Inspiration

The inspiration for this application comes from the personal experience of getting recommendation form LLM's which were too generic and with Qloo's data it provides way better recommendation as compared to an LLM's knowledge base.

What it does

It is a web application powered by Qloo's apis and LLM which can be used to fetch recommendation on different topics like movie, books, restaurants etc through a chatbot interface and get deep insight of any valid Qloo Entity.

How we built it

For this application I have used nextjs as the framework of choice, tailwindcss for styling and shadcn/ui for ui components. For LLM I have used multiple endpoints from Meta LLama through openrouter. I have also used multiple api endpoints from qloo like:

  1. /v2/insights
  2. /search
  3. v2/tags

Challenges we ran into

Initially I was quite lost since Qloo was very new to me and it took some time to understand its term and also Sarah has been very helpful through disocrd. One major Issue I faced was while trying to create an api route to get recommendation based on places. But after rereading the docs I was able to solve my issue.

Accomplishments that we're proud of

I am really proud of the fact that I was able to create an application which can be used to fetch recommendations which are culturally relevant. Apart from it I am also very proud to understand the different concepts of Qloo's api and how much big of a change it brings to the answers as compared to just using the default knowledge of an LLM.

What we learned

I am very happy to learn about the different endpoint that are available and also about the how to use them properly. The endpoints has a lot of parameters which influences the results. I am happy that I now have confidence on how different parameters can be used to manipulate results.

What's next for Rec&Sight

In the future I want to integrate some more advance queries using the qloo endpoints.

Built With

  • llama
  • nextjs
  • qloo
  • qloo-api
  • qloo-insight
  • qloo-tags
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