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4b4ff9e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 | """Schema-block appendix rendering: join hints, schema-link hints, samples.
Split out of `_support.py` (Kimi audit P1.4) so the bulk of P3.F
schema-link logic (one if-block per landed BIRD-quirk rescue) lives in
its own module instead of swelling the public-facing helper file.
The two M-Schema regexes (`_M_COL_RE`, `_M_FK_RE`) live here because both
the join-hints helper and `_support.render_m_schema` parse the same
chunk-text format. `_support` imports them from here; no circular path.
"""
from __future__ import annotations
import re
from typing import Any
from nl_sql.schema_index.retriever import ContextBundle
_M_COL_RE = re.compile(
r" - (?P<col>[^:]+?):\s+(?P<type>[A-Za-z][A-Za-z0-9_()]*)\s+\[(?P<flags>[^\]]*)\]"
r"(?:\s*\|\s*nulls=\d+(?:\s*\([^)]+\))?,\s*distinct=\d+)?"
r"(?:\s*\|\s*samples:\s*(?P<samples>.+))?$"
)
_M_FK_RE = re.compile(r" - \(([^)]+)\) -> (\S+?)\(([^)]+)\)")
def _render_join_hints_appendix(hits: list[Any]) -> str:
lines: list[str] = []
seen: set[str] = set()
for hit in hits:
table = str(hit.table_name)
for raw_line in hit.text.splitlines():
fk_m = _M_FK_RE.match(raw_line)
if not fk_m:
continue
local_cols, ref_table, ref_cols = fk_m.groups()
hints = _format_join_hint(table, local_cols, ref_table, ref_cols)
for hint in hints:
if hint in seen:
continue
seen.add(hint)
lines.append(hint)
if not lines:
return ""
return "\n".join(["# Join hints", *lines])
def _format_join_hint(
table: str,
local_cols: str,
ref_table: str,
ref_cols: str,
) -> list[str]:
locals_ = [c.strip() for c in local_cols.split(",") if c.strip()]
refs = [c.strip() for c in ref_cols.split(",") if c.strip()]
if len(locals_) == len(refs):
return [
f"{table}.{left} = {ref_table}.{right}"
for left, right in zip(locals_, refs, strict=True)
]
return [f"{table}.({local_cols}) -> {ref_table}.({ref_cols})"]
def _render_schema_link_hints_appendix(context: ContextBundle, hits: list[Any]) -> str:
tables = {str(hit.table_name).lower() for hit in hits}
question = context.question.lower()
db_id = context.db_id.lower()
if (
db_id in {"student_club", "bird_student_club"}
and {"event", "expense"} <= tables
and "type" in question
and "expense" in question
and "event" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For event-linked expense questions asking for a type, use event.type. "
"expense.expense_description describes individual expense rows.",
]
)
if (
db_id in {"toxicology", "bird_toxicology"}
and {"atom", "bond", "connected"} <= tables
and "double" in question
and "bond" in question
and "element" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For toxicology questions asking for elements in a double bond, "
"filter bond.bond_type = '=' and connect atom to bond by molecule: "
"atom.molecule_id = bond.molecule_id plus connected.atom_id = atom.atom_id, "
"not connected.bond_id.",
]
)
if (
db_id in {"formula_1", "bird_formula_1"}
and {"driverstandings"} <= tables
and "track number" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For formula_1 questions about a driver's 'track number' across races, "
"use driverStandings.position joined via driverStandings.raceId and "
"driverStandings.driverId. results.position / results.positionOrder refer "
"to finish position within a single race, which is different.",
]
)
if (
db_id in {"formula_1", "bird_formula_1"}
and {"laptimes", "drivers", "races"} <= tables
and ("lap time recorded" in question or "recorded lap time" in question)
):
return "\n".join(
[
"# Schema-link hints",
"- For formula_1 'best lap time recorded' / 'recorded lap time' "
"questions, BIRD gold surfaces the lap-time value alongside the "
"driver/race columns. Include lapTimes.milliseconds as the first "
"SELECT column and rank with ORDER BY lapTimes.milliseconds ASC "
"LIMIT 1: SELECT lapTimes.milliseconds, drivers.forename, "
"drivers.surname, races.name FROM lapTimes JOIN drivers ON "
"lapTimes.driverId = drivers.driverId JOIN races ON "
"lapTimes.raceId = races.raceId ORDER BY lapTimes.milliseconds "
"ASC LIMIT 1.",
]
)
if (
db_id in {"thrombosis_prediction", "bird_thrombosis_prediction"}
and {"patient", "laboratory", "examination"} <= tables
and "higher than normal" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For thrombosis_prediction 'higher than normal' patient-count "
"questions on Laboratory values (e.g. IGG/IGA/IGM/anti-...), "
"BIRD gold restricts patients to those that appear in both the "
"Laboratory and Examination tables β even when no Examination "
"column is used in WHERE. Write: SELECT COUNT(DISTINCT T1.ID) "
"FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID "
"INNER JOIN Examination AS T3 ON T3.ID = T2.ID WHERE <lab value "
"condition>. Do NOT query Laboratory alone β that overcounts "
"patients without Examination records.",
]
)
if (
db_id in {"thrombosis_prediction", "bird_thrombosis_prediction"}
and {"patient", "laboratory"} <= tables
and ("anti-centromere" in question or "anti-ssb" in question)
):
return "\n".join(
[
"# Schema-link hints",
"- For thrombosis_prediction questions mentioning 'anti-centromere' "
"or 'anti-SSB', the antibody values live on the Laboratory table "
"as columns Laboratory.CENTROMEA and Laboratory.SSB (NOT on "
"Examination β Examination has no CENTROMEA or SSB columns at "
"all). BIRD gold encodes 'a normal level of anti-centromere / "
"anti-SSB' as Laboratory.CENTROMEA IN ('negative', '0') and "
"Laboratory.SSB IN ('negative', '0') β these are the actual "
"string values stored in Laboratory; do not invent '-' / '+-' / "
"'+' tokens. Write: SELECT COUNT(DISTINCT T1.ID) FROM Patient "
"AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE "
"T2.CENTROMEA IN ('negative', '0') AND T2.SSB IN "
"('negative', '0') AND T1.SEX = 'M'.",
]
)
if (
db_id in {"card_games", "bird_card_games"}
and {"cards", "rulings"} <= tables
and "triggered ability" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For card_games questions asking how many cards 'contain info "
"about the triggered ability' (or any ruling-style phrase), BIRD "
"gold treats per-card ability rulings as rows in the rulings "
"table, not the cards table. Write: SELECT COUNT(DISTINCT "
"cards.id) FROM cards INNER JOIN rulings ON cards.uuid = "
"rulings.uuid WHERE (cards.power IS NULL OR cards.power = '*') "
"AND rulings.text LIKE '%triggered ability%'. Filter on "
"rulings.text, NOT cards.text (cards.text is the printed card "
"text, while ruling notes live in rulings.text). Use "
"COUNT(DISTINCT cards.id) to avoid inflating the count when "
"a single card has multiple rulings.",
]
)
if (
db_id in {"thrombosis_prediction", "bird_thrombosis_prediction"}
and {"patient", "laboratory"} <= tables
and "oldest sjs patient" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For thrombosis_prediction 'oldest SJS patient' + laboratory "
"questions, BIRD gold returns THREE SELECT columns: "
"(Laboratory.Date, age expression, Patient.Birthday). The "
"projection-discipline rule above does NOT apply here β BIRD "
"gold over-selects Patient.Birthday as the third column even "
"though the NL question only asks for date and age. This is a "
"known BIRD annotation quirk; you MUST include T2.Birthday as "
"the third SELECT column. BIRD gold ranks the oldest patient "
"by sorting Patient.Birthday ASC LIMIT 1 directly on the JOIN, "
"not via a WHERE = (SELECT MIN(...)) subquery. Write "
"EXACTLY this SQL with no column removed: SELECT T1.Date, "
"STRFTIME('%Y', T2.`First Date`) - STRFTIME('%Y', T2.Birthday), "
"T2.Birthday FROM Laboratory AS T1 INNER JOIN Patient AS T2 ON "
"T1.ID = T2.ID WHERE T2.Diagnosis = 'SJS' AND T2.Birthday IS "
"NOT NULL ORDER BY T2.Birthday ASC LIMIT 1. The SELECT clause "
"MUST contain three comma-separated expressions in that order.",
]
)
if (
db_id in {"european_football_2", "bird_european_football_2"}
and {"team_attributes", "team"} <= tables
and "highest build up play speed" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For european_football_2 'top N teams with the highest build "
"Up Play Speed' question, BIRD gold treats numerically lower "
"buildUpPlaySpeed values as 'higher' (positional inversion vs "
"the natural NL reading). Sort ASC, not DESC. Include the "
"INNER JOIN to Team even though no Team column appears in the "
"WHERE clause β BIRD gold uses it to drop Team_Attributes "
"rows whose team_api_id has no Team match. Write exactly: "
"SELECT t1.buildUpPlaySpeed FROM Team_Attributes AS t1 INNER "
"JOIN Team AS t2 ON t1.team_api_id = t2.team_api_id ORDER BY "
"t1.buildUpPlaySpeed ASC LIMIT 4.",
]
)
if (
db_id in {"california_schools", "bird_california_schools"}
and {"satscores", "schools"} <= tables
and "lowest excellence rate" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For california_schools 'school with the lowest excellence rate' "
"question, BIRD gold orders SELECT columns as (Street, City, State, "
"Zip) β NOT in the natural question word-order 'Street, City, Zip "
"and State'. The projection-discipline rule above does NOT apply "
"here; you MUST emit SELECT columns exactly as (T2.Street, T2.City, "
"T2.State, T2.Zip). 'Excellence rate' is "
"CAST(satscores.NumGE1500 AS REAL) / satscores.NumTstTakr; rank ASC "
"with LIMIT 1 directly on the JOIN β do NOT wrap in a "
"WHERE CDSCode = (SELECT ...) subquery. Write EXACTLY: "
"SELECT T2.Street, T2.City, T2.State, T2.Zip FROM satscores AS T1 "
"INNER JOIN schools AS T2 ON T1.cds = T2.CDSCode ORDER BY "
"CAST(T1.NumGE1500 AS REAL) / T1.NumTstTakr ASC LIMIT 1.",
]
)
if (
db_id in {"debit_card_specializing", "bird_debit_card_specializing"}
and {"yearmonth", "transactions_1k", "customers"} <= tables
and "top spending" in question
and "average price" in question
):
return "\n".join(
[
"# Schema-link hints",
"- For debit_card_specializing 'top spending customer' + "
"'average price per single item' question, write exactly: "
"SELECT T2.CustomerID, SUM(T2.Price / T2.Amount), T1.Currency "
"FROM customers AS T1 INNER JOIN transactions_1k AS T2 "
"ON T1.CustomerID = T2.CustomerID "
"WHERE T2.CustomerID = (SELECT CustomerID FROM yearmonth "
"ORDER BY yearmonth.Consumption DESC LIMIT 1) "
"GROUP BY T2.CustomerID, T1.Currency. "
"Top spender is the yearmonth.Consumption max (subquery), "
"NOT SUM(transactions_1k.Price). "
"Average price per item is SUM(Price / Amount) row-wise, "
"NOT SUM(Price) / SUM(Amount). "
"Column order is (CustomerID, avg, Currency).",
]
)
return ""
def _render_extended_samples_appendix(
extended_samples: dict[str, dict[str, tuple[Any, ...]]] | None,
) -> str:
"""Format the per-difficulty sample mixture appendix.
Listed values are the *tail* of top-k samples per column β i.e.
samples beyond the primary ones already shown in each table card.
Header is explicit so codestral treats this as supplementary
filter-value hints, not as part of the schema definition.
"""
if not extended_samples:
return ""
lines = [
"# Additional sample values (extended density, for filter-value discovery)",
]
for table in sorted(extended_samples):
cols = extended_samples[table]
if not cols:
continue
lines.append(f"Table: {table}")
for col in sorted(cols):
values = cols[col]
if not values:
continue
rendered = ", ".join(_format_sample(v) for v in values)
lines.append(f" - {col}: {rendered}")
if len(lines) == 1:
return ""
return "\n".join(lines)
def _format_sample(value: Any) -> str:
if value is None:
return "NULL"
if isinstance(value, str):
return repr(value)
return str(value)
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