Integrate QueryData with an application

Preview

This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms, and the Additional Terms for Generative AI Preview Products. Pre-GA features are available "as is" and might have limited support. For more information, see the launch stage descriptions.

This tutorial describes how to set up and use QueryData in Bigtable using the Google Cloud console and integrate it with your application. Learn how to build the context set file, create a context set that uses the context set file, use MCP Toolbox to call the QueryData method in the Conversational Analytics API to generate SQL queries for natural language questions, and integrate it with your application.

For more information, see QueryData overview.

Objectives

This tutorial covers the following objectives:

• Create database tables and populate them with data.
• Build a context set file with the context engineering agent.
• Create a context set and upload a context set file.
• Test QueryData and generate SQL queries in Bigtable Studio.
• Integrate QueryData with your application using Gemini Data Analytics QueryData tool in MCP Toolbox.
• Add grounding to LLM responses using value search queries.

Costs

In this document, you use the following billable components of Google Cloud:

• Bigtable
• Gemini for Google Cloud API

To generate a cost estimate based on your projected usage, use the pricing calculator.

New Google Cloud users might be eligible for a free trial.

To avoid continued billing, delete the resources you created when you finish the tasks in this document. For more information, see Clean up.

Before you begin

Complete the following prerequisites before creating a context set.

Enable required services

Enable the following services for your project:

• Data Analytics API with Gemini
• Gemini for Google Cloud API
• Knowledge Catalog API

Prepare a Bigtable instance

Make sure that a Bigtable instance is available. For more information, see Create an instance.

Install the cbt CLI

Install and configure the cbt CLI to create tables and populate them with data. For more information, see cbt CLI overview.

Required roles and permissions

• Grant the bigtable.admin role to the IAM user at the instance or project level. For more information, see Bigtable access control with IAM.
• Grant the geminidataanalytics.queryDataUser role to the IAM user at the project level. For more information, see Add IAM policy binding for a project.
• To create, upload, and manage context sets, grant the Dataplex Catalog Editor (roles/dataplex.catalogEditor) or Dataplex Catalog Admin (roles/dataplex.catalogAdmin) role to the IAM user at the project level. For more information, see Context sets permissions.

Create the flights and airports schema and tables

In this section, you create the flights and airports database tables for this tutorial.

1. Configure your default project and instance in ~/.cbtrc:

   echo project = PROJECT_ID >> ~/.cbtrc
   echo instance = INSTANCE_ID >> ~/.cbtrc

   where:
   • PROJECT_ID: your Google Cloud project ID.
   • INSTANCE_ID: your Bigtable instance ID.

2. Run the following command to create the airports table and info column family:

   cbt createtable airports "families=info"

3. Run the following command to create the flights table and info column family:

   cbt createtable flights "families=info"

Populate the flights and airports tables

In this section, you populate the flights and airports tables using the cbt import command.

1. Create a file named airports.csv with the following contents:

   ,info,info,info,info
   ,iata,name,city,country
   AIRPORT#3249,BOS,General Edward Lawrence Logan International Airport,Boston,United States
   AIRPORT#3257,OGG,Kahului Airport,Kahului,United States
   AIRPORT#3259,MCI,Kansas City International Airport,Kansas City,United States
   AIRPORT#3263,PHX,Phoenix Sky Harbor International Airport,Phoenix,United States
   AIRPORT#3270,SFO,San Francisco International Airport,San Francisco,United States
   AIRPORT#3285,LAX,Los Angeles International Airport,Los Angeles,United States
   AIRPORT#3287,CLE,Cleveland Hopkins International Airport,Cleveland,United States
   AIRPORT#3295,EWR,Newark Liberty International Airport,Newark,United States
   AIRPORT#3296,BOI,Boise Air Terminal/Gowen Field,Boise,United States
   AIRPORT#3303,DAL,Dallas Love Field,Dallas,United States
   AIRPORT#3315,KOA,Ellison Onizuka Kona International At Keahole Airport,Kona,United States
   AIRPORT#3321,DCA,Ronald Reagan Washington National Airport,Washington,United States
   AIRPORT#3336,SLC,Salt Lake City International Airport,Salt Lake City,United States
   AIRPORT#3350,IAH,George Bush Intercontinental Houston Airport,Houston,United States
   AIRPORT#3370,PIT,Pittsburgh International Airport,Pittsburgh,United States
   AIRPORT#3376,MIA,Miami International Airport,Miami,United States
   AIRPORT#3377,SEA,Seattle Tacoma International Airport,Seattle,United States
   AIRPORT#3382,LGB,Long Beach /Daugherty Field/ Airport,Long Beach,United States
   AIRPORT#3385,IND,Indianapolis International Airport,Indianapolis,United States
   AIRPORT#3402,LIH,Lihue Airport,Lihue,United States
   AIRPORT#3421,SAT,San Antonio International Airport,San Antonio,United States
   AIRPORT#3426,RDU,Raleigh Durham International Airport,Raleigh-durham,United States
   AIRPORT#3436,TUS,Tucson International Airport,Tucson,United States
   AIRPORT#3444,BUR,Bob Hope Airport,Burbank,United States
   AIRPORT#3445,DTW,Detroit Metropolitan Wayne County Airport,Detroit,United States
   AIRPORT#3470,DFW,Dallas Fort Worth International Airport,Dallas-Fort Worth,United States
   AIRPORT#3473,AUS,Austin Bergstrom International Airport,Austin,United States
   AIRPORT#3478,STL,St Louis Lambert International Airport,St. Louis,United States
   AIRPORT#3482,ATL,Hartsfield Jackson Atlanta International Airport,Atlanta,United States
   AIRPORT#3487,FAT,Fresno Yosemite International Airport,Fresno,United States
   AIRPORT#3514,IAD,Washington Dulles International Airport,Washington,United States
   AIRPORT#3517,MKE,General Mitchell International Airport,Milwaukee,United States
   AIRPORT#3520,PDX,Portland International Airport,Portland,United States
   AIRPORT#3528,HNL,Daniel K Inouye International Airport,Honolulu,United States
   AIRPORT#3531,SAN,San Diego International Airport,San Diego,United States
   AIRPORT#3534,ONT,Ontario International Airport,Ontario,United States
   AIRPORT#3547,MDW,Chicago Midway International Airport,Chicago,United States
   AIRPORT#3551,DEN,Denver International Airport,Denver,United States
   AIRPORT#3552,PHL,Philadelphia International Airport,Philadelphia,United States
   AIRPORT#3597,JFK,John F Kennedy International Airport,New York,United States
   AIRPORT#3607,RNO,Reno Tahoe International Airport,Reno,United States
   AIRPORT#3617,SMF,Sacramento International Airport,Sacramento,United States
   AIRPORT#3619,COS,City of Colorado Springs Municipal Airport,Colorado Springs,United States
   AIRPORT#3639,PSP,Palm Springs International Airport,Palm Springs,United States
   AIRPORT#3649,BWI,Baltimore/Washington International Thurgood Marshall Airport,Baltimore,United States
   AIRPORT#3658,MSP,Minneapolis-St Paul International/Wold-Chamberlain Airport,Minneapolis,United States
   AIRPORT#3661,MSY,Louis Armstrong New Orleans International Airport,New Orleans,United States
   AIRPORT#3667,SNA,John Wayne Airport-Orange County Airport,Santa Ana,United States
   AIRPORT#3676,CLT,Charlotte Douglas International Airport,Charlotte,United States
   AIRPORT#3677,LAS,McCarran International Airport,Las Vegas,United States
   AIRPORT#3678,MCO,Orlando International Airport,Orlando,United States
   AIRPORT#3742,MRY,Monterey Peninsula Airport,Monterey,United States
   AIRPORT#3743,SBA,Santa Barbara Municipal Airport,Santa Barbara,United States
   AIRPORT#3875,RDD,Redding Municipal Airport,Redding,United States
   AIRPORT#3876,EUG,Mahlon Sweet Field,Eugene,United States
   AIRPORT#3878,MFR,Rogue Valley International Medford Airport,Medford,United States
   AIRPORT#3880,RDM,Roberts Field,Redmond-Bend,United States
   AIRPORT#4111,ACV,California Redwood Coast-Humboldt County Airport,Arcata CA,United States
   AIRPORT#4419,CEC,Jack Mc Namara Field Airport,Crescent City,United States
   AIRPORT#4460,SBP,San Luis County Regional Airport,San Luis Obispo,United States
   AIRPORT#4768,PSC,Tri Cities Airport,Pasco,United States
   AIRPORT#5088,SUN,Friedman Memorial Airport,Hailey,United States
   AIRPORT#5305,ASE,Aspen-Pitkin Co/Sardy Field,Aspen,United States
   AIRPORT#5362,MMH,Mammoth Yosemite Airport,Mammoth Lakes,United States

2. Import the data from the airports.csv file into the airports table:

   cbt import airports airports.csv

3. Create a file named flights.csv with the following contents:

   ,info,info,info,info,info,info,info,info,info,info
   ,airline,flight_number,departure_airport,arrival_airport,departure_time,arrival_time,departure_gate,arrival_gate,departure_city,arrival_city
   FLIGHT#0000,UA,1532,SFO,DEN,2025-01-01 05:50:00,2025-01-01 09:23:00,E49,D6,San Francisco,Denver
   FLIGHT#0001,UA,1158,SFO,ORD,2025-01-01 05:57:00,2025-01-01 12:13:00,C38,D30,San Francisco,Chicago
   FLIGHT#0002,F9,1057,IAH,SFO,2025-01-01 05:52:00,2025-01-01 08:14:00,E33,E43,Houston,San Francisco
   FLIGHT#0003,OO,6403,MFR,SFO,2025-01-01 05:57:00,2025-01-01 07:23:00,A6,E50,Medford,San Francisco
   FLIGHT#0004,OO,5628,RNO,SFO,2025-01-01 06:19:00,2025-01-01 07:37:00,A37,B29,Reno,San Francisco
   FLIGHT#0005,CY,922,SFO,LAX,2025-01-01 06:38:00,2025-01-01 07:49:00,D20,E45,San Francisco,Los Angeles
   FLIGHT#0006,AA,338,LAX,SFO,2025-01-01 06:44:00,2025-01-01 08:03:00,E20,A45,Los Angeles,San Francisco
   FLIGHT#0007,UA,1195,MCO,SFO,2025-01-01 12:28:00,2025-01-01 15:06:00,D22,B36,Orlando,San Francisco
   FLIGHT#0008,OO,5632,SBA,SFO,2025-01-01 06:56:00,2025-01-01 08:39:00,E19,A49,Santa Barbara,San Francisco
   FLIGHT#0009,UA,300,CLE,SFO,2025-01-01 07:15:00,2025-01-01 09:22:00,E8,C28,Cleveland,San Francisco
   FLIGHT#0010,UA,706,SEA,SFO,2025-01-01 07:14:00,2025-01-01 09:07:00,A32,B26,Seattle,San Francisco
   FLIGHT#0011,AA,167,MIA,SFO,2025-01-01 07:47:00,2025-01-01 10:51:00,A23,E4,Miami,San Francisco
   FLIGHT#0012,OO,5441,SFO,SBP,2025-01-01 07:08:00,2025-01-01 08:12:00,E21,D24,San Francisco,San Luis Obispo
   FLIGHT#0013,UA,616,SFO,ORD,2025-01-01 07:14:00,2025-01-01 13:24:00,A11,D8,San Francisco,Chicago
   FLIGHT#0014,AA,24,SFO,JFK,2025-01-01 07:14:00,2025-01-01 15:46:00,D4,C15,San Francisco,New York
   FLIGHT#0015,UA,72,HNL,SFO,2025-01-01 07:28:00,2025-01-01 14:22:00,B33,D49,Honolulu,San Francisco
   FLIGHT#0016,AS,244,PDX,SFO,2025-01-01 07:24:00,2025-01-01 09:04:00,E46,B8,Portland,San Francisco
   FLIGHT#0017,OO,6307,MSP,SFO,2025-01-01 07:29:00,2025-01-01 09:32:00,C49,C36,Minneapolis,San Francisco
   FLIGHT#0018,OO,4975,STL,SFO,2025-01-01 07:31:00,2025-01-01 09:58:00,C43,E16,St. Louis,San Francisco
   FLIGHT#0019,AA,23,DFW,SFO,2025-01-01 08:41:00,2025-01-01 10:34:00,E13,E19,Dallas-Fort Worth,San Francisco
   FLIGHT#0020,B6,434,SFO,BOS,2025-01-01 08:00:00,2025-01-01 16:23:00,D16,E46,San Francisco,Boston
   FLIGHT#0021,F9,657,DEN,SFO,2025-01-01 07:58:00,2025-01-01 09:13:00,E41,E28,Denver,San Francisco
   FLIGHT#0022,OO,6464,COS,SFO,2025-01-01 07:56:00,2025-01-01 09:45:00,D49,E17,Colorado Springs,San Francisco
   FLIGHT#0023,UA,1235,IAD,SFO,2025-01-01 08:28:00,2025-01-01 11:15:00,A22,D19,Washington,San Francisco
   FLIGHT#0024,OO,6527,EUG,SFO,2025-01-01 07:54:00,2025-01-01 09:36:00,D9,B26,Eugene,San Francisco
   FLIGHT#0025,AA,242,SFO,ORD,2025-01-01 08:18:00,2025-01-01 14:26:00,E30,C1,San Francisco,Chicago
   FLIGHT#0026,UA,1739,SFO,EWR,2025-01-01 08:22:00,2025-01-01 16:42:00,C13,D45,San Francisco,Newark
   FLIGHT#0027,B6,133,BOS,SFO,2025-01-01 08:34:00,2025-01-01 12:30:00,D49,C16,Boston,San Francisco
   FLIGHT#0028,OO,6336,SFO,RNO,2025-01-01 08:32:00,2025-01-01 09:29:00,B45,A2,San Francisco,Reno
   FLIGHT#0029,UA,567,IAD,SFO,2025-01-01 10:47:00,2025-01-01 13:39:00,C27,B24,Washington,San Francisco
   FLIGHT#0030,OO,5223,SLC,SFO,2025-01-01 08:50:00,2025-01-01 09:55:00,C38,C11,Salt Lake City,San Francisco
   FLIGHT#0031,US,1784,SFO,CLT,2025-01-01 08:47:00,2025-01-01 16:32:00,C42,C31,San Francisco,Charlotte
   FLIGHT#0032,WN,1579,ATL,SFO,2025-01-01 08:48:00,2025-01-01 10:55:00,C47,B5,Atlanta,San Francisco
   FLIGHT#0033,OO,6396,BOI,SFO,2025-01-01 08:56:00,2025-01-01 09:43:00,E20,A6,Boise,San Francisco
   FLIGHT#0034,AA,2293,DFW,SFO,2025-01-01 08:57:00,2025-01-01 11:08:00,D41,C37,Dallas-Fort Worth,San Francisco
   FLIGHT#0035,DL,1106,SFO,MSP,2025-01-01 09:06:00,2025-01-01 14:56:00,E38,B30,San Francisco,Minneapolis
   FLIGHT#0036,DL,1631,SFO,ATL,2025-01-01 09:00:00,2025-01-01 16:26:00,B13,B45,San Francisco,Atlanta
   FLIGHT#0037,OO,5427,SFO,SMF,2025-01-01 09:06:00,2025-01-01 10:00:00,C34,C25,San Francisco,Sacramento
   FLIGHT#0038,CY,352,SFO,BOS,2025-01-01 09:25:00,2025-01-01 17:51:00,A46,E42,San Francisco,Boston
   FLIGHT#0039,UA,1239,LAX,SFO,2025-01-01 09:59:00,2025-01-01 11:19:00,A35,C2,Los Angeles,San Francisco
   FLIGHT#0040,UA,1285,SFO,IAH,2025-01-01 09:41:00,2025-01-01 15:20:00,A39,E10,San Francisco,Houston
   FLIGHT#0041,CY,753,SEA,SFO,2025-01-01 09:58:00,2025-01-01 11:53:00,C40,E35,Seattle,San Francisco
   FLIGHT#0042,CY,956,SFO,SAN,2025-01-01 09:57:00,2025-01-01 11:30:00,B10,E44,San Francisco,San Diego
   FLIGHT#0043,OO,5196,PDX,SFO,2025-01-01 09:53:00,2025-01-01 11:39:00,D13,C34,Portland,San Francisco
   FLIGHT#0044,WN,2346,SFO,LAX,2025-01-01 09:59:00,2025-01-01 11:17:00,C24,E45,San Francisco,Los Angeles
   FLIGHT#0045,OO,6400,EUG,SFO,2025-01-01 10:06:00,2025-01-01 11:27:00,E46,D20,Eugene,San Francisco
   FLIGHT#0046,CY,23,JFK,SFO,2025-01-01 10:21:00,2025-01-01 14:09:00,D2,B21,New York,San Francisco
   FLIGHT#0047,B6,534,SFO,BOS,2025-01-01 10:33:00,2025-01-01 18:55:00,A49,A5,San Francisco,Boston
   FLIGHT#0048,UA,1727,BOS,SFO,2025-01-01 10:34:00,2025-01-01 13:57:00,D43,A31,Boston,San Francisco
   FLIGHT#0049,WN,4391,LAS,SFO,2025-01-01 10:49:00,2025-01-01 12:17:00,A40,C49,Las Vegas,San Francisco
   FLIGHT#0050,OO,5335,CEC,SFO,2025-01-01 10:25:00,2025-01-01 12:04:00,C8,C6,Crescent City,San Francisco
   FLIGHT#0051,DL,1680,ATL,SFO,2025-01-01 10:43:00,2025-01-01 12:45:00,E49,E24,Atlanta,San Francisco
   FLIGHT#0052,OO,6283,SFO,MCI,2025-01-01 10:38:00,2025-01-01 17:01:00,C32,B12,San Francisco,Kansas City
   FLIGHT#0053,OO,5260,SFO,FAT,2025-01-01 10:37:00,2025-01-01 11:39:00,B46,B43,San Francisco,Fresno
   FLIGHT#0054,OO,6249,LAS,SFO,2025-01-01 10:48:00,2025-01-01 12:19:00,D11,A49,Las Vegas,San Francisco
   FLIGHT#0055,AA,23,SFO,DFW,2025-01-01 11:23:00,2025-01-01 17:00:00,B31,A11,San Francisco,Dallas-Fort Worth
   FLIGHT#0056,UA,753,SFO,AUS,2025-01-01 10:59:00,2025-01-01 16:44:00,B18,D6,San Francisco,Austin
   FLIGHT#0057,WN,4855,SFO,MKE,2025-01-01 11:08:00,2025-01-01 17:33:00,D3,D40,San Francisco,Milwaukee
   FLIGHT#0058,DL,1845,SLC,SFO,2025-01-01 11:29:00,2025-01-01 12:06:00,A22,D2,Salt Lake City,San Francisco
   FLIGHT#0059,UA,720,SFO,DEN,2025-01-01 12:46:00,2025-01-01 16:19:00,C41,E39,San Francisco,Denver
   FLIGHT#0060,UA,1257,IAH,SFO,2025-01-01 11:30:00,2025-01-01 13:19:00,A26,D2,Houston,San Francisco
   FLIGHT#0061,WN,2509,SFO,LAX,2025-01-01 11:34:00,2025-01-01 13:03:00,C42,D35,San Francisco,Los Angeles
   FLIGHT#0062,UA,73,EWR,SFO,2025-01-01 12:11:00,2025-01-01 15:24:00,C5,E10,Newark,San Francisco
   FLIGHT#0063,UA,364,PHX,SFO,2025-01-01 11:56:00,2025-01-01 13:11:00,A39,D26,Phoenix,San Francisco
   FLIGHT#0064,AA,221,DFW,SFO,2025-01-01 11:55:00,2025-01-01 13:30:00,A47,B22,Dallas-Fort Worth,San Francisco
   FLIGHT#0065,AA,2293,SFO,DFW,2025-01-01 12:04:00,2025-01-01 17:36:00,C43,E30,San Francisco,Dallas-Fort Worth
   FLIGHT#0066,OO,5199,SFO,SLC,2025-01-01 12:09:00,2025-01-01 14:58:00,A40,E42,San Francisco,Salt Lake City
   FLIGHT#0067,OO,6280,SLC,SFO,2025-01-01 12:13:00,2025-01-01 13:09:00,E16,E36,Salt Lake City,San Francisco
   FLIGHT#0068,OO,6317,RNO,SFO,2025-01-01 12:05:00,2025-01-01 13:09:00,C23,A31,Reno,San Francisco
   FLIGHT#0069,UA,864,SFO,EWR,2025-01-01 12:14:00,2025-01-01 20:38:00,C30,E37,San Francisco,Newark
   FLIGHT#0070,OO,5400,ONT,SFO,2025-01-01 12:25:00,2025-01-01 13:40:00,A48,E19,Ontario,San Francisco
   FLIGHT#0071,UA,236,HNL,SFO,2025-01-01 12:40:00,2025-01-01 19:36:00,A34,C12,Honolulu,San Francisco
   FLIGHT#0072,OO,6343,SNA,SFO,2025-01-01 12:37:00,2025-01-01 13:57:00,A15,D26,Santa Ana,San Francisco
   FLIGHT#0073,UA,1148,SFO,IAD,2025-01-01 13:10:00,2025-01-01 21:02:00,D24,A23,San Francisco,Washington
   FLIGHT#0074,DL,432,JFK,SFO,2025-01-01 13:00:00,2025-01-01 16:28:00,E3,A35,New York,San Francisco
   FLIGHT#0075,B6,1435,SFO,LGB,2025-01-01 13:33:00,2025-01-01 14:47:00,B24,C12,San Francisco,Long Beach
   FLIGHT#0076,OO,6408,SFO,EUG,2025-01-01 13:43:00,2025-01-01 15:10:00,B47,A35,San Francisco,Eugene
   FLIGHT#0077,UA,645,PDX,SFO,2025-01-01 13:27:00,2025-01-01 15:02:00,D7,E4,Portland,San Francisco
   FLIGHT#0078,WN,1812,SFO,SAN,2025-01-01 14:32:00,2025-01-01 15:51:00,B35,D48,San Francisco,San Diego
   FLIGHT#0079,OO,6409,SFO,PDX,2025-01-01 13:42:00,2025-01-01 15:27:00,C10,B17,San Francisco,Portland
   FLIGHT#0080,UA,358,AUS,SFO,2025-01-01 14:31:00,2025-01-01 15:48:00,E33,D21,Austin,San Francisco
   FLIGHT#0081,UA,1728,OGG,SFO,2025-01-01 14:02:00,2025-01-01 20:38:00,A30,C29,Kahului,San Francisco
   FLIGHT#0082,UA,816,SEA,SFO,2025-01-01 13:44:00,2025-01-01 15:38:00,A36,A9,Seattle,San Francisco
   FLIGHT#0083,UA,724,HNL,SFO,2025-01-01 13:59:00,2025-01-01 20:44:00,A14,C9,Honolulu,San Francisco
   FLIGHT#0084,UA,1733,SFO,DEN,2025-01-01 14:38:00,2025-01-01 18:35:00,B27,E32,San Francisco,Denver
   FLIGHT#0085,OO,5543,SFO,BOI,2025-01-01 14:27:00,2025-01-01 17:10:00,E10,B16,San Francisco,Boise
   FLIGHT#0086,UA,1761,IAH,SFO,2025-01-01 14:55:00,2025-01-01 16:45:00,B2,E20,Houston,San Francisco
   FLIGHT#0087,UA,277,DEN,SFO,2025-01-01 14:44:00,2025-01-01 16:04:00,B47,B13,Denver,San Francisco
   FLIGHT#0088,AA,1213,DFW,SFO,2025-01-01 15:14:00,2025-01-01 16:45:00,D11,C31,Dallas-Fort Worth,San Francisco
   FLIGHT#0089,US,407,PHX,SFO,2025-01-01 15:03:00,2025-01-01 16:00:00,C7,D19,Phoenix,San Francisco
   FLIGHT#0090,OO,5367,SFO,RDM,2025-01-01 14:52:00,2025-01-01 16:23:00,A5,E40,San Francisco,Redmond-Bend
   FLIGHT#0091,OO,5454,SMF,SFO,2025-01-01 15:46:00,2025-01-01 16:33:00,A20,A40,Sacramento,San Francisco
   FLIGHT#0092,WN,2687,SFO,LAX,2025-01-01 15:15:00,2025-01-01 16:35:00,D41,B37,San Francisco,Los Angeles
   FLIGHT#0093,CY,932,SFO,LAX,2025-01-01 15:31:00,2025-01-01 16:51:00,A19,E46,San Francisco,Los Angeles
   FLIGHT#0094,WN,3236,SFO,SAN,2025-01-01 15:56:00,2025-01-01 17:23:00,B29,B32,San Francisco,San Diego
   FLIGHT#0095,UA,404,IAH,SFO,2025-01-01 15:56:00,2025-01-01 17:52:00,B15,B42,Houston,San Francisco
   FLIGHT#0096,CY,933,LAX,SFO,2025-01-01 15:42:00,2025-01-01 16:51:00,E16,E7,Los Angeles,San Francisco
   FLIGHT#0097,US,596,SFO,PHX,2025-01-01 15:51:00,2025-01-01 18:52:00,B25,E38,San Francisco,Phoenix
   FLIGHT#0098,AA,379,SFO,DFW,2025-01-01 16:04:00,2025-01-01 21:55:00,A30,D49,San Francisco,Dallas-Fort Worth
   FLIGHT#0099,OO,6280,SFO,SNA,2025-01-01 16:52:00,2025-01-01 18:19:00,B5,C40,San Francisco,Santa Ana
   FLIGHT#0100,UA,735,DEN,SFO,2025-01-01 17:34:00,2025-01-01 19:09:00,C31,B15,Denver,San Francisco
   FLIGHT#0101,OO,5553,PDX,SFO,2025-01-01 16:00:00,2025-01-01 17:36:00,E9,D27,Portland,San Francisco
   FLIGHT#0102,UA,73,SFO,HNL,2025-01-01 16:13:00,2025-01-01 19:52:00,C37,B37,San Francisco,Honolulu
   FLIGHT#0103,UA,587,SEA,SFO,2025-01-01 16:25:00,2025-01-01 18:27:00,B7,B23,Seattle,San Francisco
   FLIGHT#0104,OO,5363,SFO,ONT,2025-01-01 16:09:00,2025-01-01 17:28:00,D21,E29,San Francisco,Ontario
   FLIGHT#0105,OO,6386,SFO,BOI,2025-01-01 16:12:00,2025-01-01 18:58:00,D48,E33,San Francisco,Boise
   FLIGHT#0106,CY,27,JFK,SFO,2025-01-01 16:28:00,2025-01-01 20:19:00,C6,E14,New York,San Francisco
   FLIGHT#0107,OO,5190,SFO,ASE,2025-01-01 16:24:00,2025-01-01 19:42:00,C50,B44,San Francisco,Aspen
   FLIGHT#0108,CY,746,SFO,SEA,2025-01-01 16:40:00,2025-01-01 18:32:00,D35,C24,San Francisco,Seattle
   FLIGHT#0109,UA,1640,SFO,ORD,2025-01-01 17:01:00,2025-01-01 23:02:00,E27,C24,San Francisco,Chicago
   FLIGHT#0110,OO,6221,MCI,SFO,2025-01-01 17:28:00,2025-01-01 19:08:00,E2,C36,Kansas City,San Francisco
   FLIGHT#0111,UA,486,SFO,LAS,2025-01-01 16:47:00,2025-01-01 18:16:00,C42,B47,San Francisco,Las Vegas
   FLIGHT#0112,CY,2,DCA,SFO,2025-01-01 17:01:00,2025-01-01 20:07:00,E43,A33,Washington,San Francisco
   FLIGHT#0113,B6,1436,LGB,SFO,2025-01-01 16:59:00,2025-01-01 18:35:00,B12,B22,Long Beach,San Francisco
   FLIGHT#0114,WN,694,PHX,SFO,2025-01-01 17:11:00,2025-01-01 18:05:00,B44,B18,Phoenix,San Francisco
   FLIGHT#0115,OO,5635,MMH,SFO,2025-01-01 17:00:00,2025-01-01 18:01:00,A25,D7,Mammoth Lakes,San Francisco
   FLIGHT#0116,AS,341,PSP,SFO,2025-01-01 18:25:00,2025-01-01 19:46:00,A11,E18,Palm Springs,San Francisco
   FLIGHT#0117,OO,6364,PSP,SFO,2025-01-01 18:01:00,2025-01-01 19:31:00,A14,B47,Palm Springs,San Francisco
   FLIGHT#0118,OO,5418,SBP,SFO,2025-01-01 17:17:00,2025-01-01 18:15:00,B24,D17,San Luis Obispo,San Francisco
   FLIGHT#0119,AA,197,SFO,ORD,2025-01-01 17:21:00,2025-01-01 23:33:00,D25,E49,San Francisco,Chicago
   FLIGHT#0120,CY,720,SFO,DAL,2025-01-01 18:25:00,2025-01-01 23:43:00,B24,A2,San Francisco,Dallas
   FLIGHT#0121,OO,6268,FAT,SFO,2025-01-01 17:33:00,2025-01-01 18:39:00,E35,D25,Fresno,San Francisco
   FLIGHT#0122,OO,5615,SFO,EUG,2025-01-01 17:45:00,2025-01-01 19:18:00,B11,A34,San Francisco,Eugene
   FLIGHT#0123,CY,960,SFO,SAN,2025-01-01 17:55:00,2025-01-01 19:23:00,D23,E44,San Francisco,San Diego
   FLIGHT#0124,AA,1393,DFW,SFO,2025-01-01 17:51:00,2025-01-01 19:25:00,E11,A41,Dallas-Fort Worth,San Francisco
   FLIGHT#0125,OO,6352,BOI,SFO,2025-01-01 17:58:00,2025-01-01 18:46:00,B31,D23,Boise,San Francisco
   FLIGHT#0126,DL,1151,SFO,HNL,2025-01-01 17:53:00,2025-01-01 21:34:00,E29,B45,San Francisco,Honolulu
   FLIGHT#0127,OO,5227,SFO,SAN,2025-01-01 19:07:00,2025-01-01 20:31:00,A35,B38,San Francisco,San Diego
   FLIGHT#0128,CY,941,LAX,SFO,2025-01-01 18:19:00,2025-01-01 19:34:00,C33,B44,Los Angeles,San Francisco
   FLIGHT#0129,UA,1044,EWR,SFO,2025-01-01 19:19:00,2025-01-01 22:53:00,D50,D26,Newark,San Francisco
   FLIGHT#0130,CY,211,ORD,SFO,2025-01-01 18:41:00,2025-01-01 21:14:00,D13,E45,Chicago,San Francisco
   FLIGHT#0131,UA,685,ORD,SFO,2025-01-01 18:51:00,2025-01-01 21:04:00,D26,D45,Chicago,San Francisco
   FLIGHT#0132,UA,370,SFO,SEA,2025-01-01 18:49:00,2025-01-01 20:41:00,B6,E20,San Francisco,Seattle
   FLIGHT#0133,UA,1433,IAH,SFO,2025-01-01 19:45:00,2025-01-01 21:39:00,C42,C48,Houston,San Francisco
   FLIGHT#0134,UA,1172,DEN,SFO,2025-01-01 20:19:00,2025-01-01 22:37:00,E31,D43,Denver,San Francisco
   FLIGHT#0135,CY,593,PSP,SFO,2025-01-01 19:09:00,2025-01-01 20:26:00,C23,C43,Palm Springs,San Francisco
   FLIGHT#0136,UA,1564,SFO,ORD,2025-01-01 19:14:00,2025-01-02 01:14:00,E3,C48,San Francisco,Chicago
   FLIGHT#0137,UA,741,ORD,SFO,2025-01-01 19:18:00,2025-01-01 21:58:00,A25,B38,Chicago,San Francisco
   FLIGHT#0138,WN,600,SFO,SNA,2025-01-01 19:36:00,2025-01-01 20:53:00,D21,D11,San Francisco,Santa Ana
   FLIGHT#0139,F9,664,SFO,DEN,2025-01-01 19:31:00,2025-01-01 23:13:00,E11,E12,San Francisco,Denver
   FLIGHT#0140,OO,4995,LAS,SFO,2025-01-01 19:18:00,2025-01-01 20:58:00,B42,B49,Las Vegas,San Francisco
   FLIGHT#0141,CY,717,DAL,SFO,2025-01-01 19:31:00,2025-01-01 21:02:00,A42,D32,Dallas,San Francisco
   FLIGHT#0142,UA,1243,SFO,DEN,2025-01-01 19:38:00,2025-01-01 23:15:00,B34,A3,San Francisco,Denver
   FLIGHT#0143,UA,560,IAD,SFO,2025-01-01 19:41:00,2025-01-01 22:29:00,D9,D33,Washington,San Francisco
   FLIGHT#0144,WN,2791,LAX,SFO,2025-01-01 19:45:00,2025-01-01 20:57:00,C49,C22,Los Angeles,San Francisco
   FLIGHT#0145,WN,2079,SAN,SFO,2025-01-01 21:03:00,2025-01-01 22:33:00,A25,E24,San Diego,San Francisco
   FLIGHT#0146,OO,6356,SFO,SLC,2025-01-01 19:57:00,2025-01-01 22:49:00,A28,C45,San Francisco,Salt Lake City
   FLIGHT#0147,OO,6290,PSP,SFO,2025-01-01 19:48:00,2025-01-01 21:12:00,A33,E27,Palm Springs,San Francisco
   FLIGHT#0148,OO,5363,ONT,SFO,2025-01-01 20:27:00,2025-01-01 21:54:00,A14,E17,Ontario,San Francisco
   FLIGHT#0149,OO,5206,SFO,PHX,2025-01-01 20:12:00,2025-01-01 23:05:00,D22,E31,San Francisco,Phoenix
   FLIGHT#0150,B6,1136,LGB,SFO,2025-01-01 20:41:00,2025-01-01 21:56:00,B7,E45,Long Beach,San Francisco
   FLIGHT#0151,US,736,PHX,SFO,2025-01-01 21:12:00,2025-01-01 22:11:00,B22,E33,Phoenix,San Francisco
   FLIGHT#0152,AA,1611,DFW,SFO,2025-01-01 21:42:00,2025-01-01 23:37:00,A13,B44,Dallas-Fort Worth,San Francisco
   FLIGHT#0153,UA,1241,SFO,EWR,2025-01-01 21:44:00,2025-01-02 05:55:00,D3,A17,San Francisco,Newark
   FLIGHT#0154,UA,1726,OGG,SFO,2025-01-01 22:19:00,2025-01-02 04:56:00,C35,B23,Kahului,San Francisco
   FLIGHT#0155,US,898,SFO,CLT,2025-01-01 22:29:00,2025-01-02 06:18:00,D7,D15,San Francisco,Charlotte
   FLIGHT#0156,UA,1669,SFO,PHL,2025-01-01 22:26:00,2025-01-02 06:30:00,B13,A12,San Francisco,Philadelphia
   FLIGHT#0157,UA,362,SFO,BWI,2025-01-01 22:31:00,2025-01-02 06:36:00,E32,A36,San Francisco,Baltimore
   FLIGHT#0158,OO,6220,SFO,RNO,2025-01-01 22:25:00,2025-01-01 23:23:00,D18,A31,San Francisco,Reno
   FLIGHT#0159,OO,6376,SFO,MRY,2025-01-01 22:35:00,2025-01-01 23:19:00,C24,E48,San Francisco,Monterey
   FLIGHT#0160,UA,522,SFO,PDX,2025-01-01 22:36:00,2025-01-02 00:31:00,B17,A40,San Francisco,Portland
   FLIGHT#0161,UA,1728,SFO,BOS,2025-01-01 22:46:00,2025-01-02 07:20:00,C40,E43,San Francisco,Boston
   FLIGHT#0162,UA,724,SFO,LAX,2025-01-01 22:45:00,2025-01-02 00:29:00,E43,B23,San Francisco,Los Angeles
   FLIGHT#0163,UA,1681,SFO,CLE,2025-01-01 23:03:00,2025-01-02 06:45:00,D26,E19,San Francisco,Cleveland
   FLIGHT#0164,UA,1580,OGG,SFO,2025-01-01 23:24:00,2025-01-02 06:07:00,E38,A35,Kahului,San Francisco
   FLIGHT#0165,DL,806,SFO,MSP,2025-01-02 00:22:00,2025-01-02 05:57:00,B27,A3,San Francisco,Minneapolis
   FLIGHT#0166,OO,5467,ONT,SFO,2025-01-02 05:02:00,2025-01-02 06:18:00,E8,C32,Ontario,San Francisco
   FLIGHT#0167,WN,1989,SFO,LAS,2025-01-02 05:35:00,2025-01-02 06:46:00,A21,D15,San Francisco,Las Vegas
   FLIGHT#0168,UA,1619,BOS,SFO,2025-01-02 05:56:00,2025-01-02 09:56:00,C46,E11,Boston,San Francisco
   FLIGHT#0169,UA,1076,SFO,ORD,2025-01-02 05:58:00,2025-01-02 12:00:00,E27,A31,San Francisco,Chicago
   FLIGHT#0170,F9,1056,SFO,IAH,2025-01-02 05:59:00,2025-01-02 12:09:00,A29,B13,San Francisco,Houston
   FLIGHT#0171,WN,2242,LAX,SFO,2025-01-02 06:22:00,2025-01-02 07:36:00,C12,D43,Los Angeles,San Francisco
   FLIGHT#0172,B6,735,SFO,LGB,2025-01-02 06:01:00,2025-01-02 07:20:00,C2,C37,San Francisco,Long Beach
   FLIGHT#0173,WN,3859,SFO,MDW,2025-01-02 06:27:00,2025-01-02 12:26:00,A28,E38,San Francisco,Chicago
   FLIGHT#0174,UA,1285,SFO,ORD,2025-01-02 06:43:00,2025-01-02 12:47:00,B43,A35,San Francisco,Chicago
   FLIGHT#0175,WN,1726,SFO,PHX,2025-01-02 06:32:00,2025-01-02 09:20:00,C16,B2,San Francisco,Phoenix
   FLIGHT#0176,OO,5186,SFO,SAN,2025-01-02 06:25:00,2025-01-02 07:59:00,C47,C1,San Francisco,San Diego
   FLIGHT#0177,UA,566,PIT,SFO,2025-01-02 07:15:00,2025-01-02 09:46:00,C39,E39,Pittsburgh,San Francisco
   FLIGHT#0178,UA,1195,MCO,SFO,2025-01-02 07:18:00,2025-01-02 10:05:00,A47,C43,Orlando,San Francisco
   FLIGHT#0179,CY,925,LAX,SFO,2025-01-02 06:57:00,2025-01-02 08:07:00,E29,C19,Los Angeles,San Francisco
   FLIGHT#0180,UA,761,ORD,SFO,2025-01-02 07:07:00,2025-01-02 09:34:00,B22,A3,Chicago,San Francisco
   FLIGHT#0181,UA,758,SFO,JFK,2025-01-02 07:07:00,2025-01-02 15:53:00,B15,B39,San Francisco,New York
   FLIGHT#0182,CY,67,IAD,SFO,2025-01-02 07:07:00,2025-01-02 10:00:00,D24,E33,Washington,San Francisco
   FLIGHT#0183,UA,706,SEA,SFO,2025-01-02 07:05:00,2025-01-02 08:59:00,D9,C28,Seattle,San Francisco
   FLIGHT#0184,OO,5441,SFO,SBP,2025-01-02 07:06:00,2025-01-02 08:11:00,B3,B29,San Francisco,San Luis Obispo
   FLIGHT#0185,CY,202,SFO,ORD,2025-01-02 07:18:00,2025-01-02 13:23:00,C16,D10,San Francisco,Chicago
   FLIGHT#0186,CY,710,SFO,DAL,2025-01-02 07:16:00,2025-01-02 12:43:00,D1,E13,San Francisco,Dallas
   FLIGHT#0187,AA,24,SFO,JFK,2025-01-02 07:06:00,2025-01-02 15:29:00,C38,D2,San Francisco,New York
   FLIGHT#0188,UA,72,HNL,SFO,2025-01-02 07:28:00,2025-01-02 14:20:00,C8,E18,Honolulu,San Francisco
   FLIGHT#0189,UA,1278,ATL,SFO,2025-01-02 07:30:00,2025-01-02 09:41:00,C16,B21,Atlanta,San Francisco
   FLIGHT#0190,UA,498,SFO,SAN,2025-01-02 07:20:00,2025-01-02 08:38:00,B42,E44,San Francisco,San Diego
   FLIGHT#0191,CY,183,EWR,SFO,2025-01-02 07:26:00,2025-01-02 10:51:00,B33,A12,Newark,San Francisco
   FLIGHT#0192,AA,76,SFO,LAX,2025-01-02 07:22:00,2025-01-02 08:44:00,E28,B18,San Francisco,Los Angeles
   FLIGHT#0193,WN,2325,DEN,SFO,2025-01-02 07:40:00,2025-01-02 09:03:00,A5,A17,Denver,San Francisco
   FLIGHT#0194,WN,1545,LAX,SFO,2025-01-02 07:48:00,2025-01-02 09:02:00,D42,A25,Los Angeles,San Francisco
   FLIGHT#0195,OO,5196,SFO,PDX,2025-01-02 07:46:00,2025-01-02 09:32:00,B12,B11,San Francisco,Portland
   FLIGHT#0196,UA,1053,DEN,SFO,2025-01-02 08:06:00,2025-01-02 09:41:00,C37,E7,Denver,San Francisco
   FLIGHT#0197,AA,23,DFW,SFO,2025-01-02 07:53:00,2025-01-02 09:26:00,D24,C34,Dallas-Fort Worth,San Francisco
   FLIGHT#0198,UA,322,SNA,SFO,2025-01-02 07:53:00,2025-01-02 09:17:00,E22,D32,Santa Ana,San Francisco
   FLIGHT#0199,UA,500,IND,SFO,2025-01-02 08:02:00,2025-01-02 09:46:00,D47,B25,Indianapolis,San Francisco
   FLIGHT#0200,UA,662,SAN,SFO,2025-01-02 08:51:00,2025-01-02 10:38:00,C36,B37,San Diego,San Francisco
   FLIGHT#0201,UA,834,LAS,SFO,2025-01-02 07:51:00,2025-01-02 09:17:00,B24,E14,Las Vegas,San Francisco
   FLIGHT#0202,CY,1930,SFO,LAX,2025-01-02 07:58:00,2025-01-02 09:29:00,D1,E49,San Francisco,Los Angeles
   FLIGHT#0203,UA,1454,ORD,SFO,2025-01-02 08:09:00,2025-01-02 10:54:00,C45,D18,Chicago,San Francisco
   FLIGHT#0204,AA,1368,SFO,DFW,2025-01-02 08:11:00,2025-01-02 13:35:00,A24,D28,San Francisco,Dallas-Fort Worth
   FLIGHT#0205,UA,460,LAX,SFO,2025-01-02 08:22:00,2025-01-02 09:53:00,E4,D14,Los Angeles,San Francisco
   FLIGHT#0206,UA,1547,SFO,BOS,2025-01-02 08:30:00,2025-01-02 16:52:00,B24,D37,San Francisco,Boston
   FLIGHT#0207,AA,242,SFO,ORD,2025-01-02 08:28:00,2025-01-02 14:41:00,D10,B31,San Francisco,Chicago
   FLIGHT#0208,OO,5538,MFR,SFO,2025-01-02 08:15:00,2025-01-02 09:44:00,D3,B43,Medford,San Francisco
   FLIGHT#0209,UA,1739,SFO,EWR,2025-01-02 08:56:00,2025-01-02 17:03:00,B18,A15,San Francisco,Newark
   FLIGHT#0210,DL,745,DTW,SFO,2025-01-02 08:36:00,2025-01-02 10:43:00,B2,D29,Detroit,San Francisco
   FLIGHT#0211,OO,5445,SFO,SBP,2025-01-02 10:35:00,2025-01-02 11:50:00,D39,A1,San Francisco,San Luis Obispo
   FLIGHT#0212,OO,5223,SLC,SFO,2025-01-02 08:52:00,2025-01-02 09:50:00,C17,C19,Salt Lake City,San Francisco
   FLIGHT#0213,UA,1615,SFO,IAD,2025-01-02 08:44:00,2025-01-02 16:41:00,A19,C46,San Francisco,Washington
   FLIGHT#0214,AA,1435,ORD,SFO,2025-01-02 08:43:00,2025-01-02 11:08:00,B49,B11,Chicago,San Francisco
   FLIGHT#0215,HA,11,SFO,HNL,2025-01-02 09:28:00,2025-01-02 13:38:00,E28,B21,San Francisco,Honolulu
   FLIGHT#0216,OO,6373,SFO,DFW,2025-01-02 08:51:00,2025-01-02 14:40:00,B42,D13,San Francisco,Dallas-Fort Worth
   FLIGHT#0217,UA,479,SFO,LAX,2025-01-02 11:15:00,2025-01-02 12:47:00,E32,B7,San Francisco,Los Angeles
   FLIGHT#0218,UA,361,SFO,LIH,2025-01-02 09:33:00,2025-01-02 13:10:00,A45,C26,San Francisco,Lihue
   FLIGHT#0219,WN,2074,SFO,SNA,2025-01-02 09:08:00,2025-01-02 10:18:00,A6,A49,San Francisco,Santa Ana
   FLIGHT#0220,CY,84,SFO,IAD,2025-01-02 09:20:00,2025-01-02 17:25:00,A37,B4,San Francisco,Washington
   FLIGHT#0221,WN,2969,SAN,SFO,2025-01-02 09:35:00,2025-01-02 10:59:00,B50,A43,San Diego,San Francisco
   FLIGHT#0222,UA,1249,SFO,MCO,2025-01-02 10:10:00,2025-01-02 18:15:00,D13,E20,San Francisco,Orlando
   FLIGHT#0223,WN,1820,SFO,LAS,2025-01-02 09:52:00,2025-01-02 11:19:00,B19,D16,San Francisco,Las Vegas
   FLIGHT#0224,WN,2414,SFO,PHX,2025-01-02 09:57:00,2025-01-02 12:52:00,E1,C5,San Francisco,Phoenix
   FLIGHT#0225,UA,698,SEA,SFO,2025-01-02 09:54:00,2025-01-02 11:59:00,E37,D34,Seattle,San Francisco
   FLIGHT#0226,AS,303,SFO,SEA,2025-01-02 10:06:00,2025-01-02 12:11:00,D36,C9,San Francisco,Seattle
   FLIGHT#0227,WN,3323,SFO,DEN,2025-01-02 10:40:00,2025-01-02 13:59:00,A4,E35,San Francisco,Denver
   FLIGHT#0228,OO,6286,SBA,SFO,2025-01-02 10:23:00,2025-01-02 11:47:00,B46,A8,Santa Barbara,San Francisco
   FLIGHT#0229,OO,5603,PHX,SFO,2025-01-02 10:29:00,2025-01-02 11:41:00,A2,C22,Phoenix,San Francisco
   FLIGHT#0230,CY,218,SFO,AUS,2025-01-02 10:28:00,2025-01-02 15:56:00,E49,C21,San Francisco,Austin
   FLIGHT#0231,OO,5335,CEC,SFO,2025-01-02 10:32:00,2025-01-02 12:09:00,D29,D17,Crescent City,San Francisco
   FLIGHT#0232,OO,5646,SFO,SBA,2025-01-02 10:33:00,2025-01-02 11:54:00,A50,E40,San Francisco,Santa Barbara
   FLIGHT#0233,OO,5635,SFO,SNA,2025-01-02 11:22:00,2025-01-02 12:55:00,C17,D47,San Francisco,Santa Ana
   FLIGHT#0234,OO,6380,SFO,BOI,2025-01-02 10:41:00,2025-01-02 13:18:00,B18,C15,San Francisco,Boise
   FLIGHT#0235,UA,662,SFO,MSP,2025-01-02 10:52:00,2025-01-02 16:39:00,B6,E11,San Francisco,Minneapolis
   FLIGHT#0236,OO,6270,SFO,RNO,2025-01-02 10:43:00,2025-01-02 11:52:00,C15,E10,San Francisco,Reno
   FLIGHT#0237,OO,4975,SFO,TUS,2025-01-02 12:23:00,2025-01-02 15:18:00,D5,C12,San Francisco,Tucson
   FLIGHT#0238,UA,322,SFO,SEA,2025-01-02 10:49:00,2025-01-02 12:54:00,E29,D3,San Francisco,Seattle
   FLIGHT#0239,WN,1009,LAX,SFO,2025-01-02 11:33:00,2025-01-02 12:45:00,E12,C30,Los Angeles,San Francisco
   FLIGHT#0240,OO,4966,SFO,SUN,2025-01-02 11:11:00,2025-01-02 14:15:00,D39,D21,San Francisco,Hailey
   FLIGHT#0241,UA,753,SFO,AUS,2025-01-02 11:40:00,2025-01-02 17:33:00,B30,D47,San Francisco,Austin
   FLIGHT#0242,UA,242,SFO,SAN,2025-01-02 12:00:00,2025-01-02 13:24:00,B27,E27,San Francisco,San Diego
   FLIGHT#0243,UA,390,SEA,SFO,2025-01-02 11:10:00,2025-01-02 13:08:00,A17,A23,Seattle,San Francisco
   FLIGHT#0244,OO,6336,RNO,SFO,2025-01-02 11:17:00,2025-01-02 12:17:00,A45,E39,Reno,San Francisco
   FLIGHT#0245,OO,5250,MRY,SFO,2025-01-02 11:12:00,2025-01-02 12:28:00,B33,E11,Monterey,San Francisco
   FLIGHT#0246,UA,317,SAN,SFO,2025-01-02 12:10:00,2025-01-02 13:40:00,A14,A42,San Diego,San Francisco
   FLIGHT#0247,OO,5652,SFO,PSP,2025-01-02 12:14:00,2025-01-02 13:50:00,E17,B17,San Francisco,Palm Springs
   FLIGHT#0248,UA,1195,SFO,ORD,2025-01-02 11:56:00,2025-01-02 18:12:00,B39,B19,San Francisco,Chicago
   FLIGHT#0249,CY,714,SFO,DAL,2025-01-02 11:40:00,2025-01-02 17:22:00,C50,A19,San Francisco,Dallas
   FLIGHT#0250,WN,2779,LAX,SFO,2025-01-02 11:58:00,2025-01-02 13:09:00,B19,C27,Los Angeles,San Francisco
   FLIGHT#0251,UA,1722,SFO,IAH,2025-01-02 11:58:00,2025-01-02 18:29:00,E12,D6,San Francisco,Houston
   FLIGHT#0252,UA,766,JFK,SFO,2025-01-02 11:55:00,2025-01-02 15:21:00,A16,C18,New York,San Francisco
   FLIGHT#0253,UA,1437,ORD,SFO,2025-01-02 12:36:00,2025-01-02 15:09:00,A33,E19,Chicago,San Francisco
   FLIGHT#0254,UA,1294,LAS,SFO,2025-01-02 12:20:00,2025-01-02 13:45:00,E7,A10,Las Vegas,San Francisco
   FLIGHT#0255,UA,1266,SEA,SFO,2025-01-02 12:13:00,2025-01-02 14:11:00,B32,C18,Seattle,San Francisco
   FLIGHT#0256,UA,1668,SFO,EWR,2025-01-02 12:24:00,2025-01-02 20:34:00,D37,A30,San Francisco,Newark
   FLIGHT#0257,OO,6304,BUR,SFO,2025-01-02 12:31:00,2025-01-02 14:01:00,C7,C4,Burbank,San Francisco
   FLIGHT#0258,WN,4391,SFO,STL,2025-01-02 12:55:00,2025-01-02 18:36:00,A12,D39,San Francisco,St. Louis
   FLIGHT#0259,UA,236,HNL,SFO,2025-01-02 13:19:00,2025-01-02 20:12:00,B25,D26,Honolulu,San Francisco
   FLIGHT#0260,UA,1705,SFO,IAH,2025-01-02 12:51:00,2025-01-02 18:50:00,E11,E32,San Francisco,Houston
   FLIGHT#0261,OO,6490,EUG,SFO,2025-01-02 13:00:00,2025-01-02 14:21:00,D34,D29,Eugene,San Francisco
   FLIGHT#0262,UA,820,SFO,ORD,2025-01-02 13:02:00,2025-01-02 19:11:00,B45,E24,San Francisco,Chicago
   FLIGHT#0263,AS,381,SFO,PDX,2025-01-02 12:52:00,2025-01-02 14:34:00,E11,B3,San Francisco,Portland
   FLIGHT#0264,AS,305,SFO,SEA,2025-01-02 12:59:00,2025-01-02 15:10:00,C34,C41,San Francisco,Seattle
   FLIGHT#0265,OO,6273,SFO,SLC,2025-01-02 12:57:00,2025-01-02 15:50:00,C3,D36,San Francisco,Salt Lake City
   FLIGHT#0266,DL,2254,SFO,DTW,2025-01-02 13:05:00,2025-01-02 20:29:00,E10,D30,San Francisco,Detroit
   FLIGHT#0267,B6,1435,SFO,LGB,2025-01-02 13:34:00,2025-01-02 15:02:00,B31,D48,San Francisco,Long Beach
   FLIGHT#0268,F9,661,DEN,SFO,2025-01-02 13:11:00,2025-01-02 14:35:00,C3,E38,Denver,San Francisco
   FLIGHT#0269,UA,1092,EWR,SFO,2025-01-02 13:44:00,2025-01-02 17:05:00,D13,A41,Newark,San Francisco
   FLIGHT#0270,US,1812,SFO,CLT,2025-01-02 13:32:00,2025-01-02 21:36:00,A50,A5,San Francisco,Charlotte
   FLIGHT#0271,WN,2598,LAX,SFO,2025-01-02 13:48:00,2025-01-02 14:54:00,E23,C38,Los Angeles,San Francisco
   FLIGHT#0272,UA,216,SFO,SNA,2025-01-02 15:23:00,2025-01-02 16:41:00,C23,E6,San Francisco,Santa Ana
   FLIGHT#0273,UA,1060,SFO,DCA,2025-01-02 15:19:00,2025-01-02 23:18:00,D14,B18,San Francisco,Washington
   FLIGHT#0274,OO,6326,BOI,SFO,2025-01-02 13:51:00,2025-01-02 14:24:00,D49,A43,Boise,San Francisco
   FLIGHT#0275,UA,724,HNL,SFO,2025-01-02 14:43:00,2025-01-02 21:33:00,B26,A50,Honolulu,San Francisco
   FLIGHT#0276,OO,5463,SFO,SMF,2025-01-02 13:50:00,2025-01-02 14:32:00,A13,D23,San Francisco,Sacramento
   FLIGHT#0277,UA,698,SFO,MCO,2025-01-02 14:24:00,2025-01-02 22:33:00,D49,B2,San Francisco,Orlando
   FLIGHT#0278,CY,1178,SFO,EWR,2025-01-02 13:58:00,2025-01-02 22:06:00,C27,D9,San Francisco,Newark
   FLIGHT#0279,OO,6425,TUS,SFO,2025-01-02 14:50:00,2025-01-02 15:54:00,E29,D17,Tucson,San Francisco
   FLIGHT#0280,OO,5615,MFR,SFO,2025-01-02 13:55:00,2025-01-02 15:15:00,B44,E27,Medford,San Francisco
   FLIGHT#0281,WN,3450,SFO,MDW,2025-01-02 14:50:00,2025-01-02 20:46:00,D39,B44,San Francisco,Chicago
   FLIGHT#0282,UA,1733,SFO,DEN,2025-01-02 15:11:00,2025-01-02 18:47:00,D8,D2,San Francisco,Denver
   FLIGHT#0283,UA,1263,KOA,SFO,2025-01-02 14:59:00,2025-01-02 21:49:00,C39,E3,Kona,San Francisco
   FLIGHT#0284,UA,1568,SFO,RDU,2025-01-02 14:55:00,2025-01-02 23:03:00,A30,A26,San Francisco,Raleigh-durham
   FLIGHT#0285,UA,1159,SFO,BOS,2025-01-02 14:57:00,2025-01-02 23:23:00,C19,A30,San Francisco,Boston
   FLIGHT#0286,OO,5652,PSP,SFO,2025-01-02 14:52:00,2025-01-02 16:46:00,D37,A5,Palm Springs,San Francisco
   FLIGHT#0287,US,749,CLT,SFO,2025-01-02 15:28:00,2025-01-02 17:47:00,D17,D38,Charlotte,San Francisco
   FLIGHT#0288,UA,1491,SFO,DEN,2025-01-02 15:09:00,2025-01-02 18:45:00,E31,E36,San Francisco,Denver
   FLIGHT#0289,WN,2687,SFO,LAX,2025-01-02 15:27:00,2025-01-02 16:31:00,E42,B13,San Francisco,Los Angeles
   FLIGHT#0290,DL,2040,SFO,JFK,2025-01-02 15:09:00,2025-01-02 23:20:00,E2,D33,San Francisco,New York
   FLIGHT#0291,OO,5549,SFO,AUS,2025-01-02 15:24:00,2025-01-02 21:11:00,B42,C1,San Francisco,Austin
   FLIGHT#0292,AS,308,SEA,SFO,2025-01-02 15:22:00,2025-01-02 17:18:00,C39,A46,Seattle,San Francisco
   FLIGHT#0293,F9,662,SFO,DEN,2025-01-02 15:16:00,2025-01-02 18:50:00,C5,A8,San Francisco,Denver
   FLIGHT#0294,UA,735,DEN,SFO,2025-01-02 16:00:00,2025-01-02 17:19:00,A32,C24,Denver,San Francisco
   FLIGHT#0295,UA,404,IAH,SFO,2025-01-02 17:26:00,2025-01-02 19:32:00,C14,A7,Houston,San Francisco
   FLIGHT#0296,CY,210,SFO,ORD,2025-01-02 15:42:00,2025-01-02 21:44:00,A31,B46,San Francisco,Chicago
   FLIGHT#0297,AS,315,SFO,SEA,2025-01-02 19:47:00,2025-01-02 22:16:00,A8,B49,San Francisco,Seattle
   FLIGHT#0298,WN,1901,SAN,SFO,2025-01-02 15:48:00,2025-01-02 17:09:00,A23,B38,San Diego,San Francisco
   FLIGHT#0299,OO,5580,SFO,SNA,2025-01-02 16:35:00,2025-01-02 18:03:00,D40,E43,San Francisco,Santa Ana
   FLIGHT#0300,AA,2265,DFW,SFO,2025-01-02 16:07:00,2025-01-02 17:41:00,A4,A23,Dallas-Fort Worth,San Francisco
   FLIGHT#0301,OO,5363,SFO,ONT,2025-01-02 16:15:00,2025-01-02 17:32:00,A10,A26,San Francisco,Ontario
   FLIGHT#0302,OO,5609,SFO,PDX,2025-01-02 17:01:00,2025-01-02 18:42:00,E49,D4,San Francisco,Portland
   FLIGHT#0303,OO,5645,MFR,SFO,2025-01-02 16:15:00,2025-01-02 17:35:00,A25,E49,Medford,San Francisco
   FLIGHT#0304,OO,4976,SFO,STL,2025-01-02 16:37:00,2025-01-02 22:27:00,C35,A2,San Francisco,St. Louis
   FLIGHT#0305,OO,6217,BUR,SFO,2025-01-02 16:44:00,2025-01-02 17:55:00,D50,A14,Burbank,San Francisco
   FLIGHT#0306,WN,1276,SFO,LAX,2025-01-02 16:25:00,2025-01-02 17:32:00,B8,D22,San Francisco,Los Angeles
   FLIGHT#0307,OO,6238,ACV,SFO,2025-01-02 16:25:00,2025-01-02 17:36:00,E24,A39,Arcata CA,San Francisco
   FLIGHT#0308,OO,5190,SFO,ASE,2025-01-02 17:08:00,2025-01-02 20:17:00,C9,E6,San Francisco,Aspen
   FLIGHT#0309,OO,4627,SFO,SLC,2025-01-02 16:43:00,2025-01-02 19:41:00,C32,C4,San Francisco,Salt Lake City
   FLIGHT#0310,OO,6476,SFO,MFR,2025-01-02 16:38:00,2025-01-02 18:16:00,B26,D33,San Francisco,Medford
   FLIGHT#0311,UA,486,SFO,LAS,2025-01-02 16:52:00,2025-01-02 18:24:00,D25,E8,San Francisco,Las Vegas
   FLIGHT#0312,DL,214,SFO,DTW,2025-01-02 19:09:00,2025-01-03 02:20:00,C6,E35,San Francisco,Detroit
   FLIGHT#0313,CY,592,SFO,PSP,2025-01-02 16:54:00,2025-01-02 18:14:00,B40,B9,San Francisco,Palm Springs
   FLIGHT#0314,UA,529,SNA,SFO,2025-01-02 17:01:00,2025-01-02 18:15:00,D28,B30,Santa Ana,San Francisco
   FLIGHT#0315,UA,372,MSP,SFO,2025-01-02 17:39:00,2025-01-02 19:19:00,E28,C18,Minneapolis,San Francisco
   FLIGHT#0316,AA,1213,SFO,DFW,2025-01-02 18:20:00,2025-01-03 00:19:00,E39,A42,San Francisco,Dallas-Fort Worth
   FLIGHT#0317,AS,341,PSP,SFO,2025-01-02 17:15:00,2025-01-02 18:37:00,D40,D15,Palm Springs,San Francisco
   FLIGHT#0318,OO,5418,SBP,SFO,2025-01-02 18:11:00,2025-01-02 19:09:00,C31,D39,San Luis Obispo,San Francisco
   FLIGHT#0319,CY,193,EWR,SFO,2025-01-02 17:29:00,2025-01-02 20:59:00,E20,E40,Newark,San Francisco
   FLIGHT#0320,UA,1723,SFO,KOA,2025-01-02 17:26:00,2025-01-02 21:02:00,E18,D41,San Francisco,Kona
   FLIGHT#0321,UA,1762,SFO,IAH,2025-01-02 17:37:00,2025-01-02 23:11:00,C40,C37,San Francisco,Houston
   FLIGHT#0322,CY,720,SFO,DAL,2025-01-02 17:23:00,2025-01-02 22:47:00,D13,D23,San Francisco,Dallas
   FLIGHT#0323,CY,963,SAN,SFO,2025-01-02 17:36:00,2025-01-02 19:05:00,B1,E32,San Diego,San Francisco
   FLIGHT#0324,OO,5255,SFO,EUG,2025-01-02 17:27:00,2025-01-02 19:02:00,C7,B2,San Francisco,Eugene
   FLIGHT#0325,CY,960,SFO,SAN,2025-01-02 17:32:00,2025-01-02 18:50:00,C3,C4,San Francisco,San Diego
   FLIGHT#0326,UA,1419,MSY,SFO,2025-01-02 17:46:00,2025-01-02 20:07:00,C26,E49,New Orleans,San Francisco
   FLIGHT#0327,WN,1585,SFO,LAX,2025-01-02 17:46:00,2025-01-02 19:31:00,A12,A12,San Francisco,Los Angeles
   FLIGHT#0328,DL,1505,MSP,SFO,2025-01-02 17:47:00,2025-01-02 19:48:00,A33,B37,Minneapolis,San Francisco
   FLIGHT#0329,US,686,PHX,SFO,2025-01-02 17:59:00,2025-01-02 19:05:00,C28,C11,Phoenix,San Francisco
   FLIGHT#0330,AS,302,SEA,SFO,2025-01-02 18:00:00,2025-01-02 20:04:00,B28,E17,Seattle,San Francisco
   FLIGHT#0331,UA,1552,RDU,SFO,2025-01-02 18:08:00,2025-01-02 20:51:00,B15,D48,Raleigh-durham,San Francisco
   FLIGHT#0332,UA,697,LAS,SFO,2025-01-02 17:55:00,2025-01-02 19:14:00,E37,B31,Las Vegas,San Francisco
   FLIGHT#0333,AA,219,LAX,SFO,2025-01-02 17:54:00,2025-01-02 19:05:00,C27,E34,Los Angeles,San Francisco
   FLIGHT#0334,OO,5425,ONT,SFO,2025-01-02 18:04:00,2025-01-02 19:23:00,C46,A14,Ontario,San Francisco
   FLIGHT#0335,WN,1861,SFO,PHX,2025-01-02 20:49:00,2025-01-02 23:31:00,C31,B42,San Francisco,Phoenix
   FLIGHT#0336,OO,5631,SFO,BUR,2025-01-02 18:10:00,2025-01-02 19:29:00,D26,E29,San Francisco,Burbank
   FLIGHT#0337,UA,720,SFO,AUS,2025-01-02 18:13:00,2025-01-02 23:41:00,E10,D1,San Francisco,Austin
   FLIGHT#0338,UA,1581,SFO,OGG,2025-01-02 18:15:00,2025-01-02 22:06:00,B40,E18,San Francisco,Kahului
   FLIGHT#0339,OO,5227,SFO,SAN,2025-01-02 18:26:00,2025-01-02 19:59:00,E33,E50,San Francisco,San Diego
   FLIGHT#0340,CY,941,LAX,SFO,2025-01-02 18:24:00,2025-01-02 19:39:00,D4,A22,Los Angeles,San Francisco
   FLIGHT#0341,AA,1459,ORD,SFO,2025-01-02 18:21:00,2025-01-02 21:11:00,D42,B25,Chicago,San Francisco
   FLIGHT#0342,OO,5442,SFO,RDD,2025-01-02 18:19:00,2025-01-02 19:35:00,E21,B9,San Francisco,Redding
   FLIGHT#0343,AA,69,MIA,SFO,2025-01-02 18:31:00,2025-01-02 21:33:00,B11,B15,Miami,San Francisco
   FLIGHT#0344,OO,6220,DFW,SFO,2025-01-02 19:01:00,2025-01-02 20:40:00,D35,E4,Dallas-Fort Worth,San Francisco
   FLIGHT#0345,UA,1670,SFO,HNL,2025-01-02 18:42:00,2025-01-02 22:52:00,A15,C18,San Francisco,Honolulu
   FLIGHT#0346,DL,435,JFK,SFO,2025-01-02 18:57:00,2025-01-02 22:25:00,D35,C33,New York,San Francisco
   FLIGHT#0347,UA,508,SEA,SFO,2025-01-02 19:01:00,2025-01-02 21:05:00,C16,B8,Seattle,San Francisco
   FLIGHT#0348,UA,1523,BOS,SFO,2025-01-02 21:19:00,2025-01-03 01:19:00,E7,B32,Boston,San Francisco
   FLIGHT#0349,CY,593,PSP,SFO,2025-01-02 19:03:00,2025-01-02 20:21:00,C13,A47,Palm Springs,San Francisco
   FLIGHT#0350,UA,741,ORD,SFO,2025-01-02 19:44:00,2025-01-02 22:14:00,A16,C32,Chicago,San Francisco
   FLIGHT#0351,WN,3414,SFO,SAN,2025-01-02 19:43:00,2025-01-02 21:10:00,E3,D46,San Francisco,San Diego
   FLIGHT#0352,UA,404,SFO,PDX,2025-01-02 19:42:00,2025-01-02 21:24:00,B48,A30,San Francisco,Portland
   FLIGHT#0353,UA,637,SFO,SNA,2025-01-02 19:32:00,2025-01-02 20:49:00,D40,A23,San Francisco,Santa Ana
   FLIGHT#0354,OO,5573,SAT,SFO,2025-01-02 21:13:00,2025-01-02 22:57:00,D34,E33,San Antonio,San Francisco
   FLIGHT#0355,AA,219,SFO,LAX,2025-01-02 20:03:00,2025-01-02 22:00:00,E27,D38,San Francisco,Los Angeles
   FLIGHT#0356,OO,5600,BUR,SFO,2025-01-02 19:55:00,2025-01-02 21:21:00,A7,A27,Burbank,San Francisco
   FLIGHT#0357,CY,947,LAX,SFO,2025-01-02 20:38:00,2025-01-02 22:06:00,D28,C15,Los Angeles,San Francisco
   FLIGHT#0358,WN,138,SFO,LAS,2025-01-02 20:26:00,2025-01-02 21:49:00,B35,E31,San Francisco,Las Vegas
   FLIGHT#0359,OO,5302,SFO,PSC,2025-01-02 20:29:00,2025-01-02 22:28:00,C9,A15,San Francisco,Pasco
   FLIGHT#0360,CY,748,SFO,SEA,2025-01-02 20:46:00,2025-01-02 23:17:00,D7,E25,San Francisco,Seattle
   FLIGHT#0361,UA,236,SFO,EWR,2025-01-02 20:41:00,2025-01-03 05:04:00,D12,B47,San Francisco,Newark
   FLIGHT#0362,OO,6503,SFO,EUG,2025-01-02 20:54:00,2025-01-02 22:27:00,A50,E49,San Francisco,Eugene
   FLIGHT#0363,WN,1174,LAS,SFO,2025-01-02 20:58:00,2025-01-02 22:19:00,C42,D33,Las Vegas,San Francisco
   FLIGHT#0364,AS,744,SFO,SLC,2025-01-02 20:52:00,2025-01-02 23:33:00,B11,A39,San Francisco,Salt Lake City
   FLIGHT#0365,WN,4992,SFO,PHX,2025-01-02 21:49:00,2025-01-03 00:32:00,D19,E15,San Francisco,Phoenix
   FLIGHT#0366,UA,469,EWR,SFO,2025-01-02 23:07:00,2025-01-03 02:27:00,E3,D19,Newark,San Francisco
   FLIGHT#0367,UA,1163,SFO,EWR,2025-01-02 21:44:00,2025-01-03 05:45:00,D19,C17,San Francisco,Newark
   FLIGHT#0368,DL,2337,SFO,ATL,2025-01-02 21:44:00,2025-01-03 05:23:00,B4,A39,San Francisco,Atlanta
   FLIGHT#0369,OO,6432,SFO,EUG,2025-01-02 22:24:00,2025-01-02 23:57:00,E11,A4,San Francisco,Eugene
   FLIGHT#0370,US,898,SFO,CLT,2025-01-02 22:24:00,2025-01-03 06:16:00,A45,A24,San Francisco,Charlotte
   FLIGHT#0371,UA,292,SFO,MCO,2025-01-02 22:30:00,2025-01-03 06:37:00,C7,C5,San Francisco,Orlando
   FLIGHT#0372,OO,5600,SFO,MFR,2025-01-02 22:36:00,2025-01-03 00:01:00,E42,E38,San Francisco,Medford
   FLIGHT#0373,UA,263,LAX,SFO,2025-01-02 22:48:00,2025-01-03 00:04:00,B22,E27,Los Angeles,San Francisco
   FLIGHT#0374,OO,5414,SFO,RDM,2025-01-02 22:32:00,2025-01-03 00:12:00,A46,C18,San Francisco,Redmond-Bend
   FLIGHT#0375,UA,1241,SFO,EWR,2025-01-02 23:22:00,2025-01-03 07:44:00,A28,E27,San Francisco,Newark
   FLIGHT#0376,UA,522,SFO,PDX,2025-01-02 22:55:00,2025-01-03 00:42:00,A10,E39,San Francisco,Portland
   FLIGHT#0377,UA,724,SFO,ORD,2025-01-02 23:05:00,2025-01-03 05:20:00,B40,D23,San Francisco,Chicago
   FLIGHT#0378,UA,156,SFO,MSY,2025-01-02 23:22:00,2025-01-03 05:24:00,C40,A9,San Francisco,New Orleans
   FLIGHT#0379,CY,358,SFO,BOS,2025-01-02 22:52:00,2025-01-03 07:31:00,B23,A44,San Francisco,Boston
   FLIGHT#0380,DL,1370,SFO,JFK,2025-01-02 23:04:00,2025-01-03 07:36:00,E10,A49,San Francisco,New York
   FLIGHT#0381,UA,1729,SFO,IAD,2025-01-02 23:10:00,2025-01-03 07:35:00,D32,E42,San Francisco,Washington
   FLIGHT#0382,CY,34,SFO,JFK,2025-01-02 23:15:00,2025-01-03 07:54:00,D28,E25,San Francisco,New York
   FLIGHT#0383,DL,1880,SFO,ATL,2025-01-02 00:53:00,2025-01-02 08:27:00,E2,A29,San Francisco,Atlanta
   FLIGHT#0384,UA,1523,SFO,EWR,2025-01-02 23:39:00,2025-01-03 07:43:00,B9,D15,San Francisco,Newark
   FLIGHT#0385,US,426,PHX,SFO,2025-01-02 00:18:00,2025-01-02 01:16:00,D47,C42,Phoenix,San Francisco

4. Import the data from the flights.csv file into the flights table:

   cbt import flights flights.csv

5. In Bigtable Studio, run the following queries to verify that the tables are populated:

   • SELECT * FROM airports LIMIT 10;

   • SELECT * FROM flights LIMIT 10;

Create a context set in Bigtable Studio

In this section, create a context set named flights-assistant. This context set doesn't include any context set file uploaded to it.

1. In the Google Cloud console, go to the Bigtable page.

   Go to Bigtable

2. Select an instance from the list.

3. In the navigation menu, click Bigtable Studio.

4. In the Explorer pane, next to Context sets, click View actions ().

5. Click Create context set.

6. In Context set name, enter flights-assistant.

7. Click Create.

Test QueryData in Studio

In this section, use the flights-assistant context set by asking natural language questions to generate a SQL query. Since the context set doesn't have any context set file uploaded to it and Bigtable schemas only expose column family names (info) rather than individual column qualifiers, QueryData guesses column qualifiers and generates sub-optimal queries.

1. In the Explorer pane, next to your context set, click View actions ().
2. Click Test context set.
3. In the query editor, click Generate SQL using QueryData with: flights-assistant.

4. Enter the following natural language question to generate a SQL query, and click Generate.

   Find flights from SFO to JFK.
   

   Review the SQL query. Without a context set, QueryData sees the info column family (MAP<BYTES, BYTES>) on the flights table, but not the column qualifiers departure_airport and arrival_airport, so it guesses qualifier names such as origin and destination:

     SELECT
       _key,
       info
     FROM
       flights
     WHERE
       CAST(info['origin'] AS STRING) = 'SFO'
       AND CAST(info['destination'] AS STRING) = 'JFK';
   

5. In the Generate SQL using QueryData with: flights-assistant window, click Edit.

6. Enter the following natural language question to generate a SQL query, and click Update.

   Tell me flights that can help me beat nighttime traffic if traveling from New York
   

   The database fails to understand the term nighttime traffic and guesses column qualifiers that don't exist in the flights table as the following query shows.

   Note: GenAI models are nondeterministic, meaning the same prompt may yield different responses across separate calls due to the probabilistic nature of the output generation.

   -- Assuming 'nighttime traffic' refers to flights departing during the night,
   -- defined here as between 8:00 PM (20:00) and 5:00 AM (05:00).
   SELECT
     CAST(_key AS STRING) AS flight_id,
     CAST(info['flight_number'] AS STRING) AS flight_number,
     CAST(info['origin'] AS STRING) AS origin,
     CAST(info['destination'] AS STRING) AS destination,
     CAST(info['departure_time'] AS STRING) AS departure_time
   FROM
     flights
   WHERE
     CAST(info['origin'] AS STRING) = 'New York'
     AND (
       EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 20
       OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 5
     );
   

7. In the Generate SQL using QueryData with: flights-assistant window, click Edit.

8. Enter the following natural language question to generate a SQL query, and click Update.

   Show me flights to Raleigh-Durham
   

   Without value search context, QueryData guesses a column qualifier and filters on Raleigh-Durham. Because the flights table stores the city as Raleigh-durham under info['arrival_city'], the query won't return any rows.

   Note: GenAI models are nondeterministic, meaning the same prompt may yield different responses across separate calls due to the probabilistic nature of the output generation.

   SELECT
     _key,
     info
   FROM
     flights
   WHERE
     CAST(info['destination_city'] AS STRING) = 'Raleigh-Durham';
   

Generate context for the context set

In this section, you prepare the environment and create a context file that helps improve the context set's querying capabilities.

Set up your environment

Before you can start generating context, you must prepare your environment.

To set up your environment, perform the following steps:

1. Install Antigravity CLI. For more information, see Get Started with Antigravity CLI.
2. Install the Google Cloud CLI.

3. Set up Application Default Credentials (ADC). Run the following commands in your terminal to authenticate and select your project:

   gcloud auth application-default login

4. Install uv, a Python package and project manager that is a prerequisite for the context engineering agent. If you don't already have Python on your system, uv can install it for you.

5. Install the context engineering agent:

   agy plugin install https://github.com/GoogleCloudPlatform/db-context-enrichment/tree/main/plugin

6. In your terminal, start the Antigravity CLI.

   agy

7. Set up a database connection for context generation using MCP Toolbox. The connection is defined in the tools.yaml configuration file.

   To create the tools.yaml configuration file in your current directory, enter a prompt such as:

   Help me set up a database connection.
   

   Follow the instructions provided by the skill. For more information about the tools.yaml file, see MCP Toolbox documentation.

   Note: If this connection is not established, the extension returns error messages, such as Error Discovering tools from mcp_toolbox, and context generation fails to work.

8. To reload the configuration after the tools.yaml file is created, run the following command in the Antigravity CLI and follow the instruction to reload the toolbox MCP server:

   /mcp

   1. Select db-context-engineering_toolbox.

   2. Select Restart.

9. Verify that the MCP toolbox and the context engineering agent plugin are connected and ready to use.

   /mcp

Generate template context

In this section, to address the issue from the previous section where QueryData didn't know the flights column qualifiers or the term nighttime traffic, define templates in the context set file that map natural language questions to the info column family qualifiers and define nighttime traffic as traffic occurring between 5:00 PM and 7:00 PM.

To generate template context, perform the following steps:

1. Enter the following prompt into the Antigravity CLI:

   Generate templates for the following two questions and SQL queries:
   
   1. Question: "Show me flights from SFO to JFK"
   SQL:
   SELECT
     CAST(_key AS STRING) AS flight_id,
     CAST(info['airline'] AS STRING) AS airline,
     CAST(info['flight_number'] AS STRING) AS flight_number,
     CAST(info['departure_airport'] AS STRING) AS departure_airport,
     CAST(info['arrival_airport'] AS STRING) AS arrival_airport,
     CAST(info['departure_time'] AS STRING) AS departure_time,
     CAST(info['arrival_time'] AS STRING) AS arrival_time,
     CAST(info['departure_gate'] AS STRING) AS departure_gate,
     CAST(info['arrival_gate'] AS STRING) AS arrival_gate,
     CAST(info['departure_city'] AS STRING) AS departure_city,
     CAST(info['arrival_city'] AS STRING) AS arrival_city
   FROM
     flights
   WHERE
     CAST(info['departure_airport'] AS STRING) = 'SFO'
     AND CAST(info['arrival_airport'] AS STRING) = 'JFK'
   ORDER BY
     departure_time;
   
   2. Question: "Tell me flights that can help me beat nighttime traffic if traveling from New York"
   SQL:
   SELECT
     CAST(info['airline'] AS STRING) AS airline,
     CAST(info['flight_number'] AS STRING) AS flight_number,
     CAST(info['departure_airport'] AS STRING) AS departure_airport,
     CAST(info['departure_time'] AS STRING) AS departure_time
   FROM
     flights
   WHERE
     CAST(info['departure_city'] AS STRING) = 'New York'
     AND (
       EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17
       OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19
     )
   ORDER BY
     departure_time;
   

2. The agent converts your input into a specific format that refines the context set's performance across a wide range of user queries. For more information, see Context sets overview.

3. Review the generated query template. You can either save the query template as a new agent context file or append it to an existing agent context file.

4. Prompt the agent to save the template:

   Save it to context_set.json.
   

   The agent creates the file in the same directory, with the following content:

   {
     "templates": [
       {
         "nl_query": "Show me flights from SFO to JFK",
         "sql": "SELECT CAST(_key AS STRING) AS flight_id, CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['arrival_airport'] AS STRING) AS arrival_airport, CAST(info['departure_time'] AS STRING) AS departure_time, CAST(info['arrival_time'] AS STRING) AS arrival_time, CAST(info['departure_gate'] AS STRING) AS departure_gate, CAST(info['arrival_gate'] AS STRING) AS arrival_gate, CAST(info['departure_city'] AS STRING) AS departure_city, CAST(info['arrival_city'] AS STRING) AS arrival_city FROM flights WHERE CAST(info['departure_airport'] AS STRING) = 'SFO' AND CAST(info['arrival_airport'] AS STRING) = 'JFK' ORDER BY departure_time",
         "intent": "Find flights from SFO to JFK.",
         "manifest": "Find flights from a given departure airport code to a given arrival airport code.",
         "parameterized": {
           "parameterized_sql": "SELECT CAST(_key AS STRING) AS flight_id, CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['arrival_airport'] AS STRING) AS arrival_airport, CAST(info['departure_time'] AS STRING) AS departure_time, CAST(info['arrival_time'] AS STRING) AS arrival_time, CAST(info['departure_gate'] AS STRING) AS departure_gate, CAST(info['arrival_gate'] AS STRING) AS arrival_gate, CAST(info['departure_city'] AS STRING) AS departure_city, CAST(info['arrival_city'] AS STRING) AS arrival_city FROM flights WHERE CAST(info['departure_airport'] AS STRING) = ? AND CAST(info['arrival_airport'] AS STRING) = ? ORDER BY departure_time",
           "parameterized_intent": "Find flights from ? to ?."
         }
       },
       {
         "nl_query": "Tell me flights that can help me beat nighttime traffic if traveling from New York",
         "sql": "SELECT CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['departure_time'] AS STRING) AS departure_time FROM flights WHERE CAST(info['departure_city'] AS STRING) = 'New York' AND (EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17 OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19) ORDER BY departure_time",
         "intent": "Tell me flights that can help me beat nighttime traffic if traveling from New York",
         "manifest": "Tell me flights that can help me beat nighttime traffic if traveling from a given city",
         "parameterized": {
           "parameterized_sql": "SELECT CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['departure_time'] AS STRING) AS departure_time FROM flights WHERE CAST(info['departure_city'] AS STRING) = ? AND (EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17 OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19) ORDER BY departure_time",
           "parameterized_intent": "Tell me flights that can help me beat nighttime traffic if traveling from ?"
         }
       }
     ]
   }
   

Generate value search context

In this section, you generate value search context to help context set logic map value phrases to specific values stored in your Bigtable columns using case-insensitive exact string matching. For example, if a user asks for flights to "Raleigh-Durham," value search maps this to the stored database value "Raleigh-durham" (airport code RDU).

To generate value search context, perform the following steps:

1. Enter the following prompt into the agent harness.

   Generate a case-insensitive value search on table "airports" for column "info['city']" with concept "Airport City" using match function "EXACT_MATCH_STRINGS".

2. Review the generated value search definition. You can either save the value search definition as a new context set file or append it to an existing context set file.

3. Prompt the agent with Append the context to context_set.json. This adds the value search definition to the context file created in the earlier section.

4. Enter the database instance and database name for which the context set file was generated.

   The existing context file is updated with the value search definition, with the following content:

   {
     "templates": [
       {
         "nl_query": "Show me flights from SFO to JFK",
         "sql": "SELECT CAST(_key AS STRING) AS flight_id, CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['arrival_airport'] AS STRING) AS arrival_airport, CAST(info['departure_time'] AS STRING) AS departure_time, CAST(info['arrival_time'] AS STRING) AS arrival_time, CAST(info['departure_gate'] AS STRING) AS departure_gate, CAST(info['arrival_gate'] AS STRING) AS arrival_gate, CAST(info['departure_city'] AS STRING) AS departure_city, CAST(info['arrival_city'] AS STRING) AS arrival_city FROM flights WHERE CAST(info['departure_airport'] AS STRING) = 'SFO' AND CAST(info['arrival_airport'] AS STRING) = 'JFK' ORDER BY departure_time",
         "intent": "Find flights from SFO to JFK.",
         "manifest": "Find flights from a given departure airport code to a given arrival airport code.",
         "parameterized": {
           "parameterized_sql": "SELECT CAST(_key AS STRING) AS flight_id, CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['arrival_airport'] AS STRING) AS arrival_airport, CAST(info['departure_time'] AS STRING) AS departure_time, CAST(info['arrival_time'] AS STRING) AS arrival_time, CAST(info['departure_gate'] AS STRING) AS departure_gate, CAST(info['arrival_gate'] AS STRING) AS arrival_gate, CAST(info['departure_city'] AS STRING) AS departure_city, CAST(info['arrival_city'] AS STRING) AS arrival_city FROM flights WHERE CAST(info['departure_airport'] AS STRING) = ? AND CAST(info['arrival_airport'] AS STRING) = ? ORDER BY departure_time",
           "parameterized_intent": "Find flights from ? to ?."
         }
       },
       {
         "nl_query": "Tell me flights that can help me beat nighttime traffic if traveling from New York",
         "sql": "SELECT CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['departure_time'] AS STRING) AS departure_time FROM flights WHERE CAST(info['departure_city'] AS STRING) = 'New York' AND (EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17 OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19) ORDER BY departure_time",
         "intent": "Tell me flights that can help me beat nighttime traffic if traveling from New York",
         "manifest": "Tell me flights that can help me beat nighttime traffic if traveling from a given city",
         "parameterized": {
           "parameterized_sql": "SELECT CAST(info['airline'] AS STRING) AS airline, CAST(info['flight_number'] AS STRING) AS flight_number, CAST(info['departure_airport'] AS STRING) AS departure_airport, CAST(info['departure_time'] AS STRING) AS departure_time FROM flights WHERE CAST(info['departure_city'] AS STRING) = ? AND (EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17 OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19) ORDER BY departure_time",
           "parameterized_intent": "Tell me flights that can help me beat nighttime traffic if traveling from ?"
         }
       }
     ],
     "facets": [],
     "value_searches": [
       {
         "query": "SELECT CAST(T.info['city'] AS STRING) AS value, 'info:city' AS `columns`, 'Airport City' AS concept_type, 0.0 AS distance, CONCAT('iata=', CAST(T.info['iata'] AS STRING), ', name=', CAST(T.info['name'] AS STRING)) AS context FROM `airports` AS T WHERE LOWER(CAST(T.info['city'] AS STRING)) = LOWER(CAST($value AS STRING))",
         "concept_type": "Airport City",
         "description": "Exact case-insensitive match on airport city name in the airports table."
       }
     ]
   }
   

Upload the context set file to the QueryData

In this section, you upload the context set file to QueryData, so that it improves the QueryData's SQL generation capabilities on your database.

To upload the context, perform the following steps:

1. In the Google Cloud console, go to the Bigtable page.

   Go to Bigtable

2. Select an instance from the list.

3. In the navigation menu, click Bigtable Studio.

4. In the Explorer pane, under Context sets and next to the flights-assistant context set, click the View actions () icon.

5. Click Edit context set.

6. Click Browse in the Upload context file section, and then select the context set file generated earlier.

7. Click Save.

Generate SQL query using QueryData

In this section, you use the context set file you uploaded to ask natural language questions. This lets you verify that QueryData correctly understands and applies definitions for terms like nighttime traffic and other related phrases.

Note: GenAI models are nondeterministic, meaning the same prompt may yield different responses across separate calls due to the probabilistic nature of the output generation.

To generate SQL queries, perform the following steps:

1. In the Explorer pane, next to your context set, click View actions ().
2. Click Test context set.
3. In the query editor, click Generate SQL using QueryData with: flights-assistant.

4. To generate a SQL query, enter the following natural language question, and then click Generate.

   Tell me flights that can help me beat nighttime traffic if traveling from New York
   

   The generated SQL query looks similar to the following:

   SELECT
     CAST(info['airline'] AS STRING) AS airline,
     CAST(info['flight_number'] AS STRING) AS flight_number,
     CAST(info['departure_airport'] AS STRING) AS departure_airport,
     CAST(info['departure_time'] AS STRING) AS departure_time
   FROM
     flights
   WHERE
     CAST(info['departure_city'] AS STRING) = 'New York'
     AND (
       EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17
       OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19
     )
   ORDER BY
     departure_time;
   

   This is the same question you added to QueryData's context. Observe that QueryData can now accurately interpret the term nighttime traffic.

   Although the context originates from one particular question, QueryData uses it to enhance SQL generation for a wide range of similar questions.

5. In the Generate SQL using QueryData with: flights-assistant window, click Edit.

6. Enter the following similar question to generate a SQL query, and click Update.

   What are the flights that can help me avoid evening traffic if departing from Boston
   

   Since the question replaces the term nighttime traffic with a similar term, evening traffic, QueryData provides a consistent answer to this question by applying the same interpretation.

   The generated SQL query looks similar to the following:

   SELECT
     CAST(info['airline'] AS STRING) AS airline,
     CAST(info['flight_number'] AS STRING) AS flight_number,
     CAST(info['departure_airport'] AS STRING) AS departure_airport,
     CAST(info['departure_time'] AS STRING) AS departure_time
   FROM
     flights
   WHERE
     CAST(info['departure_city'] AS STRING) = 'Boston'
     AND (
       EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) < 17
       OR EXTRACT(HOUR FROM TIMESTAMP(CAST(info['departure_time'] AS STRING))) >= 19
     )
   ORDER BY
     departure_time;
   

7. In the Generate SQL using QueryData with: flights-assistant window, and then click Edit.

8. Enter the following question to generate a SQL query, and then click Update.

   Show me flights to Raleigh-Durham
   

   The generated SQL query looks similar to the following:

   SELECT
     CAST(_key AS STRING) AS flight_id,
     CAST(info['airline'] AS STRING) AS airline,
     CAST(info['flight_number'] AS STRING) AS flight_number,
     CAST(info['departure_airport'] AS STRING) AS departure_airport,
     CAST(info['arrival_airport'] AS STRING) AS arrival_airport,
     CAST(info['departure_time'] AS STRING) AS departure_time,
     CAST(info['arrival_time'] AS STRING) AS arrival_time,
     CAST(info['departure_gate'] AS STRING) AS departure_gate,
     CAST(info['arrival_gate'] AS STRING) AS arrival_gate,
     CAST(info['departure_city'] AS STRING) AS departure_city,
     CAST(info['arrival_city'] AS STRING) AS arrival_city
   FROM
     flights
   WHERE
     CAST(info['arrival_city'] AS STRING) = 'Raleigh-durham'
   ORDER BY
     departure_time;
   

   Observe that QueryData can now accurately map Raleigh-Durham to the stored value "Raleigh-durham" (RDU).

Integrate QueryData with your application

In this section, you create a data agent for a flight-finding application. This data agent provides a conversational interface to the flights and airports tables that you created earlier. It also explains how to create and integrate this data agent into your application using Agent Development Kit (ADK), the Gemini Data Analytics QueryData MCP tool, and a context set to improve quality of the responses.

Note: GenAI models are nondeterministic, meaning the same prompt may yield different responses across separate calls due to the probabilistic nature of the output generation.

1. Download MCP Toolbox version 1.14.0 or later. MCP Toolbox exposes the data agent as a tool for applications to connect with. The MCP Toolbox differs from the context engineering agent you installed earlier, which generates context.

2. Set up Application Default Credentials (ADC).

   gcloud auth application-default login

3. Find the ID of the context set you created earlier. For more information about how to find the context set ID, see Find the context set ID.

4. Append the following to the tools.yaml configuration to connect to the data agent using the MCP Toolbox. For more information, see Gemini Data Analytics Source and Gemini Data Analytics QueryData tool.

   ---
   kind: source
   name: gda-api-source
   type: cloud-gemini-data-analytics
   projectId: "PROJECT_ID"
   ---
   kind: tool
   name: cloud_gda_query_tool
   type: cloud-gemini-data-analytics-query
   source: gda-api-source
   description: Use this tool to send natural language queries to the Gemini Data Analytics API and receive SQL, natural language answers, and explanations.
   location: "REGION_ID"
   context:
     datasourceReferences:
       bigtableReference:
         databaseReference:
           projectId: "PROJECT_ID"
           instanceId: "INSTANCE_ID"
         agentContextReference:
           contextSetId: "CONTEXT_SET_ID"
   generationOptions:
     generateQueryResult: true
     generateNaturalLanguageAnswer: true
     generateExplanation: true
     generateDisambiguationQuestion: true
   

   Replace the following:

   • PROJECT_ID: your Google Cloud project ID.
   • REGION_ID: the region of your Bigtable cluster (for example, us-central1).
   • INSTANCE_ID: the ID of your Bigtable instance.
   • CONTEXT_SET_ID: the context set ID. For more information about how to find the context set ID, see Find the context set ID.

5. Run the MCP Toolbox server with the tools.yaml file.

   ./toolbox --config PATH_TO_TOOLS_YAML

   Replace PATH_TO_TOOLS_YAML with the path to the tools.yaml file you created earlier.

   Note: Don't close the terminal window where the MCP Toolbox server is running.

6. Create an ADK application that invokes Gemini Data Analytics QueryData tool using the MCP Toolbox's Python SDK. For more information about how to use the MCP Toolbox's Python SDK, see the quickstart for Toolbox and for Python ADK, see the quickstart for ADK.

   1. Create a directory to store the application, for example flight-assistant-app.

   2. Change directory to the flight-assistant-app directory.

      mkdir flight-assistant-app
      cd flight-assistant-app

   3. Run the following commands under the flight-assistant-app directory to create a virtual environment and install required components.

      uv init
      uv add google-adk toolbox-core google-genai

   4. Set up an ADK agent.

      1. Create an ADK agent.

         uv run adk create my_agent

      2. Select the gemini-2.5-flash model, or newer.

      3. Select Google AI, and enter your Gemini API key. For more information about how to find your API key, see Using Gemini API keys. (Alternatively, if you don't need a free trial, you can select Vertex AI and specify a Google Cloud project with billing enabled).

   5. Replace the contents of the agent.py file with the following Flight Data Assistant sample application code.

      from typing import cast
      
      from google.adk.agents.llm_agent import Agent
      from google.adk.agents.llm_agent import ToolUnion
      
      from toolbox_core import ToolboxSyncClient
      
      TOOLBOX_URL = "http://127.0.0.1:5000"
      
      INSTRUCTION = """
      # ROLE
      You are a friendly and factual flight data assistant. Your goal is to help users find the best flights for their needs by providing accurate information with a helpful, professional tone.
      - use the Query Data Tool to answer the user's question, if the tool fails to generate a valid query, ask the user to clarify their question.
      
      # OPERATIONAL CONSTRAINTS
      - TOOL LIMITATION: You only have access to the Query Data Tool. Do not claim to have capabilities beyond what this tool provides.
      - TRANSPARENCY POLICY: Maintain a seamless user experience. Never mention that you are using a tool, querying a database, or generating SQL. Frame all responses as your own direct assistance.
      - SCOPE MANAGEMENT: If a user asks for something beyond your capabilities, politely state that you cannot perform that specific task. Guide the user towards what you can help with.
      
      # COMMUNICATION STYLE
      - Be concise and scannable when listing answers.
      - Maintain a helpful, professional persona.
      
      =====
      
      # QUERY DATA TOOL
      
      Inputs:
      1. query: A natural language formulation of a database query.
      
      Outputs: (all optional)
      1. disambiguation_question: Clarification questions or comments where the tool needs the users' input.
      2. generated_query: The generated query for the user query.
      3. intent_explanation: An explanation for why the tool produced `generated_query`.
      4. query_result: The result of executing `generated_query`.
      5. natural_language_answer: The natural language answer that summarizes the `query` and `query_result`.
      
      Usage guidance:
      1. If `disambiguation_question` is produced, then solicit the needed inputs from the user and try the tool with a new `query` that has the needed clarification.
      2. If `natural_language_answer` is produced, use `intent_explanation` and `generated_query` to see if you need to clarify any assumptions for the user.
      3. If the tool output indicates failure or empty results, explain that clearly using the provided reasoning.
      """
      
      client = ToolboxSyncClient(TOOLBOX_URL)
      
      mcp_tool = client.load_tool("cloud_gda_query_tool")
      
      root_agent = Agent(
          model="gemini-2.5-flash",  # Or newer.
          name="root_agent",
          instruction=INSTRUCTION,
          tools=cast(list[ToolUnion], [mcp_tool]),
      )
      

   Note: The instruction contains a system prompt that sets up a flight assistant data agent. It also instructs the agent how to use the Gemini Data Analytics QueryData tool you set up in the tools.yaml file you created earlier.

7. To start the application, run the following commands under the flight-assistant-app directory. Access the ADK web server at http://127.0.0.1:8000.

   uv run adk web --port 8000

8. Enter any text, such as hello, to start interacting with the agent.

   The ADK agent answers general questions and calls the required MCP tools.

9. Enter the following flight-related question.

   How many flights depart from the west side?
   

   The MCP tool is called to answer this question. Because the database doesn't define the west side, QueryData assumes a list of West Coast airports and returns the flight count and explanation, which the agent uses to clarify the assumption in its response:

   There are 253 flights departing from the west side.
   
   Please note that "the west side" is not explicitly defined in our records, so this count assumes flights departing from major West Coast airports: Los Angeles (LAX), San Francisco (SFO), San Diego (SAN), Seattle (SEA), Portland (PDX), Las Vegas (LAS), and Phoenix (PHX). If you had a different set of airports in mind, please let me know!
   

10. Enter a question similar to that in the query template generated for the agent.

    Help me find flights from San Francisco that avoid the evening rush hour.
    

    Based on the QueryData context added earlier, the MCP tool understands that evening traffic occurs between 5 PM and 7 PM. The MCP tool returns the associated data for the agent to use in constructing its response.

    Here are the flights departing from San Francisco that avoid the evening rush hour (defined as 5 PM to 7 PM):
    
    * UA 1532 departing at 05:50:00
    * UA 1158 departing at 05:57:00
    * CY 922 departing at 06:38:00
    * OO 5441 departing at 07:08:00
    * UA 616 departing at 07:14:00
    * AA 24 departing at 07:14:00
    * B6 434 departing at 08:00:00
    * AA 242 departing at 08:18:00
    * UA 1739 departing at 08:22:00
    * OO 6336 departing at 08:32:00
    * US 1784 departing at 08:47:00
    * DL 1631 departing at 09:00:00
    * DL 1106 departing at 09:06:00
    * OO 5427 departing at 09:06:00
    * CY 352 departing at 09:25:00
    

11. Enter a question based on the concept type that you added in the QueryData agent context.

    Show me flights to Raleigh-Durham
    

    Based on the value search context added earlier, the agent understands that "Raleigh-Durham" matches the stored city "Raleigh-durham" (airport code RDU) and returns the associated data for the agent to use in constructing its response.

    Here is the flight heading to Raleigh-Durham (RDU):
    
    * Flight UA 1568 departs from San Francisco (SFO) at Gate A30 on 2025-01-02 at 14:55:00 and arrives at Raleigh-Durham (RDU) at Gate A26 on 2025-01-02 at 23:03:00.
    

Iterate agent performance

The ADK web UI lets you inspect the request and response from the Gemini Data Analytics QueryData MCP tool. You can use this response to observe the tool responses such as generated SQL query, result set, intent explanation, disambiguation question, and natural language answer, to help you confirm the correctness of your agent's responses.

For example, for the input text How many flights depart from the west side? that you entered earlier, click the agent bubble. In the Event tab in the left navigation, expand the functionResponse to see the following response.

{"result": "{"generatedQuery":"SELECT COUNT(*) AS flight_count FROM flights WHERE CAST(info['departure_airport'] AS STRING) IN ('LAX', 'SFO', 'SAN', 'SEA', 'PDX', 'LAS', 'PHX')","intentExplanation":"The user is asking for the number of flights departing from the 'west side'. Since there is no explicit definition or column for 'west side' in the schema, I will assume this refers to major airports on the West Coast of the United States (e.g., LAX, SFO, SAN, SEA, PDX, LAS, PHX).","queryResult":{"columns":[{"name":"flight_count"}],"rows":[{"values":[{"value":"253"}]}],"totalRowCount":"1"},"naturalLanguageAnswer":"There are 253 flights departing from West Coast airports (LAX, SFO, SAN, SEA, PDX, LAS, PHX)."}"}

Refine response accuracy

You can continuously refine the accuracy of responses from the Gemini Data Analytics QueryData tool by adding additional context. Use the context engineering agent to generate context, and then upload the updated context set file to the existing flights-assistant data agent. For more information, see Manage context sets in Bigtable Studio. The console immediately ingests new context after you upload it, enabling you to enhance the agent's accuracy without any application downtime.

Multiple agents

In your development environment, you can perform A/B testing on multiple data agent contexts by assigning distinct names to tools in your tools.yaml file. For example, you can create unique tools.yaml configurations by defining two cloud-gemini-data-analytics-query tools with different names, such as cloud_gda_query_tool_v1 and cloud_gda_query_tool_v2. This setup lets you implement application logic that programmatically selects the required context version by choosing the corresponding tool name.

The following example tools.yaml shows how to set up multiple data agents for a database source:

kind: source
name: gda-api-source
type: cloud-gemini-data-analytics
projectId: PROJECT_ID
---
kind: tool
name: cloud_gda_query_tool_v1
type: cloud-gemini-data-analytics-query
source: gda-api-source
context:
  datasourceReferences:
    DB_SOURCE:
      databaseReference: ...
      agentContextReference:
        contextSetId: "V1_YOUR_CONTEXT_SET_ID"
generationOptions: ...
---
kind: tool
name: cloud_gda_query_tool_v2
type: cloud-gemini-data-analytics-query
source: gda-api-source
context:
  datasourceReferences:
    DB_SOURCE:
      databaseReference: ...
      agentContextReference:
        contextSetId: "V2_YOUR_CONTEXT_SET_ID"
generationOptions: ...

Replace the following:

• PROJECT_ID: your Google Cloud project ID.
• V1_YOUR_CONTEXT_SET_ID: the context set ID for version 1.
• V2_YOUR_CONTEXT_SET_ID: the context set ID for version 2.
• DB_SOURCE: the database source configurations.

Clean up

After you've finished following this tutorial, delete the resources that you created to avoid incurring ongoing costs. The following sections describe how to delete these resources.

Delete the context set

Before you delete the instance, delete the context set that you created.

1. In the Google Cloud console, go to the Bigtable page.

   Go to Bigtable

2. Select an instance from the list.

3. In the navigation menu, click Bigtable Studio.

4. In the Explorer pane, next to your context set, click View actions ().

5. Click Delete context set.

6. In the Delete context set window, enter flights-assistant.

7. Click Confirm.

Delete the instance

When you delete the instance that you created in the before you begin section, you also delete all of the objects you created.

1. In the Google Cloud console, go to the Bigtable page.

   Go to Bigtable

2. Click the name of the instance that you want to delete, for example, Test Instance.

3. Click Delete instance.

4. Confirm that you want to delete the instance by entering the instance ID and clicking Delete.

What's next

• Learn more about context sets.
• Learn how to define authored context for database data sources.