Hello everyone,
I am new to the RASA Stack and have downloaded a GitHub project created by jackdh called RASA Talk, based on Rasa_nlu, React, and Mongodb.
Here’s the link to it:
https://github.com/jackdh/RasaTalk
After setting up my rasa_nlu file (based on the rasa starter pack), and connecting the NLU backend with the project, I was unable to train my model after adding intents, utterances, and entities.
The NLU server keeps throwing the following error every time I try to train a model:
" rasa_nlu.data_router - [Failure instance: Traceback (failure with no frames): <class ‘rasa_nlu.train.TrainingException’>: Can not train an empty pipeline. Make sure to specify a proper pipeline in the configuration using the pipeline key.The backend configuration key is NOT supported anymore. "
Thank you, I have done that. But I also wanted to know if anyone from the RASA community has encountered a similar empty pipeline error, just in case it could be insightful.
Hello @souvikg10
After communicating with the project’s creator, it appears that this is indeed a Rasa NLU problem:
This is what my http://localhost:5000/status shows :
{ "max_training_processes": 1, "current_training_processes": 0, "available_projects": { "default": { "status": "ready", "current_training_processes": 0, "available_models": [ "fallback" ], "loaded_models": [ "fallback" ] } } }
I guess the problem comes from it saying "available_models": [ "fallback" ]
What I’m using to start my NLU server are the commands:
Using a MakeFile, I start with make train-nlu which is
@souvikg10 thank you for your answer.
The path I give in the --path parameter is the same one I cd into when I start the server.
The models I try to train show up this way when I use curl localhost:5000/status | python -mjson.tool
"status": "failed",
"error_message": "[Failure instance: Traceback (failure with no frames): <class 'rasa_nlu.train.TrainingException'>: <TrainingException instance at 0x18a5bacc228 with str error:\n Traceback (most recent call last):\n File \"C:\\Users\\Asus\\Anaconda3\\envs\\py\\lib\\site-packages\\twisted\\python\\reflect.py\", line 448, in safe_str\n return str(o)\nTypeError: __str__ returned non-string (type int)\n>\n]",
"current_training_processes": 0,
"available_models": [
"fallback"
],
"loaded_models": [
"fallback"
]
}
I tried with both the tensorflow_embedding pipeline and the spacy-sklearn pipeline.