Open Issues Need Help
View All on GitHubAI Summary: Implement a flexible storage system for a multimodal AI chat application, allowing users to choose between a Cloud SQL database and local file storage. This involves creating an abstract storage module with concrete implementations for both backends, adding a configuration option to switch between them, and ensuring the application functions identically regardless of the chosen backend.
A demo multimodal AI chat application built with Streamlit and Google's Gemini model. Features include: secure Google OAuth, persistent data storage with Cloud SQL (PostgreSQL), and intelligent function calling. Includes a persona-based newsletter engine to deliver personalized insights.
AI Summary: This task requires a significant architectural refactor of a multimodal AI chat application. The current monolithic Streamlit application needs to be decoupled into a Streamlit frontend and a FastAPI backend microservice. All business logic, including Gemini API interactions, database operations, and newsletter functionality, must be migrated to the FastAPI service. New FastAPI endpoints for newsletter subscription management, tracking (using a 1x1 pixel), and automated daily sending (triggered by an external scheduler) must be implemented. The Streamlit frontend will be updated to interact with the new backend via API calls and include a UI for newsletter subscription management.
A demo multimodal AI chat application built with Streamlit and Google's Gemini model. Features include: secure Google OAuth, persistent data storage with Cloud SQL (PostgreSQL), and intelligent function calling. Includes a persona-based newsletter engine to deliver personalized insights.