Integrating Amazon AI with Google Slides
- Ensure you have administrative access to both an Amazon Web Services (AWS) account and a Google account to access Google Slides.
- Obtain necessary credentials for both platforms: AWS Access Key ID, Secret Access Key, and Google OAuth 2.0 credentials.
Set Up AWS SDK
- Install the AWS SDK for your preferred programming language. In this example, we'll use Python. You can install the AWS SDK using pip:
pip install boto3
- Configure your AWS credentials on your local machine:
aws configure
- Input your Access Key ID, Secret Access Key, region, and output format when prompted.
Authorize Access to Google Slides API
- Go to the Google Cloud Console and create a new project or select an existing one.
- Enable the Google Slides API from the API Library.
- Under "Credentials," click "Create credentials" and select "OAuth client ID". Follow the instructions to set up the consent screen and create the credentials.
- Download the JSON file containing your client secrets and save it as `credentials.json` in your project directory.
Set Up Google Slides API
- Install the Google client library for Python:
pip install --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib
- Follow the prompt to authorize access when running the app for the first time, this will involve a browser verification step.
Connect and Integrate Both Services
- Start by importing necessary libraries. Establish connections to AWS and Google Slides API using their respective SDKs.
import boto3
from google.oauth2.credentials import Credentials
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
import os
import pickle
# AWS Client
aws_client = boto3.client('comprehend', region_name='us-east-1')
# Google Slides API
SCOPES = ['https://www.googleapis.com/auth/presentations']
creds = None
if os.path.exists('token.pickle'):
with open('token.pickle', 'rb') as token:
creds = pickle.load(token)
if not creds or not creds.valid:
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
flow = InstalledAppFlow.from_client_secrets_file('credentials.json', SCOPES)
creds = flow.run_local_server(port=0)
with open('token.pickle', 'wb') as token:
pickle.dump(creds, token)
slides_service = build('slides', 'v1', credentials=creds)
- Create a function to extract text from Google Slides, pass it to an AWS AI service (e.g., Amazon Comprehend for natural language processing), and return the result.
def analyze_presentation(presentation_id):
presentation = slides_service.presentations().get(presentationId=presentation_id).execute()
slides = presentation.get('slides')
for slide in slides:
for element in slide['pageElements']:
if 'shape' in element and 'text' in element['shape']:
text = element['shape']['text']['textElements']
full_text = ''.join([te.get('textRun', {}).get('content', '') for te in text if 'textRun' in te])
if full_text.strip():
response = aws_client.detect_dominant_language(Text=full_text)
languages = response['Languages']
print('Detected languages:', languages)
- Replace `presentation_id` with your Google Slide presentation ID and run the function to analyze text using Amazon AI capabilities.
Test and Implement Your Integration
- Run your script to ensure both the AWS and Google APIs are responding correctly and you are receiving the expected analysis results.
- Debug any issues by checking credentials, permissions, and existing API service configurations.
- Once successful, expand the integration to include more sophisticated use cases, such as enrichments or embedding results back into slides.
