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利用 jev 刮削音乐元数据,风格,语言
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CommunityJev Tools & CLIs
Jev Music Tag
Minimal Jev metadata workbench for local music files: a FastAPI backend sends track metadata and scoring questions to TypeSafe Jev and can write the chosen genre or language back with Mutagen, behind a small React page for editing prompts and questions.
- Stars
- 6
- Language
- Python
- Reading time
- 3 min
- Published by
- Community
- Author
- xhongc
- Last verified
- Oct 2026
- Languages
- PythonJavaScript
- Platforms
- API
- Capabilities
- Open sourceRequires API key
Highlights
- FastAPI POST /api/decide sends track metadata plus scoring questions to TypeSafe Jev's systemone endpoint and returns metadata_updates ready to write back.
- Mutagen reads and writes tags on MP3, FLAC and M4A files on the server; separate POST /api/read and POST /api/write endpoints handle tags directly.
- Empty values are stripped and album_img excluded before anything reaches the model; only allowlisted writable metadata fields can be a target_field.
- The React page is a capsule-style workbench where you edit the JSON, prompt and question configuration; the server picks the top probability or score.
- Config lives in .env: JEV_API_KEY is required and server-side, JEV_BASE_URL defaults to api.typesafe.ai and JEV_MODEL_NAME to jev-latest.
Quickstart
bash
cp .env.example .env
uv sync
uv run uvicorn backend.main:app --reload --port 8000Watch out
Copy reviewed against the Chinese README on 2026-10-15; an English README.en.md is linked. The README itself calls this a minimal demo: no database, login or batch scanning, and production use would need auth, a path allowlist, log redaction and rate limiting. GitHub metadata lists no license, and typed file paths refer to the server machine.
Questions about this entry
Short answers drawn from the linked project or page.
A minimal Jev metadata decision workbench for local music. It sends track metadata and score questions to TypeSafe Jev's systemone endpoint, returns suggested fields such as genre, and can write the chosen values back into the audio file. One FastAPI endpoint and one React page, designed for validating decision prompts and field mapping.
Copy .env.example to .env and fill JEV_API_KEY, run uv sync, then uv run uvicorn backend.main:app --reload --port 8000. The README insists on uv run rather than a system uvicorn so declared dependencies like mutagen load. In another terminal: npm install and npm run dev in frontend/, opening http://localhost:5173.
MP3, FLAC and M4A files on the server, per the README. Mutagen reads the tags from those files and writes the decision results back to the originals; separate POST /api/read and POST /api/write endpoints handle tags directly if you want to drive it yourself.
No. The README lists the boundaries: no database, no login and no batch file scanning. You point it at files one at a time, and the file path typed into the frontend is a path on the FastAPI machine, not the browser's machine.
The metadata fields you provide, a prompt, and question definitions. The backend strips empty values and excludes album_img before sending, and only allowlisted writable metadata fields can be used as a target_field, so unrelated content should not reach the model.
You define typed questions — the README's example is a score question for genre with criteria Pop, Rock and Soundtrack — and the server picks the highest entry from Jev's probabilities or score, returning metadata_updates. Clicking write saves those updates back to the file.
No; the README calls it a minimal demo. Before production it says you should add authentication, a path allowlist, log redaction and rate limiting, and it keeps the JEV_API_KEY server-side so it never reaches the browser. GitHub metadata lists no license for the repository.
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