How to integrate rasa open source to the Django running website
Published July 28, 2024, 10:15 a.m. by cloudblog
Integrating Rasa Open Source with a Django website involves several steps to ensure that your chatbot can interact seamlessly with your existing Django application. Here’s a step-by-step guide to help you through the integration process:
Integrating Rasa Open Source with a Django website involves several steps to ensure that your chatbot can interact seamlessly with your existing Django application. Here’s a step-by-step guide to help you through the integration process:
### 1. Set Up Rasa Open Source
1. **Install Rasa Open Source**:
Ensure that you have Rasa installed. You can install it using pip:
```bash
pip install rasa
```
2. **Create a New Rasa Project**:
If you don’t already have a Rasa project, create one:
```bash
rasa init
```
This will generate a basic project structure for you.
3. **Train Your Model**:
Train your Rasa model using the training data provided in the `data` folder:
```bash
rasa train
```
4. **Run the Rasa Server**:
Start the Rasa server, which will be responsible for handling requests to your chatbot:
```bash
rasa run
```
### 2. Set Up Your Django Project
1. **Install Required Packages**:
Ensure you have Django installed. If not, install it using pip:
```bash
pip install django
```
2. **Create a Django Project**:
If you don’t have a Django project set up, create one:
```bash
django-admin startproject myproject
```
3. **Create a Django App**:
Inside your Django project, create a new app where you will add the integration logic:
```bash
python manage.py startapp chatbot
```
### 3. Integrate Rasa with Django
1. **Create a View for Chatbot Interaction**:
In your Django app, create a view that will handle interactions between the Django frontend and the Rasa server.
```python
# chatbot/views.py
import requests
from django.http import JsonResponse
from django.views.decorators.csrf import csrf_exempt
import json
@csrf_exempt
def chat(request):
if request.method == 'POST':
user_message = json.loads(request.body.decode('utf-8')).get('message')
response = requests.post('http://localhost:5005/webhooks/rest/webhook', json={'message': user_message})
rasa_response = response.json()
return JsonResponse({'responses': rasa_response})
return JsonResponse({'error': 'Invalid request'}, status=400)
```
2. **Add URL Routing**:
Add a URL route for the chat view in your Django app’s `urls.py`.
```python
# chatbot/urls.py
from django.urls import path
from .views import chat
urlpatterns = [
path('chat/', chat, name='chat'),
]
```
Then, include this URL configuration in your project's `urls.py`.
```python
# myproject/urls.py
from django.contrib import admin
from django.urls import path, include
urlpatterns = [
path('admin/', admin.site.urls),
path('chatbot/', include('chatbot.urls')),
]
```
3. **Set Up Frontend Interaction**:
On the frontend, you’ll need to set up a form or WebSocket connection to send messages to your Django view and display the responses.
Here’s a basic example using JavaScript with fetch API:
```html
<!-- template.html -->
<html>
<body>
<input type="text" id="messageInput" placeholder="Type a message..."/>
<button onclick="sendMessage()">Send</button>
<div id="chatBox"></div>
<script>
function sendMessage() {
const message = document.getElementById('messageInput').value;
fetch('/chatbot/chat/', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({ 'message': message }),
})
.then(response => response.json())
.then(data => {
const chatBox = document.getElementById('chatBox');
data.responses.forEach(response => {
chatBox.innerHTML += `<p>${response.text}</p>`;
});
});
}
</script>
</body>
</html>
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