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6 Commits

Author SHA1 Message Date
João Moura
9a4b060f78 Merge branch 'main' into feat/joao-flow-improvement-requests 2024-12-24 18:52:59 -03:00
Brandon Hancock
756767df0f Merge branch 'feat/joao-flow-improvement-requests' of https://github.com/joaomdmoura/crewAI into feat/joao-flow-improvement-requests 2024-12-23 13:02:51 -05:00
Brandon Hancock
cac1ea7632 final plot changes 2024-12-23 13:02:46 -05:00
Brandon Hancock (bhancock_ai)
156726f7cd Merge branch 'main' into feat/joao-flow-improvement-requests 2024-12-23 12:52:12 -05:00
Brandon Hancock
10706ce2ee In the middle of improving plotting 2024-12-17 09:26:56 -05:00
Brandon Hancock
8eea6bc090 Add in or and and in router 2024-12-16 12:10:33 -05:00
4 changed files with 233 additions and 125 deletions

View File

@@ -80,10 +80,27 @@ def listen(condition):
return decorator
def router(method):
def router(condition):
def decorator(func):
func.__is_router__ = True
func.__router_for__ = method.__name__
# Handle conditions like listen/start
if isinstance(condition, str):
func.__trigger_methods__ = [condition]
func.__condition_type__ = "OR"
elif (
isinstance(condition, dict)
and "type" in condition
and "methods" in condition
):
func.__trigger_methods__ = condition["methods"]
func.__condition_type__ = condition["type"]
elif callable(condition) and hasattr(condition, "__name__"):
func.__trigger_methods__ = [condition.__name__]
func.__condition_type__ = "OR"
else:
raise ValueError(
"Condition must be a method, string, or a result of or_() or and_()"
)
return func
return decorator
@@ -123,8 +140,8 @@ class FlowMeta(type):
start_methods = []
listeners = {}
routers = {}
router_paths = {}
routers = set()
for attr_name, attr_value in dct.items():
if hasattr(attr_value, "__is_start_method__"):
@@ -137,18 +154,11 @@ class FlowMeta(type):
methods = attr_value.__trigger_methods__
condition_type = getattr(attr_value, "__condition_type__", "OR")
listeners[attr_name] = (condition_type, methods)
elif hasattr(attr_value, "__is_router__"):
routers[attr_value.__router_for__] = attr_name
possible_returns = get_possible_return_constants(attr_value)
if possible_returns:
router_paths[attr_name] = possible_returns
# Register router as a listener to its triggering method
trigger_method_name = attr_value.__router_for__
methods = [trigger_method_name]
condition_type = "OR"
listeners[attr_name] = (condition_type, methods)
if hasattr(attr_value, "__is_router__") and attr_value.__is_router__:
routers.add(attr_name)
possible_returns = get_possible_return_constants(attr_value)
if possible_returns:
router_paths[attr_name] = possible_returns
setattr(cls, "_start_methods", start_methods)
setattr(cls, "_listeners", listeners)
@@ -163,7 +173,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
_start_methods: List[str] = []
_listeners: Dict[str, tuple[str, List[str]]] = {}
_routers: Dict[str, str] = {}
_routers: Set[str] = set()
_router_paths: Dict[str, List[str]] = {}
initial_state: Union[Type[T], T, None] = None
event_emitter = Signal("event_emitter")
@@ -210,20 +220,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
return self._method_outputs
def _initialize_state(self, inputs: Dict[str, Any]) -> None:
"""
Initializes or updates the state with the provided inputs.
Args:
inputs: Dictionary of inputs to initialize or update the state.
Raises:
ValueError: If inputs do not match the structured state model.
TypeError: If state is neither a BaseModel instance nor a dictionary.
"""
if isinstance(self._state, BaseModel):
# Structured state management
# Structured state
try:
# Define a function to create the dynamic class
def create_model_with_extra_forbid(
base_model: Type[BaseModel],
) -> Type[BaseModel]:
@@ -233,34 +233,20 @@ class Flow(Generic[T], metaclass=FlowMeta):
return ModelWithExtraForbid
# Create the dynamic class
ModelWithExtraForbid = create_model_with_extra_forbid(
self._state.__class__
)
# Create a new instance using the combined state and inputs
self._state = cast(
T, ModelWithExtraForbid(**{**self._state.model_dump(), **inputs})
)
except ValidationError as e:
raise ValueError(f"Invalid inputs for structured state: {e}") from e
elif isinstance(self._state, dict):
# Unstructured state management
self._state.update(inputs)
else:
raise TypeError("State must be a BaseModel instance or a dictionary.")
def kickoff(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
"""
Starts the execution of the flow synchronously.
Args:
inputs: Optional dictionary of inputs to initialize or update the state.
Returns:
The final output from the flow execution.
"""
self.event_emitter.send(
self,
event=FlowStartedEvent(
@@ -274,15 +260,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
return asyncio.run(self.kickoff_async())
async def kickoff_async(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
"""
Starts the execution of the flow asynchronously.
Args:
inputs: Optional dictionary of inputs to initialize or update the state.
Returns:
The final output from the flow execution.
"""
if not self._start_methods:
raise ValueError("No start method defined")
@@ -290,16 +267,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
self.__class__.__name__, list(self._methods.keys())
)
# Create tasks for all start methods
tasks = [
self._execute_start_method(start_method)
for start_method in self._start_methods
]
# Run all start methods concurrently
await asyncio.gather(*tasks)
# Determine the final output (from the last executed method)
final_output = self._method_outputs[-1] if self._method_outputs else None
self.event_emitter.send(
@@ -310,7 +283,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
result=final_output,
),
)
return final_output
async def _execute_start_method(self, start_method_name: str) -> None:
@@ -327,49 +299,68 @@ class Flow(Generic[T], metaclass=FlowMeta):
if asyncio.iscoroutinefunction(method)
else method(*args, **kwargs)
)
self._method_outputs.append(result) # Store the output
# Track method execution counts
self._method_outputs.append(result)
self._method_execution_counts[method_name] = (
self._method_execution_counts.get(method_name, 0) + 1
)
return result
async def _execute_listeners(self, trigger_method: str, result: Any) -> None:
listener_tasks = []
if trigger_method in self._routers:
router_method = self._methods[self._routers[trigger_method]]
path = await self._execute_method(
self._routers[trigger_method], router_method
# First, handle routers repeatedly until no router triggers anymore
while True:
routers_triggered = self._find_triggered_methods(
trigger_method, router_only=True
)
trigger_method = path
if not routers_triggered:
break
for router_name in routers_triggered:
await self._execute_single_listener(router_name, result)
# After executing router, the router's result is the path
# The last router executed sets the trigger_method
# The router result is the last element in self._method_outputs
trigger_method = self._method_outputs[-1]
# Now that no more routers are triggered by current trigger_method,
# execute normal listeners
listeners_triggered = self._find_triggered_methods(
trigger_method, router_only=False
)
if listeners_triggered:
tasks = [
self._execute_single_listener(listener_name, result)
for listener_name in listeners_triggered
]
await asyncio.gather(*tasks)
def _find_triggered_methods(
self, trigger_method: str, router_only: bool
) -> List[str]:
triggered = []
for listener_name, (condition_type, methods) in self._listeners.items():
is_router = listener_name in self._routers
if router_only != is_router:
continue
if condition_type == "OR":
# If the trigger_method matches any in methods, run this
if trigger_method in methods:
# Schedule the listener without preventing re-execution
listener_tasks.append(
self._execute_single_listener(listener_name, result)
)
triggered.append(listener_name)
elif condition_type == "AND":
# Initialize pending methods for this listener if not already done
if listener_name not in self._pending_and_listeners:
self._pending_and_listeners[listener_name] = set(methods)
# Remove the trigger method from pending methods
self._pending_and_listeners[listener_name].discard(trigger_method)
if trigger_method in self._pending_and_listeners[listener_name]:
self._pending_and_listeners[listener_name].discard(trigger_method)
if not self._pending_and_listeners[listener_name]:
# All required methods have been executed
listener_tasks.append(
self._execute_single_listener(listener_name, result)
)
triggered.append(listener_name)
# Reset pending methods for this listener
self._pending_and_listeners.pop(listener_name, None)
# Run all listener tasks concurrently and wait for them to complete
if listener_tasks:
await asyncio.gather(*listener_tasks)
return triggered
async def _execute_single_listener(self, listener_name: str, result: Any) -> None:
try:
@@ -386,17 +377,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
sig = inspect.signature(method)
params = list(sig.parameters.values())
# Exclude 'self' parameter
method_params = [p for p in params if p.name != "self"]
if method_params:
# If listener expects parameters, pass the result
listener_result = await self._execute_method(
listener_name, method, result
)
else:
# If listener does not expect parameters, call without arguments
listener_result = await self._execute_method(listener_name, method)
self.event_emitter.send(
@@ -408,8 +395,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
),
)
# Execute listeners of this listener
# Execute listeners (and possibly routers) of this listener
await self._execute_listeners(listener_name, listener_result)
except Exception as e:
print(
f"[Flow._execute_single_listener] Error in method {listener_name}: {e}"
@@ -422,5 +410,4 @@ class Flow(Generic[T], metaclass=FlowMeta):
self._telemetry.flow_plotting_span(
self.__class__.__name__, list(self._methods.keys())
)
plot_flow(self, filename)

View File

@@ -31,16 +31,50 @@ def get_possible_return_constants(function):
print(f"Source code:\n{source}")
return None
return_values = []
return_values = set()
dict_definitions = {}
class DictionaryAssignmentVisitor(ast.NodeVisitor):
def visit_Assign(self, node):
# Check if this assignment is assigning a dictionary literal to a variable
if isinstance(node.value, ast.Dict) and len(node.targets) == 1:
target = node.targets[0]
if isinstance(target, ast.Name):
var_name = target.id
dict_values = []
# Extract string values from the dictionary
for val in node.value.values:
if isinstance(val, ast.Constant) and isinstance(val.value, str):
dict_values.append(val.value)
# If non-string, skip or just ignore
if dict_values:
dict_definitions[var_name] = dict_values
self.generic_visit(node)
class ReturnVisitor(ast.NodeVisitor):
def visit_Return(self, node):
# Check if the return value is a constant (Python 3.8+)
if isinstance(node.value, ast.Constant):
return_values.append(node.value.value)
# Direct string return
if isinstance(node.value, ast.Constant) and isinstance(
node.value.value, str
):
return_values.add(node.value.value)
# Dictionary-based return, like return paths[result]
elif isinstance(node.value, ast.Subscript):
# Check if we're subscripting a known dictionary variable
if isinstance(node.value.value, ast.Name):
var_name = node.value.value.id
if var_name in dict_definitions:
# Add all possible dictionary values
for v in dict_definitions[var_name]:
return_values.add(v)
self.generic_visit(node)
# First pass: identify dictionary assignments
DictionaryAssignmentVisitor().visit(code_ast)
# Second pass: identify returns
ReturnVisitor().visit(code_ast)
return return_values
return list(return_values) if return_values else None
def calculate_node_levels(flow):
@@ -61,10 +95,7 @@ def calculate_node_levels(flow):
current_level = levels[current]
visited.add(current)
for listener_name, (
condition_type,
trigger_methods,
) in flow._listeners.items():
for listener_name, (condition_type, trigger_methods) in flow._listeners.items():
if condition_type == "OR":
if current in trigger_methods:
if (
@@ -89,7 +120,7 @@ def calculate_node_levels(flow):
queue.append(listener_name)
# Handle router connections
if current in flow._routers.values():
if current in flow._routers:
router_method_name = current
paths = flow._router_paths.get(router_method_name, [])
for path in paths:
@@ -105,6 +136,7 @@ def calculate_node_levels(flow):
levels[listener_name] = current_level + 1
if listener_name not in visited:
queue.append(listener_name)
return levels
@@ -142,7 +174,7 @@ def dfs_ancestors(node, ancestors, visited, flow):
dfs_ancestors(listener_name, ancestors, visited, flow)
# Handle router methods separately
if node in flow._routers.values():
if node in flow._routers:
router_method_name = node
paths = flow._router_paths.get(router_method_name, [])
for path in paths:

View File

@@ -94,12 +94,14 @@ def add_edges(net, flow, node_positions, colors):
ancestors = build_ancestor_dict(flow)
parent_children = build_parent_children_dict(flow)
# Edges for normal listeners
for method_name in flow._listeners:
condition_type, trigger_methods = flow._listeners[method_name]
is_and_condition = condition_type == "AND"
for trigger in trigger_methods:
if trigger in flow._methods or trigger in flow._routers.values():
# Check if nodes exist before adding edges
if trigger in node_positions and method_name in node_positions:
is_router_edge = any(
trigger in paths for paths in flow._router_paths.values()
)
@@ -135,7 +137,22 @@ def add_edges(net, flow, node_positions, colors):
}
net.add_edge(trigger, method_name, **edge_style)
else:
# Nodes not found in node_positions. Check if it's a known router outcome and a known method.
is_router_edge = any(
trigger in paths for paths in flow._router_paths.values()
)
# Check if method_name is a known method
method_known = method_name in flow._methods
# If it's a known router edge and the method is known, don't warn.
# This means the path is legitimate, just not reflected as nodes here.
if not (is_router_edge and method_known):
print(
f"Warning: No node found for '{trigger}' or '{method_name}'. Skipping edge."
)
# Edges for router return paths
for router_method_name, paths in flow._router_paths.items():
for path in paths:
for listener_name, (
@@ -143,36 +160,49 @@ def add_edges(net, flow, node_positions, colors):
trigger_methods,
) in flow._listeners.items():
if path in trigger_methods:
is_cycle_edge = is_ancestor(trigger, method_name, ancestors)
parent_has_multiple_children = (
len(parent_children.get(router_method_name, [])) > 1
)
needs_curvature = is_cycle_edge or parent_has_multiple_children
if (
router_method_name in node_positions
and listener_name in node_positions
):
is_cycle_edge = is_ancestor(
router_method_name, listener_name, ancestors
)
parent_has_multiple_children = (
len(parent_children.get(router_method_name, [])) > 1
)
needs_curvature = is_cycle_edge or parent_has_multiple_children
if needs_curvature:
source_pos = node_positions.get(router_method_name)
target_pos = node_positions.get(listener_name)
if needs_curvature:
source_pos = node_positions.get(router_method_name)
target_pos = node_positions.get(listener_name)
if source_pos and target_pos:
dx = target_pos[0] - source_pos[0]
smooth_type = "curvedCCW" if dx <= 0 else "curvedCW"
index = get_child_index(
router_method_name, listener_name, parent_children
)
edge_smooth = {
"type": smooth_type,
"roundness": 0.2 + (0.1 * index),
}
if source_pos and target_pos:
dx = target_pos[0] - source_pos[0]
smooth_type = "curvedCCW" if dx <= 0 else "curvedCW"
index = get_child_index(
router_method_name, listener_name, parent_children
)
edge_smooth = {
"type": smooth_type,
"roundness": 0.2 + (0.1 * index),
}
else:
edge_smooth = {"type": "cubicBezier"}
else:
edge_smooth = {"type": "cubicBezier"}
else:
edge_smooth = False
edge_smooth = False
edge_style = {
"color": colors["router_edge"],
"width": 2,
"arrows": "to",
"dashes": True,
"smooth": edge_smooth,
}
net.add_edge(router_method_name, listener_name, **edge_style)
edge_style = {
"color": colors["router_edge"],
"width": 2,
"arrows": "to",
"dashes": True,
"smooth": edge_smooth,
}
net.add_edge(router_method_name, listener_name, **edge_style)
else:
# Same check here: known router edge and known method?
method_known = listener_name in flow._methods
if not method_known:
print(
f"Warning: No node found for '{router_method_name}' or '{listener_name}'. Skipping edge."
)

View File

@@ -263,3 +263,62 @@ def test_flow_with_custom_state():
flow = StateFlow()
flow.kickoff()
assert flow.counter == 2
def test_router_with_multiple_conditions():
"""Test a router that triggers when any of multiple steps complete (OR condition),
and another router that triggers only after all specified steps complete (AND condition).
"""
execution_order = []
class ComplexRouterFlow(Flow):
@start()
def step_a(self):
execution_order.append("step_a")
@start()
def step_b(self):
execution_order.append("step_b")
@router(or_("step_a", "step_b"))
def router_or(self):
execution_order.append("router_or")
return "next_step_or"
@listen("next_step_or")
def handle_next_step_or_event(self):
execution_order.append("handle_next_step_or_event")
@listen(handle_next_step_or_event)
def branch_2_step(self):
execution_order.append("branch_2_step")
@router(and_(handle_next_step_or_event, branch_2_step))
def router_and(self):
execution_order.append("router_and")
return "final_step"
@listen("final_step")
def log_final_step(self):
execution_order.append("log_final_step")
flow = ComplexRouterFlow()
flow.kickoff()
assert "step_a" in execution_order
assert "step_b" in execution_order
assert "router_or" in execution_order
assert "handle_next_step_or_event" in execution_order
assert "branch_2_step" in execution_order
assert "router_and" in execution_order
assert "log_final_step" in execution_order
# Check that the AND router triggered after both relevant steps:
assert execution_order.index("router_and") > execution_order.index(
"handle_next_step_or_event"
)
assert execution_order.index("router_and") > execution_order.index("branch_2_step")
# final_step should run after router_and
assert execution_order.index("log_final_step") > execution_order.index("router_and")