# rasa-kick-starter

**Repository Path**: mirrors_RocketChat/rasa-kick-starter

## Basic Information

- **Project Name**: rasa-kick-starter
- **Description**: Rocket.Chat connector kick starter for Rasa.AI
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-25
- **Last Updated**: 2026-02-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# rasa-rocketchat-kickstarter

A simple bot to test the integration with Rocket.Chat.

## Quickstart

### 1. Install Rocket.Chat

If you already have a Rocket.Chat instance you can skip this step

```sh
docker-compose up -d mongo
docker-compose up -d mongo-init-replica
docker-compose up -d rocketchat
```
Access http://localhost:3000/ 

Create an `admin` user with the password `admin`.

### 2. Rocket.Chat Bot User Configurations

Create a Rasa bot user in Rocket.Chat. You can either manually login to Rocket.Chat and create a bot user via the 
user management page or can use the following script to create the bot user.

Run the following command to create the RASA bot.

**Note:** Please replace the user name and password of the RocketChat admin and bot user accordingly. 
```sh
python3 scripts/bot_config.py -an admin_username -ap admin_password -bn bot_username -bp bot_pass -r http://rocketchaturl
```

If you are using docker-compose following is a sample usage

```sh
python3 scripts/bot_config.py -an admin -ap admin -bn bot_rasa -bp bot_rasa -r http://localhost:3000
```

### 3. Configure Rasa Bot

* Configure the Credentials file

    Update your `credentials.yml` file inside the `bot_rasa` folder with Rasa bot's username and password.
    ```sh
    rocketchat:
      user: "bot_rasa"
      password: "bot_rasa"
      server_url: "http://localhost:3000"
    ```

* Train the Machine Learning Model
    The Rasa bots machine learning model can built by using either Rasa CLI or Docker. After the training a machine 
    learning model will be created inside the `bot_rasa/models` folder.
    
    * **If using Docker**
        
        ```sh
        docker run -it -v $(pwd)/bot_rasa:/app rasa/rasa train
        ```
    
    * **If using Rasa CLI**
    
        ```bash
        pip3 install rasa
        cd bot_rasa
        rasa train
        ``` 
    
### 4. Start Rasa server

Rasa bot can be started via the Docker or Rasa CLI. 

* **If using Docker-compose**

    ```sh
    docker-compose up -d bot_rasa
    ```

* **If using Rasa CLI**

    ```python
    cd bot_rasa
    rasa run
    ```

#### 5. Make Rasa Bot accessible by Rocket.Chat

The Rasa bot should be reachable via Rocket.Chat.

*  If you are following the tutorial with docker-compose file then following is the URL to access the Rasa bot.
    ```bash
    http://bot_rasa:5005
    ```
    

* If you are trying to connect to a standalone Rocker.Chat instance or using Rasa CLI, lets user ngrok to get a 
public url for the Rasa Bot.

    Install ngrok via: https://ngrok.com/download

    After downloading the ngrok navigate to the ngrok file in the downloded content and execute the following command. 
    This will provide a public URL to the Rasa bot

    ```bash
    ./ngork http 5005
    ```
    
    Following will be the output of ngrok
    ```sh                                                                                                                                                                                                      
    Session Status                online                                                                                                                                                                        
    Session Expires               7 hours, 59 minutes                                                                                                                                                           
    Version                       2.3.30                                                                                                                                                                        
    Region                        United States (us)                                                                                                                                                            
    Web Interface                 http://127.0.0.1:4040                                                                                                                                                         
    Forwarding                    http://e3d5a17b.ngrok.io -> http://localhost:5005                                                                                                                             
    Forwarding                    https://e3d5a17b.ngrok.io -> http://localhost:5005  
    ```
    Copy the http URL provided by ngrok: `http://e3d5a17b.ngrok.io`

### 6. Configure Rocket.Chat webhook

Go to **Administration > New Integration > Outgoing webhook**.
Inside the configuration insert this:

```
Event Trigger: Message Sent
Enabled: True
Channel: #general
URLs: http://bot_rasa:5005/webhooks/rocketchat/webhook
Post as: bot_rasa
```

If you are using ngrok then replace the URL `http://bot:5005`, with the url obtained by ngrok.

```bash
URLs: http://ngrok_public_url/webhooks/rocketchat/webhook
```

**Save** all the changes.

### Example

Type `@bot_rasa hello` to start a conversation with the Rasa bot
![example]

[example]: rasa_bot_example.png


### Additional Information

If you want the Rasa bot to direct message with the users create another webhook with the following configurations

```
Event Trigger: Message Sent
Enabled: True
Channel: all_direct_messages
URLs: http://bot_rasa:5005/webhooks/rocketchat/webhook
Post as: bot_rasa
```