pi-orchestration

# Pi Orchestration Use Claude as an orchestrator to spawn and coordinate multiple AI model workers (GLM, MiniMax, etc.) via Pi Coding Agent. ## Supported Providers | Provider | Model | Status | |----------|-------|--------| | **GLM** | glm-4.7 | ✅ Working | | **MiniMax** | MiniMax-M2.1 | ✅ Working | | OpenAI | gpt-4o, etc. | ✅ Working | | Anthropic | claude-* | ✅ Working | ## Setup ### 1. GLM (Zhipu AI) Get API key from [open.bigmodel.cn](https://open.bigmodel.cn/) ```bash export GLM_API_KEY="your-glm-api-key" ``` ### 2. MiniMax Get API key from [api.minimax.chat](https://api.minimax.chat/) ```bash export MINIMAX_API_KEY="your-minimax-api-key" export MINIMAX_GROUP_ID="your-group-id" # Required for MiniMax ``` ## Usage ### Direct Commands ```bash # GLM-4.7 pi --provider glm --model glm-4.7 -p "Your task" # MiniMax M2.1 pi --provider minimax --model MiniMax-M2.1 -p "Your task" # Test connectivity pi --provider glm --model glm-4.7 -p "Say hello" ``` ### Orchestration Patterns Claude (Opus) can spawn these as background workers: #### Background Worker ```bash bash workdir:/tmp/task background:true command:"pi --provider glm --model glm-4.7 -p 'Build feature X'" ``` #### Parallel Army (tmux) ```bash # Create worker sessions tmux new-session -d -s worker-1 tmux new-session -d -s worker-2 # Dispatch tasks tmux send-keys -t worker-1 "pi --provider glm --model glm-4.7 -p 'Task 1'" Enter tmux send-keys -t worker-2 "pi --provider minimax --model MiniMax-M2.1 -p 'Task 2'" Enter # Check progress tmux capture-pane -t worker-1 -p tmux capture-pane -t worker-2 -p ``` #### Map-Reduce Pattern ```bash # Map: Distribute subtasks to workers for i in 1 2 3; do tmux send-keys -t worker-$i "pi --provider glm --model glm-4.7 -p 'Process chunk $i'" Enter done # Reduce: Collect and combine results for i in 1 2 3; do tmux capture-pane -t worker-$i -p >> /tmp/results.txt done ``` ## Orchestration Script ```bash # Quick orchestration helper uv run {baseDir}/scripts/orchestrate.py spawn --provider glm --model glm-4.7 --task "Build a REST API" uv run {baseDir}/scripts/orchestrate.py status uv run {baseDir}/scripts/orchestrate.py collect ``` ## Best Practices 1. **Task Decomposition**: Break large tasks into independent subtasks 2. **Model Selection**: Use GLM for Chinese content, MiniMax for creative tasks 3. **Error Handling**: Check worker status before collecting results 4. **Resource Management**: Clean up tmux sessions after completion ## Example: Parallel Code Review ```bash # Claude orchestrates 3 workers to review different files tmux send-keys -t worker-1 "pi --provider glm -p 'Review auth.py for security issues'" Enter tmux send-keys -t worker-2 "pi --provider minimax -p 'Review api.py for performance'" Enter tmux send-keys -t worker-3 "pi --provider glm -p 'Review db.py for SQL injection'" Enter # Wait and collect sleep 30 for i in 1 2 3; do echo "=== Worker $i ===" >> review.md tmux capture-pane -t worker-$i -p >> review.md done ``` ## Notes - Pi Coding Agent must be installed: `npm install -g @anthropic/pi-coding-agent` - GLM and MiniMax have generous free tiers - Claude acts as coordinator, workers do the heavy lifting - Combine with process tool for background task management