tools/sql_tool.py

# tools/sql_tool.py
import os
import re
from typing import Optional, Tuple

import duckdb

# DuckDB file path (can be overridden in Space settings)
DUCKDB_PATH = os.getenv("DUCKDB_PATH", "alm.duckdb")

# Default schema/table -> your path my_db.masterdataset_v
DEFAULT_SCHEMA = os.getenv("SQL_DEFAULT_SCHEMA", "my_db")
DEFAULT_TABLE  = os.getenv("SQL_DEFAULT_TABLE",  "masterdataset_v")


def _full_table(schema: Optional[str] = None, table: Optional[str] = None) -> str:
    schema = schema or DEFAULT_SCHEMA
    table = table or DEFAULT_TABLE
    return f"{schema}.{table}"


class SQLTool:
    """
    Minimal NL→SQL helper wired to my_db.masterdataset_v with a DuckDB runner.
    """

    def __init__(self, db_path: Optional[str] = None):
        self.db_path = db_path or DUCKDB_PATH
        self.con = duckdb.connect(self.db_path)

    # -------------------------
    # SQL Runner
    # -------------------------
    def run_sql(self, sql: str):
        return self.con.execute(sql).df()

    # -------------------------
    # NL → SQL
    # -------------------------
    def _nl_to_sql(
        self, message: str, schema: Optional[str] = None, table: Optional[str] = None
    ) -> Tuple[str, str]:
        """
        Returns (sql, rationale). Small template library covering common queries.
        Falls back to a filtered SELECT or a sample.
        """
        full_table = _full_table(schema, table)
        m = (message or "").strip().lower()

        def has_any(txt, words):
            return any(w in txt for w in words)

        # Extract "top N"
        limit = None
        m_top = re.search(r"\btop\s+(\d+)", m)
        if m_top:
            limit = int(m_top.group(1))

        # 1) Top N FDs by Portfolio_value
        if has_any(m, ["fd", "fixed deposit", "deposits"]) and has_any(
            m, ["top", "largest", "biggest"]
        ) and has_any(m, ["portfolio value", "portfolio_value"]):
            n = limit or 10
            sql = f"""
            SELECT contract_number, Portfolio_value, Interest_rate, currency, segments
            FROM {full_table}
            WHERE lower(product) = 'fd'
            ORDER BY Portfolio_value DESC
            LIMIT {n};
            """
            why = f"Top {n} fixed deposits by Portfolio_value from {full_table}"
            return sql, why

        # 2) Top N Assets by Portfolio_value
        if has_any(m, ["asset", "loan", "advances"]) and has_any(
            m, ["top", "largest", "biggest"]
        ) and has_any(m, ["portfolio value", "portfolio_value"]):
            n = limit or 10
            sql = f"""
            SELECT contract_number, Portfolio_value, Interest_rate, currency, segments
            FROM {full_table}
            WHERE lower(product) = 'assets'
            ORDER BY Portfolio_value DESC
            LIMIT {n};
            """
            why = f"Top {n} assets by Portfolio_value from {full_table}"
            return sql, why

        # 3) Aggregate (SUM/AVG) by segment or currency
        if has_any(m, ["sum", "total", "avg", "average"]) and has_any(
            m, ["segment", "currency"]
        ):
            agg = "SUM" if has_any(m, ["sum", "total"]) else "AVG"
            dim = "segments" if "segment" in m else "currency"
            sql = f"""
            SELECT {dim}, {agg}(Portfolio_value) AS {agg.lower()}_Portfolio_value
            FROM {full_table}
            GROUP BY 1
            ORDER BY 2 DESC;
            """
            why = f"{agg} Portfolio_value grouped by {dim} from {full_table}"
            return sql, why

        # 4) Generic filters
        product = None
        if "fd" in m or "deposit" in m:
            product = "fd"
        elif "asset" in m or "loan" in m or "advance" in m:
            product = "assets"

        parts = [f"SELECT * FROM {full_table} WHERE 1=1"]
        why_parts = [f"Filtered rows from {full_table}"]

        if product:
            parts.append(f"AND lower(product) = '{product}'")
            why_parts.append(f"product = {product}")

        # currency filter like: "in lkr", "currency usd"
        cur_match = re.search(r"\b(currency|in)\s+([a-z]{3})\b", m)
        if cur_match:
            cur = cur_match.group(2).upper()
            parts.append(f"AND upper(currency) = '{cur}'")
            why_parts.append(f"currency = {cur}")

        # segment filter like: "segment retail" or "for corporate"
        seg_match = re.search(r"(segment|for)\s+([a-z0-9_\- ]+)", m)
        if seg_match:
            seg = seg_match.group(2).strip()
            if seg:
                parts.append(f"AND lower(segments) LIKE '%{seg.lower()}%'")
                why_parts.append(f"segments like '{seg}'")

        if limit:
            parts.append(f"LIMIT {limit}")

        fallback_sql = " ".join(parts) + ";"
        fallback_why = "; ".join(why_parts)
        return fallback_sql, fallback_why

    # Public helpers
    def query_from_nl(self, message: str):
        sql, why = self._nl_to_sql(message)
        df = self.run_sql(sql)
        return df, sql, why

    def table_exists(self, schema: Optional[str] = None, table: Optional[str] = None) -> bool:
        schema = schema or DEFAULT_SCHEMA
        table = table or DEFAULT_TABLE
        q = f"""
        SELECT COUNT(*) AS n
        FROM information_schema.tables
        WHERE table_schema = '{schema}' AND table_name = '{table}';
        """
        n = self.con.execute(q).fetchone()[0]
        return n > 0