An AI API is not a mobile product by itself. The interface needs clear conversation behavior, local persistence, sensible setup, and an approachable path for contributors.
The problem
What had to work beyond the model.
The public repository has visible open-source interest; current stars and forks are shown from the GitHub snapshot on the page.
Implements a conversational Gemini interface with local history and app-level navigation.
Documents modern Android Gradle, Kotlin, and Java compatibility updates for contributors.
How the pieces connect.
- 01Conversation UI
The Flutter interface manages message composition, response rendering, auto-scroll behavior, and image selection.
- 02App state
Provider-based state management keeps loading, conversation, and navigation behavior organized across the app.
- 03AI connection
Gemini requests are configured through the app environment, while Markdown rendering keeps responses readable.
- 04Local continuity
Hive-backed history preserves conversations locally so the product experience survives a single screen session.
Choices that make the system usable.
- 01
Used Flutter to focus on the interaction layer around an AI capability rather than presenting a bare API call.
- 02
Kept local history in the product so the conversation experience survives beyond a single screen session.
- 03
Kept environment and API-key setup explicit so a contributor can run the app without hard-coding secrets.
- 04
Modernized the Android toolchain around Gradle 8.14, AGP 8.11.1, Kotlin 2.2.20, and Java 17 for current Flutter tooling.
How the work can be inspected.
- The repository documents environment setup, dependency installation, and the Android compatibility path for contributors.
- Local persistence, state management, response rendering, and scrolling behavior are visible product-level concerns rather than hidden behind one API call.
- Stars and forks are rendered from the current GitHub repository snapshot instead of being used as a fixed marketing claim.
Local history does not make the model offline-capable, and this case study does not claim an App Store or Play Store release, engagement metrics, or production adoption.
FlutterDartGeminiHiveProviderMarkdownAndroidiOS