mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-10 08:38:30 +00:00
Lorenzejay/byoa (#776)
* better spacing * works with llama index * works on langchain custom just need delegation to work * cleanup for custom_agent class * works with different argument expectations for agent_executor * cleanup for hierarchial process, better agent_executor args handler and added to the crew agent doc page * removed code examples for langchain + llama index, added to docs instead * added key output if return is not a str for and added some tests * added hinting for CustomAgent class * removed pass as it was not needed * closer just need to figuire ou agentTools * running agents - llamaindex and langchain with base agent * some cleanup on baseAgent * minimum for agent to run for base class and ensure it works with hierarchical process * cleanup for original agent to take on BaseAgent class * Agent takes on langchainagent and cleanup across * token handling working for usage_metrics to continue working * installed llama-index, updated docs and added better name * fixed some type errors * base agent holds token_process * heirarchail process uses proper tools and no longer relies on hasattr for token_processes * removal of test_custom_agent_executions * this fixes copying agents * leveraging an executor class for trigger llamaindex agent * llama index now has ask_human * executor mixins added * added output converter base class * type listed * cleanup for output conversions and tokenprocess eliminated redundancy * properly handling tokens * simplified token calc handling * original agent with base agent builder structure setup * better docs * no more llama-index dep * cleaner docs * test fixes * poetry reverts and better docs * base_agent_tools set for third party agents * updated task and test fix
This commit is contained in:
Lorenze Jay
@@ -1,106 +1,25 @@
|
||||
from typing import List, Union
|
||||
|
||||
from langchain.tools import StructuredTool
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from crewai.agent import Agent
|
||||
from crewai.task import Task
|
||||
from crewai.utilities import I18N
|
||||
from crewai.agents.agent_builder.utilities.base_agent_tool import BaseAgentTools
|
||||
|
||||
|
||||
class AgentTools(BaseModel):
|
||||
class AgentTools(BaseAgentTools):
|
||||
"""Default tools around agent delegation"""
|
||||
|
||||
agents: List[Agent] = Field(description="List of agents in this crew.")
|
||||
i18n: I18N = Field(default=I18N(), description="Internationalization settings.")
|
||||
|
||||
def tools(self):
|
||||
coworkers = f"[{', '.join([f'{agent.role}' for agent in self.agents])}]"
|
||||
tools = [
|
||||
StructuredTool.from_function(
|
||||
func=self.delegate_work,
|
||||
name="Delegate work to coworker",
|
||||
description=self.i18n.tools("delegate_work").format(
|
||||
coworkers=f"[{', '.join([f'{agent.role}' for agent in self.agents])}]"
|
||||
coworkers=coworkers
|
||||
),
|
||||
),
|
||||
StructuredTool.from_function(
|
||||
func=self.ask_question,
|
||||
name="Ask question to coworker",
|
||||
description=self.i18n.tools("ask_question").format(
|
||||
coworkers=f"[{', '.join([f'{agent.role}' for agent in self.agents])}]"
|
||||
),
|
||||
description=self.i18n.tools("ask_question").format(coworkers=coworkers),
|
||||
),
|
||||
]
|
||||
return tools
|
||||
|
||||
def delegate_work(
|
||||
self,
|
||||
task: str,
|
||||
context: Union[str, None] = None,
|
||||
coworker: Union[str, None] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Useful to delegate a specific task to a coworker passing all necessary context and names."""
|
||||
coworker = coworker or kwargs.get("co_worker") or kwargs.get("coworker")
|
||||
if coworker:
|
||||
is_list = coworker.startswith("[") and coworker.endswith("]")
|
||||
if is_list:
|
||||
coworker = coworker[1:-1].split(",")[0]
|
||||
return self._execute(coworker, task, context)
|
||||
|
||||
def ask_question(
|
||||
self,
|
||||
question: str,
|
||||
context: Union[str, None] = None,
|
||||
coworker: Union[str, None] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Useful to ask a question, opinion or take from a coworker passing all necessary context and names."""
|
||||
coworker = coworker or kwargs.get("co_worker") or kwargs.get("coworker")
|
||||
if coworker:
|
||||
is_list = coworker.startswith("[") and coworker.endswith("]")
|
||||
if is_list:
|
||||
coworker = coworker[1:-1].split(",")[0]
|
||||
return self._execute(coworker, question, context)
|
||||
|
||||
def _execute(self, agent: Union[str, None], task: str, context: Union[str, None]):
|
||||
"""Execute the command."""
|
||||
try:
|
||||
if agent is None:
|
||||
agent = ""
|
||||
|
||||
# It is important to remove the quotes from the agent name.
|
||||
# The reason we have to do this is because less-powerful LLM's
|
||||
# have difficulty producing valid JSON.
|
||||
# As a result, we end up with invalid JSON that is truncated like this:
|
||||
# {"task": "....", "coworker": "....
|
||||
# when it should look like this:
|
||||
# {"task": "....", "coworker": "...."}
|
||||
agent_name = agent.casefold().replace('"', "").replace("\n", "")
|
||||
|
||||
agent = [
|
||||
available_agent
|
||||
for available_agent in self.agents
|
||||
if available_agent.role.casefold().replace("\n", "") == agent_name
|
||||
]
|
||||
except Exception as _:
|
||||
return self.i18n.errors("agent_tool_unexsiting_coworker").format(
|
||||
coworkers="\n".join(
|
||||
[f"- {agent.role.casefold()}" for agent in self.agents]
|
||||
)
|
||||
)
|
||||
|
||||
if not agent:
|
||||
return self.i18n.errors("agent_tool_unexsiting_coworker").format(
|
||||
coworkers="\n".join(
|
||||
[f"- {agent.role.casefold()}" for agent in self.agents]
|
||||
)
|
||||
)
|
||||
|
||||
agent = agent[0]
|
||||
task = Task(
|
||||
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)
|
||||
|
||||
Reference in New Issue
Block a user