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adding agent step callback

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This commit is contained in:
João Moura
2024-02-08 23:01:30 -08:00
parent ed0131b46f
commit c5839b215e
3 changed files with 13 additions and 5 deletions
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3
docs/core-concepts/Agents.md
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@@ -25,7 +25,7 @@ description: What are crewAI Agents and how to use them.
| **Max RPM** | The maximum number of requests per minute the agent can perform to avoid rate limits | | **Max RPM** | The maximum number of requests per minute the agent can perform to avoid rate limits |
| **Verbose** | This allow you to actually see what is going on during the Crew execution. | | **Verbose** | This allow you to actually see what is going on during the Crew execution. |
| **Allow Delegation** | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. | | **Allow Delegation** | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. |
| **Step Callback** | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. |
## Creating an Agent ## Creating an Agent
@@ -51,6 +51,7 @@ agent = Agent(
max_rpm=10, max_rpm=10,
verbose=True, verbose=True,
allow_delegation=True allow_delegation=True
step_callback=my_intermediate_step_callback
) )
``` ```

12
src/crewai/agent.py
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@@ -46,6 +46,7 @@ class Agent(BaseModel):
verbose: Whether the agent execution should be in verbose mode. verbose: Whether the agent execution should be in verbose mode.
allow_delegation: Whether the agent is allowed to delegate tasks to other agents. allow_delegation: Whether the agent is allowed to delegate tasks to other agents.
tools: Tools at agents disposal tools: Tools at agents disposal
step_callback: Callback to be executed after each step of the agent execution.
""" """
__hash__ = object.__hash__ # type: ignore __hash__ = object.__hash__ # type: ignore
@@ -90,6 +91,10 @@ class Agent(BaseModel):
cache_handler: InstanceOf[CacheHandler] = Field( cache_handler: InstanceOf[CacheHandler] = Field(
default=CacheHandler(), description="An instance of the CacheHandler class." default=CacheHandler(), description="An instance of the CacheHandler class."
) )
step_callback: Optional[Any] = Field(
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( llm: Any = Field(
default_factory=lambda: ChatOpenAI( default_factory=lambda: ChatOpenAI(
@@ -200,12 +205,13 @@ class Agent(BaseModel):
"verbose": self.verbose, "verbose": self.verbose,
"handle_parsing_errors": True, "handle_parsing_errors": True,
"max_iterations": self.max_iter, "max_iterations": self.max_iter,
"step_callback": self.step_callback,
} }
if self._rpm_controller: if self._rpm_controller:
executor_args["request_within_rpm_limit"] = ( executor_args[
self._rpm_controller.check_or_wait "request_within_rpm_limit"
) ] = self._rpm_controller.check_or_wait
if self.memory: if self.memory:
summary_memory = ConversationSummaryMemory( summary_memory = ConversationSummaryMemory(

3
src/crewai/agents/executor.py
View File

@@ -22,6 +22,7 @@ class CrewAgentExecutor(AgentExecutor):
request_within_rpm_limit: Any = None request_within_rpm_limit: Any = None
max_iterations: Optional[int] = 15 max_iterations: Optional[int] = 15
force_answer_max_iterations: Optional[int] = None force_answer_max_iterations: Optional[int] = None
step_callback: Optional[Any] = None
@root_validator() @root_validator()
def set_force_answer_max_iterations(cls, values: Dict) -> Dict: def set_force_answer_max_iterations(cls, values: Dict) -> Dict:
@@ -67,7 +68,7 @@ class CrewAgentExecutor(AgentExecutor):
return self._return( return self._return(
next_step_output, intermediate_steps, run_manager=run_manager next_step_output, intermediate_steps, run_manager=run_manager
) )
self.step_callback(next_step_output)
intermediate_steps.extend(next_step_output) intermediate_steps.extend(next_step_output)
if len(next_step_output) == 1: if len(next_step_output) == 1:
next_step_action = next_step_output[0] next_step_action = next_step_output[0]