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- Correct asynchronous behavior in the EveAICrewAI classes.

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This commit is contained in:
Josako
2025-03-31 10:26:23 +02:00
parent d57bc5cf03
commit 1762b930bc
5 changed files with 49 additions and 67 deletions
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22
config/logging_config.py
View File

@@ -13,6 +13,26 @@ GRAYLOG_PORT = int(os.environ.get('GRAYLOG_PORT', 12201))
env = os.environ.get('FLASK_ENV', 'development')
def pad_string(s, target_length=100, pad_char='-'):
"""
Pads a string with the specified character until it reaches the target length.
Args:
s: The original string
target_length: The desired total length
pad_char: Character to use for padding
Returns:
The padded string
"""
current_length = len(s)
if current_length >= target_length:
return s
padding_needed = target_length - current_length - 1
return s + " " + (pad_char * padding_needed)
class TuningLogRecord(logging.LogRecord):
"""Extended LogRecord that handles both tuning and business event logging"""
@@ -153,7 +173,7 @@ class TuningLogger:
level=level,
pathname='',
lineno=0,
msg=message,
msg=pad_string(message, 100, '-'),
args=(),
exc_info=None
)

14
eveai_chat_workers/specialists/RAG_SPECIALIST/1_0.py
View File

@@ -139,16 +139,8 @@ class RAGFlow(EveAICrewAIFlow[RAGFlowState]):
self.exception_raised = True
raise e
async def execute_async(self, inputs=None):
async with current_event.create_span_async("RAG Specialist Execution"):
self.specialist_executor.log_tuning("Inputs retrieved", inputs)
async def kickoff_async(self, inputs=None):
current_app.logger.debug(f"Async kickoff {self.name}")
self.state.input = RAGSpecialistInput.model_validate(inputs)
self.specialist.update_progress("EveAI Flow Start", {"name": "RAG"})
try:
result = await super().kickoff_async()
except Exception as e:
current_app.logger.error(f"Error kicking of Flow: {str(e)}")
self.specialist.update_progress("EveAI Flow End", {"name": "RAG"})
result = await super().kickoff_async(inputs)
return self.state

18
eveai_chat_workers/specialists/SPIN_SPECIALIST/1_0.py
View File

@@ -64,7 +64,7 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
self._add_pydantic_output("rag_task", RAGOutput, "rag_output")
self._add_pydantic_output("spin_questions_task", SPINOutput, "spin_questions")
self._add_pydantic_output("identification_questions_task", LeadInfoOutput, "lead_identification_questions")
self._add_pydantic_output("rag_consolidation_task", RAGOutput, "rag_output")
self._add_pydantic_output("rag_consolidation_task", RAGOutput, "final_output")
def _instantiate_specialist(self):
verbose = self.tuning
@@ -275,7 +275,6 @@ class SPINFlow(EveAICrewAIFlow[SPINFlowState]):
additional_questions = self.state.lead_info.questions + "\n"
if self.state.spin:
additional_questions = additional_questions + self.state.spin.questions
current_app.logger.debug(f"Additional Questions: {additional_questions}")
inputs["additional_questions"] = additional_questions
try:
crew_output = await self.rag_consolidation_crew.kickoff_async(inputs=inputs)
@@ -291,19 +290,8 @@ class SPINFlow(EveAICrewAIFlow[SPINFlowState]):
self.exception_raised = True
raise e
async def execute_async(self, inputs=None):
async def kickoff_async(self, inputs=None):
current_app.logger.debug(f"Async kickoff {self.name}")
async with current_event.create_span_async("SPIN Specialist Execution"):
self.specialist_executor.log_tuning("Inputs retrieved", inputs)
self.state.input = SPINSpecialistInput.model_validate(inputs)
self.specialist.update_progress("EveAI Flow Start", {"name": "SPIN"})
try:
current_app.logger.debug(f"Async super kickoff {self.name}")
result = await super().kickoff_async()
current_app.logger.debug(f"Async super kickoff {self.name} ended")
except Exception as e:
current_app.logger.error(f"Error kicking of Flow: {str(e)}")
self.specialist.update_progress("EveAI Flow End", {"name": "SPIN"})
result = await super().kickoff_async(inputs)
return self.state

2
eveai_chat_workers/specialists/base_specialist.py
View File

@@ -20,7 +20,7 @@ class BaseSpecialistExecutor(ABC):
self.session_id = session_id
self.task_id = task_id
self.tuning = False
self.tuning_logger = None
self.tuning_logger: TuningLogger = None
self._setup_tuning_logger()
self.ept = ExecutionProgressTracker()

52
eveai_chat_workers/specialists/crewai_base_classes.py
View File

@@ -42,10 +42,7 @@ class EveAICrewAIAgent(Agent):
"""
current_app.logger.debug(f"Task Execution {task.name} by {self.name}")
# with current_event.create_span(f"Task Execution {task.name} by {self.name}"):
self.specialist.log_tuning("EveAI Agent Task Start",
{"name": self.name,
'task': task.name,
})
self.specialist.log_tuning(f"EveAI Agent {self.name}, Task {task.name} Start", {})
self.specialist.update_progress("EveAI Agent Task Start",
{"name": self.name,
'task': task.name,
@@ -53,17 +50,11 @@ class EveAICrewAIAgent(Agent):
result = super().execute_task(task, context, tools)
self.specialist.log_tuning("EveAI Agent Task Complete",
{"name": self.name,
'task': task.name,
'result': result,
})
self.specialist.log_tuning(f"EveAI Agent {self.name}, Task {task.name} Complete", {})
self.specialist.update_progress("EveAI Agent Task Complete",
{"name": self.name,
'task': task.name,
})
current_app.logger.debug(f"Task Execution Ended {task.name} by {self.name}")
return result
@@ -90,25 +81,6 @@ class EveAICrewAICrew(Crew):
self.specialist = specialist
self.name = name
def kickoff(
self,
inputs: Optional[Dict[str, Any]] = None,
) -> CrewOutput:
with current_event.create_span(f"Crew {self.name} kickoff"):
start_time = time.time()
results = super().kickoff(inputs)
end_time = time.time()
metrics = {
"total_tokens": self.usage_metrics.total_tokens,
"prompt_tokens": self.usage_metrics.prompt_tokens,
"completion_tokens": self.usage_metrics.completion_tokens,
"time_elapsed": end_time - start_time,
"interaction_type": "Crew Execution"
}
current_event.log_llm_metrics(metrics)
return results
async def kickoff_async(
self,
inputs: Optional[Dict[str, Any]] = None,
@@ -124,6 +96,7 @@ class EveAICrewAICrew(Crew):
"time_elapsed": end_time - start_time,
"interaction_type": "Crew Execution"
}
self.specialist.log_tuning(f"Crew {self.name} async metrics", metrics)
current_event.log_llm_metrics(metrics)
return results
@@ -141,12 +114,21 @@ class EveAICrewAIFlow(Flow):
self.specialist.log_tuning("Initializing EveAICrewAIFlow", {"name": self.name})
self.specialist.update_progress("EveAI Flow Initialisation", {"name": self.name})
def kickoff(self, inputs=None):
result = asyncio.run(self.execute_async(inputs=inputs))
async def kickoff_async(self, inputs=None) -> Any:
"""Properly override the library's async method"""
async with current_event.create_span_async(f"Flow {self.name} execution"):
self.specialist.log_tuning("Inputs retrieved", inputs)
self.specialist.update_progress("EveAI Flow Start", {"name": self.name})
@abstractmethod
async def execute_async(self, inputs=None):
raise NotImplementedError
try:
# Call parent's kickoff_async to handle start methods
result = await super().kickoff_async(inputs)
except Exception as e:
current_app.logger.error(f"Error in Flow kickoff_async: {str(e)}")
raise
self.specialist.update_progress("EveAI Flow End", {"name": self.name})
return self.state
class EveAIFlowState(BaseModel):