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Master AI Music Autonomously

Automation system for Suno music creation, mastering, and export using a hybrid architecture:

  • deterministic browser skills for reliable execution
  • planner-driven orchestration for autonomous runs
  • optional AI-assisted spec generation

Current Focus (Build Now)

We are actively building and hardening the in-repo hybrid autopilot:

  • input: high-level music_type
  • auto-generate: lyrics, styles, weirdness, style influence
  • execute: create -> wait -> master -> export
  • resilience: retries, checkpoint/resume, phase artifacts

Local Model Defaults

Project defaults are configured for local Ollama:

  • provider: ollama
  • default model: qwen3:8b
  • fast fallback option: qwen3:0.6b

Example:

cd suno_mastering_agent
source venv/bin/activate
python main.py autopilot --music-type "edm" --count 3

Phase 2 planning mode (parallel candidates + artifacts):

python main.py autopilot \
  --music-type "edm" \
  --count 3 \
  --phase2 \
  --candidate-count 4 \
  --phase2-artifact-log /tmp/suno_phase2_artifacts.jsonl

Resumable robust mode:

python main.py autopilot \
  --music-type "edm" \
  --count 20 \
  --step-retries 3 \
  --checkpoint-file /tmp/suno_autopilot_checkpoint.json \
  --resume \
  --continue-on-error

Future Features (Not Active Dependencies Yet)

These are tracked as future enhancements, not required for the current build:

Decision: we will keep using lightweight in-repo equivalents first, then consider full external adoption once execution reliability is consistently strong.

Project Layout

  • suno_mastering_agent/main.py - CLI entry point (autopilot, autocreate, agent, etc.)
  • suno_mastering_agent/src/skills/ - deterministic browser action primitives
  • suno_mastering_agent/src/agents/ - composed automation runners
  • suno_mastering_agent/src/agent/ - LLM/tool workflows
  • suno_mastering_agent/src/ui/ - Gradio UI

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Master your AI song autonomously on web UI

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