| --- |
| license: apache-2.0 |
| language: [en] |
| task_categories: [text-generation] |
| tags: [text-to-sql, oracle, accounts-payable, sql, chat] |
| pretty_name: AP Text-to-SQL (Oracle) PEFT dataset |
| size_categories: [1K<n<10K] |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: train.jsonl |
| - split: validation |
| path: val.jsonl |
| - split: test |
| path: test.jsonl |
| --- |
| |
| # ap-sql-peft |
|
|
| A chat-format text-to-SQL dataset for Accounts Payable analytics on Oracle. The schema is modelled on Oracle Fusion |
| AP, Payments and Supplier tables, and the data behind it is synthetic. The dataset was used to train the LoRA adapter |
| [`samrat-kar/ap-sql-v1`](https://huggingface.co/samrat-kar/ap-sql-v1). |
|
|
| Every gold SQL query was run against the demo database when the dataset was built; `meta.result_rows` records how many rows it returned. |
|
|
| ## Format |
|
|
| One JSON object per line: |
|
|
| ```json |
| {"messages": [{"role": "system", "content": "...rules + CREATE TABLE DDL + glossary..."}, |
| {"role": "user", "content": "question (or follow-up / repair request)"}, |
| {"role": "assistant", "content": "```sql\nSELECT ...\n```"}], |
| "meta": {"id": "...", "tier": "T1-T5", "family": "...", "kind": "ask|followup|repair-exec|repair-parse", |
| "source": "...", "group": "...", "tables": ["..."], "result_rows": 3, "approx_prompt_tokens": 3089, "split": "..."}} |
| ``` |
|
|
| The system prompt is the one the assistant builds at runtime: the rules, then the DDL of the retrieved tables |
| (wide tables pruned to join keys plus the relevant columns), then the glossary entries. It is capped at about |
| 3,584 tokens so the whole prompt fits a 4,096-token window. |
|
|
| ## Splits |
|
|
| | tier | train | validation | test | |
| |---|---|---|---| |
| | T1 (single table, simple) | 284 | 17 | 37 | |
| | T2 | 463 | 28 | 56 | |
| | T3 | 471 | 34 | 58 | |
| | T4 | 143 | 10 | 19 | |
| | T5 (hardest) | 80 | 6 | 9 | |
| | **total** | **1,441** | **95** | **179** | |
|
|
| - **Split by `meta.group`.** Paraphrases and variants of one question always land in the same split, so no test group |
| appears in train. |
| - **Kinds.** `ask` is a plain question. `followup` carries conversation history. `repair-exec` and `repair-parse` |
| give the model a failed query and its Oracle or parse error, and the target is the corrected query. |
| - **Sources.** `S2-templated` rows are generated from templates, `S6-repair` rows are repair cases, and |
| `S1-golden` rows are hand-written (test split only). |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("samrat-kar/ap-sql-peft") |
| ``` |
|
|
| ## Limitations |
|
|
| - Covers one synthetic schema. |
| - Most rows are templated, so question phrasing is less varied than real user traffic. |
| - Oracle SQL dialect only. |
|
|
