# user_question_log

user_id: 1
agent_id: 1
question: show me all expenses by month for Scott Haber
chart: N
web: N
executed: Y
execution_time: 5.0
question_normalized: show_me_all_expenses_by_month_for_scott_haber
created_at: 2026-05-11 15:21:36
updated_at: 2026-05-11 15:21:46
sql:
  SELECT 
      MONTH,
      YEAR,
      SUM(AMOUNT) AS total_expense
  FROM TR_EXPENSE_ANALYSYS_V
  WHERE EMPLOYEENAME = 'Scott Haber'
  GROUP BY YEAR, MONTH
  ORDER BY YEAR, MONTH
  LIMIT 1000

sql_query_summaries:
  [{"agent_id": "1", "sub_question": "show me all expenses by month for Scott Haber", "summary": "This query retrieves the total expenses for Scott Haber, grouped by each month and year. It looks at the TR_EXPENSE_ANALYSYS_V table, filters for records where the employee name is Scott Haber, sums the AMOUNT column for each month and year, and orders the results chronologically. The output shows the month, year, and total expense for each period, up to 1000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds the total expenses submitted by Scott Haber, broken down by each month and year. It summarizes how much Scott Haber spent in each period.</p><hr><h4>Step 1 - Filter for Scott Haber</h4><p>The query selects only the records where the employee name is 'Scott Haber'.</p><h4>Step 2 - Group and Sum Expenses</h4><p>It groups the data by year and month, then calculates the total expense amount for each group.</p><h4>Step 3 - Order and Limit Results</h4><p>The results are ordered by year and month, showing up to 1000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>MONTH</td><td>The month of the expenses</td></tr><tr><td>YEAR</td><td>The year of the expenses</td></tr><tr><td>total_expense</td><td>The total amount Scott Haber spent in that month and year</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of months and years, each with the total expenses Scott Haber incurred during that period, sorted chronologically.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>MONTH, YEAR, SUM(AMOUNT) AS total_expense</td><td>Chooses the columns to display and calculates the total expenses</td></tr><tr><td>FROM</td><td>TR_EXPENSE_ANALYSYS_V</td><td>Specifies the source table</td></tr><tr><td>WHERE</td><td>EMPLOYEENAME = 'Scott Haber'</td><td>Filters for Scott Haber's expenses only</td></tr><tr><td>GROUP BY</td><td>YEAR, MONTH</td><td>Groups expenses by year and month</td></tr><tr><td>ORDER BY</td><td>YEAR, MONTH</td><td>Sorts results chronologically</td></tr><tr><td>LIMIT</td><td>1000</td><td>Limits the output to 1000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 1
question: Show me all expenses by month and expense type for Scott Haber.
chart: N
web: N
executed: Y
execution_time: 5.0
question_normalized: show_me_all_expenses_by_month_and_expense_type_for_scott_haber.
created_at: 2026-05-11 15:25:15
updated_at: 2026-05-11 15:25:20
sql:
  SELECT 
      MONTH, 
      EXPENSETYPE, 
      AMOUNT
  FROM 
      TR_EXPENSE_ANALYSYS_V
  WHERE 
      EMPLOYEENAME = 'Scott Haber'
  ORDER BY 
      YEAR, MONTH, EXPENSETYPE
  LIMIT 1000

sql_query_summaries:
  [{"agent_id": "1", "sub_question": "Show me all expenses by month and expense type for Scott Haber.", "summary": "This query retrieves a list of all expenses for the employee Scott Haber, grouped by month and expense type. It pulls the month, type of expense, and the amount spent from the TR_EXPENSE_ANALYSYS_V table, only including rows where the employee name is Scott Haber. The results are sorted by year, month, and expense type, and limited to the first 1,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists all expenses made by Scott Haber, showing the month, type of expense, and the amount for each entry. It only includes expenses for Scott Haber and organizes the results by year, month, and expense type, up to 1,000 records.</p><h3>The Final Output</h3><p>The output will be a table where each row shows a specific month, the type of expense, and the amount spent by Scott Haber during that month.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>MONTH, EXPENSETYPE, AMOUNT</td><td>Columns to display: month, expense type, and amount spent</td></tr><tr><td>FROM</td><td>TR_EXPENSE_ANALYSYS_V</td><td>Source table containing expense data</td></tr><tr><td>WHERE</td><td>EMPLOYEENAME = 'Scott Haber'</td><td>Filters to only include Scott Haber's expenses</td></tr><tr><td>ORDER BY</td><td>YEAR, MONTH, EXPENSETYPE</td><td>Sorts results by year, month, and expense type</td></tr><tr><td>LIMIT</td><td>1000</td><td>Limits output to the first 1,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 1
question: show me total expenses by month and year and expense type
chart: N
web: N
executed: Y
execution_time: 7.0
question_normalized: show_me_total_expenses_by_month_and_year_and_expense_type
created_at: 2026-05-11 15:26:25
updated_at: 2026-05-11 15:26:33
sql:
  SELECT
      YEAR,
      MONTH,
      EXPENSETYPE,
      SUM(TOTAL_AMOUNT) AS total_expenses
  FROM
      TR_EXPENSE_ANALYSYS_V
  GROUP BY
      YEAR,
      MONTH,
      EXPENSETYPE
  ORDER BY
      YEAR,
      MONTH,
      EXPENSETYPE
  LIMIT 1000;

sql_query_summaries:
  [{"agent_id": "1", "sub_question": "show me total expenses by month and year and expense type", "summary": "This query retrieves the total expenses for each combination of year, month, and expense type from the TR_EXPENSE_ANALYSYS_V table. It groups the data by year, month, and expense type, then sums up the TOTAL_AMOUNT for each group. The results are ordered by year, month, and expense type, and only the first 1000 records are shown.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total expenses for each month and year, broken down by the type of expense. It uses the TR_EXPENSE_ANALYSYS_V table and summarizes the TOTAL_AMOUNT for each combination of year, month, and expense type.</p><hr><h4>What it shows</h4><table><thead><tr><th>Column</th><th>What it means</th></tr></thead><tbody><tr><td>YEAR</td><td>The year in which the expenses occurred</td></tr><tr><td>MONTH</td><td>The month in which the expenses occurred</td></tr><tr><td>EXPENSETYPE</td><td>The category or type of expense</td></tr><tr><td>total_expenses</td><td>The total amount spent for that year, month, and expense type</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list showing, for each year, month, and expense type, the total expenses recorded. This helps track spending patterns over time and by category.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>YEAR, MONTH, EXPENSETYPE, SUM(TOTAL_AMOUNT) AS total_expenses</td><td>Chooses the columns to display and calculates total expenses</td></tr><tr><td>FROM</td><td>TR_EXPENSE_ANALYSYS_V</td><td>Specifies the source table</td></tr><tr><td>GROUP BY</td><td>YEAR, MONTH, EXPENSETYPE</td><td>Groups data to summarize totals by year, month, and expense type</td></tr><tr><td>ORDER BY</td><td>YEAR, MONTH, EXPENSETYPE</td><td>Sorts the results for easier reading</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts output to the first 1000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 1
question: show me total by employee and month, show month total in column
chart: N
web: N
executed: Y
execution_time: 3.0
question_normalized: show_me_total_by_employee_and_month,_show_month_total_in_column
created_at: 2026-05-11 15:27:22
updated_at: 2026-05-11 15:27:29
sql:
  SELECT
      EMPLOYEENAME,
      MONTH,
      SUM(TOTAL_AMOUNT) AS month_total
  FROM TR_EXPENSE_ANALYSYS_V
  GROUP BY EMPLOYEENAME, MONTH
  ORDER BY EMPLOYEENAME, MONTH
  LIMIT 1000

sql_query_summaries:
  [{"agent_id": "1", "sub_question": "show me total by employee and month, show month total in column", "summary": "This query retrieves the total expenses for each employee, broken down by month. It uses the TR_EXPENSE_ANALYSYS_V table, groups the data by employee name and month, and calculates the sum of the TOTAL_AMOUNT for each group. The results are sorted by employee name and month, and only the first 1000 records are shown.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows the total expenses for each employee for each month. It lists each employee's name, the month, and the total amount they spent in that month.</p><hr><h4>What it shows</h4><table><thead><tr><th>Column</th><th>What it means</th></tr></thead><tbody><tr><td>EMPLOYEENAME</td><td>The name of the employee</td></tr><tr><td>MONTH</td><td>The month for the expense records</td></tr><tr><td>month_total</td><td>The total expenses for that employee in that month</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of employees with their total expenses for each month, showing up to 1000 rows.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>EMPLOYEENAME, MONTH, SUM(TOTAL_AMOUNT) AS month_total</td><td>Chooses columns to display and calculates monthly totals</td></tr><tr><td>FROM</td><td>TR_EXPENSE_ANALYSYS_V</td><td>Specifies the source table</td></tr><tr><td>GROUP BY</td><td>EMPLOYEENAME, MONTH</td><td>Groups data by employee and month</td></tr><tr><td>ORDER BY</td><td>EMPLOYEENAME, MONTH</td><td>Sorts results by employee and month</td></tr><tr><td>LIMIT</td><td>1000</td><td>Limits output to 1000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 1
question: show me claim documents of 2026
sql:
  SELECT RECEIPT
  FROM TR_EXPENSE_ANALYSYS_V
  WHERE YEAR = 2026
  ORDER BY RECEIPT
  LIMIT 1000;

chart: N
web: N
executed: Y
execution_time: 3.0
question_normalized: show_me_claim_documents_of_2026
created_at: 2026-05-12 08:53:20
updated_at: 2026-05-12 08:53:30
sql_query_summaries:
  [{"agent_id": "1", "sub_question": "show me claim documents of 2026", "summary": "This query retrieves a list of claim document receipts from the TR_EXPENSE_ANALYSYS_V table for the year 2026. It selects only the RECEIPT column, filters the results to include only those records where the YEAR is 2026, sorts the receipts in order, and limits the output to the first 1,000 entries.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query gets a list of claim document receipts for the year 2026 from the TR_EXPENSE_ANALYSYS_V table. It only shows the receipt numbers or identifiers for claims made in 2026, sorted in order, and displays up to 1,000 results.</p><h3>The Final Output</h3><p>The output will be a list of up to 1,000 claim document receipts from 2026, showing only the receipt identifier for each claim.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>RECEIPT</td><td>Shows the receipt identifier for each claim</td></tr><tr><td>FROM</td><td>TR_EXPENSE_ANALYSYS_V</td><td>Uses the expense analysis view as the data source</td></tr><tr><td>WHERE</td><td>YEAR = 2026</td><td>Filters to only claims from the year 2026</td></tr><tr><td>ORDER BY</td><td>RECEIPT</td><td>Sorts the receipts in order</td></tr><tr><td>LIMIT</td><td>1000</td><td>Limits the results to 1,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Show me accident details of VIN 1FDUF5GY7CEB33379
web: N
executed: Y
execution_time: 38.0
question_normalized: show_me_accident_details_of_vin_1fduf5gy7ceb33379
sql_query_summaries: []
created_at: 2026-05-12 09:50:13
updated_at: 2026-05-12 09:50:21
sql:
  SELECT
      a.VEHICLE_ACCIDENT_ID,
      a.ORG_ID,
      a.LOCATION_ID,
      a.WORK_PLACE_ID,
      wp.WORK_PLACE_NAME,
      wp.WORK_PLACE_ABRV AS CITY,
      a.TEAM_ID,
      t.TEAM_NAME AS ENTITY,
      a.VEHICLE_ID,
      COALESCE(a.VEHICLE_NO, v.VEHICLE_NO) AS VEHICLE_NO,
      COALESCE(a.VIN, v.VIN) AS VIN,
      v.PLATE,
      v.YEAR AS VEHICLE_YEAR,
      mk.MAKE AS VEHICLE_MAKE,
      mdl.MODEL AS VEHICLE_MODEL,
      v.PAX AS VEHICLE_CAPACITY,
      a.TRIP_ID,
      a.TRIP_DATE,
      a.ACCIDENT_DATE,
      a.ACCIDENT_LOCATION,
      a.ACCIDENT_LOCATION_GEO_CODE,
      a.ACCIDENT_REPORTED_BY,
      a.STATUS,
      a.NOTES,
      a.AREA_OF_DAMAGE,
      a.ACCIDENT_INCIDENT_TYPE,
      accident_type.LOOKUP_MEANING AS ACCIDENT_INCIDENT_TYPE_NAME,
      a.ROAD_CONDITION,
      road_condition.LOOKUP_MEANING AS ROAD_CONDITION_NAME,
      a.ROAD_TYPE,
      road_type.LOOKUP_MEANING AS ROAD_TYPE_NAME,
      a.SEVERITY,
      severity.LOOKUP_MEANING AS SEVERITY_NAME,
      a.WEATHER_CONDITION,
      weather.LOOKUP_MEANING AS WEATHER_CONDITION_NAME,
      a.DAY_LIGHT_CONDITION,
      daylight.LOOKUP_MEANING AS DAY_LIGHT_CONDITION_NAME,
      a.VEHICLE_DIRECTION,
      direction_lkp.LOOKUP_MEANING AS VEHICLE_DIRECTION_NAME,
      a.DRIVER_ID,
      a.DRIVER_NAME,
      a.DRIVER_ADDRESS,
      a.DRIVER_EMAIL,
      a.DRIVER_BUSINESS_PHONE,
      a.DRIVER_HOME_PHONE,
      a.DRIVER_LICENSE_NO,
      a.DRIVER_LICENSE_ISSUED_STATE,
      a.DRIVER_LICENSE_EXP_DATE,
      a.DRIVER_INJURED,
      a.CARGO_DAMAGED,
      a.HAZARDOUS,
      a.OTHER_DRIVERS_INVOLCED,
      a.PROPERTY_DAMAGED,
      a.INJURED,
      a.OTHER_VEHICLES_INVOLVED,
      a.PASSENGER_INVOLVED,
      a.POLICE_INVOLVED,
      a.POLICE_AREA,
      a.VEHICLE_DRIVABLE,
      a.TOW_COMPANY,
      a.TOW_COMPANY_PHONE,
      a.PREVENTABLE,
      a.DOT_REPORTABLE,
      a.SCHOOL_ZONE,
      a.CONSTRUCTION_ZONE,
      a.ON_PREMISE,
      a.TELEMATICS,
      a.EVENT_RECORDER,
      a.AVOIDANCE_SYSTEM,
      a.TOTAL_LOSS,
      a.FUEL_SPILL,
      a.CARGO_SPILL,
      a.HAZMAT_SPILL,
      a.FATALITIES,
      a.TOTAL_PAX,
      a.TOTAL_INJURED_PAX,
      a.LOSS_CLAIM_FILED,
      a.REPORT_TO_INSURANCE,
      a.SEND_TO_INSURANCE,
      a.INSURANCE_REPORT_DATE,
      a.DRIVER_STATEMENT_DATE,
      a.DRIVER_STATEMENT,
      a.OUR_DAMAGE_COSTS,
      a.PAID_TO_OTHER_VEHICLE,
      a.RECIEVED_PAYMENT,
      a.LOST_REVENUE,
      COALESCE(ov.other_vehicle_count, 0) AS OTHER_VEHICLE_COUNT,
      COALESCE(op.other_property_count, 0) AS OTHER_PROPERTY_COUNT,
      COALESCE(p.passenger_count, 0) AS PASSENGER_COUNT,
      COALESCE(p.injured_passenger_count, 0) AS INJURED_PASSENGER_COUNT,
      COALESCE(w.witness_count, 0) AS WITNESS_COUNT,
      ov.other_vehicle_summary,
      op.other_property_summary,
      p.passenger_summary,
      w.witness_summary,
      a.INSERTED_DATE,
      a.UPDATED_DATE,
      a.INSERTED_BY,
      a.UPDATED_BY,
      a.IS_DEFAULT,
      a.DEL
  FROM FM_VEHICLES_ACCIDENT a
  LEFT JOIN FM_VEHICLES v
      ON v.VEHICLE_ID = a.VEHICLE_ID
     AND v.DEL = 'N'
  LEFT JOIN FM_VEHICLE_MAKE mk
      ON mk.MAKE_ID = v.MAKE_ID
     AND mk.DEL = 'N'
  LEFT JOIN FM_VEHICLE_MODEL mdl
      ON mdl.MODEL_ID = v.MODEL_ID
     AND mdl.DEL = 'N'
  LEFT JOIN ADMIN_WORK_PLACE wp
      ON wp.WORK_PLACE_ID = a.WORK_PLACE_ID
     AND wp.DEL = 'N'
  LEFT JOIN ADMIN_TEAMS t
      ON t.TEAM_ID = a.TEAM_ID
     AND t.DEL = 'N'
  LEFT JOIN ADMIN_LOOKUPS accident_type
      ON accident_type.LOOKUP_ID = a.ACCIDENT_INCIDENT_TYPE
     AND accident_type.DEL = 'N'
     AND accident_type.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS road_condition
      ON road_condition.LOOKUP_ID = a.ROAD_CONDITION
     AND road_condition.DEL = 'N'
     AND road_condition.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS road_type
      ON road_type.LOOKUP_ID = a.ROAD_TYPE
     AND road_type.DEL = 'N'
     AND road_type.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS severity
      ON severity.LOOKUP_ID = a.SEVERITY
     AND severity.DEL = 'N'
     AND severity.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS weather
      ON weather.LOOKUP_ID = a.WEATHER_CONDITION
     AND weather.DEL = 'N'
     AND weather.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS daylight
      ON daylight.LOOKUP_ID = a.DAY_LIGHT_CONDITION
     AND daylight.DEL = 'N'
     AND daylight.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS direction_lkp
      ON direction_lkp.LOOKUP_ID = a.VEHICLE_DIRECTION
     AND direction_lkp.DEL = 'N'
     AND direction_lkp.VALID = 'Y'
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS other_vehicle_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Owner: ', OWNER_NAME),
                  CONCAT('Driver: ', DRIVER_NAME),
                  CONCAT('Plate: ', VEHICLE_PLATE),
                  CONCAT('Vehicle: ', VEHICLE_MAKE_MODEL),
                  CONCAT('Injured: ', INJURED)
              )
              SEPARATOR ' || '
          ) AS other_vehicle_summary
      FROM FM_VEHICLES_ACCIDENT_OTHER_VEHICLES
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) ov
      ON ov.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS other_property_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Owner: ', OWNER_NAME),
                  CONCAT('Address: ', PROPERTY_EXACT_ADDRESS),
                  CONCAT('Damage: ', AREA_OF_DAMAGE),
                  CONCAT('Cost: ', DAMAGED_COST)
              )
              SEPARATOR ' || '
          ) AS other_property_summary
      FROM FM_VEHICLES_ACCIDENT_OTHER_PROPERTY
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) op
      ON op.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS passenger_count,
          SUM(CASE WHEN INJURED = 'Y' THEN 1 ELSE 0 END) AS injured_passenger_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Name: ', PASSENGER_NAME),
                  CONCAT('Phone: ', PASSENGER_PHONE),
                  CONCAT('Injured: ', INJURED),
                  CONCAT('Injury Details: ', INJURY_DETAILS)
              )
              SEPARATOR ' || '
          ) AS passenger_summary
      FROM FM_VEHICLES_ACCIDENT_PASSENGER_DETAILS
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) p
      ON p.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS witness_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Name: ', WITNESS_NAME),
                  CONCAT('Phone: ', WITNESS_PHONE),
                  CONCAT('Address: ', WITNESS_ADDRESS)
              )
              SEPARATOR ' || '
          ) AS witness_summary
      FROM FM_VEHICLES_ACCIDENT_WITNESS
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) w
      ON w.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  WHERE a.DEL = 'N'
    AND COALESCE(a.VIN, v.VIN) = '1FDUF5GY7CEB33379'
  ORDER BY a.VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_DATE'].tolist(),
              'y': df['SEVERITY'].tolist(),
              'type': 'bar',
              'name': 'Accident Severity'
          }
      ],
      'layout': {
          'title': 'Accident Severity Over Time for VIN 1FDUF5GY7CEB33379',
          'xaxis': {'title': 'Accident Date'},
          'yaxis': {'title': 'Severity'}
      }
  }


user_id: 1
agent_id: 2
question: Show me accident details along with images for VIN YE2XC82B4K3081255
web: N
executed: Y
execution_time: 14.0
question_normalized: show_me_accident_details_along_with_images_for_vin_ye2xc82b4k3081255
created_at: 2026-05-12 10:30:51
updated_at: 2026-05-12 10:30:57
sql:
  SELECT
      a.VEHICLE_ACCIDENT_ID,
      a.ORG_ID,
      a.LOCATION_ID,
      a.WORK_PLACE_ID,
      a.TRIP_ID,
      a.TRIP_DATE,
      a.ACCIDENT_DATE,
      a.ACCIDENT_LOCATION,
      a.ACCIDENT_LOCATION_GEO_CODE,
      a.ACCIDENT_REPORTED_BY,
      a.STATUS,
      a.NOTES,
      a.AREA_OF_DAMAGE,
      a.ACCIDENT_INCIDENT_TYPE,
      a.ROAD_CONDITION,
      a.ROAD_TYPE,
      a.SEVERITY,
      a.WEATHER_CONDITION,
      a.DAY_LIGHT_CONDITION,
      a.VEHICLE_DIRECTION,
      a.DRIVER_ID,
      a.DRIVER_NAME,
      a.DRIVER_ADDRESS,
      a.DRIVER_EMAIL,
      a.DRIVER_BUSINESS_PHONE,
      a.DRIVER_HOME_PHONE,
      a.DRIVER_LICENSE_NO,
      a.DRIVER_LICENSE_ISSUED_STATE,
      a.DRIVER_LICENSE_EXP_DATE,
      a.DRIVER_INJURED,
      a.CARGO_DAMAGED,
      a.HAZARDOUS,
      a.OTHER_DRIVERS_INVOLCED,
      a.PROPERTY_DAMAGED,
      a.INJURED,
      a.OTHER_VEHICLES_INVOLVED,
      a.PASSENGER_INVOLVED,
      a.POLICE_INVOLVED,
      a.POLICE_AREA,
      a.VEHICLE_DRIVABLE,
      a.TOW_COMPANY,
      a.TOW_COMPANY_PHONE,
      a.PREVENTABLE,
      a.DOT_REPORTABLE,
      a.SCHOOL_ZONE,
      a.CONSTRUCTION_ZONE,
      a.ON_PREMISE,
      a.TELEMATICS,
      a.EVENT_RECORDER,
      a.AVOIDANCE_SYSTEM,
      a.TOTAL_LOSS,
      a.FUEL_SPILL,
      a.CARGO_SPILL,
      a.HAZMAT_SPILL,
      a.FATALITIES,
      a.TOTAL_PAX,
      a.TOTAL_INJURED_PAX,
      a.LOSS_CLAIM_FILED,
      a.REPORT_TO_INSURANCE,
      a.SEND_TO_INSURANCE,
      a.INSURANCE_REPORT_DATE,
      a.DRIVER_STATEMENT_DATE,
      a.DRIVER_STATEMENT,
      a.OUR_DAMAGE_COSTS,
      a.PAID_TO_OTHER_VEHICLE,
      a.RECIEVED_PAYMENT,
      a.LOST_REVENUE,
      a.INSERTED_DATE,
      a.UPDATED_DATE,
      a.INSERTED_BY,
      a.UPDATED_BY,
      a.IS_DEFAULT,
      a.DEL,
      v.VIN
  FROM FM_VEHICLES_ACCIDENT a
  LEFT JOIN FM_VEHICLES v
      ON v.VEHICLE_ID = a.VEHICLE_ID
     AND v.DEL = 'N'
  WHERE a.DEL = 'N'
    AND v.VIN = 'YE2XC82B4K3081255'
  ORDER BY a.VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_DATE'].tolist(),
              'y': df['SEVERITY'].tolist(),
              'type': 'bar',
              'name': 'Severity by Accident Date'
          }
      ],
      'layout': {
          'title': 'Accident Severity by Date for VIN YE2XC82B4K3081255',
          'xaxis': {'title': 'Accident Date'},
          'yaxis': {'title': 'Severity'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Show me accident details along with images for VIN YE2XC82B4K3081255", "summary": "This query retrieves detailed accident records for the vehicle with VIN YE2XC82B4K3081255, including information about the accident, driver, location, damages, and related insurance details. It pulls data from the accident and vehicle tables, ensuring only active (not deleted) records are included, and limits the results to 1000 entries. The query does not directly retrieve images, but provides comprehensive accident data for the specified vehicle.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query collects detailed information about all recorded accidents involving the vehicle with VIN YE2XC82B4K3081255. It includes accident specifics, driver and location details, damage assessments, insurance information, and other related fields. The data is sourced from accident and vehicle records, ensuring only active (not deleted) entries are shown.</p><hr><h3>The Final Output</h3><p>The output will be a list of up to 1000 accident records for the specified vehicle, each containing comprehensive details about the incident, but not including images directly.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>All accident and vehicle details</td><td>Specifies which columns to retrieve</td></tr><tr><td>FROM</td><td>FM_VEHICLES_ACCIDENT, FM_VEHICLES</td><td>Specifies source tables</td></tr><tr><td>LEFT JOIN</td><td>FM_VEHICLES ON VEHICLE_ID and DEL = 'N'</td><td>Links accident to vehicle, only active vehicles</td></tr><tr><td>WHERE</td><td>a.DEL = 'N' AND v.VIN = 'YE2XC82B4K3081255'</td><td>Filters to active accidents for the specified VIN</td></tr><tr><td>ORDER BY</td><td>a.VEHICLE_ACCIDENT_ID</td><td>Sorts results by accident ID</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts output to 1000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Show me accident images for VIN YE2XC82B4K3081255.
chart: N
web: N
executed: N
execution_time: 7.0
question_normalized: show_me_accident_images_for_vin_ye2xc82b4k3081255.
created_at: 2026-05-12 10:31:48
updated_at: 2026-05-12 10:31:48
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (1146, "Table 'ta_US000316000245.FM_VEHICLES_ACCIDENT_IMAGES' doesn't exist")
  Failed SQL:
  ```sql
  SELECT
      a.VEHICLE_ACCIDENT_ID,
      a.VIN,
      img.IMAGE_URL,
      img.IMAGE_DESCRIPTION
  FROM FM_VEHICLES_ACCIDENT a
  INNER JOIN FM_VEHICLES_ACCIDENT_IMAGES img
      ON img.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  WHERE a.VIN = 'YE2XC82B4K3081255'
    AND a.DEL = 'N'
    AND img.DEL = 'N'
  ORDER BY a.VEHICLE_ACCIDENT_ID, img.IMAGE_URL
  LIMIT 1000;
  ```


user_id: 1
agent_id: 2
question: List all incidents for VIN YE2XC82B4K3081255 where insurance claims were filed.
chart: N
web: N
executed: Y
execution_time: 5.0
question_normalized: list_all_incidents_for_vin_ye2xc82b4k3081255_where_insurance_claims_were_filed.
sql_query_summaries: []
created_at: 2026-05-12 10:32:23
updated_at: 2026-05-12 10:32:30
sql:
  SELECT
      VEHICLE_ACCIDENT_ID,
      VIN,
      ACCIDENT_DATE,
      ACCIDENT_LOCATION,
      LOSS_CLAIM_FILED,
      INSURANCE_REPORT_DATE,
      OUR_DAMAGE_COSTS,
      PAID_TO_OTHER_VEHICLE
  FROM FM_VEHICLES_ACCIDENT
  WHERE VIN = 'YE2XC82B4K3081255'
    AND LOSS_CLAIM_FILED = 'Y'
    AND DEL = 'N'
  ORDER BY ACCIDENT_DATE DESC
  LIMIT 1000;


user_id: 1
agent_id: 2
question: Show me accident details for VIN 2MG3JMBAXFW067038
web: N
executed: Y
execution_time: 36.0
question_normalized: show_me_accident_details_for_vin_2mg3jmbaxfw067038
sql_query_summaries: []
created_at: 2026-05-12 10:36:37
updated_at: 2026-05-12 10:36:46
sql:
  SELECT
      a.VEHICLE_ACCIDENT_ID,
      a.ORG_ID,
      a.LOCATION_ID,
      a.WORK_PLACE_ID,
      wp.WORK_PLACE_NAME,
      wp.WORK_PLACE_ABRV AS CITY,
      a.TEAM_ID,
      t.TEAM_NAME AS ENTITY,
      a.VEHICLE_ID,
      COALESCE(a.VEHICLE_NO, v.VEHICLE_NO) AS VEHICLE_NO,
      COALESCE(a.VIN, v.VIN) AS VIN,
      v.PLATE,
      v.YEAR AS VEHICLE_YEAR,
      mk.MAKE AS VEHICLE_MAKE,
      mdl.MODEL AS VEHICLE_MODEL,
      v.PAX AS VEHICLE_CAPACITY,
      a.TRIP_ID,
      a.TRIP_DATE,
      a.ACCIDENT_DATE,
      a.ACCIDENT_LOCATION,
      a.ACCIDENT_LOCATION_GEO_CODE,
      a.ACCIDENT_REPORTED_BY,
      a.STATUS,
      a.NOTES,
      a.AREA_OF_DAMAGE,
      a.ACCIDENT_INCIDENT_TYPE,
      accident_type.LOOKUP_MEANING AS ACCIDENT_INCIDENT_TYPE_NAME,
      a.ROAD_CONDITION,
      road_condition.LOOKUP_MEANING AS ROAD_CONDITION_NAME,
      a.ROAD_TYPE,
      road_type.LOOKUP_MEANING AS ROAD_TYPE_NAME,
      a.SEVERITY,
      severity.LOOKUP_MEANING AS SEVERITY_NAME,
      a.WEATHER_CONDITION,
      weather.LOOKUP_MEANING AS WEATHER_CONDITION_NAME,
      a.DAY_LIGHT_CONDITION,
      daylight.LOOKUP_MEANING AS DAY_LIGHT_CONDITION_NAME,
      a.VEHICLE_DIRECTION,
      direction_lkp.LOOKUP_MEANING AS VEHICLE_DIRECTION_NAME,
      a.DRIVER_ID,
      a.DRIVER_NAME,
      a.DRIVER_ADDRESS,
      a.DRIVER_EMAIL,
      a.DRIVER_BUSINESS_PHONE,
      a.DRIVER_HOME_PHONE,
      a.DRIVER_LICENSE_NO,
      a.DRIVER_LICENSE_ISSUED_STATE,
      a.DRIVER_LICENSE_EXP_DATE,
      a.DRIVER_INJURED,
      a.CARGO_DAMAGED,
      a.HAZARDOUS,
      a.OTHER_DRIVERS_INVOLCED,
      a.PROPERTY_DAMAGED,
      a.INJURED,
      a.OTHER_VEHICLES_INVOLVED,
      a.PASSENGER_INVOLVED,
      a.POLICE_INVOLVED,
      a.POLICE_AREA,
      a.VEHICLE_DRIVABLE,
      a.TOW_COMPANY,
      a.TOW_COMPANY_PHONE,
      a.PREVENTABLE,
      a.DOT_REPORTABLE,
      a.SCHOOL_ZONE,
      a.CONSTRUCTION_ZONE,
      a.ON_PREMISE,
      a.TELEMATICS,
      a.EVENT_RECORDER,
      a.AVOIDANCE_SYSTEM,
      a.TOTAL_LOSS,
      a.FUEL_SPILL,
      a.CARGO_SPILL,
      a.HAZMAT_SPILL,
      a.FATALITIES,
      a.TOTAL_PAX,
      a.TOTAL_INJURED_PAX,
      a.LOSS_CLAIM_FILED,
      a.REPORT_TO_INSURANCE,
      a.SEND_TO_INSURANCE,
      a.INSURANCE_REPORT_DATE,
      a.DRIVER_STATEMENT_DATE,
      a.DRIVER_STATEMENT,
      a.OUR_DAMAGE_COSTS,
      a.PAID_TO_OTHER_VEHICLE,
      a.RECIEVED_PAYMENT,
      a.LOST_REVENUE,
      COALESCE(ov.other_vehicle_count, 0) AS OTHER_VEHICLE_COUNT,
      COALESCE(op.other_property_count, 0) AS OTHER_PROPERTY_COUNT,
      COALESCE(p.passenger_count, 0) AS PASSENGER_COUNT,
      COALESCE(p.injured_passenger_count, 0) AS INJURED_PASSENGER_COUNT,
      COALESCE(w.witness_count, 0) AS WITNESS_COUNT,
      ov.other_vehicle_summary,
      op.other_property_summary,
      p.passenger_summary,
      w.witness_summary,
      a.INSERTED_DATE,
      a.UPDATED_DATE,
      a.INSERTED_BY,
      a.UPDATED_BY,
      a.IS_DEFAULT,
      a.DEL
  FROM FM_VEHICLES_ACCIDENT a
  LEFT JOIN FM_VEHICLES v
      ON v.VEHICLE_ID = a.VEHICLE_ID
     AND v.DEL = 'N'
  LEFT JOIN FM_VEHICLE_MAKE mk
      ON mk.MAKE_ID = v.MAKE_ID
     AND mk.DEL = 'N'
  LEFT JOIN FM_VEHICLE_MODEL mdl
      ON mdl.MODEL_ID = v.MODEL_ID
     AND mdl.DEL = 'N'
  LEFT JOIN ADMIN_WORK_PLACE wp
      ON wp.WORK_PLACE_ID = a.WORK_PLACE_ID
     AND wp.DEL = 'N'
  LEFT JOIN ADMIN_TEAMS t
      ON t.TEAM_ID = a.TEAM_ID
     AND t.DEL = 'N'
  LEFT JOIN ADMIN_LOOKUPS accident_type
      ON accident_type.LOOKUP_ID = a.ACCIDENT_INCIDENT_TYPE
     AND accident_type.DEL = 'N'
     AND accident_type.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS road_condition
      ON road_condition.LOOKUP_ID = a.ROAD_CONDITION
     AND road_condition.DEL = 'N'
     AND road_condition.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS road_type
      ON road_type.LOOKUP_ID = a.ROAD_TYPE
     AND road_type.DEL = 'N'
     AND road_type.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS severity
      ON severity.LOOKUP_ID = a.SEVERITY
     AND severity.DEL = 'N'
     AND severity.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS weather
      ON weather.LOOKUP_ID = a.WEATHER_CONDITION
     AND weather.DEL = 'N'
     AND weather.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS daylight
      ON daylight.LOOKUP_ID = a.DAY_LIGHT_CONDITION
     AND daylight.DEL = 'N'
     AND daylight.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS direction_lkp
      ON direction_lkp.LOOKUP_ID = a.VEHICLE_DIRECTION
     AND direction_lkp.DEL = 'N'
     AND direction_lkp.VALID = 'Y'
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS other_vehicle_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Owner: ', OWNER_NAME),
                  CONCAT('Driver: ', DRIVER_NAME),
                  CONCAT('Plate: ', VEHICLE_PLATE),
                  CONCAT('Vehicle: ', VEHICLE_MAKE_MODEL),
                  CONCAT('Injured: ', INJURED)
              )
              SEPARATOR ' || '
          ) AS other_vehicle_summary
      FROM FM_VEHICLES_ACCIDENT_OTHER_VEHICLES
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) ov
      ON ov.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS other_property_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Owner: ', OWNER_NAME),
                  CONCAT('Address: ', PROPERTY_EXACT_ADDRESS),
                  CONCAT('Damage: ', AREA_OF_DAMAGE),
                  CONCAT('Cost: ', DAMAGED_COST)
              )
              SEPARATOR ' || '
          ) AS other_property_summary
      FROM FM_VEHICLES_ACCIDENT_OTHER_PROPERTY
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) op
      ON op.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS passenger_count,
          SUM(CASE WHEN INJURED = 'Y' THEN 1 ELSE 0 END) AS injured_passenger_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Name: ', PASSENGER_NAME),
                  CONCAT('Phone: ', PASSENGER_PHONE),
                  CONCAT('Injured: ', INJURED),
                  CONCAT('Injury Details: ', INJURY_DETAILS)
              )
              SEPARATOR ' || '
          ) AS passenger_summary
      FROM FM_VEHICLES_ACCIDENT_PASSENGER_DETAILS
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) p
      ON p.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS witness_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Name: ', WITNESS_NAME),
                  CONCAT('Phone: ', WITNESS_PHONE),
                  CONCAT('Address: ', WITNESS_ADDRESS)
              )
              SEPARATOR ' || '
          ) AS witness_summary
      FROM FM_VEHICLES_ACCIDENT_WITNESS
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) w
      ON w.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  WHERE a.DEL = 'N'
    AND COALESCE(a.VIN, v.VIN) = '2MG3JMBAXFW067038'
  ORDER BY a.VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_DATE'].tolist(),
              'y': df['SEVERITY'].tolist(),
              'type': 'bar',
              'name': 'Accident Severity by Date'
          }
      ],
      'layout': {
          'title': 'Accident Severity Over Time for VIN 2MG3JMBAXFW067038',
          'xaxis': {'title': 'Accident Date'},
          'yaxis': {'title': 'Severity'}
      }
  }


user_id: 1
agent_id: 2
question: Show me accident details for VIN 2MG3JMBAXFW067038
web: N
executed: Y
execution_time: 2.0
question_normalized: show_me_accident_details_for_vin_2mg3jmbaxfw067038
sql_query_summaries: []
created_at: 2026-05-12 10:41:29
updated_at: 2026-05-12 10:41:37
sql:
  SELECT
      a.VEHICLE_ACCIDENT_ID,
      a.ORG_ID,
      a.LOCATION_ID,
      a.WORK_PLACE_ID,
      wp.WORK_PLACE_NAME,
      wp.WORK_PLACE_ABRV AS CITY,
      a.TEAM_ID,
      t.TEAM_NAME AS ENTITY,
      a.VEHICLE_ID,
      COALESCE(a.VEHICLE_NO, v.VEHICLE_NO) AS VEHICLE_NO,
      COALESCE(a.VIN, v.VIN) AS VIN,
      v.PLATE,
      v.YEAR AS VEHICLE_YEAR,
      mk.MAKE AS VEHICLE_MAKE,
      mdl.MODEL AS VEHICLE_MODEL,
      v.PAX AS VEHICLE_CAPACITY,
      a.TRIP_ID,
      a.TRIP_DATE,
      a.ACCIDENT_DATE,
      a.ACCIDENT_LOCATION,
      a.ACCIDENT_LOCATION_GEO_CODE,
      a.ACCIDENT_REPORTED_BY,
      a.STATUS,
      a.NOTES,
      a.AREA_OF_DAMAGE,
      a.ACCIDENT_INCIDENT_TYPE,
      accident_type.LOOKUP_MEANING AS ACCIDENT_INCIDENT_TYPE_NAME,
      a.ROAD_CONDITION,
      road_condition.LOOKUP_MEANING AS ROAD_CONDITION_NAME,
      a.ROAD_TYPE,
      road_type.LOOKUP_MEANING AS ROAD_TYPE_NAME,
      a.SEVERITY,
      severity.LOOKUP_MEANING AS SEVERITY_NAME,
      a.WEATHER_CONDITION,
      weather.LOOKUP_MEANING AS WEATHER_CONDITION_NAME,
      a.DAY_LIGHT_CONDITION,
      daylight.LOOKUP_MEANING AS DAY_LIGHT_CONDITION_NAME,
      a.VEHICLE_DIRECTION,
      direction_lkp.LOOKUP_MEANING AS VEHICLE_DIRECTION_NAME,
      a.DRIVER_ID,
      a.DRIVER_NAME,
      a.DRIVER_ADDRESS,
      a.DRIVER_EMAIL,
      a.DRIVER_BUSINESS_PHONE,
      a.DRIVER_HOME_PHONE,
      a.DRIVER_LICENSE_NO,
      a.DRIVER_LICENSE_ISSUED_STATE,
      a.DRIVER_LICENSE_EXP_DATE,
      a.DRIVER_INJURED,
      a.CARGO_DAMAGED,
      a.HAZARDOUS,
      a.OTHER_DRIVERS_INVOLCED,
      a.PROPERTY_DAMAGED,
      a.INJURED,
      a.OTHER_VEHICLES_INVOLVED,
      a.PASSENGER_INVOLVED,
      a.POLICE_INVOLVED,
      a.POLICE_AREA,
      a.VEHICLE_DRIVABLE,
      a.TOW_COMPANY,
      a.TOW_COMPANY_PHONE,
      a.PREVENTABLE,
      a.DOT_REPORTABLE,
      a.SCHOOL_ZONE,
      a.CONSTRUCTION_ZONE,
      a.ON_PREMISE,
      a.TELEMATICS,
      a.EVENT_RECORDER,
      a.AVOIDANCE_SYSTEM,
      a.TOTAL_LOSS,
      a.FUEL_SPILL,
      a.CARGO_SPILL,
      a.HAZMAT_SPILL,
      a.FATALITIES,
      a.TOTAL_PAX,
      a.TOTAL_INJURED_PAX,
      a.LOSS_CLAIM_FILED,
      a.REPORT_TO_INSURANCE,
      a.SEND_TO_INSURANCE,
      a.INSURANCE_REPORT_DATE,
      a.DRIVER_STATEMENT_DATE,
      a.DRIVER_STATEMENT,
      a.OUR_DAMAGE_COSTS,
      a.PAID_TO_OTHER_VEHICLE,
      a.RECIEVED_PAYMENT,
      a.LOST_REVENUE,
      COALESCE(ov.other_vehicle_count, 0) AS OTHER_VEHICLE_COUNT,
      COALESCE(op.other_property_count, 0) AS OTHER_PROPERTY_COUNT,
      COALESCE(p.passenger_count, 0) AS PASSENGER_COUNT,
      COALESCE(p.injured_passenger_count, 0) AS INJURED_PASSENGER_COUNT,
      COALESCE(w.witness_count, 0) AS WITNESS_COUNT,
      ov.other_vehicle_summary,
      op.other_property_summary,
      p.passenger_summary,
      w.witness_summary,
      a.INSERTED_DATE,
      a.UPDATED_DATE,
      a.INSERTED_BY,
      a.UPDATED_BY,
      a.IS_DEFAULT,
      a.DEL
  FROM FM_VEHICLES_ACCIDENT a
  LEFT JOIN FM_VEHICLES v
      ON v.VEHICLE_ID = a.VEHICLE_ID
     AND v.DEL = 'N'
  LEFT JOIN FM_VEHICLE_MAKE mk
      ON mk.MAKE_ID = v.MAKE_ID
     AND mk.DEL = 'N'
  LEFT JOIN FM_VEHICLE_MODEL mdl
      ON mdl.MODEL_ID = v.MODEL_ID
     AND mdl.DEL = 'N'
  LEFT JOIN ADMIN_WORK_PLACE wp
      ON wp.WORK_PLACE_ID = a.WORK_PLACE_ID
     AND wp.DEL = 'N'
  LEFT JOIN ADMIN_TEAMS t
      ON t.TEAM_ID = a.TEAM_ID
     AND t.DEL = 'N'
  LEFT JOIN ADMIN_LOOKUPS accident_type
      ON accident_type.LOOKUP_ID = a.ACCIDENT_INCIDENT_TYPE
     AND accident_type.DEL = 'N'
     AND accident_type.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS road_condition
      ON road_condition.LOOKUP_ID = a.ROAD_CONDITION
     AND road_condition.DEL = 'N'
     AND road_condition.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS road_type
      ON road_type.LOOKUP_ID = a.ROAD_TYPE
     AND road_type.DEL = 'N'
     AND road_type.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS severity
      ON severity.LOOKUP_ID = a.SEVERITY
     AND severity.DEL = 'N'
     AND severity.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS weather
      ON weather.LOOKUP_ID = a.WEATHER_CONDITION
     AND weather.DEL = 'N'
     AND weather.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS daylight
      ON daylight.LOOKUP_ID = a.DAY_LIGHT_CONDITION
     AND daylight.DEL = 'N'
     AND daylight.VALID = 'Y'
  LEFT JOIN ADMIN_LOOKUPS direction_lkp
      ON direction_lkp.LOOKUP_ID = a.VEHICLE_DIRECTION
     AND direction_lkp.DEL = 'N'
     AND direction_lkp.VALID = 'Y'
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS other_vehicle_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Owner: ', OWNER_NAME),
                  CONCAT('Driver: ', DRIVER_NAME),
                  CONCAT('Plate: ', VEHICLE_PLATE),
                  CONCAT('Vehicle: ', VEHICLE_MAKE_MODEL),
                  CONCAT('Injured: ', INJURED)
              )
              SEPARATOR ' || '
          ) AS other_vehicle_summary
      FROM FM_VEHICLES_ACCIDENT_OTHER_VEHICLES
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) ov
      ON ov.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS other_property_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Owner: ', OWNER_NAME),
                  CONCAT('Address: ', PROPERTY_EXACT_ADDRESS),
                  CONCAT('Damage: ', AREA_OF_DAMAGE),
                  CONCAT('Cost: ', DAMAGED_COST)
              )
              SEPARATOR ' || '
          ) AS other_property_summary
      FROM FM_VEHICLES_ACCIDENT_OTHER_PROPERTY
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) op
      ON op.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS passenger_count,
          SUM(CASE WHEN INJURED = 'Y' THEN 1 ELSE 0 END) AS injured_passenger_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Name: ', PASSENGER_NAME),
                  CONCAT('Phone: ', PASSENGER_PHONE),
                  CONCAT('Injured: ', INJURED),
                  CONCAT('Injury Details: ', INJURY_DETAILS)
              )
              SEPARATOR ' || '
          ) AS passenger_summary
      FROM FM_VEHICLES_ACCIDENT_PASSENGER_DETAILS
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) p
      ON p.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  LEFT JOIN (
      SELECT
          VEHICLE_ACCIDENT_ID,
          COUNT(*) AS witness_count,
          GROUP_CONCAT(
              CONCAT_WS(
                  ' | ',
                  CONCAT('Name: ', WITNESS_NAME),
                  CONCAT('Phone: ', WITNESS_PHONE),
                  CONCAT('Address: ', WITNESS_ADDRESS)
              )
              SEPARATOR ' || '
          ) AS witness_summary
      FROM FM_VEHICLES_ACCIDENT_WITNESS
      WHERE DEL = 'N'
      GROUP BY VEHICLE_ACCIDENT_ID
  ) w
      ON w.VEHICLE_ACCIDENT_ID = a.VEHICLE_ACCIDENT_ID
  WHERE a.DEL = 'N'
    AND COALESCE(a.VIN, v.VIN) = '2MG3JMBAXFW067038'
  ORDER BY a.VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_DATE'].tolist(),
              'y': df['SEVERITY_NAME'].tolist(),
              'type': 'bar',
              'name': 'Accident Severity'
          }
      ],
      'layout': {
          'title': 'Accident Details for VIN 2MG3JMBAXFW067038',
          'xaxis': {'title': 'Accident Date'},
          'yaxis': {'title': 'Severity'}
      }
  }


user_id: 1
agent_id: 2
question: Show accident images for VIN 2MG3JMBAXFW067038.
chart: N
web: N
executed: N
execution_time: 7.0
question_normalized: show_accident_images_for_vin_2mg3jmbaxfw067038.
created_at: 2026-05-12 10:42:26
updated_at: 2026-05-12 10:42:26
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (1146, "Table 'ta_US000316000245.FM_VEHICLES_ACCIDENT_IMAGES' doesn't exist")
  Failed SQL:
  ```sql
  SELECT
      a.VEHICLE_ACCIDENT_ID,
      a.VIN,
      i.IMAGE_URL,
      i.IMAGE_DESC,
      i.INSERTED_DATE
  FROM FM_VEHICLES_ACCIDENT a
  JOIN FM_VEHICLES v
      ON v.VEHICLE_ID = a.VEHICLE_ID
  JOIN FM_VEHICLES_ACCIDENT_IMAGES i
      ON a.VEHICLE_ACCIDENT_ID = i.VEHICLE_ACCIDENT_ID
  WHERE a.VIN = '2MG3JMBAXFW067038'
    AND a.DEL = 'N'
    AND i.DEL = 'N'
  ORDER BY i.INSERTED_DATE DESC
  LIMIT 1000;
  ```


user_id: 1
agent_id: 2
question: Show me accident details for VIN 2MG3JMBAXFW067038 along with images
web: N
executed: Y
execution_time: 12.0
question_normalized: show_me_accident_details_for_vin_2mg3jmbaxfw067038_along_with_images
created_at: 2026-05-12 10:47:47
updated_at: 2026-05-12 10:47:55
sql:
  SELECT
      VEHICLE_ACCIDENT_ID,
      ORG_ID,
      LOCATION_ID,
      WORK_PLACE_ID,
      WORK_PLACE_NAME,
      CITY,
      TEAM_ID,
      ENTITY,
      VEHICLE_ID,
      VEHICLE_NO,
      VIN,
      PLATE,
      VEHICLE_YEAR,
      VEHICLE_MAKE,
      VEHICLE_MODEL,
      VEHICLE_CAPACITY,
      TRIP_ID,
      TRIP_DATE,
      ACCIDENT_DATE,
      ACCIDENT_LOCATION,
      ACCIDENT_LOCATION_GEO_CODE,
      ACCIDENT_REPORTED_BY,
      STATUS,
      NOTES,
      AREA_OF_DAMAGE,
      ACCIDENT_INCIDENT_TYPE,
      ACCIDENT_INCIDENT_TYPE_NAME,
      ROAD_CONDITION,
      ROAD_CONDITION_NAME,
      ROAD_TYPE,
      ROAD_TYPE_NAME,
      SEVERITY,
      SEVERITY_NAME,
      WEATHER_CONDITION,
      WEATHER_CONDITION_NAME,
      DAY_LIGHT_CONDITION,
      DAY_LIGHT_CONDITION_NAME,
      VEHICLE_DIRECTION,
      VEHICLE_DIRECTION_NAME,
      DRIVER_ID,
      DRIVER_NAME,
      DRIVER_ADDRESS,
      DRIVER_EMAIL,
      DRIVER_BUSINESS_PHONE,
      DRIVER_HOME_PHONE,
      DRIVER_LICENSE_NO,
      DRIVER_LICENSE_ISSUED_STATE,
      DRIVER_LICENSE_EXP_DATE,
      DRIVER_INJURED,
      CARGO_DAMAGED,
      HAZARDOUS,
      OTHER_DRIVERS_INVOLCED,
      PROPERTY_DAMAGED,
      INJURED,
      OTHER_VEHICLES_INVOLVED,
      PASSENGER_INVOLVED,
      POLICE_INVOLVED,
      POLICE_AREA,
      VEHICLE_DRIVABLE,
      TOW_COMPANY,
      TOW_COMPANY_PHONE,
      PREVENTABLE,
      DOT_REPORTABLE,
      SCHOOL_ZONE,
      CONSTRUCTION_ZONE,
      ON_PREMISE,
      TELEMATICS,
      EVENT_RECORDER,
      AVOIDANCE_SYSTEM,
      TOTAL_LOSS,
      FUEL_SPILL,
      CARGO_SPILL,
      HAZMAT_SPILL,
      FATALITIES,
      TOTAL_PAX,
      TOTAL_INJURED_PAX,
      LOSS_CLAIM_FILED,
      REPORT_TO_INSURANCE,
      SEND_TO_INSURANCE,
      INSURANCE_REPORT_DATE,
      DRIVER_STATEMENT_DATE,
      DRIVER_STATEMENT,
      OUR_DAMAGE_COSTS,
      PAID_TO_OTHER_VEHICLE,
      RECIEVED_PAYMENT,
      LOST_REVENUE,
      OTHER_VEHICLE_COUNT,
      OTHER_PROPERTY_COUNT,
      PASSENGER_COUNT,
      INJURED_PASSENGER_COUNT,
      WITNESS_COUNT,
      other_vehicle_summary,
      other_property_summary,
      passenger_summary,
      witness_summary,
      ACCIDENT_IMAGES,
      INSERTED_DATE,
      UPDATED_DATE,
      INSERTED_BY,
      UPDATED_BY,
      IS_DEFAULT,
      DEL
  FROM FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE VIN = '2MG3JMBAXFW067038'
  ORDER BY ACCIDENT_DATE DESC
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_DATE'].tolist(),
              'y': df['SEVERITY_NAME'].tolist(),
              'type': 'bar',
              'name': 'Accident Severity'
          }
      ],
      'layout': {
          'title': 'Accident Severity Over Time for VIN 2MG3JMBAXFW067038',
          'xaxis': {'title': 'Accident Date'},
          'yaxis': {'title': 'Severity'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Show me accident details for VIN 2MG3JMBAXFW067038 along with images", "summary": "This query retrieves detailed accident records for the vehicle with VIN 2MG3JMBAXFW067038, including accident circumstances, vehicle and driver information, and associated images. It pulls up to 1000 records from the FM_VEHICLE_ACCIDENT_DETAILS_V view, sorted by the most recent accident date.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query gathers comprehensive accident details for the vehicle with VIN 2MG3JMBAXFW067038. It includes information about the accident (such as date, location, severity, and type), the vehicle and driver involved, and any related images. The results are sorted to show the most recent accidents first, with a maximum of 1000 records displayed.</p><hr><h4>What it shows | What it means</h4><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>Accident details (date, location, severity, type)</td><td>Specifics about each accident involving this vehicle</td></tr><tr><td>Vehicle and driver information</td><td>Who was driving, vehicle specs, and related data</td></tr><tr><td>ACCIDENT_IMAGES</td><td>Links or references to images from the accident</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a detailed list of up to 1000 accident records for the specified vehicle, including all available accident data and images, sorted by the most recent accident date.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>All listed columns</td><td>To retrieve detailed accident, vehicle, driver, and image data</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Source of accident records</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBAXFW067038'</td><td>Filters for the specific vehicle</td></tr><tr><td>ORDER BY</td><td>ACCIDENT_DATE DESC</td><td>Shows most recent accidents first</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts output to 1000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Show me accident images for VIN 2MG3JMBAXFW067038.
web: N
executed: Y
execution_time: 4.0
question_normalized: show_me_accident_images_for_vin_2mg3jmbaxfw067038.
created_at: 2026-05-12 10:49:01
updated_at: 2026-05-12 10:49:08
sql:
  SELECT ACCIDENT_IMAGES
  FROM FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE VIN = '2MG3JMBAXFW067038'
  ORDER BY VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['ACCIDENT_IMAGES'].tolist(),
              'type': 'bar',
              'name': 'ACCIDENT_IMAGES'
          }
      ],
      'layout': {
          'title': 'Accident Images for VIN 2MG3JMBAXFW067038',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'ACCIDENT_IMAGES'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Show me accident images for VIN 2MG3JMBAXFW067038.", "summary": "This query retrieves accident images for the vehicle with VIN 2MG3JMBAXFW067038 from the FM_VEHICLE_ACCIDENT_DETAILS_V view. It selects the ACCIDENT_IMAGES column, filters for the specified VIN, orders the results by VEHICLE_ACCIDENT_ID, and limits the output to 1000 records. The output will show the accident images associated with this particular vehicle.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query fetches accident images for the vehicle identified by VIN 2MG3JMBAXFW067038. It looks in the FM_VEHICLE_ACCIDENT_DETAILS_V view and returns up to 1000 accident images related to this specific vehicle.</p><hr><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>ACCIDENT_IMAGES</td><td>Images related to accidents for the specified vehicle</td></tr></tbody></table><h3>The Final Output</h3><p>The result will be a list of accident images for the vehicle with VIN 2MG3JMBAXFW067038, up to a maximum of 1000 images.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_IMAGES</td><td>Specifies which column to retrieve</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Specifies the data source</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBAXFW067038'</td><td>Filters for the specific vehicle</td></tr><tr><td>ORDER BY</td><td>VEHICLE_ACCIDENT_ID</td><td>Sorts results by accident record</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts the number of results</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Show me accident images for VIN 2MG3JMBAXFW067038
web: N
executed: Y
execution_time: 4.0
question_normalized: show_me_accident_images_for_vin_2mg3jmbaxfw067038
created_at: 2026-05-12 10:55:26
updated_at: 2026-05-12 10:55:31
sql:
  SELECT ACCIDENT_IMAGES
  FROM FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE VIN = '2MG3JMBAXFW067038'
  ORDER BY ACCIDENT_DATE DESC
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['ACCIDENT_IMAGES'].tolist(),
              'type': 'bar',
              'name': 'ACCIDENT_IMAGES'
          }
      ],
      'layout': {
          'title': 'Accident Images for VIN 2MG3JMBAXFW067038',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'ACCIDENT_IMAGES'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Show me accident images for VIN 2MG3JMBAXFW067038", "summary": "This query retrieves accident images for the vehicle with VIN 2MG3JMBAXFW067038. It looks in the FM_VEHICLE_ACCIDENT_DETAILS_V table and selects the ACCIDENT_IMAGES column, which likely contains links or references to images related to each accident. The results are sorted so that the most recent accidents appear first, and up to 1000 records are returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query fetches accident images for the vehicle with VIN 2MG3JMBAXFW067038. It searches the FM_VEHICLE_ACCIDENT_DETAILS_V table for records matching this VIN and retrieves the accident images, showing the most recent accidents first, up to a maximum of 1000 records.</p><h3>The Final Output</h3><p>The output will be a list of accident images (or their references) for the specified vehicle, ordered by the most recent accident date.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_IMAGES</td><td>Specifies to retrieve accident images</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Source table for accident details</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBAXFW067038'</td><td>Filters for the specific vehicle</td></tr><tr><td>ORDER BY</td><td>ACCIDENT_DATE DESC</td><td>Shows most recent accidents first</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts output to 1000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: show me accident images for VIN 2MG3JMBA7KW069310
web: N
executed: Y
execution_time: 5.0
question_normalized: show_me_accident_images_for_vin_2mg3jmba7kw069310
created_at: 2026-05-12 11:09:03
updated_at: 2026-05-12 11:09:10
sql:
  SELECT ACCIDENT_IMAGES
  FROM FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE VIN = '2MG3JMBA7KW069310'
  ORDER BY VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['ACCIDENT_IMAGES'].tolist(),
              'type': 'bar',
              'name': 'ACCIDENT_IMAGES'
          }
      ],
      'layout': {
          'title': "Accident Images for VIN 2MG3JMBA7KW069310",
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'ACCIDENT_IMAGES'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "show me accident images for VIN 2MG3JMBA7KW069310", "summary": "This query retrieves accident images for the vehicle with VIN 2MG3JMBA7KW069310. It looks into the FM_VEHICLE_ACCIDENT_DETAILS_V table and selects the ACCIDENT_IMAGES column, filtering only records where the VIN matches the specified value. The results are ordered by VEHICLE_ACCIDENT_ID and limited to a maximum of 1000 records. The output will show the accident images associated with this particular vehicle.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query fetches accident images for the vehicle with the VIN number 2MG3JMBA7KW069310. It searches the FM_VEHICLE_ACCIDENT_DETAILS_V table and returns the images related to any accidents involving this specific vehicle.</p><hr><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>ACCIDENT_IMAGES</td><td>Images related to accidents for the specified vehicle</td></tr></tbody></table><h3>The Final Output</h3><p>The output will be a list of accident images for the vehicle with VIN 2MG3JMBA7KW069310, up to 1000 images, ordered by accident record ID.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_IMAGES</td><td>Specifies the column to retrieve (accident images)</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Specifies the table to search for accident details</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBA7KW069310'</td><td>Filters results to only this vehicle</td></tr><tr><td>ORDER BY</td><td>VEHICLE_ACCIDENT_ID</td><td>Sorts results by accident record ID</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts output to 1000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: show me accident images for VIN 2MG3JMBA7KW069310
web: N
executed: Y
execution_time: 2.0
question_normalized: show_me_accident_images_for_vin_2mg3jmba7kw069310
created_at: 2026-05-12 12:10:58
updated_at: 2026-05-12 12:10:59
sql:
  SELECT ACCIDENT_IMAGES
  FROM FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE VIN = '2MG3JMBA7KW069310'
  ORDER BY VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['ACCIDENT_IMAGES'].tolist(),
              'type': 'bar',
              'name': 'ACCIDENT_IMAGES'
          }
      ],
      'layout': {
          'title': 'Accident Images for VIN 2MG3JMBA7KW069310',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'ACCIDENT_IMAGES'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "show me accident images for VIN 2MG3JMBA7KW069310", "summary": "This query retrieves accident images for the vehicle with VIN 2MG3JMBA7KW069310. It looks into the FM_VEHICLE_ACCIDENT_DETAILS_V table and selects the ACCIDENT_IMAGES column, filtering only records where the VIN matches the specified value. The results are ordered by VEHICLE_ACCIDENT_ID and limited to a maximum of 1000 records. The output will show the accident images associated with this particular vehicle.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query fetches accident images for the vehicle with the VIN number 2MG3JMBA7KW069310. It searches the FM_VEHICLE_ACCIDENT_DETAILS_V table and returns the images related to any accidents involving this specific vehicle.</p><hr><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>ACCIDENT_IMAGES</td><td>Images related to accidents for the specified vehicle</td></tr></tbody></table><h3>The Final Output</h3><p>The output will be a list of accident images for the vehicle with VIN 2MG3JMBA7KW069310, up to 1000 images, ordered by accident record ID.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_IMAGES</td><td>Specifies the column to retrieve (accident images)</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Specifies the table to search for accident details</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBA7KW069310'</td><td>Filters results to only this vehicle</td></tr><tr><td>ORDER BY</td><td>VEHICLE_ACCIDENT_ID</td><td>Sorts results by accident record ID</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts output to 1000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Accident Images for VIN 2MG3JMBA7KW069310
web: N
executed: Y
execution_time: 5.0
question_normalized: accident_images_for_vin_2mg3jmba7kw069310
created_at: 2026-05-12 12:14:52
updated_at: 2026-05-12 12:14:58
sql:
  SELECT ACCIDENT_IMAGES
  FROM FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE VIN = '2MG3JMBA7KW069310'
  ORDER BY VEHICLE_ACCIDENT_ID
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['ACCIDENT_IMAGES'].tolist(),
              'type': 'bar',
              'name': 'ACCIDENT_IMAGES'
          }
      ],
      'layout': {
          'title': 'Accident Images for VIN 2MG3JMBA7KW069310',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'ACCIDENT_IMAGES'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Accident Images for VIN 2MG3JMBA7KW069310", "summary": "This query retrieves accident images related to the vehicle with VIN 2MG3JMBA7KW069310. It looks up the FM_VEHICLE_ACCIDENT_DETAILS_V table and selects the ACCIDENT_IMAGES column for this specific VIN. The results are ordered by VEHICLE_ACCIDENT_ID and limited to 1000 records. The output will show the accident images associated with this vehicle.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query fetches accident images for the vehicle identified by VIN 2MG3JMBA7KW069310. It searches the FM_VEHICLE_ACCIDENT_DETAILS_V table and returns up to 1000 records of accident images, sorted by the accident record ID.</p><hr><h3>The Final Output</h3><p>The output will be a list of accident images linked to the specified vehicle VIN, showing up to 1000 images if available.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_IMAGES</td><td>Specifies the column to retrieve (accident images)</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Specifies the table to search for data</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBA7KW069310'</td><td>Filters results to a specific vehicle</td></tr><tr><td>ORDER BY</td><td>VEHICLE_ACCIDENT_ID</td><td>Sorts results by accident record ID</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts the number of records returned</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Show a timeline of reported incidents for VIN 2MG3JMBA7KW069310.
web: N
executed: Y
execution_time: 5.0
question_normalized: show_a_timeline_of_reported_incidents_for_vin_2mg3jmba7kw069310.
created_at: 2026-05-12 12:16:20
updated_at: 2026-05-12 12:16:30
sql:
  SELECT
      ACCIDENT_DATE,
      ACCIDENT_INCIDENT_TYPE_NAME,
      SEVERITY_NAME,
      STATUS,
      ACCIDENT_LOCATION,
      INSERTED_DATE
  FROM
      FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE
      VIN = '2MG3JMBA7KW069310'
  ORDER BY
      ACCIDENT_DATE ASC,
      INSERTED_DATE ASC
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_DATE'].tolist(),
              'y': df['ACCIDENT_INCIDENT_TYPE_NAME'].tolist(),
              'type': 'scatter',
              'mode': 'markers',
              'name': 'Incident Type'
          }
      ],
      'layout': {
          'title': 'Timeline of Reported Incidents for VIN 2MG3JMBA7KW069310',
          'xaxis': {'title': 'Accident Date'},
          'yaxis': {'title': 'Incident Type'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Show a timeline of reported incidents for VIN 2MG3JMBA7KW069310.", "summary": "This query retrieves a list of all reported accident incidents for the vehicle with VIN 2MG3JMBA7KW069310. It pulls details such as the date of each accident, the type of incident, severity, status, location, and when the record was added. The results are sorted in chronological order by accident date and then by the date the record was inserted, showing up to 1000 incidents.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves a timeline of all reported accident incidents for the vehicle with VIN 2MG3JMBA7KW069310. It includes details about each incident, such as the date, type, severity, status, location, and when the record was entered into the system. The results are ordered by the accident date and the record's insertion date, showing up to 1000 incidents.</p><hr><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>ACCIDENT_DATE</td><td>The date when the accident occurred</td></tr><tr><td>ACCIDENT_INCIDENT_TYPE_NAME</td><td>The type of incident reported (e.g., collision, theft)</td></tr><tr><td>SEVERITY_NAME</td><td>The severity level of the incident</td></tr><tr><td>STATUS</td><td>The current status of the incident report</td></tr><tr><td>ACCIDENT_LOCATION</td><td>The location where the accident happened</td></tr><tr><td>INSERTED_DATE</td><td>The date when this record was added to the database</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a chronological list of up to 1000 reported incidents for the specified vehicle, providing a clear timeline of accident history with relevant details for each event.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_DATE, ACCIDENT_INCIDENT_TYPE_NAME, SEVERITY_NAME, STATUS, ACCIDENT_LOCATION, INSERTED_DATE</td><td>Specifies which details about each incident to display</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Indicates the data source for vehicle accident details</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBA7KW069310'</td><td>Filters results to only incidents for the specified vehicle</td></tr><tr><td>ORDER BY</td><td>ACCIDENT_DATE ASC, INSERTED_DATE ASC</td><td>Sorts incidents chronologically and by record entry date</td></tr><tr><td>LIMIT</td><td>1000</td><td>Restricts the output to a maximum of 1000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 2
question: Show a summary of the most frequent types of incidents reported for VIN 2MG3JMBA7KW069310.
web: N
executed: Y
execution_time: 6.0
question_normalized: show_a_summary_of_the_most_frequent_types_of_incidents_reported_for_vin_2mg3jmba7kw069310.
created_at: 2026-05-12 12:17:25
updated_at: 2026-05-12 12:17:34
sql:
  SELECT
      ACCIDENT_INCIDENT_TYPE,
      ACCIDENT_INCIDENT_TYPE_NAME,
      COUNT(*) AS incident_count
  FROM
      FM_VEHICLE_ACCIDENT_DETAILS_V
  WHERE
      VIN = '2MG3JMBA7KW069310'
  GROUP BY
      ACCIDENT_INCIDENT_TYPE,
      ACCIDENT_INCIDENT_TYPE_NAME
  ORDER BY
      incident_count DESC
  LIMIT 1000;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ACCIDENT_INCIDENT_TYPE_NAME'].tolist(),
              'y': df['incident_count'].tolist(),
              'type': 'bar',
              'name': 'Incident Count'
          }
      ],
      'layout': {
          'title': 'Most Frequent Types of Incidents Reported for VIN 2MG3JMBA7KW069310',
          'xaxis': {'title': 'Incident Type'},
          'yaxis': {'title': 'Incident Count'}
      }
  }

sql_query_summaries:
  [{"agent_id": "2", "sub_question": "Show a summary of the most frequent types of incidents reported for VIN 2MG3JMBA7KW069310.", "summary": "This query retrieves a summary of the most common types of incidents reported for the vehicle with VIN 2MG3JMBA7KW069310. It counts how many times each incident type has occurred for this specific vehicle, sorts them from most to least frequent, and lists up to 1,000 different incident types.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds and summarizes the most frequent types of incidents that have been reported for the vehicle with VIN 2MG3JMBA7KW069310. It counts how many times each type of incident has occurred for this vehicle.</p><hr><h4>Step 1 - Filter for the Specific Vehicle</h4><p>The query looks only at records in the FM_VEHICLE_ACCIDENT_DETAILS_V table where the VIN is '2MG3JMBA7KW069310'.</p><h4>Step 2 - Group and Count Incident Types</h4><p>It groups the results by both the incident type code (ACCIDENT_INCIDENT_TYPE) and the incident type name (ACCIDENT_INCIDENT_TYPE_NAME), then counts how many times each group appears.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted so the most frequent incident types appear first, and only the top 1,000 are shown.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>ACCIDENT_INCIDENT_TYPE</td><td>The code representing the type of incident</td></tr><tr><td>ACCIDENT_INCIDENT_TYPE_NAME</td><td>The name or description of the incident type</td></tr><tr><td>incident_count</td><td>The number of times this incident type was reported for the vehicle</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a ranked list of incident types (with their codes and names) and how many times each was reported for the specified vehicle.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ACCIDENT_INCIDENT_TYPE, ACCIDENT_INCIDENT_TYPE_NAME, COUNT(*) AS incident_count</td><td>Choose columns to display and count incidents</td></tr><tr><td>FROM</td><td>FM_VEHICLE_ACCIDENT_DETAILS_V</td><td>Source table with accident details</td></tr><tr><td>WHERE</td><td>VIN = '2MG3JMBA7KW069310'</td><td>Filter for the specific vehicle</td></tr><tr><td>GROUP BY</td><td>ACCIDENT_INCIDENT_TYPE, ACCIDENT_INCIDENT_TYPE_NAME</td><td>Summarize by incident type</td></tr><tr><td>ORDER BY</td><td>incident_count DESC</td><td>Show most frequent incidents first</td></tr><tr><td>LIMIT</td><td>1000</td><td>Show up to 1,000 results</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 3
question: Show me total trips by city as of yesterday
web: N
executed: Y
execution_time: 11.0
question_normalized: show_me_total_trips_by_city_as_of_yesterday
created_at: 2026-05-13 12:46:54
updated_at: 2026-05-13 12:47:03
sql:
  SELECT 
      PU.City, 
      COUNT(RS.SegmentRowId) AS TotalTrips
  FROM 
      ResSegments RS
      INNER JOIN ResSegmentLocations PU ON (RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0)
  WHERE 
      CAST(RS.PickupDateTime AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)
  GROUP BY 
      PU.City
  ORDER BY 
      PU.City
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          }
      ],
      'layout': {
          'title': 'Total Trips by City as of Yesterday',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'TotalTrips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "3", "sub_question": "Show me total trips by city as of yesterday", "summary": "This query calculates the total number of trips for each city where a trip started (pickup location) on the previous day. It looks at the 'ResSegments' table for trip segments and joins it with 'ResSegmentLocations' to get the city for each pickup. Only trips with a pickup date equal to yesterday are counted. The results are grouped by city, sorted alphabetically, and limited to the first 10,000 cities.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many trips started in each city yesterday. It checks the pickup location for each trip and counts the number of trips per city for the previous day.</p><hr><h4>Step 1 - Join Trip Segments with Pickup Locations</h4><p>The query joins the 'ResSegments' table (which tracks trip segments) with the 'ResSegmentLocations' table to get the city where each trip segment started. It only considers rows where the location phase type is 0, which means pickup locations.</p><h4>Step 2 - Filter for Yesterday's Pickups</h4><p>It filters the trips to include only those where the pickup date is exactly yesterday.</p><h4>Step 3 - Group and Count Trips by City</h4><p>The query groups the results by city and counts the number of trips for each city. It then sorts the cities alphabetically and limits the output to 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>PU.City</td><td>The name of the city where the trip started (pickup location).</td></tr><tr><td>TotalTrips</td><td>The total number of trips that started in that city yesterday.</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of cities with the total number of trips that started in each city yesterday, sorted by city name and limited to 10,000 results.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>PU.City, COUNT(RS.SegmentRowId) AS TotalTrips</td><td>Shows city and total trips per city</td></tr><tr><td>FROM</td><td>ResSegments INNER JOIN ResSegmentLocations</td><td>Joins trip segments with pickup locations</td></tr><tr><td>WHERE</td><td>Pickup date is yesterday, LocationPhaseType = 0</td><td>Filters to pickups from yesterday only</td></tr><tr><td>GROUP BY</td><td>PU.City</td><td>Groups results by city</td></tr><tr><td>ORDER BY</td><td>PU.City</td><td>Sorts cities alphabetically</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 3
question: show me trip details for Beverly Hills
chart: N
web: N
executed: Y
execution_time: 108.0
question_normalized: show_me_trip_details_for_beverly_hills
sql_query_summaries: []
created_at: 2026-05-13 12:50:06
updated_at: 2026-05-13 12:50:14
sql:
  SELECT
      R.ResNumber,
      RS.SegmentSequenceId,
      RS.SegmentRowId,
      RS.PickupDateTime,
      RS.DropoffDateTime,
      RS.SegmentStartDateTime,
      RS.SegmentEndDateTime,
      AF.AffiliateId,
      AF.AffiliateCode,
      AF.AffiliateName,
      S.ServiceAreaCode,
      LVT.VehicleTypeCode,
      RS.PassengerFirstName,
      RS.PassengerLastName,
      C.CustomerCode,
      C.CustomerName,
      C.CustomerType,
      LPO.PaymentOptionCode,
      DSS.Meaning,
      DSS.SegementStatusCode,
      RSP.SegmentTotal,
      DR.DriverCode,
      DR.FullName,
      V.VehicleCode,
      PU.City AS PickupCity,
      DO.City AS DropoffCity,
      PU.FlightAssociatedAirport AS PickupAirport,
      DO.FlightAssociatedAirport AS DropoffAirport,
      PU.PlaceType AS PickupPlaceType,
      DO.PlaceType AS DropoffPlaceType,
      I.InvoiceTotal,
      I.InvoiceNumber,
      I.InvoiceDate
  FROM
      ResSegments RS
      INNER JOIN ResMain R ON R.ResRowId = RS.ResRowId
      INNER JOIN ResSegmentLocations PU ON RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0
      INNER JOIN ResSegmentLocations DO ON RS.SegmentRowId = DO.SegmentRowId AND DO.LocationPhaseType = 1
      LEFT OUTER JOIN ListVehicleTypes LVT ON LVT.VehicleTypeId = RS.RequestedVehicleTypeId
      LEFT OUTER JOIN Customers C ON R.CustomerId = C.CustomerId
      LEFT OUTER JOIN ServiceAreas S ON RS.ServiceAreaId = S.ServiceAreaId
      LEFT OUTER JOIN Passengers P ON RS.PassengerId = P.PassengerId
      LEFT OUTER JOIN ListPaymentOptions LPO ON RS.PaymentOptionId = LPO.PaymentOptionId
      LEFT OUTER JOIN Drivers DR ON DR.DriverId = (ISNULL(RS.DispatchDriverId, ISNULL(RS.AssignDriverId, ISNULL(RS.RequestedDriverId,0))))
      LEFT OUTER JOIN Vehicles V ON V.VehicleId = (ISNULL(RS.DispatchVehicleId, ISNULL(RS.AssignVehicleId, ISNULL(RS.RequestedVehicleId,0))))
      LEFT OUTER JOIN DomainSegmentStatuses DSS ON RS.SegmentStatusId = DSS.SegmentStatus
      LEFT OUTER JOIN ResSegmentPricing RSP ON RS.SegmentRowId = RSP.SegmentRowId
      LEFT OUTER JOIN ResSegmentBillingTxns RBT ON RBT.SegmentRowId = RS.SegmentRowId AND ISNULL(RBT.InvoiceRowId,0) != 0
      LEFT OUTER JOIN InvoicesLink IL ON RBT.InvoiceRowId = IL.InvoiceRowId
      LEFT OUTER JOIN Invoices I ON IL.InvoiceRowId = I.InvoiceRowId
      LEFT OUTER JOIN InvoicesPosted IP ON IL.InvoiceRowId = IP.InvoiceRowId
      LEFT OUTER JOIN InvoicesPaid IPA ON IL.InvoiceRowId = IPA.InvoiceRowId
      LEFT OUTER JOIN ResSegmentCost DCost ON DCost.SegmentRowId = RS.SegmentRowId
      LEFT OUTER JOIN DriverPaymentBatches DPB ON DPB.DriverPaymentBatchId = DCost.DriverPaymentBatchId
      LEFT OUTER JOIN Affiliates AF ON AF.AffiliateId = (ISNULL(RS.DispatchAffiliateId, ISNULL(RS.AssignAffiliateId, ISNULL(RS.RequestedAffiliateId,0))))
      LEFT OUTER JOIN DomainPricingTypes DPT ON DPT.PricingTypeValue = RSP.PricingType
      LEFT OUTER JOIN EVENTS E ON E.EventCode = ISNULL(R.EventCode, RSP.PricingEventCode)
      LEFT OUTER JOIN ListSegmentTypes LST ON LST.SegmentType = RS.SegmentTypeId
  WHERE
      PU.City = 'Beverly Hills'
      OR DO.City = 'Beverly Hills'
  ORDER BY
      RS.PickupDateTime DESC,
      RS.SegmentRowId DESC
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 3
question: Show me total trips by city as of yesterday
web: N
executed: Y
execution_time: 3.0
question_normalized: show_me_total_trips_by_city_as_of_yesterday
created_at: 2026-05-13 12:51:44
updated_at: 2026-05-13 12:51:45
sql:
  SELECT 
      PU.City, 
      COUNT(RS.SegmentRowId) AS TotalTrips
  FROM 
      ResSegments RS
      INNER JOIN ResSegmentLocations PU ON (RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0)
  WHERE 
      CAST(RS.PickupDateTime AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)
  GROUP BY 
      PU.City
  ORDER BY 
      PU.City
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          }
      ],
      'layout': {
          'title': 'Total Trips by City as of Yesterday',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'Total Trips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "3", "sub_question": "Show me total trips by city as of yesterday", "summary": "This query calculates the total number of trips for each city where a trip started (pickup location) on the previous day. It looks at the 'ResSegments' table for trip segments and joins it with 'ResSegmentLocations' to get the city for each pickup. Only trips with a pickup date equal to yesterday are counted. The results are grouped by city, sorted alphabetically, and limited to the first 10,000 cities.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many trips started in each city yesterday. It checks the pickup location for each trip and counts the number of trips per city for the previous day.</p><hr><h4>Step 1 - Join Trip Segments with Pickup Locations</h4><p>The query joins the 'ResSegments' table (which tracks trip segments) with the 'ResSegmentLocations' table to get the city where each trip segment started. It only considers rows where the location phase type is 0, which means pickup locations.</p><h4>Step 2 - Filter for Yesterday's Pickups</h4><p>It filters the trips to include only those where the pickup date is exactly yesterday.</p><h4>Step 3 - Group and Count Trips by City</h4><p>The query groups the results by city and counts the number of trips for each city. It then sorts the cities alphabetically and limits the output to 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>PU.City</td><td>The name of the city where the trip started (pickup location).</td></tr><tr><td>TotalTrips</td><td>The total number of trips that started in that city yesterday.</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of cities with the total number of trips that started in each city yesterday, sorted by city name and limited to 10,000 results.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>PU.City, COUNT(RS.SegmentRowId) AS TotalTrips</td><td>Shows city and total trips per city</td></tr><tr><td>FROM</td><td>ResSegments INNER JOIN ResSegmentLocations</td><td>Joins trip segments with pickup locations</td></tr><tr><td>WHERE</td><td>Pickup date is yesterday, LocationPhaseType = 0</td><td>Filters to pickups from yesterday only</td></tr><tr><td>GROUP BY</td><td>PU.City</td><td>Groups results by city</td></tr><tr><td>ORDER BY</td><td>PU.City</td><td>Sorts cities alphabetically</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 3
question: show me total trips along with total value of yesterday
web: N
executed: Y
execution_time: 8.0
question_normalized: show_me_total_trips_along_with_total_value_of_yesterday
created_at: 2026-05-13 12:54:36
updated_at: 2026-05-13 12:54:45
sql:
  SELECT 
      COUNT(RS.SegmentRowId) AS TotalTrips,
      SUM(ISNULL(RSP.SegmentTotal, 0)) AS TotalValue
  FROM 
      ResSegments RS
      LEFT OUTER JOIN ResSegmentPricing RSP ON RS.SegmentRowId = RSP.SegmentRowId
  WHERE 
      CAST(RS.PickupDateTime AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)
  ORDER BY
      TotalTrips DESC
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': ['TotalTrips', 'TotalValue'],
              'y': [df['TotalTrips'].iloc[0], df['TotalValue'].iloc[0]],
              'type': 'bar',
              'name': 'Total Trips and Value'
          }
      ],
      'layout': {
          'title': 'Total Trips and Total Value of Yesterday',
          'xaxis': {'title': 'Metric'},
          'yaxis': {'title': 'Value'}
      }
  }

sql_query_summaries:
  [{"agent_id": "3", "sub_question": "show me total trips along with total value of yesterday", "summary": "This query calculates the total number of trips and the total value of those trips that occurred yesterday. It does this by counting the number of segment IDs in the ResSegments table and summing up the SegmentTotal values from the ResSegmentPricing table for trips where the pickup date is exactly one day before today. The results show two columns: the total number of trips and the total value for those trips.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many trips happened yesterday and what the total value of those trips was. It looks at the ResSegments table for trip records and joins it with the ResSegmentPricing table to get the value of each trip. Only trips with a pickup date matching yesterday are included.</p><hr><h4>Step 1 - Count Trips and Sum Values for Yesterday</h4><p>The query counts the number of trip records (SegmentRowId) and adds up their total values (SegmentTotal) for trips where the pickup date is yesterday.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>TotalTrips</td><td>The number of trips that took place yesterday</td></tr><tr><td>TotalValue</td><td>The combined value of all those trips</td></tr></tbody></table><h3>The Final Output</h3><p>The output will be a single row showing the total number of trips and the total value for all trips that happened yesterday.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(RS.SegmentRowId), SUM(ISNULL(RSP.SegmentTotal, 0))</td><td>Calculates total trips and total value</td></tr><tr><td>FROM</td><td>ResSegments, ResSegmentPricing</td><td>Main and joined tables for trip data</td></tr><tr><td>WHERE</td><td>PickupDateTime = yesterday</td><td>Filters for trips that happened yesterday</td></tr><tr><td>ORDER BY</td><td>TotalTrips DESC</td><td>Sorts by trip count (not needed for single row)</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, 10000 ROWS</td><td>Limits results (not needed for single row)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 3
question: Show me total trips along with total value of yesterday by city.
web: N
executed: Y
execution_time: 10.0
question_normalized: show_me_total_trips_along_with_total_value_of_yesterday_by_city.
created_at: 2026-05-13 12:55:11
updated_at: 2026-05-13 12:55:20
sql:
  SELECT 
      ResSegmentLocations.City, 
      COUNT(DISTINCT ResSegments.SegmentRowId) AS TotalTrips, 
      SUM(ISNULL(ResSegmentPricing.SegmentTotal, 0)) AS TotalValue
  FROM 
      ResSegments
      INNER JOIN ResMain ON ResMain.ResRowId = ResSegments.ResRowId
      INNER JOIN ResSegmentLocations ON ResSegments.SegmentRowId = ResSegmentLocations.SegmentRowId 
          AND ResSegmentLocations.LocationPhaseType = 0
      LEFT OUTER JOIN ResSegmentPricing ON ResSegments.SegmentRowId = ResSegmentPricing.SegmentRowId
  WHERE 
      CAST(ResSegments.PickupDateTime AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)
  GROUP BY 
      ResSegmentLocations.City
  ORDER BY 
      ResSegmentLocations.City
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          },
          {
              'x': df['City'].tolist(),
              'y': df['TotalValue'].tolist(),
              'type': 'bar',
              'name': 'Total Value'
          }
      ],
      'layout': {
          'title': 'Total Trips and Total Value by City for Yesterday',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'Value'}
      }
  }

sql_query_summaries:
  [{"agent_id": "3", "sub_question": "Show me total trips along with total value of yesterday by city.", "summary": "This query retrieves, for each city, the total number of unique trips and the total value of those trips that took place yesterday. It uses data from several tables related to trip segments, their locations, and pricing. The results are grouped by city and only include trips where the pickup date was exactly one day before today. The output is sorted alphabetically by city and limited to the first 10,000 results.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows, for each city, the total number of unique trips and the total value of those trips that occurred yesterday. It gathers this information from trip segment, location, and pricing tables, focusing only on trips with a pickup date matching yesterday's date.</p><hr><h4>Step 1 - Join Relevant Tables</h4><p>The query joins the trip segments table with the main reservation, location, and pricing tables to collect all necessary details for each trip.</p><h4>Step 2 - Filter for Yesterday's Trips</h4><p>It filters the data to include only trips where the pickup date is exactly one day before the current date.</p><h4>Step 3 - Group and Summarize by City</h4><p>The results are grouped by city, counting unique trip segments and summing up their total value.</p><h4>Step 4 - Sort and Limit Results</h4><p>The output is sorted by city name and limited to the first 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>City</td><td>Name of the city where trips started</td></tr><tr><td>TotalTrips</td><td>Number of unique trips in that city yesterday</td></tr><tr><td>TotalValue</td><td>Total value of those trips in that city yesterday</td></tr></tbody></table><h3>The Final Output</h3><p>The final output is a list of cities, each with the total number of trips and the total value of those trips that took place yesterday, sorted alphabetically by city.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>City, COUNT(DISTINCT SegmentRowId), SUM(ISNULL(SegmentTotal, 0))</td><td>Choose city, total trips, and total value</td></tr><tr><td>FROM / JOIN</td><td>ResSegments, ResMain, ResSegmentLocations, ResSegmentPricing</td><td>Combine trip, reservation, location, and pricing data</td></tr><tr><td>WHERE</td><td>PickupDateTime = yesterday</td><td>Only include trips from yesterday</td></tr><tr><td>GROUP BY</td><td>City</td><td>Summarize results by city</td></tr><tr><td>ORDER BY</td><td>City</td><td>Sort results alphabetically by city</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limit results to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 3
question: Show me trip details for City Beverly Hills.
chart: N
web: N
executed: Y
execution_time: 45.0
question_normalized: show_me_trip_details_for_city_beverly_hills.
created_at: 2026-05-13 12:56:57
updated_at: 2026-05-13 12:57:05
sql:
  SELECT
      DCost.DriverPaymentBatchId,
      R.ResNumber,
      RS.SegmentSequenceId,
      RS.SegmentRowId,
      I.InvoiceTotal,
      I.InvoiceNumber,
      I.InvoiceDate,
      RS.PickupDateTime,
      RS.DropoffDateTime,
      RS.SegmentStartDateTime,
      RS.SegmentEndDateTime,
      AF.AffiliateId,
      AF.AffiliateCode,
      AF.AffiliateName,
      S.ServiceAreaCode,
      LVT.VehicleTypeCode,
      RS.PassengerFirstName,
      RS.PassengerLastName,
      C.CustomerCode,
      C.CustomerName,
      C.CustomerType,
      LPO.PaymentOptionCode,
      DSS.Meaning,
      DSS.SegementStatusCode,
      RSP.SegmentTotal,
      DR.DriverCode,
      DR.FullName,
      V.VehicleCode,
      PU.City AS PickupCity,
      DO.City AS DropoffCity,
      PU.FlightAssociatedAirport AS PickupFlightAssociatedAirport,
      DO.FlightAssociatedAirport AS DropoffFlightAssociatedAirport,
      RSP.BaseChargeTotal,
      RSP.SurchargeBaseTotal,
      RSP.StopChargesTotal,
      RSP.WaitChargesTotal,
      RSP.TollsTotal,
      RSP.ParkingTotal,
      RSP.GratuityTotal,
      RSP.TaxesTotal,
      RSP.ServiceChargesTotal,
      RSP.DiscountTotal,
      RSP.PromotionTotal,
      RSP.CCBatchNumber,
      RSP.CCBatchDate
  FROM
      ResSegments RS
      INNER JOIN ResMain R ON (R.ResRowId = RS.ResRowId)
      INNER JOIN ResSegmentLocations PU ON (RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0)
      INNER JOIN ResSegmentLocations DO ON (RS.SegmentRowId = DO.SegmentRowId AND DO.LocationPhaseType = 1)
      LEFT OUTER JOIN ListVehicleTypes LVT ON (LVT.VehicleTypeId = RS.RequestedVehicleTypeId)
      LEFT OUTER JOIN Customers C ON (R.CustomerId = C.CustomerId)
      LEFT OUTER JOIN ServiceAreas S ON (RS.ServiceAreaId = S.ServiceAreaId)
      LEFT OUTER JOIN Passengers P ON (RS.PassengerId = P.PassengerId)
      LEFT OUTER JOIN ListPaymentOptions LPO ON (RS.PaymentOptionId = LPO.PaymentOptionId)
      LEFT OUTER JOIN Drivers DR ON (DR.DriverId = (ISNULL(RS.DispatchDriverId, ISNULL(RS.AssignDriverId, ISNULL(RS.RequestedDriverId,0)))))
      LEFT OUTER JOIN Vehicles V ON (V.VehicleId = (ISNULL(RS.DispatchVehicleId, ISNULL(RS.AssignVehicleId, ISNULL(RS.RequestedVehicleId,0)))))
      LEFT OUTER JOIN DomainSegmentStatuses DSS ON (RS.SegmentStatusId = DSS.SegmentStatus)
      LEFT OUTER JOIN ResSegmentPricing RSP ON (RS.SegmentRowId = RSP.SegmentRowId)
      LEFT OUTER JOIN ResSegmentBillingTxns RBT ON (RBT.SegmentRowId = RS.SegmentRowId AND ISNULL(RBT.InvoiceRowId, 0) != 0)
      LEFT OUTER JOIN InvoicesLink IL ON (RBT.InvoiceRowId = IL.InvoiceRowId)
      LEFT OUTER JOIN Invoices I ON (IL.InvoiceRowId = I.InvoiceRowId)
      LEFT OUTER JOIN InvoicesPosted IP ON (IL.InvoiceRowId = IP.InvoiceRowId)
      LEFT OUTER JOIN InvoicesPaid IPA ON (IL.InvoiceRowId = IPA.InvoiceRowId)
      LEFT OUTER JOIN ResSegmentCost DCost ON (DCost.SegmentRowId = RS.SegmentRowId AND (DCost.DriverId = RS.DispatchDriverId OR (DCost.AffiliateId = RS.DispatchAffiliateId)))
      LEFT OUTER JOIN DriverPaymentBatches DPB ON (DPB.DriverPaymentBatchId = DCost.DriverPaymentBatchId)
      LEFT OUTER JOIN Affiliates AF ON (AF.AffiliateId = (ISNULL(RS.DispatchAffiliateId, ISNULL(RS.AssignAffiliateId, ISNULL(RS.RequestedAffiliateId,0)))))
      LEFT OUTER JOIN DomainPricingTypes DPT ON DPT.PricingTypeValue = RSP.PricingType
      LEFT OUTER JOIN EVENTS E ON (E.EventCode = ISNULL(R.EventCode, RSP.PricingEventCode))
      LEFT OUTER JOIN ListSegmentTypes LST ON (LST.SegmentType = RS.SegmentTypeId)
  WHERE
      PU.City = 'Beverly Hills'
      OR DO.City = 'Beverly Hills'
  ORDER BY
      RS.PickupDateTime DESC
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "3", "sub_question": "Show me trip details for City Beverly Hills.", "summary": "This query retrieves detailed information about trips that either start or end in the city of Beverly Hills. It gathers data from multiple tables to provide a comprehensive view of each trip, including reservation numbers, segment details, invoice information, pickup and dropoff times and locations, passenger and customer details, payment information, driver and vehicle data, and a breakdown of trip charges. The query only includes trips where the pickup or dropoff city is 'Beverly Hills', and it returns up to 10,000 of the most recent trips, sorted by pickup date and time in descending order.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query collects detailed records for trips that either begin or end in Beverly Hills. It pulls together reservation, passenger, driver, vehicle, payment, and charge details for each relevant trip, focusing only on those where the pickup or dropoff city is 'Beverly Hills'.</p><hr><h4>Step 1 - Join Multiple Tables</h4><p>The query joins many tables to combine information about reservations, segments, locations, invoices, customers, drivers, vehicles, affiliates, and pricing.</p><h4>Step 2 - Filter for Beverly Hills</h4><p>It filters the results to include only trips where either the pickup city or the dropoff city is 'Beverly Hills'.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by the pickup date and time (most recent first), and only the first 10,000 records are shown.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>DriverPaymentBatchId, ResNumber, SegmentSequenceId, InvoiceTotal, PickupDateTime, DropoffDateTime, PassengerFirstName, CustomerName, DriverCode, VehicleCode, PickupCity, DropoffCity, BaseChargeTotal, SurchargeBaseTotal, etc.</td><td>All key trip details, including financials, people involved, and trip timing, for trips linked to Beverly Hills.</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a detailed list of up to 10,000 trips that either started or ended in Beverly Hills, with comprehensive information about each trip, including financial, logistical, and participant details.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>Multiple columns from joined tables</td><td>To retrieve all relevant trip, financial, and participant details</td></tr><tr><td>FROM / JOIN</td><td>ResSegments, ResMain, ResSegmentLocations, Customers, Drivers, Vehicles, etc.</td><td>To combine data from all necessary sources</td></tr><tr><td>WHERE</td><td>PU.City = 'Beverly Hills' OR DO.City = 'Beverly Hills'</td><td>To include only trips with pickup or dropoff in Beverly Hills</td></tr><tr><td>ORDER BY</td><td>RS.PickupDateTime DESC</td><td>To show the most recent trips first</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>To limit the output to 10,000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 3
question: Show me trip details for City Beverly Hills for yesterday only.
web: N
executed: Y
execution_time: 22.0
question_normalized: show_me_trip_details_for_city_beverly_hills_for_yesterday_only.
sql_query_summaries: []
created_at: 2026-05-13 12:59:02
updated_at: 2026-05-13 12:59:14
sql:
  SELECT 
      RS.SegmentRowId,
      RS.SegmentSequenceId,
      RS.PickupDateTime,
      RS.DropoffDateTime,
      RS.SegmentStartDateTime,
      RS.SegmentEndDateTime,
      PU.City AS PickupCity,
      DO.City AS DropoffCity,
      R.ResNumber,
      I.InvoiceTotal,
      I.InvoiceNumber,
      I.InvoiceDate,
      AF.AffiliateId,
      AF.AffiliateCode,
      AF.AffiliateName,
      S.ServiceAreaCode,
      LVT.VehicleTypeCode,
      RS.PassengerFirstName,
      RS.PassengerLastName,
      C.CustomerCode,
      C.CustomerName,
      C.CustomerType,
      LPO.PaymentOptionCode,
      DSS.Meaning AS SegmentStatus,
      DSS.SegementStatusCode AS StatusCode,
      RSP.SegmentTotal,
      DR.DriverCode,
      DR.FullName AS DriverName,
      V.VehicleCode
  FROM
      ResSegments RS
      INNER JOIN ResMain R ON R.ResRowId = RS.ResRowId
      INNER JOIN ResSegmentLocations PU ON RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0
      INNER JOIN ResSegmentLocations DO ON RS.SegmentRowId = DO.SegmentRowId AND DO.LocationPhaseType = 1
      LEFT OUTER JOIN ListVehicleTypes LVT ON LVT.VehicleTypeId = RS.RequestedVehicleTypeId
      LEFT OUTER JOIN Customers C ON R.CustomerId = C.CustomerId
      LEFT OUTER JOIN ServiceAreas S ON RS.ServiceAreaId = S.ServiceAreaId
      LEFT OUTER JOIN Passengers P ON RS.PassengerId = P.PassengerId
      LEFT OUTER JOIN ListPaymentOptions LPO ON RS.PaymentOptionId = LPO.PaymentOptionId
      LEFT OUTER JOIN Drivers DR ON DR.DriverId = (ISNULL(RS.DispatchDriverId, ISNULL(RS.AssignDriverId, ISNULL(RS.RequestedDriverId,0))))
      LEFT OUTER JOIN Vehicles V ON V.VehicleId = (ISNULL(RS.DispatchVehicleId, ISNULL(RS.AssignVehicleId, ISNULL(RS.RequestedVehicleId,0))))
      LEFT OUTER JOIN DomainSegmentStatuses DSS ON RS.SegmentStatusId = DSS.SegmentStatus
      LEFT OUTER JOIN ResSegmentPricing RSP ON RS.SegmentRowId = RSP.SegmentRowId
      LEFT OUTER JOIN ResSegmentBillingTxns RBT ON RBT.SegmentRowId = RS.SegmentRowId AND ISNULL(RBT.InvoiceRowId,0) != 0
      LEFT OUTER JOIN InvoicesLink IL ON RBT.InvoiceRowId = IL.InvoiceRowId
      LEFT OUTER JOIN Invoices I ON IL.InvoiceRowId = I.InvoiceRowId
      LEFT OUTER JOIN InvoicesPosted IP ON IL.InvoiceRowId = IP.InvoiceRowId
      LEFT OUTER JOIN InvoicesPaid IPA ON IL.InvoiceRowId = IPA.InvoiceRowId
      LEFT OUTER JOIN ResSegmentCost DCost ON (DCost.SegmentRowId = RS.SegmentRowId AND (DCost.DriverId = RS.DispatchDriverId OR (DCost.AffiliateId = RS.DispatchAffiliateId)))
      LEFT OUTER JOIN DriverPaymentBatches DPB ON DPB.DriverPaymentBatchId = DCost.DriverPaymentBatchId
      LEFT OUTER JOIN Affiliates AF ON AF.AffiliateId = (ISNULL(RS.DispatchAffiliateId, ISNULL(RS.AssignAffiliateId, ISNULL(RS.RequestedAffiliateId,0))))
      LEFT OUTER JOIN DomainPricingTypes DPT ON DPT.PricingTypeValue = RSP.PricingType
      LEFT OUTER JOIN [EVENTS] E ON (E.EventCode = ISNULL(R.EventCode, RSP.PricingEventCode))
      LEFT OUTER JOIN ListSegmentTypes LST ON LST.SegmentType = RS.SegmentTypeId
  WHERE
      (PU.City = 'Beverly Hills' OR DO.City = 'Beverly Hills')
      AND CAST(RS.PickupDateTime AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)
  ORDER BY RS.PickupDateTime DESC
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['PickupDateTime'].tolist(),
              'y': df['InvoiceTotal'].tolist(),
              'type': 'bar',
              'name': 'InvoiceTotal'
          }
      ],
      'layout': {
          'title': 'Trip Invoice Totals for Beverly Hills - Yesterday',
          'xaxis': {'title': 'PickupDateTime'},
          'yaxis': {'title': 'InvoiceTotal'}
      }
  }


user_id: 1
agent_id: 3
question: show me todays trip details
chart: N
web: N
executed: Y
execution_time: 42.0
question_normalized: show_me_todays_trip_details
sql_query_summaries: []
created_at: 2026-05-13 15:36:25
updated_at: 2026-05-13 15:36:37
sql:
  SELECT 
      DCost.DriverPaymentBatchId,
      R.ResNumber + '*' + CONVERT(VARCHAR, RS.SegmentSequenceId) AS ResNumber,
      RS.SegmentRowId,
      RS.SegmentSequenceId,
      I.InvoiceTotal AS InvoiceTotal,
      I.InvoiceNumber AS InvoiceNumber,
      I.InvoiceDate AS InvoiceDate,
      LEFT(CONVERT(varchar, RS.PickupDateTime,112),6) AS FiscalPeriod,
      RS.PickupDateTime,
      RS.DropoffDateTime,
      RS.SegmentStartDateTime,
      RS.SegmentEndDateTime,
      AF.AffiliateId,
      AF.AffiliateCode,
      AF.AffiliateName,
      S.ServiceAreaCode AS ServiceArea,
      ISNULL(LVT.VehicleTypeCode,'') AS VehicleType,
      ISNULL(RS.PassengerFirstName,'') AS PassengerFirstName,
      ISNULL(RS.PassengerLastName,'') AS PassengerLastName,
      ISNULL(C.CustomerCode,'') AS CustomerAccount,
      ISNULL(C.CustomerName,'') AS CustomerName,
      ISNULL(C.CustomerType,'') AS CustomerType,
      ISNULL(LPO.PaymentOptionCode,'') AS PaidBy,
      ISNULL(DSS.Meaning,'') AS SegmentStatus,
      ISNULL(DSS.SegementStatusCode,'') AS StatusCode,
      ISNULL(RSP.SegmentTotal,'0.0') AS SegmentTotal,
      ISNULL(DR.DriverCode,'') AS DriverCode,
      ISNULL(DR.FullName,'') AS DriverName,
      ISNULL(V.VehicleCode,'') AS VehicleCode,
      CASE 
          WHEN PU.PlaceType = 2 THEN (ISNULL(PU.FlightAssociatedAirport,'') ) 
          ELSE  ISNULL(PU.City,'')  
      END AS PickupAddress,
      CASE 
          WHEN DO.PlaceType = 2 THEN (ISNULL(DO.FlightAssociatedAirport,'') ) 
          ELSE  ISNULL(DO.City,'') 
      END AS DropoffAddress,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN (ISNULL(RSP.BaseChargeTotal,0) + ISNULL(RSP.SurchargeBaseTotal,0)) ELSE 0 END AS BaseChargeTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.StopChargesTotal,0) ELSE 0 END AS StopChargesTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.WaitChargesTotal,0) ELSE 0 END AS WaitChargesTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.TollsTotal,0) ELSE 0 END AS TollsTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.ParkingTotal,0) ELSE 0 END AS ParkingTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.GratuityTotal,0) ELSE 0 END AS GratuityTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.TaxesTotal,0) ELSE 0 END AS TaxesTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ISNULL(RSP.ServiceChargesTotal,0) ELSE 0 END AS ServiceChargesTotal,
      CASE WHEN ISNULL(DCost.CostOrder, 1) = 1 
          THEN
              (
                  (
                      (ISNULL(RSP.SegmentTotal,0) + (ISNULL(RSP.DiscountTotal,0) + ISNULL(RSP.PromotionTotal, 0))) 
                      - 
                      (  
                          ISNULL(RSP.BaseChargeTotal,0) + ISNULL(RSP.SurchargeBaseTotal,0) + ISNULL(RSP.StopChargesTotal,0)  + 
                          ISNULL(RSP.TollsTotal,0) + ISNULL(RSP.ParkingTotal,0)+ ISNULL(RSP.ServiceChargesTotal,0) + ISNULL(RSP.GratuityTotal,0) + 
                          ISNULL(RSP.WaitChargesTotal,0) + ISNULL(RSP.TaxesTotal,0)
                      )
                  )
                  +  
                  (0)
              ) 
          ELSE 0 END AS Other,
      CASE 
          WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN(ISNULL(RSP.SegmentTotal,0) + (ISNULL(RSP.DiscountTotal,0) + ISNULL(RSP.PromotionTotal, 0)))
          ELSE 0
      END AS Total,
      ISNULL(I.InvoiceNumber,ISNULL(IP.InvoiceNumber,ISNULL(IPA.InvoiceNumber,(CASE WHEN ISNULL(RSP.CCBatchNumber,'') = '' THEN '' ELSE 'CC' + RSP.CCBatchNumber END)))) AS InvoiceNumber,
      ISNULL(I.InvoiceDate,ISNULL(IP.InvoiceDate,ISNULL(IPA.InvoiceDate, RSP.CCBatchDate))) AS InvoiceDate,
      ISNULL(DPB.PaymentStatementDate,NULL) AS PayStmt,
      ISNULL(DPT.Meaning,'') AS PricingMethod,
      CASE 
          WHEN ISNULL(DCost.CostOrder, 1) = 1 THEN ((ISNULL(RSP.DiscountTotal,0) + ISNULL(RSP.PromotionTotal, 0)) * (-1)) 
          ELSE 0 
      END AS DiscountTotal,
      AF.AffiliateCode,
      LST.SegmentTypeCode AS RunType,
      E.EventCode,
      DCost.TotalCost
  FROM
      ResSegments RS
      INNER JOIN ResMain R ON (R.ResRowId = RS.ResRowId)
      INNER JOIN ResSegmentLocations PU ON (RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0)
      INNER JOIN ResSegmentLocations DO ON (RS.SegmentRowId = DO.SegmentRowId AND DO.LocationPhaseType = 1)
      LEFT OUTER JOIN ListVehicleTypes LVT ON (LVT.VehicleTypeId = RS.RequestedVehicleTypeId)
      LEFT OUTER JOIN Customers C ON (R.CustomerId = C.CustomerId)
      LEFT OUTER JOIN ServiceAreas S ON (RS.ServiceAreaId = S.ServiceAreaId)
      LEFT OUTER JOIN Passengers P ON (RS.PassengerId = P.PassengerId)
      LEFT OUTER JOIN ListPaymentOptions LPO ON (RS.PaymentOptionId = LPO.PaymentOptionId)
      LEFT OUTER JOIN Drivers DR ON (DR.DriverId = (ISNULL(RS.DispatchDriverId,ISNULL(RS.AssignDriverId, ISNULL(RS.RequestedDriverId,0)))))
      LEFT OUTER JOIN Vehicles V ON (V.VehicleId = (ISNULL(RS.DispatchVehicleId,ISNULL(RS.AssignVehicleId, ISNULL(RS.RequestedVehicleId,0)))))
      LEFT OUTER JOIN DomainSegmentStatuses DSS ON (RS.SegmentStatusId= DSS.SegmentStatus)
      LEFT OUTER JOIN ResSegmentPricing RSP ON (RS.SegmentRowId = RSP.SegmentRowId)
      LEFT OUTER JOIN ResSegmentBillingTxns RBT ON (RBT.SegmentRowId = RS.SegmentRowId AND ISNULL(RBT.InvoiceRowId,0) != 0)
      LEFT OUTER JOIN ResSegmentDispatchInfo RSD ON (RS.SegmentRowId = RSD.SegmentRowId)
      LEFT OUTER JOIN InvoicesLink IL ON (RBT.InvoiceRowId = IL.InvoiceRowId)
      LEFT OUTER JOIN Invoices I ON (IL.InvoiceRowId = I.InvoiceRowId)
      LEFT OUTER JOIN InvoicesPosted IP ON (IL.InvoiceRowId = IP.InvoiceRowId)
      LEFT OUTER JOIN InvoicesPaid IPA ON (IL.InvoiceRowId = IPA.InvoiceRowId)
      LEFT OUTER JOIN ResSegmentCost DCost ON (DCost.SegmentRowId = RS.SegmentRowId AND (DCost.DriverId = RS.DispatchDriverId OR (DCost.AffiliateId=RS.DispatchAffiliateId)))
      LEFT OUTER JOIN DriverPaymentBatches DPB ON (DPB.DriverPaymentBatchId = DCost.DriverPaymentBatchId)
      LEFT OUTER JOIN Affiliates AF ON (AF.AffiliateId = (ISNULL(RS.DispatchAffiliateId,ISNULL(RS.AssignAffiliateId, ISNULL(RS.RequestedAffiliateId,0)))))
      LEFT OUTER JOIN DomainPricingTypes DPT ON DPT.PricingTypeValue =  RSP.PricingType
      LEFT OUTER JOIN EVENTS E ON (E.EventCode =  ISNULL(R.EventCode, RSP.PricingEventCode))
      LEFT OUTER JOIN ListSegmentTypes LST ON (LST.SegmentType = RS.SegmentTypeId)
  WHERE
      CAST(RS.PickupDateTime AS DATE) = CAST(GETDATE() AS DATE)
  ORDER BY
      RS.PickupDateTime, RS.SegmentRowId
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 3
question: Show a breakdown of today's trips by service area or city.
web: N
executed: Y
execution_time: 13.0
question_normalized: show_a_breakdown_of_today's_trips_by_service_area_or_city.
sql_query_summaries: []
created_at: 2026-05-13 15:37:40
updated_at: 2026-05-13 15:37:49
sql:
  SELECT 
      S.ServiceAreaCode,
      PU.City,
      COUNT(RS.SegmentRowId) AS TripCount
  FROM
      ResSegments RS
      INNER JOIN ResMain R ON (R.ResRowId = RS.ResRowId)
      INNER JOIN ResSegmentLocations PU ON (RS.SegmentRowId = PU.SegmentRowId AND PU.LocationPhaseType = 0)
      LEFT OUTER JOIN ServiceAreas S ON (RS.ServiceAreaId = S.ServiceAreaId)
  WHERE
      CONVERT(date, RS.PickupDateTime) = CONVERT(date, GETDATE())
  GROUP BY
      S.ServiceAreaCode,
      PU.City
  ORDER BY
      S.ServiceAreaCode,
      PU.City
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ServiceAreaCode'].tolist(),
              'y': df['TripCount'].tolist(),
              'type': 'bar',
              'name': 'Trip Count'
          }
      ],
      'layout': {
          'title': "Today's Trips by Service Area",
          'xaxis': {'title': 'ServiceAreaCode'},
          'yaxis': {'title': 'TripCount'}
      }
  }


user_id: 1
agent_id: 3
question: Compare today's trip counts to the same day last week.
web: N
executed: Y
execution_time: 10.0
question_normalized: compare_today's_trip_counts_to_the_same_day_last_week.
created_at: 2026-05-13 15:40:54
updated_at: 2026-05-13 15:41:01
sql:
  SELECT 
      COUNT(*) AS TripCount,
      CAST(RS.PickupDateTime AS DATE) AS TripDate
  FROM 
      ResSegments RS
  WHERE 
      CAST(RS.PickupDateTime AS DATE) = CAST(GETDATE() AS DATE)
      OR CAST(RS.PickupDateTime AS DATE) = CAST(DATEADD(day, -7, GETDATE()) AS DATE)
  GROUP BY 
      CAST(RS.PickupDateTime AS DATE)
  ORDER BY 
      TripDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['TripDate'].tolist(),
              'y': df['TripCount'].tolist(),
              'type': 'bar',
              'name': 'Trip Count'
          }
      ],
      'layout': {
          'title': "Today's Trip Counts vs Same Day Last Week",
          'xaxis': {'title': 'TripDate'},
          'yaxis': {'title': 'TripCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "3", "sub_question": "Compare today's trip counts to the same day last week.", "summary": "This query counts the number of trips that occurred today and on the same day last week, based on the pickup date in the ResSegments table. It groups the results by the trip date and returns the total trip count for each of these two dates. The output shows the date and the corresponding number of trips for today and for exactly one week ago.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query counts how many trips took place today and on the same day last week, using the pickup date from the ResSegments table. It groups the results by date and provides the total number of trips for each of these two days.</p><hr><h4>What it shows</h4><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>TripCount</td><td>The total number of trips on a specific date</td></tr><tr><td>TripDate</td><td>The date of the trips (either today or the same day last week)</td></tr></tbody></table><h3>The Final Output</h3><p>The final output is a list with two rows: one for today's date and one for the same day last week, each showing how many trips occurred on those dates.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(*), CAST(RS.PickupDateTime AS DATE)</td><td>Counts trips and extracts the trip date</td></tr><tr><td>FROM</td><td>ResSegments</td><td>Uses trip data from this table</td></tr><tr><td>WHERE</td><td>PickupDateTime = today OR PickupDateTime = same day last week</td><td>Filters for trips on the two relevant dates</td></tr><tr><td>GROUP BY</td><td>CAST(RS.PickupDateTime AS DATE)</td><td>Groups results by trip date</td></tr><tr><td>ORDER BY</td><td>TripDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, 10000 ROWS</td><td>Limits the number of rows returned</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show yesterdays charter rides by servicearea
chart: N
web: N
executed: Y
execution_time: 7.0
question_normalized: show_yesterdays_charter_rides_by_servicearea
created_at: 2026-05-14 06:28:33
updated_at: 2026-05-14 06:28:41
sql:
  SELECT
      ServiceID,
      BookingID,
      StartDateTime,
      PickupPoint,
      Destination,
      Distance,
      VehicleType,
      DriverName
  FROM
      vwAllocations01
  WHERE
      StartDateTime >= DATEADD(day, -1, CAST(GETDATE() AS date))
      AND StartDateTime < CAST(GETDATE() AS date)
      AND BookingType = 'Charter'
  ORDER BY
      ServiceID,
      StartDateTime
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show yesterdays charter rides by servicearea", "summary": "This query retrieves a list of charter rides that took place yesterday, including details such as the service ID, booking ID, start date and time, pickup point, destination, distance, vehicle type, and driver name. The data is pulled from the 'vwAllocations01' view, filtered to only include rides where the booking type is 'Charter' and the ride started at any time during the previous day. The results are sorted by service ID and start date/time, and only the first 10,000 records are shown.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists all charter rides that occurred yesterday, showing key details for each ride such as when and where it started, where it went, the distance, vehicle type, and driver name. It only includes rides labeled as 'Charter' and limits the results to the first 10,000 entries.</p><hr><h3>The Final Output</h3><p>The output is a table of up to 10,000 charter rides from yesterday, with columns for service ID, booking ID, start date/time, pickup point, destination, distance, vehicle type, and driver name.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>FROM</td><td>vwAllocations01</td><td>Source of ride data</td></tr><tr><td>WHERE</td><td>StartDateTime >= DATEADD(day, -1, CAST(GETDATE() AS date)) AND StartDateTime &lt; CAST(GETDATE() AS date) AND BookingType = 'Charter'</td><td>Filters for rides that started yesterday and are charter rides</td></tr><tr><td>ORDER BY</td><td>ServiceID, StartDateTime</td><td>Sorts results by service and time</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show all rides as of yesterday by service area
chart: N
web: N
executed: Y
execution_time: 6.0
question_normalized: show_all_rides_as_of_yesterday_by_service_area
created_at: 2026-05-14 06:29:58
updated_at: 2026-05-14 06:30:03
sql:
  SELECT
      ServiceID,
      StartDate,
      PickupPoint,
      Destination,
      Distance,
      Passengers,
      DriverName,
      VehicleID
  FROM vwAllocations01
  WHERE StartDate = DATEADD(day, -1, CAST(GETDATE() AS date))
  ORDER BY ServiceID, StartDate, PickupPoint
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show all rides as of yesterday by service area", "summary": "This query retrieves a list of all rides that took place yesterday, grouped by service area, from the 'vwAllocations01' view. It selects details such as the service ID, ride start date, pickup and destination locations, distance traveled, number of passengers, driver name, and vehicle ID. The results are filtered to only include rides where the start date matches exactly one day before today. The output is sorted by service ID, start date, and pickup point, and is limited to the first 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves a list of all rides that occurred yesterday, organized by service area, from the 'vwAllocations01' view. It provides key ride details for each entry.</p><hr><h3>The Final Output</h3><p>The output is a table showing up to 10,000 rides from yesterday, including information such as service ID, start date, pickup and destination points, distance, passenger count, driver name, and vehicle ID, sorted by service area and other ride details.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ServiceID, StartDate, PickupPoint, Destination, Distance, Passengers, DriverName, VehicleID</td><td>Specifies which ride details to show</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of ride data</td></tr><tr><td>WHERE</td><td>StartDate = DATEADD(day, -1, CAST(GETDATE() AS date))</td><td>Filters to rides from yesterday only</td></tr><tr><td>ORDER BY</td><td>ServiceID, StartDate, PickupPoint</td><td>Sorts results by service area and ride details</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show all ride details as of yesterday by service area.
chart: N
web: N
executed: Y
execution_time: 6.0
question_normalized: show_all_ride_details_as_of_yesterday_by_service_area.
created_at: 2026-05-14 06:31:06
updated_at: 2026-05-14 06:31:15
sql:
  SELECT
      ServiceID,
      StartDate,
      SortDateTime,
      StartDateTime,
      StartBase,
      StartPoint,
      PickupDateTime,
      PickupPoint,
      Destination,
      ArrivalDateTime,
      FinishDateTime,
      VehicleID,
      DriverID,
      Passengers,
      Distance,
      Price,
      Total
  FROM vwAllocations01
  WHERE StartDate = CAST(GETDATE() - 1 AS DATE)
  ORDER BY StartBase, SortDateTime
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show all ride details as of yesterday by service area.", "summary": "This query retrieves detailed information about all rides that started yesterday, grouped by their starting service area. It pulls data from the 'vwAllocations01' view and includes columns such as service ID, ride start and finish times, pickup and drop-off points, vehicle and driver IDs, number of passengers, distance, price, and total amount. The results are filtered to only include rides where the start date matches yesterday's date, and are sorted by the starting base (service area) and the ride's sort date/time. Only the first 10,000 records are returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists all the details for rides that started yesterday, organized by the service area where each ride began. It provides comprehensive ride information such as times, locations, vehicle and driver details, passenger count, distance, and pricing.</p><hr><h3>The Final Output</h3><p>The output is a table showing up to 10,000 rides from yesterday, grouped by starting service area and sorted by the ride's scheduled time. Each row contains detailed ride information.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ServiceID, StartDate, SortDateTime, StartDateTime, StartBase, StartPoint, PickupDateTime, PickupPoint, Destination, ArrivalDateTime, FinishDateTime, VehicleID, DriverID, Passengers, Distance, Price, Total</td><td>Specifies which ride details to retrieve</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of ride data</td></tr><tr><td>WHERE</td><td>StartDate = CAST(GETDATE() - 1 AS DATE)</td><td>Filters to rides that started yesterday</td></tr><tr><td>ORDER BY</td><td>StartBase, SortDateTime</td><td>Sorts by service area and ride time</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits results to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show all ride details with booking ID as of yesterday by service area.
chart: N
web: N
executed: Y
execution_time: 13.0
question_normalized: show_all_ride_details_with_booking_id_as_of_yesterday_by_service_area.
created_at: 2026-05-14 06:33:53
updated_at: 2026-05-14 06:34:01
sql:
  SELECT 
      BookingID,
      ServiceID,
      StartDate,
      PickupPoint,
      Destination,
      DriverName,
      VehicleID,
      Price,
      Total,
      Company,
      ClientID
  FROM vwAllocations01
  WHERE StartDate = CAST(GETDATE()-1 AS DATE)
  ORDER BY ServiceID, BookingID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show all ride details with booking ID as of yesterday by service area.", "summary": "This query retrieves all ride booking details from the vwAllocations01 view for rides that started yesterday. It lists key information such as booking ID, service area, ride times, pickup and destination points, driver and vehicle details, pricing, and client information. The results are sorted by service area (ServiceID) and booking ID, and only the first 10,000 records are shown.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query fetches all ride booking details from the vwAllocations01 view for rides that started yesterday. It includes information like booking ID, service area, start date, pickup and destination locations, driver and vehicle details, price, total fare, company, and client ID. The results are organized by service area and booking ID, showing up to 10,000 records.</p><hr><h4>What it shows</h4><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>BookingID</td><td>Unique identifier for each ride booking</td></tr><tr><td>ServiceID</td><td>Identifier for the service area or type</td></tr><tr><td>StartDate</td><td>Date the ride started (yesterday)</td></tr><tr><td>PickupPoint</td><td>Location where the ride began</td></tr><tr><td>Destination</td><td>Location where the ride ended</td></tr><tr><td>DriverName</td><td>Name of the driver assigned</td></tr><tr><td>VehicleID</td><td>Identifier for the vehicle used</td></tr><tr><td>Price</td><td>Base price of the ride</td></tr><tr><td>Total</td><td>Total fare charged</td></tr><tr><td>Company</td><td>Company associated with the ride</td></tr><tr><td>ClientID</td><td>Identifier for the client who booked</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a detailed list of up to 10,000 ride bookings from yesterday, grouped by service area and booking ID, with all relevant ride, driver, and client details included.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>BookingID, ServiceID, StartDate, PickupPoint, Destination, DriverName, VehicleID, Price, Total, Company, ClientID</td><td>Specifies which ride details to retrieve</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source view for ride data</td></tr><tr><td>WHERE</td><td>StartDate = CAST(GETDATE()-1 AS DATE)</td><td>Filters for rides that started yesterday</td></tr><tr><td>ORDER BY</td><td>ServiceID, BookingID</td><td>Sorts results by service area and booking ID</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to the first 10,000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show a summary of yesterday’s rides by driver to highlight which driver completed the most trips.
chart: N
web: N
executed: Y
execution_time: 9.0
question_normalized: show_a_summary_of_yesterday’s_rides_by_driver_to_highlight_which_driver_completed_the_most_trips.
created_at: 2026-05-14 08:38:40
updated_at: 2026-05-14 08:38:49
sql:
  SELECT
      DriverID,
      DriverName,
      COUNT(*) AS TripCount
  FROM
      vwAllocations01
  WHERE
      CAST(StartDate AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)
  GROUP BY
      DriverID,
      DriverName
  ORDER BY
      TripCount DESC,
      DriverID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show a summary of yesterday\u2019s rides by driver to highlight which driver completed the most trips.", "summary": "This query retrieves a summary of all rides completed by each driver yesterday. It counts the number of trips for every driver, sorts them from most to least trips, and lists up to 10,000 drivers. The goal is to easily identify which driver had the highest number of completed trips yesterday.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query provides a summary of all rides completed by each driver for yesterday. It counts how many trips each driver completed, sorts the drivers by the number of trips in descending order, and displays up to 10,000 results. This helps highlight which driver completed the most trips yesterday.</p><hr><h4>Step 1 - Filter Rides to Yesterday</h4><p>The query selects only rides where the start date matches yesterday's date.</p><h4>Step 2 - Group and Count Trips by Driver</h4><p>It groups the filtered rides by driver ID and name, then counts the number of trips for each driver.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted so that drivers with the most trips appear first. If two drivers have the same trip count, the one with the lower driver ID comes first. Only the top 10,000 drivers are shown.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>DriverID</td><td>The unique identifier for each driver</td></tr><tr><td>DriverName</td><td>The name of the driver</td></tr><tr><td>TripCount</td><td>The total number of trips completed by the driver yesterday</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a ranked list of drivers showing how many trips each completed yesterday, making it easy to see who had the most trips.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>FROM</td><td>vwAllocations01</td><td>Source of ride and driver data</td></tr><tr><td>WHERE</td><td>CAST(StartDate AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE)</td><td>Filters rides to only those that started yesterday</td></tr><tr><td>GROUP BY</td><td>DriverID, DriverName</td><td>Groups rides by each driver</td></tr><tr><td>ORDER BY</td><td>TripCount DESC, DriverID</td><td>Sorts drivers by most trips, then by driver ID</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits results to the top 10,000 drivers</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me all trips for may 2026 by servicearea
chart: N
web: N
executed: Y
execution_time: 14.0
question_normalized: show_me_all_trips_for_may_2026_by_servicearea
created_at: 2026-05-14 08:41:42
updated_at: 2026-05-14 08:41:48
sql:
  SELECT
      ServiceID,
      StartDate,
      PickupPoint,
      Destination,
      BookingID,
      DriverName,
      VehicleID
  FROM
      vwAllocations01
  WHERE
      StartDate >= '2026-05-01'
      AND StartDate < '2026-06-01'
  ORDER BY
      ServiceID,
      StartDate,
      BookingID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me all trips for may 2026 by servicearea", "summary": "This query retrieves all trip records from the vwAllocations01 view where the trip's start date falls within May 2026. It selects details such as ServiceID, StartDate, PickupPoint, Destination, BookingID, DriverName, and VehicleID. The results are sorted by ServiceID, StartDate, and BookingID, and only the first 10,000 records are shown.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists all trips that took place in May 2026, showing key details for each trip. The data comes from the vwAllocations01 view and includes information like the service identifier, trip start date, pickup and destination points, booking ID, driver name, and vehicle ID. Only trips that started between May 1, 2026, and before June 1, 2026, are included.</p><hr><h3>The Final Output</h3><p>The output is a list of up to 10,000 trips from May 2026, organized by service area (ServiceID), with details about each trip, such as when and where it started, where it ended, who drove, and which vehicle was used.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>ServiceID, StartDate, PickupPoint, Destination, BookingID, DriverName, VehicleID</td><td>Specifies which trip details to show</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of trip data</td></tr><tr><td>WHERE</td><td>StartDate &gt;= '2026-05-01' AND StartDate &lt; '2026-06-01'</td><td>Filters trips to those in May 2026</td></tr><tr><td>ORDER BY</td><td>ServiceID, StartDate, BookingID</td><td>Sorts trips by service area, date, and booking</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to the first 10,000 trips</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me total trips by service area for May 2026
web: N
executed: Y
execution_time: 13.0
question_normalized: show_me_total_trips_by_service_area_for_may_2026
created_at: 2026-05-14 08:46:36
updated_at: 2026-05-14 08:46:41
sql:
  SELECT StartBase, COUNT(*) AS TotalTrips
  FROM vwAllocations01
  WHERE StartDate >= '2026-05-01' AND StartDate < '2026-06-01'
  GROUP BY StartBase
  ORDER BY StartBase
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartBase'].tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          }
      ],
      'layout': {
          'title': 'Total Trips by Service Area for May 2026',
          'xaxis': {'title': 'StartBase'},
          'yaxis': {'title': 'TotalTrips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me total trips by service area for May 2026", "summary": "This query calculates the total number of trips that started in each service area during May 2026. It looks at the 'vwAllocations01' table, counts all trips grouped by the 'StartBase' column (which represents the service area), and only includes trips with a 'StartDate' in May 2026. The results are sorted by service area name and limited to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total number of trips that started in each service area during May 2026. It uses the 'vwAllocations01' table, counts trips grouped by the 'StartBase' column (service area), and only includes trips with a 'StartDate' in May 2026. The results are sorted by service area and limited to 10,000 rows.</p><hr><h3>The Final Output</h3><p>The output is a list showing each service area and the total number of trips that started there in May 2026.</p><h3>What it shows | What it means</h3><table><thead><tr><th>StartBase</th><th>TotalTrips</th></tr></thead><tbody><tr><td>Service area name</td><td>Total number of trips started in that area during May 2026</td></tr></tbody></table><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartBase, COUNT(*) AS TotalTrips</td><td>Chooses service area and counts trips</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the trip allocation data</td></tr><tr><td>WHERE</td><td>StartDate &gt;= '2026-05-01' AND StartDate &lt; '2026-06-01'</td><td>Filters trips to May 2026</td></tr><tr><td>GROUP BY</td><td>StartBase</td><td>Groups results by service area</td></tr><tr><td>ORDER BY</td><td>StartBase</td><td>Sorts results by service area</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me total trips by service area for May 2026 and compare with May 2025.
web: N
executed: Y
execution_time: 21.0
question_normalized: show_me_total_trips_by_service_area_for_may_2026_and_compare_with_may_2025.
sql_query_summaries: []
created_at: 2026-05-14 08:48:06
updated_at: 2026-05-14 08:48:14
sql:
  SELECT
      StartBase,
      YEAR(StartDate) AS Year,
      MONTH(StartDate) AS Month,
      COUNT(*) AS TotalTrips
  FROM
      vwAllocations01
  WHERE
      StartDate >= '2025-05-01'
      AND StartDate < '2026-06-01'
      AND MONTH(StartDate) = 5
      AND (YEAR(StartDate) = 2025 OR YEAR(StartDate) = 2026)
  GROUP BY
      StartBase,
      YEAR(StartDate),
      MONTH(StartDate)
  ORDER BY
      StartBase,
      Year,
      Month
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df[df['Year'] == year]['StartBase'].tolist(),
              'y': df[df['Year'] == year]['TotalTrips'].tolist(),
              'type': 'bar',
              'name': f"{year}"
          } for year in sorted(df['Year'].dropna().unique())
      ],
      'layout': {
          'title': 'Total Trips by Service Area: May 2026 vs May 2025',
          'xaxis': {'title': 'Service Area (StartBase)'},
          'yaxis': {'title': 'Total Trips'}
      }
  }


user_id: 1
agent_id: 4
question: Show me total trips by service area for May 2026 and May 2025 with month and year as columns.
web: N
executed: Y
execution_time: 22.0
question_normalized: show_me_total_trips_by_service_area_for_may_2026_and_may_2025_with_month_and_year_as_columns.
sql_query_summaries: []
created_at: 2026-05-14 08:53:24
updated_at: 2026-05-14 08:53:32
sql:
  SELECT
      BookingBase,
      YEAR(StartDate) AS Year,
      MONTH(StartDate) AS Month,
      COUNT(*) AS TotalTrips
  FROM
      vwAllocations01
  WHERE
      YEAR(StartDate) IN (2025, 2026)
      AND MONTH(StartDate) = 5
  GROUP BY
      BookingBase,
      YEAR(StartDate),
      MONTH(StartDate)
  ORDER BY
      BookingBase,
      Year,
      Month
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': [f"{month}-{year}" for month, year in zip(df[df['BookingBase'] == booking_base]['Month'], df[df['BookingBase'] == booking_base]['Year'])],
              'y': df[df['BookingBase'] == booking_base]['TotalTrips'].tolist(),
              'type': 'bar',
              'name': str(booking_base)
          }
          for booking_base in sorted(df['BookingBase'].dropna().unique())
      ],
      'layout': {
          'title': 'Total Trips by Service Area for May 2026 and May 2025',
          'xaxis': {'title': 'Month-Year'},
          'yaxis': {'title': 'TotalTrips'}
      }
  }


user_id: 1
agent_id: 4
question: Show me total trips by service area with May 2026 and May 2025 as separate columns.
web: N
executed: Y
execution_time: 264.0
question_normalized: show_me_total_trips_by_service_area_with_may_2026_and_may_2025_as_separate_columns.
created_at: 2026-05-14 08:53:44
updated_at: 2026-05-14 08:53:51
sql:
  SELECT
      StartBase,
      COUNT(CASE WHEN StartDate >= '2026-05-01' AND StartDate < '2026-06-01' THEN 1 END) AS Trips_May_2026,
      COUNT(CASE WHEN StartDate >= '2025-05-01' AND StartDate < '2025-06-01' THEN 1 END) AS Trips_May_2025
  FROM
      vwAllocations01
  GROUP BY
      StartBase
  ORDER BY
      StartBase
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartBase'].tolist(),
              'y': df['Trips_May_2026'].tolist(),
              'type': 'bar',
              'name': 'May 2026'
          },
          {
              'x': df['StartBase'].tolist(),
              'y': df['Trips_May_2025'].tolist(),
              'type': 'bar',
              'name': 'May 2025'
          }
      ],
      'layout': {
          'title': 'Total Trips by Service Area: May 2026 vs May 2025',
          'xaxis': {'title': 'Service Area (StartBase)'},
          'yaxis': {'title': 'Total Trips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me total trips by service area with May 2026 and May 2025 as separate columns.", "summary": "This query retrieves the total number of trips for each service area (StartBase), showing separate counts for trips that started in May 2026 and May 2025. It uses the vwAllocations01 table, groups the results by service area, and limits the output to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows the total number of trips for each service area, with separate columns for trips that started in May 2026 and May 2025. It uses the vwAllocations01 table and organizes the results by service area.</p><hr><h4>Step 1 - Count Trips by Month and Service Area</h4><p>The query counts trips for each service area (StartBase) where the trip's start date falls in May 2026 or May 2025. It creates two columns: one for May 2026 trips and one for May 2025 trips.</p><h4>Step 2 - Group and Order Results</h4><p>The results are grouped by service area and ordered alphabetically by StartBase. Only the first 10,000 rows are returned.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartBase</td><td>The name of the service area or base where trips started.</td></tr><tr><td>Trips_May_2026</td><td>Total number of trips that started in May 2026 for each service area.</td></tr><tr><td>Trips_May_2025</td><td>Total number of trips that started in May 2025 for each service area.</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a table listing each service area, with columns showing the total trips for May 2026 and May 2025. This allows for easy comparison of trip volumes by service area across the two months.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartBase, COUNT(CASE...)</td><td>Chooses service area and counts trips for each month</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the trip allocation data</td></tr><tr><td>GROUP BY</td><td>StartBase</td><td>Groups results by service area</td></tr><tr><td>ORDER BY</td><td>StartBase</td><td>Sorts results alphabetically by service area</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, 10000 ROWS</td><td>Limits output to first 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me total trips along with total amount by companyid for may 2026
web: N
executed: Y
execution_time: 13.0
question_normalized: show_me_total_trips_along_with_total_amount_by_companyid_for_may_2026
created_at: 2026-05-14 08:57:55
updated_at: 2026-05-14 08:58:02
sql:
  SELECT 
      CompanyID, 
      COUNT(*) AS TotalTrips, 
      SUM(Total) AS TotalAmount
  FROM 
      vwAllocations01
  WHERE 
      StartDate >= '2026-05-01' 
      AND StartDate < '2026-06-01'
  GROUP BY 
      CompanyID
  ORDER BY 
      CompanyID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['CompanyID'].tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          },
          {
              'x': df['CompanyID'].tolist(),
              'y': df['TotalAmount'].tolist(),
              'type': 'bar',
              'name': 'Total Amount'
          }
      ],
      'layout': {
          'title': 'Total Trips and Total Amount by CompanyID for May 2026',
          'xaxis': {'title': 'CompanyID'},
          'yaxis': {'title': 'Value'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me total trips along with total amount by companyid  for may 2026", "summary": "This query retrieves the total number of trips and the total amount for each company, based on records from the vwAllocations01 table, for trips that started in May 2026. It groups the results by CompanyID, orders them by CompanyID, and limits the output to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many trips each company had and the total amount billed for those trips, using data from the vwAllocations01 table, for trips that started in May 2026.</p><hr><h4>Step 1 - Filter Trips by Date</h4><p>The query selects only those trips where the StartDate is on or after May 1, 2026, and before June 1, 2026. This ensures only trips from May 2026 are included.</p><h4>Step 2 - Group and Summarize by Company</h4><p>For each CompanyID, it counts the number of trips and sums up the total amount for those trips.</p><h4>Step 3 - Order and Limit Results</h4><p>The results are sorted by CompanyID and only the first 10,000 rows are shown.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>CompanyID</td><td>The unique identifier for each company</td></tr><tr><td>TotalTrips</td><td>The total number of trips for that company in May 2026</td></tr><tr><td>TotalAmount</td><td>The sum of the Total column for those trips</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of companies, each with the total number of trips and total amount billed for trips that started in May 2026.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>CompanyID, COUNT(*), SUM(Total)</td><td>Chooses company, trip count, and total amount</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of trip data</td></tr><tr><td>WHERE</td><td>StartDate >= '2026-05-01' AND StartDate < '2026-06-01'</td><td>Filters to trips in May 2026</td></tr><tr><td>GROUP BY</td><td>CompanyID</td><td>Summarizes data by company</td></tr><tr><td>ORDER BY</td><td>CompanyID</td><td>Sorts results by company</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limits output to first 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me total trips along with total amount by companyid for May 2026 and compare with May 2025.
web: N
executed: Y
execution_time: 23.0
question_normalized: show_me_total_trips_along_with_total_amount_by_companyid_for_may_2026_and_compare_with_may_2025.
sql_query_summaries: []
created_at: 2026-05-14 08:59:11
updated_at: 2026-05-14 08:59:21
sql:
  SELECT
      CompanyID,
      YEAR(StartDate) AS [Year],
      MONTH(StartDate) AS [Month],
      COUNT(*) AS TotalTrips,
      SUM(Total) AS TotalAmount
  FROM
      vwAllocations01
  WHERE
      (YEAR(StartDate) = 2025 OR YEAR(StartDate) = 2026)
      AND MONTH(StartDate) = 5
  GROUP BY
      CompanyID,
      YEAR(StartDate),
      MONTH(StartDate)
  ORDER BY
      CompanyID,
      [Year],
      [Month]
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df[df['Year'] == year]['CompanyID'].tolist(),
              'y': df[df['Year'] == year]['TotalTrips'].tolist(),
              'type': 'bar',
              'name': f'Total Trips {year}'
          }
          for year in sorted(df['Year'].dropna().unique())
      ] + [
          {
              'x': df[df['Year'] == year]['CompanyID'].tolist(),
              'y': df[df['Year'] == year]['TotalAmount'].tolist(),
              'type': 'bar',
              'name': f'Total Amount {year}',
              'yaxis': 'y2'
          }
          for year in sorted(df['Year'].dropna().unique())
      ],
      'layout': {
          'title': 'Total Trips and Total Amount by CompanyID for May 2026 vs May 2025',
          'xaxis': {'title': 'CompanyID'},
          'yaxis': {'title': 'Total Trips'},
          'yaxis2': {'title': 'Total Amount', 'overlaying': 'y', 'side': 'right'}
      }
  }


user_id: 1
agent_id: 5
question: show me total hours of each employee in may 2026
chart: N
web: N
executed: Y
execution_time: 9.0
question_normalized: show_me_total_hours_of_each_employee_in_may_2026
created_at: 2026-05-14 09:28:18
updated_at: 2026-05-14 09:28:27
sql:
  SELECT
      workerId,
      SUM(TRY_CAST(hours AS FLOAT)) AS total_hours
  FROM
      [AvalonReporting].[dbo].[tbl_Payroll_Checks_Earnings]
  WHERE
      checkDate >= '2026-05-01'
      AND checkDate < '2026-06-01'
  GROUP BY
      workerId
  ORDER BY
      workerId
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "5", "sub_question": "show me total hours of each employee in may 2026", "summary": "This query calculates the total number of hours worked by each employee during May 2026. It looks at payroll earnings records, sums up the hours for each worker, and lists the results for up to 10,000 employees. The output shows each employee's ID and their total hours worked in that month.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many hours each employee worked in May 2026 by adding up their reported hours from payroll records. It lists each employee's ID along with their total hours for that month.</p><hr><h4>Step 1 - Filter Payroll Records for May 2026</h4><p>The query selects records from the payroll earnings table where the check date is between May 1, 2026 and May 31, 2026 (excluding June 1).</p><h4>Step 2 - Sum Hours for Each Employee</h4><p>For each employee (identified by workerId), it adds up the hours worked, converting the hours to a numeric value if needed.</p><h4>Step 3 - List Results</h4><p>The results are grouped by employee and sorted by their ID. Only the first 10,000 employees are shown.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>workerId</td><td>The unique ID of each employee</td></tr><tr><td>total_hours</td><td>The total number of hours that employee worked in May 2026</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of employee IDs with the total hours each one worked in May 2026, based on payroll data.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>workerId, SUM(TRY_CAST(hours AS FLOAT)) AS total_hours</td><td>Choose employee ID and sum of hours</td></tr><tr><td>FROM</td><td>[AvalonReporting].[dbo].[tbl_Payroll_Checks_Earnings]</td><td>Use payroll earnings data</td></tr><tr><td>WHERE</td><td>checkDate >= '2026-05-01' AND checkDate < '2026-06-01'</td><td>Only include records from May 2026</td></tr><tr><td>GROUP BY</td><td>workerId</td><td>Sum hours for each employee</td></tr><tr><td>ORDER BY</td><td>workerId</td><td>Sort results by employee ID</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limit to first 10,000 employees</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 5
question: show me total hours by employee for May 2026
chart: N
web: N
executed: Y
execution_time: 13.0
question_normalized: show_me_total_hours_by_employee_for_may_2026
sql_query_summaries: []
created_at: 2026-05-14 09:51:14
updated_at: 2026-05-14 09:51:23
sql:
  SELECT
      PED.EmployeeId,
      PED.FamilyName,
      PED.GivenName,
      PED.FamilyName + ', ' + PED.GivenName AS [Full Name],
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours
  FROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED
      ON PLC.LocationId = PED.LocationId
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE
      ON PED.WorkerId = PCE.WorkerId
  WHERE
      CAST(PCE.CheckDate AS DATE) >= '2026-05-01'
      AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'
      AND PCE.OrganizationName NOT IN (
          '250 General Manager',
          '200 Corp Office Admin',
          '250 General Mgr',
          '800 Operations Manager',
          '800 Operations Mgr',
          '900 Sales/Marketing',
          '200 Corp Office'
      )
      AND PCE.ComponentName NOT LIKE '%Phone Reimburse%'
      AND PCE.ComponentName NOT LIKE '%Exp Reimb%'
      AND PCE.ComponentName NOT LIKE '%Expense Reimburse%'
      AND PCE.ComponentName NOT LIKE '%Parking%'
      AND PCE.ComponentName NOT LIKE '%Toll%'
      AND PCE.ComponentName NOT LIKE '%Per Diem%'
      AND PCE.ComponentName NOT LIKE '%Stale Dated PR%'
  GROUP BY
      PED.EmployeeId,
      PED.FamilyName,
      PED.GivenName
  ORDER BY
      PED.FamilyName,
      PED.GivenName,
      PED.EmployeeId
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 5
chart: N
web: N
executed: Y
execution_time: 9.0
sql_query_summaries: []
created_at: 2026-05-14 09:53:46
updated_at: 2026-05-14 09:53:54
question:
  Show me total hours by employee for May 2026 along with designation of employee, and do not show family name and given name columns.

sql:
  SELECT 
      PED.EmployeeId,
      PED.FamilyName + ', ' + PED.GivenName AS [Full Name],
      PED.OrganizationName,
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours
  FROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC
  JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED
      ON PLC.LocationId = PED.LocationId
  JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE
      ON PED.WorkerId = PCE.WorkerId
  WHERE YEAR(PCE.CheckDate) = 2026
    AND MONTH(PCE.CheckDate) = 5
  GROUP BY PED.EmployeeId, PED.FamilyName, PED.GivenName, PED.OrganizationName
  ORDER BY PED.EmployeeId
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

question_normalized:
  show_me_total_hours_by_employee_for_may_2026_along_with_designation_of_employee,_and_do_not_show_family_name_and_given_name_columns.


user_id: 1
agent_id: 5
chart: N
web: N
executed: Y
execution_time: 11.0
sql_query_summaries: []
created_at: 2026-05-14 09:55:25
updated_at: 2026-05-14 09:55:33
question:
  show me total hours by employee for May 2026 along with designation, pay period of employee and do not show family name and given name columns, only show rows ith total hours data

sql:
  SELECT
      PED.EmployeeId AS [EE ID],
      CAST(PCE.CheckDate AS DATE) AS CheckDate,
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours
  FROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED
      ON PLC.LocationId = PED.LocationId
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE
      ON PED.WorkerId = PCE.WorkerId
  WHERE
      CAST(PCE.CheckDate AS DATE) >= '2026-05-01'
      AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'
  GROUP BY
      PED.EmployeeId,
      CAST(PCE.CheckDate AS DATE)
  HAVING
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) > 0
  ORDER BY
      PED.EmployeeId,
      CAST(PCE.CheckDate AS DATE)
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

question_normalized:
  show_me_total_hours_by_employee_for_may_2026_along_with_designation,_pay_period_of_employee_and_do_not_show_family_name_and_given_name_columns,_only_show_rows_ith_total_hours_data


user_id: 1
agent_id: 5
chart: N
web: N
executed: Y
execution_time: 22.0
sql_query_summaries: []
created_at: 2026-05-14 10:31:25
updated_at: 2026-05-14 10:31:34
question:
  Show total hours by employee for May 2026 along with designation, pay period of employee, and employee name, and do not show family name and given name columns, only show rows with total hours data.

sql:
  SELECT
      PED.EmployeeId AS [EE ID],
      PED.FamilyName + ', ' + PED.GivenName AS [Full Name],
      PCE.OrganizationName,
      CAST(PCE.CheckDate AS DATE) AS CheckDate,
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours
  FROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED
      ON PLC.LocationId = PED.LocationId
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE
      ON PED.WorkerId = PCE.WorkerId
  WHERE
      YEAR(PCE.CheckDate) = 2026
      AND MONTH(PCE.CheckDate) = 5
      AND PCE.OrganizationName NOT IN (
          '250 General Manager',
          '200 Corp Office Admin',
          '250 General Mgr',
          '800 Operations Manager',
          '800 Operations Mgr',
          '900 Sales/Marketing',
          '200 Corp Office'
      )
      AND PCE.ComponentName NOT LIKE '%Phone Reimburse%'
      AND PCE.ComponentName NOT LIKE '%Exp Reimb%'
      AND PCE.ComponentName NOT LIKE '%Expense Reimburse%'
      AND PCE.ComponentName NOT LIKE '%Parking%'
      AND PCE.ComponentName NOT LIKE '%Toll%'
      AND PCE.ComponentName NOT LIKE '%Per Diem%'
      AND PCE.ComponentName NOT LIKE '%Stale Dated PR%'
  GROUP BY
      PED.EmployeeId,
      PED.FamilyName,
      PED.GivenName,
      PCE.OrganizationName,
      CAST(PCE.CheckDate AS DATE)
  HAVING
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) > 0
  ORDER BY
      PED.EmployeeId,
      CAST(PCE.CheckDate AS DATE)
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

question_normalized:
  show_total_hours_by_employee_for_may_2026_along_with_designation,_pay_period_of_employee,_and_employee_name,_and_do_not_show_family_name_and_given_name_columns,_only_show_rows_with_total_hours_data.


user_id: 1
agent_id: 5
chart: N
web: N
executed: Y
execution_time: 11.0
sql_query_summaries: []
created_at: 2026-05-14 10:33:24
updated_at: 2026-05-14 10:33:32
question:
  show me employee name, total hours by employee for May 2026 along with designation, pay period of employee and do not show family name and given name columns, only show rows ith total hours data

sql:
  SELECT
      PED.EmployeeId,
      PED.FamilyName + ', ' + PED.GivenName AS [Full Name],
      PCE.OrganizationName AS Designation,
      CAST(PCE.CheckDate AS DATE) AS PayPeriod,
      SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours
  FROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED
      ON PLC.LocationId = PED.LocationId
  INNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE
      ON PED.WorkerId = PCE.WorkerId
  WHERE YEAR(PCE.CheckDate) = 2026
    AND MONTH(PCE.CheckDate) = 5
  GROUP BY
      PED.EmployeeId,
      PED.FamilyName,
      PED.GivenName,
      PCE.OrganizationName,
      CAST(PCE.CheckDate AS DATE)
  HAVING SUM(CAST(PCE.Hours AS DECIMAL(18,2))) > 0
  ORDER BY PED.EmployeeId, PayPeriod
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

question_normalized:
  show_me_employee_name,_total_hours_by_employee_for_may_2026_along_with_designation,_pay_period_of_employee_and_do_not_show_family_name_and_given_name_columns,_only_show_rows_ith_total_hours_data


user_id: 1
agent_id: 4
question: show me hours worked by each driver by day in May 2026
chart: N
web: N
executed: Y
execution_time: 13.0
question_normalized: show_me_hours_worked_by_each_driver_by_day_in_may_2026
created_at: 2026-05-14 11:08:24
updated_at: 2026-05-14 11:08:32
sql:
  SELECT
      DriverName,
      CAST(StartDateTime AS DATE) AS WorkDay,
      SUM(DurationDecimalHours) AS HoursWorked
  FROM
      vwAllocations01
  WHERE
      StartDateTime >= '2026-05-01'
      AND StartDateTime < '2026-06-01'
  GROUP BY
      DriverName,
      CAST(StartDateTime AS DATE)
  ORDER BY
      DriverName,
      WorkDay
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me hours worked by each driver by day in May 2026", "summary": "This query retrieves the total number of hours worked by each driver for each day during May 2026. It uses the vwAllocations01 view, groups the data by driver name and work day, and sums up the hours worked per day. The results are sorted by driver name and date, and only the first 10,000 rows are returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows, for each driver, the total hours they worked on each day in May 2026. It summarizes daily work hours for every driver, using data from the vwAllocations01 view.</p><hr><h4>Step 1 - Filter Records for May 2026</h4><p>The query selects records where the work start date is on or after May 1, 2026, and before June 1, 2026.</p><h4>Step 2 - Group and Summarize Hours Worked</h4><p>For each driver and each day, it adds up the total hours worked (using the DurationDecimalHours column) and groups the results by driver name and date.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by driver name and work day, and only the first 10,000 rows are included.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>DriverName</td><td>The name of the driver</td></tr><tr><td>WorkDay</td><td>The specific date in May 2026</td></tr><tr><td>HoursWorked</td><td>Total hours worked by that driver on that day</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of drivers, each day in May 2026 they worked, and the total hours they worked on each of those days, up to 10,000 rows.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>DriverName, CAST(StartDateTime AS DATE), SUM(DurationDecimalHours)</td><td>Chooses driver, date, and total hours worked</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the vwAllocations01 view as data source</td></tr><tr><td>WHERE</td><td>StartDateTime >= '2026-05-01' AND StartDateTime < '2026-06-01'</td><td>Filters to only include records from May 2026</td></tr><tr><td>GROUP BY</td><td>DriverName, CAST(StartDateTime AS DATE)</td><td>Groups data by driver and day</td></tr><tr><td>ORDER BY</td><td>DriverName, WorkDay</td><td>Sorts results by driver and date</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me trip details by driver Ahmod Butler on April 30, 2026.
web: N
executed: Y
execution_time: 7.0
question_normalized: show_me_trip_details_by_driver_ahmod_butler_on_april_30,_2026.
created_at: 2026-05-14 11:10:01
updated_at: 2026-05-14 11:10:11
sql:
  SELECT
      StartDate,
      DriverName,
      PickupDateTime,
      PickupPoint,
      Destination,
      ArrivalDateTime,
      Distance,
      Passengers,
      VehicleType,
      BookingID
  FROM vwAllocations01
  WHERE DriverName = 'Ahmod Butler'
    AND StartDate = '2026-04-30'
  ORDER BY PickupDateTime
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['PickupDateTime'].tolist(),
              'y': df['Distance'].tolist(),
              'type': 'bar',
              'name': 'Distance'
          }
      ],
      'layout': {
          'title': 'Trip Distances by Pickup DateTime for Driver Ahmod Butler on April 30, 2026',
          'xaxis': {'title': 'PickupDateTime'},
          'yaxis': {'title': 'Distance'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me trip details by driver Ahmod Butler on April 30, 2026.", "summary": "This query retrieves all trip details for the driver named Ahmod Butler that started on April 30, 2026. It looks in the vwAllocations01 table and selects columns such as the trip's start date, driver name, pickup and arrival times, pickup and destination locations, distance traveled, number of passengers, vehicle type, and booking ID. The results are sorted by the pickup time and limited to the first 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves all trip details for the driver named Ahmod Butler that started on April 30, 2026. It searches the vwAllocations01 table for trips matching this driver and date, and returns key information about each trip.</p><hr><h4>What it shows | What it means</h4><table><thead><tr><th>Column</th><th>Meaning</th></tr></thead><tbody><tr><td>StartDate</td><td>Date the trip started</td></tr><tr><td>DriverName</td><td>Name of the driver (Ahmod Butler)</td></tr><tr><td>PickupDateTime</td><td>When the trip was picked up</td></tr><tr><td>PickupPoint</td><td>Where the trip started</td></tr><tr><td>Destination</td><td>Where the trip ended</td></tr><tr><td>ArrivalDateTime</td><td>When the trip ended</td></tr><tr><td>Distance</td><td>Distance traveled during the trip</td></tr><tr><td>Passengers</td><td>Number of passengers</td></tr><tr><td>VehicleType</td><td>Type of vehicle used</td></tr><tr><td>BookingID</td><td>Unique booking identifier</td></tr></tbody></table><h3>The Final Output</h3><p>The output will be a list of all trips by Ahmod Butler on April 30, 2026, showing detailed trip information for each ride.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, DriverName, PickupDateTime, PickupPoint, Destination, ArrivalDateTime, Distance, Passengers, VehicleType, BookingID</td><td>Specifies which trip details to show</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of trip data</td></tr><tr><td>WHERE</td><td>DriverName = 'Ahmod Butler' AND StartDate = '2026-04-30'</td><td>Filters for trips by this driver on this date</td></tr><tr><td>ORDER BY</td><td>PickupDateTime</td><td>Sorts trips by pickup time</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits results to 10,000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
web: N
executed: Y
execution_time: 7.0
created_at: 2026-05-14 11:11:12
updated_at: 2026-05-14 11:11:20
question:
  Show me trip details by driver Ahmod Butler on April 30, 2026, including the start date and time, drop-off date and time, and total hours.

sql:
  SELECT
      StartDateTime,
      ArrivalDateTime,
      DurationHoursMinutes
  FROM
      vwAllocations01
  WHERE
      DriverName = 'Ahmod Butler'
      AND StartDate = '2026-04-30'
  ORDER BY
      StartDateTime
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDateTime'].tolist(),
              'y': df['DurationHoursMinutes'].tolist(),
              'type': 'bar',
              'name': 'Trip Duration'
          }
      ],
      'layout': {
          'title': 'Trip Durations by Ahmod Butler on April 30, 2026',
          'xaxis': {'title': 'Start Date and Time'},
          'yaxis': {'title': 'Duration (Hours:Minutes)'}
      }
  }

question_normalized:
  show_me_trip_details_by_driver_ahmod_butler_on_april_30,_2026,_including_the_start_date_and_time,_drop-off_date_and_time,_and_total_hours.

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me trip details by driver Ahmod Butler on April 30, 2026, including the start date and time, drop-off date and time, and total hours.", "summary": "This query retrieves trip details for the driver Ahmod Butler on April 30, 2026. It shows when each trip started and ended, as well as the total duration of each trip, by selecting the StartDateTime, ArrivalDateTime, and DurationHoursMinutes columns from the vwAllocations01 view. The results are filtered to only include trips by this driver on the specified date and are sorted by the trip start time. Up to 10,000 records are returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves trip details for the driver Ahmod Butler on April 30, 2026. It shows when each trip started and ended, as well as the total duration of each trip, by selecting the StartDateTime, ArrivalDateTime, and DurationHoursMinutes columns from the vwAllocations01 view. The results are filtered to only include trips by this driver on the specified date and are sorted by the trip start time. Up to 10,000 records are returned.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDateTime</td><td>The date and time when the trip began</td></tr><tr><td>ArrivalDateTime</td><td>The date and time when the trip ended</td></tr><tr><td>DurationHoursMinutes</td><td>The total duration of the trip in hours and minutes</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of all trips by Ahmod Butler on April 30, 2026, showing when each trip started, when it ended, and how long it lasted.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDateTime, ArrivalDateTime, DurationHoursMinutes</td><td>Specifies which trip details to show</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the trip allocation view</td></tr><tr><td>WHERE</td><td>DriverName = 'Ahmod Butler' AND StartDate = '2026-04-30'</td><td>Filters for trips by this driver on this date</td></tr><tr><td>ORDER BY</td><td>StartDateTime</td><td>Sorts trips by when they started</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits results to the first 10,000 records</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: ["4", "5"]
question: show me total duration hours and minutes by driver Ahmod Butler for month of May 2026
web: N
executed: Y
execution_time: 19.0
question_normalized: show_me_total_duration_hours_and_minutes_by_driver_ahmod_butler_for_month_of_may_2026
created_at: 2026-05-14 11:14:18
updated_at: 2026-05-14 11:14:18
sql:
  [{"agent_id": "4", "sub_question": "Show the total duration in hours and minutes for trips driven by driver Ahmod Butler during May 2026.", "sql": "SELECT TOP 10000\n    SUM(DurationHours) AS TotalHours,\n    SUM(DurationMinutes) AS TotalMinutes\nFROM\n    vwAllocations01\nWHERE\n    DriverName = 'Ahmod Butler'\n    AND StartDate >= '2026-05-01'\n    AND StartDate < '2026-06-01';"}, {"agent_id": "5", "sub_question": "Show the total hours worked by employee Ahmod Butler for the month of May 2026.", "sql": "SELECT \n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName,\n    SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours\nFROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED\n    ON PLC.LocationId = PED.LocationId\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE\n    ON PED.WorkerId = PCE.WorkerId\nWHERE PED.FamilyName = 'Butler'\n  AND PED.GivenName = 'Ahmod'\n  AND CAST(PCE.CheckDate AS DATE) >= '2026-05-01'\n  AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'\n  AND PCE.OrganizationName NOT IN (\n        '250 General Manager',\n        '200 Corp Office Admin',\n        '250 General Mgr',\n        '800 Operations Manager',\n        '800 Operations Mgr',\n        '900 Sales/Marketing',\n        '200 Corp Office'\n    )\n  AND PCE.ComponentName NOT LIKE '%Phone Reimburse%'\n  AND PCE.ComponentName NOT LIKE '%Exp Reimb%'\n  AND PCE.ComponentName NOT LIKE '%Expense Reimburse%'\n  AND PCE.ComponentName NOT LIKE '%Parking%'\n  AND PCE.ComponentName NOT LIKE '%Toll%'\n  AND PCE.ComponentName NOT LIKE '%Per Diem%'\n  AND PCE.ComponentName NOT LIKE '%Stale Dated PR%'\nGROUP BY \n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName\nORDER BY PED.EmployeeId\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}]

chart:
  chart_json = {
      'data': [
          {
              'x': df['GivenName'] + ' ' + df['FamilyName'],
              'y': df['TotalHours'],
              'type': 'bar',
              'name': 'Total Hours'
          },
          {
              'x': df['GivenName'] + ' ' + df['FamilyName'],
              'y': df['TotalMinutes'],
              'type': 'bar',
              'name': 'Total Minutes'
          }
      ],
      'layout': {
          'title': 'Total Duration Hours and Minutes by Driver Ahmod Butler for May 2026',
          'xaxis': {'title': 'Driver Name'},
          'yaxis': {'title': 'Duration'}
      }
  }


user_id: 1
agent_id: ["4", "5"]
question: show me total duration hours and minutes by driver Ahmod Butler for month of May 2026
web: N
executed: Y
execution_time: 10.0
question_normalized: show_me_total_duration_hours_and_minutes_by_driver_ahmod_butler_for_month_of_may_2026
created_at: 2026-05-14 11:14:56
updated_at: 2026-05-14 11:15:08
sql:
  [{"agent_id": "4", "sub_question": "Show the total duration in hours and minutes for trips driven by driver Ahmod Butler during May 2026.", "sql": "SELECT TOP 10000\n    SUM(DurationHours) AS TotalHours,\n    SUM(DurationMinutes) AS TotalMinutes\nFROM\n    vwAllocations01\nWHERE\n    DriverName = 'Ahmod Butler'\n    AND StartDate >= '2026-05-01'\n    AND StartDate < '2026-06-01';"}, {"agent_id": "5", "sub_question": "Show the total hours worked by employee Ahmod Butler for the month of May 2026.", "sql": "SELECT \n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName,\n    SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours\nFROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED\n    ON PLC.LocationId = PED.LocationId\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE\n    ON PED.WorkerId = PCE.WorkerId\nWHERE PED.FamilyName = 'Butler'\n  AND PED.GivenName = 'Ahmod'\n  AND CAST(PCE.CheckDate AS DATE) >= '2026-05-01'\n  AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'\n  AND PCE.OrganizationName NOT IN (\n        '250 General Manager',\n        '200 Corp Office Admin',\n        '250 General Mgr',\n        '800 Operations Manager',\n        '800 Operations Mgr',\n        '900 Sales/Marketing',\n        '200 Corp Office'\n    )\n  AND PCE.ComponentName NOT LIKE '%Phone Reimburse%'\n  AND PCE.ComponentName NOT LIKE '%Exp Reimb%'\n  AND PCE.ComponentName NOT LIKE '%Expense Reimburse%'\n  AND PCE.ComponentName NOT LIKE '%Parking%'\n  AND PCE.ComponentName NOT LIKE '%Toll%'\n  AND PCE.ComponentName NOT LIKE '%Per Diem%'\n  AND PCE.ComponentName NOT LIKE '%Stale Dated PR%'\nGROUP BY \n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName\nORDER BY PED.EmployeeId\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}]

chart:
  chart_json = {
      'data': [
          {
              'x': ['TotalHours', 'TotalMinutes'],
              'y': [df['TotalHours'].iloc[0], df['TotalMinutes'].iloc[0]],
              'type': 'bar',
              'name': 'Ahmod Butler'
          }
      ],
      'layout': {
          'title': 'Total Duration Hours and Minutes by Ahmod Butler for May 2026',
          'xaxis': {'title': 'Duration Type'},
          'yaxis': {'title': 'Value'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the total duration in hours and minutes for trips driven by driver Ahmod Butler during May 2026.", "summary": "This query calculates the total number of hours and minutes that Ahmod Butler spent driving trips during May 2026. It looks at the vwAllocations01 table, filters for trips where the driver's name is 'Ahmod Butler' and the trip start date is within May 2026, and then sums up the DurationHours and DurationMinutes columns to get the total time spent driving in that month. The output shows two columns: TotalHours (sum of hours) and TotalMinutes (sum of minutes). The final result is a single row with the total driving time for Ahmod Butler in May 2026.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total number of hours and minutes that Ahmod Butler spent driving trips during May 2026. It sums up the time from all trips he drove in that month.</p><hr><h3>The Final Output</h3><p>The output is a single row showing the total hours and total minutes Ahmod Butler drove in May 2026.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>SUM(DurationHours), SUM(DurationMinutes)</td><td>Calculates total driving time</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses trip allocation data</td></tr><tr><td>WHERE</td><td>DriverName = 'Ahmod Butler', StartDate between '2026-05-01' and '2026-06-01'</td><td>Filters for trips by Ahmod Butler in May 2026</td></tr><tr><td>TOP</td><td>10000</td><td>Limits output to 10,000 rows (not needed here, as only one row is expected)</td></tr></tbody></table></div>"}, {"agent_id": "5", "sub_question": "Show the total hours worked by employee Ahmod Butler for the month of May 2026.", "summary": "This query finds the total number of hours worked by employee Ahmod Butler during May 2026, based on payroll records. It joins several payroll-related tables to match Ahmod Butler's employee data with his payroll earnings, filters for records where his family name is 'Butler' and given name is 'Ahmod', and only includes payroll entries with check dates in May 2026. The query excludes hours from certain organization names (such as corporate office or management roles) and removes payroll components related to reimbursements, parking, tolls, per diems, and stale checks. The output lists Ahmod Butler's EmployeeId, FamilyName, GivenName, and the total hours worked in May 2026. The final result is a single row with these details for Ahmod Butler.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total number of hours worked by employee Ahmod Butler during May 2026, based on payroll records. It excludes hours from certain roles and reimbursement-related payroll items to focus on regular work hours.</p><hr><h4>Step 1 - Join Payroll Tables</h4><p>The query joins payroll location, employee, and earnings tables to connect Ahmod Butler's employee information with his payroll records.</p><h4>Step 2 - Filter for Ahmod Butler and May 2026</h4><p>It filters for records where the employee's name is Ahmod Butler and the payroll check date is in May 2026.</p><h4>Step 3 - Exclude Certain Roles and Components</h4><p>The query excludes hours from specific organization names (like management or corporate office) and removes payroll components related to reimbursements, parking, tolls, per diems, and stale checks.</p><h4>Step 4 - Calculate Total Hours</h4><p>It sums up the hours worked by Ahmod Butler in the filtered records.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>EmployeeId</td><td>Ahmod Butler's unique employee identifier</td></tr><tr><td>FamilyName</td><td>Last name (Butler)</td></tr><tr><td>GivenName</td><td>First name (Ahmod)</td></tr><tr><td>TotalHours</td><td>Total hours worked in May 2026</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a single row showing Ahmod Butler's employee ID, name, and the total hours he worked in May 2026, excluding non-regular work items.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>EmployeeId, FamilyName, GivenName, SUM(Hours)</td><td>Shows employee details and total hours</td></tr><tr><td>FROM</td><td>tbl_Payroll_Location_Data, tbl_Payroll_Employee_Data, tbl_Payroll_Checks_Earnings</td><td>Uses payroll and employee data</td></tr><tr><td>INNER JOIN</td><td>On LocationId and WorkerId</td><td>Links employee and payroll records</td></tr><tr><td>WHERE</td><td>FamilyName = 'Butler', GivenName = 'Ahmod', CheckDate in May 2026, excludes certain organizations and components</td><td>Filters for Ahmod Butler's regular work hours in May 2026</td></tr><tr><td>GROUP BY</td><td>EmployeeId, FamilyName, GivenName</td><td>Groups results by employee</td></tr><tr><td>ORDER BY</td><td>EmployeeId</td><td>Sorts results by employee ID</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limits output to 10,000 rows (only one expected)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: ["4", "5"]
question: Show Ahmod Butler’s total trip durations in hours and minutes broken down by week for May 2026.
web: N
executed: Y
execution_time: 17.0
question_normalized: show_ahmod_butler’s_total_trip_durations_in_hours_and_minutes_broken_down_by_week_for_may_2026.
created_at: 2026-05-14 11:16:53
updated_at: 2026-05-14 11:16:53
sql:
  [{"agent_id": "4", "sub_question": "Show total trip durations in hours and minutes for Ahmod Butler, broken down by week for May 2026.", "sql": "SELECT\n    DATEPART(week, StartDateTime) AS WeekNumber,\n    SUM(DurationHours) AS TotalHours,\n    SUM(DurationMinutes) AS TotalMinutes\nFROM vwAllocations01\nWHERE\n    DriverName = 'Ahmod Butler'\n    AND StartDateTime >= '2026-05-01'\n    AND StartDateTime < '2026-06-01'\nGROUP BY\n    DATEPART(week, StartDateTime)\nORDER BY\n    WeekNumber\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}, {"agent_id": "5", "sub_question": "Retrieve Ahmod Butler\u2019s total trip durations in hours and minutes, broken down by week for May 2026, using payroll or time-tracking data that may reflect trip or work durations for this employee.", "sql": "SELECT\n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName,\n    DATEPART(ISO_WEEK, PCE.CheckDate) AS ISO_Week,\n    SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours,\n    (SUM(CAST(PCE.Hours AS DECIMAL(18,2))) * 60) AS TotalMinutes\nFROM\n    AvalonReporting.dbo.tbl_Payroll_Location_Data PLC\n    INNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED\n        ON PLC.LocationId = PED.LocationId\n    INNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE\n        ON PED.WorkerId = PCE.WorkerId\nWHERE\n    PED.FamilyName = 'Butler'\n    AND PED.GivenName = 'Ahmod'\n    AND CAST(PCE.CheckDate AS DATE) >= '2026-05-01'\n    AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'\nGROUP BY\n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName,\n    DATEPART(ISO_WEEK, PCE.CheckDate)\nORDER BY\n    PED.EmployeeId,\n    ISO_Week\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}]

chart:
  chart_json = {
      'data': [
          {
              'x': df['WeekNumber'].tolist(),
              'y': df['TotalMinutes'].tolist(),
              'type': 'bar',
              'name': 'Total Trip Duration (Minutes)'
          }
      ],
      'layout': {
          'title': "Ahmod Butler’s Total Trip Durations by Week (May 2026)",
          'xaxis': {'title': 'Week Number'},
          'yaxis': {'title': 'Total Duration (Minutes)'}
      }
  }


user_id: 1
agent_id: ["4", "5"]
question: Show me total hours by employee or driver in May 2026
chart: N
web: N
executed: Y
execution_time: 20.0
question_normalized: show_me_total_hours_by_employee_or_driver_in_may_2026
created_at: 2026-05-15 12:36:14
updated_at: 2026-05-15 12:36:14
sql:
  [{"agent_id": "4", "sub_question": "Show total hours by driver in May 2026.", "sql": "SELECT\n    DriverName,\n    SUM(DurationDecimalHours) AS TotalHours\nFROM\n    vwAllocations01\nWHERE\n    StartDate >= '2026-05-01'\n    AND StartDate < '2026-06-01'\nGROUP BY\n    DriverName\nORDER BY\n    DriverName\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}, {"agent_id": "5", "sub_question": "Show total hours by employee in May 2026.", "sql": "SELECT\n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName,\n    PED.FamilyName + ', ' + PED.GivenName AS [Full Name],\n    SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours\nFROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED\n    ON PLC.LocationId = PED.LocationId\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE\n    ON PED.WorkerId = PCE.WorkerId\nWHERE\n    CAST(PCE.CheckDate AS DATE) >= '2026-05-01'\n    AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'\n    AND PCE.OrganizationName NOT IN (\n        '250 General Manager',\n        '200 Corp Office Admin',\n        '250 General Mgr',\n        '800 Operations Manager',\n        '800 Operations Mgr',\n        '900 Sales/Marketing',\n        '200 Corp Office'\n    )\n    AND PCE.ComponentName NOT LIKE '%Phone Reimburse%'\n    AND PCE.ComponentName NOT LIKE '%Exp Reimb%'\n    AND PCE.ComponentName NOT LIKE '%Expense Reimburse%'\n    AND PCE.ComponentName NOT LIKE '%Parking%'\n    AND PCE.ComponentName NOT LIKE '%Toll%'\n    AND PCE.ComponentName NOT LIKE '%Per Diem%'\n    AND PCE.ComponentName NOT LIKE '%Stale Dated PR%'\nGROUP BY\n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName\nORDER BY\n    PED.FamilyName,\n    PED.GivenName,\n    PED.EmployeeId\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}]


user_id: 1
agent_id: ["4", "5"]
question: Show me total hours by employee or driver in May 2026
chart: N
web: N
executed: Y
execution_time: 10.0
question_normalized: show_me_total_hours_by_employee_or_driver_in_may_2026
created_at: 2026-05-15 12:37:21
updated_at: 2026-05-15 12:37:38
sql:
  [{"agent_id": "4", "sub_question": "Show total hours by driver in May 2026.", "sql": "SELECT\n    DriverName,\n    SUM(DurationDecimalHours) AS TotalHours\nFROM\n    vwAllocations01\nWHERE\n    StartDate >= '2026-05-01'\n    AND StartDate < '2026-06-01'\nGROUP BY\n    DriverName\nORDER BY\n    DriverName\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}, {"agent_id": "5", "sub_question": "Show total hours by employee in May 2026.", "sql": "SELECT\n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName,\n    PED.FamilyName + ', ' + PED.GivenName AS [Full Name],\n    SUM(CAST(PCE.Hours AS DECIMAL(18,2))) AS TotalHours\nFROM AvalonReporting.dbo.tbl_Payroll_Location_Data PLC\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Employee_Data PED\n    ON PLC.LocationId = PED.LocationId\nINNER JOIN AvalonReporting.dbo.tbl_Payroll_Checks_Earnings PCE\n    ON PED.WorkerId = PCE.WorkerId\nWHERE\n    CAST(PCE.CheckDate AS DATE) >= '2026-05-01'\n    AND CAST(PCE.CheckDate AS DATE) <= '2026-05-31'\n    AND PCE.OrganizationName NOT IN (\n        '250 General Manager',\n        '200 Corp Office Admin',\n        '250 General Mgr',\n        '800 Operations Manager',\n        '800 Operations Mgr',\n        '900 Sales/Marketing',\n        '200 Corp Office'\n    )\n    AND PCE.ComponentName NOT LIKE '%Phone Reimburse%'\n    AND PCE.ComponentName NOT LIKE '%Exp Reimb%'\n    AND PCE.ComponentName NOT LIKE '%Expense Reimburse%'\n    AND PCE.ComponentName NOT LIKE '%Parking%'\n    AND PCE.ComponentName NOT LIKE '%Toll%'\n    AND PCE.ComponentName NOT LIKE '%Per Diem%'\n    AND PCE.ComponentName NOT LIKE '%Stale Dated PR%'\nGROUP BY\n    PED.EmployeeId,\n    PED.FamilyName,\n    PED.GivenName\nORDER BY\n    PED.FamilyName,\n    PED.GivenName,\n    PED.EmployeeId\nOFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;"}]

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show total hours by driver in May 2026.", "summary": "This query calculates the total number of hours worked by each driver during May 2026. It uses the vwAllocations01 table, sums up the DurationDecimalHours for each driver where the StartDate falls within May 2026, and lists the results by DriverName. The output shows each driver's name and their total hours for the month, sorted alphabetically by driver name. The query limits the results to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total hours worked by each driver during May 2026. It looks at the vwAllocations01 table, adds up the DurationDecimalHours for each driver where the StartDate is between May 1 and May 31, 2026, and lists the results by driver name.</p><hr><h3>The Final Output</h3><p>The output is a list showing each driver's name and the total number of hours they worked in May 2026, sorted alphabetically by driver name. Only the first 10,000 results are included.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>DriverName, SUM(DurationDecimalHours) AS TotalHours</td><td>Shows driver names and their total hours</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source table for driver allocations</td></tr><tr><td>WHERE</td><td>StartDate >= '2026-05-01' AND StartDate < '2026-06-01'</td><td>Filters records to May 2026</td></tr><tr><td>GROUP BY</td><td>DriverName</td><td>Calculates totals per driver</td></tr><tr><td>ORDER BY</td><td>DriverName</td><td>Sorts results alphabetically by driver</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}, {"agent_id": "5", "sub_question": "Show total hours by employee in May 2026.", "summary": "This query reports the total hours worked by each employee in May 2026. It joins three tables\u2014tbl_Payroll_Location_Data, tbl_Payroll_Employee_Data, and tbl_Payroll_Checks_Earnings\u2014to match employees with their payroll records. The query sums the Hours field for each employee where the CheckDate is in May 2026, excluding certain organization names and pay components related to reimbursements and non-work items. The results show each employee's ID, family name, given name, full name, and their total hours, sorted by family name, given name, and employee ID. Only the first 10,000 rows are returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total hours worked by each employee during May 2026. It combines payroll and employee data from three tables, sums up the hours for each employee where the check date is in May 2026, and excludes records related to reimbursements and certain administrative roles.</p><hr><h4>Step 1 - Join Tables</h4><p>The query joins tbl_Payroll_Location_Data, tbl_Payroll_Employee_Data, and tbl_Payroll_Checks_Earnings to connect employees with their payroll hours.</p><h4>Step 2 - Filter Records</h4><p>It filters for payroll records with check dates in May 2026 and excludes specific organization names and pay components related to reimbursements and non-work items.</p><h4>Step 3 - Group and Summarize</h4><p>The query groups the results by employee and calculates the total hours for each person.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>EmployeeId</td><td>Unique identifier for each employee</td></tr><tr><td>FamilyName, GivenName</td><td>Employee's last and first names</td></tr><tr><td>Full Name</td><td>Combined family and given name</td></tr><tr><td>TotalHours</td><td>Total hours worked in May 2026</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of employees with their ID, names, and total hours worked in May 2026, sorted by family name, given name, and employee ID. Only the first 10,000 results are shown.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>EmployeeId, FamilyName, GivenName, Full Name, SUM(Hours) AS TotalHours</td><td>Shows employee details and total hours</td></tr><tr><td>FROM</td><td>tbl_Payroll_Location_Data, tbl_Payroll_Employee_Data, tbl_Payroll_Checks_Earnings</td><td>Source tables for payroll and employee data</td></tr><tr><td>INNER JOIN</td><td>LocationId, WorkerId</td><td>Connects employee and payroll records</td></tr><tr><td>WHERE</td><td>CheckDate in May 2026, excludes certain organizations and components</td><td>Filters for relevant payroll records</td></tr><tr><td>GROUP BY</td><td>EmployeeId, FamilyName, GivenName</td><td>Calculates totals per employee</td></tr><tr><td>ORDER BY</td><td>FamilyName, GivenName, EmployeeId</td><td>Sorts results by employee name and ID</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me hours worked in company id HO in May 2026
web: N
executed: Y
execution_time: 9.0
question_normalized: show_me_hours_worked_in_company_id_ho_in_may_2026
created_at: 2026-05-15 18:17:47
updated_at: 2026-05-15 18:17:53
sql:
  SELECT CompanyID, SUM(DurationDecimalHours) AS HoursWorked
  FROM vwAllocations01
  WHERE CompanyID = 'HO'
    AND StartDateTime >= '2026-05-01'
    AND StartDateTime < '2026-06-01'
  GROUP BY CompanyID
  ORDER BY CompanyID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['CompanyID'].tolist(),
              'y': df['HoursWorked'].tolist(),
              'type': 'bar',
              'name': 'Hours Worked'
          }
      ],
      'layout': {
          'title': 'Hours Worked in Company ID HO in May 2026',
          'xaxis': {'title': 'CompanyID'},
          'yaxis': {'title': 'HoursWorked'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me hours worked in company id HO in May 2026", "summary": "This query calculates the total number of hours worked for the company with ID 'HO' during May 2026. It does this by summing up the 'DurationDecimalHours' from the 'vwAllocations01' table for all records where the 'CompanyID' is 'HO' and the 'StartDateTime' falls within May 2026. The results are grouped by company and limited to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total hours worked for the company with ID 'HO' during the month of May 2026. It adds up all the recorded work durations for that company within the specified date range.</p><hr><h4>Step 1 - Filter Records for Company 'HO' in May 2026</h4><p>The query selects records from the 'vwAllocations01' table where the 'CompanyID' is 'HO' and the 'StartDateTime' is between May 1, 2026, and before June 1, 2026.</p><h4>Step 2 - Sum Hours Worked</h4><p>It then sums the 'DurationDecimalHours' for these filtered records to get the total hours worked.</p><h4>Step 3 - Group and Limit Results</h4><p>The results are grouped by 'CompanyID' and limited to the first 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>CompanyID</td><td>The unique identifier for the company (in this case, 'HO').</td></tr><tr><td>HoursWorked</td><td>The total number of hours worked for company 'HO' in May 2026.</td></tr></tbody></table><h3>The Final Output</h3><p>The output will display the company ID and the total hours worked for company 'HO' during May 2026.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>CompanyID, SUM(DurationDecimalHours) AS HoursWorked</td><td>Chooses company and total hours worked</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of work allocation data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO' AND StartDateTime &gt;= '2026-05-01' AND StartDateTime &lt; '2026-06-01'</td><td>Filters for company 'HO' and May 2026</td></tr><tr><td>GROUP BY</td><td>CompanyID</td><td>Groups results by company</td></tr><tr><td>ORDER BY</td><td>CompanyID</td><td>Sorts results by company ID</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits to first 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me the breakdown of hours worked by each driver in company id HO in May 2026.
web: N
executed: Y
execution_time: 7.0
question_normalized: show_me_the_breakdown_of_hours_worked_by_each_driver_in_company_id_ho_in_may_2026.
created_at: 2026-05-15 18:18:22
updated_at: 2026-05-15 18:18:31
sql:
  SELECT
      DriverName,
      DriverID,
      SUM(DurationDecimalHours) AS TotalHours
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= '2026-05-01'
      AND StartDate < '2026-06-01'
  GROUP BY
      DriverName,
      DriverID
  ORDER BY
      DriverName,
      DriverID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['DriverName'].tolist(),
              'y': df['TotalHours'].tolist(),
              'type': 'bar',
              'name': 'Total Hours Worked'
          }
      ],
      'layout': {
          'title': 'Breakdown of Hours Worked by Each Driver in Company HO in May 2026',
          'xaxis': {'title': 'Driver Name'},
          'yaxis': {'title': 'Total Hours'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me the breakdown of hours worked by each driver in company id HO in May 2026.", "summary": "This query retrieves a list of drivers from company HO and shows the total number of hours each driver worked during May 2026. It uses the vwAllocations01 table, filters for records where the company ID is 'HO' and the work start date is within May 2026, then groups the results by driver name and ID. The output includes each driver's name, ID, and their total hours worked, sorted alphabetically by driver name and ID. The query limits the results to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists each driver in company HO and shows how many hours they worked in total during May 2026. It summarizes work hours for each driver based on records from the vwAllocations01 table.</p><hr><h4>Step 1 - Filter Records</h4><p>The query selects records where the CompanyID is 'HO' and the StartDate is between May 1, 2026, and before June 1, 2026.</p><h4>Step 2 - Group and Summarize</h4><p>It groups the filtered records by DriverName and DriverID, then calculates the total hours worked (using the SUM of DurationDecimalHours) for each driver.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by DriverName and DriverID, and only the first 10,000 rows are returned.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>DriverName</td><td>The name of the driver</td></tr><tr><td>DriverID</td><td>The unique identifier for the driver</td></tr><tr><td>TotalHours</td><td>The total number of hours worked by the driver in May 2026</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of drivers from company HO, showing each driver's name, ID, and the total hours they worked in May 2026, sorted alphabetically.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>FROM</td><td>vwAllocations01</td><td>Source of driver work records</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate between '2026-05-01' and '2026-06-01'</td><td>Filter for company HO and May 2026</td></tr><tr><td>GROUP BY</td><td>DriverName, DriverID</td><td>Summarize hours per driver</td></tr><tr><td>ORDER BY</td><td>DriverName, DriverID</td><td>Sort results alphabetically</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limit results to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me trips for Elton Harris.
chart: N
web: N
executed: Y
execution_time: 11.0
question_normalized: show_me_trips_for_elton_harris.
created_at: 2026-05-15 18:20:07
updated_at: 2026-05-15 18:20:14
sql:
  SELECT
      StartDate,
      PickupDateTime,
      PickupPoint,
      Destination,
      DriverName,
      BookingID,
      ClientID
  FROM vwAllocations01
  WHERE DriverName = 'Elton Harris'
  ORDER BY StartDate, PickupDateTime
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me trips for Elton Harris.", "summary": "This query retrieves a list of trips assigned to the driver Elton Harris. It selects details such as the trip's start date, pickup time, pickup location, destination, driver name, booking ID, and client ID from the 'vwAllocations01' view. The results are filtered to only include trips where the driver is Elton Harris, sorted by start date and pickup time, and limited to the first 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists all trips for the driver Elton Harris, showing key trip details such as when and where each trip started, the destination, and associated booking and client information. Only trips assigned to Elton Harris are included.</p><hr><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date the trip started</td></tr><tr><td>PickupDateTime</td><td>The exact time the passenger was picked up</td></tr><tr><td>PickupPoint</td><td>The location where the trip began</td></tr><tr><td>Destination</td><td>The end location of the trip</td></tr><tr><td>DriverName</td><td>The name of the driver (always Elton Harris here)</td></tr><tr><td>BookingID</td><td>The unique ID for the booking</td></tr><tr><td>ClientID</td><td>The unique ID for the client</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a detailed list of up to 10,000 trips driven by Elton Harris, including trip timing, locations, and booking/client identifiers.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, PickupDateTime, PickupPoint, Destination, DriverName, BookingID, ClientID</td><td>Specifies which trip details to display</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the trip allocation view as the data source</td></tr><tr><td>WHERE</td><td>DriverName = 'Elton Harris'</td><td>Filters to only trips for Elton Harris</td></tr><tr><td>ORDER BY</td><td>StartDate, PickupDateTime</td><td>Sorts trips by date and pickup time</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits the output to the first 10,000 trips</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me total rides as of yesterday for company id HO
web: N
executed: Y
execution_time: 7.0
question_normalized: show_me_total_rides_as_of_yesterday_for_company_id_ho
created_at: 2026-05-19 08:10:28
updated_at: 2026-05-19 08:10:34
sql:
  SELECT TOP 10000 COUNT(*) AS TotalRides
  FROM vwAllocations01
  WHERE CompanyID = 'HO'
    AND CAST(StartDate AS DATE) = CAST(DATEADD(day, -1, GETDATE()) AS DATE);

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalRides'].tolist(),
              'type': 'bar',
              'name': 'Total Rides'
          }
      ],
      'layout': {
          'title': 'Total Rides as of Yesterday for Company ID HO',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalRides'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me total rides as of yesterday for company id HO", "summary": "This query counts the total number of rides that started yesterday for the company with ID 'HO'. It looks at the 'vwAllocations01' table, filters for records where the CompanyID is 'HO', and where the StartDate matches yesterday's date. The result is a single number representing the total rides for that company on that day.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total number of rides that started yesterday for the company with the ID 'HO'. It checks the 'vwAllocations01' table for all rides that match these criteria.</p><h3>The Final Output</h3><p>The output is a single value showing how many rides started yesterday for company 'HO'.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(*) AS TotalRides</td><td>Counts the total number of rides</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source table containing ride data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO' AND StartDate = yesterday</td><td>Filters for company 'HO' and rides that started yesterday</td></tr><tr><td>TOP</td><td>10000</td><td>Limits output to 10,000 rows (though only one row is expected)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the trend of rides for company HO over the past week.
chart: N
web: N
executed: Y
execution_time: 4.0
question_normalized: show_the_trend_of_rides_for_company_ho_over_the_past_week.
created_at: 2026-05-19 08:11:29
updated_at: 2026-05-19 08:11:36
sql:
  SELECT
    StartDate,
    COUNT(*) AS RideCount
  FROM vwAllocations01
  WHERE
    Company = 'HO'
    AND StartDate >= DATEADD(day, -6, CAST(GETDATE() AS date))
    AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY StartDate
  ORDER BY StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the trend of rides for company HO over the past week.", "summary": "This query retrieves the daily number of rides for company HO over the past week. It counts how many rides started on each day, from six days ago up to today, using data from the vwAllocations01 table. The results are grouped by the ride start date and sorted in chronological order, with a maximum of 10,000 rows returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows how many rides were started each day by company HO over the last seven days, including today. It helps track the daily trend in ride activity for this company.</p><hr><h4>Step 1 - Filter Data for Company HO and Past Week</h4><p>The query selects records from the vwAllocations01 table where the Company column is 'HO' and the StartDate is within the last seven days (from six days ago to today).</p><h4>Step 2 - Group and Count Rides by Date</h4><p>For each date in this period, it counts the number of rides (rows) and groups the results by StartDate.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by StartDate in ascending order and limited to 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when rides started</td></tr><tr><td>RideCount</td><td>The total number of rides started on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past week, each with the corresponding number of rides started by company HO on that day. This allows you to see the trend in ride volume over the week.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, COUNT(*) AS RideCount</td><td>Chooses the date and counts rides per day</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the ride allocation data</td></tr><tr><td>WHERE</td><td>Company = 'HO' AND StartDate between last 6 days and today</td><td>Filters for company HO and the past week</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Groups results by each ride start date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the trend of rides for company HO over the past week.
chart: N
web: N
executed: N
execution_time: 2.0
question_normalized: show_the_trend_of_rides_for_company_ho_over_the_past_week.
created_at: 2026-05-19 08:12:57
updated_at: 2026-05-19 08:12:57
sql:
  SELECT
    StartDate,
    COUNT(*) AS RideCount
  FROM vwAllocations01
  WHERE
    Company_id = 'HO'
    AND StartDate >= DATEADD(day, -6, CAST(GETDATE() AS date))
    AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY StartDate
  ORDER BY StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 4
question: Show the trend of rides for companyid HO over the past week.
chart: N
web: N
executed: Y
execution_time: 10.0
question_normalized: show_the_trend_of_rides_for_companyid_ho_over_the_past_week.
created_at: 2026-05-19 08:13:35
updated_at: 2026-05-19 08:13:44
sql:
  SELECT
    StartDate,
    COUNT(*) AS RideCount
  FROM
    vwAllocations01
  WHERE
    CompanyID = 'HO'
    AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
  GROUP BY
    StartDate
  ORDER BY
    StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the trend of rides for companyid HO over the past week.", "summary": "This query retrieves the number of rides that started each day for the company with ID 'HO' over the past week. It counts how many rides began on each date, groups the results by the ride start date, and sorts them in chronological order. The output shows the date and the corresponding number of rides for each day, limited to the most recent 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many rides started each day for the company with ID 'HO' during the past week. It summarizes the daily ride counts and lists them by date.</p><hr><h4>Step 1 - Filter Rides for Company 'HO' in the Past Week</h4><p>The query looks at the 'vwAllocations01' table and selects only those rides where the CompanyID is 'HO' and the StartDate is within the last 7 days (including today).</p><h4>Step 2 - Group and Count Rides by Start Date</h4><p>It groups the filtered rides by their StartDate and counts how many rides started on each date.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by StartDate in ascending order and limited to the first 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when rides started</td></tr><tr><td>RideCount</td><td>The number of rides that began on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past week, each paired with the total number of rides that started on that day for company 'HO'. This allows you to see the daily trend in ride activity.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>FROM</td><td>vwAllocations01</td><td>Source of ride data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO' AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))</td><td>Filters for company 'HO' and rides in the past week</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Groups rides by the date they started</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the trend of rides for companyid HO over the past week.
chart: N
web: N
executed: N
execution_time: 2.0
question_normalized: show_the_trend_of_rides_for_companyid_ho_over_the_past_week.
created_at: 2026-05-19 08:16:50
updated_at: 2026-05-19 08:16:50
sql:
  SELECT
    StartDate,
    COUNT(*) AS RideCount
  FROM
    vwAllocations01
  WHERE
    CompanyID = 'HO'
    AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
  AND StartDate <= CAST(GETDATE())
  GROUP BY
    StartDate
  ORDER BY
    StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 4
question: Show the trend of rides for companyid HO over the past week.
chart: N
web: N
executed: Y
execution_time: 9.0
question_normalized: show_the_trend_of_rides_for_companyid_ho_over_the_past_week.
created_at: 2026-05-19 08:17:14
updated_at: 2026-05-19 08:17:23
sql:
  SELECT
      StartDate,
      COUNT(*) AS RideCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
  GROUP BY
      StartDate
  ORDER BY
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the trend of rides for companyid HO over the past week.", "summary": "This query retrieves the number of rides that started each day for the company with ID 'HO' over the past week. It looks at the 'vwAllocations01' table, counts how many rides occurred on each 'StartDate' where the company is 'HO' and the date is within the last 7 days, then lists these counts by date in order. The results are limited to the first 10,000 rows, which is more than enough for a week's worth of daily data.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many rides started each day in the past week for the company with ID 'HO'. It summarizes the daily ride counts using data from the 'vwAllocations01' table.</p><hr><h4>Step 1 - Filter Rides for Company 'HO' in the Past Week</h4><p>The query selects only those rides where the CompanyID is 'HO' and the StartDate is within the last 7 days from today.</p><h4>Step 2 - Count Rides Per Day</h4><p>For each date in this period, it counts the number of rides that started on that day.</p><h4>Step 3 - Order and Limit Results</h4><p>The results are sorted by StartDate and only the first 10,000 rows are returned (which covers all days in a week).</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when rides started</td></tr><tr><td>RideCount</td><td>The number of rides that started on that date for company 'HO'</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past week, each with the total number of rides that started on that day for company 'HO'. This allows you to see the daily trend in ride activity for that company.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, COUNT(*) AS RideCount</td><td>Chooses the date and counts rides per day</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the rides data source</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO' AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))</td><td>Filters for company 'HO' and rides in the past week</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Aggregates counts by each date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits the number of rows returned</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the trend of rides for companyid HO over the past week.
chart: N
web: N
executed: N
execution_time: 2.0
question_normalized: show_the_trend_of_rides_for_companyid_ho_over_the_past_week.
created_at: 2026-05-19 08:25:12
updated_at: 2026-05-19 08:25:12
sql:
  SELECT
      StartDate,
      COUNT(*) AS RideCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
  AND StartDate <= CAST(GETDATE())
  GROUP BY
      StartDate
  ORDER BY
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 4
question: Show you the trend of rides for companyid HO over the past week.
web: N
executed: Y
execution_time: 7.0
question_normalized: show_you_the_trend_of_rides_for_companyid_ho_over_the_past_week.
created_at: 2026-05-19 08:28:54
updated_at: 2026-05-19 08:29:02
sql:
  SELECT
      StartDate,
      COUNT(*) AS RideCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY
      StartDate
  ORDER BY
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['RideCount'].tolist(),
              'type': 'line',
              'name': 'Rides'
          }
      ],
      'layout': {
          'title': 'Trend of Rides for Company HO Over the Past Week',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'RideCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show you the trend of rides for companyid HO over the past week.", "summary": "This query retrieves the daily number of rides for the company with ID 'HO' over the past week. It counts how many rides started each day, using the StartDate column from the vwAllocations01 table, and only includes rides where the StartDate falls within the last seven days up to today. The results are grouped by each StartDate and sorted in chronological order, showing up to 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves the daily number of rides for the company with ID 'HO' over the past week. It counts how many rides started each day, using the StartDate column from the vwAllocations01 table, and only includes rides where the StartDate falls within the last seven days up to today. The results are grouped by each StartDate and sorted in chronological order, showing up to 10,000 rows.</p><hr><h4>What it shows</h4><table><thead><tr><th>Column</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when rides started</td></tr><tr><td>RideCount</td><td>The total number of rides that started on that date for company 'HO'</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past week, each with the total number of rides that started on that day for company 'HO'. This allows you to see the trend in ride activity over the last seven days.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, COUNT(*) AS RideCount</td><td>Chooses the ride start date and counts rides per day</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the ride allocation data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate >= DATEADD(day, -7, ...), StartDate <= GETDATE()</td><td>Filters for company 'HO' and rides in the past week</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Groups results by each day</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits the output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the busiest day for company HO during the past week.
chart: N
web: N
executed: Y
execution_time: 4.0
question_normalized: show_the_busiest_day_for_company_ho_during_the_past_week.
created_at: 2026-05-19 08:30:57
updated_at: 2026-05-19 08:31:05
sql:
  SELECT TOP 1
      StartDate,
      COUNT(*) AS JourneyCount
  FROM vwAllocations01
  WHERE Company = 'HO'
    AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
    AND StartDate < CAST(GETDATE() AS date)
  GROUP BY StartDate
  ORDER BY JourneyCount DESC, StartDate ASC

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the busiest day for company HO during the past week.", "summary": "This query finds the single day in the past week when company HO had the highest number of journeys, based on the StartDate of each journey. It looks at records from the vwAllocations01 table, counts the number of journeys for each day in the last 7 days (excluding today), and returns the day with the most journeys.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query identifies which day in the past week (not including today) had the most journeys for company HO. It checks the vwAllocations01 table, counts the journeys for each day, and returns the day with the highest count.</p><hr><h4>Step 1 - Filter for Company HO and Past Week</h4><p>The query selects only records where the Company is 'HO' and the StartDate is within the last 7 days, but not including today.</p><h4>Step 2 - Count Journeys Per Day</h4><p>It groups the filtered records by StartDate and counts how many journeys happened each day.</p><h4>Step 3 - Find the Busiest Day</h4><p>It orders the days by the number of journeys (from highest to lowest) and picks the top one.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date of the busiest day for company HO in the past week</td></tr><tr><td>JourneyCount</td><td>The number of journeys that started on that day</td></tr></tbody></table><h3>The Final Output</h3><p>The result is a single row showing the date with the most journeys for company HO in the past week, along with the total number of journeys on that day.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT TOP 1</td><td>StartDate, COUNT(*) AS JourneyCount</td><td>Returns only the busiest day and its journey count</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source table for journey data</td></tr><tr><td>WHERE</td><td>Company = 'HO', StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date)), StartDate < CAST(GETDATE() AS date)</td><td>Filters for company HO and journeys in the past week (excluding today)</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Counts journeys per day</td></tr><tr><td>ORDER BY</td><td>JourneyCount DESC, StartDate ASC</td><td>Sorts by most journeys, then earliest date if tied</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the busiest day for company HO during the past week.
web: N
executed: Y
execution_time: 7.0
question_normalized: show_the_busiest_day_for_company_ho_during_the_past_week.
created_at: 2026-05-19 08:36:24
updated_at: 2026-05-19 08:36:32
sql:
  SELECT TOP 1
      StartDate,
      COUNT(*) AS TotalBookings
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY
      StartDate
  ORDER BY
      TotalBookings DESC, StartDate DESC

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['TotalBookings'].tolist(),
              'type': 'bar',
              'name': 'Total Bookings'
          }
      ],
      'layout': {
          'title': 'Busiest Day for Company HO in the Past Week',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'TotalBookings'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the busiest day for company HO during the past week.", "summary": "This query finds the single day in the past week when company HO had the most bookings. It looks at the vwAllocations01 table, counts the number of bookings for each day where the CompanyID is 'HO' and the StartDate is within the last 7 days (including today), and then returns the day with the highest count. The output shows the date and the total number of bookings for that day.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query identifies the day in the past week when company HO had the highest number of bookings. It examines the vwAllocations01 table, focusing on records where the CompanyID is 'HO' and the StartDate falls within the last 7 days, including today. The query then counts the bookings for each day and selects the day with the highest total.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Past Week</h4><p>The query filters records to include only those where CompanyID is 'HO' and StartDate is between 7 days ago and today.</p><h4>Step 2 - Count Bookings Per Day</h4><p>It groups the filtered records by StartDate and counts the number of bookings for each day.</p><h4>Step 3 - Select the Busiest Day</h4><p>The results are ordered by the total number of bookings (descending), and the most recent date is used as a tiebreaker. Only the top result is returned.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The specific date within the past week</td></tr><tr><td>TotalBookings</td><td>The number of bookings for company HO on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a single row showing the date in the past week when company HO had the most bookings, along with the total number of bookings on that day.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT TOP 1</td><td>StartDate, COUNT(*) AS TotalBookings</td><td>Returns only the busiest day</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of booking data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date)), StartDate <= CAST(GETDATE() AS date)</td><td>Filters to company HO and the past week</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Aggregates bookings by day</td></tr><tr><td>ORDER BY</td><td>TotalBookings DESC, StartDate DESC</td><td>Ranks days by bookings, most recent first if tied</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: List the top three days with the highest bookings for company HO in the past week.
web: N
executed: Y
execution_time: 7.0
question_normalized: list_the_top_three_days_with_the_highest_bookings_for_company_ho_in_the_past_week.
created_at: 2026-05-19 08:38:00
updated_at: 2026-05-19 08:38:07
sql:
  SELECT TOP 3
      StartDate,
      COUNT(*) AS BookingCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY
      StartDate
  ORDER BY
      BookingCount DESC,
      StartDate DESC

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['BookingCount'].tolist(),
              'type': 'bar',
              'name': 'Booking Count'
          }
      ],
      'layout': {
          'title': 'Top 3 Days with Highest Bookings for Company HO in the Past Week',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'BookingCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "List the top three days with the highest bookings for company HO in the past week.", "summary": "This query finds the three days in the past week when company HO had the most bookings. It looks at the vwAllocations01 table, counts the number of bookings for each day (using the StartDate column), and only includes bookings where the CompanyID is 'HO' and the StartDate is within the last seven days up to today. The results are sorted so that the days with the highest booking counts appear first, and if there are ties, the most recent days are shown first. The output lists the top three days with the highest number of bookings.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query identifies the three days in the past week when company HO had the highest number of bookings. It examines booking records from the vwAllocations01 table, focusing only on those for company HO and within the last seven days, then ranks the days by booking count.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Past Week</h4><p>The query selects records where CompanyID is 'HO' and StartDate is between seven days ago and today.</p><h4>Step 2 - Count Bookings Per Day</h4><p>It groups the filtered records by StartDate and counts the number of bookings for each day.</p><h4>Step 3 - Sort and Select Top Three Days</h4><p>The results are sorted by the booking count (highest first), and then by the most recent date in case of ties. Only the top three days are shown.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date of the bookings</td></tr><tr><td>BookingCount</td><td>The number of bookings on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of the three days in the past week when company HO had the most bookings, showing the date and the number of bookings for each.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT TOP 3</td><td>StartDate, COUNT(*) AS BookingCount</td><td>Returns only the top three days with the most bookings</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of booking data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate between last 7 days and today</td><td>Filters for company HO and bookings in the past week</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Groups bookings by date</td></tr><tr><td>ORDER BY</td><td>BookingCount DESC, StartDate DESC</td><td>Sorts by highest booking count, then most recent date</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the overall trend of bookings for company HO over the past month.
web: N
executed: Y
execution_time: 11.0
question_normalized: show_the_overall_trend_of_bookings_for_company_ho_over_the_past_month.
created_at: 2026-05-19 08:38:33
updated_at: 2026-05-19 08:38:43
sql:
  SELECT
      StartDate,
      COUNT(BookingID) AS BookingCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(month, -1, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY
      StartDate
  ORDER BY
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['BookingCount'].tolist(),
              'type': 'line',
              'name': 'Bookings'
          }
      ],
      'layout': {
          'title': 'Overall Trend of Bookings for Company HO Over the Past Month',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'BookingCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the overall trend of bookings for company HO over the past month.", "summary": "This query retrieves the daily number of bookings for company HO over the past month. It counts how many bookings (BookingID) occurred on each StartDate, only including records where the CompanyID is 'HO' and the StartDate falls within the last month up to today. The results are grouped by date and sorted chronologically, showing up to 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows how many bookings were made each day for company HO over the past month. It helps visualize the daily trend in bookings for this company during that period.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Last Month</h4><p>The query selects records from the vwAllocations01 table where the CompanyID is 'HO' and the StartDate is within the last month (from one month ago up to today).</p><h4>Step 2 - Count Bookings Per Day</h4><p>For each date (StartDate), it counts the number of bookings (BookingID) and groups the results by date.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by StartDate in chronological order and limited to the first 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date of each booking</td></tr><tr><td>BookingCount</td><td>The total number of bookings made on that date for company HO</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past month, each with the number of bookings for company HO on that day. This allows you to see the overall trend in bookings over time.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, COUNT(BookingID) AS BookingCount</td><td>Choose date and count of bookings</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of booking data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate within last month</td><td>Filter for company HO and recent dates</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Aggregate bookings by date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sort results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limit number of rows returned</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me the last 7 days trips for the company HO
chart: N
web: N
executed: Y
execution_time: 6.0
question_normalized: show_me_the_last_7_days_trips_for_the_company_ho
created_at: 2026-05-19 08:41:46
updated_at: 2026-05-19 08:41:54
sql:
  SELECT
      StartDate,
      SortDateTime,
      StartDateTime,
      StartBase,
      StartPoint,
      Destination,
      ArrivalDateTime,
      FinishDateTime,
      BookingID,
      CompanyID
  FROM
      vwAllocations01
  WHERE
      StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
      AND CompanyID = 'HO'
  ORDER BY
      StartDate DESC,
      SortDateTime DESC
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me the last 7 days trips for the company HO", "summary": "This query retrieves a list of trips from the past 7 days for the company with ID 'HO'. It selects detailed trip information from the 'vwAllocations01' view, including start and end times, locations, and booking details. The results are sorted by the most recent start date and time, and only the most recent 10,000 trips are shown.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query lists all trips that started in the last 7 days for the company identified as 'HO'. It pulls detailed trip information, such as start and end times, locations, and booking IDs, from the 'vwAllocations01' view.</p><hr><h4>What it shows | What it means</h4><table><thead><tr><th>Column</th><th>Meaning</th></tr></thead><tbody><tr><td>StartDate</td><td>Date the trip started</td></tr><tr><td>SortDateTime</td><td>Date and time used for sorting trips</td></tr><tr><td>StartDateTime</td><td>Exact start date and time of the trip</td></tr><tr><td>StartBase</td><td>Starting base location</td></tr><tr><td>StartPoint</td><td>Starting point of the trip</td></tr><tr><td>Destination</td><td>Trip destination</td></tr><tr><td>ArrivalDateTime</td><td>Date and time of arrival at destination</td></tr><tr><td>FinishDateTime</td><td>Date and time the trip finished</td></tr><tr><td>BookingID</td><td>Unique identifier for the booking</td></tr><tr><td>CompanyID</td><td>Identifier for the company (filtered to 'HO')</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a detailed, chronological list of up to 10,000 trips for company 'HO' that started within the last 7 days, including all key trip details.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, SortDateTime, StartDateTime, StartBase, StartPoint, Destination, ArrivalDateTime, FinishDateTime, BookingID, CompanyID</td><td>Specifies which trip details to show</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of trip data</td></tr><tr><td>WHERE</td><td>StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date)) AND StartDate <= CAST(GETDATE() AS date) AND CompanyID = 'HO'</td><td>Filters to trips from the last 7 days for company 'HO'</td></tr><tr><td>ORDER BY</td><td>StartDate DESC, SortDateTime DESC</td><td>Shows most recent trips first</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits results to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me the total number of trips in the last 7 days for the company HO.
web: N
executed: Y
execution_time: 6.0
question_normalized: show_me_the_total_number_of_trips_in_the_last_7_days_for_the_company_ho.
created_at: 2026-05-19 08:44:03
updated_at: 2026-05-19 08:44:11
sql:
  SELECT TOP 10000 COUNT(*) AS TotalTrips
  FROM vwAllocations01
  WHERE CompanyID = 'HO'
    AND StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))
    AND StartDate < CAST(GETDATE() + 1 AS date);

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          }
      ],
      'layout': {
          'title': 'Total Number of Trips in the Last 7 Days for Company HO',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalTrips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me the total number of trips in the last 7 days for the company HO.", "summary": "This query counts the total number of trips recorded in the 'vwAllocations01' table for the company with ID 'HO' that started within the last 7 days, including today. It filters trips by the 'CompanyID' column and checks that the 'StartDate' is between 7 days ago and the end of today. The result is a single number representing the total trips for this period.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates how many trips have started in the last 7 days for the company identified as 'HO'. It checks the trip records in the 'vwAllocations01' table, filtering by company and date range, and returns the total count.</p><h3>The Final Output</h3><p>The output is a single number labeled 'TotalTrips', showing how many trips the company 'HO' started in the last 7 days (including today).</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(*) AS TotalTrips</td><td>Counts the number of trips</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the trip allocation view</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO'</td><td>Filters for company HO</td></tr><tr><td>WHERE</td><td>StartDate >= DATEADD(day, -7, CAST(GETDATE() AS date))</td><td>Only trips from the last 7 days</td></tr><tr><td>WHERE</td><td>StartDate &lt; CAST(GETDATE() + 1 AS date)</td><td>Ensures trips are up to and including today</td></tr><tr><td>TOP</td><td>10000</td><td>Limits output rows (not needed here as only one row is returned)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the overall trend of bookings for company HO over the past month
web: N
executed: Y
execution_time: 8.0
question_normalized: show_the_overall_trend_of_bookings_for_company_ho_over_the_past_month
created_at: 2026-05-19 08:49:29
updated_at: 2026-05-19 08:49:39
sql:
  SELECT
      StartDate,
      COUNT(*) AS BookingCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(month, -1, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY
      StartDate
  ORDER BY
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['BookingCount'].tolist(),
              'type': 'line',
              'name': 'BookingCount'
          }
      ],
      'layout': {
          'title': 'Overall Trend of Bookings for Company HO Over the Past Month',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'BookingCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the overall trend of bookings for company HO over the past month", "summary": "This query retrieves the daily number of bookings made by company HO over the past month. It counts how many bookings started on each date within the last month, groups the results by each start date, and sorts them in chronological order. The output shows the booking date and the corresponding number of bookings for that day, limited to the first 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows how many bookings company HO made each day over the past month. It provides a day-by-day count of bookings, helping to visualize booking trends for the company during this period.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Past Month</h4><p>The query selects records from the <strong>vwAllocations01</strong> table where the <strong>CompanyID</strong> is 'HO' and the <strong>StartDate</strong> falls within the last month up to today.</p><h4>Step 2 - Count Bookings Per Day</h4><p>It groups the filtered bookings by <strong>StartDate</strong> and counts the number of bookings for each date.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by <strong>StartDate</strong> in chronological order and limited to 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when bookings started</td></tr><tr><td>BookingCount</td><td>The number of bookings that began on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past month, each with the total number of bookings made by company HO on that day. This allows you to see booking trends over time.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, COUNT(*) AS BookingCount</td><td>Chooses the booking date and counts bookings per day</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the bookings data view</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate >= DATEADD(month, -1, CAST(GETDATE() AS date)), StartDate <= CAST(GETDATE() AS date)</td><td>Filters for company HO and bookings in the last month</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Groups bookings by date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits the output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: what is the overall trend of bookings for company HO over the past month
web: N
executed: Y
execution_time: 8.0
question_normalized: what_is_the_overall_trend_of_bookings_for_company_ho_over_the_past_month
created_at: 2026-05-19 09:07:27
updated_at: 2026-05-19 09:07:40
sql:
  SELECT 
      CONVERT(varchar(10), StartDate, 120) AS StartDate,
      COUNT(*) AS BookingCount
  FROM 
      vwAllocations01
  WHERE 
      CompanyID = 'HO'
      AND StartDate >= DATEADD(month, -1, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY 
      CONVERT(varchar(10), StartDate, 120)
  ORDER BY 
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['BookingCount'].tolist(),
              'type': 'line',
              'name': 'Bookings'
          }
      ],
      'layout': {
          'title': 'Overall Trend of Bookings for Company HO Over the Past Month',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'BookingCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "what is the overall trend of bookings for company HO over the past month", "summary": "This query retrieves the daily number of bookings for company HO over the past month. It counts how many bookings started on each date within the last month, groups the results by each date, and sorts them in chronological order. The output shows the booking date and the corresponding number of bookings for that day, allowing you to see how booking activity has changed over time.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves the daily number of bookings for company HO over the past month. It counts how many bookings started on each date within the last month, groups the results by each date, and sorts them in chronological order. The output shows the booking date and the corresponding number of bookings for that day, allowing you to see how booking activity has changed over time.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Past Month</h4><p>The query selects records from the vwAllocations01 table where the CompanyID is 'HO' and the StartDate is within the last month (from one month ago up to today).</p><h4>Step 2 - Group and Count Bookings by Date</h4><p>It groups the filtered bookings by the StartDate (formatted as YYYY-MM-DD) and counts the number of bookings for each date.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by date in ascending order, and up to 10,000 rows are returned.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when bookings started (formatted as YYYY-MM-DD)</td></tr><tr><td>BookingCount</td><td>The number of bookings that started on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The final output is a list of dates from the past month, each with the total number of bookings for company HO on that day. This allows you to observe trends, such as increases or decreases in daily bookings over the past month.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>CONVERT(varchar(10), StartDate, 120), COUNT(*)</td><td>Choose booking date and count of bookings</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of booking data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate in past month</td><td>Filter for company HO and recent bookings</td></tr><tr><td>GROUP BY</td><td>CONVERT(varchar(10), StartDate, 120)</td><td>Aggregate bookings by date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sort results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limit number of rows returned</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show the overall trend of bookings for company HO over the past month
web: N
executed: Y
execution_time: 4.0
question_normalized: show_the_overall_trend_of_bookings_for_company_ho_over_the_past_month
created_at: 2026-05-19 09:08:19
updated_at: 2026-05-19 09:08:20
sql:
  SELECT
      StartDate,
      COUNT(*) AS BookingCount
  FROM
      vwAllocations01
  WHERE
      CompanyID = 'HO'
      AND StartDate >= DATEADD(month, -1, CAST(GETDATE() AS date))
      AND StartDate <= CAST(GETDATE() AS date)
  GROUP BY
      StartDate
  ORDER BY
      StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['BookingCount'].tolist(),
              'type': 'line',
              'name': 'Booking Count'
          }
      ],
      'layout': {
          'title': 'Overall Trend of Bookings for Company HO Over the Past Month',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'BookingCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show the overall trend of bookings for company HO over the past month", "summary": "This query retrieves the daily number of bookings made by company HO over the past month. It counts how many bookings started on each date within the last month, groups the results by each start date, and sorts them in chronological order. The output shows the booking date and the corresponding number of bookings for that day, limited to the first 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows how many bookings company HO made each day over the past month. It provides a day-by-day count of bookings, helping to visualize booking trends for the company during this period.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Past Month</h4><p>The query selects records from the <strong>vwAllocations01</strong> table where the <strong>CompanyID</strong> is 'HO' and the <strong>StartDate</strong> falls within the last month up to today.</p><h4>Step 2 - Count Bookings Per Day</h4><p>It groups the filtered bookings by <strong>StartDate</strong> and counts the number of bookings for each date.</p><h4>Step 3 - Sort and Limit Results</h4><p>The results are sorted by <strong>StartDate</strong> in chronological order and limited to 10,000 rows.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date when bookings started</td></tr><tr><td>BookingCount</td><td>The number of bookings that began on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past month, each with the total number of bookings made by company HO on that day. This allows you to see booking trends over time.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>StartDate, COUNT(*) AS BookingCount</td><td>Chooses the booking date and counts bookings per day</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the bookings data view</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate >= DATEADD(month, -1, CAST(GETDATE() AS date)), StartDate <= CAST(GETDATE() AS date)</td><td>Filters for company HO and bookings in the last month</td></tr><tr><td>GROUP BY</td><td>StartDate</td><td>Groups bookings by date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sorts results by date</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits the output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show overall trend of bookings for company HO over the past month.
web: N
executed: Y
execution_time: 8.0
question_normalized: show_overall_trend_of_bookings_for_company_ho_over_the_past_month.
created_at: 2026-05-19 09:08:50
updated_at: 2026-05-19 09:08:58
sql:
  SELECT
      CAST([StartDate] AS date) AS StartDate,
      COUNT(*) AS BookingCount
  FROM vwAllocations01
  WHERE
      [CompanyID] = 'HO'
      AND CAST([StartDate] AS date) >= DATEADD(month, -1, CAST(GETDATE() AS date))
      AND CAST([StartDate] AS date) <= CAST(GETDATE() AS date)
  GROUP BY CAST([StartDate] AS date)
  ORDER BY StartDate
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['StartDate'].tolist(),
              'y': df['BookingCount'].tolist(),
              'type': 'line',
              'name': 'Bookings'
          }
      ],
      'layout': {
          'title': 'Overall Trend of Bookings for Company HO Over the Past Month',
          'xaxis': {'title': 'StartDate'},
          'yaxis': {'title': 'BookingCount'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show overall trend of bookings for company HO over the past month.", "summary": "This query retrieves the daily count of bookings for company HO from the vwAllocations01 view over the past month. It filters records where the CompanyID is 'HO' and the StartDate falls within the last month up to today. The results are grouped by each date and sorted in chronological order, showing up to 10,000 rows. The output includes the booking date and the number of bookings on each date, which helps visualize the trend in bookings for company HO over the past month.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query shows how many bookings were made each day for company HO over the past month. It helps track the daily trend in bookings.</p><hr><h4>Step 1 - Filter Bookings for Company HO in the Past Month</h4><p>The query selects records from the vwAllocations01 view where the CompanyID is 'HO' and the StartDate is within the last month up to today.</p><h4>Step 2 - Group and Count Bookings by Date</h4><p>For each date, it counts the number of bookings and lists them in order from earliest to latest date.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>StartDate</td><td>The date of the booking</td></tr><tr><td>BookingCount</td><td>The number of bookings made on that date</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of dates from the past month and the number of bookings for company HO on each date, showing the overall trend in bookings.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>CAST([StartDate] AS date), COUNT(*)</td><td>Choose booking date and count of bookings</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of booking data</td></tr><tr><td>WHERE</td><td>CompanyID = 'HO', StartDate in past month</td><td>Filter for company HO and recent bookings</td></tr><tr><td>GROUP BY</td><td>CAST([StartDate] AS date)</td><td>Aggregate bookings by date</td></tr><tr><td>ORDER BY</td><td>StartDate</td><td>Sort results by date</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limit output to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show total completed trips for May 2026.
web: N
executed: Y
execution_time: 11.0
question_normalized: show_total_completed_trips_for_may_2026.
created_at: 2026-05-19 09:09:48
updated_at: 2026-05-19 09:09:55
sql:
  SELECT TOP 10000 COUNT(*) AS TotalCompletedTrips
  FROM vwAllocations01
  WHERE StartDate >= '2026-05-01'
    AND StartDate < '2026-06-01'
    AND FinishDateTime IS NOT NULL;

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalCompletedTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Completed Trips'
          }
      ],
      'layout': {
          'title': 'Total Completed Trips for May 2026',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalCompletedTrips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show total completed trips for May 2026.", "summary": "This query counts the total number of completed trips that started in May 2026. It looks at the vwAllocations01 view, filtering for trips with a StartDate between May 1, 2026 and before June 1, 2026, and only includes trips where the FinishDateTime is not empty (meaning the trip was completed). The output is a single number labeled as TotalCompletedTrips, representing the total completed trips for that month.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total number of trips that were completed and started during May 2026. It only includes trips that have a recorded finish time, indicating completion.</p><hr><h3>The Final Output</h3><p>The result is a single value showing the total number of completed trips that began in May 2026.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(*) AS TotalCompletedTrips</td><td>Counts total completed trips</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Source of trip data</td></tr><tr><td>WHERE</td><td>StartDate &gt;= '2026-05-01' AND StartDate &lt; '2026-06-01' AND FinishDateTime IS NOT NULL</td><td>Filters for trips started in May 2026 and completed</td></tr><tr><td>TOP</td><td>10000</td><td>Limits maximum rows returned (not relevant here since only one row is expected)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show total completed trips for 2026, broken down by month and by company.
chart: N
web: N
executed: Y
execution_time: 52.0
question_normalized: show_total_completed_trips_for_2026,_broken_down_by_month_and_by_company.
created_at: 2026-05-19 09:12:10
updated_at: 2026-05-19 09:12:17
sql:
  SELECT
      CompanyID,
      YEAR(StartDate) AS Year,
      MONTH(StartDate) AS Month,
      COUNT(*) AS TotalCompletedTrips
  FROM
      vwAllocations01
  WHERE
      StartDate >= '2026-01-01'
      AND StartDate < '2027-01-01'
  GROUP BY
      CompanyID,
      YEAR(StartDate),
      MONTH(StartDate)
  ORDER BY
      CompanyID,
      Year,
      Month
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show total completed trips for 2026, broken down by month and by company.", "summary": "This query calculates the total number of completed trips for each company in the year 2026, with results grouped by both company and month. It uses the vwAllocations01 table, focusing only on trips that started between January 1, 2026 and December 31, 2026. The output lists each company, the year, the month, and the corresponding count of completed trips, sorted by company, year, and month. The query limits the output to the first 10,000 rows.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many trips were completed by each company in every month of 2026. It looks at the vwAllocations01 table and only includes trips that started during the year 2026. The results are grouped by company and by month, showing the total number of completed trips for each combination.</p><hr><h4>What it shows | What it means</h4><table><thead><tr><th>Column</th><th>What it means</th></tr></thead><tbody><tr><td>CompanyID</td><td>The unique identifier for each company.</td></tr><tr><td>Year</td><td>The year of the trip start date (always 2026 here).</td></tr><tr><td>Month</td><td>The month of the trip start date (1 for January, 2 for February, etc.).</td></tr><tr><td>TotalCompletedTrips</td><td>The total number of completed trips for that company and month.</td></tr></tbody></table><h3>The Final Output</h3><p>The final output is a list showing, for each company and each month in 2026, how many trips they completed. The list is sorted by company, year, and month, and only the first 10,000 results are shown.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>CompanyID, YEAR(StartDate), MONTH(StartDate), COUNT(*)</td><td>Chooses company, year, month, and trip count to display.</td></tr><tr><td>FROM</td><td>vwAllocations01</td><td>Uses the trip allocations data.</td></tr><tr><td>WHERE</td><td>StartDate >= '2026-01-01' AND StartDate < '2027-01-01'</td><td>Filters trips to only those starting in 2026.</td></tr><tr><td>GROUP BY</td><td>CompanyID, YEAR(StartDate), MONTH(StartDate)</td><td>Groups results by company and month.</td></tr><tr><td>ORDER BY</td><td>CompanyID, Year, Month</td><td>Sorts the results by company, year, and month.</td></tr><tr><td>OFFSET/FETCH</td><td>OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits output to the first 10,000 rows.</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me total rides for HO
web: N
executed: Y
execution_time: 7.0
question_normalized: show_me_total_rides_for_ho
created_at: 2026-05-19 09:31:17
updated_at: 2026-05-19 09:31:22
sql:
  SELECT TOP 10000 COUNT(*) AS TotalRides
  FROM PrivateHires
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  WHERE Bases.Base = 'HO';

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalRides'].tolist(),
              'type': 'bar',
              'name': 'Total Rides'
          }
      ],
      'layout': {
          'title': 'Total Rides for HO',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalRides'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me total rides for HO", "summary": "This query calculates the total number of rides associated with the base named 'HO'. It does this by counting all records in the PrivateHires table that are linked to the Bases table where the base name is 'HO'. The result is a single number representing the total rides for this specific base.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many rides have been recorded for the base called 'HO' by counting all matching ride records in the PrivateHires table that are linked to this base.</p><hr><h3>The Final Output</h3><p>The output is a single number showing the total rides for the 'HO' base.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(*) AS TotalRides</td><td>Counts total rides</td></tr><tr><td>FROM</td><td>PrivateHires</td><td>Main table of ride records</td></tr><tr><td>INNER JOIN</td><td>Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo</td><td>Links rides to their base</td></tr><tr><td>WHERE</td><td>Bases.Base = 'HO'</td><td>Filters for base named 'HO'</td></tr><tr><td>TOP</td><td>10000</td><td>Limits output to 10,000 rows (not needed here since only one row is returned)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me total rides for HO for March 2026.
web: N
executed: Y
execution_time: 11.0
question_normalized: show_me_total_rides_for_ho_for_march_2026.
created_at: 2026-05-19 09:31:39
updated_at: 2026-05-19 09:31:46
sql:
  SELECT TOP 10000 COUNT(DISTINCT PrivateHires.PrivateHireID) AS TotalRides
  FROM Invoices
  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE Invoices.[Type] IN ('CR', 'IN')
    AND Bases.Base = 'HO'
    AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
    AND PrivateHireMovements.PickupDateTime < '2026-04-01';

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalRides'].tolist(),
              'type': 'bar',
              'name': 'Total Rides'
          }
      ],
      'layout': {
          'title': 'Total Rides for HO for March 2026',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalRides'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me total rides for HO for March 2026.", "summary": "This query calculates the total number of unique private hire rides that started from the 'HO' base during March 2026. It does this by joining several tables related to invoices, private hire movements, and base information, and then counting the distinct PrivateHireID values. The query filters for invoices of type 'CR' or 'IN', ensures the base is 'HO', and only includes rides with a pickup date in March 2026. The result is a single number representing the total rides for the specified criteria.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query counts the total number of unique private hire rides that started from the 'HO' base during March 2026. It only includes rides linked to invoices of type 'CR' or 'IN' and considers rides with pickup dates within March 2026.</p><hr><h3>The Final Output</h3><p>The output is a single value showing the total number of distinct rides for the 'HO' base in March 2026.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(DISTINCT PrivateHires.PrivateHireID) AS TotalRides</td><td>Counts unique rides</td></tr><tr><td>FROM / JOIN</td><td>Invoices, InvoicePrivateHireMovements, InvoicePrivateHireDetails, PrivateHireMovements, PrivateHires, Bases, NominalCodes</td><td>Links related ride, invoice, and base data</td></tr><tr><td>WHERE</td><td>Invoices.[Type] IN ('CR', 'IN')</td><td>Filters for relevant invoice types</td></tr><tr><td>WHERE</td><td>Bases.Base = 'HO'</td><td>Filters for the 'HO' base</td></tr><tr><td>WHERE</td><td>PrivateHireMovements.PickupDateTime &gt;= '2026-03-01' AND &lt; '2026-04-01'</td><td>Limits rides to March 2026</td></tr><tr><td>TOP</td><td>10000</td><td>Limits output to 10,000 rows (not needed here, as only one row is expected)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show a list of trips.
chart: N
web: N
executed: Y
execution_time: 12.0
question_normalized: show_a_list_of_trips.
sql_query_summaries: []
created_at: 2026-05-19 09:33:45
updated_at: 2026-05-19 09:33:55
sql:
  SELECT 
      'P ' + LTRIM(STR(PrivateHires.PrivateHireID)) + '/' + LTRIM(STR(PrivateHireMovements.PrivateHireMovementID)) AS ResNumber,
      SUM(CASE WHEN NominalCodes.Description = 'Gratuity' THEN InvoicePrivateHireDetails.Total ELSE 0.0 END) AS GratuityTotal,
      SUM(InvoicePrivateHireDetails.VAT) AS TaxesTotal,
      SUM(InvoicePrivateHireDetails.Total) AS Segmenttotal,
      Bases.Base AS ServiceAreaCode,
      Bases.Base AS Pickup_State
  FROM 
      Invoices
      INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
      INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
      INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE 
      Invoices.[Type] IN ('CR', 'IN')
  GROUP BY 
      PrivateHires.PrivateHireID, 
      PrivateHireMovements.PrivateHireMovementID, 
      Bases.Base, 
      InvoicePrivateHireDetails.TransactionDate, 
      PrivateHireMovements.PickupDateTime, 
      InvoicePrivateHireDetails.NominalCode
  ORDER BY 
      ResNumber
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 4
question: what is the total affiliate revenue for March 2026
web: N
executed: Y
execution_time: 19.0
question_normalized: what_is_the_total_affiliate_revenue_for_march_2026
sql_query_summaries: []
created_at: 2026-05-19 09:39:20
updated_at: 2026-05-19 09:39:31
sql:
  SELECT TOP 10000 
      SUM((ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0)) AS TotalAffiliateRevenue
  FROM 
      PrivateHireMovements
      INNER JOIN (
          SELECT DISTINCT InvoicePrivateHireMovements.PrivateHireMovementID, InvoicePrivateHireMovements.PrivateHireID
          FROM Invoices
          INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
          UNION
          SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID, PrivateHireMovements.PrivateHireID
          FROM Invoices
          INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
          INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
          UNION
          SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID, PrivateHireMovements.PrivateHireID
          FROM Invoices
          INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
          INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
      ) InvoicePrivateHireDetails 
          ON InvoicePrivateHireDetails.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID 
          AND InvoicePrivateHireDetails.PrivateHireID = PrivateHireMovements.PrivateHireID
      INNER JOIN PrivateHires ON InvoicePrivateHireDetails.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              DriverId, 
              (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
              dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
              + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
              + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
              + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0 AND ActualDriverType = 'Affiliate'
      ) PrivateHireDrivers 
          ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      INNER JOIN (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              COUNT(DriverId) AS Driver_Count
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0
          GROUP BY PrivateHireMovementId, PrivateHireVehicleId
      ) DC 
          ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
          AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  WHERE 
      PrivateHireMovements.StartDateTime >= '2026-03-01'
      AND PrivateHireMovements.StartDateTime < '2026-04-01';

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalAffiliateRevenue'].tolist(),
              'type': 'bar',
              'name': 'Total Affiliate Revenue'
          }
      ],
      'layout': {
          'title': 'Total Affiliate Revenue for March 2026',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalAffiliateRevenue'}
      }
  }


user_id: 1
agent_id: 4
question: What is the total affiliate revenue for March 2026 for HO?
web: N
executed: Y
execution_time: 11.0
question_normalized: what_is_the_total_affiliate_revenue_for_march_2026_for_ho?
sql_query_summaries: []
created_at: 2026-05-19 09:40:36
updated_at: 2026-05-19 09:40:45
sql:
  SELECT 
      Bases.Base AS ServiceAreaCode,
      SUM((ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0)) AS Total_Affiliate_Revenue
  FROM 
      PrivateHireMovements
      INNER JOIN PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      INNER JOIN (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              DriverId, 
              (ISNULL(Total, 0.0)) AS Affiliate_Revenue, 
              dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType) 
                  + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom) 
                  + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom) 
                  + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0 AND ActualDriverType = 'Affiliate'
      ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      LEFT OUTER JOIN (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              COUNT(DriverId) AS Driver_Count
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0
          GROUP BY PrivateHireMovementId, PrivateHireVehicleId
      ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
  WHERE 
      Bases.Base = 'HO'
      AND PrivateHireMovements.StartDateTime >= '2026-03-01'
      AND PrivateHireMovements.StartDateTime < '2026-04-01'
  GROUP BY 
      Bases.Base
  ORDER BY 
      Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['ServiceAreaCode'].tolist(),
              'y': df['Total_Affiliate_Revenue'].tolist(),
              'type': 'bar',
              'name': 'Total Affiliate Revenue'
          }
      ],
      'layout': {
          'title': 'Total Affiliate Revenue for March 2026 for HO by Service Area',
          'xaxis': {'title': 'ServiceAreaCode'},
          'yaxis': {'title': 'Total_Affiliate_Revenue'}
      }
  }


user_id: 1
agent_id: 4
question: What is the total affiliate revenue for March 2026 by city?
web: N
executed: Y
execution_time: 21.0
question_normalized: what_is_the_total_affiliate_revenue_for_march_2026_by_city?
sql_query_summaries: []
created_at: 2026-05-19 09:41:22
updated_at: 2026-05-19 09:41:32
sql:
  SELECT 
      Bases.Base AS City,
      SUM(ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00) / ISNULL(DC.Driver_Count, 1.0)) AS Total_Affiliate_Revenue
  FROM 
      PrivateHireMovements
  INNER JOIN 
      PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN 
      Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN 
      (SELECT 
           PrivateHireMovementId, 
           PrivateHireVehicleId, 
           DriverId, 
           (ISNULL(Total, 0.0)) AS Affiliate_Revenue, 
           dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType) 
               + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom) 
               + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom) 
               + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue,
           ActualDriverType,
           Cancelled,
           MovementCancelled
       FROM AvalonReporting.dbo.vwPrivateHireDrivers
      ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
                           AND ISNULL(PrivateHireDrivers.Cancelled, 0) = 0
                           AND ISNULL(PrivateHireDrivers.MovementCancelled, 0) = 0
                           AND PrivateHireDrivers.ActualDriverType = 'Affiliate'
  INNER JOIN 
      (SELECT 
           PrivateHireMovementId, 
           PrivateHireVehicleId, 
           COUNT(DriverId) AS Driver_Count
       FROM AvalonReporting.dbo.vwPrivateHireDrivers
       WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0
       GROUP BY PrivateHireMovementId, PrivateHireVehicleId
      ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
          AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
  WHERE 
      PrivateHireMovements.StartDateTime >= '2026-03-01'
      AND PrivateHireMovements.StartDateTime < '2026-04-01'
  GROUP BY 
      Bases.Base
  ORDER BY 
      Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['Total_Affiliate_Revenue'].tolist(),
              'type': 'bar',
              'name': 'Total Affiliate Revenue'
          }
      ],
      'layout': {
          'title': 'Total Affiliate Revenue for March 2026 by City',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'Total Affiliate Revenue'}
      }
  }


user_id: 1
agent_id: 4
question: what is the total affiliate revenue for 2026 by city by month
chart: N
web: N
executed: N
execution_time: 17.0
question_normalized: what_is_the_total_affiliate_revenue_for_2026_by_city_by_month
created_at: 2026-05-19 10:01:18
updated_at: 2026-05-19 10:01:18
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (207, b"Invalid column name 'Affiliate_Total_Revenue'.DB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT 
      Bases.Base AS ServiceAreaCode,
      YEAR(PrivateHireMovements.StartDateTime) AS Year,
      MONTH(PrivateHireMovements.StartDateTime) AS Month,
      SUM(ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00) / ISNULL(DC.Driver_Count, 1.0)) AS Affiliate_Revenue
  FROM 
      PrivateHireMovements
  INNER JOIN 
      PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN 
      Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN 
      (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              DriverId, 
              (ISNULL(Total, 0.0)) AS Affiliate_Revenue, 
              Affiliate_Total_Revenue
          FROM 
              AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE 
              ISNULL(Cancelled, 0) = 0 
              AND ISNULL(MovementCancelled, 0) = 0 
              AND ActualDriverType = 'Affiliate'
      ) PrivateHireDrivers 
          ON PrivateHireDrivers.PrivateHireMovementId = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN 
      (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              COUNT(DriverId) AS Driver_Count
          FROM 
              AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE 
              ISNULL(Cancelled, 0) = 0 
              AND ISNULL(MovementCancelled, 0) = 0
          GROUP BY 
              PrivateHireMovementId, PrivateHireVehicleId
      ) DC 
          ON PrivateHireDrivers.PrivateHireMovementId = DC.PrivateHireMovementId 
          AND PrivateHireDrivers.PrivateHireVehicleId = DC.PrivateHireVehicleId
  WHERE 
      YEAR(PrivateHireMovements.StartDateTime) = 2026
  GROUP BY 
      Bases.Base, YEAR(PrivateHireMovements.StartDateTime), MONTH(PrivateHireMovements.StartDateTime)
  ORDER BY 
      Bases.Base, Year, Month
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: What is the total affiliate revenue for each month in 2026 by city?
chart: N
web: N
executed: N
execution_time: 15.0
question_normalized: what_is_the_total_affiliate_revenue_for_each_month_in_2026_by_city?
created_at: 2026-05-19 10:02:06
updated_at: 2026-05-19 10:02:06
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (207, b"Invalid column name 'Affiliate_Total_Revenue'.DB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT 
      YEAR(PrivateHireMovements.StartDateTime) AS Year,
      MONTH(PrivateHireMovements.StartDateTime) AS Month,
      Bases.Base AS City,
      SUM(ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00) / ISNULL(DC.Driver_Count, 1.0)) AS TotalAffiliateRevenue
  FROM 
      PrivateHireMovements
      INNER JOIN PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      INNER JOIN (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              DriverId, 
              ISNULL(Total, 0.0) AS Affiliate_Revenue, 
              Affiliate_Total_Revenue,
              ActualDriverType, 
              Cancelled, 
              MovementCancelled
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0 AND ActualDriverType = 'Affiliate'
      ) AS PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementId = PrivateHireMovements.PrivateHireMovementID
      LEFT OUTER JOIN (
          SELECT 
              PrivateHireMovementId, 
              PrivateHireVehicleId, 
              COUNT(DriverId) AS Driver_Count
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0
          GROUP BY PrivateHireMovementId, PrivateHireVehicleId
      ) AS DC ON PrivateHireDrivers.PrivateHireMovementId = DC.PrivateHireMovementId AND PrivateHireDrivers.PrivateHireVehicleId = DC.PrivateHireVehicleId
  WHERE 
      YEAR(PrivateHireMovements.StartDateTime) = 2026
  GROUP BY 
      YEAR(PrivateHireMovements.StartDateTime),
      MONTH(PrivateHireMovements.StartDateTime),
      Bases.Base
  ORDER BY 
      Year,
      Month,
      City
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: show me total affiliate trips for each City for March 2026
web: N
executed: Y
execution_time: 14.0
question_normalized: show_me_total_affiliate_trips_for_each_city_for_march_2026
created_at: 2026-05-22 14:15:02
updated_at: 2026-05-22 14:15:08
sql:
  SELECT 
      Bases.Base AS City,
      COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID) AS TotalAffiliateTrips
  FROM PrivateHireMovements
  INNER JOIN PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  WHERE 
      AvalonReporting.dbo.vwPrivateHireDrivers.ActualDriverType = 'Affiliate'
      AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
      AND PrivateHireMovements.PickupDateTime < '2026-04-01'
  GROUP BY 
      Bases.Base
  ORDER BY 
      Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['TotalAffiliateTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Affiliate Trips'
          }
      ],
      'layout': {
          'title': 'Total Affiliate Trips for Each City for March 2026',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'Total Affiliate Trips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me total affiliate trips for each City for March 2026", "summary": "This query calculates the total number of affiliate trips for each city during March 2026. It does this by counting unique trip records (PrivateHireMovementID) where the driver type is 'Affiliate' and the pickup date falls within March 2026. The results are grouped by city and sorted alphabetically, with a maximum of 10,000 rows returned.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many affiliate trips took place in each city during March 2026. It counts unique trip records where the driver was marked as an affiliate and the trip happened between March 1 and March 31, 2026. The results are grouped by city and sorted alphabetically.</p><hr><h4>Step 1 - Filter for Affiliate Trips in March 2026</h4><p>The query looks for trips where the driver type is 'Affiliate' and the pickup date is between March 1, 2026 and March 31, 2026 (not including April 1).</p><h4>Step 2 - Count Trips by City</h4><p>It joins several tables to match trips to their respective cities, then counts the number of unique trips for each city.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>City</td><td>The name of the city where the trip started</td></tr><tr><td>TotalAffiliateTrips</td><td>The total number of unique affiliate trips in that city during March 2026</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of cities, each with the total number of affiliate trips that occurred there in March 2026, sorted by city name.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>Bases.Base, COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID)</td><td>Choose city and count of unique affiliate trips</td></tr><tr><td>FROM / JOIN</td><td>PrivateHireMovements, PrivateHires, Bases, vwPrivateHireDrivers</td><td>Combine trip, hire, city, and driver info</td></tr><tr><td>WHERE</td><td>ActualDriverType = 'Affiliate', PickupDateTime between '2026-03-01' and '2026-04-01'</td><td>Filter for affiliate trips in March 2026</td></tr><tr><td>GROUP BY</td><td>Bases.Base</td><td>Summarize by city</td></tr><tr><td>ORDER BY</td><td>Bases.Base</td><td>Sort results alphabetically by city</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS ONLY</td><td>Limit results to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show me the total affiliate trips amount for each city for March 2026.
web: N
executed: Y
execution_time: 29.0
question_normalized: show_me_the_total_affiliate_trips_amount_for_each_city_for_march_2026.
sql_query_summaries: []
created_at: 2026-05-22 14:16:27
updated_at: 2026-05-22 14:16:33
sql:
  SELECT 
      Bases.Base AS City,
      SUM(
          (
              ISNULL(
                  dbo.VehicleRevenuePrice(
                      AvalonReporting.dbo.vwPrivateHireDrivers.Price, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.Seats, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.VehicleType
                  ), 
                  0.0
              )
              + ISNULL(
                  dbo.ExtrasRevenue(
                      AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom
                  ), 
                  0.0
              )
              + ISNULL(
                  dbo.ClientDiscountRevenue(
                      AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom
                  ),
                  0.0
              )
              + ISNULL(
                  dbo.VehicleTypeSurchargeRevenue(
                      AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.VehicleTypeSurchargePrice, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, 
                      AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom
                  ),
                  0.0
              )
          ) / ISNULL(DC.Driver_Count, 1.0)
      ) AS TotalAffiliateAmount
  FROM PrivateHireMovements
  INNER JOIN InvoicePrivateHireMovements 
      ON PrivateHireMovements.PrivateHireMovementID = InvoicePrivateHireMovements.PrivateHireMovementID
  INNER JOIN Invoices 
      ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers 
      ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires 
      ON PrivateHires.PrivateHireID = PrivateHireMovements.PrivateHireID
  INNER JOIN InvoicePrivateHireDetails 
      ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = InvoicePrivateHireMovements.InvoicePrivateHireMovementID
  INNER JOIN Clients 
      ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN Bases 
      ON Bases.BaseSerialNo = PrivateHires.BaseSerialNo
  LEFT OUTER JOIN (
      SELECT 
          PrivateHireMovementId, 
          PrivateHireVehicleId, 
          COUNT(DriverId) AS Driver_Count
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled,0)=0 
        AND ISNULL(MovementCancelled,0)=0
      GROUP BY PrivateHireMovementId, PrivateHireVehicleId
  ) DC 
      ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementId 
      AND AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleId
  WHERE 
      Invoices.[Type] IN ('CR', 'IN')
      AND ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.Cancelled, 0) = 0
      AND ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.MovementCancelled, 0) = 0
      AND AvalonReporting.dbo.vwPrivateHireDrivers.ActualDriverType = 'Affiliate'
      AND InvoicePrivateHireMovements.InvoiceNo IS NOT NULL
      AND YEAR(InvoicePrivateHireDetails.TransactionDate) = 2026
      AND MONTH(InvoicePrivateHireDetails.TransactionDate) = 3
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['TotalAffiliateAmount'].tolist(),
              'type': 'bar',
              'name': 'Total Affiliate Trips Amount'
          }
      ],
      'layout': {
          'title': 'Total Affiliate Trips Amount by City for March 2026',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'TotalAffiliateAmount'}
      }
  }


user_id: 1
agent_id: 4
question: Show me total trips, total value, gratuity, and taxes along with Affiliateid for March 2026.
chart: N
web: N
executed: N
execution_time: 69.0
question_normalized: show_me_total_trips,_total_value,_gratuity,_and_taxes_along_with_affiliateid_for_march_2026.
created_at: 2026-05-22 14:20:42
updated_at: 2026-05-22 14:20:42
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (102, b"Incorrect syntax near ')'.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT DISTINCT InvoicePrivateHireMovements.PrivateHireMovementID, 
                              InvoicePrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
          ) PrivateId ON PrivateId.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
              AND PrivateId.PrivateHireID = PrivateHireMovements.PrivateHireID
          INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          INNER JOIN PrivateHires ON PrivateId.PrivateHireID = PrivateHires.PrivateHireID 
          INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
          INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
          INNER JOIN (
              SELECT PrivateHireMovementId, PrivateHireVehicleId, DriverId,
                     (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
                     dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
                     + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom) + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                     + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                AND ISNULL(MovementCancelled, 0) = 0
                AND ActualDriverType = 'Affiliate'
          ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          LEFT OUTER JOIN (
              SELECT PrivateHireMovementId, PrivateHireVehicleId, Count(DriverId) AS Driver_Count
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                AND ISNULL(MovementCancelled, 0) = 0
              GROUP BY PrivateHireMovementId, PrivateHireVehicleId
          ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
              AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
          LEFT OUTER JOIN (
              SELECT PrivateHireMovementId,
                     CASE WHEN IsNull(B.Total_Count, 0) = 0
                          THEN Total_Extras ELSE Total_Extras / Total_Count END AS Extras
              FROM (
                  SELECT PrivateHireMovementId,
                         SUM(Total) AS Total_Extras,
                         (SELECT COUNT(DISTINCT PrivateHireVehicleId) 
                          FROM AvalonReporting.dbo.vwPrivateHireDrivers
                          WHERE ISNULL(Cancelled, 0) = 0 
                            AND ISNULL(MovementCancelled, 0) = 0 
                            AND vwPrivateHireDrivers.PrivateHireMovementID = vwPrivateHireExtras.PrivateHireMovementID) AS Total_Count
                  FROM AvalonReporting.dbo.[vwPrivateHireExtras]
                  WHERE VehicleRevenue = 1 AND Quantity > 0
                  GROUP BY PrivateHireMovementId
              ) B
          ) Extras ON PrivateHireDrivers.PrivateHireMovementID = Extras.PrivateHireMovementId
          INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
          INNER JOIN Invoices ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
      WHERE InvoicePrivateHireDetails.TransactionDate >= '2026-03-01'
        AND InvoicePrivateHireDetails.TransactionDate < '2026-04-01'
        AND Invoices.[Type] IN ('CR', 'IN')
        AND PrivateHireDrivers.DriverId IS NOT NULL

      UNION ALL

      -- CONTRACT AFFILIATE REVENUE SEGMENT
      SELECT
          Drivers.DriverId AS AffiliateCode,
          'C ' + LTRIM(STR(Contracts.ContractID)) + ISNULL('/' + LTRIM(STR(ContractMovements.ContractMovementID)), '') AS ResNumber,
          0.0 AS GratuityTotal,
          0.0 AS TaxesTotal,
          0.0 AS Segmenttotal
      FROM ContractDates 
          INNER JOIN ContractVehicles ON ContractVehicles.ContractMovementID = ContractDates.ContractMovementID
          INNER JOIN ContractDrivers ON ContractDrivers.ContractVehicleID = ContractVehicles.ContractVehicleID
          INNER JOIN ContractDriverAllocations ON ContractDriverAllocations.ContractDriverID = ContractDrivers.ContractDriverID
          INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID 
                                AND ContractDates.StartDate = ContractDriverAllocations.StartDate
          INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID 
          INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
          INNER JOIN (SELECT DISTINCT ContractMovementID, DriverID, DriverName, Salutation FROM vwContractDriverData) vwContractDriverData ON vwContractDriverData.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
          LEFT OUTER JOIN ContractVehicleAllocations ON ContractVehicles.ContractVehicleID = ContractVehicleAllocations.ContractVehicleID
                                AND ContractDates.StartDate = ContractVehicleAllocations.StartDate
      WHERE Drivers.DriverType = 'Affiliate'
        AND ContractDates.Invoice = 1
        AND InvoiceContractPassengerDetails.TransactionDate >= '2026-03-01'
        AND InvoiceContractPassengerDetails.TransactionDate < '2026-04-01'
  ) AS AffiliateTrips
  GROUP BY AffiliateCode
  ORDER BY AffiliateCode
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: Show me total trips and total affiliate revenue by each city for March 2026.
chart: N
web: N
executed: N
execution_time: 22.0
question_normalized: show_me_total_trips_and_total_affiliate_revenue_by_each_city_for_march_2026.
created_at: 2026-05-22 14:27:53
updated_at: 2026-05-22 14:27:53
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (207, b"Invalid column name 'Affiliate_Revenue'.DB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT 
      Bases.Base AS City,
      COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID) AS TotalTrips,
      SUM(ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.Affiliate_Revenue, 0.00) / ISNULL(DC.Driver_Count, 1.0)) AS TotalAffiliateRevenue
  FROM PrivateHires
  INNER JOIN PrivateHireMovements ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN InvoicePrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = InvoicePrivateHireMovements.InvoicePrivateHireMovementID
  INNER JOIN Invoices ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  LEFT JOIN (
      SELECT 
          PrivateHireMovementID, 
          PrivateHireVehicleID, 
          COUNT(DriverID) AS Driver_Count
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled, 0) = 0
        AND ISNULL(MovementCancelled, 0) = 0
      GROUP BY PrivateHireMovementID, PrivateHireVehicleID
  ) DC 
      ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID
      AND AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
  WHERE 
      Invoices.[Type] IN ('CR', 'IN')
      AND ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.Cancelled, 0) = 0
      AND ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.MovementCancelled, 0) = 0
      AND AvalonReporting.dbo.vwPrivateHireDrivers.ActualDriverType = 'Affiliate'
      AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
      AND PrivateHireMovements.PickupDateTime < '2026-04-01'
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: show me total trips, total affiliate revenue by each city for March 2026
chart: N
web: N
executed: Y
execution_time: 19.0
question_normalized: show_me_total_trips,_total_affiliate_revenue_by_each_city_for_march_2026
created_at: 2026-05-22 14:33:34
updated_at: 2026-05-22 14:33:39
sql:
  SELECT
      Bases.Base AS City,
      COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID) AS TotalTrips,
      SUM((ISNULL(PrivateHireDrivers.Affiliate_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0)) AS TotalAffiliateRevenue
  FROM PrivateHireMovements
  INNER JOIN (
      SELECT DISTINCT 
          InvoicePrivateHireMovements.PrivateHireMovementID, 
          InvoicePrivateHireMovements.PrivateHireID,
          InvoicePrivateHireMovements.InvoicePrivateHireMovementID
      FROM Invoices 
      INNER JOIN InvoicePrivateHireMovements 
          ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
      UNION
      SELECT DISTINCT 
          PrivateHireMovements.PrivateHireMovementID,
          PrivateHireMovements.PrivateHireID,
          InvoicePrivateHireMovements.InvoicePrivateHireMovementID
      FROM Invoices 
      INNER JOIN InvoicePrivateHireMovements 
          ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
      INNER JOIN PrivateHireMovements 
          ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
      UNION
      SELECT DISTINCT 
          PrivateHireMovements.PrivateHireMovementID,
          PrivateHireMovements.PrivateHireID,
          InvoicePrivateHireMovements.InvoicePrivateHireMovementID
      FROM Invoices 
      INNER JOIN InvoicePrivateHireMovements 
          ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
      INNER JOIN PrivateHireMovements 
          ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
  ) PrivateId 
      ON PrivateId.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      AND PrivateId.PrivateHireID = PrivateHireMovements.PrivateHireID
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers 
      ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires 
      ON PrivateId.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients 
      ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN InvoicePrivateHireDetails 
      ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
  INNER JOIN (
      SELECT 
          PrivateHireMovementId,
          PrivateHireVehicleId,
          DriverId,
          (ISNULL(Total, 0.0)) AS Affiliate_Revenue
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled, 0) = 0
        AND ISNULL(MovementCancelled, 0) = 0
        AND ActualDriverType = 'Affiliate'
  ) PrivateHireDrivers 
      ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN (
      SELECT 
          PrivateHireMovementId,
          PrivateHireVehicleId,
          COUNT(DriverId) AS Driver_Count
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled, 0) = 0
        AND ISNULL(MovementCancelled, 0) = 0
      GROUP BY PrivateHireMovementId, PrivateHireVehicleId
  ) DC 
      ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
      AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
  INNER JOIN Bases 
      ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  WHERE 
      EXISTS (
          SELECT 1
          FROM Invoices 
          WHERE Invoices.InvoiceNo = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
            AND Invoices.[Type] IN ('CR', 'IN')
      )
      AND YEAR(PrivateHireMovements.PickupDateTime) = 2026
      AND MONTH(PrivateHireMovements.PickupDateTime) = 3
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me total trips, total affiliate revenue by each city for March 2026", "summary": "This query calculates the total number of trips and the total affiliate revenue for each city (referred to as 'Base') for the month of March 2026. It does this by joining several tables related to private hire movements, invoices, drivers, and city bases, filtering for trips that occurred in March 2026 and only including relevant invoice types. The affiliate revenue is summed per city, and the number of unique trips is counted, with results grouped and ordered by city name.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query finds out how many private hire trips happened in each city and how much affiliate revenue was earned in each city during March 2026. It uses trip, driver, and invoice data to calculate these totals, focusing only on valid trips and invoices for that month.</p><hr><h4>Step 1 - Identify Relevant Trips and Invoices</h4><p>The query joins several tables to ensure only trips with valid invoice types ('CR', 'IN') are included, and only those that took place in March 2026.</p><h4>Step 2 - Calculate Affiliate Revenue</h4><p>It sums up the affiliate revenue for each trip, dividing by the number of drivers per trip to allocate revenue fairly, and only includes non-cancelled affiliate driver trips.</p><h4>Step 3 - Group and Summarize by City</h4><p>Results are grouped by city (Base), showing the total number of trips and total affiliate revenue for each city.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>City</td><td>Name of the city (Base) where trips originated</td></tr><tr><td>TotalTrips</td><td>Total number of unique trips in March 2026 for that city</td></tr><tr><td>TotalAffiliateRevenue</td><td>Total affiliate revenue earned in March 2026 for that city</td></tr></tbody></table><h3>The Final Output</h3><p>The output is a list of cities, each with the total number of trips and the total affiliate revenue for March 2026, sorted alphabetically by city name. Only the first 10,000 rows are shown if there are more results.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>City, TotalTrips, TotalAffiliateRevenue</td><td>Chooses columns to display</td></tr><tr><td>FROM</td><td>PrivateHireMovements and related joins</td><td>Specifies data sources</td></tr><tr><td>WHERE</td><td>Invoice type ('CR', 'IN'), PickupDateTime March 2026</td><td>Filters for valid trips and invoices in March 2026</td></tr><tr><td>GROUP BY</td><td>Bases.Base</td><td>Groups results by city</td></tr><tr><td>ORDER BY</td><td>Bases.Base</td><td>Sorts results by city name</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS FETCH NEXT 10000 ROWS ONLY</td><td>Limits results to 10,000 rows</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show total trips for HO city in March 2026 where affiliate revenue is greater than zero.
chart: N
web: N
executed: N
execution_time: 12.0
question_normalized: show_total_trips_for_ho_city_in_march_2026_where_affiliate_revenue_is_greater_than_zero.
created_at: 2026-05-22 14:35:48
updated_at: 2026-05-22 14:35:48
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (207, b"Invalid column name 'Affiliate_Revenue'.DB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT
      Bases.Base,
      COUNT(*) AS TotalTrips
  FROM PrivateHires
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN PrivateHireMovements ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE
      Bases.Base = 'HO'
      AND YEAR(PrivateHireMovements.PickupDateTime) = 2026
      AND MONTH(PrivateHireMovements.PickupDateTime) = 3
      AND AvalonReporting.dbo.vwPrivateHireDrivers.Affiliate_Revenue > 0
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: Show total trips for HO city in March 2026.
web: N
executed: Y
execution_time: 9.0
question_normalized: show_total_trips_for_ho_city_in_march_2026.
created_at: 2026-05-22 14:36:22
updated_at: 2026-05-22 14:36:26
sql:
  SELECT TOP 10000 
      COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID) AS TotalTrips
  FROM PrivateHires
  INNER JOIN PrivateHireMovements ON PrivateHires.PrivateHireID = PrivateHireMovements.PrivateHireID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN InvoicePrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN Invoices ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  WHERE Bases.Base = 'HO'
    AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
    AND PrivateHireMovements.PickupDateTime < '2026-04-01'
    AND Invoices.[Type] IN ('CR', 'IN');

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'TotalTrips'
          }
      ],
      'layout': {
          'title': 'Total Trips for HO city in March 2026',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalTrips'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show total trips for HO city in March 2026.", "summary": "This query calculates the total number of unique private hire trips that started in the city labeled 'HO' during March 2026. It combines data from several tables to ensure only trips with valid invoices of type 'CR' or 'IN' are counted, and only those with pickup dates in March 2026 are included.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query counts the total number of unique private hire trips that began in the city labeled 'HO' during March 2026. It only includes trips that have a related invoice of type 'CR' or 'IN'.</p><hr><h3>The Final Output</h3><p>The result is a single number showing how many distinct private hire trips started in 'HO' city in March 2026, filtered to include only those with the specified invoice types.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID) AS TotalTrips</td><td>Counts unique trips</td></tr><tr><td>FROM / JOIN</td><td>PrivateHires, PrivateHireMovements, Bases, InvoicePrivateHireMovements, Invoices</td><td>Combines trip, base, and invoice data</td></tr><tr><td>WHERE</td><td>Bases.Base = 'HO'</td><td>Limits to 'HO' city</td></tr><tr><td>WHERE</td><td>PrivateHireMovements.PickupDateTime >= '2026-03-01' AND <br>PrivateHireMovements.PickupDateTime < '2026-04-01'</td><td>Limits to March 2026</td></tr><tr><td>WHERE</td><td>Invoices.[Type] IN ('CR', 'IN')</td><td>Only includes certain invoice types</td></tr><tr><td>TOP</td><td>10000</td><td>Limits output rows (not relevant here since only one row is returned)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: Show total trips for HO city in March 2026 where there is affiliate-specific revenue.
chart: N
web: N
executed: N
execution_time: 9.0
question_normalized: show_total_trips_for_ho_city_in_march_2026_where_there_is_affiliate-specific_revenue.
created_at: 2026-05-22 14:37:15
updated_at: 2026-05-22 14:37:15
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (207, b"Invalid column name 'Affiliate_Revenue'.DB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT COUNT(*) AS TotalTrips
  FROM PrivateHires
  INNER JOIN PrivateHireMovements ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  WHERE Bases.Base = 'HO'
    AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
    AND PrivateHireMovements.PickupDateTime < '2026-04-01'
    AND AvalonReporting.dbo.vwPrivateHireDrivers.ActualDriverType = 'Affiliate'
    AND ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.Affiliate_Revenue, 0) > 0
  ```


user_id: 1
agent_id: 4
question: show total rides and total amount by city for driver type Affiliates for march 2026
chart: N
web: N
executed: N
execution_time: 18.0
question_normalized: show_total_rides_and_total_amount_by_city_for_driver_type_affiliates_for_march_2026
created_at: 2026-05-22 14:48:49
updated_at: 2026-05-22 14:48:49
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (207, b"Invalid column name 'InvoiceNo'.DB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 16:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT 
      Bases.Base AS City,
      COUNT(DISTINCT PrivateHireMovements.PrivateHireMovementID) AS TotalRides,
      SUM(ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00) / ISNULL(DC.Driver_Count, 1.0)) AS TotalAmount
  FROM PrivateHireMovements
  INNER JOIN PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients ON PrivateHires.ClientID = Clients.ClientID
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN Invoices ON Invoices.InvoiceNo = InvoicePrivateHireDetails.InvoiceNo
  INNER JOIN (
      SELECT 
          PrivateHireMovementID,
          PrivateHireVehicleID,
          DriverId,
          (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
          dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
              + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom) 
              + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
              + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue,
          ActualDriverType
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled, 0) = 0
        AND ISNULL(MovementCancelled, 0) = 0
  ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      AND PrivateHireDrivers.DriverId = AvalonReporting.dbo.vwPrivateHireDrivers.DriverID
  LEFT OUTER JOIN (
      SELECT 
          PrivateHireMovementID,
          PrivateHireVehicleID,
          COUNT(DriverId) AS Driver_Count
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled, 0) = 0
        AND ISNULL(MovementCancelled, 0) = 0
      GROUP BY PrivateHireMovementID, PrivateHireVehicleID
  ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID
      AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
  WHERE 
      PrivateHireDrivers.ActualDriverType = 'Affiliate'
      AND Invoices.[Type] IN ('CR', 'IN')
      AND YEAR(InvoicePrivateHireDetails.TransactionDate) = 2026
      AND MONTH(InvoicePrivateHireDetails.TransactionDate) = 3
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY
  ```


user_id: 1
agent_id: 4
question: Show total rides by city for driver type Affiliates for March 2026.
chart: N
web: N
executed: Y
execution_time: 15.0
question_normalized: show_total_rides_by_city_for_driver_type_affiliates_for_march_2026.
sql_query_summaries: []
created_at: 2026-05-22 14:49:55
updated_at: 2026-05-22 14:50:01
sql:
  SELECT 
      Bases.Base AS City,
      COUNT(DISTINCT ContractMovements.ContractMovementID) AS TotalRides
  FROM ContractDates
      INNER JOIN ContractVehicles ON ContractDates.ContractMovementID = ContractVehicles.ContractMovementID
      INNER JOIN ContractDrivers ON ContractVehicles.ContractVehicleID = ContractDrivers.ContractVehicleID
      INNER JOIN ContractDriverAllocations ON ContractDrivers.ContractDriverID = ContractDriverAllocations.ContractDriverID
      INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID AND ContractDates.StartDate = ContractDriverAllocations.StartDate
      INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID
      INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
      INNER JOIN (SELECT DISTINCT ContractMovementID, DriverID, DriverName, Salutation FROM vwContractDriverData) vwContractDriverData ON vwContractDriverData.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
  WHERE 
      Drivers.DriverType = 'Affiliate'
      AND ContractDates.Invoice = 1
      AND ContractDates.StartDate >= '2026-03-01'
      AND ContractDates.StartDate < '2026-04-01'
  GROUP BY 
      Bases.Base
  ORDER BY 
      Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 4
question: show affiliate revenue by city for march 2026
web: N
executed: Y
execution_time: 22.0
question_normalized: show_affiliate_revenue_by_city_for_march_2026
sql_query_summaries: []
created_at: 2026-05-22 15:06:23
updated_at: 2026-05-22 15:06:30
sql:
  SELECT 
      Bases.Base AS City,
      SUM(ISNULL(Affiliate_PrivateHire.Affiliate_Revenue, 0)) AS AffiliateRevenue_PrivateHire,
      SUM(ISNULL(Affiliate_Contract.Affiliate_Revenue, 0)) AS AffiliateRevenue_Contract
  FROM
  (
      -- Private Hire Affiliate Revenue for March 2026
      SELECT 
          Bases.Base,
          (ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0) AS Affiliate_Revenue
      FROM PrivateHireMovements
          INNER JOIN (
              SELECT DISTINCT InvoicePrivateHireMovements.PrivateHireMovementID, 
                              InvoicePrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
          ) PrivateId ON PrivateId.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
              AND PrivateId.PrivateHireID = PrivateHireMovements.PrivateHireID
          INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          INNER JOIN PrivateHires ON PrivateId.PrivateHireID = PrivateHires.PrivateHireID 
          INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
          INNER JOIN (
              SELECT PrivateHireMovementId,
                     PrivateHireVehicleId,
                     DriverId,
                     (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
                     dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
                          + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom) + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                          + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                  AND ISNULL(MovementCancelled, 0) = 0
                  AND ActualDriverType = 'Affiliate'
          ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          LEFT OUTER JOIN (
              SELECT PrivateHireMovementId,
                     PrivateHireVehicleId,
                     Count(DriverId) AS Driver_Count
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                  AND ISNULL(MovementCancelled, 0) = 0
              GROUP BY PrivateHireMovementId, PrivateHireVehicleId
          ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
              AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
          INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      WHERE 
          PrivateHireMovements.PickupDateTime >= '2026-03-01'
          AND PrivateHireMovements.PickupDateTime < '2026-04-01'
  ) Affiliate_PrivateHire

  FULL OUTER JOIN
  (
      -- Contract Affiliate Revenue for March 2026
      SELECT 
          Bases.Base,
          ISNULL(ContractVehicles.Revenue, 0) AS Affiliate_Revenue
      FROM ContractDates 
          INNER JOIN ContractVehicles ON ContractVehicles.ContractMovementID = ContractDates.ContractMovementID
          INNER JOIN ContractDrivers ON ContractDrivers.ContractVehicleID = ContractVehicles.ContractVehicleID
          INNER JOIN ContractDriverAllocations ON ContractDriverAllocations.ContractDriverID = ContractDrivers.ContractDriverID
          INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID 
                              AND ContractDates.StartDate = ContractDriverAllocations.StartDate
          INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID 
          INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
          INNER JOIN (SELECT DISTINCT ContractMovementID,DriverID,DriverName,Salutation FROM vwContractDriverData) vwContractDriverData ON vwContractDriverData.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
          LEFT OUTER JOIN ContractVehicleAllocations ON ContractVehicles.ContractVehicleID = ContractVehicleAllocations.ContractVehicleID
                              AND ContractDates.StartDate = ContractVehicleAllocations.StartDate
      WHERE 
          Drivers.DriverType = 'Affiliate'
          AND ContractDates.Invoice = 1
          AND ContractDates.StartDate >= '2026-03-01'
          AND ContractDates.StartDate < '2026-04-01'
  ) Affiliate_Contract
  ON Affiliate_PrivateHire.Base = Affiliate_Contract.Base
  INNER JOIN Bases ON Bases.Base = ISNULL(Affiliate_PrivateHire.Base, Affiliate_Contract.Base)
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['AffiliateRevenue_PrivateHire'].tolist(),
              'type': 'bar',
              'name': 'AffiliateRevenue_PrivateHire'
          },
          {
              'x': df['City'].tolist(),
              'y': df['AffiliateRevenue_Contract'].tolist(),
              'type': 'bar',
              'name': 'AffiliateRevenue_Contract'
          }
      ],
      'layout': {
          'title': 'Affiliate Revenue by City for March 2026',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'Affiliate Revenue'}
      }
  }


user_id: 1
agent_id: 4
question: Show revenue by city for March 2026 for driver type Affiliate.
web: N
executed: Y
execution_time: 32.0
question_normalized: show_revenue_by_city_for_march_2026_for_driver_type_affiliate.
sql_query_summaries: []
created_at: 2026-05-22 15:08:05
updated_at: 2026-05-22 15:08:11
sql:
  SELECT 
      City,
      SUM(Affiliate_Revenue) AS Affiliate_Revenue
  FROM (
      -- Affiliate Revenue from Private Hire
      SELECT 
          Bases.Base AS City,
          (ISNULL(
              dbo.VehicleRevenuePrice(PrivateHireDrivers.Price, PrivateHireDrivers.PrivateHireMovementID, PrivateHireMovements.SplitTo, PrivateHireMovements.SplitFrom, PrivateHireDrivers.Seats, PrivateHireDrivers.VehicleType), 0)
           + ISNULL(dbo.ExtrasRevenue(PrivateHireDrivers.PrivateHireMovementID, PrivateHireMovements.SplitTo, PrivateHireMovements.SplitFrom), 0)
           + ISNULL(dbo.ClientDiscountRevenue(PrivateHireDrivers.PrivateHireMovementID, PrivateHireMovements.SplitTo, PrivateHireMovements.SplitFrom), 0)
           + ISNULL(dbo.VehicleTypeSurchargeRevenue(PrivateHireDrivers.PrivateHireMovementID, PrivateHireDrivers.VehicleTypeSurchargePrice, PrivateHireMovements.SplitTo, PrivateHireMovements.SplitFrom), 0)
          ) / ISNULL(DC.Driver_Count, 1.0) AS Affiliate_Revenue
      FROM Invoices
      INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
      INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers AS PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      LEFT OUTER JOIN (
          SELECT PrivateHireMovementID, PrivateHireVehicleID, COUNT(DriverID) AS Driver_Count
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0 AND ISNULL(MovementCancelled, 0) = 0
          GROUP BY PrivateHireMovementID, PrivateHireVehicleID
      ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
      INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
      WHERE 
          Invoices.[Type] IN ('CR', 'IN')
          AND PrivateHireDrivers.ActualDriverType = 'Affiliate'
          AND InvoicePrivateHireDetails.TransactionDate >= '2026-03-01'
          AND InvoicePrivateHireDetails.TransactionDate < '2026-04-01'

      UNION ALL

      -- Affiliate Revenue from Contracts (Passenger)
      SELECT 
          Bases.Base AS City,
          ISNULL(ContractVehicles.Revenue, 0) AS Affiliate_Revenue
      FROM ContractDates
      INNER JOIN ContractVehicles ON ContractVehicles.ContractMovementID = ContractDates.ContractMovementID
      INNER JOIN ContractDrivers ON ContractDrivers.ContractVehicleID = ContractVehicles.ContractVehicleID
      INNER JOIN ContractDriverAllocations ON ContractDriverAllocations.ContractDriverID = ContractDrivers.ContractDriverID
      INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID
      INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID
      INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
      INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
      WHERE 
          Drivers.DriverType = 'Affiliate'
          AND ContractDates.Invoice = 1
          AND InvoiceContractPassengerDetails.TransactionDate >= '2026-03-01'
          AND InvoiceContractPassengerDetails.TransactionDate < '2026-04-01'
  ) AS Combined
  GROUP BY City
  ORDER BY City
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['City'].tolist(),
              'y': df['Affiliate_Revenue'].tolist(),
              'type': 'bar',
              'name': 'Affiliate Revenue'
          }
      ],
      'layout': {
          'title': 'Revenue by City for March 2026 (Affiliate Drivers)',
          'xaxis': {'title': 'City'},
          'yaxis': {'title': 'Affiliate Revenue'}
      }
  }


user_id: 1
agent_id: 4
question: Show me total trips and total affiliate revenue for March 2026.
web: N
executed: Y
execution_time: 11071.0
question_normalized: show_me_total_trips_and_total_affiliate_revenue_for_march_2026.
created_at: 2026-05-22 17:27:10
updated_at: 2026-05-22 17:27:16
sql:
  SELECT 
      COUNT(*) AS TotalTrips,
      SUM(Affiliate_Revenue) AS TotalAffiliateRevenue
  FROM (
      -- Private Hire Affiliate Revenue
      SELECT 
          1 AS TripCount,
          (ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0) AS Affiliate_Revenue
      FROM 
          (
              SELECT DISTINCT InvoicePrivateHireMovements.PrivateHireMovementID, 
                              InvoicePrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
          ) PrivateId
          INNER JOIN PrivateHireMovements ON PrivateId.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
              AND PrivateId.PrivateHireID = PrivateHireMovements.PrivateHireID
          INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          INNER JOIN PrivateHires ON PrivateId.PrivateHireID = PrivateHires.PrivateHireID 
          INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
          INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
          INNER JOIN (
              SELECT 
                  PrivateHireMovementId,
                  PrivateHireVehicleId,
                  DriverId,
                  (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
                  dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
                      + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                      + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                      + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom)
                      AS Affiliate_Total_Revenue
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                AND ISNULL(MovementCancelled, 0) = 0
                AND ActualDriverType = 'Affiliate'
          ) PrivateHireDrivers 
              ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          LEFT OUTER JOIN (
              SELECT 
                  PrivateHireMovementId,
                  PrivateHireVehicleId,
                  COUNT(DriverId) AS Driver_Count
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                AND ISNULL(MovementCancelled, 0) = 0
              GROUP BY PrivateHireMovementId, PrivateHireVehicleId
          ) DC 
              ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
             AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
          INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
          INNER JOIN Invoices ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
      WHERE 
          InvoicePrivateHireDetails.TransactionDate >= '2026-03-01'
          AND InvoicePrivateHireDetails.TransactionDate < '2026-04-01'
          AND Invoices.[Type] IN ('CR', 'IN')
          AND ((ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0)) > 0

      UNION ALL

      -- Contract Affiliate Revenue
      SELECT
          1 AS TripCount,
          ISNULL(ContractVehicles.Revenue, 0) AS Affiliate_Revenue
      FROM ContractDates 
          INNER JOIN ContractVehicles ON ContractVehicles.ContractMovementID = ContractDates.ContractMovementID
          INNER JOIN ContractDrivers ON ContractDrivers.ContractVehicleID = ContractVehicles.ContractVehicleID
          INNER JOIN ContractDriverAllocations ON ContractDriverAllocations.ContractDriverID = ContractDrivers.ContractDriverID
          INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID 
                                  AND ContractDates.StartDate = ContractDriverAllocations.StartDate
          INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID 
          INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
          INNER JOIN (SELECT DISTINCT ContractMovementID,DriverID,DriverName,Salutation FROM vwContractDriverData) vwContractDriverData ON vwContractDriverData.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
          LEFT OUTER JOIN ContractVehicleAllocations ON ContractVehicles.ContractVehicleID = ContractVehicleAllocations.ContractVehicleID
                                  AND ContractDates.StartDate = ContractVehicleAllocations.StartDate
      WHERE Drivers.DriverType = 'Affiliate'
        AND ContractDates.Invoice = 1
        AND InvoiceContractPassengerDetails.TransactionDate >= '2026-03-01'
        AND InvoiceContractPassengerDetails.TransactionDate < '2026-04-01'
        AND ISNULL(ContractVehicles.Revenue, 0) > 0
  ) AS AffiliateTrips
  ORDER BY 1
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': ['TotalTrips', 'TotalAffiliateRevenue'],
              'y': [df['TotalTrips'].iloc[0], df['TotalAffiliateRevenue'].iloc[0]],
              'type': 'bar',
              'name': 'March 2026'
          }
      ],
      'layout': {
          'title': 'Total Trips and Affiliate Revenue for March 2026',
          'xaxis': {'title': 'Metric'},
          'yaxis': {'title': 'Value'}
      }
  }

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "Show me total trips and total affiliate revenue for March 2026.", "summary": "This query calculates the total number of trips and the total affiliate revenue for all affiliate drivers for the month of March 2026. It combines data from both private hire and contract trips, ensuring only completed (non-cancelled) trips with positive revenue are included. The output shows the total trip count and the sum of affiliate revenue for the specified period.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query calculates the total number of trips and the total affiliate revenue for all affiliate drivers for the month of March 2026. It combines data from both private hire and contract trips, ensuring only completed (non-cancelled) trips with positive revenue are included. The output shows the total trip count and the sum of affiliate revenue for the specified period.</p><hr><h4>Step 1 - Gather Private Hire Affiliate Revenue</h4><p>The query first collects all private hire trips involving affiliate drivers that occurred between March 1, 2026 and March 31, 2026. It excludes cancelled trips and only includes those with positive affiliate revenue. The revenue is calculated per driver and adjusted for the number of drivers per vehicle.</p><h4>Step 2 - Gather Contract Affiliate Revenue</h4><p>Next, the query collects contract trips for affiliate drivers within the same date range, again only including trips with positive revenue and completed invoices.</p><h4>Step 3 - Combine and Summarize</h4><p>Both sets of trips are combined, and the query calculates the total number of trips and the total affiliate revenue for March 2026.</p><table><thead><tr><th>What it shows</th><th>What it means</th></tr></thead><tbody><tr><td>TotalTrips</td><td>The total number of affiliate trips in March 2026</td></tr><tr><td>TotalAffiliateRevenue</td><td>The total revenue earned by affiliates for these trips</td></tr></tbody></table><h3>The Final Output</h3><p>The result is a single row showing the total number of affiliate trips and the total affiliate revenue for March 2026, combining both private hire and contract sources.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>SELECT</td><td>COUNT(*), SUM(Affiliate_Revenue)</td><td>Calculates total trips and total affiliate revenue</td></tr><tr><td>FROM</td><td>Private hire and contract trip subqueries</td><td>Combines data sources</td></tr><tr><td>WHERE</td><td>TransactionDate between '2026-03-01' and '2026-04-01', revenue > 0, affiliate drivers only</td><td>Filters for March 2026 affiliate trips with revenue</td></tr><tr><td>ORDER BY</td><td>1</td><td>Orders by the first column (not significant here)</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS</td><td>Limits output to 10,000 rows (only one row expected)</td></tr></tbody></table></div>"}]


user_id: 1
agent_id: 4
question: show me total trips and Affiliate Revenue for city HO for March 2026 for driver type Affiliates
web: N
executed: Y
execution_time: 27.0
question_normalized: show_me_total_trips_and_affiliate_revenue_for_city_ho_for_march_2026_for_driver_type_affiliates
sql_query_summaries: []
created_at: 2026-05-25 10:47:26
updated_at: 2026-05-25 10:47:32
sql:
  WITH unified AS (
      -- Block 6: Private Hire Affiliate Revenue
      SELECT 
          Bases.Base AS ServiceAreaCode,
          PrivateHireDrivers.DriverId AS AffiliateCode,
          'P ' + LTRIM(STR(PrivateHires.PrivateHireID)) + '/' + LTRIM(STR(PrivateHireMovements.PrivateHireMovementID)) AS ResNumber,
          (ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0) AS Affiliate_Revenue,
          0 AS DriverCode,
          NULL AS StartDate
      FROM PrivateHireMovements
          INNER JOIN (
              SELECT DISTINCT InvoicePrivateHireMovements.PrivateHireMovementID, 
                              InvoicePrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
              UNION
              SELECT DISTINCT PrivateHireMovements.PrivateHireMovementID,
                              PrivateHireMovements.PrivateHireID,
                              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
              FROM Invoices 
                  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo 
                  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
          ) PrivateId ON PrivateId.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
                     AND PrivateId.PrivateHireID = PrivateHireMovements.PrivateHireID
          INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          INNER JOIN PrivateHires ON PrivateId.PrivateHireID = PrivateHires.PrivateHireID 
          INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
          INNER JOIN (
              SELECT PrivateHireMovementId,
                     PrivateHireVehicleId,
                     DriverId,
                     (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
                     dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
                          + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom) 
                          + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                          + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                AND ISNULL(MovementCancelled, 0) = 0
                AND ActualDriverType = 'Affiliate'
          ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          LEFT OUTER JOIN (
              SELECT PrivateHireMovementId,
                     PrivateHireVehicleId,
                     COUNT(DriverId) AS Driver_Count
              FROM AvalonReporting.dbo.vwPrivateHireDrivers
              WHERE ISNULL(Cancelled, 0) = 0
                AND ISNULL(MovementCancelled, 0) = 0
              GROUP BY PrivateHireMovementId, PrivateHireVehicleId
          ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
               AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
          INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo

      UNION ALL

      -- Block 7: Contract Affiliate Revenue
      SELECT 
          Bases.Base AS ServiceAreaCode,
          Drivers.DriverId AS AffiliateCode,
          'C ' + LTRIM(STR(Contracts.ContractID)) + ISNULL('/' + LTRIM(STR(ContractMovements.ContractMovementID)), '') AS ResNumber,
          ISNULL(ContractVehicles.Revenue, 0) AS Affiliate_Revenue,
          0 AS DriverCode,
          ContractDates.StartDate
      FROM ContractDates 
          INNER JOIN ContractVehicles ON ContractVehicles.ContractMovementID = ContractDates.ContractMovementID
          INNER JOIN ContractDrivers ON ContractDrivers.ContractVehicleID = ContractVehicles.ContractVehicleID
          INNER JOIN ContractDriverAllocations ON ContractDriverAllocations.ContractDriverID = ContractDrivers.ContractDriverID
          INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID 
                               AND ContractDates.StartDate = ContractDriverAllocations.StartDate
          INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID 
          INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
          INNER JOIN (
              SELECT DISTINCT ContractMovementID, DriverID, DriverName, Salutation 
              FROM vwContractDriverData
          ) vwContractDriverData ON vwContractDriverData.ContractMovementID = ContractMovements.ContractMovementID
          INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
          LEFT OUTER JOIN ContractVehicleAllocations ON ContractVehicles.ContractVehicleID = ContractVehicleAllocations.ContractVehicleID
                               AND ContractDates.StartDate = ContractVehicleAllocations.StartDate
      WHERE Drivers.DriverType = 'Affiliate'
        AND ContractDates.Invoice = 1
  )

  SELECT 
      ServiceAreaCode,
      AffiliateCode,
      COUNT(DISTINCT ResNumber) AS TotalTrips,
      SUM(Affiliate_Revenue) AS TotalAffiliateRevenue
  FROM unified
  WHERE ServiceAreaCode = 'HO'
    AND DriverCode = 0
    AND (
          StartDate IS NULL
          OR (
              TRY_CAST(StartDate AS DATE) >= '2026-03-01'
              AND TRY_CAST(StartDate AS DATE) <  '2026-04-01'
          )
        )
  GROUP BY ServiceAreaCode, AffiliateCode
  ORDER BY ServiceAreaCode, AffiliateCode
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

chart:
  chart_json = {
      'data': [
          {
              'x': df['AffiliateCode'].tolist(),
              'y': df['TotalTrips'].tolist(),
              'type': 'bar',
              'name': 'Total Trips'
          },
          {
              'x': df['AffiliateCode'].tolist(),
              'y': df['TotalAffiliateRevenue'].tolist(),
              'type': 'bar',
              'name': 'Affiliate Revenue'
          }
      ],
      'layout': {
          'title': 'Total Trips and Affiliate Revenue for City HO (March 2026, Driver Type: Affiliates)',
          'xaxis': {'title': 'AffiliateCode'},
          'yaxis': {'title': 'Count / Revenue'}
      }
  }


user_id: 1
agent_id: 4
chart: N
web: N
executed: Y
execution_time: 18.0
sql_query_summaries: []
created_at: 2026-05-25 10:54:25
updated_at: 2026-05-25 10:54:31
question:
  show me total trips and Affiliate Revenue for city HO and Nominal Code 40100 for March 2026 for driver type Affiliates

sql:
  WITH affiliate_revenue AS (
      -- Block 6: Private Hire Affiliate Revenue
      SELECT
          Bases.Base AS ServiceAreaCode,
          STRING_AGG(CAST(InvoicePrivateHireDetails.NominalCode AS VARCHAR(50)), ',') AS NominalCodes,
          PrivateHireDrivers.DriverId AS AffiliateCode,
          'P ' + LTRIM(STR(PrivateHires.PrivateHireID)) + '/' + LTRIM(STR(PrivateHireMovements.PrivateHireMovementID)) AS ResNumber,
          0.0 AS GratuityTotal,
          0.0 AS TaxesTotal,
          0.0 AS Segmenttotal,
          (ISNULL(PrivateHireDrivers.Affiliate_Total_Revenue, 0.00)) / ISNULL(DC.Driver_Count, 1.0) AS Affiliate_Revenue
      FROM PrivateHireMovements
      INNER JOIN (
          SELECT DISTINCT
              InvoicePrivateHireMovements.PrivateHireMovementID,
              InvoicePrivateHireMovements.PrivateHireID,
              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
          FROM Invoices
          INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
          UNION
          SELECT DISTINCT
              PrivateHireMovements.PrivateHireMovementID,
              PrivateHireMovements.PrivateHireID,
              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
          FROM Invoices
          INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
          INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitFrom
          UNION
          SELECT DISTINCT
              PrivateHireMovements.PrivateHireMovementID,
              PrivateHireMovements.PrivateHireID,
              InvoicePrivateHireMovements.InvoicePrivateHireMovementID
          FROM Invoices
          INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
          INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.SplitTo
      ) PrivateId ON PrivateId.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          AND PrivateId.PrivateHireID = PrivateHireMovements.PrivateHireID
      INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      INNER JOIN PrivateHires ON PrivateId.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
      INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateId.InvoicePrivateHireMovementID
      INNER JOIN (
          SELECT
              PrivateHireMovementId,
              PrivateHireVehicleId,
              DriverId,
              (ISNULL(Total, 0.0)) AS Affiliate_Revenue,
              dbo.VehicleRevenuePrice(Price, PrivateHireMovementID, SplitTo, SplitFrom, Seats, VehicleType)
                  + dbo.ExtrasRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                  + dbo.ClientDiscountRevenue(PrivateHireMovementID, SplitTo, SplitFrom)
                  + dbo.VehicleTypeSurchargeRevenue(PrivateHireMovementID, VehicleTypeSurchargePrice, SplitTo, SplitFrom) AS Affiliate_Total_Revenue
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0
            AND ISNULL(MovementCancelled, 0) = 0
            AND ActualDriverType = 'Affiliate'
      ) PrivateHireDrivers ON PrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      LEFT OUTER JOIN (
          SELECT
              PrivateHireMovementId,
              PrivateHireVehicleId,
              COUNT(DriverId) AS Driver_Count
          FROM AvalonReporting.dbo.vwPrivateHireDrivers
          WHERE ISNULL(Cancelled, 0) = 0
            AND ISNULL(MovementCancelled, 0) = 0
          GROUP BY PrivateHireMovementId, PrivateHireVehicleId
      ) DC ON PrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID
           AND PrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      WHERE Bases.Base = 'HO'
        AND EXISTS (
            SELECT 1
            FROM InvoicePrivateHireDetails iphd
            WHERE iphd.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
              AND iphd.NominalCode LIKE '%40100%'
        )
        AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
        AND PrivateHireMovements.PickupDateTime < '2026-04-01'
      GROUP BY
          Bases.Base,
          PrivateHires.PrivateHireID,
          PrivateHireMovements.PrivateHireMovementID,
          PrivateHireDrivers.DriverId,
          PrivateHireDrivers.Affiliate_Total_Revenue,
          DC.Driver_Count

      UNION ALL

      -- Block 7: Contract Affiliate Revenue
      SELECT
          Bases.Base AS ServiceAreaCode,
          CAST(InvoiceContractPassengerDetails.NominalCode AS VARCHAR(50)) AS NominalCodes,
          Drivers.DriverId AS AffiliateCode,
          'C ' + LTRIM(STR(Contracts.ContractID)) + ISNULL('/' + LTRIM(STR(ContractMovements.ContractMovementID)), '') AS ResNumber,
          0.0 AS GratuityTotal,
          0.0 AS TaxesTotal,
          0.0 AS Segmenttotal,
          ISNULL(ContractVehicles.Revenue, 0) AS Affiliate_Revenue
      FROM ContractDates
      INNER JOIN ContractVehicles ON ContractVehicles.ContractMovementID = ContractDates.ContractMovementID
      INNER JOIN ContractDrivers ON ContractDrivers.ContractVehicleID = ContractVehicles.ContractVehicleID
      INNER JOIN ContractDriverAllocations ON ContractDriverAllocations.ContractDriverID = ContractDrivers.ContractDriverID
      INNER JOIN Drivers ON Drivers.DriverID = ContractDriverAllocations.DriverID
          AND ContractDates.StartDate = ContractDriverAllocations.StartDate
      INNER JOIN ContractMovements ON ContractDates.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN Contracts ON ContractMovements.ContractID = Contracts.ContractID
      INNER JOIN InvoiceContractMovementPassengers ON InvoiceContractMovementPassengers.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN InvoiceContractPassengerDetails ON InvoiceContractMovementPassengers.InvoiceContractMovementPassengerSerialNo = InvoiceContractPassengerDetails.InvoiceContractMovementPassengerSerialNo
      INNER JOIN (SELECT DISTINCT ContractMovementID, DriverID, DriverName, Salutation FROM vwContractDriverData) vwContractDriverData
          ON vwContractDriverData.ContractMovementID = ContractMovements.ContractMovementID
      INNER JOIN Bases ON Contracts.BaseSerialNo = Bases.BaseSerialNo
      LEFT OUTER JOIN ContractVehicleAllocations ON ContractVehicles.ContractVehicleID = ContractVehicleAllocations.ContractVehicleID
          AND ContractDates.StartDate = ContractVehicleAllocations.StartDate
      WHERE Drivers.DriverType = 'Affiliate'
        AND ContractDates.Invoice = 1
        AND Bases.Base = 'HO'
        AND InvoiceContractPassengerDetails.NominalCode LIKE '%40100%'
        AND ContractDates.StartDate >= '2026-03-01'
        AND ContractDates.StartDate < '2026-04-01'
  )
  SELECT
      ServiceAreaCode,
      NominalCodes,
      AffiliateCode,
      COUNT(ResNumber) AS TotalTrips,
      SUM(Affiliate_Revenue) AS TotalAffiliateRevenue
  FROM affiliate_revenue
  GROUP BY ServiceAreaCode, NominalCodes, AffiliateCode
  ORDER BY ServiceAreaCode, AffiliateCode
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

question_normalized:
  show_me_total_trips_and_affiliate_revenue_for_city_ho_and_nominal_code_40100_for_march_2026_for_driver_type_affiliates


user_id: 1
agent_id: 4
chart: N
web: N
executed: Y
execution_time: 16.0
sql_query_summaries: []
created_at: 2026-05-25 10:56:00
updated_at: 2026-05-25 10:56:08
question:
  Show the total trips and affiliate revenue for city HO and Nominal Code 40100 for February 2026 for affiliate drivers.

sql:
  SELECT 
      Bases.Base AS ServiceAreaCode,
      COUNT(*) AS TotalTrips,
      SUM(
          ISNULL(
              (
                  ISNULL(AvalonReporting.dbo.vwPrivateHireDrivers.Total, 0.0) 
                  + ISNULL(dbo.VehicleRevenuePrice(AvalonReporting.dbo.vwPrivateHireDrivers.Price, PrivateHireMovements.PrivateHireMovementID, AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom, AvalonReporting.dbo.vwPrivateHireDrivers.Seats, AvalonReporting.dbo.vwPrivateHireDrivers.VehicleType), 0.0)
                  + ISNULL(dbo.ExtrasRevenue(PrivateHireMovements.PrivateHireMovementID, AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom), 0.0)
                  + ISNULL(dbo.ClientDiscountRevenue(PrivateHireMovements.PrivateHireMovementID, AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom), 0.0)
                  + ISNULL(dbo.VehicleTypeSurchargeRevenue(PrivateHireMovements.PrivateHireMovementID, AvalonReporting.dbo.vwPrivateHireDrivers.VehicleTypeSurchargePrice, AvalonReporting.dbo.vwPrivateHireDrivers.SplitTo, AvalonReporting.dbo.vwPrivateHireDrivers.SplitFrom), 0.0)
              ), 0.0
          ) / ISNULL(DC.Driver_Count, 1.0)
      ) AS AffiliateRevenue
  FROM PrivateHireMovements
  INNER JOIN PrivateHires ON PrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireDetails.InvoicePrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN (
      SELECT 
          PrivateHireMovementId, 
          PrivateHireVehicleId, 
          COUNT(DriverId) AS Driver_Count
      FROM AvalonReporting.dbo.vwPrivateHireDrivers
      WHERE ISNULL(Cancelled, 0) = 0 
        AND ISNULL(MovementCancelled, 0) = 0
      GROUP BY PrivateHireMovementId, PrivateHireVehicleId
  ) DC ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = DC.PrivateHireMovementID 
       AND AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireVehicleID = DC.PrivateHireVehicleID
  WHERE Bases.Base = 'HO'
    AND ',' + CAST(InvoicePrivateHireDetails.NominalCode AS VARCHAR(50)) + ',' LIKE '%,40100,%'
    AND AvalonReporting.dbo.vwPrivateHireDrivers.ActualDriverType = 'Affiliate'
    AND PrivateHireMovements.PickupDateTime >= '2026-02-01'
    AND PrivateHireMovements.PickupDateTime < '2026-03-01'
  GROUP BY Bases.Base
  ORDER BY Bases.Base
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;

question_normalized:
  show_the_total_trips_and_affiliate_revenue_for_city_ho_and_nominal_code_40100_for_february_2026_for_affiliate_drivers.


user_id: 1
agent_id: 4
question: Show me list of rides of HO City for March 2026
chart: N
web: N
executed: Y
execution_time: 11.0
question_normalized: show_me_list_of_rides_of_ho_city_for_march_2026
sql_query_summaries: []
created_at: 2026-05-27 13:39:31
updated_at: 2026-05-27 13:39:37
sql:
  SELECT
      PrivateHires.PrivateHireID,
      PrivateHireMovements.PrivateHireMovementID,
      PrivateHires.ClientID,
      Clients.Salutation,
      PrivateHires.BookingType,
      PrivateHires.OperatorID,
      Bases.Base AS ServiceAreaCode,
      PrivateHireMovements.PickupDateTime,
      InvoicePrivateHireDetails.NominalCode,
      InvoicePrivateHireDetails.Total,
      InvoicePrivateHireDetails.VAT
  FROM Invoices
  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  WHERE
      Invoices.[Type] IN ('CR', 'IN')
      AND Bases.Base = 'HO'
      AND PrivateHireMovements.PickupDateTime >= '2026-03-01'
      AND PrivateHireMovements.PickupDateTime < '2026-04-01'
  ORDER BY PrivateHireMovements.PickupDateTime, PrivateHires.PrivateHireID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;


user_id: 1
agent_id: 4
question: Show me the total of all rides for HO City with Nominal Code 40000 for December 2025.
web: N
executed: Y
execution_time: 10.0
question_normalized: show_me_the_total_of_all_rides_for_ho_city_with_nominal_code_40000_for_december_2025.
sql_query_summaries: []
created_at: 2026-05-27 13:44:25
updated_at: 2026-05-27 13:44:31
sql:
  SELECT TOP 10000 
      SUM(InvoicePrivateHireDetails.Total) AS TotalRides
  FROM Invoices
  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE Bases.Base = 'HO City'
    AND InvoicePrivateHireDetails.NominalCode = '40000'
    AND InvoicePrivateHireDetails.TransactionDate >= '2025-12-01'
    AND InvoicePrivateHireDetails.TransactionDate < '2026-01-01'
    AND Invoices.[Type] IN ('CR', 'IN');

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalRides'].tolist(),
              'type': 'bar',
              'name': 'TotalRides'
          }
      ],
      'layout': {
          'title': 'Total Rides for HO City with Nominal Code 40000 in December 2025',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalRides'}
      }
  }


user_id: 1
agent_id: 4
question: Show me the total of all rides for HO City with Nominal Code 40000 for December 2025.
web: N
executed: Y
execution_time: 3.0
question_normalized: show_me_the_total_of_all_rides_for_ho_city_with_nominal_code_40000_for_december_2025.
sql_query_summaries: []
created_at: 2026-05-27 13:45:23
updated_at: 2026-05-27 13:45:30
sql:
  SELECT TOP 10000 
      SUM(InvoicePrivateHireDetails.Total) AS TotalRides
  FROM Invoices
  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE Bases.Base = 'HO'
    AND InvoicePrivateHireDetails.NominalCode = '40000'
    AND InvoicePrivateHireDetails.TransactionDate >= '2025-12-01'
    AND InvoicePrivateHireDetails.TransactionDate < '2026-01-01'
    AND Invoices.[Type] IN ('CR', 'IN');

chart:
  chart_json = {
      'data': [
          {
              'x': df.index.tolist(),
              'y': df['TotalRides'].tolist(),
              'type': 'bar',
              'name': 'TotalRides'
          }
      ],
      'layout': {
          'title': 'Total Rides for HO City with Nominal Code 40000 in December 2025',
          'xaxis': {'title': 'Index'},
          'yaxis': {'title': 'TotalRides'}
      }
  }


user_id: 1
agent_id: 4
question: Show me the detailed list of all rides for HO City with Nominal Code 40000 for December 2025.
chart: N
web: N
executed: N
execution_time: 17.0
question_normalized: show_me_the_detailed_list_of_all_rides_for_ho_city_with_nominal_code_40000_for_december_2025.
created_at: 2026-05-27 13:46:56
updated_at: 2026-05-27 13:46:56
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (102, b"Incorrect syntax near ')'.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT DISTINCT ',' + CAST(v.DriverID AS VARCHAR(50))
              FROM AvalonReporting.dbo.vwPrivateHireDrivers v
              WHERE v.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
              FOR XML PATH('')
          ), 1, 1, ''
      ) AS DriverID,
      STUFF(
          (
              SELECT DISTINCT ',' + CAST(v.DriverName AS VARCHAR(50))
              FROM AvalonReporting.dbo.vwPrivateHireDrivers v
              WHERE v.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
              FOR XML PATH('')
          ), 1, 1, ''
      ) AS DriverName,
      PrivateHires.BookingType,
      PrivateHires.OperatorID,
      InvoicePrivateHireDetails.NominalCode,
      SUM(CASE WHEN NominalCodes.Description = 'Gratuity' THEN InvoicePrivateHireDetails.Total ELSE 0.0 END) AS GratuityTotal,
      SUM(InvoicePrivateHireDetails.VAT) AS TaxesTotal,
      SUM(InvoicePrivateHireDetails.Total) AS Segmenttotal,
      Bases.Base AS ServiceAreaCode,
      Bases.Base AS Pickup_State,
      1 AS DriverCode,
      NULL AS AffiliateCode,
      0.0 AS Charter_Revenue,
      0.0 AS Affiliate_Revenue,
      'R' AS PAY_CAT,
      CASE
          WHEN DATEADD(DAY, 1, EOMONTH(InvoicePrivateHireDetails.TransactionDate, -1)) = DATEADD(DAY, 1, EOMONTH(PrivateHireMovements.PickupDateTime, -1))
              THEN 'CP'
          WHEN DATEADD(DAY, 1, EOMONTH(InvoicePrivateHireDetails.TransactionDate, -1)) > DATEADD(DAY, 1, EOMONTH(PrivateHireMovements.PickupDateTime, -1))
               AND InvoicePrivateHireDetails.NominalCode <> '10600'
              THEN 'PP'
          ELSE 'CP'
      END AS PER_CAT,
      0.0 AS Congestion_Schg
  FROM Invoices
      INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
      INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
      INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
      INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
      INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
      INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
      INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE Invoices.[Type] IN ('CR', 'IN')
      AND Bases.Base = 'HO City'
      AND InvoicePrivateHireDetails.NominalCode = '40000'
      AND InvoicePrivateHireDetails.TransactionDate >= '2025-12-01'
      AND InvoicePrivateHireDetails.TransactionDate < '2026-01-01'
  GROUP BY
      PrivateHires.PrivateHireID,
      PrivateHires.ClientID,
      Clients.Salutation,
      PrivateHireMovements.PrivateHireMovementID,
      Bases.Base,
      InvoicePrivateHireDetails.TransactionDate,
      PrivateHireMovements.PickupDateTime,
      InvoicePrivateHireDetails.NominalCode,
      PrivateHires.BookingType,
      PrivateHires.OperatorID
  ORDER BY ResNumber
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: show me details of all rides for City HO and Nominal Code 40000 for Dec 2025
chart: N
web: N
executed: N
execution_time: 19.0
question_normalized: show_me_details_of_all_rides_for_city_ho_and_nominal_code_40000_for_dec_2025
created_at: 2026-05-27 13:48:01
updated_at: 2026-05-27 13:48:01
sql:
  SQL generation failed after 3 attempts. Last error: Execution test failed: (102, b"Incorrect syntax near ')'.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\nDB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
  Failed SQL:
  ```sql
  SELECT DISTINCT ',' + CAST(v.DriverID AS VARCHAR(50))
          FROM AvalonReporting.dbo.vwPrivateHireDrivers v
          WHERE v.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          FOR XML PATH('')
      ),1,1,'') AS DriverID,
      STUFF((
          SELECT DISTINCT ',' + CAST(v.DriverName AS VARCHAR(50))
          FROM AvalonReporting.dbo.vwPrivateHireDrivers v
          WHERE v.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
          FOR XML PATH('')
      ),1,1,'') AS DriverName,
      PrivateHires.BookingType,
      PrivateHires.OperatorID,
      InvoicePrivateHireDetails.NominalCode,
      SUM(CASE WHEN NominalCodes.Description = 'Gratuity' THEN InvoicePrivateHireDetails.Total ELSE 0.0 END) AS GratuityTotal,
      SUM(InvoicePrivateHireDetails.VAT) AS TaxesTotal,
      SUM(InvoicePrivateHireDetails.Total) AS Segmenttotal,
      Bases.Base AS ServiceAreaCode,
      Bases.Base AS Pickup_State,
      1 AS DriverCode,
      NULL AS AffiliateCode,
      0.0 AS Charter_Revenue,
      0.0 AS Affiliate_Revenue,
      'R' AS PAY_CAT,
      CASE
          WHEN DATEADD(DAY, 1, EOMONTH(InvoicePrivateHireDetails.TransactionDate, -1)) = DATEADD(DAY, 1, EOMONTH(PrivateHireMovements.PickupDateTime, -1))
              THEN 'CP'
          WHEN DATEADD(DAY, 1, EOMONTH(InvoicePrivateHireDetails.TransactionDate, -1)) > DATEADD(DAY, 1, EOMONTH(PrivateHireMovements.PickupDateTime, -1))
              AND InvoicePrivateHireDetails.NominalCode <> '10600'
              THEN 'PP'
          ELSE 'CP'
      END AS PER_CAT,
      0.0 AS Congestion_Schg
  FROM Invoices
  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN AvalonReporting.dbo.vwPrivateHireDrivers ON AvalonReporting.dbo.vwPrivateHireDrivers.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE
      Invoices.[Type] IN ('CR', 'IN')
      AND Bases.Base = 'HO'
      AND InvoicePrivateHireDetails.NominalCode = '40000'
      AND InvoicePrivateHireDetails.TransactionDate >= '2025-12-01'
      AND InvoicePrivateHireDetails.TransactionDate < '2026-01-01'
  GROUP BY
      PrivateHires.PrivateHireID,
      PrivateHires.ClientID,
      Clients.Salutation,
      PrivateHireMovements.PrivateHireMovementID,
      Bases.Base,
      InvoicePrivateHireDetails.TransactionDate,
      PrivateHireMovements.PickupDateTime,
      InvoicePrivateHireDetails.NominalCode,
      PrivateHires.BookingType,
      PrivateHires.OperatorID
  ORDER BY
      PrivateHires.PrivateHireID,
      PrivateHireMovements.PrivateHireMovementID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY;
  ```


user_id: 1
agent_id: 4
question: show me details of all rides for City HO and Nominal Code 40000 for Dec 2025
chart: N
web: N
executed: Y
execution_time: 13.0
question_normalized: show_me_details_of_all_rides_for_city_ho_and_nominal_code_40000_for_dec_2025
created_at: 2026-05-27 14:16:57
updated_at: 2026-05-27 14:17:02
sql:
  SELECT
      PrivateHires.PrivateHireID,
      PrivateHires.ClientID,
      Clients.Salutation,
      PrivateHireMovements.PrivateHireMovementID,
      Bases.Base AS ServiceAreaCode,
      InvoicePrivateHireDetails.NominalCode,
      InvoicePrivateHireDetails.Total,
      InvoicePrivateHireDetails.VAT,
      PrivateHireMovements.PickupDateTime
  FROM Invoices
  INNER JOIN InvoicePrivateHireMovements ON Invoices.InvoiceNo = InvoicePrivateHireMovements.InvoiceNo
  INNER JOIN InvoicePrivateHireDetails ON InvoicePrivateHireMovements.InvoicePrivateHireMovementID = InvoicePrivateHireDetails.InvoicePrivateHireMovementID
  INNER JOIN PrivateHireMovements ON InvoicePrivateHireMovements.PrivateHireMovementID = PrivateHireMovements.PrivateHireMovementID
  INNER JOIN PrivateHires ON InvoicePrivateHireMovements.PrivateHireID = PrivateHires.PrivateHireID
  INNER JOIN Clients ON Clients.ClientID = PrivateHires.ClientID
  INNER JOIN Bases ON PrivateHires.BaseSerialNo = Bases.BaseSerialNo
  INNER JOIN NominalCodes ON InvoicePrivateHireDetails.NominalCode = NominalCodes.Code
  WHERE
      Bases.Base = 'HO'
      AND InvoicePrivateHireDetails.NominalCode = '40000'
      AND PrivateHireMovements.PickupDateTime >= '2025-12-01'
      AND PrivateHireMovements.PickupDateTime < '2026-01-01'
      AND Invoices.[Type] IN ('CR', 'IN')
  ORDER BY PrivateHires.PrivateHireID, PrivateHireMovements.PrivateHireMovementID
  OFFSET 0 ROWS FETCH NEXT 10000 ROWS ONLY

sql_query_summaries:
  [{"agent_id": "4", "sub_question": "show me details of all rides for City HO and Nominal Code 40000 for Dec 2025", "summary": "This query retrieves detailed information about all private hire rides that took place in December 2025 for the City HO location and are associated with the nominal code 40000. It pulls together data from several related tables to show ride IDs, client details, service area, nominal code, amounts, VAT, and pickup times, but only for invoices of type 'CR' or 'IN'. The results are sorted by ride and movement IDs and limited to the first 10,000 records.", "summary_html": "<div><h3>What This Query Does (Plain English)</h3><p>This query retrieves detailed information about all private hire rides that took place in December 2025 for the City HO location and are associated with the nominal code 40000. It pulls together data from several related tables to show ride IDs, client details, service area, nominal code, amounts, VAT, and pickup times, but only for invoices of type 'CR' or 'IN'. The results are sorted by ride and movement IDs and limited to the first 10,000 records.</p><hr><h3>The Final Output</h3><p>The output is a list of up to 10,000 rides for City HO with nominal code 40000 in December 2025, showing key details such as ride and movement IDs, client salutation, service area code, nominal code, total amount, VAT, and pickup date/time.</p><h3>Quick Summary Table</h3><table><thead><tr><th>Clause</th><th>Value Used</th><th>Purpose</th></tr></thead><tbody><tr><td>FROM</td><td>Invoices (with multiple INNER JOINs)</td><td>Combines ride, client, invoice, and code details</td></tr><tr><td>WHERE</td><td>Bases.Base = 'HO', InvoicePrivateHireDetails.NominalCode = '40000', PickupDateTime in Dec 2025, Invoices.[Type] IN ('CR', 'IN')</td><td>Filters for City HO, nominal code 40000, December 2025, and invoice types</td></tr><tr><td>ORDER BY</td><td>PrivateHires.PrivateHireID, PrivateHireMovements.PrivateHireMovementID</td><td>Sorts results by ride and movement IDs</td></tr><tr><td>OFFSET/FETCH</td><td>0 ROWS, NEXT 10000 ROWS ONLY</td><td>Limits output to 10,000 records</td></tr></tbody></table></div>"}]


