result type → cast

README.md

@@ -40,7 +40,7 @@ def demo():
         name = get_user_name()
 
         # define an AI task inline
-        interests = run_ai("ask user for three interests", result_type=list[str], user_access=True)
+        interests = run_ai("ask user for three interests", cast=list[str], user_access=True)
 
         # set instructions for just the next task
         with instructions("no more than 8 lines"):

examples/readme_example.py

@@ -28,7 +28,7 @@ def demo():
         # define an AI task inline
         interests = run_ai(
             "ask user for three interests",
-            result_type=list[str],
+            cast=list[str],
             user_access=True,
         )
 

src/control_flow/agent.py

@@ -127,6 +127,9 @@
 ### Task {{ task.id }}
 - Status: {{ task.status.value }}
 - Objective: {{ task.objective }}
+{% if task.instructions %}
+- Additional instructions: {{ task.instructions }}
+{% endif %}
 {% if task.status.value == "completed" %}
 - Result: {{ task.result }}
 {% elif task.status.value == "failed" %}
@@ -503,7 +506,7 @@ def wrapper(*args, **kwargs):
 
         return run_ai.with_options(name=f"Task: {fn.__name__}")(
             task=objective,
-            result_type=fn.__annotations__.get("return"),
+            cast=fn.__annotations__.get("return"),
             context=bound.arguments,
             user_access=user_access,
             **agent_kwargs,
@@ -517,23 +520,23 @@ def _name_from_objective():
     from prefect.runtime import task_run
 
     objective = task_run.parameters["task"]
-    if len(objective) > 32:
-        return f"Task: {objective[:32]}..."
+    if len(objective) > 50:
+        return f"Task: {objective[:50]}..."
     return f"Task: {objective}"
 
 
 @prefect_task(task_run_name=_name_from_objective)
 def run_ai(
     task: str,
-    result_type: T = str,
+    cast: T = str,
     context: dict = None,
     user_access: bool = None,
     model: str = None,
     **agent_kwargs: dict,
 ) -> T:
     """
     Run an agent to complete a task with the given objective and context. The
-    response will be of the given result type.
+    response will be cast to the given result type.
     """
 
     # load flow
@@ -542,7 +545,7 @@ def run_ai(
         flow = AIFlow()
 
     # create task
-    ai_task = AITask[result_type](objective=task, context=context)
+    ai_task = AITask[cast](objective=task, context=context)
     flow.add_task(ai_task)
 
     # run agent

src/control_flow/task.py

@@ -30,6 +30,7 @@ class AITask(BaseModel, Generic[T]):
 
     id: int = Field(None, validate_default=True)
     objective: str
+    instructions: Optional[str] = None
     context: dict = Field(None, validate_default=True)
     status: TaskStatus = TaskStatus.PENDING
     result: T = None
@@ -108,4 +109,7 @@ def fail(self, message: Optional[str] = None):
         self.status = TaskStatus.FAILED
 
     def get_result_type(self) -> T:
+        """
+        Returns the `type` of the task's result field.
+        """
         return self.model_fields["result"].annotation