Developer Adds AI Chat to Expense Tracker Using Google Gemini and Streaming

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A developer enhanced an existing React, Express, and SQLite expense tracker by integrating a conversational AI feature powered by Google's Gemini model. The chat interface allows users to query their own spending data in plain English, asking questions like how much was spent on a category or comparing time periods. Rather than generating a static summary, the backend fetches live expense data from the database on every message and injects it into the model's system prompt to prevent fabricated figures. Streaming was implemented to match the real-time feel of modern chat applications, and Google AI Studio was used for the API key due to its free, no-card-required access. During development, the engineer encountered issues including a misnamed environment variable and temporary 503 errors caused by Google server overload, not code bugs.

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ProgrammingDEV Community ·

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