- name
- pi-orchestration
- description
- Orchestrate multiple AI models (GLM, MiniMax, etc.) as workers using Pi Coding Agent with Claude as coordinator.
- homepage
- https://github.com/mariozechner/pi-coding-agent
- metadata
- {"clawdis":{"emoji":"🎭","requires":{"bins":["pi"]}}}
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
export GLM_API_KEY="your-glm-api-key"2. MiniMax
Get API key from api.minimax.chat
export MINIMAX_API_KEY="your-minimax-api-key"
export MINIMAX_GROUP_ID="your-group-id" # Required for MiniMaxUsage
Direct Commands
# 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 workdir:/tmp/task background:true command:"pi --provider glm --model glm-4.7 -p 'Build feature X'"Parallel Army (tmux)
# 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 -pMap-Reduce Pattern
# 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
doneOrchestration Script
# 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 collectBest Practices
- Task Decomposition: Break large tasks into independent subtasks
- Model Selection: Use GLM for Chinese content, MiniMax for creative tasks
- Error Handling: Check worker status before collecting results
- Resource Management: Clean up tmux sessions after completion
Example: Parallel Code Review
# 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
doneNotes
- 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