Fix Flow initialization with Pydantic models having required fields

- Modified _create_initial_state() to accept kwargs parameter
- Pass kwargs when instantiating BaseModel classes
- Updated __init__() to pass kwargs to _create_initial_state()
- Added comprehensive tests covering various scenarios

Fixes #3744

Co-Authored-By: João <joao@crewai.com>

src/crewai/flow/flow.py

@@ -31,7 +31,7 @@ from crewai.flow.flow_visualizer import plot_flow
 from crewai.flow.persistence.base import FlowPersistence
 from crewai.flow.types import FlowExecutionData
 from crewai.flow.utils import get_possible_return_constants
-from crewai.utilities.printer import Printer
+from crewai.utilities.printer import Printer, PrinterColor
 
 logger = logging.getLogger(__name__)
 
@@ -105,7 +105,7 @@ def start(condition: str | dict | Callable | None = None) -> Callable:
     condition : Optional[Union[str, dict, Callable]], optional
         Defines when the start method should execute. Can be:
         - str: Name of a method that triggers this start
-        - dict: Contains "type" ("AND"/"OR") and "methods" (list of triggers)
+        - dict: Result from or_() or and_(), including nested conditions
         - Callable: A method reference that triggers this start
         Default is None, meaning unconditional start.
 
@@ -140,13 +140,18 @@ def start(condition: str | dict | Callable | None = None) -> Callable:
             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 isinstance(condition, dict) and "type" in condition:
+                if "conditions" in condition:
+                    func.__trigger_condition__ = condition
+                    func.__trigger_methods__ = _extract_all_methods(condition)
+                    func.__condition_type__ = condition["type"]
+                elif "methods" in condition:
+                    func.__trigger_methods__ = condition["methods"]
+                    func.__condition_type__ = condition["type"]
+                else:
+                    raise ValueError(
+                        "Condition dict must contain 'conditions' or 'methods'"
+                    )
             elif callable(condition) and hasattr(condition, "__name__"):
                 func.__trigger_methods__ = [condition.__name__]
                 func.__condition_type__ = "OR"
@@ -172,7 +177,7 @@ def listen(condition: str | dict | Callable) -> Callable:
     condition : Union[str, dict, Callable]
         Specifies when the listener should execute. Can be:
         - str: Name of a method that triggers this listener
-        - dict: Contains "type" ("AND"/"OR") and "methods" (list of triggers)
+        - dict: Result from or_() or and_(), including nested conditions
         - Callable: A method reference that triggers this listener
 
     Returns
@@ -200,13 +205,18 @@ def listen(condition: str | dict | Callable) -> Callable:
         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 isinstance(condition, dict) and "type" in condition:
+            if "conditions" in condition:
+                func.__trigger_condition__ = condition
+                func.__trigger_methods__ = _extract_all_methods(condition)
+                func.__condition_type__ = condition["type"]
+            elif "methods" in condition:
+                func.__trigger_methods__ = condition["methods"]
+                func.__condition_type__ = condition["type"]
+            else:
+                raise ValueError(
+                    "Condition dict must contain 'conditions' or 'methods'"
+                )
         elif callable(condition) and hasattr(condition, "__name__"):
             func.__trigger_methods__ = [condition.__name__]
             func.__condition_type__ = "OR"
@@ -233,7 +243,7 @@ def router(condition: str | dict | Callable) -> Callable:
     condition : Union[str, dict, Callable]
         Specifies when the router should execute. Can be:
         - str: Name of a method that triggers this router
-        - dict: Contains "type" ("AND"/"OR") and "methods" (list of triggers)
+        - dict: Result from or_() or and_(), including nested conditions
         - Callable: A method reference that triggers this router
 
     Returns
@@ -266,13 +276,18 @@ def router(condition: str | dict | Callable) -> Callable:
         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 isinstance(condition, dict) and "type" in condition:
+            if "conditions" in condition:
+                func.__trigger_condition__ = condition
+                func.__trigger_methods__ = _extract_all_methods(condition)
+                func.__condition_type__ = condition["type"]
+            elif "methods" in condition:
+                func.__trigger_methods__ = condition["methods"]
+                func.__condition_type__ = condition["type"]
+            else:
+                raise ValueError(
+                    "Condition dict must contain 'conditions' or 'methods'"
+                )
         elif callable(condition) and hasattr(condition, "__name__"):
             func.__trigger_methods__ = [condition.__name__]
             func.__condition_type__ = "OR"
@@ -298,14 +313,15 @@ def or_(*conditions: str | dict | Callable) -> dict:
     *conditions : Union[str, dict, Callable]
         Variable number of conditions that can be:
         - str: Method names
-        - dict: Existing condition dictionaries
+        - dict: Existing condition dictionaries (nested conditions)
         - Callable: Method references
 
     Returns
     -------
     dict
         A condition dictionary with format:
-        {"type": "OR", "methods": list_of_method_names}
+        {"type": "OR", "conditions": list_of_conditions}
+        where each condition can be a string (method name) or a nested dict
 
     Raises
     ------
@@ -317,18 +333,22 @@ def or_(*conditions: str | dict | Callable) -> dict:
     >>> @listen(or_("success", "timeout"))
     >>> def handle_completion(self):
     ...     pass
+
+    >>> @listen(or_(and_("step1", "step2"), "step3"))
+    >>> def handle_nested(self):
+    ...     pass
     """
-    methods = []
+    processed_conditions: list[str | dict[str, Any]] = []
     for condition in conditions:
-        if isinstance(condition, dict) and "methods" in condition:
-            methods.extend(condition["methods"])
+        if isinstance(condition, dict):
+            processed_conditions.append(condition)
         elif isinstance(condition, str):
-            methods.append(condition)
+            processed_conditions.append(condition)
         elif callable(condition):
-            methods.append(getattr(condition, "__name__", repr(condition)))
+            processed_conditions.append(getattr(condition, "__name__", repr(condition)))
         else:
             raise ValueError("Invalid condition in or_()")
-    return {"type": "OR", "methods": methods}
+    return {"type": "OR", "conditions": processed_conditions}
 
 
 def and_(*conditions: str | dict | Callable) -> dict:
@@ -344,14 +364,15 @@ def and_(*conditions: str | dict | Callable) -> dict:
     *conditions : Union[str, dict, Callable]
         Variable number of conditions that can be:
         - str: Method names
-        - dict: Existing condition dictionaries
+        - dict: Existing condition dictionaries (nested conditions)
         - Callable: Method references
 
     Returns
     -------
     dict
         A condition dictionary with format:
-        {"type": "AND", "methods": list_of_method_names}
+        {"type": "AND", "conditions": list_of_conditions}
+        where each condition can be a string (method name) or a nested dict
 
     Raises
     ------
@@ -363,18 +384,69 @@ def and_(*conditions: str | dict | Callable) -> dict:
     >>> @listen(and_("validated", "processed"))
     >>> def handle_complete_data(self):
     ...     pass
+
+    >>> @listen(and_(or_("step1", "step2"), "step3"))
+    >>> def handle_nested(self):
+    ...     pass
     """
-    methods = []
+    processed_conditions: list[str | dict[str, Any]] = []
     for condition in conditions:
-        if isinstance(condition, dict) and "methods" in condition:
-            methods.extend(condition["methods"])
+        if isinstance(condition, dict):
+            processed_conditions.append(condition)
         elif isinstance(condition, str):
-            methods.append(condition)
+            processed_conditions.append(condition)
         elif callable(condition):
-            methods.append(getattr(condition, "__name__", repr(condition)))
+            processed_conditions.append(getattr(condition, "__name__", repr(condition)))
         else:
             raise ValueError("Invalid condition in and_()")
-    return {"type": "AND", "methods": methods}
+    return {"type": "AND", "conditions": processed_conditions}
+
+
+def _normalize_condition(condition: str | dict | list) -> dict:
+    """Normalize a condition to standard format with 'conditions' key.
+
+    Args:
+        condition: Can be a string (method name), dict (condition), or list
+
+    Returns:
+        Normalized dict with 'type' and 'conditions' keys
+    """
+    if isinstance(condition, str):
+        return {"type": "OR", "conditions": [condition]}
+    if isinstance(condition, dict):
+        if "conditions" in condition:
+            return condition
+        if "methods" in condition:
+            return {"type": condition["type"], "conditions": condition["methods"]}
+        return condition
+    if isinstance(condition, list):
+        return {"type": "OR", "conditions": condition}
+    return {"type": "OR", "conditions": [condition]}
+
+
+def _extract_all_methods(condition: str | dict | list) -> list[str]:
+    """Extract all method names from a condition (including nested).
+
+    Args:
+        condition: Can be a string, dict, or list
+
+    Returns:
+        List of all method names in the condition tree
+    """
+    if isinstance(condition, str):
+        return [condition]
+    if isinstance(condition, dict):
+        normalized = _normalize_condition(condition)
+        methods = []
+        for sub_cond in normalized.get("conditions", []):
+            methods.extend(_extract_all_methods(sub_cond))
+        return methods
+    if isinstance(condition, list):
+        methods = []
+        for item in condition:
+            methods.extend(_extract_all_methods(item))
+        return methods
+    return []
 
 
 class FlowMeta(type):
@@ -402,7 +474,10 @@ class FlowMeta(type):
                 if hasattr(attr_value, "__trigger_methods__"):
                     methods = attr_value.__trigger_methods__
                     condition_type = getattr(attr_value, "__condition_type__", "OR")
-                    listeners[attr_name] = (condition_type, methods)
+                    if hasattr(attr_value, "__trigger_condition__"):
+                        listeners[attr_name] = attr_value.__trigger_condition__
+                    else:
+                        listeners[attr_name] = (condition_type, methods)
 
                     if (
                         hasattr(attr_value, "__is_router__")
@@ -464,8 +539,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
         self._persistence: FlowPersistence | None = persistence
         self._is_execution_resuming: bool = False
 
-        # Initialize state with initial values
-        self._state = self._create_initial_state()
+        # Initialize state with initial values and kwargs
+        self._state = self._create_initial_state(kwargs if kwargs else None)
         self.tracing = tracing
         if (
             is_tracing_enabled()
@@ -474,9 +549,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
         ):
             trace_listener = TraceCollectionListener()
             trace_listener.setup_listeners(crewai_event_bus)
-        # Apply any additional kwargs
-        if kwargs:
-            self._initialize_state(kwargs)
 
         crewai_event_bus.emit(
             self,
@@ -502,9 +574,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
                         method = method.__get__(self, self.__class__)
                     self._methods[method_name] = method
 
-    def _create_initial_state(self) -> T:
+    def _create_initial_state(self, kwargs: dict[str, Any] | None = None) -> T:
         """Create and initialize flow state with UUID and default values.
 
+        Args:
+            kwargs: Optional dictionary of initial state values
+
         Returns:
             New state instance with UUID and default values initialized
 
@@ -512,13 +587,16 @@ class Flow(Generic[T], metaclass=FlowMeta):
             ValueError: If structured state model lacks 'id' field
             TypeError: If state is neither BaseModel nor dictionary
         """
+        if kwargs is None:
+            kwargs = {}
+            
         # Handle case where initial_state is None but we have a type parameter
         if self.initial_state is None and hasattr(self, "_initial_state_t"):
             state_type = self._initial_state_t
             if isinstance(state_type, type):
                 if issubclass(state_type, FlowState):
-                    # Create instance without id, then set it
-                    instance = state_type()
+                    # Create instance with kwargs
+                    instance = state_type(**kwargs)
                     if not hasattr(instance, "id"):
                         instance.id = str(uuid4())
                     return cast(T, instance)
@@ -527,35 +605,42 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     class StateWithId(state_type, FlowState):  # type: ignore
                         pass
 
-                    instance = StateWithId()
+                    instance = StateWithId(**kwargs)
                     if not hasattr(instance, "id"):
                         instance.id = str(uuid4())
                     return cast(T, instance)
                 if state_type is dict:
-                    return cast(T, {"id": str(uuid4())})
+                    state_dict = {"id": str(uuid4())}
+                    state_dict.update(kwargs)
+                    return cast(T, state_dict)
 
         # Handle case where no initial state is provided
         if self.initial_state is None:
-            return cast(T, {"id": str(uuid4())})
+            state_dict = {"id": str(uuid4())}
+            state_dict.update(kwargs)
+            return cast(T, state_dict)
 
         # Handle case where initial_state is a type (class)
         if isinstance(self.initial_state, type):
             if issubclass(self.initial_state, FlowState):
-                return cast(T, self.initial_state())  # Uses model defaults
+                return cast(T, self.initial_state(**kwargs))  # Uses model defaults and kwargs
             if issubclass(self.initial_state, BaseModel):
                 # Validate that the model has an id field
                 model_fields = getattr(self.initial_state, "model_fields", None)
                 if not model_fields or "id" not in model_fields:
                     raise ValueError("Flow state model must have an 'id' field")
-                return cast(T, self.initial_state())  # Uses model defaults
+                return cast(T, self.initial_state(**kwargs))  # Uses model defaults and kwargs
             if self.initial_state is dict:
-                return cast(T, {"id": str(uuid4())})
+                state_dict = {"id": str(uuid4())}
+                state_dict.update(kwargs)
+                return cast(T, state_dict)
 
         # Handle dictionary instance case
         if isinstance(self.initial_state, dict):
             new_state = dict(self.initial_state)  # Copy to avoid mutations
             if "id" not in new_state:
                 new_state["id"] = str(uuid4())
+            new_state.update(kwargs)  # Apply kwargs
             return cast(T, new_state)
 
         # Handle BaseModel instance case
@@ -577,6 +662,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     k: v for k, v in model.__dict__.items() if not k.startswith("_")
                 }
 
+            state_dict.update(kwargs)
+            
             # Create new instance of the same class
             model_class = type(model)
             return cast(T, model_class(**state_dict))
@@ -822,6 +909,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 # Clear completed methods and outputs for a fresh start
                 self._completed_methods.clear()
                 self._method_outputs.clear()
+                self._pending_and_listeners.clear()
             else:
                 # We're restoring from persistence, set the flag
                 self._is_execution_resuming = True
@@ -1086,10 +1174,16 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     for method_name in self._start_methods:
                         # Check if this start method is triggered by the current trigger
                         if method_name in self._listeners:
-                            condition_type, trigger_methods = self._listeners[
-                                method_name
-                            ]
-                            if current_trigger in trigger_methods:
+                            condition_data = self._listeners[method_name]
+                            should_trigger = False
+                            if isinstance(condition_data, tuple):
+                                _, trigger_methods = condition_data
+                                should_trigger = current_trigger in trigger_methods
+                            elif isinstance(condition_data, dict):
+                                all_methods = _extract_all_methods(condition_data)
+                                should_trigger = current_trigger in all_methods
+
+                            if should_trigger:
                                 # Only execute if this is a cycle (method was already completed)
                                 if method_name in self._completed_methods:
                                     # For router-triggered start methods in cycles, temporarily clear resumption flag
@@ -1099,6 +1193,51 @@ class Flow(Generic[T], metaclass=FlowMeta):
                                     await self._execute_start_method(method_name)
                                     self._is_execution_resuming = was_resuming
 
+    def _evaluate_condition(
+        self, condition: str | dict, trigger_method: str, listener_name: str
+    ) -> bool:
+        """Recursively evaluate a condition (simple or nested).
+
+        Args:
+            condition: Can be a string (method name) or dict (nested condition)
+            trigger_method: The method that just completed
+            listener_name: Name of the listener being evaluated
+
+        Returns:
+            True if the condition is satisfied, False otherwise
+        """
+        if isinstance(condition, str):
+            return condition == trigger_method
+
+        if isinstance(condition, dict):
+            normalized = _normalize_condition(condition)
+            cond_type = normalized.get("type", "OR")
+            sub_conditions = normalized.get("conditions", [])
+
+            if cond_type == "OR":
+                return any(
+                    self._evaluate_condition(sub_cond, trigger_method, listener_name)
+                    for sub_cond in sub_conditions
+                )
+
+            if cond_type == "AND":
+                pending_key = f"{listener_name}:{id(condition)}"
+
+                if pending_key not in self._pending_and_listeners:
+                    all_methods = set(_extract_all_methods(condition))
+                    self._pending_and_listeners[pending_key] = all_methods
+
+                if trigger_method in self._pending_and_listeners[pending_key]:
+                    self._pending_and_listeners[pending_key].discard(trigger_method)
+
+                if not self._pending_and_listeners[pending_key]:
+                    self._pending_and_listeners.pop(pending_key, None)
+                    return True
+
+                return False
+
+        return False
+
     def _find_triggered_methods(
         self, trigger_method: str, router_only: bool
     ) -> list[str]:
@@ -1106,7 +1245,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
         Finds all methods that should be triggered based on conditions.
 
         This internal method evaluates both OR and AND conditions to determine
-        which methods should be executed next in the flow.
+        which methods should be executed next in the flow. Supports nested conditions.
 
         Parameters
         ----------
@@ -1123,14 +1262,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
         Notes
         -----
-        - Handles both OR and AND conditions:
-          * OR: Triggers if any condition is met
-          * AND: Triggers only when all conditions are met
+        - Handles both OR and AND conditions, including nested combinations
         - Maintains state for AND conditions using _pending_and_listeners
         - Separates router and normal listener evaluation
         """
         triggered = []
-        for listener_name, (condition_type, methods) in self._listeners.items():
+
+        for listener_name, condition_data in self._listeners.items():
             is_router = listener_name in self._routers
 
             if router_only != is_router:
@@ -1139,23 +1277,29 @@ class Flow(Generic[T], metaclass=FlowMeta):
             if not router_only and listener_name in self._start_methods:
                 continue
 
-            if condition_type == "OR":
-                # If the trigger_method matches any in methods, run this
-                if trigger_method in methods:
-                    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
-                if trigger_method in self._pending_and_listeners[listener_name]:
-                    self._pending_and_listeners[listener_name].discard(trigger_method)
+            if isinstance(condition_data, tuple):
+                condition_type, methods = condition_data
 
-                if not self._pending_and_listeners[listener_name]:
-                    # All required methods have been executed
+                if condition_type == "OR":
+                    if trigger_method in methods:
+                        triggered.append(listener_name)
+                elif condition_type == "AND":
+                    if listener_name not in self._pending_and_listeners:
+                        self._pending_and_listeners[listener_name] = set(methods)
+                    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]:
+                        triggered.append(listener_name)
+                        self._pending_and_listeners.pop(listener_name, None)
+
+            elif isinstance(condition_data, dict):
+                if self._evaluate_condition(
+                    condition_data, trigger_method, listener_name
+                ):
                     triggered.append(listener_name)
-                    # Reset pending methods for this listener
-                    self._pending_and_listeners.pop(listener_name, None)
 
         return triggered
 
@@ -1218,7 +1362,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
             raise
 
     def _log_flow_event(
-        self, message: str, color: str = "yellow", level: str = "info"
+        self, message: str, color: PrinterColor | None = "yellow", level: str = "info"
     ) -> None:
         """Centralized logging method for flow events.
 

src/crewai/utilities/printer.py

@@ -1,6 +1,11 @@
 """Utility for colored console output."""
 
-from typing import Final, Literal, NamedTuple
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Final, Literal, NamedTuple
+
+if TYPE_CHECKING:
+    from _typeshed import SupportsWrite
 
 PrinterColor = Literal[
     "purple",
@@ -54,13 +59,22 @@ class Printer:
 
     @staticmethod
     def print(
-        content: str | list[ColoredText], color: PrinterColor | None = None
+        content: str | list[ColoredText],
+        color: PrinterColor | None = None,
+        sep: str | None = " ",
+        end: str | None = "\n",
+        file: SupportsWrite[str] | None = None,
+        flush: Literal[False] = False,
     ) -> None:
         """Prints content to the console with optional color formatting.
 
         Args:
             content: Either a string or a list of ColoredText objects for multicolor output.
             color: Optional color for the text when content is a string. Ignored when content is a list.
+            sep: Separator to use between the text and color.
+            end: String appended after the last value.
+            file: A file-like object (stream); defaults to the current sys.stdout.
+            flush: Whether to forcibly flush the stream.
         """
         if isinstance(content, str):
             content = [ColoredText(content, color)]
@@ -68,5 +82,9 @@ class Printer:
             "".join(
                 f"{_COLOR_CODES[c.color] if c.color else ''}{c.text}{RESET}"
                 for c in content
-            )
+            ),
+            sep=sep,
+            end=end,
+            file=file,
+            flush=flush,
         )

tests/test_flow.py

@@ -6,15 +6,15 @@ from datetime import datetime
 import pytest
 from pydantic import BaseModel
 
-from crewai.flow.flow import Flow, and_, listen, or_, router, start
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.types.flow_events import (
     FlowFinishedEvent,
-    FlowStartedEvent,
     FlowPlotEvent,
+    FlowStartedEvent,
     MethodExecutionFinishedEvent,
     MethodExecutionStartedEvent,
 )
+from crewai.flow.flow import Flow, and_, listen, or_, router, start
 
 
 def test_simple_sequential_flow():
@@ -679,11 +679,11 @@ def test_structured_flow_event_emission():
     assert isinstance(received_events[3], MethodExecutionStartedEvent)
     assert received_events[3].method_name == "send_welcome_message"
     assert received_events[3].params == {}
-    assert getattr(received_events[3].state, "sent") is False
+    assert received_events[3].state.sent is False
 
     assert isinstance(received_events[4], MethodExecutionFinishedEvent)
     assert received_events[4].method_name == "send_welcome_message"
-    assert getattr(received_events[4].state, "sent") is True
+    assert received_events[4].state.sent is True
     assert received_events[4].result == "Welcome, Anakin!"
 
     assert isinstance(received_events[5], FlowFinishedEvent)
@@ -894,3 +894,75 @@ def test_flow_name():
 
     flow = MyFlow()
     assert flow.name == "MyFlow"
+
+
+def test_nested_and_or_conditions():
+    """Test nested conditions like or_(and_(A, B), and_(C, D)).
+
+    Reproduces bug from issue #3719 where nested conditions are flattened,
+    causing premature execution.
+    """
+    execution_order = []
+
+    class NestedConditionFlow(Flow):
+        @start()
+        def method_1(self):
+            execution_order.append("method_1")
+
+        @listen(method_1)
+        def method_2(self):
+            execution_order.append("method_2")
+
+        @router(method_2)
+        def method_3(self):
+            execution_order.append("method_3")
+            # Choose b_condition path
+            return "b_condition"
+
+        @listen("b_condition")
+        def method_5(self):
+            execution_order.append("method_5")
+
+        @listen(method_5)
+        async def method_4(self):
+            execution_order.append("method_4")
+
+        @listen(or_("a_condition", "b_condition"))
+        async def method_6(self):
+            execution_order.append("method_6")
+
+        @listen(
+            or_(
+                and_("a_condition", method_6),
+                and_(method_6, method_4),
+            )
+        )
+        def method_7(self):
+            execution_order.append("method_7")
+
+        @listen(method_7)
+        async def method_8(self):
+            execution_order.append("method_8")
+
+    flow = NestedConditionFlow()
+    flow.kickoff()
+
+    # Verify execution happened
+    assert "method_1" in execution_order
+    assert "method_2" in execution_order
+    assert "method_3" in execution_order
+    assert "method_5" in execution_order
+    assert "method_4" in execution_order
+    assert "method_6" in execution_order
+    assert "method_7" in execution_order
+    assert "method_8" in execution_order
+
+    # Critical assertion: method_7 should only execute AFTER both method_6 AND method_4
+    # Since b_condition was returned, method_6 triggers on b_condition
+    # method_7 requires: (a_condition AND method_6) OR (method_6 AND method_4)
+    # The second condition (method_6 AND method_4) should be the one that triggers
+    assert execution_order.index("method_7") > execution_order.index("method_6")
+    assert execution_order.index("method_7") > execution_order.index("method_4")
+
+    # method_8 should execute after method_7
+    assert execution_order.index("method_8") > execution_order.index("method_7")

tests/test_flow_pydantic_required_fields.py

@@ -0,0 +1,145 @@
+"""Tests for Flow initialization with Pydantic models having required fields.
+Covers https://github.com/crewAIInc/crewAI/issues/3744
+"""
+
+import pytest
+from pydantic import BaseModel, ValidationError
+
+from crewai.flow.flow import Flow, FlowState, listen, start
+
+
+class RequiredState(BaseModel):
+    """State model with required fields."""
+    name: str
+    age: int
+
+
+class RequiredStateFlow(Flow[RequiredState]):
+    """Flow with required state fields."""
+    
+    @start()
+    def begin(self):
+        return "started"
+
+
+class MixedState(BaseModel):
+    """State model with both required and optional fields."""
+    name: str  # Required
+    age: int  # Required
+    email: str = "default@example.com"  # Optional with default
+
+
+class MixedStateFlow(Flow[MixedState]):
+    """Flow with mixed required and optional state fields."""
+    
+    @start()
+    def begin(self):
+        return f"Started with {self.state.name}, {self.state.age}, {self.state.email}"
+
+
+class RequiredStateWithFlowState(FlowState):
+    """State model extending FlowState with required fields."""
+    name: str
+    age: int
+
+
+class RequiredFlowStateFlow(Flow[RequiredStateWithFlowState]):
+    """Flow with required FlowState fields."""
+    
+    @start()
+    def begin(self):
+        return "started"
+
+
+def test_flow_initialization_without_kwargs_raises_validation_error():
+    """Test that Flow initialization without kwargs raises ValidationError for required fields."""
+    with pytest.raises(ValidationError) as exc_info:
+        RequiredStateFlow()
+    
+    error_str = str(exc_info.value)
+    assert "name" in error_str
+    assert "age" in error_str
+
+
+def test_flow_initialization_with_kwargs_passes_and_sets_state():
+    """Test that Flow initialization with kwargs properly sets state values."""
+    flow = RequiredStateFlow(name="John", age=30)
+    assert flow.state.name == "John"
+    assert flow.state.age == 30
+    assert hasattr(flow.state, "id")
+    assert flow.state.id is not None
+
+
+def test_flow_initialization_with_partial_kwargs_raises_validation_error():
+    """Test that Flow initialization with only some required kwargs raises ValidationError."""
+    with pytest.raises(ValidationError) as exc_info:
+        RequiredStateFlow(name="John")
+    
+    error_str = str(exc_info.value)
+    assert "age" in error_str
+
+
+def test_flow_initialization_with_mixed_required_and_optional_fields():
+    """Test Flow initialization with both required and optional fields."""
+    flow1 = MixedStateFlow(name="Alice", age=25)
+    assert flow1.state.name == "Alice"
+    assert flow1.state.age == 25
+    assert flow1.state.email == "default@example.com"
+    
+    flow2 = MixedStateFlow(name="Bob", age=35, email="bob@example.com")
+    assert flow2.state.name == "Bob"
+    assert flow2.state.age == 35
+    assert flow2.state.email == "bob@example.com"
+
+
+def test_flow_initialization_with_flowstate_and_required_fields():
+    """Test Flow initialization with FlowState subclass having required fields."""
+    flow = RequiredFlowStateFlow(name="Charlie", age=40)
+    assert flow.state.name == "Charlie"
+    assert flow.state.age == 40
+    assert hasattr(flow.state, "id")
+    assert flow.state.id is not None
+
+
+def test_flow_execution_with_required_state():
+    """Test that Flow execution works correctly with required state fields."""
+    flow = RequiredStateFlow(name="David", age=45)
+    result = flow.kickoff()
+    assert result == "started"
+    assert flow.state.name == "David"
+    assert flow.state.age == 45
+
+
+def test_flow_with_state_modification():
+    """Test that state can be modified during flow execution."""
+    
+    class ModifiableState(BaseModel):
+        counter: int
+        name: str
+    
+    class ModifiableFlow(Flow[ModifiableState]):
+        @start()
+        def increment(self):
+            self.state.counter += 10
+            return "incremented"
+        
+        @listen(increment)
+        def check_value(self):
+            assert self.state.counter == 15
+            return "checked"
+    
+    flow = ModifiableFlow(counter=5, name="Test")
+    result = flow.kickoff()
+    assert result == "checked"
+    assert flow.state.counter == 15
+
+
+def test_flow_initialization_preserves_id_field():
+    """Test that the automatically generated id field is preserved."""
+    flow = RequiredStateFlow(name="Eve", age=28)
+    original_id = flow.state.id
+    
+    assert isinstance(original_id, str)
+    assert len(original_id) == 36  # UUID format with hyphens
+    
+    assert flow.state.id == original_id