Student Support Bot

A conversational AI , built using Rasa open source framework, with a purpose to solve educational queries.

Hers is a demo video ~ Video link

Create a virtual environment and install dependencies

python3 -m venv venv

source venv/bin/activate (Linux/UNIX)

venv\Scripts\activate (Windows)

pip install -r requirements.txt

Train model

python3 -m rasa train

Run rasa in terminal

python3 -m rasa shell

Train rasa with examples while running it on terminal

python3 -m rasa interactive

Run RASA on web (needs to be updated, use shell/interactive in the meantime)

Clone this repository and run the following command in the terminal -

rasa run actions

python3 -m rasa run --enable-api --cors="*"

Run the index.html file in Frontend-Widget.

How to add data to dataset

Add intent examples to data/nlu.yml

- intent: new_intent_name
  examples: |
    - some intent examples
    - make sure the examples help train the AI
    - and has all necessary keywords as well as variations of the keywords
    - minimum 5 examples are recommended
    - these examples all correspond to the same intent and will be mapped to a particular response so kindly do not club various examples together.

Add intent name and response to domain.yml

intents:
  - existing_intent_name
  - new_intent_name
  .
  .
  .
responses:
  utter_new_intent_name:
  - text: "The response to new_intent_name"
  - image: "https://image.com/image.png" # optional

Add rules to data/rules.yml to map the intent and response

- rule: Do action when asked about intent
  steps:
  - intent: new_intent_name
    action: utter_new_intent_name