samrat-kar/ap-sql-v1
Text Generation • Updated • 1
messages listlengths 3 3 | meta unknown |
|---|---|
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00660",
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],
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"approx_prompt_tokens": 2829,
"context_complete": true,
"missing_tables": [],
"schema_fingerprint": ... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "r-00057",
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"AP_INVOICES_ALL",
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],
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"context_complete": true,
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"schema_fingerpri... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-01638",
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"tables": [
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],
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"context_complete": true,
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"schema_fingerpri... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-01196",
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"schema_fingerprint": "a978c48ca1a87c06b... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00010",
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"AP_INVOICES_ALL"
],
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"approx_prompt_tokens": 2676,
"context_complete": true,
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"schema_fingerprint": "a978c48ca1a87c06b... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00126",
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"context_complete": true,
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"schema_fingerprint": "a978c48ca1a87c06b... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
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],
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"context_complete": true,
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"schema_fingerprint":... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
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],
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[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "r-00033",
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"POZ_SUPPLIERS"
],
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[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00681",
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],
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[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
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[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00597",
"tier": "T2",
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"kind": "ask",
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"tables": [
"AP_INVOICES_ALL",
"POZ_SUPPLIER_ADDRESSES"
],
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"schema_fi... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-01520",
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"tables": [
"AP_INVOICES_ALL",
"POZ_SUPPLIERS"
],
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"context_complete": true,
"missing_tables": [],
"schema_fingerpr... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00808",
"tier": "T2",
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"kind": "ask",
"source": "S2-templated",
"group": "5e4a52ff4474",
"tables": [
"AP_INVOICES_ALL",
"AP_TERMS_B"
],
"result_rows": 5,
"approx_prompt_tokens": 2847,
"context_complete": true,
"missing_tables": [],
"schema_fingerprint": ... |
[
{
"role": "system",
"content": "You are a precise Oracle SQL generator for an Accounts Payable analytics assistant.\n\nRules:\n- Output ONLY a single read-only Oracle SQL SELECT statement that answers the user's question.\n- Respond with the SQL in a single ```sql code block and nothing else — no prose, no ... | {
"id": "a-00367",
"tier": "T2",
"family": "t2-invoice-lookup",
"kind": "ask",
"source": "S2-templated",
"group": "78deaf491a34",
"tables": [
"AP_INVOICES_ALL",
"AP_PAYMENT_SCHEDULES_ALL"
],
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"context_complete": true,
"missing_tables": [],
... |
End of preview. Expand in Data Studio
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.
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:
{"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.
askis a plain question.followupcarries conversation history.repair-execandrepair-parsegive the model a failed query and its Oracle or parse error, and the target is the corrected query. - Sources.
S2-templatedrows are generated from templates,S6-repairrows are repair cases, andS1-goldenrows are hand-written (test split only).
Usage
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.
- Downloads last month
- 13
Models trained or fine-tuned on samrat-kar/ap-sql-peft