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A chatbot developed using Flask, Rasa NLU and Spacy
This project forked from lkamat/startbot
A chatbot developed using Flask, Rasa NLU and Spacy
Create a chatbot with Flask, Python and Rasa NLU using supervised training Backend: step1) Startup csv data file from Kaggle step2) Use Jupyter notebook for data analysis step3) Create training data json file using rasa nlu trainer: https://rasahq.github.io/rasa-nlu-trainer/ step4) mkdir startbot step5) mkdir startbot/data to store the startup data json file data files : data/startup-data.json step6) Cretae a config file that uses spacy for NLP, model directory to store the trained model config.json step7) Train the chatbot using rasa_nlu and config by running the following command python -m rasa_nlu.train -c config.json This will create a model in the directory specified (models) in the config files with the timestamp step8) Set up http server to run with the config file and latest model python -m rasa_nlu.server -c config.json step9) To setup the knowledge base for the startbot create a knowledge file with responses using python dictionary. knowledge.py Frontend: Flask application Step1) Create templates folder and the following templates: layout.html, index.html Step2) Create static folder and css and js sub folders: css/chat-interface.css, js/bind.js Step3) Use bootstrap, googlefontapi Step4) Create app.py : main flask application python app.py to begin
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