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474 lines
17 KiB
Python
474 lines
17 KiB
Python
#!/usr/bin/env python3
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# /// script
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# requires-python = ">=3.10"
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# dependencies = []
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# ///
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"""
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Map feedback dimension categories to Suno parameter adjustment recommendations.
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Takes structured feedback dimensions (from parse-feedback.py or LLM triage)
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and returns baseline parameter adjustment recommendations as structured JSON.
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The LLM then refines these recommendations with contextual judgment.
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Exit codes:
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0 = adjustments generated successfully
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1 = invalid input
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2 = runtime error
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"""
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import argparse
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import json
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import sys
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from pathlib import Path
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from typing import Any
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent / "_shared"))
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from suno_constants import CRITICAL_ZONE, EXCLUSION_RECOMMENDED_MAX, PAID_TIERS
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# Adjustment lookup tables
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# Each dimension maps to a set of possible adjustments categorized by direction
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STYLE_PROMPT_ADJUSTMENTS: dict[str, dict[str, dict[str, Any]]] = {
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"instrumentation": {
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"too_much": {
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"add": ["minimal arrangement", "sparse instrumentation", "stripped-back"],
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"remove_patterns": ["lush", "layered", "full", "dense", "wall of sound"],
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"exclude_add": ["no dense layering"],
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},
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"too_little": {
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"add": ["lush arrangement", "layered instrumentation", "full sound"],
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"remove_patterns": ["minimal", "sparse", "stripped"],
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"exclude_add": [],
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},
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"wrong_type": {
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"add": [],
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"remove_patterns": [],
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"exclude_add": [],
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"note": "Specify the unwanted instrument in exclusions and desired instrument in style prompt",
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},
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},
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"vocals": {
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"too_polished": {
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"add": ["raw vocal", "imperfect delivery", "organic phrasing"],
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"remove_patterns": ["polished", "clean vocal", "perfect"],
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"exclude_add": ["no overproduced vocals"],
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},
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"too_rough": {
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"add": ["polished vocal", "smooth delivery", "clean singing"],
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"remove_patterns": ["raw", "rough", "gritty"],
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"exclude_add": ["no raspy vocals"],
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},
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"too_quiet": {
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"add": ["prominent vocals", "voice-forward mix"],
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"remove_patterns": [],
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"exclude_add": [],
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},
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"too_loud": {
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"add": ["balanced mix", "instrument-forward"],
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"remove_patterns": ["prominent vocal", "voice-forward"],
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"exclude_add": [],
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},
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"wrong_character": {
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"add": [],
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"remove_patterns": [],
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"exclude_add": [],
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"note": "Specify desired vocal character: gender, age, tone, delivery style",
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},
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},
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"energy": {
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"too_high": {
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"add": ["gentle", "soft", "understated", "subtle"],
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"remove_patterns": ["high energy", "powerful", "driving", "intense"],
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"exclude_add": [],
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"slider": {"weirdness": "unchanged", "style_influence": "unchanged"},
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},
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"too_low": {
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"add": ["high energy", "powerful", "dynamic", "driving"],
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"remove_patterns": ["gentle", "soft", "subtle", "laid-back"],
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"exclude_add": [],
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"slider": {"style_influence": "decrease_slightly"},
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},
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"flat": {
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"add": ["dynamic shifts", "building energy", "crescendo", "varied sections"],
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"remove_patterns": [],
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"exclude_add": [],
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"slider": {"weirdness": "increase_slightly"},
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},
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},
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"tempo": {
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"too_fast": {
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"add": ["slow tempo", "laid-back", "relaxed groove"],
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"remove_patterns": ["uptempo", "fast", "driving rhythm", "energetic pace"],
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"exclude_add": [],
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},
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"too_slow": {
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"add": ["uptempo", "driving rhythm", "energetic pace"],
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"remove_patterns": ["slow", "laid-back", "relaxed", "gentle pace"],
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"exclude_add": [],
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},
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},
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"production": {
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"too_polished": {
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"add": ["lo-fi", "raw production", "analog warmth", "rough edges"],
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"remove_patterns": ["radio-ready", "clean production", "crisp", "polished"],
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"exclude_add": [],
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"slider": {"weirdness": "increase"},
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},
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"too_rough": {
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"add": ["radio-ready mix", "clean production", "crisp", "polished"],
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"remove_patterns": ["lo-fi", "raw", "rough", "analog"],
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"exclude_add": [],
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"slider": {"weirdness": "decrease"},
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},
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"too_reverb": {
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"add": ["dry mix", "close mic", "intimate"],
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"remove_patterns": ["spacious", "reverb", "ambient", "atmospheric"],
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"exclude_add": [],
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},
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"too_dry": {
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"add": ["spacious", "reverb", "ambient", "atmospheric"],
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"remove_patterns": ["dry", "close mic"],
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"exclude_add": [],
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},
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},
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"vibe": {
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"too_happy": {
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"add": ["melancholic", "bittersweet", "minor key", "moody"],
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"remove_patterns": ["uplifting", "bright", "happy", "cheerful", "major key"],
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"exclude_add": [],
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},
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"too_dark": {
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"add": ["uplifting", "bright", "major key", "hopeful"],
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"remove_patterns": ["melancholic", "dark", "moody", "minor key"],
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"exclude_add": [],
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},
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"too_generic": {
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"add": ["distinctive", "unique", "unconventional"],
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"remove_patterns": ["classic", "traditional", "conventional"],
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"exclude_add": [],
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"slider": {"weirdness": "increase_significantly"},
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},
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"too_weird": {
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"add": ["familiar", "classic", "conventional", "straightforward"],
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"remove_patterns": ["experimental", "unexpected", "unconventional"],
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"exclude_add": [],
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"slider": {"weirdness": "decrease_significantly"},
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},
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},
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"music": {
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"general_issue": {
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"add": [],
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"remove_patterns": [],
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"exclude_add": [],
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"note": "Music feedback requires further narrowing — which aspect of the music? Instrumentation, tempo, energy, production?",
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},
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},
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"structure": {
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"needs_bridge": {
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"lyric_change": "Add [Bridge] section between second chorus and outro",
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},
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"chorus_weak": {
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"lyric_change": "Add [Energy: High] before chorus, consider [Build-Up] section",
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},
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"too_long": {
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"lyric_change": "Remove repeated sections or shorten verses",
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},
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"too_short": {
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"lyric_change": "Add additional verse or extend instrumental sections",
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},
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},
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"lyrics": {
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"phrasing_unnatural": {
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"lyric_change": "Run syllable counter, normalize line lengths within sections",
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},
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"content_mismatch": {
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"lyric_change": "Review lyrics against intended mood/theme, revise for alignment",
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},
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"vocal_style_inconsistent": {
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"lyric_change": "Add consistent [Vocal Style: ...] tags before each section",
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},
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},
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"quality": {
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"artifacts": {
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"note": "Audio artifacts are generation-specific. Regenerate 3-5 times before modifying prompt. If persistent, simplify style prompt.",
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},
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"robotic_vocals": {
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"add": ["natural vocal", "organic phrasing", "human delivery", "breathy"],
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"remove_patterns": [],
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"exclude_add": ["no auto-tune", "no robotic vocals"],
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},
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"clipping": {
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"add": ["clean mix", "dynamic range", "headroom"],
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"remove_patterns": ["heavy", "distorted", "loud", "wall of sound"],
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"exclude_add": [],
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},
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"muffled": {
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"add": ["crisp", "clear mix", "defined frequencies", "bright"],
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"remove_patterns": ["warm", "lo-fi", "analog"],
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"exclude_add": [],
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},
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},
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"length": {
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"too_short": {
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"lyric_change": "Add sections in lyrics (additional verse, bridge, instrumental break) or use Suno extend feature",
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},
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"too_long": {
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"lyric_change": "Remove repeated sections, trim [Outro] content, remove non-essential [Breakdown]",
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},
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"intro_too_long": {
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"lyric_change": "Shorten or remove [Intro] content, add [Verse 1] tag earlier",
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},
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"outro_cuts_off": {
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"lyric_change": "Add explicit [Outro] section with 2-4 lines, add [Fade Out] metatag",
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},
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"pacing_drags": {
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"lyric_change": "Add [Energy: building] metatags, shorten dragging sections, add [Breakdown] or [Build-Up] for variety",
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},
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},
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}
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SLIDER_DIRECTION_MAP = {
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"increase_slightly": "+5-10 from current",
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"increase": "+15-20 from current",
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"increase_significantly": "+25-35 from current (cap at 85)",
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"decrease_slightly": "-5-10 from current",
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"decrease": "-15-20 from current",
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"decrease_significantly": "-25-35 from current (floor at 15)",
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"unchanged": "no change recommended",
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}
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def generate_adjustments(
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dimensions: list[dict[str, str]],
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current_tier: str = "",
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) -> dict[str, Any]:
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"""Generate adjustment recommendations from feedback dimensions."""
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style_add: list[str] = []
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style_remove: list[str] = []
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exclude_add: list[str] = []
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slider_adjustments: dict[str, str] = {}
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lyric_changes: list[str] = []
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notes: list[str] = []
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for dim_entry in dimensions:
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dimension = dim_entry.get("dimension", "")
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direction = dim_entry.get("direction", "")
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if dimension not in STYLE_PROMPT_ADJUSTMENTS:
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notes.append(f"Unknown dimension '{dimension}' — requires LLM judgment")
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continue
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dim_adjustments = STYLE_PROMPT_ADJUSTMENTS[dimension]
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if direction not in dim_adjustments:
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available = list(dim_adjustments.keys())
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notes.append(
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f"Unknown direction '{direction}' for dimension '{dimension}'. "
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f"Available: {', '.join(available)}"
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)
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continue
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adj = dim_adjustments[direction]
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if "add" in adj:
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style_add.extend(adj["add"])
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if "remove_patterns" in adj:
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style_remove.extend(adj["remove_patterns"])
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if "exclude_add" in adj:
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exclude_add.extend(adj["exclude_add"])
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if "slider" in adj:
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for slider_name, slider_dir in adj["slider"].items():
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slider_adjustments[slider_name] = SLIDER_DIRECTION_MAP.get(
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slider_dir, slider_dir
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)
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if "lyric_change" in adj:
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lyric_changes.append(adj["lyric_change"])
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if "note" in adj:
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notes.append(adj["note"])
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is_paid = current_tier.lower() in PAID_TIERS if current_tier else False
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result: dict[str, Any] = {
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"style_prompt": {
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"add_descriptors": list(dict.fromkeys(style_add)), # dedupe preserving order
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"remove_patterns": list(dict.fromkeys(style_remove)),
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},
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"exclusions": {
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"add": list(dict.fromkeys(exclude_add)),
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},
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}
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if slider_adjustments:
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if is_paid:
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result["sliders"] = slider_adjustments
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else:
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result["sliders"] = {
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"note": "Slider adjustments recommended but not available on free tier. Compensate through style prompt wording.",
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"recommended_if_upgraded": slider_adjustments,
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}
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if lyric_changes:
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result["lyrics"] = {"changes": lyric_changes}
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if notes:
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result["notes"] = notes
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consistency_warnings = check_adjustment_consistency(result)
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if consistency_warnings:
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if "notes" not in result:
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result["notes"] = []
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result["consistency_warnings"] = consistency_warnings
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return result
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def check_adjustment_consistency(adjustments: dict[str, Any]) -> list[dict[str, Any]]:
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"""Check for internal contradictions in adjustment recommendations."""
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warnings = []
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style_add = set(adjustments.get("style_prompt", {}).get("add_descriptors", []))
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style_remove = set(adjustments.get("style_prompt", {}).get("remove_patterns", []))
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exclude_add = set(adjustments.get("exclusions", {}).get("add", []))
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# Check for add/remove conflicts
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conflicts = style_add & style_remove
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if conflicts:
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warnings.append({
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"type": "add_remove_conflict",
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"detail": f"Descriptors appear in both add and remove: {', '.join(conflicts)}",
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})
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# Check for add/exclude conflicts
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for add_desc in style_add:
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for excl in exclude_add:
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# Simple substring check
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if add_desc.lower() in excl.lower() or excl.replace("no ", "").lower() in add_desc.lower():
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warnings.append({
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"type": "add_exclude_conflict",
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"detail": f"Adding '{add_desc}' conflicts with exclusion '{excl}'",
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})
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# Check style prompt estimated length
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total_add_chars = sum(len(d) + 2 for d in style_add) # +2 for ", " separator
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if total_add_chars > CRITICAL_ZONE:
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warnings.append({
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"type": "critical_zone_overflow",
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"detail": f"Added descriptors total ~{total_add_chars} chars — prioritize most important for the first {CRITICAL_ZONE} chars of style prompt (critical zone)",
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})
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# Check exclusion estimated length
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total_excl_chars = sum(len(e) + 2 for e in exclude_add)
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if total_excl_chars > EXCLUSION_RECOMMENDED_MAX:
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warnings.append({
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"type": "exclusion_overflow",
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"detail": f"Exclusion additions total ~{total_excl_chars} chars — keep total exclusions under ~{EXCLUSION_RECOMMENDED_MAX} chars, prioritize 2-3 most important",
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})
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return warnings
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def main():
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parser = argparse.ArgumentParser(
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description="Map feedback dimensions to Suno parameter adjustment recommendations.",
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epilog="""
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Input JSON schema:
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Required:
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dimensions (array of objects) - Each with:
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dimension (string) - Feedback dimension (instrumentation, vocals, energy, tempo, production, vibe, music, structure, lyrics)
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direction (string) - Direction of the issue within the dimension
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Optional:
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tier (string) - User's Suno tier (free, pro, premier) — affects slider recommendations
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Dimension/Direction combinations:
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instrumentation: too_much, too_little, wrong_type
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vocals: too_polished, too_rough, too_quiet, too_loud, wrong_character
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energy: too_high, too_low, flat
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tempo: too_fast, too_slow
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production: too_polished, too_rough, too_reverb, too_dry
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vibe: too_happy, too_dark, too_generic, too_weird
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music: general_issue
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structure: needs_bridge, chorus_weak, too_long, too_short
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lyrics: phrasing_unnatural, content_mismatch, vocal_style_inconsistent
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Example:
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echo '{"dimensions": [{"dimension": "vocals", "direction": "too_polished"}, {"dimension": "energy", "direction": "too_low"}], "tier": "pro"}' | python3 map-adjustments.py --stdin
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""",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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)
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input_group = parser.add_mutually_exclusive_group(required=True)
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input_group.add_argument("--input", "-i", help="Path to dimensions JSON file")
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input_group.add_argument("--stdin", action="store_true", help="Read JSON from stdin")
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parser.add_argument("--output", "-o", help="Output file path (default: stdout)")
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parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output to stderr")
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args = parser.parse_args()
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try:
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if args.stdin:
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raw = sys.stdin.read()
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else:
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with open(args.input, "r") as f:
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raw = f.read()
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data = json.loads(raw)
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except (json.JSONDecodeError, FileNotFoundError) as e:
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print(json.dumps({
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"script": "map-adjustments",
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"version": "1.0.0",
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"status": "fail",
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"findings": [{
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"severity": "critical",
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"category": "structure",
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"issue": str(e),
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"fix": "Provide valid JSON input",
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}],
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"summary": {"total": 1, "critical": 1, "high": 0, "medium": 0, "low": 0},
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}, indent=2))
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sys.exit(1)
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if not isinstance(data, dict) or "dimensions" not in data:
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print(json.dumps({
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"script": "map-adjustments",
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"version": "1.0.0",
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"status": "fail",
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"findings": [{
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"severity": "critical",
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"category": "structure",
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"issue": "Input must be a JSON object with a 'dimensions' array",
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"fix": 'Provide {"dimensions": [{"dimension": "...", "direction": "..."}]}',
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}],
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"summary": {"total": 1, "critical": 1, "high": 0, "medium": 0, "low": 0},
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}, indent=2))
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sys.exit(1)
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dimensions = data["dimensions"]
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tier = data.get("tier", "")
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adjustments = generate_adjustments(dimensions, tier)
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result = {
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"script": "map-adjustments",
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"version": "1.0.0",
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"status": "pass",
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"adjustments": adjustments,
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"input_dimensions": len(dimensions),
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"findings": [],
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"summary": {"total": 0, "critical": 0, "high": 0, "medium": 0, "low": 0},
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}
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if args.verbose:
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print(f"[map-adjustments] Processed {len(dimensions)} dimensions", file=sys.stderr)
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output_json = json.dumps(result, indent=2)
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if args.output:
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with open(args.output, "w") as f:
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f.write(output_json)
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else:
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print(output_json)
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sys.exit(0)
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if __name__ == "__main__":
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main()
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