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fix: type checking

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This commit is contained in:
Eduardo Chiarotti
2024-06-27 10:28:52 -07:00
parent 62679d2fec
commit a4f7631e57
4 changed files with 35 additions and 50 deletions
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10
src/crewai/agent.py
View File

@@ -210,8 +210,7 @@ class Agent(BaseModel):
Output of the agent
"""
if self.tools_handler:
# type: ignore # Incompatible types in assignment (expression has type "dict[Never, Never]", variable has type "ToolCalling")
self.tools_handler.last_used_tool = {}
self.tools_handler.last_used_tool = {} # type: ignore # Incompatible types in assignment (expression has type "dict[Never, Never]", variable has type "ToolCalling")
task_prompt = task.prompt()
@@ -231,8 +230,8 @@ class Agent(BaseModel):
task_prompt += self.i18n.slice("memory").format(memory=memory)
tools = tools or self.tools
# type: ignore # Argument 1 to "_parse_tools" of "Agent" has incompatible type "list[Any] | None"; expected "list[Any]"
parsed_tools = self._parse_tools(tools)
parsed_tools = self._parse_tools(tools) # type: ignore # Argument 1 to "_parse_tools" of "Agent" has incompatible type "list[Any] | None"; expected "list[Any]"
self.create_agent_executor(tools=tools)
self.agent_executor.tools = parsed_tools
@@ -399,8 +398,7 @@ class Agent(BaseModel):
return copied_agent
# type: ignore # Function "langchain_core.tools.tool" is not valid as a type
def _parse_tools(self, tools: List[Any]) -> List[LangChainTool]:
def _parse_tools(self, tools: List[Any]) -> List[LangChainTool]: # type: ignore # Function "langchain_core.tools.tool" is not valid as a type
"""Parse tools to be used for the task."""
# tentatively try to import from crewai_tools import BaseTool as CrewAITool
tools_list = []

31
src/crewai/crew.py
View File

@@ -281,8 +281,8 @@ class Crew(BaseModel):
) -> Union[str, Dict[str, Any]]:
"""Starts the crew to work on its assigned tasks."""
self._execution_span = self._telemetry.crew_execution_span(self)
# type: ignore # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
self._interpolate_inputs(inputs)
self._interpolate_inputs(inputs) # type: ignore # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
self._set_tasks_callbacks()
i18n = I18N(prompt_file=self.prompt_file)
@@ -303,10 +303,8 @@ class Crew(BaseModel):
if self.process == Process.sequential:
result = self._run_sequential_process()
elif self.process == Process.hierarchical:
# type: ignore # Unpacking a string is disallowed
result, manager_metrics = self._run_hierarchical_process()
# type: ignore # Cannot determine type of "manager_metrics"
metrics.append(manager_metrics)
result, manager_metrics = self._run_hierarchical_process() # type: ignore # Unpacking a string is disallowed
metrics.append(manager_metrics) # type: ignore # Cannot determine type of "manager_metrics"
else:
raise NotImplementedError(
f"The process '{self.process}' is not implemented yet."
@@ -316,7 +314,8 @@ class Crew(BaseModel):
agent._token_process.get_summary() for agent in self.agents
]
self.usage_metrics = {
key: sum([m[key] for m in metrics if m is not None]) for key in metrics[0]
key: sum([m[key] for m in metrics if m is not None]) # type: ignore # List comprehension has incompatible type List[Any | str]; expected List[bool]
for key in metrics[0]
}
return result
@@ -395,10 +394,10 @@ class Crew(BaseModel):
self._file_handler.log(agent=role, task=task_output, status="completed")
self._finish_execution(task_output)
# type: ignore # Item "None" of "Agent | None" has no attribute "_token_process"
token_usage = task.agent._token_process.get_summary()
# type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
return self._format_output(task_output, token_usage)
token_usage = task.agent._token_process.get_summary() # type: ignore # Item "None" of "Agent | None" has no attribute "_token_process"
return self._format_output(task_output, token_usage) # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
def _run_hierarchical_process(self) -> Union[str, Dict[str, Any]]:
"""Creates and assigns a manager agent to make sure the crew completes the tasks."""
@@ -434,7 +433,7 @@ class Crew(BaseModel):
agent=manager, context=task_output, tools=manager.tools
)
self._logger.log("debug", f"[{manager.role}] Task output: {task_output}")
self._logger.log("debug", f"[{manager.role}] Task ouptput: {task_output}")
if self.output_log_file:
self._file_handler.log(
@@ -442,9 +441,9 @@ class Crew(BaseModel):
)
self._finish_execution(task_output)
# type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
manager_token_usage = manager._token_process.get_summary()
return self._format_output(
return self._format_output( # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
task_output, manager_token_usage
), manager_token_usage
@@ -493,8 +492,8 @@ class Crew(BaseModel):
)
for task in self.tasks
]
# type: ignore # "interpolate_inputs" of "Agent" does not return a value (it only ever returns None)
[agent.interpolate_inputs(inputs) for agent in self.agents]
[agent.interpolate_inputs(inputs) for agent in self.agents] # type: ignore # "interpolate_inputs" of "Agent" does not return a value (it only ever returns None)
def _format_output(
self, output: str, token_usage: Optional[Dict[str, Any]]

38
src/crewai/task.py
View File

@@ -1,8 +1,8 @@
from copy import deepcopy
import os
import re
import threading
import uuid
from copy import deepcopy
from typing import Any, Dict, List, Optional, Type
from langchain_openai import ChatOpenAI
@@ -164,16 +164,13 @@ class Task(BaseModel):
)
if self.context:
# type: ignore # Incompatible types in assignment (expression has type "list[Never]", variable has type "str | None")
context = []
context = [] # type: ignore # Incompatible types in assignment (expression has type "list[Never]", variable has type "str | None")
for task in self.context:
if task.async_execution:
task.thread.join() # type: ignore # Item "None" of "Thread | None" has no attribute "join"
if task and task.output:
# type: ignore # Item "str" of "str | None" has no attribute "append"
context.append(task.output.raw_output)
# type: ignore # Argument 1 to "join" of "str" has incompatible type "str | None"; expected "Iterable[str]"
context = "\n".join(context)
context.append(task.output.raw_output) # type: ignore # Item "str" of "str | None" has no attribute "append"
context = "\n".join(context) # type: ignore # Argument 1 to "join" of "str" has incompatible type "str | None"; expected "Iterable[str]"
self.prompt_context = context
tools = tools or self.tools
@@ -281,32 +278,26 @@ class Task(BaseModel):
# try to convert task_output directly to pydantic/json
try:
# type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
exported_result = model.model_validate_json(result)
exported_result = model.model_validate_json(result) # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
if self.output_json:
# type: ignore # "str" has no attribute "model_dump"
return exported_result.model_dump()
return exported_result.model_dump() # type: ignore # "str" has no attribute "model_dump"
return exported_result
except Exception:
# sometimes the response contains valid JSON in the middle of text
match = re.search(r"({.*})", result, re.DOTALL)
if match:
try:
# type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
exported_result = model.model_validate_json(match.group(0))
exported_result = model.model_validate_json(match.group(0)) # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
if self.output_json:
# type: ignore # "str" has no attribute "model_dump"
return exported_result.model_dump()
return exported_result.model_dump() # type: ignore # "str" has no attribute "model_dump"
return exported_result
except Exception:
pass
# type: ignore # Item "None" of "Agent | None" has no attribute "function_calling_llm"
llm = self.agent.function_calling_llm or self.agent.llm
llm = self.agent.function_calling_llm or self.agent.llm # type: ignore # Item "None" of "Agent | None" has no attribute "function_calling_llm"
if not self._is_gpt(llm):
# type: ignore # Argument "model" to "PydanticSchemaParser" has incompatible type "type[BaseModel] | None"; expected "type[BaseModel]"
model_schema = PydanticSchemaParser(model=model).get_schema()
model_schema = PydanticSchemaParser(model=model).get_schema() # type: ignore # Argument "model" to "PydanticSchemaParser" has incompatible type "type[BaseModel] | None"; expected "type[BaseModel]"
instructions = f"{instructions}\n\nThe json should have the following structure, with the following keys:\n{model_schema}"
converter = Converter(
@@ -327,8 +318,7 @@ class Task(BaseModel):
if self.output_file:
content = (
# type: ignore # "str" has no attribute "json"
exported_result if not self.output_pydantic else exported_result.json()
exported_result if not self.output_pydantic else exported_result.json() # type: ignore # "str" has no attribute "json"
)
self._save_file(content)
@@ -338,14 +328,12 @@ class Task(BaseModel):
return isinstance(llm, ChatOpenAI) and llm.openai_api_base is None
def _save_file(self, result: Any) -> None:
# type: ignore # Value of type variable "AnyOrLiteralStr" of "dirname" cannot be "str | None"
directory = os.path.dirname(self.output_file)
directory = os.path.dirname(self.output_file) # type: ignore # Value of type variable "AnyOrLiteralStr" of "dirname" cannot be "str | None"
if directory and not os.path.exists(directory):
os.makedirs(directory)
# type: ignore # Argument 1 to "open" has incompatible type "str | None"; expected "int | str | bytes | PathLike[str] | PathLike[bytes]"
with open(self.output_file, "w", encoding="utf-8") as file:
with open(self.output_file, "w", encoding="utf-8") as file: # type: ignore # Argument 1 to "open" has incompatible type "str | None"; expected "int | str | bytes | PathLike[str] | PathLike[bytes]"
file.write(result)
return None

6
src/crewai/tools/agent_tools.py
View File

@@ -78,7 +78,7 @@ class AgentTools(BaseModel):
# {"task": "....", "coworker": "...."}
agent_name = agent.casefold().replace('"', "").replace("\n", "")
agent = [
agent = [ # type: ignore # Incompatible types in assignment (expression has type "list[Agent]", variable has type "str | None")
available_agent
for available_agent in self.agents
if available_agent.role.casefold().replace("\n", "") == agent_name
@@ -98,9 +98,9 @@ class AgentTools(BaseModel):
)
agent = agent[0]
task = Task(
task = 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)
return agent.execute_task(task, context) # type: ignore # "str" has no attribute "execute_task"