Add worker setup guide

WORKER_README.md

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+# Worker Agent Setup Guide
+
+## Architecture
+
+```
+                    ┌─────────────────┐
+                    │   OVERSEER      │
+                    │ (Your HF Space) │
+                    └────────┬────────┘
+                             │
+              ┌──────────────┼──────────────┐
+              │              │              │
+              ▼              ▼              ▼
+     ┌─────────────┐  ┌─────────────┐  ┌─────────────┐
+     │ Friend's HF │  │   Your      │  │   Your      │
+     │   Space     │  │  Laptop     │  │  Laptop      │
+     │ (Worker 1) │  │ (Worker 2)  │  │ (Overseer)   │
+     └─────────────┘  └─────────────┘  └─────────────┘
+```
+
+You have $30 credits. Here's how to use them efficiently:
+
+---
+
+## PART 1: Friend's HF Space (Worker 1)
+
+Your friend deploys this on their HF account using your trained model.
+
+### Steps for Your Friend:
+
+1. **Create New HF Space**
+   - Go to: https://huggingface.co/spaces/new
+   - Name: `aegis-worker-{friendname}`
+   - Type: **Space**
+   - SDK: **Docker**
+   - Hardware: **A10G (small)** - $3/hour
+   - Visibilty: **Private** (if they want)
+
+2. **Upload Files**
+   - Upload these 3 files:
+     - `hf_worker.py`
+     - `requirements.txt`
+     - `Dockerfile`
+
+3. **Set Environment Variables**
+   - Go to Space Settings → Variables
+   - Add:
+     - `HF_TOKEN` = your token (get from HF Settings → Access Tokens)
+     - `WORKER_MODEL` = your trained model repo
+
+4. **IMPORTANT: Cost Management**
+   - Set a **Repository Visibility** to Private
+   - After their turn, they must **Factory Reboot** the space to free resources
+   - With $30 at $3/hr = ~10 hours of runtime
+   - Can run in bursts: 1 hour at a time, then stop
+
+---
+
+## PART 2: Your Laptop (Worker 2) - Optional
+
+If you want your laptop as a worker too:
+
+### Setup:
+
+```bash
+# Install dependencies (if not already)
+pip install -r worker_agent/requirements.txt
+
+# Start the local worker
+python worker_agent/local_worker.py
+```
+
+### Expose to Internet with ngrok:
+
+```bash
+# In a new terminal
+ngrok http 7861
+```
+
+**Copy the ngrok URL** (e.g., `https://abc123.ngrok.io`) and tell your overseer about it.
+
+---
+
+## PART 3: Update Your Overseer
+
+In your overseer (where you run the main model), add:
+
+```python
+from overseer_worker_client import dispatch_to_worker, set_worker_url
+
+# After friend deploys their space, update the URL:
+# set_worker_url("friend_hf", "https://friend-space.hf.space/execute")
+# OR if using ngrok:
+# set_worker_url("local", "https://your-ngrok-url/execute")
+
+# To send a task:
+result = await dispatch_to_worker({
+    "task_id": "task_001",
+    "worker_role": "general-dev",
+    "instructions": "Write a hello world program in Python",
+    "context": "User wants a simple script"
+})
+```
+
+---
+
+## Quick Reference
+
+| Component | Cost | When to Use |
+|-----------|------|--------------|
+| Friend's HF (A10G) | ~$3/hr | When friend is online |
+| Your Laptop (free) | $0 | When laptop is on |
+| ngrok (free) | $0 | Tunnel to laptop |
+
+### Total: ~$30 covers ~10 hours of HF compute
+
+---
+
+## Files Created
+
+- `worker_agent/hf_worker.py` - Code for friend's HF Space
+- `worker_agent/local_worker.py` - Code for your laptop
+- `worker_agent/overseer_worker_client.py` - Your overseer uses this
+- `worker_agent/requirements.txt` - Python dependencies
+- `worker_agent/Dockerfile` - Container config
+
+---
+
+## Flow Example
+
+1. **You** ask overseer a question
+2. **Overseer** picks a worker (friend or laptop)
+3. **Worker** processes the task with your trained model
+4. **Worker** returns result to overseer
+5. **Overseer** evaluates and responds
+
+This lets you use both your friend's credits AND your laptop as workers while your HF Space acts as the overseer/manager.