Inspiration
We enjoyed playing online language games and wanted to make it more impactful.
What it does
Our website offers a dynamic language-learning experience through an interactive game. Users are presented with sentences in their desired language, for example, German. These sentences are followed by questions that require the user to engage with the language. Upon providing the correct responses, users earn scores, creating a gamified and rewarding learning environment.
To enhance the learning process, we've incorporated a chatbot feature. If users find themselves struggling with German words or concepts, they have the option to interact with the chatbot. This intelligent assistant can assist by translating English text into German, providing valuable support and aiding users in their language-learning journey. This dual approach aims to make language acquisition not only effective but also enjoyable for our users.
How we built it
Our frontend is built on the React framework, offering a responsive and dynamic user interface. The communication between the frontend and backend is facilitated by a Python backend utilizing a Flask server, ensuring seamless interaction and data exchange.
To handle language translation within the application, we leverage a Language Model (LLM) from the translate library in Python. This trained model enables us to provide accurate and efficient translations, enhancing the multilingual experience for our users.
In terms of frontend styling, we utilize Chakra UI and Reactstrap for CSS. These frameworks contribute to the aesthetic appeal and overall user experience, ensuring a visually cohesive and user-friendly design. By combining these technologies, we aim to deliver a robust, efficient, and visually appealing language-learning platform.
Challenges we ran into
We initially explored the idea of employing a pre-built AI chatbot, intending to customize its input and output settings to align with our language requirements. However, we had to abandon this approach due to compatibility issues that hindered the seamless integration of the chatbot into our system. Despite the initial plan, we are now exploring alternative solutions to ensure a smooth and effective communication interface within our application.
Accomplishments that we're proud of
An integrated full stack application using LLM model
What we learned
API connection
What's next
Expanding to add more levels of game and multi-lingual support
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