Plain-Language Database Query App for Finance Beginners

Added Jun 2025 3 design docs

Databases hold the answers to most quantitative questions people ask at work and in class, but SQL stands between those questions and their answers. Finance students learning to analyze data, and non-technical users staring at a transactions table, give up not because the question is hard but because the query syntax is. An app that accepts the question in plain English and handles the SQL invisibly turns a database from an obstacle into a resource. The intern builds this app as a Streamlit project in Python using LangChain's SQL capabilities. Connected to a sample database, such as financial transactions or budget records, the app takes a natural-language question, uses the language model to generate the corresponding SQL query against the known schema, executes it, and presents the results along with the generated SQL so users can learn from what was produced. The intern implements the database connection, the question-to-query chain, result rendering in readable tables, and basic guards that prevent destructive statements from executing. The project introduces text-to-SQL, one of the most practically demanded LLM applications, at a scale an early developer can master fully: the intern learns schema-aware prompting, query validation habits, and interface design that treats generated code as something to display and verify, not blindly trust.

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