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weatherbot's Introduction

AI Weather Bot using RASA Framework

Weather Client

You will need an API Key from https://weatherstack.com/
You may sign up for a free account to access this weather api 
afterwards just add your API key to the actions.py file

 
http://api.weatherstack.com/current
    ? access_key = YOUR_ACCESS_KEY
    & query = New York

Environment

To get started add a virtual python environment

$ python3 -m venv --system-site-packages ./venv

Activate your venv environment

$ source ./venv/bin/activate

Dependencies

$ pip3 install rasa[spacy]
$ python3 -m spacy download en_core_web_md
$ python3 -m spacy link en_core_web_md en
$ pip3 install -r requirements

Now you've installed the Rasa Framework and Spacy language model library you can import the module directly in python scripts -- import spacy('en')

Start Actions Server

$ rasa run actions

Install Interactive NLU Trainer & launch trainer

 $ npm i -g rasa-nlu-trainer
 $ rasa-nlu-trainer

Request Predictions from NLU Server

$ curl localhost:5005/model/parse -d '{"text":"hello"}'

Install Rasa NLU

$ pip3 install rasa_nlu

Install RASA X

$ pip3 install rasa-x --extra-index-url https://pypi.rasa.com/simpleras

Steps when creating and training your AI assistant

1. View Your NLU Training Data
2. Define Your Model Configuration
3. Write Your Stories
4. Define a Domain
5. Train a Model
6. Talk to Your Assistant

weatherbot's People

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