Add ruff rules SIM

src/backend/base/langflow/__main__.py

@@ -457,11 +457,10 @@ def migration(
     """
     Run or test migrations.
     """
-    if fix:
-        if not typer.confirm(
-            "This will delete all data necessary to fix migrations. Are you sure you want to continue?"
-        ):
-            raise typer.Abort
+    if fix and not typer.confirm(
+        "This will delete all data necessary to fix migrations. Are you sure you want to continue?"
+    ):
+        raise typer.Abort
 
     initialize_services(fix_migration=fix)
     db_service = get_db_service()

src/backend/base/langflow/api/log_router.py

@@ -90,10 +90,7 @@ async def logs(
                 status_code=HTTPStatus.BAD_REQUEST,
                 detail="Timestamp is required when requesting logs after the timestamp",
             )
-        if lines_before <= 0:
-            content = log_buffer.get_last_n(10)
-        else:
-            content = log_buffer.get_last_n(lines_before)
+        content = log_buffer.get_last_n(10) if lines_before <= 0 else log_buffer.get_last_n(lines_before)
     else:
         if lines_before > 0:
             content = log_buffer.get_before_timestamp(timestamp=timestamp, lines=lines_before)

src/backend/base/langflow/api/v1/chat.py

@@ -344,20 +344,17 @@ async def build_vertices(
             raise ValueError(msg) from exc
         event_manager.on_end_vertex(data={"build_data": build_data})
         await client_consumed_queue.get()
-        if vertex_build_response.valid:
-            if vertex_build_response.next_vertices_ids:
-                tasks = []
-                for next_vertex_id in vertex_build_response.next_vertices_ids:
-                    task = asyncio.create_task(
-                        build_vertices(next_vertex_id, graph, client_consumed_queue, event_manager)
-                    )
-                    tasks.append(task)
-                try:
-                    await asyncio.gather(*tasks)
-                except asyncio.CancelledError:
-                    for task in tasks:
-                        task.cancel()
-                    return
+        if vertex_build_response.valid and vertex_build_response.next_vertices_ids:
+            tasks = []
+            for next_vertex_id in vertex_build_response.next_vertices_ids:
+                task = asyncio.create_task(build_vertices(next_vertex_id, graph, client_consumed_queue, event_manager))
+                tasks.append(task)
+            try:
+                await asyncio.gather(*tasks)
+            except asyncio.CancelledError:
+                for task in tasks:
+                    task.cancel()
+                return
 
     async def event_generator(event_manager: EventManager, client_consumed_queue: asyncio.Queue) -> None:
         if not data:

src/backend/base/langflow/api/v1/endpoints.py

@@ -95,13 +95,12 @@ def validate_input_and_tweaks(input_request: SimplifiedAPIRequest):
                 if has_input_value and input_value_is_chat:
                     msg = "If you pass an input_value to the chat input, you cannot pass a tweak with the same name."
                     raise InvalidChatInputException(msg)
-        elif "Text Input" in key or "TextInput" in key:
-            if isinstance(value, dict):
-                has_input_value = value.get("input_value") is not None
-                input_value_is_text = input_request.input_value is not None and input_request.input_type == "text"
-                if has_input_value and input_value_is_text:
-                    msg = "If you pass an input_value to the text input, you cannot pass a tweak with the same name."
-                    raise InvalidChatInputException(msg)
+        elif ("Text Input" in key or "TextInput" in key) and isinstance(value, dict):
+            has_input_value = value.get("input_value") is not None
+            input_value_is_text = input_request.input_value is not None and input_request.input_type == "text"
+            if has_input_value and input_value_is_text:
+                msg = "If you pass an input_value to the text input, you cannot pass a tweak with the same name."
+                raise InvalidChatInputException(msg)
 
 
 async def simple_run_flow(

src/backend/base/langflow/api/v1/flows.py

@@ -310,10 +310,7 @@ async def upload_file(
     contents = await file.read()
     data = orjson.loads(contents)
     response_list = []
-    if "flows" in data:
-        flow_list = FlowListCreate(**data)
-    else:
-        flow_list = FlowListCreate(flows=[FlowCreate(**data)])
+    flow_list = FlowListCreate(**data) if "flows" in data else FlowListCreate(flows=[FlowCreate(**data)])
     # Now we set the user_id for all flows
     for flow in flow_list.flows:
         flow.user_id = current_user.id

src/backend/base/langflow/base/agents/crewai/crew.py

@@ -53,10 +53,7 @@ def get_task_callback(
         self,
     ) -> Callable:
         def task_callback(task_output: TaskOutput):
-            if self._vertex:
-                vertex_id = self._vertex.id
-            else:
-                vertex_id = self.display_name or self.__class__.__name__
+            vertex_id = self._vertex.id if self._vertex else self.display_name or self.__class__.__name__
             self.log(task_output.model_dump(), name=f"Task (Agent: {task_output.agent}) - {vertex_id}")
 
         return task_callback

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

@@ -67,10 +67,7 @@ def build_data_from_result_data(result_data: ResultData, get_final_results_only:
     if isinstance(result_data.results, dict):
         for name, result in result_data.results.items():
             dataobj: Data | Message | None = None
-            if isinstance(result, Message):
-                dataobj = result
-            else:
-                dataobj = Data(data=result, text_key=name)
+            dataobj = result if isinstance(result, Message) else Data(data=result, text_key=name)
 
             data.append(dataobj)
     else:

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

@@ -25,12 +25,16 @@ def store_message(
             msg = "Only one message can be stored at a time."
             raise ValueError(msg)
         stored_message = messages[0]
-        if hasattr(self, "_event_manager") and self._event_manager and stored_message.id:
-            if not isinstance(message.text, str):
-                complete_message = self._stream_message(message, stored_message.id)
-                message_table = update_message(message_id=stored_message.id, message={"text": complete_message})
-                stored_message = Message(**message_table.model_dump())
-                self.vertex._added_message = stored_message
+        if (
+            hasattr(self, "_event_manager")
+            and self._event_manager
+            and stored_message.id
+            and not isinstance(message.text, str)
+        ):
+            complete_message = self._stream_message(message, stored_message.id)
+            message_table = update_message(message_id=stored_message.id, message={"text": complete_message})
+            stored_message = Message(**message_table.model_dump())
+            self.vertex._added_message = stored_message
         self.status = stored_message
         return stored_message
 
@@ -77,19 +81,14 @@ def build_with_data(
         session_id: str | None = None,
         return_message: bool | None = False,
     ) -> Message:
-        message: Message | None = None
-
         if isinstance(input_value, Data):
             # Update the data of the record
             message = Message.from_data(input_value)
         else:
             message = Message(
                 text=input_value, sender=sender, sender_name=sender_name, files=files, session_id=session_id
             )
-        if not return_message:
-            message_text = message.text
-        else:
-            message_text = message  # type: ignore
+        message_text = message.text if not return_message else message
 
         self.status = message_text
         if session_id and isinstance(message, Message) and isinstance(message.text, str):

src/backend/base/langflow/components/agents/SequentialTaskAgent.py

@@ -130,10 +130,7 @@ def build_agent_and_task(self) -> list[SequentialTask]:
 
         # If there's a previous task, create a list of tasks
         if self.previous_task:
-            if isinstance(self.previous_task, list):
-                tasks = self.previous_task + [task]
-            else:
-                tasks = [self.previous_task, task]
+            tasks = self.previous_task + [task] if isinstance(self.previous_task, list) else [self.previous_task, task]
         else:
             tasks = [task]
 

src/backend/base/langflow/components/chains/SQLGenerator.py

@@ -28,10 +28,7 @@ class SQLGeneratorComponent(LCChainComponent):
     outputs = [Output(display_name="Text", name="text", method="invoke_chain")]
 
     def invoke_chain(self) -> Message:
-        if self.prompt:
-            prompt_template = PromptTemplate.from_template(template=self.prompt)
-        else:
-            prompt_template = None
+        prompt_template = PromptTemplate.from_template(template=self.prompt) if self.prompt else None
 
         if self.top_k < 1:
             msg = "Top K must be greater than 0."

src/backend/base/langflow/components/data/Gmail.py

@@ -96,10 +96,7 @@ def _extract_email_content(self, msg: Any) -> HumanMessage:
                     msg = "From email not found."
                     raise ValueError(msg)
 
-                if "parts" in msg["payload"]:
-                    parts = msg["payload"]["parts"]
-                else:
-                    parts = [msg["payload"]]
+                parts = msg["payload"]["parts"] if "parts" in msg["payload"] else [msg["payload"]]
 
                 for part in parts:
                     if part["mimeType"] == "text/plain":

src/backend/base/langflow/components/data/GoogleDriveSearch.py

@@ -96,17 +96,13 @@ def generate_file_url(self, file_id: str, mime_type: str) -> str:
         """
         Generates the appropriate Google Drive URL for a file based on its MIME type.
         """
-        if mime_type == "application/vnd.google-apps.document":
-            return f"https://docs.google.com/document/d/{file_id}/edit"
-        if mime_type == "application/vnd.google-apps.spreadsheet":
-            return f"https://docs.google.com/spreadsheets/d/{file_id}/edit"
-        if mime_type == "application/vnd.google-apps.presentation":
-            return f"https://docs.google.com/presentation/d/{file_id}/edit"
-        if mime_type == "application/vnd.google-apps.drawing":
-            return f"https://docs.google.com/drawings/d/{file_id}/edit"
-        if mime_type == "application/pdf":
-            return f"https://drive.google.com/file/d/{file_id}/view?usp=drivesdk"
-        return f"https://drive.google.com/file/d/{file_id}/view?usp=drivesdk"
+        return {
+            "application/vnd.google-apps.document": f"https://docs.google.com/document/d/{file_id}/edit",
+            "application/vnd.google-apps.spreadsheet": f"https://docs.google.com/spreadsheets/d/{file_id}/edit",
+            "application/vnd.google-apps.presentation": f"https://docs.google.com/presentation/d/{file_id}/edit",
+            "application/vnd.google-apps.drawing": f"https://docs.google.com/drawings/d/{file_id}/edit",
+            "application/pdf": f"https://drive.google.com/file/d/{file_id}/view?usp=drivesdk",
+        }.get(mime_type, f"https://drive.google.com/file/d/{file_id}/view?usp=drivesdk")
 
     def search_files(self) -> dict:
         # Load the token information from the JSON string

src/backend/base/langflow/components/embeddings/TextEmbedder.py

@@ -39,10 +39,7 @@ def generate_embeddings(self) -> Data:
         embeddings = embedding_model.embed_documents([text_content])
 
         # Assuming the embedding model returns a list of embeddings, we take the first one
-        if embeddings:
-            embedding_vector = embeddings[0]
-        else:
-            embedding_vector = []
+        embedding_vector = embeddings[0] if embeddings else []
 
         # Create a Data object to encapsulate the results
         result_data = Data(data={"text": text_content, "embeddings": embedding_vector})

src/backend/base/langflow/components/embeddings/util/AIMLEmbeddingsImpl.py

@@ -21,25 +21,24 @@ def embed_documents(self, texts: list[str]) -> list[list[float]]:
             "Authorization": f"Bearer {self.api_key.get_secret_value()}",
         }
 
-        with httpx.Client() as client:
-            with concurrent.futures.ThreadPoolExecutor() as executor:
-                futures = []
-                for i, text in enumerate(texts):
-                    futures.append((i, executor.submit(self._embed_text, client, headers, text)))
-
-                for index, future in futures:
-                    try:
-                        result_data = future.result()
-                        assert len(result_data["data"]) == 1, "Expected one embedding"
-                        embeddings[index] = result_data["data"][0]["embedding"]
-                    except (
-                        httpx.HTTPStatusError,
-                        httpx.RequestError,
-                        json.JSONDecodeError,
-                        KeyError,
-                    ) as e:
-                        logger.error(f"Error occurred: {e}")
-                        raise
+        with httpx.Client() as client, concurrent.futures.ThreadPoolExecutor() as executor:
+            futures = []
+            for i, text in enumerate(texts):
+                futures.append((i, executor.submit(self._embed_text, client, headers, text)))
+
+            for index, future in futures:
+                try:
+                    result_data = future.result()
+                    assert len(result_data["data"]) == 1, "Expected one embedding"
+                    embeddings[index] = result_data["data"][0]["embedding"]
+                except (
+                    httpx.HTTPStatusError,
+                    httpx.RequestError,
+                    json.JSONDecodeError,
+                    KeyError,
+                ) as e:
+                    logger.error(f"Error occurred: {e}")
+                    raise
 
         return embeddings  # type: ignore
 

src/backend/base/langflow/components/langchain_utilities/FirecrawlCrawlApi.py

@@ -61,15 +61,9 @@ def build(
                 "Could not import firecrawl integration package. " "Please install it with `pip install firecrawl-py`."
             )
             raise ImportError(msg)
-        if crawlerOptions:
-            crawler_options_dict = crawlerOptions.__dict__["data"]["text"]
-        else:
-            crawler_options_dict = {}
+        crawler_options_dict = crawlerOptions.__dict__["data"]["text"] if crawlerOptions else {}
 
-        if pageOptions:
-            page_options_dict = pageOptions.__dict__["data"]["text"]
-        else:
-            page_options_dict = {}
+        page_options_dict = pageOptions.__dict__["data"]["text"] if pageOptions else {}
 
         if not idempotency_key:
             idempotency_key = str(uuid.uuid4())

src/backend/base/langflow/components/langchain_utilities/FirecrawlScrapeApi.py

@@ -54,15 +54,9 @@ def build(
                 "Could not import firecrawl integration package. " "Please install it with `pip install firecrawl-py`."
             )
             raise ImportError(msg)
-        if extractorOptions:
-            extractor_options_dict = extractorOptions.__dict__["data"]["text"]
-        else:
-            extractor_options_dict = {}
+        extractor_options_dict = extractorOptions.__dict__["data"]["text"] if extractorOptions else {}
 
-        if pageOptions:
-            page_options_dict = pageOptions.__dict__["data"]["text"]
-        else:
-            page_options_dict = {}
+        page_options_dict = pageOptions.__dict__["data"]["text"] if pageOptions else {}
 
         app = FirecrawlApp(api_key=api_key)
         results = app.scrape_url(

src/backend/base/langflow/components/models/AIMLModel.py

@@ -79,10 +79,7 @@ def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         aiml_api_base = self.aiml_api_base or "https://api.aimlapi.com"
         seed = self.seed
 
-        if isinstance(aiml_api_key, SecretStr):
-            openai_api_key = aiml_api_key.get_secret_value()
-        else:
-            openai_api_key = aiml_api_key
+        openai_api_key = aiml_api_key.get_secret_value() if isinstance(aiml_api_key, SecretStr) else aiml_api_key
 
         return ChatOpenAI(
             model=model_name,

src/backend/base/langflow/components/models/CohereModel.py

@@ -36,10 +36,7 @@ def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         cohere_api_key = self.cohere_api_key
         temperature = self.temperature
 
-        if cohere_api_key:
-            api_key = SecretStr(cohere_api_key)
-        else:
-            api_key = None
+        api_key = SecretStr(cohere_api_key) if cohere_api_key else None
 
         return ChatCohere(
             temperature=temperature or 0.75,

src/backend/base/langflow/components/models/MistralModel.py

@@ -78,10 +78,7 @@ def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         random_seed = self.random_seed
         safe_mode = self.safe_mode
 
-        if mistral_api_key:
-            api_key = SecretStr(mistral_api_key)
-        else:
-            api_key = None
+        api_key = SecretStr(mistral_api_key) if mistral_api_key else None
 
         return ChatMistralAI(
             max_tokens=max_tokens or None,

src/backend/base/langflow/components/models/OpenAIModel.py

@@ -102,10 +102,7 @@ def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         json_mode = bool(output_schema_dict) or self.json_mode
         seed = self.seed
 
-        if openai_api_key:
-            api_key = SecretStr(openai_api_key)
-        else:
-            api_key = None
+        api_key = SecretStr(openai_api_key) if openai_api_key else None
         output = ChatOpenAI(
             max_tokens=max_tokens or None,
             model_kwargs=model_kwargs,

src/backend/base/langflow/components/output_parsers/OutputParser.py

@@ -34,11 +34,11 @@ class OutputParserComponent(Component):
     def build_parser(self) -> OutputParser:
         if self.parser_type == "CSV":
             return CommaSeparatedListOutputParser()
-        else:
-            raise ValueError("Unsupported or missing parser")
+        msg = "Unsupported or missing parser"
+        raise ValueError(msg)
 
     def format_instructions(self) -> Message:
         if self.parser_type == "CSV":
             return Message(text=CommaSeparatedListOutputParser().get_format_instructions())
-        else:
-            raise ValueError("Unsupported or missing parser")
+        msg = "Unsupported or missing parser"
+        raise ValueError(msg)

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

@@ -57,7 +57,7 @@ def add_inputs_to_build_config(self, inputs_vertex: list[Vertex], build_config:
         for vertex in inputs_vertex:
             new_vertex_inputs = []
             field_template = vertex.data["node"]["template"]
-            for inp in field_template.keys():
+            for inp in field_template:
                 if inp not in ["code", "_type"]:
                     field_template[inp]["display_name"] = (
                         vertex.display_name + " - " + field_template[inp]["display_name"]
@@ -84,10 +84,10 @@ def add_inputs_to_build_config(self, inputs_vertex: list[Vertex], build_config:
 
     async def generate_results(self) -> list[Data]:
         tweaks: dict = {}
-        for field in self._attributes.keys():
+        for field in self._attributes:
             if field != "flow_name":
                 [node, name] = field.split("|")
-                if node not in tweaks.keys():
+                if node not in tweaks:
                     tweaks[node] = {}
                 tweaks[node][name] = self._attributes[field]
         flow_name = self._attributes.get("flow_name")