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Bugfix/kickoff for each usage metrics (#844)

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* WIP. Figuring out disconnect issue.

* Cleaned up logs now that I've isolated the issue to the LLM

* more wip.

* WIP. It looks like usage metrics has always been broken for async

* Update parent crew who is managing for_each loop

* Merge in main to bugfix/kickoff-for-each-usage-metrics

* Clean up code for review

* Add new tests

* Final cleanup. Ready for review.

* Moving copy functionality from Agent to BaseAgent

* Fix renaming issue

* Fix linting errors

* use BaseAgent instead of Agent where applicable
This commit is contained in:
Brandon Hancock (bhancock_ai)
2024-07-03 14:30:53 -04:00
committed by GitHub
parent 706f4cd74a
commit 57fc079267
11 changed files with 1761 additions and 307 deletions
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8
src/crewai/agent.py
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@@ -7,16 +7,15 @@ 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 crewai.agents import CacheHandler, CrewAgentExecutor, CrewAgentParser
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.memory.contextual.contextual_memory import ContextualMemory
from crewai.tools.agent_tools import AgentTools
from crewai.utilities import Prompts, Converter
from crewai.utilities import Converter, Prompts
from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
from crewai.utilities.token_counter_callback import TokenCalcHandler
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.utilities.training_handler import CrewTrainingHandler
agentops = None
@@ -91,7 +90,6 @@ class Agent(BaseAgent):
response_template: Optional[str] = Field(
default=None, description="Response format for the agent."
)
allow_code_execution: Optional[bool] = Field(
default=False, description="Enable code execution for the agent."
)
@@ -103,7 +101,7 @@ class Agent(BaseAgent):
@model_validator(mode="after")
def set_agent_executor(self) -> "Agent":
"""Ensure agent executor and token process is set."""
"""Ensure agent executor and token process are set."""
if hasattr(self.llm, "model_name"):
token_handler = TokenCalcHandler(self.llm.model_name, self._token_process)