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https://github.com/crewAIInc/crewAI.git
synced 2026-01-09 08:08:32 +00:00
Adding support to export tasks as json, pydantic objects, and save as file
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@@ -41,7 +41,6 @@ class Crew(BaseModel):
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full_output: Whether the crew should return the full output with all tasks outputs or just the final output.
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full_output: Whether the crew should return the full output with all tasks outputs or just the final output.
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step_callback: Callback to be executed after each step for every agents execution.
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step_callback: Callback to be executed after each step for every agents execution.
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share_crew: Whether you want to share the complete crew infromation and execution with crewAI to make the library better, and allow us to train models.
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share_crew: Whether you want to share the complete crew infromation and execution with crewAI to make the library better, and allow us to train models.
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_cache_handler: Handles caching for the crew's operations.
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"""
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"""
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__hash__ = object.__hash__ # type: ignore
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__hash__ = object.__hash__ # type: ignore
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@@ -1,13 +1,13 @@
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import threading
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import threading
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import uuid
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import uuid
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from typing import Any, List, Optional
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from typing import Any, List, Optional, Type
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from pydantic import UUID4, BaseModel, Field, field_validator, model_validator
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from pydantic import UUID4, BaseModel, Field, field_validator, model_validator
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from pydantic_core import PydanticCustomError
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from pydantic_core import PydanticCustomError
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from crewai.agent import Agent
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from crewai.agent import Agent
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from crewai.tasks.task_output import TaskOutput
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from crewai.tasks.task_output import TaskOutput
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from crewai.utilities import I18N
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from crewai.utilities import I18N, Instructor
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class Task(BaseModel):
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class Task(BaseModel):
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@@ -39,10 +39,22 @@ class Task(BaseModel):
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description="Whether the task should be executed asynchronously or not.",
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description="Whether the task should be executed asynchronously or not.",
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default=False,
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default=False,
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)
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)
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output_json: Optional[Type[BaseModel]] = Field(
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description="A Pydantic model to be used to create a JSON output.",
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default=None,
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)
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output_pydantic: Optional[Type[BaseModel]] = Field(
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description="A Pydantic model to be used to create a Pydantic output.",
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default=None,
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)
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output_file: Optional[str] = Field(
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description="A file path to be used to create a file output.",
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default=None,
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)
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output: Optional[TaskOutput] = Field(
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output: Optional[TaskOutput] = Field(
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description="Task output, it's final result after being executed", default=None
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description="Task output, it's final result after being executed", default=None
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)
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)
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tools: List[Any] = Field(
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tools: Optional[List[Any]] = Field(
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default_factory=list,
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default_factory=list,
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description="Tools the agent is limited to use for this task.",
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description="Tools the agent is limited to use for this task.",
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)
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)
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@@ -67,6 +79,18 @@ class Task(BaseModel):
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self.tools.extend(self.agent.tools)
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self.tools.extend(self.agent.tools)
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return self
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return self
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@model_validator(mode="after")
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def check_output(self):
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"""Check if an output type is set."""
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output_types = [self.output_json, self.output_pydantic]
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if len([type for type in output_types if type]) > 1:
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raise PydanticCustomError(
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"output_type",
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"Only one output type can be set, either output_pydantic or output_json.",
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{},
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)
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return self
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def execute(
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def execute(
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self,
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self,
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agent: Agent | None = None,
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agent: Agent | None = None,
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@@ -115,9 +139,19 @@ class Task(BaseModel):
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context=context,
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context=context,
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tools=tools,
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tools=tools,
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)
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)
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self.output = TaskOutput(description=self.description, result=result)
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self.callback(self.output) if self.callback else None
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exported_output = self._export_output(result)
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return result
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self.output = TaskOutput(
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description=self.description,
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exported_output=exported_output,
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raw_output=result,
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)
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if self.callback:
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self.callback(self.output)
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return exported_output
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def prompt(self) -> str:
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def prompt(self) -> str:
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"""Prompt the task.
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"""Prompt the task.
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@@ -133,3 +167,28 @@ class Task(BaseModel):
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)
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)
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tasks_slices = [self.description, output]
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tasks_slices = [self.description, output]
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return "\n".join(tasks_slices)
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return "\n".join(tasks_slices)
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def _export_output(self, result: str) -> Any:
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if self.output_pydantic or self.output_json:
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model = self.output_pydantic or self.output_json
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instructor = Instructor(
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agent=self.agent,
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content=result,
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model=model,
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)
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if self.output_pydantic:
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result = instructor.to_pydantic()
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elif self.output_json:
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result = instructor.to_json()
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if self.output_file:
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content = result if not self.output_pydantic else result.json()
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self._save_file(content)
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return result
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def _save_file(self, result: Any) -> None:
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with open(self.output_file, "w") as file:
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file.write(result)
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return None
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@@ -1,4 +1,4 @@
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from typing import Optional
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from typing import Optional, Union
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from pydantic import BaseModel, Field, model_validator
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from pydantic import BaseModel, Field, model_validator
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@@ -8,7 +8,10 @@ class TaskOutput(BaseModel):
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description: str = Field(description="Description of the task")
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description: str = Field(description="Description of the task")
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summary: Optional[str] = Field(description="Summary of the task", default=None)
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summary: Optional[str] = Field(description="Summary of the task", default=None)
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result: str = Field(description="Result of the task")
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exported_output: Union[str, BaseModel] = Field(
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description="Output of the task", default=None
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)
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raw_output: str = Field(description="Result of the task")
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@model_validator(mode="after")
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@model_validator(mode="after")
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def set_summary(self):
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def set_summary(self):
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