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New `sheet-music-ocr review` command that sends MusicXML output to an LLM (Claude or OpenAI, configurable via --provider flag) for reviewing and fixing common OCR errors like incorrect pitches, rhythms, key signatures, and garbled lyrics. Uses httpx for direct API calls. https://claude.ai/code/session_017GqUbuRDT58toRaxMtfRmf
127 lines
3.6 KiB
Python
127 lines
3.6 KiB
Python
"""LLM-based MusicXML review and correction.
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Supports both Claude (Anthropic) and OpenAI APIs for reviewing
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MusicXML output from Audiveris and suggesting/applying fixes.
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"""
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from __future__ import annotations
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import enum
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import os
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from typing import TYPE_CHECKING
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import httpx
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if TYPE_CHECKING:
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from pathlib import Path
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REVIEW_PROMPT = """\
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You are a music notation expert. Review the following MusicXML file produced by \
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optical music recognition (Audiveris). Look for and fix common OCR errors including:
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- Incorrect note pitches or durations
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- Wrong or missing key signatures, time signatures, or clefs
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- Incorrect rest durations or placements
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- Missing or incorrect accidentals
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- Wrong beam groupings or tuplets
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- Garbled or misspelled lyrics and text annotations
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- Missing or incorrect dynamic markings
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- Incorrect measure numbers or barline types
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- Voice/staff assignment errors
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Return ONLY the corrected MusicXML. Do not include any explanation, commentary, or \
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markdown formatting. Output the raw XML directly.
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Here is the MusicXML to review:
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"""
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_TIMEOUT = 300
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class LLMProvider(enum.StrEnum):
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"""Supported LLM providers."""
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CLAUDE = "claude"
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OPENAI = "openai"
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class ReviewError(Exception):
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"""Raised when LLM review fails."""
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def _get_api_key(provider: LLMProvider) -> str:
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env_var = "ANTHROPIC_API_KEY" if provider == LLMProvider.CLAUDE else "OPENAI_API_KEY"
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key = os.environ.get(env_var)
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if not key:
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msg = f"{env_var} environment variable is not set."
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raise ReviewError(msg)
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return key
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def _call_claude(content: str, api_key: str) -> str:
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response = httpx.post(
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"https://api.anthropic.com/v1/messages",
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headers={
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"x-api-key": api_key,
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"anthropic-version": "2023-06-01",
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"content-type": "application/json",
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},
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json={
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"model": "claude-sonnet-4-20250514",
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"max_tokens": 16384,
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"messages": [{"role": "user", "content": REVIEW_PROMPT + content}],
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},
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timeout=_TIMEOUT,
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)
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if response.status_code != 200: # noqa: PLR2004
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msg = f"Claude API error ({response.status_code}): {response.text}"
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raise ReviewError(msg)
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data = response.json()
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return data["content"][0]["text"]
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def _call_openai(content: str, api_key: str) -> str:
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response = httpx.post(
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"https://api.openai.com/v1/chat/completions",
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headers={
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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},
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json={
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"model": "gpt-4o",
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"messages": [{"role": "user", "content": REVIEW_PROMPT + content}],
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"max_tokens": 16384,
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},
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timeout=_TIMEOUT,
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)
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if response.status_code != 200: # noqa: PLR2004
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msg = f"OpenAI API error ({response.status_code}): {response.text}"
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raise ReviewError(msg)
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data = response.json()
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return data["choices"][0]["message"]["content"]
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def review_mxml(mxml_path: Path, provider: LLMProvider) -> str:
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"""Review a MusicXML file using an LLM and return corrected content.
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Args:
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mxml_path: Path to the .mxml file to review.
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provider: Which LLM provider to use.
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Returns:
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The corrected MusicXML content as a string.
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Raises:
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ReviewError: If the API call fails or the key is missing.
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FileNotFoundError: If the input file does not exist.
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"""
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content = mxml_path.read_text(encoding="utf-8")
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api_key = _get_api_key(provider)
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if provider == LLMProvider.CLAUDE:
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return _call_claude(content, api_key)
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return _call_openai(content, api_key)
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