chore: pre-commit

examples/agriculture-demo.py

@@ -15,12 +15,6 @@
 import argparse
 
 import rclpy
-from rclpy.action import ActionClient
-from rclpy.callback_groups import ReentrantCallbackGroup
-from rclpy.executors import MultiThreadedExecutor
-from rclpy.node import Node
-from std_srvs.srv import Trigger
-
 from rai.node import RaiStateBasedLlmNode, describe_ros_image
 from rai.tools.ros.native import (
     GetCameraImage,
@@ -30,6 +24,12 @@
     Ros2ShowMsgInterfaceTool,
 )
 from rai.tools.time import WaitForSecondsTool
+from rclpy.action import ActionClient
+from rclpy.callback_groups import ReentrantCallbackGroup
+from rclpy.executors import MultiThreadedExecutor
+from rclpy.node import Node
+from std_srvs.srv import Trigger
+
 from rai_interfaces.action import Task
 
 

examples/manipulation-demo-streamlit.py

@@ -16,7 +16,6 @@
 
 import streamlit as st
 from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
-
 from rai.agents.integrations.streamlit import get_streamlit_cb, streamlit_invoke
 from rai.messages import HumanMultimodalMessage
 

examples/manipulation-demo.py

@@ -17,7 +17,6 @@
 import rclpy
 import rclpy.qos
 from langchain_core.messages import HumanMessage
-
 from rai.agents.conversational_agent import create_conversational_agent
 from rai.node import RaiBaseNode
 from rai.tools.ros.manipulation import GetObjectPositionsTool, MoveToPointTool

examples/rosbot-xl-demo.py

@@ -18,8 +18,6 @@
 import rclpy
 import rclpy.executors
 import rclpy.logging
-from rai_open_set_vision.tools import GetDetectionTool, GetDistanceToObjectsTool
-
 from rai.node import RaiStateBasedLlmNode
 from rai.tools.ros.native import (
     GetMsgFromTopic,
@@ -35,6 +33,7 @@
     Ros2RunActionAsync,
 )
 from rai.tools.time import WaitForSecondsTool
+from rai_open_set_vision.tools import GetDetectionTool, GetDistanceToObjectsTool
 
 p = argparse.ArgumentParser()
 p.add_argument("--allowlist", type=Path, required=False, default=None)

examples/taxi-demo.py

@@ -20,12 +20,12 @@
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_core.messages import BaseMessage, HumanMessage
 from langchain_core.tools import tool
-from std_msgs.msg import String
-
 from rai.agents.conversational_agent import create_conversational_agent
 from rai.tools.ros.cli import Ros2ServiceTool
 from rai.tools.ros.native import Ros2PubMessageTool
 from rai.utils.model_initialization import get_llm_model, get_tracing_callbacks
+from std_msgs.msg import String
+
 from rai_hmi.api import GenericVoiceNode, split_message
 
 system_prompt = """

src/examples/turtlebot4/turtlebot_demo.py

@@ -23,7 +23,6 @@
 import rclpy.qos
 import rclpy.subscription
 import rclpy.task
-
 from rai.node import RaiStateBasedLlmNode
 from rai.tools.ros.native import (
     GetCameraImage,

src/rai_asr/pyproject.toml

@@ -27,4 +27,4 @@ faster-whisper = "^1.1.1"
 pydub = "^0.25.1"
 
 [tool.isort]
-profile = "black"
+profile = "black"

src/rai_asr/rai_asr/models/__init__.py

@@ -19,10 +19,10 @@
 from rai_asr.models.silero_vad import SileroVAD
 
 __all__ = [
-    "BaseVoiceDetectionModel",
-    "SileroVAD",
-    "OpenWakeWord",
     "BaseTranscriptionModel",
+    "BaseVoiceDetectionModel",
     "LocalWhisper",
     "OpenAIWhisper",
+    "OpenWakeWord",
+    "SileroVAD",
 ]

src/rai_asr/rai_asr/models/base.py

@@ -21,7 +21,6 @@
 
 
 class BaseVoiceDetectionModel(ABC):
-
     def __call__(
         self, audio_data: NDArray, input_parameters: dict[str, Any]
     ) -> Tuple[bool, dict[str, Any]]:

src/rai_core/pyproject.toml

@@ -32,4 +32,4 @@ tomli = "^2.0.1"
 tomli-w = "^1.1.0"
 
 [tool.isort]
-profile = "black" 
+profile = "black"

src/rai_core/rai/agents/__init__.py

@@ -19,7 +19,7 @@
 
 __all__ = [
     "ToolRunner",
+    "VoiceRecognitionAgent",
     "create_conversational_agent",
     "create_state_based_agent",
-    "VoiceRecognitionAgent",
 ]

src/rai_core/rai/agents/integrations/streamlit.py

@@ -125,7 +125,7 @@ def on_tool_end(self, output: Any, **kwargs: Any) -> Any:
 
     # Decorator function to add the Streamlit execution context to a function
     def add_streamlit_context(
-        fn: Callable[..., fn_return_type]
+        fn: Callable[..., fn_return_type],
     ) -> Callable[..., fn_return_type]:
         """
         Decorator to ensure that the decorated function runs within the Streamlit execution context.

src/rai_core/rai/agents/voice_agent.py

@@ -187,7 +187,9 @@ def should_record(
     def transcription_thread(self, identifier: str):
         self.logger.info(f"transcription thread {identifier} started")
         audio_data = np.concatenate(self.transcription_buffers[identifier])
-        with self.transcription_lock:  # this is only necessary for the local model... TODO: fix this somehow
+        with (
+            self.transcription_lock
+        ):  # this is only necessary for the local model... TODO: fix this somehow
             transcription = self.transcription_model.transcribe(audio_data)
         assert isinstance(self.connectors["ros2"], ROS2ARIConnector)
         self.connectors["ros2"].send_message(

src/rai_core/rai/apps/state_analyzer.py

@@ -39,7 +39,6 @@ def robot_state_analyzer(
     state: str,
     state_analyzer_prompt: str = STATE_ANALYZER_PROMPT,
 ) -> State:
-
     template = ChatPromptTemplate.from_messages(
         [
             ("system", state_analyzer_prompt),

src/rai_core/rai/apps/talk_to_docs.py

@@ -78,7 +78,9 @@ def talk_to_docs(documentation_root: str, llm: BaseChatModel):
 
     agent = create_tool_calling_agent(llm, [query_docs], prompt)  # type: ignore
     agent_executor = AgentExecutor(
-        agent=agent, tools=[query_docs], return_intermediate_steps=True  # type: ignore
+        agent=agent,
+        tools=[query_docs],
+        return_intermediate_steps=True,  # type: ignore
     )
 
     def input_node(state: State) -> State:

src/rai_core/rai/communication/__init__.py

@@ -25,8 +25,8 @@
 __all__ = [
     "ARIConnector",
     "ARIMessage",
-    "BaseMessage",
     "BaseConnector",
+    "BaseMessage",
     "HRIConnector",
     "HRIMessage",
     "HRIPayload",

src/rai_core/rai/communication/base_connector.py

@@ -39,7 +39,6 @@ def __init__(
 
 
 class BaseConnector(Generic[T]):
-
     def _generate_handle(self) -> str:
         return str(uuid4())
 

src/rai_core/rai/communication/hri_connector.py

@@ -17,9 +17,8 @@
 from io import BytesIO
 from typing import Any, Dict, Generic, Literal, Optional, Sequence, TypeVar, get_args
 
-from langchain_core.messages import AIMessage
+from langchain_core.messages import AIMessage, HumanMessage
 from langchain_core.messages import BaseMessage as LangchainBaseMessage
-from langchain_core.messages import HumanMessage
 from PIL import Image
 from PIL.Image import Image as ImageType
 from pydub import AudioSegment
@@ -166,7 +165,6 @@ def _build_message(
         self,
         message: LangchainBaseMessage | RAIMultimodalMessage,
     ) -> T:
-
         return self.T_class.from_langchain(message)
 
     def send_all_targets(self, message: LangchainBaseMessage | RAIMultimodalMessage):

src/rai_core/rai/communication/ros2/api.py

@@ -334,7 +334,6 @@ def __post_init__(self):
 
 
 class ConfigurableROS2TopicAPI(ROS2TopicAPI):
-
     def __init__(self, node: rclpy.node.Node):
         super().__init__(node)
         self._subscribtions: dict[str, rclpy.node.Subscription] = {}
@@ -562,7 +561,7 @@ def is_goal_done(self, handle: str) -> bool:
             raise ValueError(f"Invalid action handle: {handle}")
         if self.actions[handle]["result_future"] is None:
             raise ValueError(
-                f"Result future is None for handle: {handle}. " "Was the goal accepted?"
+                f"Result future is None for handle: {handle}. Was the goal accepted?"
             )
         return self.actions[handle]["result_future"].done()
 

src/rai_core/rai/communication/ros2/connectors.py

@@ -76,7 +76,6 @@ def send_message(
         qos_profile: Optional[QoSProfile] = None,
         **kwargs: Any,
     ):
-
         self._topic_api.publish(
             topic=target,
             msg_content=message.payload,

src/rai_core/rai/communication/sound_device/__init__.py

@@ -18,6 +18,6 @@
 __all__ = [
     "SoundDeviceAPI",
     "SoundDeviceConfig",
-    "SoundDeviceError",
     "SoundDeviceConnector",
+    "SoundDeviceError",
 ]

src/rai_core/rai/communication/sound_device/api.py

@@ -49,7 +49,6 @@ def __post_init__(self):
 
 
 class SoundDeviceAPI:
-
     def __init__(self, config: SoundDeviceConfig):
         self.device_name = ""
 

src/rai_core/rai/messages/__init__.py

@@ -23,10 +23,10 @@
 from .utils import preprocess_image
 
 __all__ = [
-    "HumanMultimodalMessage",
     "AiMultimodalMessage",
+    "HumanMultimodalMessage",
+    "MultimodalArtifact",
     "SystemMultimodalMessage",
     "ToolMultimodalMessage",
-    "MultimodalArtifact",
     "preprocess_image",
 ]

src/rai_core/rai/messages/multimodal.py

@@ -72,7 +72,7 @@ def __repr_args__(self) -> Any:
                 v = [c for c in v if c["type"] != "image_url"]
             elif k == "images":
                 imgs_summary = [image[0:10] + "..." for image in v]
-                v = f'{len(v)} base64 encoded images: [{", ".join(imgs_summary)}]'
+                v = f"{len(v)} base64 encoded images: [{', '.join(imgs_summary)}]"
             new_args.append((k, v))
         return new_args
 

src/rai_core/rai/node.py

@@ -303,7 +303,6 @@ async def agent_loop(self, goal_handle: ServerGoalHandle):
                     "callbacks": get_tracing_callbacks(),
                 },
             ):
-
                 graph_node_name = list(state.keys())[0]
                 if graph_node_name == "reporter":
                     continue

src/rai_core/rai/tools/ros/__init__.py

@@ -29,15 +29,15 @@
 )
 
 __all__ = [
+    "AddDescribedWaypointToDatabaseTool",
+    "GetCurrentPositionTool",
+    "GetOccupancyGridTool",
+    "Ros2BaseInput",
+    "Ros2BaseTool",
     "ros2_action",
     "ros2_interface",
     "ros2_node",
-    "ros2_topic",
     "ros2_param",
     "ros2_service",
-    "Ros2BaseTool",
-    "Ros2BaseInput",
-    "AddDescribedWaypointToDatabaseTool",
-    "GetOccupancyGridTool",
-    "GetCurrentPositionTool",
+    "ros2_topic",
 ]

src/rai_core/rai/tools/ros/deprecated.py

@@ -104,7 +104,9 @@ def __init__(
 
     def postprocess(self, msg: Image) -> str:
         bridge = CvBridge()
-        cv_image = cast(cv2.Mat, bridge.imgmsg_to_cv2(msg, desired_encoding="passthrough"))  # type: ignore
+        cv_image = cast(
+            cv2.Mat, bridge.imgmsg_to_cv2(msg, desired_encoding="passthrough")
+        )  # type: ignore
         if cv_image.shape[-1] == 4:
             cv_image = cv2.cvtColor(cv_image, cv2.COLOR_BGRA2RGB)
             base64_image = base64.b64encode(

src/rai_core/rai/tools/ros/native_actions.py

@@ -60,9 +60,7 @@ class Ros2BaseActionTool(Ros2BaseTool):
 
 class Ros2RunActionSync(Ros2BaseTool):
     name: str = "Ros2RunAction"
-    description: str = (
-        "A tool for running a ros2 action. Make sure you know the action interface first!!! Actions might take some time to execute and are blocking - you will not be able to check their feedback, only will be informed about the result"
-    )
+    description: str = "A tool for running a ros2 action. Make sure you know the action interface first!!! Actions might take some time to execute and are blocking - you will not be able to check their feedback, only will be informed about the result"
 
     args_schema: Type[Ros2ActionRunnerInput] = Ros2ActionRunnerInput
 
@@ -176,9 +174,7 @@ def _run(self) -> bool:
 
 class Ros2GetLastActionFeedback(Ros2BaseActionTool):
     name: str = "Ros2GetLastActionFeedback"
-    description: str = (
-        "Action feedback is an optional intermediate information from ros2 action. With this tool you can get the last feedback of running action."
-    )
+    description: str = "Action feedback is an optional intermediate information from ros2 action. With this tool you can get the last feedback of running action."
 
     args_schema: Type[Ros2BaseInput] = Ros2BaseInput
 

src/rai_core/rai/tools/ros/tools.py

@@ -98,9 +98,7 @@ class GetOccupancyGridTool(BaseTool):
     """Get the current map as an image with the robot's position marked on it (red dot)."""
 
     name: str = "GetOccupancyGridTool"
-    description: str = (
-        "A tool for getting the current map as an image with the robot's position marked on it."
-    )
+    description: str = "A tool for getting the current map as an image with the robot's position marked on it."
 
     args_schema: Type[TopicInput] = TopicInput
 

src/rai_core/rai/tools/ros2/__init__.py

@@ -24,13 +24,13 @@
 )
 
 __all__ = [
-    "StartROS2ActionTool",
-    "GetROS2ImageTool",
-    "PublishROS2MessageTool",
-    "ReceiveROS2MessageTool",
     "CallROS2ServiceTool",
     "CancelROS2ActionTool",
-    "GetROS2TopicsNamesAndTypesTool",
+    "GetROS2ImageTool",
     "GetROS2MessageInterfaceTool",
+    "GetROS2TopicsNamesAndTypesTool",
     "GetROS2TransformTool",
+    "PublishROS2MessageTool",
+    "ReceiveROS2MessageTool",
+    "StartROS2ActionTool",
 ]

src/rai_core/rai/tools/ros2/topics.py

@@ -98,7 +98,9 @@ def _run(self, topic: str) -> Tuple[str, MultimodalArtifact]:
             raise ValueError(
                 f"Unsupported message type: {message.metadata['msg_type']}"
             )
-        return "Image received successfully", MultimodalArtifact(images=[preprocess_image(image)])  # type: ignore
+        return "Image received successfully", MultimodalArtifact(
+            images=[preprocess_image(image)]
+        )  # type: ignore
 
 
 class GetROS2TopicsNamesAndTypesTool(BaseTool):

src/rai_core/rai/tools/utils.py

@@ -249,7 +249,9 @@ def __init__(
 
     def postprocess(self, msg: Image) -> str:
         bridge = CvBridge()
-        cv_image = cast(cv2.Mat, bridge.imgmsg_to_cv2(msg, desired_encoding="passthrough"))  # type: ignore
+        cv_image = cast(
+            cv2.Mat, bridge.imgmsg_to_cv2(msg, desired_encoding="passthrough")
+        )  # type: ignore
         if cv_image.shape[-1] == 4:
             cv_image = cv2.cvtColor(cv_image, cv2.COLOR_BGRA2RGB)
             base64_image = base64.b64encode(