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Code Issues Actions 3 Packages Projects Releases Wiki Activity

WIP. Figuring out disconnect issue.

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This commit is contained in:
Brandon Hancock
2024-06-25 15:23:32 -07:00
parent c4d76cde8f
commit cc1c97e87d
6 changed files with 401187 additions and 41 deletions
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30
src/crewai/agent.py
View File

@@ -1,6 +1,6 @@
from copy import deepcopy
import os
import uuid
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple
from langchain.agents.agent import RunnableAgent
@@ -55,7 +55,7 @@ class Agent(BaseModel):
_logger: Logger = PrivateAttr()
_rpm_controller: RPMController = PrivateAttr(default=None)
_request_within_rpm_limit: Any = PrivateAttr(default=None)
_token_process: TokenProcess = TokenProcess()
_token_process: TokenProcess = PrivateAttr(default=TokenProcess())
formatting_errors: int = 0
model_config = ConfigDict(arbitrary_types_allowed=True)
@@ -98,8 +98,7 @@ class Agent(BaseModel):
agent_executor: InstanceOf[CrewAgentExecutor] = Field(
default=None, description="An instance of the CrewAgentExecutor class."
)
crew: Any = Field(
default=None, description="Crew to which the agent belongs.")
crew: Any = Field(default=None, description="Crew to which the agent belongs.")
tools_handler: InstanceOf[ToolsHandler] = Field(
default=None, description="An instance of the ToolsHandler class."
)
@@ -110,8 +109,7 @@ class Agent(BaseModel):
default=None,
description="Callback to be executed after each step of the agent execution.",
)
i18n: I18N = Field(
default=I18N(), description="Internationalization settings.")
i18n: I18N = Field(default=I18N(), description="Internationalization settings.")
llm: Any = Field(
default_factory=lambda: ChatOpenAI(
model=os.environ.get("OPENAI_MODEL_NAME", "gpt-4o")
@@ -172,8 +170,8 @@ class Agent(BaseModel):
def set_agent_executor(self) -> "Agent":
"""set agent executor is set."""
if hasattr(self.llm, "model_name"):
token_handler = TokenCalcHandler(
self.llm.model_name, self._token_process)
token_handler = TokenCalcHandler(self.llm.model_name, self._token_process)
print("TOKENHANDLER UUID", token_handler.id)
# Ensure self.llm.callbacks is a list
if not isinstance(self.llm.callbacks, list):
@@ -183,6 +181,10 @@ class Agent(BaseModel):
if not any(
isinstance(handler, TokenCalcHandler) for handler in self.llm.callbacks
):
print(
"IMPORTANT: TokenCalcHandler not found in callbacks. Adding",
token_handler.id,
)
self.llm.callbacks.append(token_handler)
if not self.agent_executor:
@@ -236,8 +238,7 @@ class Agent(BaseModel):
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 = render_text_description(parsed_tools)
self.agent_executor.tools_names = self.__tools_names(parsed_tools)
result = self.agent_executor.invoke(
@@ -335,8 +336,7 @@ class Agent(BaseModel):
)
bind = self.llm.bind(stop=stop_words)
inner_agent = agent_args | execution_prompt | bind | CrewAgentParser(
agent=self)
inner_agent = agent_args | execution_prompt | bind | CrewAgentParser(agent=self)
self.agent_executor = CrewAgentExecutor(
agent=RunnableAgent(runnable=inner_agent), **executor_args
)
@@ -371,7 +371,7 @@ class Agent(BaseModel):
thoughts += action.log
thoughts += f"\n{observation_prefix}{observation}\n{llm_prefix}"
return thoughts
def copy(self):
"""Create a deep copy of the Agent."""
exclude = {
@@ -379,8 +379,8 @@ class Agent(BaseModel):
"_logger",
"_rpm_controller",
"_request_within_rpm_limit",
"_token_process",
"agent_executor",
"_token_process",
"agent_executor",
"tools",
"tools_handler",
"cache_handler",

77
src/crewai/crew.py
View File

@@ -279,28 +279,37 @@ class Crew(BaseModel):
f"The process '{self.process}' is not implemented yet."
)
print("FINISHED EXECUTION OF CREW", self.id)
print("GOING TO INVESTIGATE TOKEN USAGE")
for agent in self.agents:
print("ANALYZING AGENT", agent.id)
print("AGENT _token_process id: ", agent._token_process.id)
print("AGENT USAGE METRICS", agent._token_process.get_summary())
# TODO: THIS IS A BUG. ONLY THE LAST AGENT'S TOKEN USAGE IS BEING RETURNED
metrics = metrics + [
agent._token_process.get_summary() for agent in self.agents
]
print()
self.usage_metrics = {
key: sum([m[key] for m in metrics if m is not None]) for key in metrics[0]
}
return result
def kickoff_for_each(self, inputs: List[Dict[str, Any]]) -> List:
def kickoff_for_each(
self, inputs: List[Dict[str, Any]]
) -> List[Union[str, Dict[str, Any]]]:
"""Executes the Crew's workflow for each input in the list and aggregates results."""
results = []
for input_data in inputs:
crew = self.copy()
for task in crew.tasks:
task.interpolate_inputs(input_data)
for agent in crew.agents:
agent.interpolate_inputs(input_data)
output = crew.kickoff()
output = crew.kickoff(inputs=input_data)
# TODO: FIGURE OUT HOW TO MERGE THE USAGE METRICS
# TODO: I would expect we would want to merge the usage metrics from each crew execution
results.append(output)
return results
@@ -315,17 +324,15 @@ class Crew(BaseModel):
async def run_crew(input_data):
crew = self.copy()
for task in crew.tasks:
task.interpolate_inputs(input_data)
for agent in crew.agents:
agent.interpolate_inputs(input_data)
return await crew.kickoff_async()
return await crew.kickoff_async(inputs=input_data)
tasks = [asyncio.create_task(run_crew(input_data)) for input_data in inputs]
results = await asyncio.gather(*tasks)
# TODO: FIGURE OUT HOW TO MERGE THE USAGE METRICS
# TODO: I would expect we would want to merge the usage metrics from each crew execution
return results
def train(self, n_iterations: int) -> None:
@@ -335,6 +342,13 @@ class Crew(BaseModel):
def _run_sequential_process(self) -> Union[str, Dict[str, Any]]:
"""Executes tasks sequentially and returns the final output."""
task_output = ""
total_token_usage = {
"total_tokens": 0,
"prompt_tokens": 0,
"completion_tokens": 0,
"successful_requests": 0,
}
for task in self.tasks:
if task.agent.allow_delegation: # type: ignore # Item "None" of "Agent | None" has no attribute "allow_delegation"
agents_for_delegation = [
@@ -365,11 +379,19 @@ class Crew(BaseModel):
if self.output_log_file:
self._file_handler.log(agent=role, task=task_output, status="completed")
# Update token usage for the current task
current_token_usage = task.agent._token_process.get_summary()
for key in total_token_usage:
total_token_usage[key] += current_token_usage.get(key, 0)
print("Updated total_token_usage:", total_token_usage)
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 # Item "None" of "Agent | None" has no attribute "_token_process")
# type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
return self._format_output(task_output, token_usage)
# TODO: TEST AND FIX
return self._format_output(task_output, total_token_usage)
def _run_hierarchical_process(self) -> Union[str, Dict[str, Any]]:
"""Creates and assigns a manager agent to make sure the crew completes the tasks."""
@@ -415,9 +437,11 @@ 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(
task_output, manager_token_usage
), manager_token_usage
# TODO: TEST AND FIX
return (
self._format_output(task_output, manager_token_usage),
manager_token_usage,
)
def copy(self):
"""Create a deep copy of the Crew."""
@@ -432,12 +456,18 @@ class Crew(BaseModel):
"_short_term_memory",
"_long_term_memory",
"_entity_memory",
"_telemetry",
"agents",
"tasks",
}
print("CREW ID", self.id)
print("CURRENT IDS FOR AGENTS", [agent.id for agent in self.agents])
print("CURRENT IDS FOR TASKS", [task.id for task in self.tasks])
# TODO: I think there is a disconnect. We need to pass new agents and tasks to the new crew
cloned_agents = [agent.copy() for agent in self.agents]
cloned_tasks = [task.copy() for task in self.tasks]
cloned_tasks = [task.copy(cloned_agents) for task in self.tasks]
copied_data = self.model_dump(exclude=exclude)
copied_data = {k: v for k, v in copied_data.items() if v is not None}
@@ -447,6 +477,12 @@ class Crew(BaseModel):
copied_crew = Crew(**copied_data, agents=cloned_agents, tasks=cloned_tasks)
print("COPIED CREW ID", copied_crew.id)
print("NEW IDS FOR AGENTS", [agent.id for agent in copied_crew.agents])
print("NEW IDS FOR TASKS", [task.id for task in copied_crew.tasks])
# TODO: EXPERIMENT, PRINT ID'S AND MAKE SURE I'M CALLING THE RIGHT AGENTS AND TASKS
return copied_crew
def _set_tasks_callbacks(self) -> None:
@@ -475,6 +511,7 @@ class Crew(BaseModel):
If full_output is True, then returned data type will be a dictionary else returned outputs are string
"""
if self.full_output:
print("SPITTING OUT FULL OUTPUT FOR CREW", self.id)
return { # type: ignore # Incompatible return value type (got "dict[str, Sequence[str | TaskOutput | None]]", expected "str")
"final_output": output,
"tasks_outputs": [task.output for task in self.tasks if task],

31
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
@@ -192,13 +192,19 @@ class Task(BaseModel):
)
return result
def _execute(self, agent, task, context, tools):
def _execute(self, agent: Agent, task, context, tools):
result = agent.execute_task(
task=task,
context=context,
tools=tools,
)
print("CALLING EXECUTE ON TASK WITH ID", task.id)
print("THIS TASK IS CALLING AGENT", agent.id)
print(
"CALLING TOKEN PROCESS in task on AGENT", agent._token_process.get_summary()
)
exported_output = self._export_output(result)
self.output = TaskOutput(
@@ -246,7 +252,7 @@ class Task(BaseModel):
"""Increment the delegations counter."""
self.delegations += 1
def copy(self):
def copy(self, agents: Optional[List[Agent]] = None) -> "Task":
"""Create a deep copy of the Task."""
exclude = {
"id",
@@ -254,6 +260,7 @@ class Task(BaseModel):
"context",
"tools",
}
print("ORIGINAL TOOLS:", self.tools)
copied_data = self.model_dump(exclude=exclude)
copied_data = {k: v for k, v in copied_data.items() if v is not None}
@@ -261,8 +268,16 @@ class Task(BaseModel):
cloned_context = (
[task.copy() for task in self.context] if self.context else None
)
cloned_agent = self.agent.copy() if self.agent else None
cloned_tools = deepcopy(self.tools) if self.tools else None
# TODO: Make sure this clone approach is correct.
def get_agent_by_role(role: str) -> Agent | None:
return next((agent for agent in agents if agent.role == role), None)
cloned_agent = get_agent_by_role(self.agent.role) if self.agent else None
# cloned_agent = self.agent.copy() if self.agent else None
cloned_tools = deepcopy(self.tools) if self.tools else []
print("CLONED_TOOLS", cloned_tools)
copied_task = Task(
**copied_data,
@@ -270,6 +285,8 @@ class Task(BaseModel):
agent=cloned_agent,
tools=cloned_tools,
)
print("TASK TOOLS:", copied_task.tools)
return copied_task
def _export_output(self, result: str) -> Any:
@@ -328,7 +345,9 @@ 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.model_dump_json()
)
self._save_file(content)

3
src/crewai/utilities/token_counter_callback.py
View File

@@ -1,3 +1,4 @@
import uuid
from typing import Any, Dict, List
import tiktoken
@@ -6,6 +7,7 @@ from langchain.schema import LLMResult
class TokenProcess:
id = uuid.uuid4() # TODO: REMOVE THIS
total_tokens: int = 0
prompt_tokens: int = 0
completion_tokens: int = 0
@@ -32,6 +34,7 @@ class TokenProcess:
class TokenCalcHandler(BaseCallbackHandler):
id = uuid.uuid4() # TODO: REMOVE THIS
model: str = ""
token_cost_process: TokenProcess