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Repository used for the DOPRO project dealing with food AI.
This repository contains:
a full Taiga export plus all other documents that are part of your project planning, including any project presentation materials.
the full final product, including all files, documentation and presentation materials.

درخت: bfda8a610b
شاخه‌ها تگ‌ها
LocalFoodAI_lan...
lanfr144 bfda8a610b Add snmp to Streamlit container for traps 2 ماه پیش
.agents 7d59646d57 TG-6: Finalize remaining files 2 ماه پیش
AI_History f851d49f92 TG-29 TG-31 TG-32 TG-33: Implement EAV Architecture, Dynamic Medical CRUD UI, DataFrame Alert Engine, and Email Resets. TG-30: Fix Windows utf8 Encoding in Ingestion Engine. 2 ماه پیش
alembic 0fd29e16de Reduce partition chunk size to 4 to bypass persistent row size error; include initial alembic migration 2 ماه پیش
docker bfda8a610b Add snmp to Streamlit container for traps 2 ماه پیش
docs c3fc1ef4c0 Add Sprint 8 Documentation 2 ماه پیش
k8s 4655c26f1f Add untracked project files and configs 2 ماه پیش
legacy_scripts c812444386 Sprint 6: Complete documentation and code cleanup 2 ماه پیش
taiga_wiki e78a25bf3c TG-2: Populate Sprint 2 accomplishments in Taiga Wiki 2 ماه پیش
.gitignore 4655c26f1f Add untracked project files and configs 2 ماه پیش
Final_Presentation.html 1558f08eca Execute Implementation Plan 2 2 ماه پیش
PROJECT_CONTEXT.md e3f96b1f33 Sprint 7: Zabbix and SNMPv3 Monitoring Integration 2 ماه پیش
README.md c812444386 Sprint 6: Complete documentation and code cleanup 2 ماه پیش
alembic.ini 73f7a04cd0 Optimize horizontal partitioning to slice into 8-column chunks bypassing InnoDB limits 2 ماه پیش
app.py 4f7322e4da Strip username to prevent space errors 2 ماه پیش
check_users.py 7766898050 Add check users script 2 ماه پیش
deploy.sh a54dc25344 TG-21: Update deploy.sh to include requests connectivity dependency. 2 ماه پیش
download_csv.sh 4655c26f1f Add untracked project files and configs 2 ماه پیش
generate_taiga_wiki.py e78a25bf3c TG-2: Populate Sprint 2 accomplishments in Taiga Wiki 2 ماه پیش
ingest_csv.py e3f96b1f33 Sprint 7: Zabbix and SNMPv3 Monitoring Integration 2 ماه پیش
init.sql ae711f7d4c TG-3: Docker Setup and DB Creation 2 ماه پیش
init_zabbix_db.sh 06df1fda4e Add Zabbix DB init script 2 ماه پیش
master_trigger.sh 38a83a1bf0 Deployment Finalization: Vitamin schemas, Green UI, and Taiga tools 2 ماه پیش
my.cnf 86c76e282d TG-1: Fix MySQL 8.0 startup crash by removing premature validate_password plugin config 2 ماه پیش
myloginpath.py 4655c26f1f Add untracked project files and configs 2 ماه پیش
proper_reset.sh 776d6a6153 Add proper reset 2 ماه پیش
requirements.txt e3f96b1f33 Sprint 7: Zabbix and SNMPv3 Monitoring Integration 2 ماه پیش
reset_zabbix_db.sh 9e59bd56c5 Add reset DB script 2 ماه پیش
setup_db.py d5eae6eb05 Disable foreign key checks during drop 2 ماه پیش
setup_logins.exp c830b35313 TG-2: Automate DB setup and mysql_config_editor passwords for CI/CD 2 ماه پیش
setup_mail_forwarding.sh ab7e3b1d3a TG-2: Restructure schema for all CSV columns, async ingestion, and mail forwarding 2 ماه پیش
setup_postfix.sh 38a83a1bf0 Deployment Finalization: Vitamin schemas, Green UI, and Taiga tools 2 ماه پیش
setup_searxng.sh ebfb102bc7 TG-20: Create setup_searxng.sh to install Docker and bind anonymous SearXNG to localhost:8080. 2 ماه پیش
setup_sprint7_taiga.py e3f96b1f33 Sprint 7: Zabbix and SNMPv3 Monitoring Integration 2 ماه پیش
setup_sprint8_taiga.py 69bad82b3b Add Sprint 8 Taiga script 2 ماه پیش
setup_unix_user.sh 4655c26f1f Add untracked project files and configs 2 ماه پیش
snmp_notifier.py c7eda9a94d Fix snmp_notifier to use snmptrap cli 2 ماه پیش
start_batch_ingest.sh 00f1d63625 Fix python virtual env paths 2 ماه پیش
sync_taiga.py ef9531a80d TG-3: Update python sync script with correct username FrancoisLange 2 ماه پیش
taiga_sync_fixer.py 4655c26f1f Add untracked project files and configs 2 ماه پیش
test_login.py d7f6558318 Add test login 2 ماه پیش
test_snmp.py 1d5ce8580c Add test SNMP script 2 ماه پیش
unit_converter.py 620543f87d Implement full dynamic CSV schema ingestion and unit conversion module 2 ماه پیش

README.md

Local Food AI 🍔

A strictly local, privacy-first AI Medical Dietitian and Food Explorer. This project leverages the OpenFoodFacts dataset and local LLMs (Ollama) to provide medically sound dietary advice, recipe parsing, and menu planning without sending any user data to the cloud.

Features

  • Dynamic Medical Profiling: Configure your health profile (e.g., Kidney issues, pregnancy, vegan). The AI dynamically adjusts all responses, recommendations, and warnings based on these exact medical needs.
  • RAG Architecture: The AI is connected to a massively partitioned local MySQL database. When you ask a question or request a meal plan, the AI executes SQL queries autonomously to fetch precise nutritional data.
  • Plate Builder & Unit Conversion: Input culinary recipes (e.g., "1.5 cups of flour") and the system converts them to metric standard weights based on the product's density.
  • High-Performance Database: Implements Grouped Vertical Partitioning to bypass InnoDB limits, featuring FULLTEXT indexing for lightning-fast search capabilities across millions of foods.

Documentation

Please refer to the docs/ folder for detailed guides:

Tech Stack

  • Frontend: Streamlit
  • Database: MySQL 8.0
  • AI Engine: Ollama (Mistral / Llama3)
  • Deployment: Native Ubuntu, Docker, Kubernetes
  • Project Management: Taiga (Synced dynamically via Python)