fix: add async HITL support and chained-router tests

asynchronous human-in-the-loop handling and related fixes.

- Extend human_input provider with async support: AsyncExecutorContext, handle_feedback_async, async prompt helpers (_prompt_input_async, _async_readline), and async training/regular feedback loops in SyncHumanInputProvider.
- Add async handler methods in CrewAgentExecutor and AgentExecutor (_ahandle_human_feedback, _ainvoke_loop) to integrate async provider flows.
- Change PlusAPI.get_agent to an async httpx call and adapt caller in agent_utils to run it via asyncio.run.
- Simplify listener execution in flow.Flow to correctly pass HumanFeedbackResult to listeners and unify execution path for router outcomes.
- Remove deprecated types/hitl.py definitions.
- Add tests covering chained router feedback, rejected paths, and mixed router/non-router listeners to prevent regressions.

lib/crewai/src/crewai/agents/crew_agent_executor.py

@@ -1009,7 +1009,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             raise
 
         if self.ask_for_human_input:
-            formatted_answer = self._handle_human_feedback(formatted_answer)
+            formatted_answer = await self._ahandle_human_feedback(formatted_answer)
 
         self._create_short_term_memory(formatted_answer)
         self._create_long_term_memory(formatted_answer)
@@ -1508,6 +1508,20 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         provider = get_provider()
         return provider.handle_feedback(formatted_answer, self)
 
+    async def _ahandle_human_feedback(
+        self, formatted_answer: AgentFinish
+    ) -> AgentFinish:
+        """Process human feedback asynchronously via the configured provider.
+
+        Args:
+            formatted_answer: Initial agent result.
+
+        Returns:
+            Final answer after feedback.
+        """
+        provider = get_provider()
+        return await provider.handle_feedback_async(formatted_answer, self)
+
     def _is_training_mode(self) -> bool:
         """Check if training mode is active.
 

lib/crewai/src/crewai/cli/plus_api.py

@@ -1,6 +1,8 @@
+import os
 from typing import Any
 from urllib.parse import urljoin
-import os
+
+import httpx
 import requests
 
 from crewai.cli.config import Settings
@@ -33,7 +35,11 @@ class PlusAPI:
         if settings.org_uuid:
             self.headers["X-Crewai-Organization-Id"] = settings.org_uuid
 
-        self.base_url = os.getenv("CREWAI_PLUS_URL") or str(settings.enterprise_base_url) or DEFAULT_CREWAI_ENTERPRISE_URL
+        self.base_url = (
+            os.getenv("CREWAI_PLUS_URL")
+            or str(settings.enterprise_base_url)
+            or DEFAULT_CREWAI_ENTERPRISE_URL
+        )
 
     def _make_request(
         self, method: str, endpoint: str, **kwargs: Any
@@ -49,8 +55,10 @@ class PlusAPI:
     def get_tool(self, handle: str) -> requests.Response:
         return self._make_request("GET", f"{self.TOOLS_RESOURCE}/{handle}")
 
-    def get_agent(self, handle: str) -> requests.Response:
-        return self._make_request("GET", f"{self.AGENTS_RESOURCE}/{handle}")
+    async def get_agent(self, handle: str) -> httpx.Response:
+        url = urljoin(self.base_url, f"{self.AGENTS_RESOURCE}/{handle}")
+        async with httpx.AsyncClient() as client:
+            return await client.get(url, headers=self.headers)
 
     def publish_tool(
         self,

lib/crewai/src/crewai/context.py

@@ -43,3 +43,23 @@ def platform_context(integration_token: str) -> Generator[None, Any, None]:
         yield
     finally:
         _platform_integration_token.reset(token)
+
+
+_current_task_id: contextvars.ContextVar[str | None] = contextvars.ContextVar(
+    "current_task_id", default=None
+)
+
+
+def set_current_task_id(task_id: str | None) -> contextvars.Token[str | None]:
+    """Set the current task ID in the context. Returns a token for reset."""
+    return _current_task_id.set(task_id)
+
+
+def reset_current_task_id(token: contextvars.Token[str | None]) -> None:
+    """Reset the current task ID to its previous value."""
+    _current_task_id.reset(token)
+
+
+def get_current_task_id() -> str | None:
+    """Get the current task ID from the context."""
+    return _current_task_id.get()

lib/crewai/src/crewai/core/providers/human_input.py

@@ -2,7 +2,9 @@
 
 from __future__ import annotations
 
+import asyncio
 from contextvars import ContextVar, Token
+import sys
 from typing import TYPE_CHECKING, Protocol, runtime_checkable
 
 
@@ -46,13 +48,21 @@ class ExecutorContext(Protocol):
         ...
 
 
+class AsyncExecutorContext(ExecutorContext, Protocol):
+    """Extended context for executors that support async invocation."""
+
+    async def _ainvoke_loop(self) -> AgentFinish:
+        """Invoke the agent loop asynchronously and return the result."""
+        ...
+
+
 @runtime_checkable
 class HumanInputProvider(Protocol):
     """Protocol for human input handling.
 
     Implementations handle the full feedback flow:
     - Sync: prompt user, loop until satisfied
-    - Async: raise exception for external handling
+    - Async: use non-blocking I/O and async invoke loop
     """
 
     def setup_messages(self, context: ExecutorContext) -> bool:
@@ -86,7 +96,7 @@ class HumanInputProvider(Protocol):
         formatted_answer: AgentFinish,
         context: ExecutorContext,
     ) -> AgentFinish:
-        """Handle the full human feedback flow.
+        """Handle the full human feedback flow synchronously.
 
         Args:
             formatted_answer: The agent's current answer.
@@ -100,6 +110,25 @@ class HumanInputProvider(Protocol):
         """
         ...
 
+    async def handle_feedback_async(
+        self,
+        formatted_answer: AgentFinish,
+        context: AsyncExecutorContext,
+    ) -> AgentFinish:
+        """Handle the full human feedback flow asynchronously.
+
+        Uses non-blocking I/O for user prompts and async invoke loop
+        for agent re-execution.
+
+        Args:
+            formatted_answer: The agent's current answer.
+            context: Async executor context for callbacks.
+
+        Returns:
+            The final answer after feedback processing.
+        """
+        ...
+
     @staticmethod
     def _get_output_string(answer: AgentFinish) -> str:
         """Extract output string from answer.
@@ -116,7 +145,7 @@ class HumanInputProvider(Protocol):
 
 
 class SyncHumanInputProvider(HumanInputProvider):
-    """Default synchronous human input via terminal."""
+    """Default human input provider with sync and async support."""
 
     def setup_messages(self, context: ExecutorContext) -> bool:
         """Use standard message setup.
@@ -157,6 +186,33 @@ class SyncHumanInputProvider(HumanInputProvider):
 
         return self._handle_regular_feedback(formatted_answer, feedback, context)
 
+    async def handle_feedback_async(
+        self,
+        formatted_answer: AgentFinish,
+        context: AsyncExecutorContext,
+    ) -> AgentFinish:
+        """Handle feedback asynchronously without blocking the event loop.
+
+        Args:
+            formatted_answer: The agent's current answer.
+            context: Async executor context for callbacks.
+
+        Returns:
+            The final answer after feedback processing.
+        """
+        feedback = await self._prompt_input_async(context.crew)
+
+        if context._is_training_mode():
+            return await self._handle_training_feedback_async(
+                formatted_answer, feedback, context
+            )
+
+        return await self._handle_regular_feedback_async(
+            formatted_answer, feedback, context
+        )
+
+    # ── Sync helpers ──────────────────────────────────────────────────
+
     @staticmethod
     def _handle_training_feedback(
         initial_answer: AgentFinish,
@@ -209,6 +265,62 @@ class SyncHumanInputProvider(HumanInputProvider):
 
         return answer
 
+    # ── Async helpers ─────────────────────────────────────────────────
+
+    @staticmethod
+    async def _handle_training_feedback_async(
+        initial_answer: AgentFinish,
+        feedback: str,
+        context: AsyncExecutorContext,
+    ) -> AgentFinish:
+        """Process training feedback asynchronously (single iteration).
+
+        Args:
+            initial_answer: The agent's initial answer.
+            feedback: Human feedback string.
+            context: Async executor context for callbacks.
+
+        Returns:
+            Improved answer after processing feedback.
+        """
+        context._handle_crew_training_output(initial_answer, feedback)
+        context.messages.append(context._format_feedback_message(feedback))
+        improved_answer = await context._ainvoke_loop()
+        context._handle_crew_training_output(improved_answer)
+        context.ask_for_human_input = False
+        return improved_answer
+
+    async def _handle_regular_feedback_async(
+        self,
+        current_answer: AgentFinish,
+        initial_feedback: str,
+        context: AsyncExecutorContext,
+    ) -> AgentFinish:
+        """Process regular feedback with async iteration loop.
+
+        Args:
+            current_answer: The agent's current answer.
+            initial_feedback: Initial human feedback string.
+            context: Async executor context for callbacks.
+
+        Returns:
+            Final answer after all feedback iterations.
+        """
+        feedback = initial_feedback
+        answer = current_answer
+
+        while context.ask_for_human_input:
+            if feedback.strip() == "":
+                context.ask_for_human_input = False
+            else:
+                context.messages.append(context._format_feedback_message(feedback))
+                answer = await context._ainvoke_loop()
+                feedback = await self._prompt_input_async(context.crew)
+
+        return answer
+
+    # ── I/O ───────────────────────────────────────────────────────────
+
     @staticmethod
     def _prompt_input(crew: Crew | None) -> str:
         """Show rich panel and prompt for input.
@@ -262,6 +374,79 @@ class SyncHumanInputProvider(HumanInputProvider):
         finally:
             formatter.resume_live_updates()
 
+    @staticmethod
+    async def _prompt_input_async(crew: Crew | None) -> str:
+        """Show rich panel and prompt for input without blocking the event loop.
+
+        Args:
+            crew: The crew instance for context.
+
+        Returns:
+            User input string from terminal.
+        """
+        from rich.panel import Panel
+        from rich.text import Text
+
+        from crewai.events.event_listener import event_listener
+
+        formatter = event_listener.formatter
+        formatter.pause_live_updates()
+
+        try:
+            if crew and getattr(crew, "_train", False):
+                prompt_text = (
+                    "TRAINING MODE: Provide feedback to improve the agent's performance.\n\n"
+                    "This will be used to train better versions of the agent.\n"
+                    "Please provide detailed feedback about the result quality and reasoning process."
+                )
+                title = "🎓 Training Feedback Required"
+            else:
+                prompt_text = (
+                    "Provide feedback on the Final Result above.\n\n"
+                    "• If you are happy with the result, simply hit Enter without typing anything.\n"
+                    "• Otherwise, provide specific improvement requests.\n"
+                    "• You can provide multiple rounds of feedback until satisfied."
+                )
+                title = "💬 Human Feedback Required"
+
+            content = Text()
+            content.append(prompt_text, style="yellow")
+
+            prompt_panel = Panel(
+                content,
+                title=title,
+                border_style="yellow",
+                padding=(1, 2),
+            )
+            formatter.console.print(prompt_panel)
+
+            response = await _async_readline()
+            if response.strip() != "":
+                formatter.console.print("\n[cyan]Processing your feedback...[/cyan]")
+            return response
+        finally:
+            formatter.resume_live_updates()
+
+
+async def _async_readline() -> str:
+    """Read a line from stdin using the event loop's native I/O.
+
+    Falls back to asyncio.to_thread on platforms where piping stdin
+    is unsupported.
+
+    Returns:
+        The line read from stdin, with trailing newline stripped.
+    """
+    loop = asyncio.get_running_loop()
+    try:
+        reader = asyncio.StreamReader()
+        protocol = asyncio.StreamReaderProtocol(reader)
+        await loop.connect_read_pipe(lambda: protocol, sys.stdin)
+        raw = await reader.readline()
+        return raw.decode().rstrip("\n")
+    except (OSError, NotImplementedError, ValueError):
+        return await asyncio.to_thread(input)
+
 
 _provider: ContextVar[HumanInputProvider | None] = ContextVar(
     "human_input_provider",

lib/crewai/src/crewai/crew.py

@@ -1517,6 +1517,7 @@ class Crew(FlowTrackable, BaseModel):
         final_string_output = final_task_output.raw
         self._finish_execution(final_string_output)
         self.token_usage = self.calculate_usage_metrics()
+        crewai_event_bus.flush()
         crewai_event_bus.emit(
             self,
             CrewKickoffCompletedEvent(

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -32,7 +32,8 @@ from crewai.events.types.tool_usage_events import (
     ToolUsageFinishedEvent,
     ToolUsageStartedEvent,
 )
-from crewai.flow.flow import Flow, listen, or_, router, start
+from crewai.flow.flow import Flow, StateProxy, listen, or_, router, start
+from crewai.flow.types import FlowMethodName
 from crewai.hooks.llm_hooks import (
     get_after_llm_call_hooks,
     get_before_llm_call_hooks,
@@ -225,7 +226,11 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
     @messages.setter
     def messages(self, value: list[LLMMessage]) -> None:
         """Delegate to state for ExecutorContext conformance."""
-        self._state.messages = value
+        if self._flow_initialized and hasattr(self, "_state_lock"):
+            with self._state_lock:
+                self._state.messages = value
+        else:
+            self._state.messages = value
 
     @property
     def ask_for_human_input(self) -> bool:
@@ -253,6 +258,22 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             raise RuntimeError("Agent loop did not produce a final answer")
         return answer
 
+    async def _ainvoke_loop(self) -> AgentFinish:
+        """Invoke the agent loop asynchronously and return the result.
+
+        Required by AsyncExecutorContext protocol.
+        """
+        self._state.iterations = 0
+        self._state.is_finished = False
+        self._state.current_answer = None
+
+        await self.akickoff()
+
+        answer = self._state.current_answer
+        if not isinstance(answer, AgentFinish):
+            raise RuntimeError("Agent loop did not produce a final answer")
+        return answer
+
     def _format_feedback_message(self, feedback: str) -> LLMMessage:
         """Format feedback as a message for the LLM.
 
@@ -353,6 +374,8 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
         Flow initialization is deferred to prevent event emission during agent setup.
         Returns the temporary state until invoke() is called.
         """
+        if self._flow_initialized and hasattr(self, "_state_lock"):
+            return StateProxy(self._state, self._state_lock)  # type: ignore[return-value]
         return self._state
 
     @property
@@ -461,15 +484,14 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             raise
 
     @listen("continue_reasoning_native")
-    def call_llm_native_tools(
-        self,
-    ) -> Literal["native_tool_calls", "native_finished", "context_error"]:
+    def call_llm_native_tools(self) -> None:
         """Execute LLM call with native function calling.
 
         Always calls the LLM so it can read reflection prompts and decide
         whether to provide a final answer or request more tools.
 
-        Returns routing decision based on whether tool calls or final answer.
+        Note: This is a listener, not a router. The route_native_tool_result
+        router fires after this to determine the next step based on state.
         """
         try:
             # Clear pending tools - LLM will decide what to do next after reading
@@ -499,8 +521,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             if isinstance(answer, list) and answer and self._is_tool_call_list(answer):
                 # Store tool calls for sequential processing
                 self.state.pending_tool_calls = list(answer)
-
-                return "native_tool_calls"
+                return  # Router will check pending_tool_calls
 
             if isinstance(answer, BaseModel):
                 self.state.current_answer = AgentFinish(
@@ -510,7 +531,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                 )
                 self._invoke_step_callback(self.state.current_answer)
                 self._append_message_to_state(answer.model_dump_json())
-                return "native_finished"
+                return  # Router will check current_answer
 
             # Text response - this is the final answer
             if isinstance(answer, str):
@@ -521,8 +542,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                 )
                 self._invoke_step_callback(self.state.current_answer)
                 self._append_message_to_state(answer)
-
-                return "native_finished"
+                return  # Router will check current_answer
 
             # Unexpected response type, treat as final answer
             self.state.current_answer = AgentFinish(
@@ -532,13 +552,12 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             )
             self._invoke_step_callback(self.state.current_answer)
             self._append_message_to_state(str(answer))
-
-            return "native_finished"
+            # Router will check current_answer
 
         except Exception as e:
             if is_context_length_exceeded(e):
                 self._last_context_error = e
-                return "context_error"
+                return  # Router will check _last_context_error
             if e.__class__.__module__.startswith("litellm"):
                 raise e
             handle_unknown_error(self._printer, e, verbose=self.agent.verbose)
@@ -551,6 +570,22 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             return "execute_tool"
         return "agent_finished"
 
+    @router(call_llm_native_tools)
+    def route_native_tool_result(
+        self,
+    ) -> Literal["native_tool_calls", "native_finished", "context_error"]:
+        """Route based on LLM response for native tool calling.
+
+        Checks state set by call_llm_native_tools to determine next step.
+        This router is needed because only router return values trigger
+        downstream listeners.
+        """
+        if self._last_context_error is not None:
+            return "context_error"
+        if self.state.pending_tool_calls:
+            return "native_tool_calls"
+        return "native_finished"
+
     @listen("execute_tool")
     def execute_tool_action(self) -> Literal["tool_completed", "tool_result_is_final"]:
         """Execute the tool action and handle the result."""
@@ -908,9 +943,11 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
         self.state.iterations += 1
         return "initialized"
 
-    @listen("initialized")
+    @listen(or_("initialized", "tool_completed", "native_tool_completed"))
     def continue_iteration(self) -> Literal["check_iteration"]:
         """Bridge listener that connects iteration loop back to iteration check."""
+        if self._flow_initialized:
+            self._discard_or_listener(FlowMethodName("continue_iteration"))
         return "check_iteration"
 
     @router(or_(initialize_reasoning, continue_iteration))
@@ -1152,7 +1189,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                 )
 
             if self.state.ask_for_human_input:
-                formatted_answer = self._handle_human_feedback(formatted_answer)
+                formatted_answer = await self._ahandle_human_feedback(formatted_answer)
 
             self._create_short_term_memory(formatted_answer)
             self._create_long_term_memory(formatted_answer)
@@ -1369,6 +1406,20 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
         provider = get_provider()
         return provider.handle_feedback(formatted_answer, self)
 
+    async def _ahandle_human_feedback(
+        self, formatted_answer: AgentFinish
+    ) -> AgentFinish:
+        """Process human feedback asynchronously and refine answer.
+
+        Args:
+            formatted_answer: Initial agent result.
+
+        Returns:
+            Final answer after feedback.
+        """
+        provider = get_provider()
+        return await provider.handle_feedback_async(formatted_answer, self)
+
     def _is_training_mode(self) -> bool:
         """Check if training mode is active.
 

lib/crewai/src/crewai/flow/flow.py

@@ -7,7 +7,14 @@ for building event-driven workflows with conditional execution and routing.
 from __future__ import annotations
 
 import asyncio
-from collections.abc import Callable, Sequence
+from collections.abc import (
+    Callable,
+    ItemsView,
+    Iterator,
+    KeysView,
+    Sequence,
+    ValuesView,
+)
 from concurrent.futures import Future
 import copy
 import inspect
@@ -409,6 +416,132 @@ def and_(*conditions: str | FlowCondition | Callable[..., Any]) -> FlowCondition
     return {"type": AND_CONDITION, "conditions": processed_conditions}
 
 
+class LockedListProxy(Generic[T]):
+    """Thread-safe proxy for list operations.
+
+    Wraps a list and uses a lock for all mutating operations.
+    """
+
+    def __init__(self, lst: list[T], lock: threading.Lock) -> None:
+        self._list = lst
+        self._lock = lock
+
+    def append(self, item: T) -> None:
+        with self._lock:
+            self._list.append(item)
+
+    def extend(self, items: list[T]) -> None:
+        with self._lock:
+            self._list.extend(items)
+
+    def insert(self, index: int, item: T) -> None:
+        with self._lock:
+            self._list.insert(index, item)
+
+    def remove(self, item: T) -> None:
+        with self._lock:
+            self._list.remove(item)
+
+    def pop(self, index: int = -1) -> T:
+        with self._lock:
+            return self._list.pop(index)
+
+    def clear(self) -> None:
+        with self._lock:
+            self._list.clear()
+
+    def __setitem__(self, index: int, value: T) -> None:
+        with self._lock:
+            self._list[index] = value
+
+    def __delitem__(self, index: int) -> None:
+        with self._lock:
+            del self._list[index]
+
+    def __getitem__(self, index: int) -> T:
+        return self._list[index]
+
+    def __len__(self) -> int:
+        return len(self._list)
+
+    def __iter__(self) -> Iterator[T]:
+        return iter(self._list)
+
+    def __contains__(self, item: object) -> bool:
+        return item in self._list
+
+    def __repr__(self) -> str:
+        return repr(self._list)
+
+    def __bool__(self) -> bool:
+        return bool(self._list)
+
+
+class LockedDictProxy(Generic[T]):
+    """Thread-safe proxy for dict operations.
+
+    Wraps a dict and uses a lock for all mutating operations.
+    """
+
+    def __init__(self, d: dict[str, T], lock: threading.Lock) -> None:
+        self._dict = d
+        self._lock = lock
+
+    def __setitem__(self, key: str, value: T) -> None:
+        with self._lock:
+            self._dict[key] = value
+
+    def __delitem__(self, key: str) -> None:
+        with self._lock:
+            del self._dict[key]
+
+    def pop(self, key: str, *default: T) -> T:
+        with self._lock:
+            return self._dict.pop(key, *default)
+
+    def update(self, other: dict[str, T]) -> None:
+        with self._lock:
+            self._dict.update(other)
+
+    def clear(self) -> None:
+        with self._lock:
+            self._dict.clear()
+
+    def setdefault(self, key: str, default: T) -> T:
+        with self._lock:
+            return self._dict.setdefault(key, default)
+
+    def __getitem__(self, key: str) -> T:
+        return self._dict[key]
+
+    def __len__(self) -> int:
+        return len(self._dict)
+
+    def __iter__(self) -> Iterator[str]:
+        return iter(self._dict)
+
+    def __contains__(self, key: object) -> bool:
+        return key in self._dict
+
+    def keys(self) -> KeysView[str]:
+        return self._dict.keys()
+
+    def values(self) -> ValuesView[T]:
+        return self._dict.values()
+
+    def items(self) -> ItemsView[str, T]:
+        return self._dict.items()
+
+    def get(self, key: str, default: T | None = None) -> T | None:
+        return self._dict.get(key, default)
+
+    def __repr__(self) -> str:
+        return repr(self._dict)
+
+    def __bool__(self) -> bool:
+        return bool(self._dict)
+
+
 class StateProxy(Generic[T]):
     """Proxy that provides thread-safe access to flow state.
 
@@ -423,7 +556,13 @@ class StateProxy(Generic[T]):
         object.__setattr__(self, "_proxy_lock", lock)
 
     def __getattr__(self, name: str) -> Any:
-        return getattr(object.__getattribute__(self, "_proxy_state"), name)
+        value = getattr(object.__getattribute__(self, "_proxy_state"), name)
+        lock = object.__getattribute__(self, "_proxy_lock")
+        if isinstance(value, list):
+            return LockedListProxy(value, lock)
+        if isinstance(value, dict):
+            return LockedDictProxy(value, lock)
+        return value
 
     def __setattr__(self, name: str, value: Any) -> None:
         if name in ("_proxy_state", "_proxy_lock"):
@@ -1593,7 +1732,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 reset_emission_counter()
                 reset_last_event_id()
 
-            # Emit FlowStartedEvent and log the start of the flow.
             if not self.suppress_flow_events:
                 future = crewai_event_bus.emit(
                     self,
@@ -1604,7 +1742,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     ),
                 )
                 if future:
-                    self._event_futures.append(future)
+                    try:
+                        await asyncio.wrap_future(future)
+                    except Exception:
+                        logger.warning("FlowStartedEvent handler failed", exc_info=True)
                 self._log_flow_event(
                     f"Flow started with ID: {self.flow_id}", color="bold magenta"
                 )
@@ -1696,6 +1837,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
             final_output = self._method_outputs[-1] if self._method_outputs else None
 
+            if self._event_futures:
+                await asyncio.gather(
+                    *[asyncio.wrap_future(f) for f in self._event_futures]
+                )
+                self._event_futures.clear()
+
             if not self.suppress_flow_events:
                 future = crewai_event_bus.emit(
                     self,
@@ -1707,13 +1854,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     ),
                 )
                 if future:
-                    self._event_futures.append(future)
-
-            if self._event_futures:
-                await asyncio.gather(
-                    *[asyncio.wrap_future(f) for f in self._event_futures]
-                )
-                self._event_futures.clear()
+                    try:
+                        await asyncio.wrap_future(future)
+                    except Exception:
+                        logger.warning(
+                            "FlowFinishedEvent handler failed", exc_info=True
+                        )
 
             if not self.suppress_flow_events:
                 trace_listener = TraceCollectionListener()
@@ -1788,40 +1934,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
             await self._execute_listeners(start_method_name, result, finished_event_id)
             # Then execute listeners for the router result (e.g., "approved")
             router_result_trigger = FlowMethodName(str(result))
-            listeners_for_result = self._find_triggered_methods(
-                router_result_trigger, router_only=False
+            listener_result = (
+                self.last_human_feedback
+                if self.last_human_feedback is not None
+                else result
+            )
+            await self._execute_listeners(
+                router_result_trigger, listener_result, finished_event_id
             )
-            if listeners_for_result:
-                # Pass the HumanFeedbackResult if available
-                listener_result = (
-                    self.last_human_feedback
-                    if self.last_human_feedback is not None
-                    else result
-                )
-                racing_group = self._get_racing_group_for_listeners(
-                    listeners_for_result
-                )
-                if racing_group:
-                    racing_members, _ = racing_group
-                    other_listeners = [
-                        name
-                        for name in listeners_for_result
-                        if name not in racing_members
-                    ]
-                    await self._execute_racing_listeners(
-                        racing_members,
-                        other_listeners,
-                        listener_result,
-                        finished_event_id,
-                    )
-                else:
-                    tasks = [
-                        self._execute_single_listener(
-                            listener_name, listener_result, finished_event_id
-                        )
-                        for listener_name in listeners_for_result
-                    ]
-                    await asyncio.gather(*tasks)
         else:
             await self._execute_listeners(start_method_name, result, finished_event_id)
 
@@ -2027,15 +2147,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 router_input = router_result_to_feedback.get(
                     str(current_trigger), current_result
                 )
-                current_triggering_event_id = await self._execute_single_listener(
+                (
+                    router_result,
+                    current_triggering_event_id,
+                ) = await self._execute_single_listener(
                     router_name, router_input, current_triggering_event_id
                 )
-                # After executing router, the router's result is the path
-                router_result = (
-                    self._method_outputs[-1] if self._method_outputs else None
-                )
                 if router_result:  # Only add non-None results
-                    router_results.append(router_result)
+                    router_results.append(FlowMethodName(str(router_result)))
                     # If this was a human_feedback router, map the outcome to the feedback
                     if self.last_human_feedback is not None:
                         router_result_to_feedback[str(router_result)] = (
@@ -2265,7 +2384,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
         listener_name: FlowMethodName,
         result: Any,
         triggering_event_id: str | None = None,
-    ) -> str | None:
+    ) -> tuple[Any, str | None]:
         """Executes a single listener method with proper event handling.
 
         This internal method manages the execution of an individual listener,
@@ -2278,8 +2397,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 used for causal chain tracking.
 
         Returns:
-            The event_id of the MethodExecutionFinishedEvent emitted by this listener,
-            or None if events are suppressed.
+            A tuple of (listener_result, event_id) where listener_result is the return
+            value of the listener method and event_id is the MethodExecutionFinishedEvent
+            id, or (None, None) if skipped during resumption.
 
         Note:
             - Inspects method signature to determine if it accepts the trigger result
@@ -2305,7 +2425,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
                         ):
                             # This conditional start was executed, continue its chain
                             await self._execute_start_method(start_method_name)
-                return None
+                return (None, None)
             # For cyclic flows, clear from completed to allow re-execution
             self._completed_methods.discard(listener_name)
             # Also clear from fired OR listeners for cyclic flows
@@ -2343,46 +2463,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 listener_name, listener_result, finished_event_id
             )
 
-            # If this listener is also a router (e.g., has @human_feedback with emit),
-            # we need to trigger listeners for the router result as well
-            if listener_name in self._routers and listener_result is not None:
-                router_result_trigger = FlowMethodName(str(listener_result))
-                listeners_for_result = self._find_triggered_methods(
-                    router_result_trigger, router_only=False
-                )
-                if listeners_for_result:
-                    # Pass the HumanFeedbackResult if available
-                    feedback_result = (
-                        self.last_human_feedback
-                        if self.last_human_feedback is not None
-                        else listener_result
-                    )
-                    racing_group = self._get_racing_group_for_listeners(
-                        listeners_for_result
-                    )
-                    if racing_group:
-                        racing_members, _ = racing_group
-                        other_listeners = [
-                            name
-                            for name in listeners_for_result
-                            if name not in racing_members
-                        ]
-                        await self._execute_racing_listeners(
-                            racing_members,
-                            other_listeners,
-                            feedback_result,
-                            finished_event_id,
-                        )
-                    else:
-                        tasks = [
-                            self._execute_single_listener(
-                                name, feedback_result, finished_event_id
-                            )
-                            for name in listeners_for_result
-                        ]
-                        await asyncio.gather(*tasks)
-
-            return finished_event_id
+            return (listener_result, finished_event_id)
 
         except Exception as e:
             # Don't log HumanFeedbackPending as an error - it's expected control flow

lib/crewai/src/crewai/task.py

@@ -31,6 +31,7 @@ from pydantic_core import PydanticCustomError
 from typing_extensions import Self
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.context import reset_current_task_id, set_current_task_id
 from crewai.core.providers.content_processor import process_content
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.types.task_events import (
@@ -561,6 +562,7 @@ class Task(BaseModel):
         tools: list[Any] | None,
     ) -> TaskOutput:
         """Run the core execution logic of the task asynchronously."""
+        task_id_token = set_current_task_id(str(self.id))
         self._store_input_files()
         try:
             agent = agent or self.agent
@@ -648,6 +650,7 @@ class Task(BaseModel):
             raise e  # Re-raise the exception after emitting the event
         finally:
             clear_task_files(self.id)
+            reset_current_task_id(task_id_token)
 
     def _execute_core(
         self,
@@ -656,6 +659,7 @@ class Task(BaseModel):
         tools: list[Any] | None,
     ) -> TaskOutput:
         """Run the core execution logic of the task."""
+        task_id_token = set_current_task_id(str(self.id))
         self._store_input_files()
         try:
             agent = agent or self.agent
@@ -744,6 +748,7 @@ class Task(BaseModel):
             raise e  # Re-raise the exception after emitting the event
         finally:
             clear_task_files(self.id)
+            reset_current_task_id(task_id_token)
 
     def _post_agent_execution(self, agent: BaseAgent) -> None:
         pass

lib/crewai/src/crewai/types/hitl.py

@@ -1,37 +0,0 @@
-"""Human-in-the-loop (HITL) type definitions.
-
-This module provides type definitions for human-in-the-loop interactions
-in crew executions.
-"""
-
-from typing import TypedDict
-
-
-class HITLResumeInfo(TypedDict, total=False):
-    """HITL resume information passed from flow to crew.
-
-    Attributes:
-        task_id: Unique identifier for the task.
-        crew_execution_id: Unique identifier for the crew execution.
-        task_key: Key identifying the specific task.
-        task_output: Output from the task before human intervention.
-        human_feedback: Feedback provided by the human.
-        previous_messages: History of messages in the conversation.
-    """
-
-    task_id: str
-    crew_execution_id: str
-    task_key: str
-    task_output: str
-    human_feedback: str
-    previous_messages: list[dict[str, str]]
-
-
-class CrewInputsWithHITL(TypedDict, total=False):
-    """Crew inputs that may contain HITL resume information.
-
-    Attributes:
-        _hitl_resume: Optional HITL resume information for continuing execution.
-    """
-
-    _hitl_resume: HITLResumeInfo

lib/crewai/src/crewai/utilities/agent_utils.py

@@ -832,7 +832,7 @@ def load_agent_from_repository(from_repository: str) -> dict[str, Any]:
 
             client = PlusAPI(api_key=get_auth_token())
         _print_current_organization()
-        response = client.get_agent(from_repository)
+        response = asyncio.run(client.get_agent(from_repository))
         if response.status_code == 404:
             raise AgentRepositoryError(
                 f"Agent {from_repository} does not exist, make sure the name is correct or the agent is available on your organization."

lib/crewai/tests/agents/test_lite_agent.py

@@ -606,9 +606,10 @@ def test_lite_agent_with_invalid_llm():
 
 
 @patch.dict("os.environ", {"CREWAI_PLATFORM_INTEGRATION_TOKEN": "test_token"})
+@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_action_tool.requests.post")
 @patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_tool_builder.requests.get")
 @pytest.mark.vcr()
-def test_agent_kickoff_with_platform_tools(mock_get):
+def test_agent_kickoff_with_platform_tools(mock_get, mock_post):
     """Test that Agent.kickoff() properly integrates platform tools with LiteAgent"""
     mock_response = Mock()
     mock_response.raise_for_status.return_value = None
@@ -632,6 +633,15 @@ def test_agent_kickoff_with_platform_tools(mock_get):
     }
     mock_get.return_value = mock_response
 
+    # Mock the platform tool execution
+    mock_post_response = Mock()
+    mock_post_response.ok = True
+    mock_post_response.json.return_value = {
+        "success": True,
+        "issue_url": "https://github.com/test/repo/issues/1"
+    }
+    mock_post.return_value = mock_post_response
+
     agent = Agent(
         role="Test Agent",
         goal="Test goal",

lib/crewai/tests/cassettes/agents/test_agent_kickoff_with_platform_tools.yaml

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+        \     | Al-Hilal                   | Forward/Winger   | Dribbling, Creativity,
+        Flair    | Copa America Titles, Club Success |\\n| 7     | Mohamed Salah       |
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+        \"default\",\n  \"system_fingerprint\": \"fp_f4ae844694\"\n}\n"
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+      - Fri, 06 Feb 2026 18:41:58 GMT
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+      farewell agent\nYour personal goal is: Say goodbye"},{"role":"user","content":"\nCurrent
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     headers:
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@@ -159,27 +143,24 @@ interactions:
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lib/crewai/tests/cassettes/agents/test_native_tool_calling_error_handling.yaml

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+      - 3.13.5
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+        \"default\",\n  \"system_fingerprint\": \"fp_6c0d1490cb\"\n}\n"
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@@ -67,7 +66,7 @@ interactions:
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-      - '621'
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-      tool always fails","parameters":{"properties":{},"type":"object"}}}]}'
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@@ -134,7 +128,7 @@ interactions:
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+      - 3.13.5
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lib/crewai/tests/cassettes/llms/anthropic/test_anthropic_agent_kickoff_structured_output_with_tools.yaml

@@ -43,15 +43,15 @@ interactions:
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+      - 3.13.5
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+      string: '{"model":"claude-3-5-haiku-20241022","id":"msg_01A41GpDoJbZLUhR8dQzUcUX","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01UNPdzpayoWyqDYVE7fR5oA","name":"structured_output","input":{"operation":"Addition","result":42,"explanation":"Added
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+      - '2026-02-06T18:41:24Z'
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@@ -102,7 +102,7 @@ interactions:
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+      - '1247'
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+        employees and employers, transforming traditional workplace dynamics.","key_points":["Increased
+        flexibility in work schedule","Reduced commute time and transportation costs","Improved
+        work-life balance","Higher productivity for many employees","Cost savings
+        for companies on office infrastructure","Expanded talent pool for hiring","Enhanced
+        employee job satisfaction"]}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":589,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":142,"service_tier":"standard","inference_geo":"not_available"}}'
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@@ -109,7 +108,7 @@ interactions:
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-      - '3107'
+      - '2650'
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lib/crewai/tests/cli/test_plus_api.py

@@ -1,6 +1,8 @@
 import os
 import unittest
-from unittest.mock import ANY, MagicMock, patch
+from unittest.mock import ANY, AsyncMock, MagicMock, patch
+
+import pytest
 
 from crewai.cli.plus_api import PlusAPI
 
@@ -68,37 +70,6 @@ class TestPlusAPI(unittest.TestCase):
         )
         self.assertEqual(response, mock_response)
 
-    @patch("crewai.cli.plus_api.PlusAPI._make_request")
-    def test_get_agent(self, mock_make_request):
-        mock_response = MagicMock()
-        mock_make_request.return_value = mock_response
-
-        response = self.api.get_agent("test_agent_handle")
-        mock_make_request.assert_called_once_with(
-            "GET", "/crewai_plus/api/v1/agents/test_agent_handle"
-        )
-        self.assertEqual(response, mock_response)
-
-    @patch("crewai.cli.plus_api.Settings")
-    @patch("requests.Session.request")
-    def test_get_agent_with_org_uuid(self, mock_make_request, mock_settings_class):
-        mock_settings = MagicMock()
-        mock_settings.org_uuid = self.org_uuid
-        mock_settings.enterprise_base_url = os.getenv('CREWAI_PLUS_URL')
-        mock_settings_class.return_value = mock_settings
-        # re-initialize Client
-        self.api = PlusAPI(self.api_key)
-
-        mock_response = MagicMock()
-        mock_make_request.return_value = mock_response
-
-        response = self.api.get_agent("test_agent_handle")
-
-        self.assert_request_with_org_id(
-            mock_make_request, "GET", "/crewai_plus/api/v1/agents/test_agent_handle"
-        )
-        self.assertEqual(response, mock_response)
-
     @patch("crewai.cli.plus_api.PlusAPI._make_request")
     def test_get_tool(self, mock_make_request):
         mock_response = MagicMock()
@@ -338,3 +309,49 @@ class TestPlusAPI(unittest.TestCase):
             custom_api.base_url,
             "https://custom-url-from-env.com",
         )
+
+
+@pytest.mark.asyncio
+@patch("httpx.AsyncClient")
+async def test_get_agent(mock_async_client_class):
+    api = PlusAPI("test_api_key")
+    mock_response = MagicMock()
+    mock_client_instance = AsyncMock()
+    mock_client_instance.get.return_value = mock_response
+    mock_async_client_class.return_value.__aenter__.return_value = mock_client_instance
+
+    response = await api.get_agent("test_agent_handle")
+
+    mock_client_instance.get.assert_called_once_with(
+        f"{api.base_url}/crewai_plus/api/v1/agents/test_agent_handle",
+        headers=api.headers,
+    )
+    assert response == mock_response
+
+
+@pytest.mark.asyncio
+@patch("httpx.AsyncClient")
+@patch("crewai.cli.plus_api.Settings")
+async def test_get_agent_with_org_uuid(mock_settings_class, mock_async_client_class):
+    org_uuid = "test-org-uuid"
+    mock_settings = MagicMock()
+    mock_settings.org_uuid = org_uuid
+    mock_settings.enterprise_base_url = os.getenv("CREWAI_PLUS_URL")
+    mock_settings_class.return_value = mock_settings
+
+    api = PlusAPI("test_api_key")
+
+    mock_response = MagicMock()
+    mock_client_instance = AsyncMock()
+    mock_client_instance.get.return_value = mock_response
+    mock_async_client_class.return_value.__aenter__.return_value = mock_client_instance
+
+    response = await api.get_agent("test_agent_handle")
+
+    mock_client_instance.get.assert_called_once_with(
+        f"{api.base_url}/crewai_plus/api/v1/agents/test_agent_handle",
+        headers=api.headers,
+    )
+    assert "X-Crewai-Organization-Id" in api.headers
+    assert api.headers["X-Crewai-Organization-Id"] == org_uuid
+    assert response == mock_response

lib/crewai/tests/test_human_feedback_integration.py

@@ -157,6 +157,176 @@ class TestMultiStepFlows:
 
         assert execution_order == ["generate", "review", "finalize"]
 
+    def test_chained_router_feedback_steps(self):
+        """Test that a router outcome can trigger another router method.
+
+        Regression test: @listen("outcome") combined with @human_feedback(emit=...)
+        creates a method that is both a listener and a router. The flow must find
+        and execute it when the upstream router emits the matching outcome.
+        """
+        execution_order: list[str] = []
+
+        class ChainedRouterFlow(Flow):
+            @start()
+            @human_feedback(
+                message="First review:",
+                emit=["approved", "rejected"],
+                llm="gpt-4o-mini",
+            )
+            def draft(self):
+                execution_order.append("draft")
+                return "draft content"
+
+            @listen("approved")
+            @human_feedback(
+                message="Final review:",
+                emit=["publish", "revise"],
+                llm="gpt-4o-mini",
+            )
+            def final_review(self, prev: HumanFeedbackResult):
+                execution_order.append("final_review")
+                return "final content"
+
+            @listen("rejected")
+            def on_rejected(self, prev: HumanFeedbackResult):
+                execution_order.append("on_rejected")
+                return "rejected"
+
+            @listen("publish")
+            def on_publish(self, prev: HumanFeedbackResult):
+                execution_order.append("on_publish")
+                return "published"
+
+            @listen("revise")
+            def on_revise(self, prev: HumanFeedbackResult):
+                execution_order.append("on_revise")
+                return "revised"
+
+        flow = ChainedRouterFlow()
+
+        with (
+            patch.object(
+                flow,
+                "_request_human_feedback",
+                side_effect=["looks good", "ship it"],
+            ),
+            patch.object(
+                flow,
+                "_collapse_to_outcome",
+                side_effect=["approved", "publish"],
+            ),
+        ):
+            result = flow.kickoff()
+
+        assert execution_order == ["draft", "final_review", "on_publish"]
+        assert result == "published"
+        assert len(flow.human_feedback_history) == 2
+        assert flow.human_feedback_history[0].outcome == "approved"
+        assert flow.human_feedback_history[1].outcome == "publish"
+
+    def test_chained_router_rejected_path(self):
+        """Test that a start-router outcome routes to a non-router listener."""
+        execution_order: list[str] = []
+
+        class ChainedRouterFlow(Flow):
+            @start()
+            @human_feedback(
+                message="Review:",
+                emit=["approved", "rejected"],
+                llm="gpt-4o-mini",
+            )
+            def draft(self):
+                execution_order.append("draft")
+                return "draft"
+
+            @listen("approved")
+            @human_feedback(
+                message="Final:",
+                emit=["publish", "revise"],
+                llm="gpt-4o-mini",
+            )
+            def final_review(self, prev: HumanFeedbackResult):
+                execution_order.append("final_review")
+                return "final"
+
+            @listen("rejected")
+            def on_rejected(self, prev: HumanFeedbackResult):
+                execution_order.append("on_rejected")
+                return "rejected"
+
+        flow = ChainedRouterFlow()
+
+        with (
+            patch.object(
+                flow, "_request_human_feedback", return_value="bad"
+            ),
+            patch.object(
+                flow, "_collapse_to_outcome", return_value="rejected"
+            ),
+        ):
+            result = flow.kickoff()
+
+        assert execution_order == ["draft", "on_rejected"]
+        assert result == "rejected"
+        assert len(flow.human_feedback_history) == 1
+        assert flow.human_feedback_history[0].outcome == "rejected"
+
+    def test_router_and_non_router_listeners_for_same_outcome(self):
+        """Test that both router and non-router listeners fire for the same outcome."""
+        execution_order: list[str] = []
+
+        class MixedListenerFlow(Flow):
+            @start()
+            @human_feedback(
+                message="Review:",
+                emit=["approved", "rejected"],
+                llm="gpt-4o-mini",
+            )
+            def draft(self):
+                execution_order.append("draft")
+                return "draft"
+
+            @listen("approved")
+            @human_feedback(
+                message="Final:",
+                emit=["publish", "revise"],
+                llm="gpt-4o-mini",
+            )
+            def router_listener(self, prev: HumanFeedbackResult):
+                execution_order.append("router_listener")
+                return "final"
+
+            @listen("approved")
+            def plain_listener(self, prev: HumanFeedbackResult):
+                execution_order.append("plain_listener")
+                return "logged"
+
+            @listen("publish")
+            def on_publish(self, prev: HumanFeedbackResult):
+                execution_order.append("on_publish")
+                return "published"
+
+        flow = MixedListenerFlow()
+
+        with (
+            patch.object(
+                flow,
+                "_request_human_feedback",
+                side_effect=["approve it", "publish it"],
+            ),
+            patch.object(
+                flow,
+                "_collapse_to_outcome",
+                side_effect=["approved", "publish"],
+            ),
+        ):
+            flow.kickoff()
+
+        assert "draft" in execution_order
+        assert "router_listener" in execution_order
+        assert "plain_listener" in execution_order
+        assert "on_publish" in execution_order
+
 
 class TestStateManagement:
     """Tests for state management with human feedback."""