tools/sql_tool.py

# space/tools/sql_tool.py
import os
import re
import json
import pandas as pd
from utils.config import AppConfig
from utils.tracing import Tracer


class SQLTool:
    def __init__(self, cfg: AppConfig, tracer: Tracer):
        self.cfg = cfg
        self.tracer = tracer
        self.backend = cfg.sql_backend  # "bigquery" or "motherduck"

        if self.backend == "bigquery":
            from google.cloud import bigquery
            from google.oauth2 import service_account
            key_json = os.getenv("GCP_SERVICE_ACCOUNT_JSON")
            if not key_json:
                raise RuntimeError("Missing GCP_SERVICE_ACCOUNT_JSON secret")

            # Accept full JSON string from Space Secret
            info = json.loads(key_json) if key_json.strip().startswith("{") else {}
            creds = service_account.Credentials.from_service_account_info(info)
            self.client = bigquery.Client(credentials=creds, project=cfg.gcp_project)

        elif self.backend == "motherduck":
            import duckdb
            # MotherDuck currently supports DuckDB 1.3.2 broadly across hosts
            if not duckdb.__version__.startswith("1.3.2"):
                raise RuntimeError(
                    f"Incompatible DuckDB version {duckdb.__version__}. "
                    "Pin duckdb==1.3.2 in requirements.txt and redeploy."
                )

            token = self.cfg.motherduck_token or os.getenv("MOTHERDUCK_TOKEN")
            db_name = (self.cfg.motherduck_db or "workspace").strip()
            if not token:
                raise RuntimeError("Missing MOTHERDUCK_TOKEN")

            # Easiest, correct way: connect directly to MotherDuck database.
            # This will auto-download/load the extension; no manual INSTALL/LOAD/ATTACH needed.
            # Valid URIs include:
            #   "md:"                  -> connects to workspace (all DBs)
            #   f"md:{db_name}"        -> connects to a specific DB
            #   f"md:{db_name}?motherduck_token=..." -> with token in URI
            uri = f"md:{db_name}?motherduck_token={token}"
            self.client = duckdb.connect(uri)

            # Optional: set a default database context (USE) if you connected to 'md:' (workspace)
            # if db_name in ("", "workspace"):
            #     self.client.execute("USE your_database;")
        else:
            raise RuntimeError("Unknown SQL backend")

    def _nl_to_sql(self, message: str) -> str:
        """
        Minimal NL2SQL heuristic; replace with your own mapping or LLM prompt.
        Edit table/column names to your schema.
        """
        m = message.lower()

        # Simple example (DuckDB/MotherDuck DATE_TRUNC flavor)
        if "avg" in m and " by " in m:
            return (
                "-- Example template; edit me\n"
                "SELECT DATE_TRUNC('month', date_col) AS month, "
                "AVG(metric) AS avg_metric "
                "FROM analytics.table "
                "GROUP BY 1 "
                "ORDER BY 1;"
            )

        # Pass-through if the user typed SQL explicitly
        if re.match(r"^\s*select ", m):
            return message

        return "SELECT * FROM analytics.table LIMIT 100;"

    def run(self, message: str) -> pd.DataFrame:
        sql = self._nl_to_sql(message)
        try:
            self.tracer.trace_event("sql_query", {"sql": sql, "backend": self.backend})
        except Exception:
            pass

        if self.backend == "bigquery":
            return self.client.query(sql).to_dataframe()
        else:
            # DuckDB (MotherDuck)
            return self.client.execute(sql).fetch_df()