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Web app for creating, editing, and validating JSONL fine-tuning datasets. Checks format compliance for OpenAI, Anthropic, and Llama formats, detects duplicates, scores quality, and exports clean datasets.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | finetune-data-curator |
| description | Web app for creating, editing, and validating JSONL fine-tuning datasets. Checks format compliance for OpenAI, Anthropic, and Llama formats, detects duplicates, scores quality, and exports clean datasets. |
| triggers | ["fine-tune dataset","jsonl curator","training data","finetune data","dataset quality","llm training dataset","jsonl validation"] |
Use this skill when you need to:
cd finetune-data-curator
cp .env.example .env
# edit .env: set ADMIN_KEY=<secure random string> and DATA_DIR=./data
pnpm install
pnpm dev # server + SPA on :4400
Open http://localhost:4400.
ADMIN_KEY=mysecretkey docker compose up
# App: http://localhost:4400
Via the web UI: click "New Dataset", choose a format (OpenAI, Anthropic, or Llama), name it.
Via API:
curl -X POST http://localhost:4400/api/datasets \
-H "X-Admin-Key: $ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{"name": "my-dataset", "format": "openai"}'
Via the web UI: open a dataset, click Import, paste JSONL or upload a file.
Via API:
curl -X POST http://localhost:4400/api/datasets/ds_abc/samples \
-H "X-Admin-Key: $ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '[{"messages": [{"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi!"}]}]'
Via the web UI: open a dataset, click "Run Validation".
Via API:
curl -X POST http://localhost:4400/api/datasets/ds_abc/validate \
-H "X-Admin-Key: $ADMIN_KEY"
Validation checks: format compliance, missing fields, empty content, excessive length, degenerate samples.
curl -X POST http://localhost:4400/api/datasets/ds_abc/dedup \
-H "X-Admin-Key: $ADMIN_KEY"
Returns pairs with Jaccard similarity above the configured threshold (default 0.8).
curl -X POST http://localhost:4400/api/datasets/ds_abc/split \
-H "X-Admin-Key: $ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{"ratio": 0.8, "seed": 42}'
Creates ds_abc.train.jsonl (80%) and ds_abc.eval.jsonl (20%).
# Download as OpenAI format
curl "http://localhost:4400/api/datasets/ds_abc/export?format=openai" \
-H "X-Admin-Key: $ADMIN_KEY" \
-o my-dataset.jsonl
# Convert to Anthropic format on export
curl "http://localhost:4400/api/datasets/ds_abc/export?format=anthropic" \
-H "X-Admin-Key: $ADMIN_KEY" \
-o my-dataset-anthropic.jsonl
# Export train split only
curl "http://localhost:4400/api/datasets/ds_abc/export?format=openai&split=train" \
-H "X-Admin-Key: $ADMIN_KEY" \
-o train.jsonl
| Variable | Default | Description |
|---|---|---|
PORT | 4400 | Server listen port |
DATA_DIR | ./data | Directory for JSONL files and index.json |
ADMIN_KEY | (required) | Header value required for write operations |
MAX_UPLOAD_MB | 50 | Maximum upload file size |
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