---
title: "rasa chatbot"
emoji: "❤️"
colorFrom: "red"
colorTo: "yellow"
sdk: "docker"
sdk_version: "2.0"
app_file: app.py
app_port: 5005
pinned: false
---

# Sample chatbot with rasa stack

It uses the rasa stack (rasa core/nlu/actions) to implement a simple bot which responds user messages.

## Run on local machine

#### Using docker
Both action server and rasa-core runs as separate processes in the same container. Rename the .env-sample to .env and optionally update the API_KEYs, TOKENs etc.
```
docker build -t rasa-chatbot .
docker run -it --rm -p 5005:5005 --env-file $(pwd)/.env rasa-chatbot
```
It starts a webserver with rest api and listens for messages at localhost:5005

#### Test over REST api

```bash
curl --request POST \
  --url http://localhost:5005/webhooks/rest/webhook \
  --header 'content-type: application/json' \
  --data '{
    "message": "Hi"
  }'
```
**Response**
```http
HTTP/1.1 200 OK
Content-Type: application/json
Content-Length: 59
Access-Control-Allow-Origin: *

[{
  "recipient_id": "default",
  "text": "Hi, how is it going?"
}]
```

## Try the bot using in terminal
```bash
docker run --rm --volume $(pwd):/app --env-file $(pwd)/.env -it\
          --workdir /app rasa-chatbot bash ./scripts/start_shell.sh
```

## Run using docker compose
Optionally to run the actions server in separate container start the services using docker-compose. The action server runs on http://action_server:5055/webhook (docker's internal network). The rasa-core services uses the config/endpoints.local.yml to find this actions server

```
docker-compose up
```
#### Train Rasa model
The repository already contains a trained Rasa model at models directory. To retrain the model you can run:
```bash
docker run --rm --volume $(pwd):/app \
          --workdir /app rasa/rasa \
          train --fixed-model-name rasa-model \
          --config config.yml
```

## Deploy to Heroku
On heroku free tier we can start two containers using two dynos, but there isn't a way for the containers to communicate with each other on Heroku. So, we push everything (actions server/rasa core/nlu) in the same container.

```bash
heroku container:push -a rasa-chatbot web
heroku container:release -a rasa-chatbot web
```

Another option would be to create a separate app altogether for actions server (nlu server can also be run as a separate app), which then can communicate with each other over http.

## Integration with Facebook
rasa supports integration with multiple channels. Apart from exposing the REST api over http, we can integrate with facebook. 

Go to https://developers.facebook.com and creat an app. We can handle messages sent to a facebook page from our app. To do so add messenger to the facebook app and subscribe to a page. Update app secret and page token in config/credentials.yml. On the facebook app, update the webhook url to the deployed heroku app (https://rasa-chatbot.herokuapp.com/webhooks/facebook/webhook).