Fixing missing function. Working on tests.

src/crewai/crew.py

@@ -55,7 +55,6 @@ class Crew(BaseModel):
         max_rpm: Maximum number of requests per minute for the crew execution to be respected.
         prompt_file: Path to the prompt json file to be used for the crew.
         id: A unique identifier for the crew instance.
-        full_output: Whether the crew should return the full output with all tasks outputs and token usage metrics or just the final output.
         task_callback: Callback to be executed after each task for every agents execution.
         step_callback: Callback to be executed after each step for every agents execution.
         share_crew: Whether you want to share the complete crew information and execution with crewAI to make the library better, and allow us to train models.
@@ -91,10 +90,6 @@ class Crew(BaseModel):
         default=None,
         description="Metrics for the LLM usage during all tasks execution.",
     )
-    full_output: Optional[bool] = Field(
-        default=False,
-        description="Whether the crew should return the full output with all tasks outputs and token usage metrics or just the final output.",
-    )
     manager_llm: Optional[Any] = Field(
         description="Language model that will run the agent.", default=None
     )
@@ -598,7 +593,7 @@ class Crew(BaseModel):
         return CrewOutput(
             output=output,
             tasks_output=[task.output for task in self.tasks if task],
-            token_output=token_usage,
+            token_usage=token_usage,
         )
 
     def _finish_execution(self, final_string_output: str) -> None:
@@ -606,5 +601,27 @@ class Crew(BaseModel):
             self._rpm_controller.stop_rpm_counter()
         self._telemetry.end_crew(self, final_string_output)
 
+    def calculate_usage_metrics(self) -> Dict[str, int]:
+        """Calculates and returns the usage metrics."""
+        total_usage_metrics = {
+            "total_tokens": 0,
+            "prompt_tokens": 0,
+            "completion_tokens": 0,
+            "successful_requests": 0,
+        }
+
+        for agent in self.agents:
+            if hasattr(agent, "_token_process"):
+                token_sum = agent._token_process.get_summary()
+                for key in total_usage_metrics:
+                    total_usage_metrics[key] += token_sum.get(key, 0)
+
+        if self.manager_agent and hasattr(self.manager_agent, "_token_process"):
+            token_sum = self.manager_agent._token_process.get_summary()
+            for key in total_usage_metrics:
+                total_usage_metrics[key] += token_sum.get(key, 0)
+
+        return total_usage_metrics
+
     def __repr__(self):
         return f"Crew(id={self.id}, process={self.process}, number_of_agents={len(self.agents)}, number_of_tasks={len(self.tasks)})"

src/crewai/crews/crew_output.py

@@ -11,13 +11,15 @@ class CrewOutput(BaseModel):
     tasks_output: list[TaskOutput] = Field(
         description="Output of each task", default=[]
     )
-    token_output: Dict[str, Any] = Field(
+    token_usage: Dict[str, Any] = Field(
         description="Processed token summary", default={}
     )
 
+    # TODO: Ask @joao what is the desired behavior here
     def result(self) -> Union[str, BaseModel, Dict[str, Any]]:
         """Return the result of the task based on the available output."""
-        return self.output.result()
+        results = [output.result() for output in self.output]
+        return results if len(results) > 1 else results[0]
 
     def raw_output(self) -> str:
         """Return the raw output of the task."""
@@ -29,5 +31,6 @@ class CrewOutput(BaseModel):
     def __getitem__(self, key: str) -> Any:
         self.output[key]
 
+    # TODO: Confirm with Joao that we want to print the raw output and not the object
     def __str__(self):
         return str(self.raw_output())

src/crewai/task.py

@@ -3,7 +3,7 @@ import re
 import threading
 import uuid
 from concurrent.futures import Future
-from copy import copy, deepcopy
+from copy import copy
 from typing import Any, Dict, List, Optional, Type, Union
 
 from langchain_openai import ChatOpenAI
@@ -209,8 +209,8 @@ class Task(BaseModel):
         if self.context:
             context_list = []
             for task in self.context:
-                if task.async_execution and task.thread:
-                    task.thread.join()
+                if task.async_execution and task._thread:
+                    task._thread.join()
                 if task and task.output:
                     context_list.append(task.output.raw_output)
             context = "\n".join(context_list)