Improve EventListener and TraceCollectionListener for improved event… (#4160)

* Refactor EventListener and TraceCollectionListener for improved event handling

- Removed unused threading and method branches from EventListener to simplify the code.
- Updated event handling methods in EventListener to use new formatter methods for better clarity and consistency.
- Refactored TraceCollectionListener to eliminate unnecessary parameters in formatter calls, enhancing readability.
- Simplified ConsoleFormatter by removing outdated tree management methods and focusing on panel-based output for status updates.
- Enhanced ToolUsage to track run attempts for better tool usage metrics.

* clearer for knowledge retrieval and dropped some reduancies

* Refactor EventListener and ConsoleFormatter for improved clarity and consistency

- Removed the MCPToolExecutionCompletedEvent handler from EventListener to streamline event processing.
- Updated ConsoleFormatter to enhance output formatting by adding line breaks for better readability in status content.
- Renamed status messages for MCP Tool execution to provide clearer context during tool operations.

* fix run attempt incrementation

* task name consistency

* memory events consistency

* ensure hitl works

* linting

Author: lorenzejay

lib/crewai/src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -3,6 +3,7 @@
 import time
 from typing import TYPE_CHECKING
 
+from crewai.agents.parser import AgentFinish
 from crewai.events.event_listener import event_listener
 from crewai.memory.entity.entity_memory_item import EntityMemoryItem
 from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
@@ -29,7 +30,7 @@ class CrewAgentExecutorMixin:
     _i18n: I18N
     _printer: Printer = Printer()
 
-    def _create_short_term_memory(self, output) -> None:
+    def _create_short_term_memory(self, output: AgentFinish) -> None:
         """Create and save a short-term memory item if conditions are met."""
         if (
             self.crew
@@ -53,7 +54,7 @@ def _create_short_term_memory(self, output) -> None:
                     "error", f"Failed to add to short term memory: {e}"
                 )
 
-    def _create_external_memory(self, output) -> None:
+    def _create_external_memory(self, output: AgentFinish) -> None:
         """Create and save a external-term memory item if conditions are met."""
         if (
             self.crew
@@ -75,7 +76,7 @@ def _create_external_memory(self, output) -> None:
                     "error", f"Failed to add to external memory: {e}"
                 )
 
-    def _create_long_term_memory(self, output) -> None:
+    def _create_long_term_memory(self, output: AgentFinish) -> None:
         """Create and save long-term and entity memory items based on evaluation."""
         if (
             self.crew
@@ -136,40 +137,50 @@ def _create_long_term_memory(self, output) -> None:
             )
 
     def _ask_human_input(self, final_answer: str) -> str:
-        """Prompt human input with mode-appropriate messaging."""
-        event_listener.formatter.pause_live_updates()
-        try:
-            self._printer.print(
-                content=f"\033[1m\033[95m ## Final Result:\033[00m \033[92m{final_answer}\033[00m"
-            )
+        """Prompt human input with mode-appropriate messaging.
+
+        Note: The final answer is already displayed via the AgentLogsExecutionEvent
+        panel, so we only show the feedback prompt here.
+        """
+        from rich.panel import Panel
+        from rich.text import Text
+
+        formatter = event_listener.formatter
+        formatter.pause_live_updates()
 
+        try:
             # Training mode prompt (single iteration)
             if self.crew and getattr(self.crew, "_train", False):
-                prompt = (
-                    "\n\n=====\n"
-                    "## TRAINING MODE: Provide feedback to improve the agent's performance.\n"
+                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.\n"
-                    "=====\n"
+                    "Please provide detailed feedback about the result quality and reasoning process."
                 )
+                title = "🎓 Training Feedback Required"
             # Regular human-in-the-loop prompt (multiple iterations)
             else:
-                prompt = (
-                    "\n\n=====\n"
-                    "## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n"
-                    "Please follow these guidelines:\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.\n"
-                    "=====\n"
+                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)
 
-            self._printer.print(content=prompt, color="bold_yellow")
             response = input()
             if response.strip() != "":
-                self._printer.print(
-                    content="\nProcessing your feedback...", color="cyan"
-                )
+                formatter.console.print("\n[cyan]Processing your feedback...[/cyan]")
             return response
         finally:
-            event_listener.formatter.resume_live_updates()
+            formatter.resume_live_updates()

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

@@ -7,6 +7,7 @@
 from __future__ import annotations
 
 from collections.abc import Callable
+import logging
 from typing import TYPE_CHECKING, Any, Literal, cast
 
 from pydantic import BaseModel, GetCoreSchemaHandler
@@ -51,6 +52,8 @@
 from crewai.utilities.training_handler import CrewTrainingHandler
 
 
+logger = logging.getLogger(__name__)
+
 if TYPE_CHECKING:
     from crewai.agent import Agent
     from crewai.agents.tools_handler import ToolsHandler
@@ -541,7 +544,7 @@ def _show_logs(self, formatted_answer: AgentAction | AgentFinish) -> None:
         if self.agent is None:
             raise ValueError("Agent cannot be None")
 
-        crewai_event_bus.emit(
+        future = crewai_event_bus.emit(
             self.agent,
             AgentLogsExecutionEvent(
                 agent_role=self.agent.role,
@@ -551,6 +554,12 @@ def _show_logs(self, formatted_answer: AgentAction | AgentFinish) -> None:
             ),
         )
 
+        if future is not None:
+            try:
+                future.result(timeout=5.0)
+            except Exception as e:
+                logger.error(f"Failed to show logs for agent execution event: {e}")
+
     def _handle_crew_training_output(
         self, result: AgentFinish, human_feedback: str | None = None
     ) -> None: