Create actionState.py

src/states/actionState.py

@@ -0,0 +1,39 @@
+
+import operator 
+from typing_extensions import TypedDict, Annotated, List, Sequence
+from pydantic import BaseModel, Field
+from langchain_core.messages import BaseMessage
+from langgraph.graph.message import add_messages
+from typing_extensions import Literal
+
+
+class ExecutorState(TypedDict):
+    """
+    State for the executor agent containing message history and research metadata.
+
+    This state tracks the executors conversation, iteration count for limiting
+    tool calls, the executor topic being
+    """
+    executor_messages: Annotated[Sequence[BaseMessage], add_messages]
+    execution_job: str
+    executor_data: List[str]
+
+class ExecutorOutputState(TypedDict):
+    """
+    Output state for the executor agent containing final executor results.
+
+    This represents the final output of the execution process with executor_data,
+    executor_messages and output from the execution process.
+
+    """
+    output: str  
+    executor_data: List[str]
+    executor_messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+# Structured output schema 
+class CustomerQuestion(BaseModel):
+    """Schema for customer query brief generation"""
+    query_brief: str = Field(description="A customer question that will be used to guide the execution")
+
+