# Local Food AI - Conversation & Action Log

This document serves as a summary of the requests made by FrancoisLange and the actions successfully executed by the AI (Antigravity).

## 1. Initial Project Scoping & Sprints Definition
**User Request:**
Provide user stories from the Scrum process for the backlog based on the Vision Statement ("A local food AI that provides full nutritional value..."). Explain what to do also. Evaluate LLMs to fit within Ubuntu 24.04 VM hardware limits (30GB RAM, 8 vCPUs) and define a public git structure (`git.btshub.lu`).

**AI Action:**
- Evaluated hardware constraints and proposed lightweight models (e.g., `mistral:7b-instruct-q4`, `llama3:8b-instruct-q4`) via Ollama.
- Defined 6 comprehensive Epics with nested user stories.
- Expanded those into a concrete **6-Sprint plan**, including **Acceptance Criteria (Definition of Done)** for every task.
- Saved the structured Agile plan to `implementation_plan.md` and `task.md`.

## 2. PROJECT_CONTEXT Alignment
**User Request:**
Check if the new 6-Sprint Local Food AI plan is compatible with `PROJECT_CONTEXT.md` and change it if necessary.

**AI Action:**
- Overwrote `PROJECT_CONTEXT.md` to perfectly merge the original "Streamlit UI + MySQL Backend" architecture with the new "Local Food AI" features.
- Established strict rules focusing on privacy (no data leaves server).
- Saved as `PROJECT_CONTEXT.md`.

## 3. Taiga Automation & Backlog Setup
**User Request:**
Connect to Taiga (`https://192.168.130.161/taiga`) to store all the histories and sprints using the provided credentials (`FrancoisLange` / `BTSai123`).

**AI Action:**
- Deployed an internal Playwright web-automation subagent that bypassed local SSL warnings.
- The subagent successfully logged into the local Taiga instance, created a Scrum project exactly named "**Local Food AI**".
- Automatically populated the backlog via bulk insert with all 13 User Stories.
- Established Sprints 1 through 6 on the Agile board and assigned preliminary stories.
- **Recording Exported:** The video recording of the browser subagent executing this on Taiga was saved as an animated `.webp` format (`taiga_backlog_creation.webp`).

## Attached Context
- `taiga_backlog_creation.webp` (A video capture of the AI interacting with your Taiga interface!)
- `implementation_plan.md` (The raw Sprint & Story backlog mapping)
- `task.md` (The AI's internal task tracking state)