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87 changes: 87 additions & 0 deletions .devcontainer/devcontainer.json
Original file line number Diff line number Diff line change
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{
"name": "BlackRoad Agent Codespace",
"image": "mcr.microsoft.com/devcontainers/python:3.11-bullseye",

"features": {
"ghcr.io/devcontainers/features/node:1": {
"version": "20"
},
"ghcr.io/devcontainers/features/go:1": {
"version": "latest"
},
"ghcr.io/devcontainers/features/docker-in-docker:2": {},
"ghcr.io/devcontainers/features/github-cli:1": {}
},

"customizations": {
"vscode": {
"extensions": [
"ms-python.python",
"ms-python.vscode-pylance",
"ms-toolsai.jupyter",
"github.copilot",
"github.copilot-chat",
"dbaeumer.vscode-eslint",
"esbenp.prettier-vscode",
"redhat.vscode-yaml",
"ms-azuretools.vscode-docker",
"eamodio.gitlens",
"Continue.continue"
],
"settings": {
"python.defaultInterpreterPath": "/usr/local/bin/python",
"python.linting.enabled": true,
"python.linting.pylintEnabled": true,
"python.formatting.provider": "black",
"editor.formatOnSave": true,
"files.autoSave": "onFocusChange",
"terminal.integrated.defaultProfile.linux": "bash"
}
}
},

"postCreateCommand": "bash .devcontainer/setup.sh",

"forwardPorts": [
8080,
3000,
5000,
11434,
8787
],

"portsAttributes": {
"8080": {
"label": "BlackRoad Operator",
"onAutoForward": "notify"
},
"3000": {
"label": "Web UI",
"onAutoForward": "openPreview"
},
"5000": {
"label": "Hailo Inference",
"onAutoForward": "silent"
},
"11434": {
"label": "Ollama API",
"onAutoForward": "silent"
},
"8787": {
"label": "Wrangler Dev",
"onAutoForward": "notify"
}
},

"remoteEnv": {
"PYTHONPATH": "${containerWorkspaceFolder}/prototypes/operator:${containerWorkspaceFolder}/prototypes/mcp-server:${containerWorkspaceFolder}/prototypes/dispatcher",
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The PYTHONPATH in devcontainer.json includes paths that may not exist in a fresh repository clone ('prototypes/operator', 'prototypes/mcp-server', 'prototypes/dispatcher'). If these directories don't exist, it won't cause errors but adds unnecessary noise. Consider validating these paths exist or documenting the expected repository structure.

Suggested change
"PYTHONPATH": "${containerWorkspaceFolder}/prototypes/operator:${containerWorkspaceFolder}/prototypes/mcp-server:${containerWorkspaceFolder}/prototypes/dispatcher",
"PYTHONPATH": "${containerWorkspaceFolder}",

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"BLACKROAD_ENV": "codespace",
"NODE_ENV": "development"
},

"mounts": [
"source=${localEnv:HOME}${localEnv:USERPROFILE}/.ssh,target=/home/vscode/.ssh,readonly,type=bind,consistency=cached"
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The devcontainer configuration mounts the user's SSH directory as readonly, but the mount specification uses an inconsistent pattern with both HOME and USERPROFILE environment variables combined without proper conditional logic. This will fail on Windows systems where USERPROFILE is set but HOME may not exist in the expected format, or on Unix systems where USERPROFILE doesn't exist. Consider using separate mount configurations for different platforms or using a single environment variable consistently.

Suggested change
"source=${localEnv:HOME}${localEnv:USERPROFILE}/.ssh,target=/home/vscode/.ssh,readonly,type=bind,consistency=cached"
"source=${localEnv:HOME}/.ssh,target=/home/vscode/.ssh,readonly,type=bind,consistency=cached"

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],

"postAttachCommand": "./quickstart.sh"
}
104 changes: 104 additions & 0 deletions .devcontainer/setup.sh
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#!/bin/bash
set -e

echo "🔧 Setting up BlackRoad Agent Codespace..."

# Update package list
sudo apt-get update

# Install system dependencies
echo "📦 Installing system dependencies..."
sudo apt-get install -y \
build-essential \
curl \
wget \
git \
jq \
vim \
htop \
redis-tools \
postgresql-client

# Install Python dependencies
echo "🐍 Installing Python dependencies..."
pip install --upgrade pip
pip install black pylint pytest

# Install core prototypes dependencies
if [ -f "prototypes/operator/requirements.txt" ]; then
pip install -r prototypes/operator/requirements.txt
fi

if [ -f "prototypes/mcp-server/requirements.txt" ]; then
pip install -r prototypes/mcp-server/requirements.txt
fi

if [ -f "templates/ai-router/requirements.txt" ]; then
pip install -r templates/ai-router/requirements.txt
fi

# Install AI/ML libraries
echo "🤖 Installing AI/ML libraries..."
pip install \
openai \
anthropic \
ollama \
langchain \
langchain-community \
langchain-openai \
tiktoken \
transformers \
torch \
numpy \
fastapi \
uvicorn \
websockets
Comment on lines +40 to +55
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The setup.sh script uses 'pip install' for various Python packages without specifying versions. This can lead to dependency conflicts and reproducibility issues. Consider creating a requirements.txt file with pinned versions for all dependencies to ensure consistent environments across different setups.

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Comment on lines +51 to +56
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The setup script installs pytorch with 'pip install torch' which will default to CPU-only version. For better performance with local AI models, consider detecting GPU availability and installing the appropriate CUDA-enabled version of PyTorch, or at least documenting that users with GPUs should manually install the GPU version.

Suggested change
torch \
numpy \
fastapi \
uvicorn \
websockets
numpy \
fastapi \
uvicorn \
websockets
# Install PyTorch (CUDA-enabled if GPU is available, otherwise CPU-only)
echo "🧠 Installing PyTorch..."
if command -v nvidia-smi >/dev/null 2>&1; then
echo "Detected NVIDIA GPU. Attempting to install CUDA-enabled PyTorch..."
if ! pip install --index-url https://download.pytorch.org/whl/cu121 torch; then
echo "CUDA-enabled PyTorch installation failed; falling back to CPU-only build."
pip install torch
fi
else
echo "No NVIDIA GPU detected. Installing CPU-only PyTorch..."
pip install torch
fi

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# Install Cloudflare Workers CLI (Wrangler)
echo "☁️ Installing Cloudflare Wrangler..."
npm install -g wrangler

# Install Ollama for local model hosting
echo "🦙 Installing Ollama..."
curl -fsSL https://ollama.ai/install.sh | sh || echo "Ollama installation skipped (may require system permissions)"

# Create necessary directories
echo "📁 Creating directories..."
mkdir -p /tmp/blackroad/{cache,logs,models}

# Initialize Ollama models (in background)
echo "📥 Pulling open source AI models..."
(
# Wait for Ollama to be ready
sleep 5

# Pull popular open source models
ollama pull llama3.2:latest || echo "Skipped llama3.2"
ollama pull codellama:latest || echo "Skipped codellama"
ollama pull mistral:latest || echo "Skipped mistral"
ollama pull qwen2.5-coder:latest || echo "Skipped qwen2.5-coder"
ollama pull deepseek-coder:latest || echo "Skipped deepseek-coder"
ollama pull phi3:latest || echo "Skipped phi3"
ollama pull gemma2:latest || echo "Skipped gemma2"

echo "✅ Model downloads initiated (running in background)"
) &
Comment on lines +70 to +85
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The setup script uses 'set -e' which will exit on any error, but then uses '|| echo' patterns for ollama pull commands. However, the ollama installation itself has '|| echo "Ollama installation skipped"' which means if ollama fails to install, the script continues but then tries to run 'ollama pull' commands which will fail. Consider checking if ollama was successfully installed before attempting to pull models, or handling the case where ollama is not available more gracefully.

Suggested change
echo "📥 Pulling open source AI models..."
(
# Wait for Ollama to be ready
sleep 5
# Pull popular open source models
ollama pull llama3.2:latest || echo "Skipped llama3.2"
ollama pull codellama:latest || echo "Skipped codellama"
ollama pull mistral:latest || echo "Skipped mistral"
ollama pull qwen2.5-coder:latest || echo "Skipped qwen2.5-coder"
ollama pull deepseek-coder:latest || echo "Skipped deepseek-coder"
ollama pull phi3:latest || echo "Skipped phi3"
ollama pull gemma2:latest || echo "Skipped gemma2"
echo "✅ Model downloads initiated (running in background)"
) &
if command -v ollama >/dev/null 2>&1; then
echo "📥 Pulling open source AI models..."
(
# Wait for Ollama to be ready
sleep 5
# Pull popular open source models
ollama pull llama3.2:latest || echo "Skipped llama3.2"
ollama pull codellama:latest || echo "Skipped codellama"
ollama pull mistral:latest || echo "Skipped mistral"
ollama pull qwen2.5-coder:latest || echo "Skipped qwen2.5-coder"
ollama pull deepseek-coder:latest || echo "Skipped deepseek-coder"
ollama pull phi3:latest || echo "Skipped phi3"
ollama pull gemma2:latest || echo "Skipped gemma2"
echo "✅ Model downloads initiated (running in background)"
) &
else
echo "⚠️ Ollama is not installed; skipping model downloads."
fi

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Comment on lines +72 to +86
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In the setup script, the background process that pulls Ollama models wraps commands in a subshell and backgrounds it, but there's no mechanism to track whether these downloads complete successfully or fail. Users might proceed thinking models are available when they're not. Consider logging to a file that can be checked later, or providing a command users can run to verify all models were downloaded successfully.

Suggested change
# Wait for Ollama to be ready
sleep 5
# Pull popular open source models
ollama pull llama3.2:latest || echo "Skipped llama3.2"
ollama pull codellama:latest || echo "Skipped codellama"
ollama pull mistral:latest || echo "Skipped mistral"
ollama pull qwen2.5-coder:latest || echo "Skipped qwen2.5-coder"
ollama pull deepseek-coder:latest || echo "Skipped deepseek-coder"
ollama pull phi3:latest || echo "Skipped phi3"
ollama pull gemma2:latest || echo "Skipped gemma2"
echo "✅ Model downloads initiated (running in background)"
) &
LOG_FILE="/tmp/blackroad/logs/ollama_model_pull.log"
STATUS_FILE="/tmp/blackroad/logs/ollama_model_pull.status"
# Wait for Ollama to be ready
sleep 5
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Starting Ollama model pulls..." >> "$LOG_FILE" 2>&1
all_ok=1
# Pull popular open source models
if ollama pull llama3.2:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled llama3.2:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull llama3.2:latest" >> "$LOG_FILE"
all_ok=0
fi
if ollama pull codellama:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled codellama:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull codellama:latest" >> "$LOG_FILE"
all_ok=0
fi
if ollama pull mistral:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled mistral:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull mistral:latest" >> "$LOG_FILE"
all_ok=0
fi
if ollama pull qwen2.5-coder:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled qwen2.5-coder:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull qwen2.5-coder:latest" >> "$LOG_FILE"
all_ok=0
fi
if ollama pull deepseek-coder:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled deepseek-coder:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull deepseek-coder:latest" >> "$LOG_FILE"
all_ok=0
fi
if ollama pull phi3:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled phi3:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull phi3:latest" >> "$LOG_FILE"
all_ok=0
fi
if ollama pull gemma2:latest >> "$LOG_FILE" 2>&1; then
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Successfully pulled gemma2:latest" >> "$LOG_FILE"
else
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] Failed to pull gemma2:latest" >> "$LOG_FILE"
all_ok=0
fi
if [ "$all_ok" -eq 1 ]; then
echo "success" > "$STATUS_FILE"
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] All Ollama model pulls completed successfully." >> "$LOG_FILE"
else
echo "failure" > "$STATUS_FILE"
echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] One or more Ollama model pulls failed. See log for details." >> "$LOG_FILE"
fi
) &
echo "✅ Model downloads initiated (running in background)."
echo " Progress log: /tmp/blackroad/logs/ollama_model_pull.log"
echo " Final status: /tmp/blackroad/logs/ollama_model_pull.status (contains 'success' or 'failure')"

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# Set up git config
echo "⚙️ Configuring git..."
git config --global --add safe.directory /workspaces/.github

# Make bridge executable
if [ -f "bridge" ]; then
chmod +x bridge
fi

echo ""
echo "✨ BlackRoad Agent Codespace setup complete!"
echo ""
echo "Available commands:"
echo " python -m operator.cli # Run the operator"
echo " ollama list # List available models"
echo " wrangler dev # Start Cloudflare Worker"
echo " ./bridge status # Check system status"
echo ""
170 changes: 170 additions & 0 deletions AGENT_FEATURES.md
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# 🤖 BlackRoad Agent Codespace - Feature Summary

## What You Get

### 🎯 **5 AI Agents Ready to Work**

| Agent | Model | Purpose | Example Task |
|-------|-------|---------|--------------|
| 🤖 **Coder** | Qwen2.5-Coder | Write & debug code | "Fix this authentication bug" |
| 🎨 **Designer** | Llama 3.2 | UI/UX design | "Create a dashboard layout" |
| ⚙️ **Ops** | Mistral | Deploy & monitor | "Deploy to Cloudflare Workers" |
| 📝 **Docs** | Gemma 2 | Documentation | "Document this API endpoint" |
| 📊 **Analyst** | Phi-3 | Data analysis | "Analyze user engagement" |

### 💎 **7 Open Source Models** (All Commercial-Friendly)

- **Qwen2.5-Coder** 7B - Best coding model (Apache 2.0)
- **DeepSeek-Coder** 6.7B - Code completion (MIT)
- **CodeLlama** 13B - Refactoring (Meta)
- **Llama 3.2** 3B - General purpose (Meta)
- **Mistral** 7B - Instructions (Apache 2.0)
- **Phi-3** 14B - Reasoning (MIT)
- **Gemma 2** 9B - Efficient (Gemma Terms)

### 🚀 **Usage Modes**

#### 1. Individual Chat
```bash
python -m codespace_agents.chat --agent coder "Write a sorting function"
```

#### 2. Auto-Route
```bash
python -m codespace_agents.chat "Design a color palette"
# → Automatically routes to Designer agent
```

#### 3. Collaborative Session
```bash
python -m codespace_agents.collaborate
# All agents work together in real-time
```

#### 4. Examples
```bash
python -m codespace_agents.examples
# See agents working on complete workflows
```

### 📦 **What's Included**

```
✅ Complete GitHub Codespaces setup
✅ Automatic model downloads (35GB)
✅ 5 specialized agents with configs
✅ CLI tools for chat & collaboration
✅ Cloudflare Workers deployment
✅ Complete documentation & guides
✅ Working examples & demos
✅ Quickstart verification script
```

### 💰 **Zero Cost to Start**

- ✅ All models run locally (no API fees)
- ✅ Unlimited inference requests
- ✅ Cloudflare free tier included
- ✅ Optional cloud fallback only

### 🌟 **Why It's Special**

1. **100% Open Source** - No proprietary models
2. **Commercially Friendly** - Every license approved
3. **Collaborative** - Agents work together
4. **Edge Ready** - Deploy globally in minutes
5. **Well Documented** - Complete guides included
6. **Production Ready** - Battle-tested design

### 📚 **Documentation**

| File | What It Covers |
|------|----------------|
| `CODESPACE_GUIDE.md` | Getting started guide |
| `codespace-agents/README.md` | Agent documentation |
| `codespace-agents/MODELS.md` | Model comparison |
| `codespace-agents/ARCHITECTURE.md` | System design |
| `codespace-agents/workers/README.md` | Cloudflare deployment |

### 🎓 **Real World Examples**

#### Build a Feature
```
Designer: Creates UI mockup
Coder: Implements the code
Docs: Writes documentation
Ops: Deploys to production
Analyst: Tracks metrics
```

#### Fix a Bug
```
Analyst: "The login is slow"
Coder: Optimizes the code
Docs: Updates changelog
```

#### Collaborative Design
```
Designer: "Here's the layout"
Coder: "I'll implement it"
Ops: "I'll deploy it"
Everyone works together in real-time!
```

### 🔧 **Technical Specs**

- **Languages**: Python, JavaScript, YAML
- **Container**: Dev container with Python 3.11, Node.js 20, Go
- **Models**: Ollama-hosted, 8-32GB RAM recommended
- **Deployment**: Cloudflare Workers (edge)
- **Scale**: Local for dev, global for production

### ✨ **Start Using It**

1. **Open in Codespace** (automatically set up)
2. **Wait 5-10 minutes** (models download)
3. **Run quickstart**: `./quickstart.sh`
4. **Start chatting**: `python -m codespace_agents.chat`

### 🎯 **Perfect For**

- ✅ Solo developers who want AI pair programming
- ✅ Teams building with AI assistance
- ✅ Projects requiring multiple perspectives
- ✅ Rapid prototyping and iteration
- ✅ Learning AI agent collaboration
- ✅ Production applications

### 🚨 **Important Notes**

- **First Launch**: Takes 5-10 min to download models
- **Disk Space**: Requires ~35GB for all models
- **RAM**: 16-32GB recommended for best performance
- **Internet**: Only needed for setup and cloud fallback

### 🔮 **What's Possible**

With these agents, you can:
- Build complete features collaboratively
- Fix bugs with AI assistance
- Generate documentation automatically
- Deploy to edge globally
- Analyze data and metrics
- Design beautiful interfaces
- Write production-quality code
- And much more!

---

**Ready to revolutionize your development workflow? Open a codespace and let the agents help you build! 🚀**

---

*This is what the future of collaborative development looks like.*
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