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Code Issues Actions 4 Packages Projects Releases Wiki Activity

Removing LangChain and Rebuilding Executor (#1322)

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* rebuilding executor

* removing langchain

* Making all tests good

* fixing types and adding ability for nor using system prompts

* improving types

* pleasing the types gods

* pleasing the types gods

* fixing parser, tools and executor

* making sure all tests pass

* final pass

* fixing type

* Updating Docs

* preparing to cut new version
This commit is contained in:
João Moura
2024-09-16 14:14:04 -03:00
committed by GitHub
parent 322780a5f3
commit e77442cf34
177 changed files with 27272 additions and 1618561 deletions
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26
src/crewai/crew.py
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@@ -6,7 +6,6 @@ from concurrent.futures import Future
from hashlib import md5
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
from langchain_core.callbacks import BaseCallbackHandler
from pydantic import (
UUID4,
BaseModel,
@@ -68,7 +67,6 @@ class Crew(BaseModel):
manager_llm: The language model that will run manager agent.
manager_agent: Custom agent that will be used as manager.
memory: Whether the crew should use memory to store memories of it's execution.
manager_callbacks: The callback handlers to be executed by the manager agent when hierarchical process is used
cache: Whether the crew should use a cache to store the results of the tools execution.
function_calling_llm: The language model that will run the tool calling for all the agents.
process: The process flow that the crew will follow (e.g., sequential, hierarchical).
@@ -126,10 +124,6 @@ class Crew(BaseModel):
manager_agent: Optional[BaseAgent] = Field(
description="Custom agent that will be used as manager.", default=None
)
manager_callbacks: Optional[List[InstanceOf[BaseCallbackHandler]]] = Field(
default=None,
description="A list of callback handlers to be executed by the manager agent when hierarchical process is used",
)
function_calling_llm: Optional[Any] = Field(
description="Language model that will run the agent.", default=None
)
@@ -205,6 +199,12 @@ class Crew(BaseModel):
if self.output_log_file:
self._file_handler = FileHandler(self.output_log_file)
self._rpm_controller = RPMController(max_rpm=self.max_rpm, logger=self._logger)
self.function_calling_llm = (
self.function_calling_llm.model_name
if self.function_calling_llm is not None
and hasattr(self.function_calling_llm, "model_name")
else self.function_calling_llm
)
self._telemetry = Telemetry()
self._telemetry.set_tracer()
return self
@@ -588,8 +588,14 @@ class Crew(BaseModel):
"warning", "Manager agent should not have tools", color="orange"
)
manager.tools = []
raise Exception("Manager agent should not have tools")
manager.tools = self.manager_agent.get_delegation_tools(self.agents)
else:
self.manager_llm = (
self.manager_llm.model_name
if hasattr(self.manager_llm, "model_name")
else self.manager_llm
)
manager = Agent(
role=i18n.retrieve("hierarchical_manager_agent", "role"),
goal=i18n.retrieve("hierarchical_manager_agent", "goal"),
@@ -743,9 +749,6 @@ class Crew(BaseModel):
task.tools.append(new_tool)
def _log_task_start(self, task: Task, role: str = "None"):
color = self._logging_color
self._logger.log("debug", f"== Working Agent: {role}", color=color)
self._logger.log("info", f"== Starting Task: {task.description}", color=color)
if self.output_log_file:
self._file_handler.log(agent=role, task=task.description, status="started")
@@ -768,7 +771,6 @@ class Crew(BaseModel):
def _process_task_result(self, task: Task, output: TaskOutput) -> None:
role = task.agent.role if task.agent is not None else "None"
self._logger.log("debug", f"== [{role}] Task output: {output}\n\n")
if self.output_log_file:
self._file_handler.log(agent=role, task=output, status="completed")
@@ -921,16 +923,14 @@ class Crew(BaseModel):
def calculate_usage_metrics(self) -> UsageMetrics:
"""Calculates and returns the usage metrics."""
total_usage_metrics = UsageMetrics()
for agent in self.agents:
if hasattr(agent, "_token_process"):
token_sum = agent._token_process.get_summary()
total_usage_metrics.add_usage_metrics(token_sum)
if self.manager_agent and hasattr(self.manager_agent, "_token_process"):
token_sum = self.manager_agent._token_process.get_summary()
total_usage_metrics.add_usage_metrics(token_sum)
self.usage_metrics = total_usage_metrics
return total_usage_metrics
def test(