LocalFoodAI_lanfr144/docs/Installation_Guide.md

Installation & Deployment Guide

This guide details how to deploy the Local Food AI stack on an Ubuntu 24.04 server.

1. Prerequisites

• Ubuntu 24.04 (e.g., VM at 192.168.130.170).
• Git, curl.

2. Setting Up MySQL

1. Install MySQL Server: sudo apt install mysql-server
2. Run setup_db.py to construct the schemas.

3. Configure mysql_config_editor to store encrypted login paths for app_auth and app_reader.

   mysql_config_editor set --login-path=app_reader --host=127.0.0.1 --user=db_reader --password
   mysql_config_editor set --login-path=app_auth --host=127.0.0.1 --user=db_auth --password
   

3. Setting Up Ollama (Local LLM)

The application requires ollama to run the Mistral model locally for strict privacy.

1. Install Ollama: curl -fsSL https://ollama.com/install.sh | sh
2. Pull the model: ollama run mistral

4. Python Environment

1. Clone the repository: git clone https://git.btshub.lu/...

2. Setup venv:

   python3 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt (streamlit, pandas, pymysql, bcrypt, ollama)
   

5. Running the Application

To run the Streamlit frontend:

streamlit run app.py --server.address 0.0.0.0

Note: If you run this locally on Windows without mysql_config_editor paths, you will receive a connection warning.

6. Docker & Kubernetes (Optional)

This repository also contains a full containerized CI/CD suite. Navigate to k8s/ and run kubectl apply -f . to spin up the MySQL, Taiga Sync, Ingestion Jobs, and Streamlit App in a resilient cluster.