Files
nvi/api/tools/text_to_sql.py

71 lines
2.2 KiB
Python

"""LLM-driven NL → SQL with sqlglot validation and one retry."""
from __future__ import annotations
import logging
import re
import sqlglot
from api import langfuse_client as lf
from api.llm import chat
from api.prompts import load, render
from api.tools.schema import load_schema
from api.tools.types import T2SResult
logger = logging.getLogger("nvi.tools.text_to_sql")
def text_to_sql(question: str, *, hint_tables: list[str] | None = None) -> T2SResult:
schema = load_schema()
tables = hint_tables or schema.table_names()
system = load("text_to_sql.system")
def _user(retry_hint: str = "") -> str:
return render(
"text_to_sql.user",
question=question,
schema_block=schema.render_tables(tables),
metrics_block=schema.render_metrics(),
retry_hint=retry_hint,
)
with lf.span(
"text_to_sql",
as_type="generation",
input={"question": question, "hint_tables": hint_tables},
) as span:
sql = _extract_sql(chat(system=system, user=_user()))
try:
_validate(sql)
except Exception as e:
logger.info("t2s first attempt invalid (%s); retrying once", e)
hint = f"\n\nPrevious attempt failed parsing: {e}. Fix and return only the SQL."
sql = _extract_sql(chat(system=system, user=_user(hint)))
_validate(sql)
result = T2SResult(sql=sql, used_tables=_extract_tables(sql))
span.update(output={"sql": sql, "used_tables": result.used_tables})
return result
def _extract_sql(text: str) -> str:
m = re.search(r"```sql\s*(.*?)```", text, re.DOTALL | re.IGNORECASE)
if m:
return m.group(1).strip().rstrip(";").strip()
return text.strip().rstrip(";").strip()
def _validate(sql: str) -> None:
parsed = sqlglot.parse_one(sql, dialect="postgres")
if parsed is None:
raise ValueError("sqlglot returned no parse tree")
def _extract_tables(sql: str) -> list[str]:
try:
parsed = sqlglot.parse_one(sql, dialect="postgres")
return sorted({t.name for t in parsed.find_all(sqlglot.exp.Table)})
except Exception:
return []