11 08:26:59 [TG-131] Purge database passwords from tracked files and format application versioning [PreRelease-1.0-26-g1701828] $

Final Project Report (Living Document)

Core Architecture: Deployed a resilient 8-container local fallback Docker Compose stack (MySQL, Streamlit UI, local Ollama LLM, anonymous SearXNG search, secure Nginx proxy, and local Zabbix Server/Web/Agent observability suite).
Database Optimization: Successfully loaded OpenFoodFacts records and utilized advanced vertical partitioning and FULLTEXT indices.
Clinical Subquery Strategy: Refactored the core Pandas/SQL query pipeline to use subquery limiting, resolving Cartesian join explosions and reducing query latency to ~0.04s.
Monitoring & Security: Nginx securely proxies traffic on Port 80. Zabbix actively monitors proxy and server health, dynamically handling SNMP/alert loops in local/offline fallback mode.
Git Versioning: Implemented Git .gitattributes to push $Id: 1701828b122e0c319e59134ca6511a42ecad9297 Lange François lanfr144@school.lu 2026/06/11 08:26:59 Lange François lanfr144@school.lu 2026/06/11 08:26:59 [TG-131] Purge database passwords from tracked files and format application versioning [PreRelease-1.0-26-g1701828] $ tracking directly into the Python Application UI.

SSL/TLS Certificates: The Nginx proxy is functional on HTTP port 80. Port 443 (HTTPS) must be configured with a Let's Encrypt certificate for true production encryption.
User Acceptance Testing (UAT): Clinical dietitians should rigorously test the AI Chat constraints and Plate Builder to ensure edge cases are handled safely.
Advanced Rate Limiting: Limit the number of AI requests per user using a sliding window algorithm in app.py.