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logo
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chrome extension
Inspiration:
Inspiration for our project struck when we found ourselves spending over 15 minutes manually filling out an HTM (HackTheMountain) Registration form. It was a tedious task, and it made us question whether we could automate this process and extend the idea to tackle other forms as well.
What it does:
Our solution leverages state-of-the-art technology to automate the completion of web forms. It uses a Roberta model from Hugging Face for natural language understanding, a Flask API to facilitate communication between devices, Selenium for web scraping, and JavaScript for the browser extension. The result is a comprehensive platform that simplifies the process of filling out online forms.
How we built it:
The core of our project is powered by the Roberta model, which enables us to understand and generate human-like responses. We've used Flask, a Python micro web framework, to create an API that communicates with laptops and manages data flow. Selenium is utilized for web scraping, allowing us to gather the necessary data from web pages efficiently. Furthermore, JavaScript is employed to create a user-friendly browser extension, and web development skills were essential in building our website to support the project.
Challenges we ran into:
We encountered multiple challenges during the development of our solution. A significant portion of these challenges revolved around the browser extension and the integration of the Roberta model through our API. Additionally, we faced complexities related to the database setup and management with Supabase. Overcoming these hurdles required diligent debugging, problem-solving, and continuous refinement.
Accomplishments that we're proud of:
We take immense pride in achieving a unique automation solution that not only simplifies the process of filling out forms but also utilizes your LinkedIn data and GitHub URLs to pre-fill forms. Moreover, we are proud to emphasize that our project does not rely on external APIs like OpenAI, demonstrating our ability to harness existing technology and build a powerful automation tool from the ground up.
What we learned:
Throughout this project, we acquired valuable knowledge and skills. From working with complex language models to developing browser extensions, and from API communication to managing databases, our team gained a diverse set of competencies. We also learned the importance of resilience in the face of challenges and the value of creating user-friendly solutions.
What's next for our project:
Looking ahead, we aim to enhance and expand our solution. Our roadmap includes improving the accuracy and efficiency of the automation, adding support for more web forms and platforms, and incorporating advanced natural language processing features. We're committed to making our automation tool even more versatile and user-friendly.
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