Mapping Sentiments to Emojis

Symbl's APIs empower developers to enable:

• Real-time analysis of free-flowing discussions to automatically surface highly relevant summary discussion topics, contextual insights, suggestive action items, follow-ups, decisions, and questions.
• Voice APIs that makes it easy to add AI-powered conversation intelligence to either telephony or WebSocket interfaces.
• Conversation APIs that provide a REST interface for managing and processing your conversation data.
• Summary UI with a fully customizable and editable reference experience that indexes a searchable transcript and shows generated actionable insights, topics, timecodes, and speaker information.

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Pre-requisites

• HTML
• JavaScript
• Python3

Feature:

Enable a WebSocket's live streaming sentiment polarity scores to be interpreted by emojis.

Setup and Deploy

The first step to getting setup is to sign up.

Gather your Symbl credentials:

1. Your App Id that you can get from Platform
2. Your App Secret that you can get from Platform
3. After setting up your Symbl.ai account, cURL Symbl.ai's authentication API endpoint for an authorization token in the following way:

curl -k -X POST "https://api.symbl.ai/oauth2/token:generate" \
     -H "accept: application/json" \
     -H "Content-Type: application/json" \
     -d "{ \"type\": \"application\", \"appId\": \"<appId>\", \"appSecret\": \"<appSecret>\"}"

4. Assign your authorization token as the value of accessToken.

5. Run python3 -m http.server 8000 in the root directory.

6. You app should be running at http://localhost:8000

Conclusion

You application interprets sentiments from Symbl.ai's Conversation API Message API with the /message's API's parameter for sentiments set to true. After making calls to the Message API, your application interprets the messages with scores below -0.3 as 😞, the messages with scores above 0.3 as 😃, the messages between those scores as 😐. It demonstrates how Symbl.ai's Conversation Intelligence API platform empowers developers to connect, transform or visualize conversation data in real-time streaming applications.

Community

If you have any questions, feel free to reach out to us at devrelations@symbl.ai or through our Community Slack or our forum.

This guide is actively developed, and we love to hear from you! Please feel free to create an issue or open a pull request with your questions, comments, suggestions and feedback. If you liked our integration guide, please star our repo!

This library is released under the Apache License