Prerequisites

• Ensure you have an IBM Cloud account and have set up IBM Watson services that you plan to use, such as IBM Watson Assistant or IBM Watson Natural Language Understanding.

 

• Have Zoom API Credentials (API Key and API Secret), which can be set up via Zoom's Marketplace after creating an app under "Build App."

 

• Basic knowledge of Python (or another programming language) to create a middleware that handles the integration.

Set Up Your Python Environment

• Ensure Python is installed on your machine. It's recommended to use Python 3.x for this integration.

 

• Create a virtual environment to maintain dependencies:

python3 -m venv zoom-watson-env
source zoom-watson-env/bin/activate

• Install necessary libraries using pip:

pip install ibm-watson zoomus flask

Initialize IBM Watson SDK

• Once dependencies are installed, create a new Python script named `watson_integration.py`.

 

• Import and set up the IBM Watson services in the script:

from ibm_watson import AssistantV2
from ibm_cloud_sdk_core.authenticators import IAMAuthenticator

# Configure Watson Assistant
authenticator = IAMAuthenticator('YOUR_IBM_WATSON_API_KEY')
assistant = AssistantV2(
    version='2022-02-15',
    authenticator=authenticator
)
assistant.set_service_url('YOUR_IBM_WATSON_URL')

Initialize Zoom SDK

• Integrate Zoom's SDK by importing and configuring it within the same script:

from zoomus import ZoomClient

# Initialize Zoom client
zoom_client = ZoomClient('YOUR_ZOOM_API_KEY', 'YOUR_ZOOM_API_SECRET')

Set Up Middleware

• Utilize Flask to create a simple web server that listens for Zoom webhook events, processes them with IBM Watson, and possibly sends responses back to Zoom:

from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route('/zoom-webhook', methods=['POST'])
def zoom_webhook():
    data = request.json
    event_type = data.get('event')

    if event_type == 'meeting.participant_joined':
        # Process participant joined event
        user_data = data['payload']['object']['participant']['user_name']
        handle_user_joined(user_data)

    return jsonify({'status': 'success'}), 200

Handling User Events

• Create a function to handle event data using IBM Watson's capabilities:

def handle_user_joined(user_name):
    # Sample interaction with Watson Assistant
    session_response = assistant.create_session(
        assistant_id='YOUR_ASSISTANT_ID'
    ).get_result()

    message_response = assistant.message(
        assistant_id='YOUR_ASSISTANT_ID',
        session_id=session_response['session_id'],
        input={'text': f'{user_name} has joined the meeting'}
    ).get_result()

    print(message_response['output']['generic'][0]['text'])

Testing the Integration

• Use ngrok to expose your Flask server to the internet, allowing Zoom to send webhooks:

ngrok http 5000

• Copy the `ngrok` URL and use it as the webhook endpoint in the Zoom app configuration at Zoom Marketplace.

 

• Test by starting a Zoom meeting and observing the processed data through `print` statements or logs.