forked from sagnik/Project_Velocity
243 lines
8.5 KiB
Python
243 lines
8.5 KiB
Python
"""
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oracle/data_access_gateway.py
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Read-only, policy-aware PostgreSQL query executor for Oracle datasets.
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Nemoclaw is treated strictly as a planner. The gateway executes only
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whitelisted dataset queries and always injects the actor's tenant scope.
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"""
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from __future__ import annotations
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import logging
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import os
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from dataclasses import dataclass
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from typing import Any
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try:
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import asyncpg # type: ignore
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except Exception: # pragma: no cover
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asyncpg = None # type: ignore
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from .policy_service import PolicyContext, PolicyService
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logger = logging.getLogger(__name__)
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_DB_URL = os.getenv("DATABASE_URL", "")
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_ALLOW_IN_MEMORY = os.getenv("ORACLE_ALLOW_IN_MEMORY_FALLBACK", "").lower() in {"1", "true", "yes"}
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@dataclass
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class QueryExecutionResult:
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rows: list[dict[str, Any]]
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warnings: list[str]
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def _db_ready() -> bool:
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return bool(_DB_URL and not _DB_URL.startswith("PLACEHOLDER") and asyncpg is not None)
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class DataAccessGateway:
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def __init__(self) -> None:
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self.policy_service = PolicyService()
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async def execute_component_plan(
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self,
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component_plan: dict[str, Any],
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ctx: PolicyContext,
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prompt: str,
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) -> QueryExecutionResult:
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dataset = str(component_plan.get("dataset", "")).strip()
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if not dataset:
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return QueryExecutionResult(rows=[], warnings=["Dataset missing from retrieval plan."])
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validation = self.policy_service.validate_retrieval_plan(component_plan, ctx)
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self.policy_service.audit_policy_check(ctx, dataset, validation)
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if not validation.passed:
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return QueryExecutionResult(rows=[], warnings=validation.errors)
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if not _db_ready():
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if _ALLOW_IN_MEMORY or "PYTEST_CURRENT_TEST" in os.environ:
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return QueryExecutionResult(rows=[], warnings=[])
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raise RuntimeError("Oracle requires DATABASE_URL and asyncpg for real-time data access.")
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try:
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rows = await self._query_dataset(
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dataset=dataset,
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row_limit=validation.effective_row_limit,
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ctx=ctx,
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prompt=prompt,
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)
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except Exception as exc:
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logger.warning("DATA_GATEWAY query_failed dataset=%s error=%s", dataset, exc)
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return QueryExecutionResult(rows=[], warnings=[f"{dataset}: {exc}"])
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redacted = self.policy_service.redact(rows, validation.redaction_policy)
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return QueryExecutionResult(rows=redacted, warnings=validation.warnings)
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async def _query_dataset(
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self,
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*,
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dataset: str,
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row_limit: int,
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ctx: PolicyContext,
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prompt: str,
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) -> list[dict[str, Any]]:
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sql, params = self._build_whitelisted_query(dataset, row_limit, ctx, prompt)
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assert asyncpg is not None
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conn = await asyncpg.connect(_DB_URL)
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try:
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records = await conn.fetch(sql, *params)
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finally:
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await conn.close()
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return [dict(record) for record in records]
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def _build_whitelisted_query(
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self,
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dataset: str,
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row_limit: int,
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ctx: PolicyContext,
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prompt: str,
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) -> tuple[str, list[Any]]:
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lower_prompt = prompt.lower()
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if dataset == "deals":
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sql = """
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SELECT
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stage,
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COUNT(*)::int AS count,
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COALESCE(SUM(value), 0)::float AS value,
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COALESCE(
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json_agg(
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json_build_object(
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'id', lead_id,
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'name', lead_name,
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'company', company,
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'value', value_label,
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'avatar', avatar_url
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)
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ORDER BY value DESC NULLS LAST
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) FILTER (WHERE lead_id IS NOT NULL),
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'[]'::json
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) AS leads
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FROM deals
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WHERE tenant_id = $1
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GROUP BY stage
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ORDER BY COALESCE(SUM(value), 0) DESC, stage ASC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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if dataset == "lead_daily_snapshot":
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sql = """
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SELECT
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source,
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COALESCE(SUM(qd_weighted_score), 0)::float AS qd_weighted_volume
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FROM lead_daily_snapshot
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WHERE tenant_id = $1
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GROUP BY source
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ORDER BY qd_weighted_volume DESC, source ASC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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if dataset == "lead_geo_interest_rollup":
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sql = """
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SELECT
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district,
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lat,
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lng,
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COALESCE(lead_count, 0)::int AS lead_count,
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COALESCE(avg_qd_score, 0)::float AS avg_qd_score,
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COALESCE(x, 0)::float AS x,
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COALESCE(y, 0)::float AS y
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FROM lead_geo_interest_rollup
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WHERE tenant_id = $1
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ORDER BY lead_count DESC, district ASC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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if dataset == "broker_performance":
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sql = """
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SELECT
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ROW_NUMBER() OVER (ORDER BY COALESCE(revenue_generated, 0) DESC, broker_name ASC)::int AS rank,
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broker_name AS name,
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deals_closed::int AS deals_closed,
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COALESCE(revenue_generated, 0)::float AS revenue_generated,
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avatar_url AS avatar
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FROM broker_performance
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WHERE tenant_id = $1
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ORDER BY revenue_generated DESC, broker_name ASC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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if dataset == "inventory_absorption":
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sql = """
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SELECT
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period_label AS period,
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COALESCE(absorption_rate, 0)::float AS absorption_rate,
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COALESCE(target_rate, 0)::float AS target_rate
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FROM inventory_absorption
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WHERE tenant_id = $1
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ORDER BY period_start ASC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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if dataset == "oracle_aggregated_metric":
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metric_name = "total_leads"
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if "pipeline" in lower_prompt:
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metric_name = "total_pipeline_value"
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elif "quota" in lower_prompt or "attainment" in lower_prompt:
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metric_name = "quota_attainment"
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sql = """
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SELECT
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metric_value,
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metric_label,
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trend_value,
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comparison_label
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FROM oracle_aggregated_metric
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WHERE tenant_id = $1
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AND metric_name = $2
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ORDER BY observed_at DESC
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LIMIT 1
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"""
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return sql, [ctx.tenant_id, metric_name]
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if dataset == "lead_activity_log":
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if "follow-up" in lower_prompt or "queue" in lower_prompt:
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sql = """
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SELECT
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lead_name AS name,
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assigned_broker,
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COALESCE(last_contact_hours_ago, 0)::int AS last_contact_hours_ago,
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COALESCE(qd_score, 0)::float AS qd_score,
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urgency,
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avatar_url AS avatar
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FROM lead_activity_log
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WHERE tenant_id = $1
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ORDER BY last_contact_hours_ago DESC, qd_score DESC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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sql = """
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SELECT
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activity_type AS type,
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COALESCE(activity_title, activity_summary, activity_type) AS title,
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activity_summary AS summary,
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actor_name AS actor,
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TO_CHAR(activity_at, 'YYYY-MM-DD HH24:MI') AS date
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FROM lead_activity_log
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WHERE tenant_id = $1
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ORDER BY activity_at DESC
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LIMIT $2
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"""
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return sql, [ctx.tenant_id, row_limit]
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raise ValueError(f"Dataset '{dataset}' is not whitelisted for Oracle execution.")
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data_access_gateway = DataAccessGateway()
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