Rasa Core returning ERROR rasa.core.agent - Could not load model due to HTTP Error 403: Forbidden

Dear Team, I am trying to start working with Rasa with getting started example:

But I am getting the below error: Please help:

2022-09-28 11:54:56 INFO root - Starting Rasa server on http://localhost:5005 2022-09-28 11:54:57 INFO absl - Using /tmp/tfhub_modules to cache modules. 2022-09-28 11:54:57 INFO absl - Downloading TF-Hub Module ‘http://models.poly-ai.com/convert/v1/model.tar.gz’. 2022-09-28 11:54:57 INFO absl - Downloading TF-Hub Module ‘http://models.poly-ai.com/convert/v1/model.tar.gz’. 2022-09-28 11:54:58 INFO absl - Downloading TF-Hub Module ‘http://models.poly-ai.com/convert/v1/model.tar.gz’. 2022-09-28 11:54:59 INFO absl - Downloading TF-Hub Module ‘http://models.poly-ai.com/convert/v1/model.tar.gz’. 2022-09-28 11:54:59 ERROR rasa.core.agent - Could not load model due to HTTP Error 403: Forbidden. Bot loaded. Type a message and press enter (use ‘/stop’ to exit): Experienced exception while trying to serve Traceback (most recent call last): File “/home/ttllocadmin/venv/lib/python3.6/site-packages/rasa/utils/train_utils.py”, line 162, in load_tf_hub_model return tfhub.load(model_url) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/module_v2.py”, line 90, in load module_path = resolve(handle) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/module_v2.py”, line 52, in resolve return registry.resolver(handle) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/registry.py”, line 42, in call return impl(*args, **kwargs) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/compressed_module_resolver.py”, line 88, in call self._lock_file_timeout_sec()) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/resolver.py”, line 402, in atomic_download download_fn(handle, tmp_dir) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/compressed_module_resolver.py”, line 83, in download response = self._call_urlopen(request) File “/home/ttllocadmin/venv/lib/python3.6/site-packages/tensorflow_hub/compressed_module_resolver.py”, line 96, in _call_urlopen return url.urlopen(request) File “/usr/lib/python3.6/urllib/request.py”, line 223, in urlopen return opener.open(url, data, timeout) File “/usr/lib/python3.6/urllib/request.py”, line 532, in open response = meth(req, response) File “/usr/lib/python3.6/urllib/request.py”, line 642, in http_response ‘http’, request, response, code, msg, hdrs) File “/usr/lib/python3.6/urllib/request.py”, line 570, in error return self._call_chain(*args) File “/usr/lib/python3.6/urllib/request.py”, line 504, in _call_chain result = func(*args) File “/usr/lib/python3.6/urllib/request.py”, line 650, in http_error_default raise HTTPError(req.full_url, code, msg, hdrs, fp) urllib.error.HTTPError: HTTP Error 403: Forbidden

Please use markdown to format your log.

403 means you can’t access that endpoint. It has nothing to do with Rasa. You’ll see the same with curl:

curl http://models.poly-ai.com/convert/v1/model.tar.gz

Did you train that model file with rasa train?

Thanks Stephens. I did use the rasa train to generate the model. I will check for the HTTP connectivity.

This error code occurs when a user tries to access a web page or resource that they are not authorized to view. This error code is usually returned by a web server when it recognizes that the user does not have the necessary permissions to access the requested resource.

This error, HTTP error 403 - Forbidden, can occur for a variety of reasons, including incorrect login credentials, file permission issues, or security settings that prevent access to certain pages or directories. When a user encounters this error, they will typically be unable to access the resource they were trying to view and will need to contact the website administrator or IT department for assistance in resolving the issue.

If the request includes authentication credentials, but the server deems them inadequate to grant access, the client should not automatically resubmit the request with the same credentials. The client has the option to resubmit the request with new or different credentials. It is important to note that a request may be forbidden for reasons other than insufficient credentials.