技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
llm-synthesis【数据与研究】Use SDGX SingleTableGPTModel for OpenAI-compatible tabular generation, metadata-only synthesis, raw-data prompting, off-table features, and offline response parsing.
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Use this sub-skill when the task mentions SingleTableGPTModel, OpenAI/GPT tabular synthetic data, metadata-only generation without real rows, off-table feature inference, response parsing, OPENAI_KEY, or OPENAI_URL.
Use ../single-table-synthesis/SKILL.md for CTGAN/GaussianCopula or CLI fit/sample workflows. Use ../data-preparation/SKILL.md first when the metadata itself is the blocker.
python sub-skills/llm-synthesis/scripts/inspect_llm_settings.py --json
DataLoader, or a Metadata object.SingleTableGPTModel, set dataset_description and off_table_features if needed, and call fit(...).set_openAI_settings.check() can pass.Read references/gpt-model-workflow.md for API details and offline parsing patterns.
openai_API_url: https://api.openai.com/v1/.gpt_model: gpt-3.5-turbo in the inspected source.max_tokens: 4000; temperature: 0.1; timeout: 90; query_batch: 30.OPENAI_KEY and OPENAI_URL are read from the environment at initialization.off_table_features can request new columns inferred from existing rows/metadata.Read references/troubleshooting.md for missing API keys, base URL mistakes, token limits, raw-data privacy, response parsing, and off-table feature failures.