We designed a user-friendly interface that allowed our client to feed in URLs of news articles. The application, built with FastAPI and ChatGPT-3.5-Turbo model, processed these articles and generated tweet options. This solution increased our client's posting frequency, driving a significant growth in follower count.
Our client wants to expand their reach on Twitter by attracting more followers. However, due to time constraints, they required a solution that would automate the process of generating tweets using industry news.
The client's involvement should be limited to selecting news articles and choosing their preferred tweets from a list of generated options.
To address this challenge, we developed a straightforward user interface that enables the client to add URLs to news articles or news pages.
Our application then scrapes the content from these sources and converts them into Markdown format.
Leveraging a combination of prompts, we extracted key benefits from the articles and presented them as engaging tweets.
We implemented different options on how to generate the tweets, our most compelling approach integrated facts from different news articles to generate unique content that surpassed a simple summary.
The facts are stored in a vector store and pulled based on the topic of the provided news article.
To address this challenge, we developed a straightforward user interface that enables the client to add URLs to news articles or news pages.
Our application then scrapes the content from these sources and converts them into Markdown format.
Leveraging a combination of prompts, we extracted key benefits from the articles and presented them as engaging tweets.
We implemented different options on how to generate the tweets, our most compelling approach integrated facts from different news articles to generate unique content that surpassed a simple summary.
The facts are stored in a vector store and pulled based on the topic of the provided news article.
