async def update_training_data_generator_status(
request_data: TrainingDataGeneratorStatusModel,
current_user: User = Depends(auth.get_current_user)):
"""
Update training data generator status
"""
try:
TrainingDataGenerationProcessor.retreive_response_and_set_status(
request_data, current_user.get_bot(), current_user.get_user())
except Exception as e:
raise AppException(e)
return {"message": "Status updated successfully!"}
async def get_latest_data_generation_status(
current_user: User = Depends(auth.get_current_user), ):
"""
Fetches status for latest data generation request
"""
latest_data_generation_status = TrainingDataGenerationProcessor.fetch_latest_workload(
current_user.get_bot(), current_user.get_user())
return {"data": latest_data_generation_status}
async def get_trainData_history(
current_user: User = Depends(auth.get_current_user), ):
"""
Fetches File Data Generation history, when and who initiated the process
"""
file_history = TrainingDataGenerationProcessor.get_training_data_generator_history(
current_user.get_bot())
return {"data": {"training_history": file_history}}
async def add_training_data(request_data: BulkTrainingDataAddRequest,
current_user: User = Depends(
auth.get_current_user)):
"""
Adds intents, training examples and responses along with story against the responses
"""
try:
status, training_data_added = mongo_processor.add_training_data(
training_data=request_data.training_data,
bot=current_user.get_bot(),
user=current_user.get_user(),
is_integration=current_user.get_integration_status())
TrainingDataGenerationProcessor.update_is_persisted_flag(
request_data.history_id, training_data_added)
except Exception as e:
raise AppException(e)
return {"message": "Training data added successfully!", "data": status}
async def upload_file(background_tasks: BackgroundTasks,
doc: UploadFile = File(...),
current_user: User = Depends(auth.get_current_user)):
"""
Uploads document for training data generation and triggers event for intent creation
"""
TrainingDataGenerationProcessor.is_in_progress(current_user.get_bot())
TrainingDataGenerationProcessor.check_data_generation_limit(
current_user.get_bot())
file_path = await Utility.upload_document(doc)
TrainingDataGenerationProcessor.set_status(
bot=current_user.get_bot(),
user=current_user.get_user(),
status=TRAINING_DATA_GENERATOR_STATUS.INITIATED.value,
document_path=file_path)
token = auth.create_access_token(data={"sub": current_user.email})
background_tasks.add_task(Utility.trigger_data_generation_event,
current_user.get_bot(), current_user.get_user(),
token.decode('utf8'))
return {
"message":
"File uploaded successfully and training data generation has begun"
}
