Article Semantic Comprehension

Inspiration

One of our project partners came up with this idea during the summer. We decided that the hackathon is a great opportunity for us to bring the project to life.

What it does

What our article analysis does is that it analyzes and provides a summary of the article that the person entered. It summarizes the article by giving five key bullet points that are important to help with the user's understanding of the article. The program is also able to detect misinterpretation through semantic analysis.

How we built it

We used Hume.ai to be able to analyze semantic in text. We also used Together.ai for our LLM. We coded the project in python and Taipy is used in the backend.

Challenges we ran into

The challenges we ran into were being able to implement Hume.ai to be able to analyze the article that we entered and being able to create the LLM.

Accomplishments that we're proud of

We were proud of the fact that we were able to fully implement the Hume.ai to work with the articles, as this took us the longest time to figure out.

What we learned

We learned that API are very helpful in creating our programs.

What's next for Article Semantic Comprehension

The next step is to be able to type in a concept and multiple articles popup with analysis and summaries.

Built With

• hume
• python
• taipy
• together