tried to make an Antigravity version of XARD's homeLab. looks like this
XARD: This is great -- You download the shared zip file
Antigravity creates the HomeLAB for you and then you decide what you want to run on it -- FANTASTIC
Once you have your HomeLAB the way that you want you can then say to Antigravity --
"Create a zipped share file (excluding .env etc) so I can share with the community"
And you just upload the file with an image of your HomeLAB and everyone is on the same page

# HomeLAB v3.5 — How It Works

## Overview
HomeLAB is a Python desktop application that orchestrates 6 AI models through a single Antigravity API, with real-time market data feeds and a shared memory system called the Neural Bridge.

---

## Architecture

```
┌─────────────────────────────────────────────────────┐
│ HomeLAB GUI │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │Gemini Hi │ │Gemini Lo │ │Gem Flash │ ← Buttons │
│ ├──────────┤ ├──────────┤ ├──────────┤ │
│ │Cl.Sonnet │ │Cl.Opus │ │ GPT-OSS │ │
│ └──────────┘ └──────────┘ └──────────┘ │
│ │
│ [ News] [ Whales] [ Macro] [ Intel] │
│ ← Scrolling Ticker Banners (clickable) │
│ │
│ [Input Box] → Type prompt here │
│ [Log Area] → Model responses appear here │
└──────────────────┬──────────────────────────────────┘
│
▼
┌──────────────────────────────────────┐
│ ORCHESTRATOR │
│ │
│ 1. Collects live prices (CoinGecko) │
│ 2. Reads Blackboard (shared brain) │
│ 3. Fetches news/whale/intel data │
│ 4. Builds system prompt with ALL │
│ context injected │
│ 5. Sends POST to Antigravity API │
│ 6. Writes response to Blackboard │
└──────────────────┬───────────────────┘
│
▼
┌──────────────────────────────────────┐
│ Antigravity API (local service) │
│ Routes to correct model by ID │
└──────────────────────────────────────┘
```

---

## File Structure

| File | Purpose |
|------|---------|
| `run_lab.py` | Entry point — launches the GUI |
| `src/config.py` | All settings: models, API key, endpoints, ticker config |
| `src/orchestrator.py` | Brain — API calls, live data injection, memory management |
| `src/gui.py` | User interface — buttons, tickers, input/output |
| `src/utils.py` | Utilities — price feeds, news, logging, backups |
| `src/scrapers.py` | Telegram channel scrapers for intel ticker |
| `.env` | Your `ANTIGRAVITY_API_KEY` (not committed to git) |
| `BLACKBOARD.md` | Neural Bridge shared memory (auto-managed) |

---

## What Happens When You Click a Model Button

1. **You type** a prompt in the input box
2. **You click** one of the 6 model buttons (e.g., Gemini High)
3. **Orchestrator collects context:**
- Your prompt
- Live prices (BTC $67K, Gold $5,172, DAX 23,591, etc.)
- Latest news headlines from RSS feeds
- Whale alerts from Telegram
- Fed/Macro press releases
- Sovereign intelligence signals
- Neural Bridge (BLACKBOARD.md) shared state
- Attached PDF content (if any)
4. **Sends everything** as a single API call to the Antigravity service
5. **Response** appears in the log area
6. **Neural Bridge updated** — other models can see this result

---

## Live Data Sources

### Prices (refreshed every 2 minutes)
| Asset | Source |
|-------|--------|
| BTC, ETH | CoinGecko API (free) |
| Gold (PAXG, XAUT) | CoinGecko API |
| Gold/Silver (Spot) | metals.dev API |
| DAX 40 | Yahoo Finance |
| Fear & Greed Index | alternative.me |

### Tickers (scrolling banners)
| Ticker | Source | Refresh |
|--------|--------|---------|
| News | CoinTelegraph, Kitco, CNBC, CME RSS | 30 min |
| Whales | Telegram @whale_alert | 5 min |
| Macro | White House + Federal Reserve | 60 min |
| Intel | 7 Telegram channels + AI sentiment | 5 min |

> **Clicking any headline** auto-sends it to Gemini Flash for deep analysis.

---

## Neural Bridge (Shared Brain)

The **BLACKBOARD.md** file acts as shared memory between all models:
- Every model **reads** the Blackboard before answering
- Every model **writes** its response summary to the Blackboard
- This means Claude can see what Gemini said, and GPT-OSS can see what Claude said
- Use ** Clear Blackboard** to archive and start fresh

---

## Voice Input (Optional)

- Uses **Whisper large-v3-turbo** for speech-to-text
- Click ** Hold to Talk** → speak → click again to stop
- Transcribed text goes into the input box
- Requires `sounddevice` and `faster-whisper` dependencies

---

## Quick Start

```bash
# 1. Set your API key
echo ANTIGRAVITY_API_KEY=your_key > .env

# 2. Install dependencies
pip install -r requirements.txt

# 3. Ensure Antigravity service is running

# 4. Launch HomeLAB
python run_lab.py
```