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Code Issues Actions 4 Packages Projects Releases Wiki Activity

Adding proper support to memory-less agents

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This commit is contained in:
João Moura
2023-12-20 11:30:56 -03:00
parent 09812e4249
commit d43f2df4f0
5 changed files with 50 additions and 33 deletions
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46
crewai/agent.py
View File

@@ -1,7 +1,7 @@
"""Generic agent."""
from typing import List, Any, Optional
from pydantic.v1 import BaseModel, Field, root_validator
from pydantic.v1 import BaseModel, PrivateAttr, Field, root_validator
from langchain.agents import AgentExecutor
from langchain.chat_models import ChatOpenAI as OpenAI
@@ -35,6 +35,7 @@ class Agent(BaseModel):
description="Tools at agents disposal",
default=[]
)
_task_calls: List[Any] = PrivateAttr()
@root_validator(pre=True)
def check_llm(_cls, values):
@@ -47,39 +48,42 @@ class Agent(BaseModel):
def __init__(self, **data):
super().__init__(**data)
execution_prompt = Prompts.TASK_EXECUTION_PROMPT.partial(
goal=self.goal,
role=self.role,
backstory=self.backstory,
)
llm_with_bind = self.llm.bind(stop=["\nObservation"])
inner_agent = {
agent_args = {
"input": lambda x: x["input"],
"tools": lambda x: x["tools"],
"tool_names": lambda x: x["tool_names"],
"chat_history": lambda x: x["chat_history"],
"agent_scratchpad": lambda x: format_log_to_str(x['intermediate_steps']),
} | execution_prompt | llm_with_bind | ReActSingleInputOutputParser()
summary_memory = ConversationSummaryMemory(
llm=self.llm,
memory_key='chat_history',
input_key="input"
)
args = {
}
executor_args = {
"tools": self.tools,
"verbose": self.verbose,
"handle_parsing_errors": True,
}
llm_with_bind = self.llm.bind(stop=["\nObservation"])
if self.memory:
args['memory'] = summary_memory
summary_memory = ConversationSummaryMemory(
llm=self.llm,
memory_key='chat_history',
input_key="input"
)
executor_args['memory'] = summary_memory
agent_args['chat_history'] = lambda x: x["chat_history"]
prompt = Prompts.TASK_EXECUTION_WITH_MEMORY_PROMPT
else:
prompt = Prompts.TASK_EXECUTION_PROMPT
execution_prompt = prompt.partial(
goal=self.goal,
role=self.role,
backstory=self.backstory,
)
inner_agent = agent_args | execution_prompt | llm_with_bind | ReActSingleInputOutputParser()
self.agent_executor = AgentExecutor(
agent=inner_agent,
**args
**executor_args
)
def execute_task(self, task: str, context: str = None, tools: List[Any] = None) -> str:

6
crewai/prompts.py
View File

@@ -62,9 +62,13 @@ class Prompts(BaseModel):
{coworkers}
""")
TASK_EXECUTION_PROMPT: ClassVar[str] = PromptTemplate.from_template(
TASK_EXECUTION_WITH_MEMORY_PROMPT: ClassVar[str] = PromptTemplate.from_template(
ROLE_PLAYING_SLICE + TOOLS_SLICE + MEMORY_SLICE + TASK_SLICE
)
TASK_EXECUTION_PROMPT: ClassVar[str] = PromptTemplate.from_template(
ROLE_PLAYING_SLICE + TOOLS_SLICE + TASK_SLICE
)
CONSENSUNS_VOTING_PROMPT: ClassVar[str] = PromptTemplate.from_template(
ROLE_PLAYING_SLICE + VOTING_SLICE + TASK_SLICE