capture result from recursive call

* Provide inputs on crew creation

* Better naming

* Add crew id and task index to tasks

* Fix type again

.gitignore

@@ -14,5 +14,4 @@ test.py
 rc-tests/*
 *.pkl
 temp/*
-.vscode/*
-crew_tasks_output.json
+.vscode/*

docs/core-concepts/Crews.md

@@ -155,23 +155,4 @@ for async_result in async_results:
     print(async_result)
 ```
 
-### Replaying from specific task:
-You can now replay from a specific task using our cli command replay.
-
-The replay_from_tasks feature in CrewAI allows you to replay from a specific task using the command-line interface (CLI). By running the command `crewai replay -t <task_id>`, you can specify the task name for the replay process.
-
-Kickoffs will now create a `crew_tasks_ouput.json` file with the output of the tasks which you use to retrieve the task id to replay.
-
-
-### Replaying from specific task Using the CLI
-To use the replay feature, follow these steps:
-
-1. Open your terminal or command prompt.
-2. Navigate to the directory where your CrewAI project is located.
-3. Run the following command:
-
-```shell
-crewai replay -t <task_id>
-```
-
 These methods provide flexibility in how you manage and execute tasks within your crew, allowing for both synchronous and asynchronous workflows tailored to your needs

docs/how-to/LLM-Connections.md

@@ -127,7 +127,7 @@ llm = HuggingFaceHub(
 ```
 
 ## OpenAI Compatible API Endpoints
-Switch between APIs and models seamlessly using environment variables, supporting platforms like FastChat, LM Studio, and Mistral AI.
+Switch between APIs and models seamlessly using environment variables, supporting platforms like FastChat, LM Studio, Groq, and Mistral AI.
 
 ### Configuration Examples
 #### FastChat
@@ -144,6 +144,13 @@ OPENAI_API_BASE="http://localhost:1234/v1"
 OPENAI_API_KEY="lm-studio"
 ```
 
+#### Groq API
+```sh
+OPENAI_API_KEY=your-groq-api-key
+OPENAI_MODEL_NAME='llama3-8b-8192'
+OPENAI_API_BASE=https://api.groq.com/openai/v1
+```
+
 #### Mistral API
 ```sh
 OPENAI_API_KEY=your-mistral-api-key
@@ -211,4 +218,4 @@ azure_agent = Agent(
 ```
 
 ## Conclusion
-Integrating CrewAI with different LLMs expands the framework's versatility, allowing for customized, efficient AI solutions across various domains and platforms.
+Integrating CrewAI with different LLMs expands the framework's versatility, allowing for customized, efficient AI solutions across various domains and platforms.

poetry.lock

@@ -2282,6 +2282,17 @@ files = [
     {file = "jmespath-1.0.1.tar.gz", hash = "sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe"},
 ]
 
+[[package]]
+name = "json-repair"
+version = "0.25.2"
+description = "A package to repair broken json strings"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "json_repair-0.25.2-py3-none-any.whl", hash = "sha256:51d67295c3184b6c41a3572689661c6128cef6cfc9fb04db63130709adfc5bf0"},
+    {file = "json_repair-0.25.2.tar.gz", hash = "sha256:161a56d7e6bbfd4cad3a614087e3e0dbd0e10d402dd20dc7db418432428cb32b"},
+]
+
 [[package]]
 name = "jsonpatch"
 version = "1.33"
@@ -2395,8 +2406,8 @@ langchain-core = ">=0.2.10,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = [
-    {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
     {version = ">=1,<2", markers = "python_version < \"3.12\""},
+    {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
 ]
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
@@ -2437,8 +2448,8 @@ langchain = ">=0.2.6,<0.3.0"
 langchain-core = ">=0.2.10,<0.3.0"
 langsmith = ">=0.1.0,<0.2.0"
 numpy = [
-    {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
     {version = ">=1,<2", markers = "python_version < \"3.12\""},
+    {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
 ]
 PyYAML = ">=5.3"
 requests = ">=2,<3"
@@ -2461,8 +2472,8 @@ jsonpatch = ">=1.33,<2.0"
 langsmith = ">=0.1.75,<0.2.0"
 packaging = ">=23.2,<25"
 pydantic = [
-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 PyYAML = ">=5.3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
@@ -2511,8 +2522,8 @@ files = [
 [package.dependencies]
 orjson = ">=3.9.14,<4.0.0"
 pydantic = [
-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 requests = ">=2,<3"
 
@@ -3989,8 +4000,8 @@ files = [
 annotated-types = ">=0.4.0"
 pydantic-core = "2.20.1"
 typing-extensions = [
-    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
     {version = ">=4.6.1", markers = "python_version < \"3.13\""},
+    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
 ]
 
 [package.extras]
@@ -6090,4 +6101,4 @@ tools = ["crewai-tools"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<=3.13"
-content-hash = "0dbf6f6e2e841fb3eec4ff87ea5d6b430f29702118fee91307983c6b2581e59e"
+content-hash = "2cf5a3904e7cbcfebb85e198b6035252d47213a9b0dd3dd51837516e03b38d3e"

pyproject.toml

@@ -28,6 +28,7 @@ appdirs = "^1.4.4"
 jsonref = "^1.1.0"
 agentops = { version = "^0.1.9", optional = true }
 embedchain = "^0.1.114"
+json-repair = "^0.25.2"
 
 [tool.poetry.extras]
 tools = ["crewai-tools"]

src/crewai/agent.py

@@ -1,13 +1,14 @@
 import os
+from inspect import signature
 from typing import Any, List, Optional, Tuple
 
 from langchain.agents.agent import RunnableAgent
+from langchain.agents.tools import BaseTool
 from langchain.agents.tools import tool as LangChainTool
-from langchain.tools.render import render_text_description
 from langchain_core.agents import AgentAction
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_openai import ChatOpenAI
-from pydantic import Field, InstanceOf, model_validator
+from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
 from crewai.agents import CacheHandler, CrewAgentExecutor, CrewAgentParser
 from crewai.agents.agent_builder.base_agent import BaseAgent
@@ -54,8 +55,11 @@ class Agent(BaseAgent):
             tools: Tools at agents disposal
             step_callback: Callback to be executed after each step of the agent execution.
             callbacks: A list of callback functions from the langchain library that are triggered during the agent's execution process
+            allow_code_execution: Enable code execution for the agent.
+            max_retry_limit: Maximum number of retries for an agent to execute a task when an error occurs.
     """
 
+    _times_executed: int = PrivateAttr(default=0)
     max_execution_time: Optional[int] = Field(
         default=None,
         description="Maximum execution time for an agent to execute a task",
@@ -96,6 +100,10 @@ class Agent(BaseAgent):
     allow_code_execution: Optional[bool] = Field(
         default=False, description="Enable code execution for the agent."
     )
+    max_retry_limit: int = Field(
+        default=2,
+        description="Maximum number of retries for an agent to execute a task when an error occurs.",
+    )
 
     def __init__(__pydantic_self__, **data):
         config = data.pop("config", {})
@@ -167,14 +175,15 @@ class Agent(BaseAgent):
             if memory.strip() != "":
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 
-        tools = tools or self.tools
-
-        parsed_tools = self._parse_tools(tools or [])  # type: ignore # Argument 1 to "_parse_tools" of "Agent" has incompatible type "list[Any] | None"; expected "list[Any]"
+        tools = tools or self.tools or []
+        parsed_tools = self._parse_tools(tools)
         self.create_agent_executor(tools=tools)
         self.agent_executor.tools = parsed_tools
         self.agent_executor.task = task
 
-        self.agent_executor.tools_description = render_text_description(parsed_tools)
+        self.agent_executor.tools_description = self._render_text_description_and_args(
+            parsed_tools
+        )
         self.agent_executor.tools_names = self.__tools_names(parsed_tools)
 
         if self.crew and self.crew._train:
@@ -182,13 +191,20 @@ class Agent(BaseAgent):
         else:
             task_prompt = self._use_trained_data(task_prompt=task_prompt)
 
-        result = self.agent_executor.invoke(
-            {
-                "input": task_prompt,
-                "tool_names": self.agent_executor.tools_names,
-                "tools": self.agent_executor.tools_description,
-            }
-        )["output"]
+        try:
+            result = self.agent_executor.invoke(
+                {
+                    "input": task_prompt,
+                    "tool_names": self.agent_executor.tools_names,
+                    "tools": self.agent_executor.tools_description,
+                }
+            )["output"]
+        except Exception as e:
+            self._times_executed += 1
+            if self._times_executed > self.max_retry_limit:
+                raise e
+            result = self.execute_task(task, context, tools)
+
         if self.max_rpm:
             self._rpm_controller.stop_rpm_counter()
 
@@ -220,7 +236,7 @@ class Agent(BaseAgent):
         Returns:
             An instance of the CrewAgentExecutor class.
         """
-        tools = tools or self.tools
+        tools = tools or self.tools or []
 
         agent_args = {
             "input": lambda x: x["input"],
@@ -315,6 +331,7 @@ class Agent(BaseAgent):
             tools_list = []
             for tool in tools:
                 tools_list.append(tool)
+
         return tools_list
 
     def _training_handler(self, task_prompt: str) -> str:
@@ -341,6 +358,52 @@ class Agent(BaseAgent):
                 )
         return task_prompt
 
+    def _render_text_description(self, tools: List[BaseTool]) -> str:
+        """Render the tool name and description in plain text.
+
+        Output will be in the format of:
+
+        .. code-block:: markdown
+
+            search: This tool is used for search
+            calculator: This tool is used for math
+        """
+        description = "\n".join(
+            [
+                f"Tool name: {tool.name}\nTool description:\n{tool.description}"
+                for tool in tools
+            ]
+        )
+
+        return description
+
+    def _render_text_description_and_args(self, tools: List[BaseTool]) -> str:
+        """Render the tool name, description, and args in plain text.
+
+        Output will be in the format of:
+
+        .. code-block:: markdown
+
+            search: This tool is used for search, args: {"query": {"type": "string"}}
+            calculator: This tool is used for math, \
+    args: {"expression": {"type": "string"}}
+        """
+        tool_strings = []
+        for tool in tools:
+            args_schema = str(tool.args)
+            if hasattr(tool, "func") and tool.func:
+                sig = signature(tool.func)
+                description = (
+                    f"Tool Name: {tool.name}{sig}\nTool Description: {tool.description}"
+                )
+            else:
+                description = (
+                    f"Tool Name: {tool.name}\nTool Description: {tool.description}"
+                )
+            tool_strings.append(f"{description}\nTool Arguments: {args_schema}")
+
+        return "\n".join(tool_strings)
+
     @staticmethod
     def __tools_names(tools) -> str:
         return ", ".join([t.name for t in tools])

src/crewai/agents/agent_builder/utilities/base_agent_tool.py

@@ -24,6 +24,7 @@ class BaseAgentTools(BaseModel, ABC):
             is_list = coworker.startswith("[") and coworker.endswith("]")
             if is_list:
                 coworker = coworker[1:-1].split(",")[0]
+
         return coworker
 
     def delegate_work(
@@ -40,11 +41,13 @@ class BaseAgentTools(BaseModel, ABC):
         coworker = self._get_coworker(coworker, **kwargs)
         return self._execute(coworker, question, context)
 
-    def _execute(self, agent: Union[str, None], task: str, context: Union[str, None]):
+    def _execute(
+        self, agent_name: Union[str, None], task: str, context: Union[str, None]
+    ):
         """Execute the command."""
         try:
-            if agent is None:
-                agent = ""
+            if agent_name is None:
+                agent_name = ""
 
             # It is important to remove the quotes from the agent name.
             # The reason we have to do this is because less-powerful LLM's
@@ -53,7 +56,7 @@ class BaseAgentTools(BaseModel, ABC):
             # {"task": "....", "coworker": "....
             # when it should look like this:
             # {"task": "....", "coworker": "...."}
-            agent_name = agent.casefold().replace('"', "").replace("\n", "")
+            agent_name = agent_name.casefold().replace('"', "").replace("\n", "")
 
             agent = [  # type: ignore # Incompatible types in assignment (expression has type "list[BaseAgent]", variable has type "str | None")
                 available_agent
@@ -75,9 +78,9 @@ class BaseAgentTools(BaseModel, ABC):
             )
 
         agent = agent[0]
-        task = Task(  # type: ignore # Incompatible types in assignment (expression has type "Task", variable has type "str")
+        task_with_assigned_agent = Task(  # type: ignore # Incompatible types in assignment (expression has type "Task", variable has type "str")
             description=task,
             agent=agent,
             expected_output="Your best answer to your coworker asking you this, accounting for the context shared.",
         )
-        return agent.execute_task(task, context)  # type: ignore # "str" has no attribute "execute_task"
+        return agent.execute_task(task_with_assigned_agent, context)

src/crewai/agents/agent_builder/utilities/base_output_converter.py

@@ -1,7 +1,7 @@
 from abc import ABC, abstractmethod
 from typing import Any, Optional
 
-from pydantic import BaseModel, Field, PrivateAttr
+from pydantic import BaseModel, Field
 
 
 class OutputConverter(BaseModel, ABC):
@@ -21,7 +21,6 @@ class OutputConverter(BaseModel, ABC):
         max_attempts (int): Maximum number of conversion attempts (default: 3).
     """
 
-    _is_gpt: bool = PrivateAttr(default=True)
     text: str = Field(description="Text to be converted.")
     llm: Any = Field(description="The language model to be used to convert the text.")
     model: Any = Field(description="The model to be used to convert the text.")
@@ -41,7 +40,8 @@ class OutputConverter(BaseModel, ABC):
         """Convert text to json."""
         pass
 
-    @abstractmethod  # type: ignore #  Name "_is_gpt" already defined on line 25
-    def _is_gpt(self, llm):  # type: ignore #  Name "_is_gpt" already defined on line 25
+    @property
+    @abstractmethod
+    def is_gpt(self) -> bool:
         """Return if llm provided is of gpt from openai."""
         pass

src/crewai/agents/executor.py

@@ -1,14 +1,6 @@
 import threading
 import time
-from typing import (
-    Any,
-    Dict,
-    Iterator,
-    List,
-    Optional,
-    Tuple,
-    Union,
-)
+from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
 
 from langchain.agents import AgentExecutor
 from langchain.agents.agent import ExceptionTool
@@ -19,9 +11,7 @@ from langchain_core.tools import BaseTool
 from langchain_core.utils.input import get_color_mapping
 from pydantic import InstanceOf
 
-from crewai.agents.agent_builder.base_agent_executor_mixin import (
-    CrewAgentExecutorMixin,
-)
+from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
 from crewai.utilities import I18N

src/crewai/agents/parser.py

@@ -1,6 +1,7 @@
 import re
 from typing import Any, Union
 
+from json_repair import repair_json
 from langchain.agents.output_parsers import ReActSingleInputOutputParser
 from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.exceptions import OutputParserException
@@ -48,11 +49,15 @@ class CrewAgentParser(ReActSingleInputOutputParser):
                 raise OutputParserException(
                     f"{FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE}: {text}"
                 )
-            action = action_match.group(1).strip()
-            action_input = action_match.group(2)
-            tool_input = action_input.strip(" ")
-            tool_input = tool_input.strip('"')
-            return AgentAction(action, tool_input, text)
+            action = action_match.group(1)
+            clean_action = self._clean_action(action)
+
+            action_input = action_match.group(2).strip()
+
+            tool_input = action_input.strip(" ").strip('"')
+            safe_tool_input = self._safe_repair_json(tool_input)
+
+            return AgentAction(clean_action, safe_tool_input, text)
 
         elif includes_answer:
             return AgentFinish(
@@ -87,3 +92,30 @@ class CrewAgentParser(ReActSingleInputOutputParser):
                 llm_output=text,
                 send_to_llm=True,
             )
+
+    def _clean_action(self, text: str) -> str:
+        """Clean action string by removing non-essential formatting characters."""
+        return re.sub(r"^\s*\*+\s*|\s*\*+\s*$", "", text).strip()
+
+    def _safe_repair_json(self, tool_input: str) -> str:
+        UNABLE_TO_REPAIR_JSON_RESULTS = ['""', "{}"]
+
+        # Skip repair if the input starts and ends with square brackets
+        # Explanation: The JSON parser has issues handling inputs that are enclosed in square brackets ('[]').
+        # These are typically valid JSON arrays or strings that do not require repair. Attempting to repair such inputs
+        # might lead to unintended alterations, such as wrapping the entire input in additional layers or modifying
+        # the structure in a way that changes its meaning. By skipping the repair for inputs that start and end with
+        # square brackets, we preserve the integrity of these valid JSON structures and avoid unnecessary modifications.
+        if tool_input.startswith("[") and tool_input.endswith("]"):
+            return tool_input
+
+        # Before repair, handle common LLM issues:
+        # 1. Replace """ with " to avoid JSON parser errors
+
+        tool_input = tool_input.replace('"""', '"')
+
+        result = repair_json(tool_input)
+        if result in UNABLE_TO_REPAIR_JSON_RESULTS:
+            return tool_input
+
+        return str(result)

src/crewai/cli/cli.py

@@ -1,11 +1,8 @@
 import click
 import pkg_resources
 
-
 from .create_crew import create_crew
 from .train_crew import train_crew
-from .replay_from_task import replay_task_command
-from .list_task_outputs import show_task_outputs
 
 
 @click.group()
@@ -51,32 +48,5 @@ def train(n_iterations: int):
     train_crew(n_iterations)
 
 
-@crewai.command()
-@click.option(
-    "-t",
-    "--task_id",
-    type=str,
-    help="Replay the crew from this task ID, including all subsequent tasks.",
-)
-def replay(task_id: str) -> None:
-    """
-    Replay the crew execution from a specific task.
-
-    Args:
-        task_id (str): The ID of the task to replay from.
-    """
-    try:
-        click.echo(f"Replaying the crew from task {task_id}")
-        replay_task_command(task_id)
-    except Exception as e:
-        click.echo(f"An error occurred while replaying: {e}", err=True)
-
-
-@crewai.command()
-def list_completed_tasks_ids():
-    """List all task outputs saved from crew_tasks_output.json."""
-    show_task_outputs()
-
-
 if __name__ == "__main__":
     crewai()

src/crewai/cli/list_task_outputs.py

@@ -1,34 +0,0 @@
-import subprocess
-import click
-from pathlib import Path
-import json
-
-
-def show_task_outputs() -> None:
-    """
-    Replay the crew execution from a specific task.
-
-    Args:
-      task_id (str): The ID of the task to replay from.
-    """
-
-    try:
-        file_path = Path("crew_tasks_output.json")
-        if not file_path.exists():
-            click.echo("crew_tasks_output.json not found.")
-            return
-
-        with open(file_path, "r") as f:
-            tasks = json.load(f)
-
-        for index, task in enumerate(tasks):
-            click.echo(f"Task {index + 1}: {task['task_id']}")
-            click.echo(f"Description: {task['output']['description']}")
-            click.echo("---")
-
-    except subprocess.CalledProcessError as e:
-        click.echo(f"An error occurred while replaying the task: {e}", err=True)
-        click.echo(e.output, err=True)
-
-    except Exception as e:
-        click.echo(f"An unexpected error occurred: {e}", err=True)

src/crewai/cli/replay_from_task.py

@@ -1,24 +0,0 @@
-import subprocess
-import click
-
-
-def replay_task_command(task_id: str) -> None:
-    """
-    Replay the crew execution from a specific task.
-
-    Args:
-      task_id (str): The ID of the task to replay from.
-    """
-    command = ["poetry", "run", "replay_from_task", task_id]
-
-    try:
-        result = subprocess.run(command, capture_output=False, text=True, check=True)
-        if result.stderr:
-            click.echo(result.stderr, err=True)
-
-    except subprocess.CalledProcessError as e:
-        click.echo(f"An error occurred while replaying the task: {e}", err=True)
-        click.echo(e.output, err=True)
-
-    except Exception as e:
-        click.echo(f"An unexpected error occurred: {e}", err=True)

src/crewai/cli/templates/main.py

@@ -21,13 +21,3 @@ def train():
 
     except Exception as e:
         raise Exception(f"An error occurred while training the crew: {e}")
-
-def replay_from_task():
-    """
-    Replay the crew execution from a specific task.
-    """
-    try:
-        {{crew_name}}Crew().crew().replay_from_task(task_id=sys.argv[1])
-
-    except Exception as e:
-        raise Exception(f"An error occurred while replaying the crew: {e}")

src/crewai/cli/templates/pyproject.toml

@@ -11,7 +11,6 @@ crewai = { extras = ["tools"], version = "^0.35.8" }
 [tool.poetry.scripts]
 {{folder_name}} = "{{folder_name}}.main:run"
 train = "{{folder_name}}.main:train"
-replay = "{{folder_name}}.main:replay_from_task"
 
 [build-system]
 requires = ["poetry-core"]

src/crewai/crew.py

@@ -6,15 +6,15 @@ from typing import Any, Dict, List, Optional, Tuple, Union
 
 from langchain_core.callbacks import BaseCallbackHandler
 from pydantic import (
-    UUID4,
-    BaseModel,
-    ConfigDict,
-    Field,
-    InstanceOf,
-    Json,
-    PrivateAttr,
-    field_validator,
-    model_validator,
+  UUID4,
+  BaseModel,
+  ConfigDict,
+  Field,
+  InstanceOf,
+  Json,
+  PrivateAttr,
+  field_validator,
+  model_validator,
 )
 from pydantic_core import PydanticCustomError
 
@@ -31,16 +31,8 @@ from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
 from crewai.tools.agent_tools import AgentTools
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
-from crewai.utilities.constants import (
-    CREW_TASKS_OUTPUT_FILE,
-    TRAINED_AGENTS_DATA_FILE,
-    TRAINING_DATA_FILE,
-)
+from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
-from crewai.utilities.task_output_handler import (
-    ExecutionLog,
-    TaskOutputJsonHandler,
-)
 from crewai.utilities.formatter import (
     aggregate_raw_outputs_from_task_outputs,
     aggregate_raw_outputs_from_tasks,
@@ -88,10 +80,6 @@ class Crew(BaseModel):
     _entity_memory: Optional[InstanceOf[EntityMemory]] = PrivateAttr()
     _train: Optional[bool] = PrivateAttr(default=False)
     _train_iteration: Optional[int] = PrivateAttr()
-    _inputs: Optional[Dict[str, Any]] = PrivateAttr(default=None)
-    _logging_color: str = PrivateAttr(
-        default="bold_purple",
-    )
 
     cache: bool = Field(default=True)
     model_config = ConfigDict(arbitrary_types_allowed=True)
@@ -147,14 +135,6 @@ class Crew(BaseModel):
         default=False,
         description="output_log_file",
     )
-    task_execution_output_json_files: Optional[List[str]] = Field(
-        default=None,
-        description="List of file paths for task execution JSON files.",
-    )
-    execution_logs: List[ExecutionLog] = Field(
-        default=[],
-        description="List of execution logs for tasks",
-    )
 
     @field_validator("id", mode="before")
     @classmethod
@@ -190,7 +170,6 @@ class Crew(BaseModel):
         self._rpm_controller = RPMController(max_rpm=self.max_rpm, logger=self._logger)
         self._telemetry = Telemetry()
         self._telemetry.set_tracer()
-        self._telemetry.crew_creation(self)
         return self
 
     @model_validator(mode="after")
@@ -397,12 +376,7 @@ class Crew(BaseModel):
     ) -> CrewOutput:
         """Starts the crew to work on its assigned tasks."""
         self._execution_span = self._telemetry.crew_execution_span(self, inputs)
-        TaskOutputJsonHandler(CREW_TASKS_OUTPUT_FILE).initialize_file()
-        TaskOutputJsonHandler(CREW_TASKS_OUTPUT_FILE).reset()
-        self._logging_color = "bold_purple"
-
         if inputs is not None:
-            self._inputs = inputs
             self._interpolate_inputs(inputs)
         self._set_tasks_callbacks()
 
@@ -429,7 +403,7 @@ class Crew(BaseModel):
         if self.process == Process.sequential:
             result = self._run_sequential_process()
         elif self.process == Process.hierarchical:
-            result = self._run_hierarchical_process()
+            result = self._run_hierarchical_process()  # type: ignore # Incompatible types in assignment (expression has type "str | dict[str, Any]", variable has type "str")
         else:
             raise NotImplementedError(
                 f"The process '{self.process}' is not implemented yet."
@@ -517,51 +491,126 @@ class Crew(BaseModel):
 
         return results
 
-    def _store_execution_log(
-        self,
-        task: Task,
-        output: TaskOutput,
-        task_index: int,
-        was_replayed: bool = False,
-    ):
-        if self._inputs:
-            inputs = self._inputs
-        else:
-            inputs = {}
-
-        log = ExecutionLog(
-            task_id=str(task.id),
-            expected_output=task.expected_output,
-            output={
-                "description": output.description,
-                "summary": output.summary,
-                "raw": output.raw,
-                "pydantic": output.pydantic,
-                "json_dict": output.json_dict,
-                "output_format": output.output_format,
-                "agent": output.agent,
-            },
-            task_index=task_index,
-            inputs=inputs,
-            was_replayed=was_replayed,
-        )
-        if task_index < len(self.execution_logs):
-            self.execution_logs[task_index] = log
-        else:
-            self.execution_logs.append(log)
-
-        TaskOutputJsonHandler(CREW_TASKS_OUTPUT_FILE).update(task_index, log)
-
     def _run_sequential_process(self) -> CrewOutput:
         """Executes tasks sequentially and returns the final output."""
-        return self._execute_tasks(self.tasks)
+        task_outputs: List[TaskOutput] = []
+        futures: List[Tuple[Task, Future[TaskOutput]]] = []
 
+        for task in self.tasks:
+            if task.agent and task.agent.allow_delegation:
+                agents_for_delegation = [
+                    agent for agent in self.agents if agent != task.agent
+                ]
+                if len(self.agents) > 1 and len(agents_for_delegation) > 0:
+                    delegation_tools = task.agent.get_delegation_tools(
+                        agents_for_delegation
+                    )
+
+                    # Add tools if they are not already in task.tools
+                    for new_tool in delegation_tools:
+                        # Find the index of the tool with the same name
+                        existing_tool_index = next(
+                            (
+                                index
+                                for index, tool in enumerate(task.tools or [])
+                                if tool.name == new_tool.name
+                            ),
+                            None,
+                        )
+                        if not task.tools:
+                            task.tools = []
+
+                        if existing_tool_index is not None:
+                            # Replace the existing tool
+                            task.tools[existing_tool_index] = new_tool 
+                        else:
+                            # Add the new tool
+                            task.tools.append(new_tool)
+
+            role = task.agent.role if task.agent is not None else "None"
+            self._logger.log("debug", f"== Working Agent: {role}", color="bold_purple")
+            self._logger.log(
+                "info", f"== Starting Task: {task.description}", color="bold_purple"
+            )
+
+            if self.output_log_file:
+                self._file_handler.log(
+                    agent=role, task=task.description, status="started"
+                )
+
+            if task.async_execution:
+                context = (
+                    aggregate_raw_outputs_from_tasks(task.context)
+                    if task.context
+                    else aggregate_raw_outputs_from_task_outputs(task_outputs)
+                )
+                future = task.execute_async(
+                    agent=task.agent, context=context, tools=task.tools
+                )
+                futures.append((task, future))
+            else:
+                # Before executing a synchronous task, wait for all async tasks to complete
+                if futures:
+                    # Clear task_outputs before processing async tasks
+                    task_outputs = []
+                    for future_task, future in futures:
+                        task_output = future.result()
+                        task_outputs.append(task_output)
+                        self._process_task_result(future_task, task_output)
+
+                    # Clear the futures list after processing all async results
+                    futures.clear()
+
+                context = (
+                    aggregate_raw_outputs_from_tasks(task.context)
+                    if task.context
+                    else aggregate_raw_outputs_from_task_outputs(task_outputs)
+                )
+                task_output = task.execute_sync(
+                    agent=task.agent, context=context, tools=task.tools
+                )
+                task_outputs = [task_output]
+                self._process_task_result(task, task_output)
+
+        if futures:
+            # Clear task_outputs before processing async tasks
+            task_outputs = []
+            for future_task, future in futures:
+                task_output = future.result()
+                task_outputs.append(task_output)
+                self._process_task_result(future_task, task_output)
+
+        # Important: There should only be one task output in the list
+        #            If there are more or 0, something went wrong.
+        if len(task_outputs) != 1:
+            raise ValueError(
+                "Something went wrong. Kickoff should return only one task output."
+            )
+
+        final_task_output = task_outputs[0]
+
+        final_string_output = final_task_output.raw
+        self._finish_execution(final_string_output)
+
+        token_usage = self.calculate_usage_metrics()
+
+        return CrewOutput(
+            raw=final_task_output.raw,
+            pydantic=final_task_output.pydantic,
+            json_dict=final_task_output.json_dict,
+            tasks_output=[task.output for task in self.tasks if task.output],
+            token_usage=token_usage,
+        )
+
+    def _process_task_result(self, task: Task, output: TaskOutput) -> None:
+        role = task.agent.role if task.agent is not None else "None"
+        self._logger.log("debug", f"== [{role}] Task output: {output}\n\n")
+        if self.output_log_file:
+            self._file_handler.log(agent=role, task=output, status="completed")
+
+    # TODO: @joao, Breaking change. Changed return type. Usage metrics is included in crewoutput
     def _run_hierarchical_process(self) -> CrewOutput:
         """Creates and assigns a manager agent to make sure the crew completes the tasks."""
-        self._create_manager_agent()
-        return self._execute_tasks(self.tasks, self.manager_agent)
-
-    def _create_manager_agent(self):
         i18n = I18N(prompt_file=self.prompt_file)
         if self.manager_agent is not None:
             self.manager_agent.allow_delegation = True
@@ -580,127 +629,74 @@ class Crew(BaseModel):
             )
             self.manager_agent = manager
 
-    def _execute_tasks(
-        self,
-        tasks: List[Task],
-        manager: Optional[BaseAgent] = None,
-        start_index: Optional[int] = 0,
-        was_replayed: bool = False,
-    ) -> CrewOutput:
-        """Executes tasks sequentially and returns the final output.
-
-        Args:
-            tasks (List[Task]): List of tasks to execute
-            manager (Optional[BaseAgent], optional): Manager agent to use for delegation. Defaults to None.
-
-        Returns:
-            CrewOutput: Final output of the crew
-        """
-
         task_outputs: List[TaskOutput] = []
-        futures: List[Tuple[Task, Future[TaskOutput], int]] = []
-        last_sync_output: Optional[TaskOutput] = None
+        futures: List[Tuple[Task, Future[TaskOutput]]] = []
 
-        for task_index, task in enumerate(tasks):
-            if start_index is not None and task_index < start_index:
-                if task.output:
-                    if task.async_execution:
-                        task_outputs.append(task.output)
-                    else:
-                        task_outputs = [task.output]
-                        last_sync_output = task.output
-                continue
+        # TODO: IF USER OVERRIDE THE CONTEXT, PASS THAT
+        for task in self.tasks:
+            self._logger.log("debug", f"Working Agent: {manager.role}")
+            self._logger.log("info", f"Starting Task: {task.description}")
 
-            self._prepare_task(task, manager)
-            if self.process == Process.hierarchical:
-                agent_to_use = manager
-            else:
-                agent_to_use = task.agent
-            if agent_to_use is None:
-                raise ValueError(
-                    f"No agent available for task: {task.description}. Ensure that either the task has an assigned agent or a manager agent is provided."
+            if self.output_log_file:
+                self._file_handler.log(
+                    agent=manager.role, task=task.description, status="started"
                 )
-            self._log_task_start(task, agent_to_use)
 
             if task.async_execution:
-                context = self._get_context(
-                    task, [last_sync_output] if last_sync_output else []
+                context = (
+                    aggregate_raw_outputs_from_tasks(task.context)
+                    if task.context
+                    else aggregate_raw_outputs_from_task_outputs(task_outputs)
                 )
                 future = task.execute_async(
-                    agent=agent_to_use,
-                    context=context,
-                    tools=agent_to_use.tools,
+                    agent=manager, context=context, tools=manager.tools
                 )
-                futures.append((task, future, task_index))
+                futures.append((task, future))
             else:
+                # Before executing a synchronous task, wait for all async tasks to complete
                 if futures:
-                    task_outputs.extend(
-                        self._process_async_tasks(futures, was_replayed)
-                    )
+                    # Clear task_outputs before processing async tasks
+                    task_outputs = []
+                    for future_task, future in futures:
+                        task_output = future.result()
+                        task_outputs.append(task_output)
+                        self._process_task_result(future_task, task_output)
+
+                    # Clear the futures list after processing all async results
                     futures.clear()
 
-                context = self._get_context(task, task_outputs)
+                context = (
+                    aggregate_raw_outputs_from_tasks(task.context)
+                    if task.context
+                    else aggregate_raw_outputs_from_task_outputs(task_outputs)
+                )
                 task_output = task.execute_sync(
-                    agent=agent_to_use,
-                    context=context,
-                    tools=agent_to_use.tools,
+                    agent=manager, context=context, tools=manager.tools
                 )
                 task_outputs = [task_output]
                 self._process_task_result(task, task_output)
-                self._store_execution_log(task, task_output, task_index, was_replayed)
 
+        # Process any remaining async results
         if futures:
-            task_outputs = self._process_async_tasks(futures, was_replayed)
+            # Clear task_outputs before processing async tasks
+            task_outputs = []
+            for future_task, future in futures:
+                task_output = future.result()
+                task_outputs.append(task_output)
+                self._process_task_result(future_task, task_output)
 
-        return self._create_crew_output(task_outputs)
-
-    def _prepare_task(self, task: Task, manager: Optional[BaseAgent]):
-        if self.process == Process.hierarchical:
-            self._update_manager_tools(task, manager)
-        elif task.agent and task.agent.allow_delegation:
-            self._add_delegation_tools(task)
-
-    def _add_delegation_tools(self, task: Task):
-        agents_for_delegation = [agent for agent in self.agents if agent != task.agent]
-        if len(self.agents) > 1 and agents_for_delegation:
-            task.tools += task.agent.get_delegation_tools(agents_for_delegation)  # type: ignore
-
-    def _log_task_start(self, task: Task, agent: Optional[BaseAgent]):
-        color = self._logging_color
-        role = agent.role if agent else "None"
-        self._logger.log("debug", f"== Working Agent: {role}", color=color)
-        self._logger.log("info", f"== Starting Task: {task.description}", color=color)
-        if self.output_log_file:
-            self._file_handler.log(agent=role, task=task.description, status="started")
-
-    def _update_manager_tools(self, task: Task, manager: Optional[BaseAgent]):
-        if task.agent and manager:
-            manager.tools = task.agent.get_delegation_tools([task.agent])
-        if manager:
-            manager.tools = manager.get_delegation_tools(self.agents)
-
-    def _get_context(self, task: Task, task_outputs: List[TaskOutput]):
-        context = (
-            aggregate_raw_outputs_from_tasks(task.context)
-            if task.context
-            else aggregate_raw_outputs_from_task_outputs(task_outputs)
-        )
-        return context
-
-    def _process_task_result(self, task: Task, output: TaskOutput) -> None:
-        role = task.agent.role if task.agent is not None else "None"
-        self._logger.log("debug", f"== [{role}] Task output: {output}\n\n")
-        if self.output_log_file:
-            self._file_handler.log(agent=role, task=output, status="completed")
-
-    def _create_crew_output(self, task_outputs: List[TaskOutput]) -> CrewOutput:
+        # Important: There should only be one task output in the list
+        #            If there are more or 0, something went wrong.
         if len(task_outputs) != 1:
             raise ValueError(
                 "Something went wrong. Kickoff should return only one task output."
             )
+
         final_task_output = task_outputs[0]
+
         final_string_output = final_task_output.raw
         self._finish_execution(final_string_output)
+
         token_usage = self.calculate_usage_metrics()
 
         return CrewOutput(
@@ -711,69 +707,6 @@ class Crew(BaseModel):
             token_usage=token_usage,
         )
 
-    def _process_async_tasks(
-        self,
-        futures: List[Tuple[Task, Future[TaskOutput], int]],
-        was_replayed: bool = False,
-    ) -> List[TaskOutput]:
-        task_outputs = []
-        for future_task, future, task_index in futures:
-            task_output = future.result()
-            task_outputs.append(task_output)
-            self._process_task_result(future_task, task_output)
-            self._store_execution_log(
-                future_task, task_output, task_index, was_replayed
-            )
-        return task_outputs
-
-    def _find_task_index(
-        self, task_id: str, stored_outputs: List[Any]
-    ) -> Optional[int]:
-        return next(
-            (
-                index
-                for (index, d) in enumerate(stored_outputs)
-                if d["task_id"] == str(task_id)
-            ),
-            None,
-        )
-
-    def replay_from_task(
-        self, task_id: str, inputs: Optional[Dict[str, Any]] = None
-    ) -> CrewOutput:
-        stored_outputs = TaskOutputJsonHandler(CREW_TASKS_OUTPUT_FILE).load()
-        start_index = self._find_task_index(task_id, stored_outputs)
-
-        if start_index is None:
-            raise ValueError(f"Task with id {task_id} not found in the crew's tasks.")
-
-        replay_inputs = (
-            inputs if inputs is not None else stored_outputs[start_index]["inputs"]
-        )
-        self._inputs = replay_inputs
-
-        if replay_inputs:
-            self._interpolate_inputs(replay_inputs)
-
-        if self.process == Process.hierarchical:
-            self._create_manager_agent()
-
-        for i in range(start_index):
-            stored_output = stored_outputs[i]["output"]
-            task_output = TaskOutput(
-                description=stored_output["description"],
-                agent=stored_output["agent"],
-                raw=stored_output["raw"],
-                pydantic=stored_output["pydantic"],
-                json_dict=stored_output["json_dict"],
-                output_format=stored_output["output_format"],
-            )
-            self.tasks[i].output = task_output
-
-        self._logging_color = "bold_blue"
-        result = self._execute_tasks(self.tasks, self.manager_agent, start_index, True)
-        return result
-
     def copy(self):
         """Create a deep copy of the Crew."""
 

src/crewai/crews/crew_output.py

@@ -24,6 +24,8 @@ class CrewOutput(BaseModel):
         description="Processed token summary", default={}
     )
 
+    # TODO: Joao - Adding this safety check breakes when people want to see
+    #                   The full output of a CrewOutput.
     # @property
     # def pydantic(self) -> Optional[BaseModel]:
     #     # Check if the final task output included a pydantic model

src/crewai/task.py

@@ -204,7 +204,6 @@ class Task(BaseModel):
         tools: Optional[List[Any]],
     ) -> TaskOutput:
         """Run the core execution logic of the task."""
-        self.agent = agent
         agent = agent or self.agent
         if not agent:
             raise Exception(
@@ -245,9 +244,7 @@ class Task(BaseModel):
             content = (
                 json_output
                 if json_output
-                else pydantic_output.model_dump_json()
-                if pydantic_output
-                else result
+                else pydantic_output.model_dump_json() if pydantic_output else result
             )
             self._save_file(content)
 
@@ -381,7 +378,7 @@ class Task(BaseModel):
     def _convert_with_instructions(
         self, result: str, model: Type[BaseModel]
     ) -> Union[dict, BaseModel, str]:
-        llm = self.agent.function_calling_llm or self.agent.llm  # type: ignore # Item "None" of "BaseAgent | None" has no attribute "function_calling_llm"
+        llm = self.agent.function_calling_llm or self.agent.llm
         instructions = self._get_conversion_instructions(model, llm)
 
         converter = self._create_converter(

src/crewai/tasks/task_output.py

@@ -11,7 +11,9 @@ class TaskOutput(BaseModel):
 
     description: str = Field(description="Description of the task")
     summary: Optional[str] = Field(description="Summary of the task", default=None)
-    raw: str = Field(description="Raw output of the task", default="")
+    raw: str = Field(
+        description="Raw output of the task", default=""
+    )  # TODO: @joao: breaking change, by renaming raw_output to raw, but now consistent with CrewOutput
     pydantic: Optional[BaseModel] = Field(
         description="Pydantic output of task", default=None
     )
@@ -30,6 +32,8 @@ class TaskOutput(BaseModel):
         self.summary = f"{excerpt}..."
         return self
 
+    # TODO: Joao - Adding this safety check breakes when people want to see
+    #                   The full output of a TaskOutput or CrewOutput.
     # @property
     # def pydantic(self) -> Optional[BaseModel]:
     #     # Check if the final task output included a pydantic model

src/crewai/telemetry/telemetry.py

@@ -80,7 +80,7 @@ class Telemetry:
                 self.ready = False
                 self.trace_set = False
 
-    def crew_creation(self, crew):
+    def crew_creation(self, crew: Crew, inputs: dict[str, Any] | None):
         """Records the creation of a crew."""
         if self.ready:
             try:
@@ -93,6 +93,12 @@ class Telemetry:
                 )
                 self._add_attribute(span, "python_version", platform.python_version())
                 self._add_attribute(span, "crew_id", str(crew.id))
+
+                if crew.share_crew:
+                    self._add_attribute(
+                        span, "crew_inputs", json.dumps(inputs) if inputs else None
+                    )
+
                 self._add_attribute(span, "crew_process", crew.process)
                 self._add_attribute(span, "crew_memory", crew.memory)
                 self._add_attribute(span, "crew_number_of_tasks", len(crew.tasks))
@@ -114,7 +120,7 @@ class Telemetry:
                                 "llm": json.dumps(self._safe_llm_attributes(agent.llm)),
                                 "delegation_enabled?": agent.allow_delegation,
                                 "tools_names": [
-                                    tool.name.casefold() for tool in agent.tools
+                                    tool.name.casefold() for tool in agent.tools or []
                                 ],
                             }
                             for agent in crew.agents
@@ -139,7 +145,7 @@ class Telemetry:
                                     else None
                                 ),
                                 "tools_names": [
-                                    tool.name.casefold() for tool in task.tools
+                                    tool.name.casefold() for tool in task.tools or []
                                 ],
                             }
                             for task in crew.tasks
@@ -161,10 +167,11 @@ class Telemetry:
         if self.ready:
             try:
                 tracer = trace.get_tracer("crewai.telemetry")
-                span = tracer.start_span("Task Execution")
 
                 created_span = tracer.start_span("Task Created")
 
+                self._add_attribute(created_span, "crew_id", str(crew.id))
+                self._add_attribute(created_span, "task_index", crew.tasks.index(task))
                 self._add_attribute(created_span, "task_id", str(task.id))
 
                 if crew.share_crew:
@@ -178,6 +185,10 @@ class Telemetry:
                 created_span.set_status(Status(StatusCode.OK))
                 created_span.end()
 
+                span = tracer.start_span("Task Execution")
+
+                self._add_attribute(span, "crew_id", str(crew.id))
+                self._add_attribute(span, "task_index", crew.tasks.index(task))
                 self._add_attribute(span, "task_id", str(task.id))
 
                 if crew.share_crew:
@@ -275,6 +286,8 @@ class Telemetry:
         """
         if (self.ready) and (crew.share_crew):
             try:
+                self.crew_creation(crew, inputs)
+
                 tracer = trace.get_tracer("crewai.telemetry")
                 span = tracer.start_span("Crew Execution")
                 self._add_attribute(
@@ -283,7 +296,9 @@ class Telemetry:
                     pkg_resources.get_distribution("crewai").version,
                 )
                 self._add_attribute(span, "crew_id", str(crew.id))
-                self._add_attribute(span, "inputs", json.dumps(inputs))
+                self._add_attribute(
+                    span, "crew_inputs", json.dumps(inputs) if inputs else None
+                )
                 self._add_attribute(
                     span,
                     "crew_agents",

src/crewai/tools/agent_tools.py

@@ -7,7 +7,7 @@ class AgentTools(BaseAgentTools):
     """Default tools around agent delegation"""
 
     def tools(self):
-        coworkers = f"[{', '.join([f'{agent.role}' for agent in self.agents])}]"
+        coworkers = ", ".join([f"{agent.role}" for agent in self.agents])
         tools = [
             StructuredTool.from_function(
                 func=self.delegate_work,

src/crewai/utilities/constants.py

@@ -1,3 +1,2 @@
 TRAINING_DATA_FILE = "training_data.pkl"
 TRAINED_AGENTS_DATA_FILE = "trained_agents_data.pkl"
-CREW_TASKS_OUTPUT_FILE = "crew_tasks_output.json"

src/crewai/utilities/converter.py

@@ -2,10 +2,8 @@ import json
 
 from langchain.schema import HumanMessage, SystemMessage
 from langchain_openai import ChatOpenAI
-from pydantic import model_validator
-from crewai.agents.agent_builder.utilities.base_output_converter_base import (
-    OutputConverter,
-)
+
+from crewai.agents.agent_builder.utilities.base_output_converter import OutputConverter
 
 
 class ConverterError(Exception):
@@ -19,15 +17,10 @@ class ConverterError(Exception):
 class Converter(OutputConverter):
     """Class that converts text into either pydantic or json."""
 
-    @model_validator(mode="after")
-    def check_llm_provider(self):
-        if not self._is_gpt(self.llm):
-            self._is_gpt = False
-
     def to_pydantic(self, current_attempt=1):
         """Convert text to pydantic."""
         try:
-            if self._is_gpt:
+            if self.is_gpt:
                 return self._create_instructor().to_pydantic()
             else:
                 return self._create_chain().invoke({})
@@ -41,7 +34,7 @@ class Converter(OutputConverter):
     def to_json(self, current_attempt=1):
         """Convert text to json."""
         try:
-            if self._is_gpt:
+            if self.is_gpt:
                 return self._create_instructor().to_json()
             else:
                 return json.dumps(self._create_chain().invoke({}).model_dump())
@@ -75,5 +68,7 @@ class Converter(OutputConverter):
         )
         return new_prompt | self.llm | parser
 
-    def _is_gpt(self, llm) -> bool:  # type: ignore # BUG? Name "_is_gpt" defined on line 20 hides name from outer scope
-        return isinstance(llm, ChatOpenAI) and llm.openai_api_base is None
+    @property
+    def is_gpt(self) -> bool:
+        """Return if llm provided is of gpt from openai."""
+        return isinstance(self.llm, ChatOpenAI) and self.llm.openai_api_base is None

src/crewai/utilities/crew_json_encoder.py

@@ -1,31 +0,0 @@
-from datetime import datetime
-import json
-from uuid import UUID
-from pydantic import BaseModel
-
-
-class CrewJSONEncoder(json.JSONEncoder):
-    def default(self, obj):
-        if isinstance(obj, BaseModel):
-            return self._handle_pydantic_model(obj)
-        elif isinstance(obj, UUID):
-            return str(obj)
-
-        elif isinstance(obj, datetime):
-            return obj.isoformat()
-        return super().default(obj)
-
-    def _handle_pydantic_model(self, obj):
-        try:
-            data = obj.model_dump()
-            # Remove circular references
-            for key, value in data.items():
-                if isinstance(value, BaseModel):
-                    data[key] = str(
-                        value
-                    )  # Convert nested models to string representation
-            return data
-        except RecursionError:
-            return str(
-                obj
-            )  # Fall back to string representation if circular reference is detected

src/crewai/utilities/file_handler.py

@@ -1,7 +1,5 @@
 import os
 import pickle
-
-
 from datetime import datetime
 
 

src/crewai/utilities/printer.py

@@ -8,8 +8,6 @@ class Printer:
             self._print_bold_green(content)
         elif color == "bold_purple":
             self._print_bold_purple(content)
-        elif color == "bold_blue":
-            self._print_bold_blue(content)
         else:
             print(content)
 
@@ -24,6 +22,3 @@ class Printer:
 
     def _print_red(self, content):
         print("\033[91m {}\033[00m".format(content))
-
-    def _print_bold_blue(self, content):
-        print("\033[1m\033[94m {}\033[00m".format(content))

src/crewai/utilities/task_output_handler.py

@@ -1,69 +0,0 @@
-import json
-import os
-
-from pydantic import BaseModel, Field
-from datetime import datetime
-from typing import Dict, Any, Optional, List
-from crewai.utilities.crew_json_encoder import CrewJSONEncoder
-
-
-class ExecutionLog(BaseModel):
-    task_id: str
-    expected_output: Optional[str] = None
-    output: Dict[str, Any]
-    timestamp: datetime = Field(default_factory=datetime.now)
-    task_index: int
-    inputs: Dict[str, Any] = Field(default_factory=dict)
-    was_replayed: bool = False
-
-    def __getitem__(self, key: str) -> Any:
-        return getattr(self, key)
-
-
-class TaskOutputJsonHandler:
-    def __init__(self, file_name: str) -> None:
-        self.file_path = os.path.join(os.getcwd(), file_name)
-
-    def initialize_file(self) -> None:
-        if not os.path.exists(self.file_path) or os.path.getsize(self.file_path) == 0:
-            with open(self.file_path, "w") as file:
-                json.dump([], file)
-
-    def update(self, task_index: int, log: ExecutionLog):
-        logs = self.load()
-        if task_index < len(logs):
-            logs[task_index] = log
-        else:
-            logs.append(log)
-        self.save(logs)
-
-    def save(self, logs: List[ExecutionLog]):
-        with open(self.file_path, "w") as file:
-            json.dump(logs, file, indent=2, cls=CrewJSONEncoder)
-
-    def reset(self):
-        """Reset the JSON file by creating an empty file."""
-        with open(self.file_path, "w") as f:
-            json.dump([], f)
-
-    def load(self) -> List[ExecutionLog]:
-        try:
-            if (
-                not os.path.exists(self.file_path)
-                or os.path.getsize(self.file_path) == 0
-            ):
-                return []
-
-            with open(self.file_path, "r") as file:
-                return json.load(file)
-        except FileNotFoundError:
-            print(f"File {self.file_path} not found. Returning empty list.")
-            return []
-        except json.JSONDecodeError:
-            print(
-                f"Error decoding JSON from file {self.file_path}. Returning empty list."
-            )
-            return []
-        except Exception as e:
-            print(f"An unexpected error occurred: {e}")
-            return []

tests/agent_test.py

@@ -963,3 +963,54 @@ def test_agent_use_trained_data(crew_training_handler):
     crew_training_handler.assert_has_calls(
         [mock.call(), mock.call("trained_agents_data.pkl"), mock.call().load()]
     )
+
+
+def test_agent_max_retry_limit():
+    agent = Agent(
+        role="test role",
+        goal="test goal",
+        backstory="test backstory",
+        max_retry_limit=1,
+    )
+
+    task = Task(
+        agent=agent,
+        description="Say the word: Hi",
+        expected_output="The word: Hi",
+        human_input=True,
+    )
+
+    error_message = "Error happening while sending prompt to model."
+    with patch.object(
+        CrewAgentExecutor, "invoke", wraps=agent.agent_executor.invoke
+    ) as invoke_mock:
+        invoke_mock.side_effect = Exception(error_message)
+
+        assert agent._times_executed == 0
+        assert agent.max_retry_limit == 1
+
+        with pytest.raises(Exception) as e:
+            agent.execute_task(
+                task=task,
+            )
+        assert e.value.args[0] == error_message
+        assert agent._times_executed == 2
+
+        invoke_mock.assert_has_calls(
+            [
+                mock.call(
+                    {
+                        "input": "Say the word: Hi\n\nThis is the expect criteria for your final answer: The word: Hi \n you MUST return the actual complete content as the final answer, not a summary.",
+                        "tool_names": "",
+                        "tools": "",
+                    }
+                ),
+                mock.call(
+                    {
+                        "input": "Say the word: Hi\n\nThis is the expect criteria for your final answer: The word: Hi \n you MUST return the actual complete content as the final answer, not a summary.",
+                        "tool_names": "",
+                        "tools": "",
+                    }
+                ),
+            ]
+        )

tests/agents/test_crew_agent_parser.py

@@ -0,0 +1,378 @@
+import pytest
+from crewai.agents.parser import CrewAgentParser
+from langchain_core.agents import AgentAction, AgentFinish
+from langchain_core.exceptions import OutputParserException
+
+
+@pytest.fixture
+def parser():
+    p = CrewAgentParser()
+    p.agent = MockAgent()
+    return p
+
+
+def test_valid_action_parsing_special_characters(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: what's the temperature in SF?"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what's the temperature in SF?"
+
+
+def test_valid_action_parsing_with_json_tool_input(parser):
+    text = """
+    Thought: Let's find the information
+    Action: query
+    Action Input: ** {"task": "What are some common challenges or barriers that you have observed or experienced when implementing AI-powered solutions in healthcare settings?", "context": "As we've discussed recent advancements in AI applications in healthcare, it's crucial to acknowledge the potential hurdles. Some possible obstacles include...", "coworker": "Senior Researcher"}
+    """
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    expected_tool_input = '{"task": "What are some common challenges or barriers that you have observed or experienced when implementing AI-powered solutions in healthcare settings?", "context": "As we\'ve discussed recent advancements in AI applications in healthcare, it\'s crucial to acknowledge the potential hurdles. Some possible obstacles include...", "coworker": "Senior Researcher"}'
+    assert result.tool == "query"
+    assert result.tool_input == expected_tool_input
+
+
+def test_valid_action_parsing_with_quotes(parser):
+    text = 'Thought: Let\'s find the temperature\nAction: search\nAction Input: "temperature in SF"'
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "temperature in SF"
+
+
+def test_valid_action_parsing_with_curly_braces(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: {temperature in SF}"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "{temperature in SF}"
+
+
+def test_valid_action_parsing_with_angle_brackets(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: <temperature in SF>"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "<temperature in SF>"
+
+
+def test_valid_action_parsing_with_parentheses(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: (temperature in SF)"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "(temperature in SF)"
+
+
+def test_valid_action_parsing_with_mixed_brackets(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: [temperature in {SF}]"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "[temperature in {SF}]"
+
+
+def test_valid_action_parsing_with_nested_quotes(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: \"what's the temperature in 'SF'?\""
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what's the temperature in 'SF'?"
+
+
+def test_valid_action_parsing_with_incomplete_json(parser):
+    text = 'Thought: Let\'s find the temperature\nAction: search\nAction Input: {"query": "temperature in SF"'
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == '{"query": "temperature in SF"}'
+
+
+def test_valid_action_parsing_with_special_characters(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: what is the temperature in SF? @$%^&*"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF? @$%^&*"
+
+
+def test_valid_action_parsing_with_combination(parser):
+    text = 'Thought: Let\'s find the temperature\nAction: search\nAction Input: "[what is the temperature in SF?]"'
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "[what is the temperature in SF?]"
+
+
+def test_valid_action_parsing_with_mixed_quotes(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: \"what's the temperature in SF?\""
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what's the temperature in SF?"
+
+
+def test_valid_action_parsing_with_newlines(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: what is\nthe temperature in SF?"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is\nthe temperature in SF?"
+
+
+def test_valid_action_parsing_with_escaped_characters(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: what is the temperature in SF? \\n"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF? \\n"
+
+
+def test_valid_action_parsing_with_json_string(parser):
+    text = 'Thought: Let\'s find the temperature\nAction: search\nAction Input: {"query": "temperature in SF"}'
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == '{"query": "temperature in SF"}'
+
+
+def test_valid_action_parsing_with_unbalanced_quotes(parser):
+    text = "Thought: Let's find the temperature\nAction: search\nAction Input: \"what is the temperature in SF?"
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF?"
+
+
+def test_clean_action_no_formatting(parser):
+    action = "Ask question to senior researcher"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_leading_asterisks(parser):
+    action = "** Ask question to senior researcher"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_trailing_asterisks(parser):
+    action = "Ask question to senior researcher **"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_leading_and_trailing_asterisks(parser):
+    action = "** Ask question to senior researcher **"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_multiple_leading_asterisks(parser):
+    action = "**** Ask question to senior researcher"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_multiple_trailing_asterisks(parser):
+    action = "Ask question to senior researcher ****"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_spaces_and_asterisks(parser):
+    action = "  **  Ask question to senior researcher  **  "
+    cleaned_action = parser._clean_action(action)
+    print(f"Original action: '{action}'")
+    print(f"Cleaned action: '{cleaned_action}'")
+    assert cleaned_action == "Ask question to senior researcher"
+
+
+def test_clean_action_with_only_asterisks(parser):
+    action = "****"
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == ""
+
+
+def test_clean_action_with_empty_string(parser):
+    action = ""
+    cleaned_action = parser._clean_action(action)
+    assert cleaned_action == ""
+
+
+def test_valid_final_answer_parsing(parser):
+    text = (
+        "Thought: I found the information\nFinal Answer: The temperature is 100 degrees"
+    )
+    result = parser.parse(text)
+    assert isinstance(result, AgentFinish)
+    assert result.return_values["output"] == "The temperature is 100 degrees"
+
+
+def test_missing_action_error(parser):
+    text = "Thought: Let's find the temperature\nAction Input: what is the temperature in SF?"
+    with pytest.raises(OutputParserException) as exc_info:
+        parser.parse(text)
+    assert "Could not parse LLM output" in str(exc_info.value)
+
+
+def test_missing_action_input_error(parser):
+    text = "Thought: Let's find the temperature\nAction: search"
+    with pytest.raises(OutputParserException) as exc_info:
+        parser.parse(text)
+    assert "Could not parse LLM output" in str(exc_info.value)
+
+
+def test_action_and_final_answer_error(parser):
+    text = "Thought: I found the information\nAction: search\nAction Input: what is the temperature in SF?\nFinal Answer: The temperature is 100 degrees"
+    with pytest.raises(OutputParserException) as exc_info:
+        parser.parse(text)
+    assert "both perform Action and give a Final Answer" in str(exc_info.value)
+
+
+def test_safe_repair_json(parser):
+    invalid_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": Senior Researcher'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_unrepairable(parser):
+    invalid_json = "{invalid_json"
+    result = parser._safe_repair_json(invalid_json)
+    print("result:", invalid_json)
+    assert result == invalid_json  # Should return the original if unrepairable
+
+
+def test_safe_repair_json_missing_quotes(parser):
+    invalid_json = (
+        '{task: "Research XAI", context: "Explainable AI", coworker: Senior Researcher}'
+    )
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_unclosed_brackets(parser):
+    invalid_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_extra_commas(parser):
+    invalid_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher",}'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_trailing_commas(parser):
+    invalid_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher",}'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_single_quotes(parser):
+    invalid_json = "{'task': 'Research XAI', 'context': 'Explainable AI', 'coworker': 'Senior Researcher'}"
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_mixed_quotes(parser):
+    invalid_json = "{'task': \"Research XAI\", 'context': \"Explainable AI\", 'coworker': 'Senior Researcher'}"
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_unescaped_characters(parser):
+    invalid_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher\n"}'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    print("result:", result)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_missing_colon(parser):
+    invalid_json = '{"task" "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_missing_comma(parser):
+    invalid_json = '{"task": "Research XAI" "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_unexpected_trailing_characters(parser):
+    invalid_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"} random text'
+    expected_repaired_json = '{"task": "Research XAI", "context": "Explainable AI", "coworker": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_safe_repair_json_special_characters_key(parser):
+    invalid_json = '{"task!@#": "Research XAI", "context$%^": "Explainable AI", "coworker&*()": "Senior Researcher"}'
+    expected_repaired_json = '{"task!@#": "Research XAI", "context$%^": "Explainable AI", "coworker&*()": "Senior Researcher"}'
+    result = parser._safe_repair_json(invalid_json)
+    assert result == expected_repaired_json
+
+
+def test_parsing_with_whitespace(parser):
+    text = " Thought: Let's find the temperature \n Action: search \n Action Input: what is the temperature in SF? "
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF?"
+
+
+def test_parsing_with_special_characters(parser):
+    text = 'Thought: Let\'s find the temperature\nAction: search\nAction Input: "what is the temperature in SF?"'
+    result = parser.parse(text)
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF?"
+
+
+def test_integration_valid_and_invalid(parser):
+    text = """
+    Thought: Let's find the temperature
+    Action: search
+    Action Input: what is the temperature in SF?
+
+    Thought: I found the information
+    Final Answer: The temperature is 100 degrees
+
+    Thought: Missing action
+    Action Input: invalid
+
+    Thought: Missing action input
+    Action: invalid
+    """
+    parts = text.strip().split("\n\n")
+    results = []
+    for part in parts:
+        try:
+            result = parser.parse(part.strip())
+            results.append(result)
+        except OutputParserException as e:
+            results.append(e)
+
+    assert isinstance(results[0], AgentAction)
+    assert isinstance(results[1], AgentFinish)
+    assert isinstance(results[2], OutputParserException)
+    assert isinstance(results[3], OutputParserException)
+
+
+class MockAgent:
+    def increment_formatting_errors(self):
+        pass
+
+
+# TODO: ADD TEST TO MAKE SURE ** REMOVAL DOESN'T MESS UP ANYTHING

tests/cassettes/test_replay_feature.yaml

@@ -1,697 +0,0 @@
-interactions:
-- request:
-    body: '{"messages": [{"content": "You are Researcher. You''re an expert researcher,
-      specialized in technology, software engineering, AI and startups. You work as
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tests/crew_test.py

@@ -1,6 +1,5 @@
 """Test Agent creation and execution basic functionality."""
 
-import os
 import json
 from concurrent.futures import Future
 from unittest import mock
@@ -16,10 +15,8 @@ from crewai.crews.crew_output import CrewOutput
 from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.process import Process
 from crewai.task import Task
-from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.utilities import Logger, RPMController
-from crewai.utilities.constants import CREW_TASKS_OUTPUT_FILE
 
 ceo = Agent(
     role="CEO",
@@ -139,6 +136,7 @@ def test_async_task_cannot_include_sequential_async_tasks_in_context():
 
 
 def test_context_no_future_tasks():
+
     task2 = Task(
         description="Task 2",
         expected_output="output",
@@ -586,6 +584,7 @@ def test_sequential_async_task_execution_completion():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_single_task_with_async_execution():
+
     researcher_agent = Agent(
         role="Researcher",
         goal="Make the best research and analysis on content about AI and AI agents",
@@ -741,6 +740,7 @@ def test_async_task_execution_call_count():
     ) as mock_execute_sync, patch.object(
         Task, "execute_async", return_value=mock_future
     ) as mock_execute_async:
+
         crew.kickoff()
 
         assert mock_execute_async.call_count == 2
@@ -1148,6 +1148,7 @@ def test_code_execution_flag_adds_code_tool_upon_kickoff():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_delegation_is_not_enabled_if_there_are_only_one_agent():
+
     researcher = Agent(
         role="Researcher",
         goal="Make the best research and analysis on content about AI and AI agents",
@@ -1237,10 +1238,10 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
     print(crew.usage_metrics)
 
     assert crew.usage_metrics == {
-        "total_tokens": 311,
-        "prompt_tokens": 224,
-        "completion_tokens": 87,
-        "successful_requests": 1,
+        "total_tokens": 2217,
+        "prompt_tokens": 1847,
+        "completion_tokens": 370,
+        "successful_requests": 4,
     }
 
 
@@ -1270,7 +1271,7 @@ def test_hierarchical_crew_creation_tasks_with_agents():
     assert crew.manager_agent.tools is not None
     print("TOOL DESCRIPTION", crew.manager_agent.tools[0].description)
     assert crew.manager_agent.tools[0].description.startswith(
-        "Delegate a specific task to one of the following coworkers: [Senior Writer, Researcher]"
+        "Delegate a specific task to one of the following coworkers: Senior Writer"
     )
 
 
@@ -1379,6 +1380,7 @@ def test_crew_does_not_interpolate_without_inputs():
             interpolate_task_inputs.assert_not_called()
 
 
+# TODO: Ask @joao if we want to start throwing errors if inputs are not provided
 # def test_crew_partial_inputs():
 #     agent = Agent(
 #         role="{topic} Researcher",
@@ -1402,6 +1404,7 @@ def test_crew_does_not_interpolate_without_inputs():
 #     assert crew.agents[0].backstory == "You have a lot of experience with AI."
 
 
+# TODO: If we do want ot throw errors if we are missing inputs. Add in this test.
 # def test_crew_invalid_inputs():
 #     agent = Agent(
 #         role="{topic} Researcher",
@@ -1803,472 +1806,3 @@ def test__setup_for_training():
 
     for agent in agents:
         assert agent.allow_delegation is False
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_replay_feature():
-    list_ideas = Task(
-        description="Generate a list of 5 interesting ideas to explore for an article, where each bulletpoint is under 15 words.",
-        expected_output="Bullet point list of 5 important events. No additional commentary.",
-        agent=researcher,
-    )
-    write = Task(
-        description="Write a sentence about the events",
-        expected_output="A sentence about the events",
-        agent=writer,
-        context=[list_ideas],
-    )
-
-    crew = Crew(
-        agents=[researcher, writer],
-        tasks=[list_ideas, write],
-        process=Process.sequential,
-    )
-
-    with patch.object(Task, "execute_sync") as mock_execute_task:
-        mock_execute_task.return_value = TaskOutput(
-            description="Mock description",
-            raw="Mocked output for list of ideas",
-            agent="Researcher",
-            json_dict=None,
-            output_format=OutputFormat.RAW,
-            pydantic=None,
-            summary="Mocked output for list of ideas",
-        )
-
-        crew.kickoff()
-        crew.replay_from_task(str(write.id))
-        # Ensure context was passed correctly
-        assert mock_execute_task.call_count == 3
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_crew_replay_from_task_error():
-    task = Task(
-        description="Come up with a list of 5 interesting ideas to explore for an article",
-        expected_output="5 bullet points with a paragraph for each idea.",
-        agent=researcher,
-    )
-
-    crew = Crew(
-        agents=[researcher, writer],
-        tasks=[task],
-    )
-
-    with pytest.raises(TypeError) as e:
-        crew.replay_from_task()  # type: ignore purposefully throwing err
-        assert "task_id is required" in str(e)
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_crew_task_output_file_creation():
-    agent = Agent(
-        role="Content Writer",
-        goal="Write engaging content on various topics.",
-        backstory="You have a background in journalism and creative writing.",
-    )
-
-    task = Task(
-        description="Write a detailed article about AI in healthcare.",
-        expected_output="A 1 paragraph article about AI.",
-        agent=agent,
-    )
-
-    crew = Crew(agents=[agent], tasks=[task])
-
-    with patch.object(Task, "execute_sync") as mock_execute_task:
-        mock_execute_task.return_value = TaskOutput(
-            description="Write about AI in healthcare.",
-            raw="Artificial Intelligence (AI) is revolutionizing healthcare by enhancing diagnostic accuracy, personalizing treatment plans, and streamlining administrative tasks.",
-            agent="Content Writer",
-            json_dict=None,
-            output_format=OutputFormat.RAW,
-            pydantic=None,
-            summary="Write about AI in healthcare...",
-        )
-
-        crew.kickoff()
-
-        # Check if the crew_tasks_output.json file is created
-        assert os.path.exists(CREW_TASKS_OUTPUT_FILE)
-
-        # Clean up the file after test
-        if os.path.exists(CREW_TASKS_OUTPUT_FILE):
-            os.remove(CREW_TASKS_OUTPUT_FILE)
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_replay_without_output_tasks_json():
-    agent = Agent(
-        role="Technical Writer",
-        goal="Write detailed technical documentation.",
-        backstory="You have a background in software engineering and technical writing.",
-    )
-
-    task = Task(
-        description="Document the process of setting up a Python project.",
-        expected_output="A step-by-step guide on setting up a Python project.",
-        agent=agent,
-    )
-
-    crew = Crew(agents=[agent], tasks=[task])
-
-    with patch.object(Task, "execute_sync") as mock_execute_task:
-        mock_execute_task.return_value = TaskOutput(
-            description="Document the process of setting up a Python project.",
-            raw="To set up a Python project, first create a virtual environment...",
-            agent="Technical Writer",
-            json_dict=None,
-            output_format=OutputFormat.RAW,
-            pydantic=None,
-            summary="Document the process of setting up a Python project...",
-        )
-
-        if os.path.exists(CREW_TASKS_OUTPUT_FILE):
-            os.remove(CREW_TASKS_OUTPUT_FILE)
-
-        with pytest.raises(ValueError):
-            crew.replay_from_task(str(task.id))
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_replay_task_with_context():
-    agent1 = Agent(
-        role="Researcher",
-        goal="Research AI advancements.",
-        backstory="You are an expert in AI research.",
-    )
-    agent2 = Agent(
-        role="Writer",
-        goal="Write detailed articles on AI.",
-        backstory="You have a background in journalism and AI.",
-    )
-
-    task1 = Task(
-        description="Research the latest advancements in AI.",
-        expected_output="A detailed report on AI advancements.",
-        agent=agent1,
-    )
-    task2 = Task(
-        description="Summarize the AI advancements report.",
-        expected_output="A summary of the AI advancements report.",
-        agent=agent2,
-    )
-    task3 = Task(
-        description="Write an article based on the AI advancements summary.",
-        expected_output="An article on AI advancements.",
-        agent=agent2,
-    )
-    task4 = Task(
-        description="Create a presentation based on the AI advancements article.",
-        expected_output="A presentation on AI advancements.",
-        agent=agent2,
-        context=[task1],
-    )
-
-    crew = Crew(
-        agents=[agent1, agent2],
-        tasks=[task1, task2, task3, task4],
-        process=Process.sequential,
-    )
-
-    mock_task_output1 = TaskOutput(
-        description="Research the latest advancements in AI.",
-        raw="Detailed report on AI advancements...",
-        agent="Researcher",
-        json_dict=None,
-        output_format=OutputFormat.RAW,
-        pydantic=None,
-        summary="Detailed report on AI advancements...",
-    )
-    mock_task_output2 = TaskOutput(
-        description="Summarize the AI advancements report.",
-        raw="Summary of the AI advancements report...",
-        agent="Writer",
-        json_dict=None,
-        output_format=OutputFormat.RAW,
-        pydantic=None,
-        summary="Summary of the AI advancements report...",
-    )
-    mock_task_output3 = TaskOutput(
-        description="Write an article based on the AI advancements summary.",
-        raw="Article on AI advancements...",
-        agent="Writer",
-        json_dict=None,
-        output_format=OutputFormat.RAW,
-        pydantic=None,
-        summary="Article on AI advancements...",
-    )
-    mock_task_output4 = TaskOutput(
-        description="Create a presentation based on the AI advancements article.",
-        raw="Presentation on AI advancements...",
-        agent="Writer",
-        json_dict=None,
-        output_format=OutputFormat.RAW,
-        pydantic=None,
-        summary="Presentation on AI advancements...",
-    )
-
-    with patch.object(Task, "execute_sync") as mock_execute_task:
-        mock_execute_task.side_effect = [
-            mock_task_output1,
-            mock_task_output2,
-            mock_task_output3,
-            mock_task_output4,
-        ]
-
-        crew.kickoff()
-
-        # Check if the crew_tasks_output.json file is created
-        assert os.path.exists(CREW_TASKS_OUTPUT_FILE)
-
-        # Replay task4 and ensure it uses task1's context properly
-        with patch.object(Task, "execute_sync") as mock_replay_task:
-            mock_replay_task.return_value = mock_task_output4
-
-            replayed_output = crew.replay_from_task(str(task4.id))
-            assert replayed_output.raw == "Presentation on AI advancements..."
-
-        # Clean up the file after test
-        if os.path.exists(CREW_TASKS_OUTPUT_FILE):
-            os.remove(CREW_TASKS_OUTPUT_FILE)
-
-
-def test_replay_from_task_with_context():
-    agent = Agent(role="test_agent", backstory="Test Description", goal="Test Goal")
-    task1 = Task(
-        description="Context Task", expected_output="Say Task Output", agent=agent
-    )
-    task2 = Task(
-        description="Test Task", expected_output="Say Hi", agent=agent, context=[task1]
-    )
-
-    context_output = TaskOutput(
-        description="Context Task Output",
-        agent="test_agent",
-        raw="context raw output",
-        pydantic=None,
-        json_dict={},
-        output_format=OutputFormat.RAW,
-    )
-    task1.output = context_output
-
-    crew = Crew(agents=[agent], tasks=[task1, task2], process=Process.sequential)
-
-    with patch(
-        "crewai.utilities.task_output_handler.TaskOutputJsonHandler.load",
-        return_value=[
-            {
-                "task_id": str(task1.id),
-                "output": {
-                    "description": context_output.description,
-                    "summary": context_output.summary,
-                    "raw": context_output.raw,
-                    "pydantic": context_output.pydantic,
-                    "json_dict": context_output.json_dict,
-                    "output_format": context_output.output_format,
-                    "agent": context_output.agent,
-                },
-                "inputs": {},
-            },
-            {
-                "task_id": str(task2.id),
-                "output": {
-                    "description": "Test Task Output",
-                    "summary": None,
-                    "raw": "test raw output",
-                    "pydantic": None,
-                    "json_dict": {},
-                    "output_format": "json",
-                    "agent": "test_agent",
-                },
-                "inputs": {},
-            },
-        ],
-    ):
-        crew.replay_from_task(str(task2.id))
-
-        assert crew.tasks[1].context[0].output.raw == "context raw output"
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_replay_with_invalid_task_id():
-    agent = Agent(role="test_agent", backstory="Test Description", goal="Test Goal")
-    task1 = Task(
-        description="Context Task", expected_output="Say Task Output", agent=agent
-    )
-    task2 = Task(
-        description="Test Task", expected_output="Say Hi", agent=agent, context=[task1]
-    )
-
-    context_output = TaskOutput(
-        description="Context Task Output",
-        agent="test_agent",
-        raw="context raw output",
-        pydantic=None,
-        json_dict={},
-        output_format=OutputFormat.RAW,
-    )
-    task1.output = context_output
-
-    crew = Crew(agents=[agent], tasks=[task1, task2], process=Process.sequential)
-
-    with patch(
-        "crewai.utilities.task_output_handler.TaskOutputJsonHandler.load",
-        return_value=[
-            {
-                "task_id": str(task1.id),
-                "output": {
-                    "description": context_output.description,
-                    "summary": context_output.summary,
-                    "raw": context_output.raw,
-                    "pydantic": context_output.pydantic,
-                    "json_dict": context_output.json_dict,
-                    "output_format": context_output.output_format,
-                    "agent": context_output.agent,
-                },
-                "inputs": {},
-            },
-            {
-                "task_id": str(task2.id),
-                "output": {
-                    "description": "Test Task Output",
-                    "summary": None,
-                    "raw": "test raw output",
-                    "pydantic": None,
-                    "json_dict": {},
-                    "output_format": "json",
-                    "agent": "test_agent",
-                },
-                "inputs": {},
-            },
-        ],
-    ):
-        with pytest.raises(
-            ValueError,
-            match="Task with id bf5b09c9-69bd-4eb8-be12-f9e5bae31c2d not found in the crew's tasks.",
-        ):
-            crew.replay_from_task("bf5b09c9-69bd-4eb8-be12-f9e5bae31c2d")
-
-
-@patch.object(Crew, "_interpolate_inputs")
-def test_replay_interpolates_inputs_properly(mock_interpolate_inputs):
-    agent = Agent(role="test_agent", backstory="Test Description", goal="Test Goal")
-    task1 = Task(description="Context Task", expected_output="Say {name}", agent=agent)
-    task2 = Task(
-        description="Test Task",
-        expected_output="Say Hi to {name}",
-        agent=agent,
-        context=[task1],
-    )
-
-    context_output = TaskOutput(
-        description="Context Task Output",
-        agent="test_agent",
-        raw="context raw output",
-        pydantic=None,
-        json_dict={},
-        output_format=OutputFormat.RAW,
-    )
-    task1.output = context_output
-
-    crew = Crew(agents=[agent], tasks=[task1, task2], process=Process.sequential)
-    crew.kickoff(inputs={"name": "John"})
-
-    with patch(
-        "crewai.utilities.task_output_handler.TaskOutputJsonHandler.load",
-        return_value=[
-            {
-                "task_id": str(task1.id),
-                "output": {
-                    "description": context_output.description,
-                    "summary": context_output.summary,
-                    "raw": context_output.raw,
-                    "pydantic": context_output.pydantic,
-                    "json_dict": context_output.json_dict,
-                    "output_format": context_output.output_format,
-                    "agent": context_output.agent,
-                },
-                "inputs": {"name": "John"},
-            },
-            {
-                "task_id": str(task2.id),
-                "output": {
-                    "description": "Test Task Output",
-                    "summary": None,
-                    "raw": "test raw output",
-                    "pydantic": None,
-                    "json_dict": {},
-                    "output_format": "json",
-                    "agent": "test_agent",
-                },
-                "inputs": {"name": "John"},
-            },
-        ],
-    ):
-        crew.replay_from_task(str(task2.id))
-        assert crew._inputs == {"name": "John"}
-        assert mock_interpolate_inputs.call_count == 2
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_replay_from_task_setup_context():
-    agent = Agent(role="test_agent", backstory="Test Description", goal="Test Goal")
-    task1 = Task(description="Context Task", expected_output="Say {name}", agent=agent)
-    task2 = Task(
-        description="Test Task",
-        expected_output="Say Hi to {name}",
-        agent=agent,
-    )
-    context_output = TaskOutput(
-        description="Context Task Output",
-        agent="test_agent",
-        raw="context raw output",
-        pydantic=None,
-        json_dict={},
-        output_format=OutputFormat.RAW,
-    )
-    task1.output = context_output
-    crew = Crew(agents=[agent], tasks=[task1, task2], process=Process.sequential)
-    with patch(
-        "crewai.utilities.task_output_handler.TaskOutputJsonHandler.load",
-        return_value=[
-            {
-                "task_id": str(task1.id),
-                "output": {
-                    "description": context_output.description,
-                    "summary": context_output.summary,
-                    "raw": context_output.raw,
-                    "pydantic": context_output.pydantic,
-                    "json_dict": context_output.json_dict,
-                    "output_format": context_output.output_format,
-                    "agent": context_output.agent,
-                },
-                "inputs": {"name": "John"},
-            },
-            {
-                "task_id": str(task2.id),
-                "output": {
-                    "description": "Test Task Output",
-                    "summary": None,
-                    "raw": "test raw output",
-                    "pydantic": None,
-                    "json_dict": {},
-                    "output_format": "json",
-                    "agent": "test_agent",
-                },
-                "inputs": {"name": "John"},
-            },
-        ],
-    ):
-        crew.replay_from_task(str(task2.id))
-
-        # Check if the first task's output was set correctly
-        assert crew.tasks[0].output is not None
-        assert isinstance(crew.tasks[0].output, TaskOutput)
-        assert crew.tasks[0].output.description == "Context Task Output"
-        assert crew.tasks[0].output.agent == "test_agent"
-        assert crew.tasks[0].output.raw == "context raw output"
-        assert crew.tasks[0].output.output_format == OutputFormat.RAW
-
-        assert crew.tasks[1].prompt_context == "context raw output"

tests/task_test.py

@@ -81,7 +81,7 @@ def test_task_prompt_includes_expected_output():
 
     with patch.object(Agent, "execute_task") as execute:
         execute.return_value = "ok"
-        task.execute_sync(agent=researcher)
+        task.execute_sync()
         execute.assert_called_once_with(task=task, context=None, tools=[])
 
 
@@ -104,7 +104,7 @@ def test_task_callback():
 
     with patch.object(Agent, "execute_task") as execute:
         execute.return_value = "ok"
-        task.execute_sync(agent=researcher)
+        task.execute_sync()
         task_completed.assert_called_once_with(task.output)
 
 
@@ -129,7 +129,7 @@ def test_task_callback_returns_task_ouput():
 
     with patch.object(Agent, "execute_task") as execute:
         execute.return_value = "exported_ok"
-        task.execute_sync(agent=researcher)
+        task.execute_sync()
         # Ensure the callback is called with a TaskOutput object serialized to JSON
         task_completed.assert_called_once()
         callback_data = task_completed.call_args[0][0]
@@ -521,7 +521,9 @@ def test_save_task_json_output():
     with patch.object(Task, "_save_file") as save_file:
         save_file.return_value = None
         crew.kickoff()
-        save_file.assert_called_once_with({"score": 4})
+        save_file.assert_called_once_with(
+            {"score": 4}
+        )  # TODO: @Joao, should this be a dict or a json string?
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])