Inspiration
Whenever we are searching for information regarding restaurants, we have to look through reviews to get the true sentiment from the public. It would be more efficient if there was an AI chatbot to handle the task.
What it does
Review Ninja Bot takes in restaurant names and questions regarding the restaurant from the user. It then provides an answer that gives an overview of the restaurant and a reply to the question. This cuts down the time taken for the user to screen through a restaurant's reviews.
How we built it
Our database is made from information retrieved from Google's Places API. Python flask is used to create the APIs and pass information to the JinaChat API, which returns an answer regarding the restaurant. The website uses Angular and Material to display the chatbot interface and its functionalities. If the user types in a restaurant name, the database will be searched for relevant information. If the user types in a question, the question will be sent along with the restaurant data to JinaChat, where the reply is generated.
Challenges we ran into
We had difficulty with the data format when sending it to the API and displaying on the screen. We also had challenges with the dependencies in Angular. Eventually, we managed to solve the format for the data to pass in and out of the API, and removed packages that are causing the problem in Angular.
Accomplishments that we're proud of
We are proud that we managed to build this web application in 2 days. We are also proud that we learnt how to use an LLM to solve a real-world problem.
What we learned
We learnt that different languages handle API data differently. We also learnt to collaborate and work with each other cordially.
What's next for Team 29_Review Ninja Bot
More data, trying out other LLMs to see which is more suitable for this application and automated periodical updates to the database to keep up with the latest reviews.
Built With
- angular.js
- bootstrap
- css
- flask
- google-places
- html5
- jinachat
- material
- python
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