ChatGPT API & Whisper API Global Hackathon

We will shortly introduce you to the ChatGPT API & Whisper API Global Hackathon, Challenge, lablab.ai platform, Discord server

Introduction to the Challenge

Short intro from lablab.ai's partner - Redis, the leading provider of enterprise-class solutions for vector search, data storage, and ML feature workloads

Redis Introduction

Paweł Czech and Mathias Asberg, co-founders of New Native will talk about lablab.ai's mission and vision. https://www.twitch.tv/lablabai

Start

Live Coding with ChatGPT API & Whisper API 

An introduction to Redis and a coding session where we will build an application 

Live tutorial | Building with Redis

Under the hood: Building a QA app using Redis

Time's up! Submit your solution before the deadline

Team of two tech enthusiasts. We like to explore telephony & voice channel related technologies.

TechnoCouple

shivaprasad

pritisharma127

We have built a solution for agencies which provide the caretaker services for parents who are in search of babysitters for their child. When users call the agency after business hours or when agents are not available for assistance, we are routing them to leave a voicemail with their babysitter requirement and contact number. With this solution, agents can focus on more complex tasks rather than manually retrieving voicemails, analysing them and coming up with a resolution. When the caller dials the agency phone number during office closed hours or peak hours when agents are not available to serve them, we route the caller to the voicemail menu where we ask them to leave a voicemail with babysitting requirements and their contact details, etc. Once the voicemail is available, we extract it and convert this speech to text using OpenAI’s whisper API which gives us the voicemail transcription. After that, we meticulously perform the prompt engineering for ChatGPT API to provide us all the required information from voicemail like intent, sentiment, babysitting date and time, etc in JSON format. Using this information, we query the EmployeeSchedule table which is in the H2 database. Once we have the information about availability of babysitters, we query RedisJSON to get the employee profile information like employee name, contact details, date of birth, languages spoken, image, etc. We then build a PDF document using itext library. This PDF containing available babysitter information will be sent on the caller’s WhatsApp. After this, we send an SMS to the agency as an alert notification about the customer enquiry and ask them to get in touch with the customer.
Github link - https://github.com/technocouple/technocouple-caretaker-assistant
Video link - https://drive.google.com/drive/folders/1NBew2U0Xgtm04ubQszjLvZV92fowR6-D?usp=sharing
Presentation - https://drive.google.com/file/d/1TBMSU5Ohyn1v2P2u_RqbZOpuCvWv1Crq/view?usp=share_link

DEMO is at the end of the video.

“WeCare - The caretaker assistant” is the AI based solution for agencies which provide the caretaker services for parents who are in search of babysitters for their child.

"TechnoCouple team on ChatGPT API & Whisper API Global Hackathon Hackathon"

Team Idea

Submission