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Casual-to-Formal Text Converter for English Language Learners

Added Jun 2025 3 design docs

Students and early-career professionals constantly move between linguistic registers: the message they would send a friend is not the message they should send a professor or an employer. Many, especially those learning English or entering the workforce, know their text is too casual but cannot see how to fix it. A converter that shows the formal version of their own words, instantly and side by side, is both a practical utility and a quiet language tutor.

The intern builds this converter as a Streamlit application in Python. The user pastes informal text, containing slang, abbreviations, or a conversational tone, and the app uses LangChain to send it through a language model with instructions to rewrite it in formal English while keeping the meaning intact. The intern implements the input and output interface with before-and-after display, a formality selector offering levels such as professional email versus academic writing, and prompt templates tuned so the rewrite elevates register without inventing content or losing the writer's point.

The project is an ideal introduction to LLM-powered text transformation: the intern learns to build prompt templates in LangChain, wire them into a responsive Streamlit interface, and evaluate outputs for the subtle failure mode that matters here, meaning drift. It produces a tool with obvious everyday value for its intended users.

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