Hi I linked my Rasa X instance (deployed on GCP) with my GitHub repo but my data is not automatically imported to Rasa X. Is there anything I should do or is this an abnormal behaviour ? If so how can I fix the problem Thanks
Hi there, is there an error in your rasa X container/pod when you try to connect the repo? Thats definitely abnormal behavior.
Do you by chance have a github workflows file that has variables defined like ${{ this }} ? I know there is an existing bug with 0.39 and these variables that should be fixed in an upcoming patch.
I use the quick install method to install Rasa X so I didn’t have such files
right now I just restarted the installation using the Docker Compose Installation method and some of my data (nlu, stories, domain, config) came properly in Rasa X after I linked to my repo. but neither the response data nor the models are pulled I don’t understand why.
I uploaded my model manually but when I chat with the bot it does not output any responses, guess it’s because the response data are missing.
The models will not get pulled in, as its not how the feature is designed (it’s not typically recommended to store models in git)
The responses not coming in sounds strange, can you post your domain or responses file? And any errors shown in the rasa x container?
Hi I placed my response files in the root directory and they are now pulled. but my NLU data files are not pulled anymore. here is my domain file domain.yml (4.8 KB)
my logs below
2021-04-30 13:31:56.956011: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library ‘libcudart.so.10.1’; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory 2021-04-30 13:31:56.956352: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine. 2021-04-30 13:32:06.632548: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library ‘libcuda.so.1’; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory 2021-04-30 13:32:06.632608: W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303) 2021-04-30 13:32:06.632645: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (402fd8d3230b): /proc/driver/nvidia/version does not exist /opt/venv/lib/python3.8/site-packages/tzlocal/unix.py:158: UserWarning: Can not find any timezone configuration, defaulting to UTC. warnings.warn(‘Can not find any timezone configuration, defaulting to UTC.’) 2021-04-30 14:15:41 ERROR rasa.core.agent - Failed to update model. The previous model will stay loaded instead. Traceback (most recent call last): File “/opt/venv/lib/python3.8/site-packages/transformers/tokenization_utils.py”, line 981, in _from_pretrained resolved_vocab_files[file_id] = cached_path( File “/opt/venv/lib/python3.8/site-packages/transformers/file_utils.py”, line 253, in cached_path output_path = get_from_cache( File “/opt/venv/lib/python3.8/site-packages/transformers/file_utils.py”, line 362, in get_from_cache os.makedirs(cache_dir, exist_ok=True) File “/usr/lib/python3.8/os.py”, line 213, in makedirs makedirs(head, exist_ok=exist_ok) File “/usr/lib/python3.8/os.py”, line 213, in makedirs makedirs(head, exist_ok=exist_ok) File “/usr/lib/python3.8/os.py”, line 223, in makedirs mkdir(name, mode) PermissionError: [Errno 13] Permission denied: ‘/.cache’
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File “/opt/venv/lib/python3.8/site-packages/rasa/core/agent.py”, line 160, in _update_model_from_server _load_and_set_updated_model(agent, model_directory, new_fingerprint) File “/opt/venv/lib/python3.8/site-packages/rasa/core/agent.py”, line 133, in _load_and_set_updated_model interpreter = _load_interpreter(agent, nlu_path) File “/opt/venv/lib/python3.8/site-packages/rasa/core/agent.py”, line 92, in _load_interpreter return rasa.core.interpreter.create_interpreter(nlu_path) File “/opt/venv/lib/python3.8/site-packages/rasa/core/interpreter.py”, line 33, in create_interpreter return RasaNLUInterpreter(model_directory=obj) File “/opt/venv/lib/python3.8/site-packages/rasa/core/interpreter.py”, line 127, in init self._load_interpreter() File “/opt/venv/lib/python3.8/site-packages/rasa/core/interpreter.py”, line 165, in _load_interpreter self.interpreter = Interpreter.load(self.model_directory) File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/model.py”, line 330, in load return Interpreter.create( File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/model.py”, line 401, in create component = component_builder.load_component( File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/components.py”, line 823, in load_component component = registry.load_component_by_meta( File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/registry.py”, line 177, in load_component_by_meta return component_class.load( File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/components.py”, line 512, in load return cls(meta) File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/utils/hugging_face/hf_transformers.py”, line 65, in init self._load_model_instance(skip_model_load) File “/opt/venv/lib/python3.8/site-packages/rasa/nlu/utils/hugging_face/hf_transformers.py”, line 121, in _load_model_instance self.tokenizer = model_tokenizer_dict[self.model_name].from_pretrained( File “/opt/venv/lib/python3.8/site-packages/transformers/tokenization_utils.py”, line 911, in from_pretrained return cls._from_pretrained(*inputs, **kwargs) File “/opt/venv/lib/python3.8/site-packages/transformers/tokenization_utils.py”, line 1004, in _from_pretrained raise EnvironmentError(msg) OSError: Model name ‘rasa/LaBSE’ was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed ‘rasa/LaBSE’ was a path or url to a directory containing vocabulary files named [‘vocab.txt’], but couldn’t find such vocabulary files at this path or url.