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Merge branch 'main' into feat/joao-flow-improvement-requests

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Brandon Hancock (bhancock_ai)
2024-12-23 12:52:12 -05:00
committed by GitHub
parent 10706ce2ee 22e5d39884
commit 156726f7cd
22 changed files with 583 additions and 48 deletions
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2
src/crewai/cli/templates/crew/README.md
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@@ -4,7 +4,7 @@ Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.co
## Installation
Ensure you have Python >=3.10 <=3.12 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
Ensure you have Python >=3.10 <3.13 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
First, if you haven't already, install uv:

5
src/crewai/cli/templates/crew/pyproject.toml
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@@ -3,7 +3,7 @@ name = "{{folder_name}}"
version = "0.1.0"
description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<=3.12"
requires-python = ">=3.10,<3.13"
dependencies = [
"crewai[tools]>=0.86.0,<1.0.0"
]
@@ -18,3 +18,6 @@ test = "{{folder_name}}.main:test"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.crewai]
type = "crew"

2
src/crewai/cli/templates/flow/README.md
View File

@@ -4,7 +4,7 @@ Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.co
## Installation
Ensure you have Python >=3.10 <=3.12 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
Ensure you have Python >=3.10 <3.13 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
First, if you haven't already, install uv:

2
src/crewai/cli/templates/flow/main.py
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@@ -5,7 +5,7 @@ from pydantic import BaseModel
from crewai.flow.flow import Flow, listen, start
from .crews.poem_crew.poem_crew import PoemCrew
from {{folder_name}}.crews.poem_crew.poem_crew import PoemCrew
class PoemState(BaseModel):

5
src/crewai/cli/templates/flow/pyproject.toml
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@@ -3,7 +3,7 @@ name = "{{folder_name}}"
version = "0.1.0"
description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<=3.12"
requires-python = ">=3.10,<3.13"
dependencies = [
"crewai[tools]>=0.86.0,<1.0.0",
]
@@ -15,3 +15,6 @@ plot = "{{folder_name}}.main:plot"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.crewai]
type = "flow"

2
src/crewai/cli/templates/tool/README.md
View File

@@ -5,7 +5,7 @@ custom tools to power up your crews.
## Installing
Ensure you have Python >=3.10 <=3.12 installed on your system. This project
Ensure you have Python >=3.10 <3.13 installed on your system. This project
uses [UV](https://docs.astral.sh/uv/) for dependency management and package
handling, offering a seamless setup and execution experience.

4
src/crewai/cli/templates/tool/pyproject.toml
View File

@@ -3,8 +3,10 @@ name = "{{folder_name}}"
version = "0.1.0"
description = "Power up your crews with {{folder_name}}"
readme = "README.md"
requires-python = ">=3.10,<=3.12"
requires-python = ">=3.10,<3.13"
dependencies = [
"crewai[tools]>=0.86.0"
]
[tool.crewai]
type = "tool"

1
src/crewai/llm.py
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@@ -44,6 +44,7 @@ LLM_CONTEXT_WINDOW_SIZES = {
"o1-preview": 128000,
"o1-mini": 128000,
# gemini
"gemini-2.0-flash": 1048576,
"gemini-1.5-pro": 2097152,
"gemini-1.5-flash": 1048576,
"gemini-1.5-flash-8b": 1048576,

85
src/crewai/task.py
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@@ -1,4 +1,5 @@
import datetime
import inspect
import json
import threading
import uuid
@@ -6,7 +7,7 @@ from concurrent.futures import Future
from copy import copy
from hashlib import md5
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple, Type, Union
from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Type, Union
from opentelemetry.trace import Span
from pydantic import (
@@ -20,6 +21,7 @@ from pydantic import (
from pydantic_core import PydanticCustomError
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.tasks.guardrail_result import GuardrailResult
from crewai.tasks.output_format import OutputFormat
from crewai.tasks.task_output import TaskOutput
from crewai.telemetry.telemetry import Telemetry
@@ -110,6 +112,55 @@ class Task(BaseModel):
default=None,
)
processed_by_agents: Set[str] = Field(default_factory=set)
guardrail: Optional[Callable[[TaskOutput], Tuple[bool, Any]]] = Field(
default=None,
description="Function to validate task output before proceeding to next task"
)
max_retries: int = Field(
default=3,
description="Maximum number of retries when guardrail fails"
)
retry_count: int = Field(
default=0,
description="Current number of retries"
)
@field_validator("guardrail")
@classmethod
def validate_guardrail_function(cls, v: Optional[Callable]) -> Optional[Callable]:
"""Validate that the guardrail function has the correct signature and behavior.
While type hints provide static checking, this validator ensures runtime safety by:
1. Verifying the function accepts exactly one parameter (the TaskOutput)
2. Checking return type annotations match Tuple[bool, Any] if present
3. Providing clear, immediate error messages for debugging
This runtime validation is crucial because:
- Type hints are optional and can be ignored at runtime
- Function signatures need immediate validation before task execution
- Clear error messages help users debug guardrail implementation issues
Args:
v: The guardrail function to validate
Returns:
The validated guardrail function
Raises:
ValueError: If the function signature is invalid or return annotation
doesn't match Tuple[bool, Any]
"""
if v is not None:
sig = inspect.signature(v)
if len(sig.parameters) != 1:
raise ValueError("Guardrail function must accept exactly one parameter")
# Check return annotation if present, but don't require it
return_annotation = sig.return_annotation
if return_annotation != inspect.Signature.empty:
if not (return_annotation == Tuple[bool, Any] or str(return_annotation) == 'Tuple[bool, Any]'):
raise ValueError("If return type is annotated, it must be Tuple[bool, Any]")
return v
_telemetry: Telemetry = PrivateAttr(default_factory=Telemetry)
_execution_span: Optional[Span] = PrivateAttr(default=None)
@@ -254,7 +305,6 @@ class Task(BaseModel):
)
pydantic_output, json_output = self._export_output(result)
task_output = TaskOutput(
name=self.name,
description=self.description,
@@ -265,6 +315,37 @@ class Task(BaseModel):
agent=agent.role,
output_format=self._get_output_format(),
)
if self.guardrail:
guardrail_result = GuardrailResult.from_tuple(self.guardrail(task_output))
if not guardrail_result.success:
if self.retry_count >= self.max_retries:
raise Exception(
f"Task failed guardrail validation after {self.max_retries} retries. "
f"Last error: {guardrail_result.error}"
)
self.retry_count += 1
context = (
f"### Previous attempt failed validation: {guardrail_result.error}\n\n\n"
f"### Previous result:\n{task_output.raw}\n\n\n"
"Try again, making sure to address the validation error."
)
return self._execute_core(agent, context, tools)
if guardrail_result.result is None:
raise Exception(
"Task guardrail returned None as result. This is not allowed."
)
if isinstance(guardrail_result.result, str):
task_output.raw = guardrail_result.result
pydantic_output, json_output = self._export_output(guardrail_result.result)
task_output.pydantic = pydantic_output
task_output.json_dict = json_output
elif isinstance(guardrail_result.result, TaskOutput):
task_output = guardrail_result.result
self.output = task_output
self._set_end_execution_time(start_time)

56
src/crewai/tasks/guardrail_result.py Normal file
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@@ -0,0 +1,56 @@
"""
Module for handling task guardrail validation results.
This module provides the GuardrailResult class which standardizes
the way task guardrails return their validation results.
"""
from typing import Any, Optional, Tuple, Union
from pydantic import BaseModel, field_validator
class GuardrailResult(BaseModel):
"""Result from a task guardrail execution.
This class standardizes the return format of task guardrails,
converting tuple responses into a structured format that can
be easily handled by the task execution system.
Attributes:
success (bool): Whether the guardrail validation passed
result (Any, optional): The validated/transformed result if successful
error (str, optional): Error message if validation failed
"""
success: bool
result: Optional[Any] = None
error: Optional[str] = None
@field_validator("result", "error")
@classmethod
def validate_result_error_exclusivity(cls, v: Any, info) -> Any:
values = info.data
if "success" in values:
if values["success"] and v and "error" in values and values["error"]:
raise ValueError("Cannot have both result and error when success is True")
if not values["success"] and v and "result" in values and values["result"]:
raise ValueError("Cannot have both result and error when success is False")
return v
@classmethod
def from_tuple(cls, result: Tuple[bool, Union[Any, str]]) -> "GuardrailResult":
"""Create a GuardrailResult from a validation tuple.
Args:
result: A tuple of (success, data) where data is either
the validated result or error message.
Returns:
GuardrailResult: A new instance with the tuple data.
"""
success, data = result
return cls(
success=success,
result=data if success else None,
error=data if not success else None
)

5
src/crewai/tools/tool_usage.py
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@@ -419,9 +419,10 @@ class ToolUsage:
elif value.lower() in [
"true",
"false",
"null",
]: # Check for boolean and null values
value = value.lower()
value = value.lower().capitalize()
elif value.lower() == "null":
value = "None"
else:
# Assume the value is a string and needs quotes
value = '"' + value.replace('"', '\\"') + '"'

2
src/crewai/translations/en.json
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@@ -12,7 +12,7 @@
"tools": "\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\n{tools}\n\nUse the following format:\n\nThought: you should always think about what to do\nAction: the action to take, only one name of [{tool_names}], just the name, exactly as it's written.\nAction Input: the input to the action, just a simple python dictionary, enclosed in curly braces, using \" to wrap keys and values.\nObservation: the result of the action\n\nOnce all necessary information is gathered:\n\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n",
"no_tools": "\nTo give my best complete final answer to the task use the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!",
"format": "I MUST either use a tool (use one at time) OR give my best final answer not both at the same time. To Use the following format:\n\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action, dictionary enclosed in curly braces\nObservation: the result of the action\n... (this Thought/Action/Action Input/Result can repeat N times)\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n",
"final_answer_format": "If you don't need to use any more tools, you must give your best complete final answer, make sure it satisfy the expect criteria, use the EXACT format below:\n\nThought: I now can give a great answer\nFinal Answer: my best complete final answer to the task.\n\n",
"final_answer_format": "If you don't need to use any more tools, you must give your best complete final answer, make sure it satisfies the expected criteria, use the EXACT format below:\n\nThought: I now can give a great answer\nFinal Answer: my best complete final answer to the task.\n\n",
"format_without_tools": "\nSorry, I didn't use the right format. I MUST either use a tool (among the available ones), OR give my best final answer.\nI just remembered the expected format I must follow:\n\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Result can repeat N times)\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n",
"task_with_context": "{task}\n\nThis is the context you're working with:\n{context}",
"expected_output": "\nThis is the expect criteria for your final answer: {expected_output}\nyou MUST return the actual complete content as the final answer, not a summary.",