A Telegram conversational chatbot using node-nlp, Telegraf and MongoDb with a Spanish corpus.
When the app starts up, it will load the corpus from corpus-es.json (mind that the provided corpus is in Spanish;
node-nlp is also configured to work with Spanish as language). It will trigger the node-nlp training
algorithm (notice pipelines.md).
To provide an authorization mechanism, this app will check that the startPayload value matches the one provided in
the env var UNIQUE_CODE. This means the bot will interact with the user only if he/she initiated the conversation with
the bot though a link with such parameter:
https://telegram.me/<you_bot_username>?start=<UNIQUE_CODE>
To validate further conversations, the app will store the content of the ctx.update.message.chat object provided by
the Telegraf API:
{
"id": 45930123,
"first_name": "John",
"last_name": "Doe",
"type": "private"
}On every message, the app will store information that can be used for further training:
{
"id": 45930123,
"message": "what's your name",
"firstName": "John",
"lastName": "Doe",
"utterance": "what's your name",
"intent": "agent.name",
"score": 1,
"answer": "I don't have one yet"
}To run this app, you will need to provide the following env vars
BOT_TOKEN=token generated by BotFather
UNIQUE_CODE=randomly generate code to check on /start and authorize chat id
MONGODB_CONNECTION_STRING=connection string of your mongo instace
DATABASE_NAME=name of the database to store the results of the prediction
Optionally, you may use
WELCOME_MESSAGE=message the bot will send on /start
UNATHORIZE_MESSAGE=message the bot will send if startPayload does not match UNIQUE_CODE
MIN_SCORE=minimum value for the prediction score of node-nlp
"@nlpjs/basic": "^4.23.4",
"@nlpjs/lang-es": "^4.23.4",
"mongodb": "^4.4.1",
"telegraf": "^4.7.0"
"dotenv": "^16.0.0",
"eslint": "^8.12.0",
"eslint-config-airbnb-base": "^15.0.0",
"eslint-plugin-import": "^2.25.4",
"nodemon": "^2.0.15"