Unable to fix the code issue on bot

Can you please help me, I was creating simple chatbot and the first one, every time I run bot, it response with the code

Your Rasa model is trained and saved at ‘models\nlu-20220926-010035-planar-bold.tar.gz’.

(install_rasa) C:\Users\palak\Documents\Smith School of Business\MMAI_891_Natural_Language_Processing\Chatbots\Rasa\RockPaperSissors>rasa shell

C:\Users\palak\anaconda3\envs\install_rasa\lib\site-packages\matplotlib_init_.py:169: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. if LooseVersion(module.version) < minver: C:\Users\palak\anaconda3\envs\install_rasa\lib\site-packages\setuptools_distutils\version.py:346: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. other = LooseVersion(other) C:\Users\palak\anaconda3\envs\install_rasa\lib\site-packages\tensorflow_addons\utils\ensure_tf_install.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. min_version = LooseVersion(INCLUSIVE_MIN_TF_VERSION) 2022-09-26 01:21:04 INFO rasa.core.processor - Loading model models\nlu-20220926-010035-planar-bold.tar.gz…

NLU model loaded. Type a message and press enter to parse it.

Next message:

hi { “text”: “hi”, “intent”: { “name”: “greet”, “confidence”: 0.9999998807907104 }, “entities”: [], “text_tokens”: [ [ 0, 2 ] ], “intent_ranking”: [ { “name”: “greet”, “confidence”: 0.9999998807907104 }, { “name”: “bot_challenge”, “confidence”: 5.1636668274568365e-08 }, { “name”: “goodbye”, “confidence”: 1.9684824437149473e-08 }, { “name”: “deny”, “confidence”: 4.737541470234419e-09 }, { “name”: “affirm”, “confidence”: 4.385037666310154e-09 }, { “name”: “inform”, “confidence”: 3.7210217129768353e-09 } ], “response_selector”: { “all_retrieval_intents”: [], “default”: { “response”: { “responses”: null, “confidence”: 0.0, “intent_response_key”: null, “utter_action”: “utter_None” }, “ranking”: [] } } } Next message:

Your core model is not being trained.

Run,

rasa data validate

to check for validation of the files. If there are errors, fix those errors and then run

rasa train

rasa shell