPLToolComponent(LCToolComponent):
             modules = global_imports
         else:
             msg = "global_imports must be either a string or a list"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         for module in modules:
             try:

src/backend/base/langflow/components/vectorstores/AstraDB.py

@@ -441,7 +441,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
                 documents.append(_input.to_lc_document())
             else:
                 msg = "Vector Store Inputs must be Data objects."
-                raise ValueError(msg)
+                raise TypeError(msg)
 
         if documents:
             logger.debug(f"Adding {len(documents)} documents to the Vector Store.")

src/backend/base/langflow/components/vectorstores/Chroma.py

@@ -156,7 +156,7 @@ class ChromaVectorStoreComponent(LCVectorStoreComponent):
                     documents.append(_input.to_lc_document())
             else:
                 msg = "Vector Store Inputs must be Data objects."
-                raise ValueError(msg)
+                raise TypeError(msg)
 
         if documents and self.embedding is not None:
             logger.debug(f"Adding {len(documents)} documents to the Vector Store.")

src/backend/base/langflow/components/vectorstores/Elasticsearch.py

@@ -162,7 +162,7 @@ class ElasticsearchVectorStoreComponent(LCVectorStoreComponent):
             else:
                 error_message = "Vector Store Inputs must be Data objects."
                 logger.error(error_message)
-                raise ValueError(error_message)
+                raise TypeError(error_message)
         return documents
 
     def _add_documents_to_vector_store(self, vector_store: "ElasticsearchStore") -> None:

src/backend/base/langflow/components/vectorstores/HCD.py

@@ -260,7 +260,7 @@ class HCDVectorStoreComponent(LCVectorStoreComponent):
                 documents.append(_input.to_lc_document())
             else:
                 msg = "Vector Store Inputs must be Data objects."
-                raise ValueError(msg)
+                raise TypeError(msg)
 
         if documents:
             logger.debug(f"Adding {len(documents)} documents to the Vector Store.")

src/backend/base/langflow/components/vectorstores/OpenSearch.py

@@ -159,7 +159,7 @@ class OpenSearchVectorStoreComponent(LCVectorStoreComponent):
             else:
                 error_message = f"Expected Data object, got {type(_input)}"
                 logger.error(error_message)
-                raise ValueError(error_message)
+                raise TypeError(error_message)
 
         if documents and self.embedding is not None:
             logger.debug(f"Adding {len(documents)} documents to the Vector Store.")

src/backend/base/langflow/components/vectorstores/Qdrant.py

@@ -87,7 +87,7 @@ class QdrantVectorStoreComponent(LCVectorStoreComponent):
 
         if not isinstance(self.embedding, Embeddings):
             msg = "Invalid embedding object"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         if documents:
             qdrant = Qdrant.from_documents(documents, embedding=self.embedding, **qdrant_kwargs, **server_kwargs)

src/backend/base/langflow/custom/custom_component/component.py

@@ -430,7 +430,7 @@ class Component(CustomComponent):
         # Ensure that the output method is a valid method name (string)
         if not isinstance(output.method, str):
             msg = f"Method {output.method} is not a valid output of {value.__class__.__name__}"
-            raise ValueError(msg)
+            raise TypeError(msg)
         return getattr(value, output.method)
 
     def _process_connection_or_parameter(self, key, value):
@@ -503,7 +503,7 @@ class Component(CustomComponent):
                 f"You set {value.display_name} as value for `{key}`. "
                 f"You should pass one of the following: {methods}"
             )
-            raise ValueError(msg)
+            raise TypeError(msg)
         self._set_input_value(key, value)
         self._parameters[key] = value
         self._attributes[key] = value

src/backend/base/langflow/custom/custom_component/custom_component.py

@@ -288,7 +288,7 @@ class CustomComponent(BaseComponent):
                 data_dict = item.copy()
             else:
                 msg = f"Invalid data type: {type(item)}"
-                raise ValueError(msg)
+                raise TypeError(msg)
 
             data_objects.append(Data(data=data_dict))
 

src/backend/base/langflow/custom/utils.py

@@ -268,7 +268,7 @@ def get_component_instance(custom_component: CustomComponent, user_id: str | UUI
             custom_class = eval_custom_component_code(custom_component._code)
         else:
             msg = "Invalid code type"
-            raise ValueError(msg)
+            raise TypeError(msg)
     except Exception as exc:
         logger.exception("Error while evaluating custom component code")
         raise HTTPException(
@@ -303,7 +303,7 @@ def run_build_config(
             custom_class = eval_custom_component_code(custom_component._code)
         else:
             msg = "Invalid code type"
-            raise ValueError(msg)
+            raise TypeError(msg)
     except Exception as exc:
         logger.exception("Error while evaluating custom component code")
         raise HTTPException(

src/backend/base/langflow/events/event_manager.py

@@ -27,7 +27,7 @@ class EventManager:
     def _validate_callback(callback: EventCallback):
         if not callable(callback):
             msg = "Callback must be callable"
-            raise ValueError(msg)
+            raise TypeError(msg)
         # Check if it has `self, event_type and data`
         sig = inspect.signature(callback)
         parameters = ["manager", "event_type", "data"]

src/backend/base/langflow/graph/graph/base.py

@@ -248,11 +248,11 @@ class Graph:
         source_vertex = self.get_vertex(source_id)
         if not isinstance(source_vertex, ComponentVertex):
             msg = f"Source vertex {source_id} is not a component vertex."
-            raise ValueError(msg)
+            raise TypeError(msg)
         target_vertex = self.get_vertex(target_id)
         if not isinstance(target_vertex, ComponentVertex):
             msg = f"Target vertex {target_id} is not a component vertex."
-            raise ValueError(msg)
+            raise TypeError(msg)
         output_name, input_name = output_input_tuple
         if source_vertex._custom_component is None:
             msg = f"Source vertex {source_id} does not have a custom component."
@@ -661,7 +661,7 @@ class Graph:
 
         if not isinstance(inputs.get(INPUT_FIELD_NAME, ""), str):
             msg = f"Invalid input value: {inputs.get(INPUT_FIELD_NAME)}. Expected string"
-            raise ValueError(msg)
+            raise TypeError(msg)
         if inputs:
             self._set_inputs(input_components, inputs, input_type)
         # Update all the vertices with the session_id
@@ -1529,7 +1529,7 @@ class Graph:
                 vertices.append(result.vertex)
             else:
                 msg = f"Invalid result from task {task_name}: {result}"
-                raise ValueError(msg)
+                raise TypeError(msg)
 
         for v in vertices:
             # set all executed vertices as non-runnable to not run them again.

src/backend/base/langflow/graph/state/model.py

@@ -230,7 +230,7 @@ def create_state_model(model_name: str = "State", validate: bool = True, **kwarg
             # typing.Annotated[<type>, Field(...)]
             if not isinstance(value[0], type):
                 msg = f"Invalid type for field {name}: {type(value[0])}"
-                raise ValueError(msg)
+                raise TypeError(msg)
             fields[name] = (value[0], value[1])
         else:
             msg = f"Invalid value type {type(value)} for field {name}"

src/backend/base/langflow/graph/vertex/base.py

@@ -750,7 +750,7 @@ class Vertex:
         """
         if isinstance(self._built_object, UnbuiltObject):
             msg = f"{self.display_name}: {self._built_object_repr()}"
-            raise ValueError(msg)
+            raise TypeError(msg)
         if self._built_object is None:
             message = f"{self.display_name} returned None."
             if self.base_type == "custom_components":

src/backend/base/langflow/graph/vertex/types.py

@@ -382,7 +382,7 @@ class InterfaceVertex(ComponentVertex):
         iterator = self.params.get(INPUT_FIELD_NAME, None)
         if not isinstance(iterator, AsyncIterator | Iterator):
             msg = "The message must be an iterator or an async iterator."
-            raise ValueError(msg)
+            raise TypeError(msg)
         is_async = isinstance(iterator, AsyncIterator)
         complete_message = ""
         if is_async:

src/backend/base/langflow/helpers/data.py

@@ -58,7 +58,7 @@ def messages_to_text(template: str, messages: Message | list[Message]) -> str:
         # If it is not a message, create one with the key "text"
         if not isinstance(message, Message):
             msg = "All elements in the list must be of type Message."
-            raise ValueError(msg)
+            raise TypeError(msg)
         _messages.append(message)
 
     formated_messages = [template.format(data=message.model_dump(), **message.model_dump()) for message in _messages]

src/backend/base/langflow/inputs/input_mixin.py

@@ -133,12 +133,12 @@ class FileMixin(BaseModel):
     def validate_file_types(cls, v):
         if not isinstance(v, list):
             msg = "file_types must be a list"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         # types should be a list of extensions without the dot
         for file_type in v:
             if not isinstance(file_type, str):
                 msg = "file_types must be a list of strings"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
             if file_type.startswith("."):
                 msg = "file_types should not start with a dot"
                 raise ValueError(msg)

src/backend/base/langflow/inputs/inputs.py

@@ -36,7 +36,7 @@ class TableInput(BaseInputMixin, MetadataTraceMixin, TableMixin, ListableInputMi
         # Check if value is a list of dicts
         if not isinstance(v, list):
             msg = f"TableInput value must be a list of dictionaries or Data. Value '{v}' is not a list."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         for item in v:
             if not isinstance(item, dict | Data):
@@ -44,7 +44,7 @@ class TableInput(BaseInputMixin, MetadataTraceMixin, TableMixin, ListableInputMi
                     "TableInput value must be a list of dictionaries or Data. "
                     f"Item '{item}' is not a dictionary or Data."
                 )
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
         return v
 
 
@@ -206,7 +206,7 @@ class MessageTextInput(StrInput, MetadataTraceMixin, InputTraceMixin):
             value = v
         else:
             msg = f"Invalid value type {type(v)}"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         return value
 
 
@@ -462,11 +462,11 @@ class MultiselectInput(BaseInputMixin, ListableInputMixin, DropDownMixin, Metada
         # Check if value is a list of dicts
         if not isinstance(v, list):
             msg = f"MultiselectInput value must be a list. Value: '{v}'"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         for item in v:
             if not isinstance(item, str):
                 msg = f"MultiselectInput value must be a list of strings. Item: '{item}' is not a string"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
         return v
 
 

src/backend/base/langflow/io/schema.py

@@ -33,7 +33,7 @@ def create_input_schema(inputs: list["InputTypes"]) -> type[BaseModel]:
             field_type = _convert_field_type_to_type[field_type]
         else:
             msg = f"Invalid field type: {field_type}"
-            raise ValueError(msg)
+            raise TypeError(msg)
         if hasattr(input_model, "options") and isinstance(input_model.options, list) and input_model.options:
             literal_string = f"Literal{input_model.options}"
             # validate that the literal_string is a valid literal

src/backend/base/langflow/load/utils.py

@@ -61,7 +61,7 @@ def upload_file(file_path: str, host: str, flow_id: str, components: list[str],
                     tweaks[component] = {"path": response["file_path"]}
                 else:
                     msg = f"Component ID or name must be a string. Got {type(component)}"
-                    raise ValueError(msg)
+                    raise TypeError(msg)
             return tweaks
         msg = "Error uploading file"
         raise ValueError(msg)

src/backend/base/langflow/processing/process.py

@@ -117,13 +117,13 @@ def validate_input(
 ) -> list[dict[str, Any]]:
     if not isinstance(graph_data, dict) or not isinstance(tweaks, dict):
         msg = "graph_data and tweaks should be dictionaries"
-        raise ValueError(msg)
+        raise TypeError(msg)
 
     nodes = graph_data.get("data", {}).get("nodes") or graph_data.get("nodes")
 
     if not isinstance(nodes, list):
         msg = "graph_data should contain a list of nodes under 'data' key or directly under 'nodes' key"
-        raise ValueError(msg)
+        raise TypeError(msg)
 
     return nodes
 

src/backend/base/langflow/schema/data.py

@@ -30,7 +30,7 @@ class Data(BaseModel):
     def validate_data(cls, values):
         if not isinstance(values, dict):
             msg = "Data must be a dictionary"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         if not values.get("data"):
             values["data"] = {}
         # Any other keyword should be added to the data dictionary

src/backend/base/langflow/services/chat/cache.py

@@ -113,7 +113,7 @@ class CacheService(Subject, Service):
             self.add(name, obj.to_csv(), "pandas", extension="csv")
         else:
             msg = "Object is not a pandas DataFrame or Series"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
     def add_image(self, name: str, obj: Any, extension: str = "png"):
         """
@@ -127,7 +127,7 @@ class CacheService(Subject, Service):
             self.add(name, obj, "image", extension=extension)
         else:
             msg = "Object is not a PIL Image"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
     def get(self, name: str):
         """

src/backend/base/langflow/services/database/models/flow/model.py

@@ -116,7 +116,7 @@ class FlowBase(SQLModel):
             return v
         if not isinstance(v, dict):
             msg = "Flow must be a valid JSON"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         # data must contain nodes and edges
         if "nodes" not in v:

src/backend/base/langflow/services/telemetry/opentelemetry.py

@@ -208,7 +208,7 @@ class OpenTelemetry(metaclass=ThreadSafeSingletonMetaUsingWeakref):
             counter.add(value, labels)
         else:
             msg = f"Metric '{metric_name}' is not a counter"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
     def up_down_counter(self, metric_name: str, value: float, labels: Mapping[str, str]):
         self.validate_labels(metric_name, labels)
@@ -217,7 +217,7 @@ class OpenTelemetry(metaclass=ThreadSafeSingletonMetaUsingWeakref):
             up_down_counter.add(value, labels)
         else:
             msg = f"Metric '{metric_name}' is not an up down counter"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
     def update_gauge(self, metric_name: str, value: float, labels: Mapping[str, str]):
         self.validate_labels(metric_name, labels)
@@ -226,7 +226,7 @@ class OpenTelemetry(metaclass=ThreadSafeSingletonMetaUsingWeakref):
             gauge.set_value(value, labels)
         else:
             msg = f"Metric '{metric_name}' is not a gauge"
-            raise ValueError(msg)
+            raise TypeError(msg)
 
     def observe_histogram(self, metric_name: str, value: float, labels: Mapping[str, str]):
         self.validate_labels(metric_name, labels)
@@ -235,4 +235,4 @@ class OpenTelemetry(metaclass=ThreadSafeSingletonMetaUsingWeakref):
             histogram.record(value, labels)
         else:
             msg = f"Metric '{metric_name}' is not a histogram"
-            raise ValueError(msg)
+            raise TypeError(msg)

src/backend/base/langflow/template/field/base.py

@@ -138,7 +138,7 @@ class Input(BaseModel):
     def validate_file_types(cls, value):
         if not isinstance(value, list):
             msg = "file_types must be a list"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         return [
             (f".{file_type}" if isinstance(file_type, str) and not file_type.startswith(".") else file_type)
             for file_type in value
@@ -155,7 +155,7 @@ class Input(BaseModel):
             v = format_type(v)
         elif not isinstance(v, str):
             msg = f"type must be a string or a type, not {type(v)}"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         return v
 
 

src/backend/base/langflow/utils/schemas.py

@@ -37,7 +37,7 @@ class ChatOutputResponse(BaseModel):
         for file in files:
             if not isinstance(file, dict):
                 msg = "Files must be a list of dictionaries."
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
 
             if not all(key in file for key in ["path", "name", "type"]):
                 # If any of the keys are missing, we should extract the

src/backend/base/pyproject.toml

@@ -62,12 +62,14 @@ ignore = [
     "EXE",
     "FBT",
     "N",
+    "PGH",
     "RUF006", # Store a reference to the return value of `asyncio.create_task`
     "S",
     "SLF",
     "T201",
-    "TRY",
-    "PGH",
+    "TRY002",
+    "TRY2",
+    "TRY3",
 ]
 
 [tool.ruff.lint.per-file-ignores]

src/backend/tests/unit/graph/graph/state/test_state_model.py

@@ -76,8 +76,8 @@ class TestCreateStateModel:
         assert state_instance.field_two == 123
 
     # Raises ValueError for invalid field type in tuple-based definitions
-    def test_raise_valueerror_for_invalid_field_type_in_tuple(self):
-        with pytest.raises(ValueError, match="Invalid type for field invalid_field"):
+    def test_raise_typeerror_for_invalid_field_type_in_tuple(self):
+        with pytest.raises(TypeError, match="Invalid type for field invalid_field"):
             create_state_model(invalid_field=("not_a_type", "default"))
 
     # Raises ValueError for unsupported value types in keyword arguments

src/backend/tests/unit/test_telemetry.py

@@ -24,17 +24,17 @@ def test_gauge(opentelemetry_instance):
 
 
 def test_gauge_with_counter_method(opentelemetry_instance):
-    with pytest.raises(ValueError, match="Metric 'file_uploads' is not a counter"):
+    with pytest.raises(TypeError, match="Metric 'file_uploads' is not a counter"):
         opentelemetry_instance.increment_counter(metric_name="file_uploads", value=1, labels=fixed_labels)
 
 
 def test_gauge_with_historgram_method(opentelemetry_instance):
-    with pytest.raises(ValueError, match="Metric 'file_uploads' is not a histogram"):
+    with pytest.raises(TypeError, match="Metric 'file_uploads' is not a histogram"):
         opentelemetry_instance.observe_histogram("file_uploads", 1, fixed_labels)
 
 
 def test_gauge_with_up_down_counter_method(opentelemetry_instance):
-    with pytest.raises(ValueError, match="Metric 'file_uploads' is not an up down counter"):
+    with pytest.raises(TypeError, match="Metric 'file_uploads' is not an up down counter"):
         opentelemetry_instance.up_down_counter("file_uploads", 1, labels=fixed_labels)