feat(rai_node): execute mission as ros2 action (#208)

examples/rosbot-xl-generic-node-demo.py

@@ -20,17 +20,19 @@
 import rclpy.qos
 import rclpy.subscription
 import rclpy.task
+from langchain.tools.render import render_text_description_and_args
 from langchain_openai import ChatOpenAI
 
 from rai.agents.state_based import create_state_based_agent
-from rai.node import RaiNode, describe_ros_image, wait_for_2s
+from rai.node import RaiNode, describe_ros_image
 from rai.tools.ros.native import (
     GetCameraImage,
     GetMsgFromTopic,
     Ros2ShowMsgInterfaceTool,
 )
 from rai.tools.ros.native_actions import Ros2RunActionSync
 from rai.tools.ros.tools import GetOccupancyGridTool
+from rai.tools.time import WaitForSecondsTool
 
 
 def main():
@@ -68,10 +70,9 @@ def main():
         "/wait",
     ]
 
-    SYSTEM_PROMPT = "You are an autonomous robot connected to ros2 environment. Your main goal is to fulfill the user's requests. "
-    "Do not make assumptions about the environment you are currently in. "
-    "Use the tooling provided to gather information about the environment."
-    "You can use ros2 topics, services and actions to operate."
+    # TODO(boczekbartek): refactor system prompt
+
+    SYSTEM_PROMPT = ""
 
     node = RaiNode(
         llm=ChatOpenAI(
@@ -84,7 +85,7 @@ def main():
     )
 
     tools = [
-        wait_for_2s,
+        WaitForSecondsTool(),
         GetMsgFromTopic(node=node),
         Ros2RunActionSync(node=node),
         GetCameraImage(node=node),
@@ -94,6 +95,18 @@ def main():
 
     state_retriever = node.get_robot_state
 
+    SYSTEM_PROMPT = f"""You are an autonomous robot connected to ros2 environment. Your main goal is to fulfill the user's requests.
+    Do not make assumptions about the environment you are currently in.
+    Use the tooling provided to gather information about the environment:
+
+    {render_text_description_and_args(tools)}
+
+    You can use ros2 topics, services and actions to operate. """
+
+    node.get_logger().info(f"{SYSTEM_PROMPT=}")
+
+    node.system_prompt = node.initialize_system_prompt(SYSTEM_PROMPT)
+
     app = create_state_based_agent(
         llm=llm,
         tools=tools,

src/rai/rai/agents/state_based.py

@@ -17,6 +17,7 @@
 import pickle
 import time
 from functools import partial
+from pathlib import Path
 from typing import (
     Any,
     Callable,
@@ -76,20 +77,39 @@ class Report(BaseModel):
     steps: List[str] = Field(
         ..., title="Steps", description="The steps taken to solve the problem"
     )
+    success: bool = Field(
+        ..., title="Success", description="Whether the problem was solved"
+    )
     response_to_user: str = Field(
         ..., title="Response", description="The response to the user"
     )
 
 
-def get_stored_artifacts(tool_call_id: str) -> List[Any]:
-    with open("artifact_database.pkl", "rb") as file:
-        artifact_database = pickle.load(file)
+def get_stored_artifacts(
+    tool_call_id: str, db_path="artifact_database.pkl"
+) -> List[Any]:
+    # TODO(boczekbartek): refactor
+    db_path = Path(db_path)
+    if not db_path.is_file():
+        return []
+
+    with db_path.open("rb") as db:
+        artifact_database = pickle.load(db)
         if tool_call_id in artifact_database:
             return artifact_database[tool_call_id]
+
     return []
 
 
-def store_artifacts(tool_call_id: str, artifacts: List[Any]):
+def store_artifacts(
+    tool_call_id: str, artifacts: List[Any], db_path="artifact_database.pkl"
+):
+    # TODO(boczekbartek): refactor
+    db_path = Path(db_path)
+    if not db_path.is_file():
+        artifact_database = {}
+        with open("artifact_database.pkl", "wb") as file:
+            pickle.dump(artifact_database, file)
     with open("artifact_database.pkl", "rb") as file:
         artifact_database = pickle.load(file)
         if tool_call_id not in artifact_database:
@@ -283,7 +303,7 @@ def retriever_wrapper(
     info = str_output(retrieved_info)
     state["messages"].append(
         HumanMultimodalMessage(
-            content="Retrieved state: {}".format(info), images=images, audios=audios
+            content=f"Retrieved state: {info}", images=images, audios=audios
         )
     )
     return state