build: Bump ruff version to 0.9.7 (#6614)

* Bump ruff version to 0.9.7

* [autofix.ci] apply automated fixes

* refactor: Update Gmail Agent starter project to Langflow 1.2.0

This commit updates the Gmail Agent starter project with new node IDs and configuration reflecting Langflow version 1.2.0. Changes include:
- Updated node identifiers for Agent, ChatInput, ChatOutput, and ComposioAPI
- Refreshed project metadata and version information
- Minor adjustments to node configurations and viewport settings

* [autofix.ci] apply automated fixes

* fix: Revert Gmail Agent name to original

* fix: Remove trailing comma in Gmail Agent JSON

* feat: Add tags to Gmail Agent starter project

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

.github/workflows/py_autofix.yml

@@ -14,7 +14,7 @@ jobs:
       - uses: actions/checkout@v4
       - name: "Setup Environment"
         uses: ./.github/actions/setup-uv
-      - run: uv run ruff check --fix-only . --ignore A005
+      - run: uv run ruff check --fix-only .
       - run: uv run ruff format . --config pyproject.toml
       - uses: autofix-ci/action@551dded8c6cc8a1054039c8bc0b8b48c51dfc6ef
       - name: Minimize uv cache

.github/workflows/style-check-py.yml

@@ -24,6 +24,6 @@ jobs:
       - name: Register problem matcher
         run: echo "::add-matcher::.github/workflows/matchers/ruff.json"
       - name: Run Ruff Check
-        run: uv run --only-dev ruff check --output-format=github . --ignore A005
+        run: uv run --only-dev ruff check --output-format=github .
       - name: Minimize uv cache
         run: uv cache prune --ci

Makefile

@@ -198,7 +198,7 @@ fix_codespell: ## run codespell to fix spelling errors
 	poetry run codespell --toml pyproject.toml --write
 
 format_backend: ## backend code formatters
-	@uv run ruff check . --fix --ignore EXE002 --ignore A005
+	@uv run ruff check . --fix
 	@uv run ruff format . --config pyproject.toml
 
 format_frontend: ## frontend code formatters

pyproject.toml

@@ -121,7 +121,7 @@ dev = [
     "types-redis>=4.6.0.5",
     "ipykernel>=6.29.0",
     "mypy>=1.11.0",
-    "ruff>=0.9.1,<0.10",
+    "ruff>=0.9.7,<0.10",
     "httpx>=0.27.0",
     "pytest>=8.2.0",
     "types-requests>=2.32.0",

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

@@ -580,14 +580,14 @@ async def experimental_run_flow(
 
 
 @router.post(
-    "/predict/{flow_id}",
+    "/predict/{_flow_id}",
     dependencies=[Depends(api_key_security)],
 )
 @router.post(
-    "/process/{flow_id}",
+    "/process/{_flow_id}",
     dependencies=[Depends(api_key_security)],
 )
-async def process() -> None:
+async def process(_flow_id) -> None:
     """Endpoint to process an input with a given flow_id."""
     # Raise a depreciation warning
     logger.warning(

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

@@ -0,0 +1 @@
+# noqa: A005

src/backend/base/langflow/components/apify/apify_actor.py

@@ -89,9 +89,9 @@ class ApifyActorsComponent(Component):
 
     def run_model(self) -> list[Data]:
         """Run the Actor and return node output."""
-        _input = json.loads(self.run_input)
+        input_ = json.loads(self.run_input)
         fields = ApifyActorsComponent.parse_dataset_fields(self.dataset_fields) if self.dataset_fields else None
-        res = self._run_actor(self.actor_id, _input, fields=fields)
+        res = self._run_actor(self.actor_id, input_, fields=fields)
         if self.flatten_dataset:
             res = [ApifyActorsComponent.flatten(item) for item in res]
         data = [Data(data=item) for item in res]
@@ -113,16 +113,16 @@ class ApifyActorsComponent(Component):
         properties = {"run_input": properties}
 
         # works from input schema
-        _info = [
+        info_ = [
             (
                 "JSON encoded as a string with input schema (STRICTLY FOLLOW JSON FORMAT AND SCHEMA):\n\n"
                 f"{json.dumps(properties, separators=(',', ':'))}"
             )
         ]
         if required:
-            _info.append("\n\nRequired fields:\n" + "\n".join(required))
+            info_.append("\n\nRequired fields:\n" + "\n".join(required))
 
-        info = "".join(_info)
+        info = "".join(info_)
 
         input_model_cls = ApifyActorsComponent.create_input_model_class(info)
         tool_cls = ApifyActorsComponent.create_tool_class(self, readme, input_model_cls, actor_id)

src/backend/base/langflow/components/composio/composio_api.py

@@ -158,7 +158,7 @@ class ComposioAPIComponent(LCToolComponent):
 
             for item in data.get("items", []):
                 for auth_scheme in item.get("auth_schemes", []):
-                    if auth_scheme.get("mode") in ["OAUTH1", "OAUTH2"]:
+                    if auth_scheme.get("mode") in {"OAUTH1", "OAUTH2"}:
                         oauth_apps.append(item["key"].upper())
                         break
         except requests.RequestException as e:

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

@@ -321,7 +321,7 @@ class APIRequestComponent(Component):
                 elif field_name == "curl":
                     field_config["advanced"] = not use_curl
                     field_config["real_time_refresh"] = use_curl
-                elif field_name in ["body", "headers"]:
+                elif field_name in {"body", "headers"}:
                     field_config["advanced"] = True  # Always keep body and headers in advanced when use_curl is False
                 else:
                     field_config["advanced"] = use_curl
@@ -359,7 +359,7 @@ class APIRequestComponent(Component):
                 if field_name in common_fields:
                     field_config["advanced"] = False
                 elif field_name in body_fields:
-                    field_config["advanced"] = method not in ["POST", "PUT", "PATCH"]
+                    field_config["advanced"] = method not in {"POST", "PUT", "PATCH"}
                 elif field_name in always_advanced_fields:
                     field_config["advanced"] = True
                 else:

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

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import operator
 from typing import TYPE_CHECKING, Any
 
 from loguru import logger
@@ -165,7 +166,7 @@ class BatchRunComponent(Component):
             ]
 
             # Sort by index to maintain order
-            responses_with_idx.sort(key=lambda x: x[0])
+            responses_with_idx.sort(key=operator.itemgetter(0))
 
             # Build the final data with enhanced metadata
             rows: list[dict[str, Any]] = []

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

@@ -138,7 +138,7 @@ class AnthropicModelComponent(LCModelComponent):
         return None
 
     def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):
-        if field_name in ("base_url", "model_name", "tool_model_enabled", "api_key") and field_value:
+        if field_name in {"base_url", "model_name", "tool_model_enabled", "api_key"} and field_value:
             try:
                 if len(self.api_key) == 0:
                     ids = ANTHROPIC_MODELS

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

@@ -129,7 +129,7 @@ class GoogleGenerativeAIComponent(LCModelComponent):
         return model_ids
 
     def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):
-        if field_name in ("base_url", "model_name", "tool_model_enabled", "api_key") and field_value:
+        if field_name in {"base_url", "model_name", "tool_model_enabled", "api_key"} and field_value:
             try:
                 if len(self.api_key) == 0:
                     ids = GOOGLE_GENERATIVE_AI_MODELS

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

@@ -105,7 +105,7 @@ class GroqModel(LCModelComponent):
         return model_ids
 
     def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
-        if field_name in ("base_url", "model_name", "tool_model_enabled", "api_key") and field_value:
+        if field_name in {"base_url", "model_name", "tool_model_enabled", "api_key"} and field_value:
             try:
                 if len(self.api_key) != 0:
                     try:

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

@@ -78,7 +78,7 @@ class NVIDIAModelComponent(LCModelComponent):
         return [model.id for model in build_model.available_models]
 
     def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):
-        if field_name in ("base_url", "model_name", "tool_model_enabled", "api_key") and field_value:
+        if field_name in {"base_url", "model_name", "tool_model_enabled", "api_key"} and field_value:
             try:
                 ids = self.get_models(self.tool_model_enabled)
                 build_config["model_name"]["options"] = ids

src/backend/base/langflow/components/nvidia/nvidia_ingest.py

@@ -231,5 +231,5 @@ class NvidiaIngestComponent(Component):
                     # image is not yet supported; skip if encountered
                     self.log(f"Unsupported document type: {document_type}", name="NVIDIAIngestComponent")
 
-        self.status = data if data else "No data"
+        self.status = data or "No data"
         return data

src/backend/base/langflow/components/processing/save_to_file.py

@@ -87,7 +87,7 @@ class SaveToFileComponent(Component):
             build_config["data"]["show"] = field_value == "Data"
             build_config["message"]["show"] = field_value == "Message"
 
-            if field_value in ["DataFrame", "Data"]:
+            if field_value in {"DataFrame", "Data"}:
                 build_config["file_format"]["options"] = self.DATA_FORMAT_CHOICES
             elif field_value == "Message":
                 build_config["file_format"]["options"] = self.MESSAGE_FORMAT_CHOICES

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

@@ -112,7 +112,7 @@ class ArXivComponent(Component):
 
             # Validate URL scheme and host
             parsed_url = urlparse(url)
-            if parsed_url.scheme not in ("http", "https"):
+            if parsed_url.scheme not in {"http", "https"}:
                 error_msg = f"Invalid URL scheme: {parsed_url.scheme}"
                 raise ValueError(error_msg)
             if parsed_url.hostname != "export.arxiv.org":

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

@@ -571,7 +571,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         # Go over each possible provider and add metadata to configure in Astra DB Portal
         for provider in provider_options:
             # Skip Bring your own and Nvidia, automatically configured
-            if provider in ["Bring your own", "Nvidia"]:
+            if provider in {"Bring your own", "Nvidia"}:
                 build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
                     "embedding_generation_provider"
                 ]["options_metadata"].append({"icon": self.get_provider_icon(provider_name=provider.lower())})
@@ -601,7 +601,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         # If we retrieved options based on the token, show the dropdown
         build_config["collection_name"]["options"] = [col["name"] for col in collection_options]
         build_config["collection_name"]["options_metadata"] = [
-            {k: v for k, v in col.items() if k not in ["name"]} for col in collection_options
+            {k: v for k, v in col.items() if k != "name"} for col in collection_options
         ]
 
         # Reset the selected collection
@@ -620,7 +620,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         # If we retrieved options based on the token, show the dropdown
         build_config["database_name"]["options"] = [db["name"] for db in database_options]
         build_config["database_name"]["options_metadata"] = [
-            {k: v for k, v in db.items() if k not in ["name"]} for db in database_options
+            {k: v for k, v in db.items() if k != "name"} for db in database_options
         ]
 
         # Reset the selected database
@@ -667,12 +667,8 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
                 raise ValueError(msg) from e
 
             # Add the new database to the list of options
-            build_config["database_name"]["options"] = build_config["database_name"]["options"] + [
-                field_value["new_database_name"]
-            ]
-            build_config["database_name"]["options_metadata"] = build_config["database_name"]["options_metadata"] + [
-                {"status": "PENDING"}
-            ]
+            build_config["database_name"]["options"] += [field_value["new_database_name"]]
+            build_config["database_name"]["options_metadata"] += [{"status": "PENDING"}]
 
             return self.reset_collection_list(build_config)
 
@@ -726,9 +722,9 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
 
             # Add the new collection to the list of options
             icon = "NVIDIA" if provider == "Nvidia" else "vectorstores"
-            build_config["collection_name"]["options_metadata"] = build_config["collection_name"][
-                "options_metadata"
-            ] + [{"records": 0, "provider": provider, "icon": icon, "model": model}]
+            build_config["collection_name"]["options_metadata"] += [
+                {"records": 0, "provider": provider, "icon": icon, "model": model}
+            ]
 
             return build_config
 
@@ -748,7 +744,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             return self.reset_build_config(build_config)
 
         # If this is the first execution of the component, reset and build database list
-        if first_run or field_name in ["token", "environment"]:
+        if first_run or field_name in {"token", "environment"}:
             return self.reset_database_list(build_config)
 
         # Refresh the collection name options
@@ -790,7 +786,12 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
                 # Add the new collection to the list of options
                 build_config["collection_name"]["options"].append(field_value)
                 build_config["collection_name"]["options_metadata"].append(
-                    {"records": 0, "provider": None, "icon": "", "model": None}
+                    {
+                        "records": 0,
+                        "provider": None,
+                        "icon": "",
+                        "model": None,
+                    }
                 )
 
                 # Ensure that autodetect collection is set to False, since its a new collection

src/backend/base/langflow/components/youtube/video_details.py

@@ -230,7 +230,7 @@ class YouTubeVideoDetailsComponent(Component):
                 thumb_cols = [col for col in video_df.columns if col.startswith("thumbnail_")]
 
                 # Reorder columns based on what's included
-                ordered_cols = basic_cols[:]
+                ordered_cols = basic_cols.copy()
 
                 if self.include_statistics:
                     ordered_cols.extend([col for col in stat_cols if col in video_df.columns])

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

@@ -518,7 +518,7 @@ def layered_topological_sort(
 
     layers: list[list[str]] = []
     visited = set()
-    cycle_counts = {vertex: 0 for vertex in vertices_ids}
+    cycle_counts = dict.fromkeys(vertices_ids, 0)
     current_layer = 0
 
     # Process the first layer separately to avoid duplicates

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

@@ -322,7 +322,7 @@ def json_schema_from_flow(flow: Flow) -> dict:
     from langflow.graph.graph.base import Graph
 
     # Get the flow's data which contains the nodes and their configurations
-    flow_data = flow.data if flow.data else {}
+    flow_data = flow.data or {}
 
     graph = Graph.from_payload(flow_data)
     input_nodes = [vertex for vertex in graph.vertices if vertex.is_input]

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

@@ -1,3 +1,4 @@
+# noqa: A005
 from langflow.inputs import (
     BoolInput,
     CodeInput,

src/backend/base/langflow/logging/__init__.py

@@ -1,3 +1,4 @@
+# noqa: A005
 from .logger import configure, logger
 from .setup import disable_logging, enable_logging
 

src/backend/base/langflow/serialization/serialization.py

@@ -145,7 +145,7 @@ def _serialize_numpy_type(obj: Any, max_length: int | None, max_items: int | Non
     if np.issubdtype(obj.dtype, np.bool_):
         return bool(obj)
     if np.issubdtype(obj.dtype, np.complexfloating):
-        return complex(cast(complex, obj))
+        return complex(cast("complex", obj))
     if np.issubdtype(obj.dtype, np.str_):
         return _serialize_str(str(obj), max_length, max_items)
     if np.issubdtype(obj.dtype, np.bytes_) and hasattr(obj, "tobytes"):
@@ -209,7 +209,7 @@ def _serialize_dispatcher(obj: Any, max_length: int | None, max_items: int | Non
                 if np.issubdtype(obj.dtype, np.bool_):
                     return bool(obj)
                 if np.issubdtype(obj.dtype, np.complexfloating):
-                    return complex(cast(complex, obj))
+                    return complex(cast("complex", obj))
                 if np.issubdtype(obj.dtype, np.str_):
                     return str(obj)
                 if np.issubdtype(obj.dtype, np.bytes_) and hasattr(obj, "tobytes"):

src/backend/base/langflow/services/job_queue/service.py

@@ -203,7 +203,7 @@ class JobQueueService(Service):
             return
 
         logger.info(f"Commencing cleanup for job_id {job_id}")
-        main_queue, event_manager, task = self._queues[job_id]
+        main_queue, _event_manager, task = self._queues[job_id]
 
         # Cancel the associated task if it is still running.
         if task and not task.done():

src/backend/base/langflow/services/socket/__init__.py

@@ -0,0 +1 @@
+# noqa: A005

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

@@ -93,7 +93,7 @@ class TelemetryService(Service):
 
     def _get_langflow_desktop(self) -> bool:
         # Coerce to bool, could be 1, 0, True, False, "1", "0", "True", "False"
-        return str(os.getenv("LANGFLOW_DESKTOP", "False")).lower() in ("1", "true")
+        return str(os.getenv("LANGFLOW_DESKTOP", "False")).lower() in {"1", "true"}
 
     async def log_package_version(self) -> None:
         python_version = ".".join(platform.python_version().split(".")[:2])

src/backend/tests/unit/api/v1/test_endpoints.py

@@ -57,7 +57,7 @@ async def test_update_component_outputs(client: AsyncClient, logged_in_headers:
 async def test_update_component_model_name_options(client: AsyncClient, logged_in_headers: dict):
     """Test that model_name options are updated when selecting a provider."""
     component = AgentComponent()
-    component_node, cc_instance = build_custom_component_template(
+    component_node, _cc_instance = build_custom_component_template(
         component,
     )
 

src/backend/tests/unit/components/vectorstores/test_chroma_vector_store_component.py

@@ -271,9 +271,9 @@ class TestChromaVectorStoreComponent(ComponentTestBaseWithoutClient):
             assert isinstance(data_obj, Data)
             assert "id" in data_obj.data
             assert "text" in data_obj.data
-            assert data_obj.data["text"] in ["Document 1", "Document 2"]
+            assert data_obj.data["text"] in {"Document 1", "Document 2"}
             assert "metadata_field" in data_obj.data
-            assert data_obj.data["metadata_field"] in ["value1", "value2"]
+            assert data_obj.data["metadata_field"] in {"value1", "value2"}
 
     def test_chroma_collection_to_data_without_metadata(
         self, component_class: type[ChromaVectorStoreComponent], default_kwargs: dict[str, Any]
@@ -300,7 +300,7 @@ class TestChromaVectorStoreComponent(ComponentTestBaseWithoutClient):
             assert isinstance(data_obj, Data)
             assert "id" in data_obj.data
             assert "text" in data_obj.data
-            assert data_obj.data["text"] in ["Simple document 1", "Simple document 2"]
+            assert data_obj.data["text"] in {"Simple document 1", "Simple document 2"}
 
     def test_chroma_collection_to_data_empty_collection(
         self, component_class: type[ChromaVectorStoreComponent], default_kwargs: dict[str, Any]

src/backend/tests/unit/graph/graph/test_utils.py

@@ -869,7 +869,7 @@ def test_get_sorted_vertices_with_unconnected_graph():
     predecessor_map = {vertex: data["predecessors"] for vertex, data in graph_dict.items()}
 
     def is_input_vertex(vertex_id: str) -> bool:
-        return vertex_id in ["A"]
+        return vertex_id == "A"
 
     def get_vertex_predecessors(vertex_id: str) -> list[str]:
         return predecessor_map[vertex_id]

src/backend/tests/unit/serialization/test_serialization.py

@@ -263,13 +263,13 @@ class TestSerializationHypothesis:
         assert isinstance(serialize(np.uint64(42)), int)
 
         # Test floats
-        assert serialize(np.float64(3.14)) == 3.14
-        assert isinstance(serialize(np.float64(3.14)), float)
+        assert serialize(np.float64(math.pi)) == math.pi
+        assert isinstance(serialize(np.float64(math.pi)), float)
 
         # Test float32 (need to account for precision differences)
-        float32_val = serialize(np.float32(3.14))
+        float32_val = serialize(np.float32(math.pi))
         assert isinstance(float32_val, float)
-        assert abs(float32_val - 3.14) < 1e-6  # Check if close enough
+        assert abs(float32_val - math.pi) < 1e-6  # Check if close enough
 
         # Test bool
         assert serialize(np.bool_(True)) is True  # noqa: FBT003

uv.lock

@@ -4544,7 +4544,7 @@ dev = [
     { name = "pytest-xdist", specifier = ">=3.6.0" },
     { name = "requests", specifier = ">=2.32.0" },
     { name = "respx", specifier = ">=0.21.1" },
-    { name = "ruff", specifier = ">=0.9.1,<0.10" },
+    { name = "ruff", specifier = ">=0.9.7,<0.10" },
     { name = "types-aiofiles", specifier = ">=24.1.0.20240626" },
     { name = "types-google-cloud-ndb", specifier = ">=2.2.0.0" },
     { name = "types-markdown", specifier = ">=3.7.0.20240822" },