Integra QueryData con un'applicazione

Questo tutorial descrive come configurare e utilizzare QueryData in Bigtable utilizzando la console Google Cloud e come integrarlo con la tua applicazione. Scopri come creare il file del set di contesti, creare un set di contesti che utilizza il file del set di contesti, utilizzare MCP Toolbox per chiamare il metodo QueryData nell'API Conversational Analytics per generare query SQL per domande in linguaggio naturale e integrarlo con la tua applicazione.

Per saperne di più, consulta la panoramica di QueryData.

Obiettivi

Questo tutorial illustra come raggiungere i seguenti obiettivi:

  • Creare tabelle di database e compilarle con i dati.
  • Crea un file di set di contesti con l'agente di progettazione del contesto.
  • Crea un set di contesti e carica un file del set di contesti.
  • Testa QueryData e genera query SQL in Bigtable Studio.
  • Integra QueryData con la tua applicazione utilizzando lo strumento QueryData di Gemini Data Analytics in MCP Toolbox.
  • Aggiungi il grounding alle risposte dell'LLM utilizzando query di ricerca di valore.

Costi

In questo documento vengono utilizzati i seguenti componenti fatturabili di Google Cloud:

Per generare una stima dei costi in base all'utilizzo previsto, utilizza il Calcolatore prezzi.

I nuovi utenti di Google Cloud potrebbero avere diritto a una prova senza costi.

Per evitare l'addebito di ulteriori costi, elimina le risorse create al termine delle attività descritte in questo documento. Per ulteriori informazioni, consulta Esegui la pulizia.

Prima di iniziare

Completa i seguenti prerequisiti prima di creare un set di contesto.

Attiva i servizi richiesti

Abilita i seguenti servizi per il tuo progetto:

Prepara un'istanza Bigtable

Assicurati che sia disponibile un'istanza Bigtable. Per saperne di più, consulta Crea un'istanza.

Installa l'interfaccia a riga di comando cbt

Installa e configura l'interfaccia a riga di comando cbt per creare tabelle e compilarle con i dati. Per saperne di più, consulta la panoramica dell'interfaccia a riga di comando di cbt.

Ruoli e autorizzazioni richiesti

Crea lo schema e le tabelle flights e airports

In questa sezione creerai le tabelle di database flights e airports per questo tutorial.

  1. Configura il progetto e l'istanza predefiniti in ~/.cbtrc:
    echo project = PROJECT_ID >> ~/.cbtrc
    echo instance = INSTANCE_ID >> ~/.cbtrc
    dove:
    • PROJECT_ID: il tuo ID progetto Google Cloud .
    • INSTANCE_ID: l'ID istanza Bigtable.
  2. Esegui questo comando per creare la tabella airports e la famiglia di colonne info:

    cbt createtable airports "families=info"
  3. Esegui questo comando per creare la tabella flights e la famiglia di colonne info:

    cbt createtable flights "families=info"

Compila le tabelle flights e airports

In questa sezione, compili le tabelle flights e airports utilizzando il comando cbt import.

  1. Crea un file denominato airports.csv con i seguenti contenuti:

    ,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. Importa i dati dal file airports.csv nella tabella airports:

    cbt import airports airports.csv
  3. Crea un file denominato flights.csv con i seguenti contenuti:

    ,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. Importa i dati dal file flights.csv nella tabella flights:

    cbt import flights flights.csv
  5. In Bigtable Studio, esegui le seguenti query per verificare che le tabelle siano compilate:

    • SELECT * FROM airports LIMIT 10;
    • SELECT * FROM flights LIMIT 10;

Crea un set di contesti in Bigtable Studio

In questa sezione, crea un set di contesti denominato flights-assistant. Questo set di contesto non include alcun file di set di contesto caricato.

  1. Nella console Google Cloud , vai alla pagina Bigtable.

    Vai a Bigtable

  2. Seleziona un'istanza dall'elenco.

  3. Nel menu di navigazione, fai clic su Bigtable Studio.

  4. Nel riquadro Explorer, accanto a Set di contesto, fai clic su Visualizza azioni ().

  5. Fai clic su Crea set di contesti.

  6. In Nome set di contesti, inserisci flights-assistant.

  7. Fai clic su Crea.

Testa QueryData in Studio

In questa sezione, utilizza il set di contesto flights-assistant ponendo domande in linguaggio naturale per generare una query SQL. Poiché nel set di contesto non è stato caricato alcun file di set di contesto e gli schemi Bigtable espongono solo i nomi famiglia di colonne (info) anziché i singoli qualificatori di colonna, QueryData indovina i qualificatori di colonna e genera query non ottimali.

  1. Nel riquadro Explorer, accanto al set di contesto, fai clic su Visualizza azioni ().
  2. Fai clic su Set di contesti di test.
  3. Nell'editor di query, fai clic su Genera SQL utilizzando QueryData con: flights-assistant.
  4. Inserisci la seguente domanda in linguaggio naturale per generare una query SQL e fai clic su Genera.

    Find flights from SFO to JFK.
    

    Esamina la query SQL. Senza un set di contesto, QueryData vede la famiglia di colonne info (MAP<BYTES, BYTES>) nella tabella flights, ma non i qualificatori di colonna departure_airport e arrival_airport, quindi indovina i nomi dei qualificatori come origin e destination:

      SELECT
        _key,
        info
      FROM
        flights
      WHERE
        CAST(info['origin'] AS STRING) = 'SFO'
        AND CAST(info['destination'] AS STRING) = 'JFK';
    
  5. Nella finestra Genera SQL utilizzando QueryData con: flights-assistant, fai clic su Modifica.

  6. Inserisci la seguente domanda in linguaggio naturale per generare una query SQL e fai clic su Aggiorna.

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

    Il database non riesce a comprendere il termine nighttime traffic e indovina i qualificatori di colonna che non esistono nella tabella flights, come mostra la seguente query.

    -- 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. Nella finestra Genera SQL utilizzando QueryData con: flights-assistant, fai clic su Modifica.

  8. Inserisci la seguente domanda in linguaggio naturale per generare una query SQL e fai clic su Aggiorna.

    Show me flights to Raleigh-Durham
    

    Senza il contesto di ricerca del valore, QueryData indovina un qualificatore di colonna e filtra in base a Raleigh-Durham. Poiché la tabella flights memorizza la città come Raleigh-durham in info['arrival_city'], la query non restituirà alcuna riga.

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

Genera il contesto per il set di contesti

In questa sezione, preparerai l'ambiente e creerai un file di contesto che aiuta a migliorare le funzionalità di query del set di contesto.

Configura l'ambiente

Prima di poter iniziare a generare il contesto, devi preparare l'ambiente.

Per configurare l'ambiente, segui questi passaggi:

  1. Installa Antigravity CLI. Per saperne di più, consulta Inizia a utilizzare Antigravity CLI.
  2. Installa Google Cloud CLI.
  3. Configura le Credenziali predefinite dell'applicazione (ADC). Esegui questi comandi nel terminale per autenticarti e selezionare il tuo progetto:

    gcloud auth application-default login
  4. Installa uv, un pacchetto Python e un project manager che è un prerequisito per l'agente di motore contestuale. Se non hai già Python sul tuo sistema, uv può installarlo per te.

  5. Installa l'agente di context engineering:

    agy plugin install https://github.com/GoogleCloudPlatform/db-context-enrichment/tree/main/plugin
  6. Nel terminale, avvia l'interfaccia a riga di comando di Antigravity.

    agy
  7. Configura una connessione al database per la generazione del contesto utilizzando MCP Toolbox. La connessione è definita nel file di configurazione tools.yaml.

    Per creare il file di configurazione tools.yaml nella directory attuale, inserisci un prompt come:

    Help me set up a database connection.
    

    Segui le istruzioni fornite dalla skill. Per saperne di più sul file tools.yaml, consulta la documentazione di MCP Toolbox.

  8. Per ricaricare la configurazione dopo aver creato il file tools.yaml, esegui il comando seguente nell'interfaccia a riga di comando di Antigravity e segui le istruzioni per ricaricare il server MCP della toolbox:

    /mcp
    1. Seleziona db-context-engineering_toolbox.

    2. Seleziona Restart.

  9. Verifica che il toolbox MCP e il plugin agenti di context engineering siano connessi e pronti per l'uso.

    /mcp

Genera il contesto del template

In questa sezione, per risolvere il problema della sezione precedente in cui QueryData non conosceva i qualificatori di colonna flights o il termine nighttime traffic, definisci i modelli nel file del set di contesto che mappano le domande in linguaggio naturale ai qualificatori della famiglia di colonne info e definisci nighttime traffic come traffico che si verifica tra le 17:00 e le 19:00.

Per generare il contesto del template, segui questi passaggi:

  1. Inserisci il seguente prompt nell'interfaccia a riga di comando di Antigravity:

    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. L'agente converte l'input in un formato specifico che perfeziona le prestazioni del set di contesto in un'ampia gamma di query degli utenti. Per saperne di più, consulta la panoramica dei set di contesti.

  3. Esamina il template di query generato. Puoi salvare il modello di query come nuovo file di contesto dell'agente o aggiungerlo a un file di contesto dell'agente esistente.

  4. Chiedi all'agente di salvare il template:

    Save it to context_set.json.
    

    L'agente crea il file nella stessa directory, con i seguenti contenuti:

    {
      "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 ?"
          }
        }
      ]
    }
    

Genera il contesto di ricerca del valore

In questa sezione, generi il contesto di ricerca dei valori per aiutare la logica del set di contesto a mappare le frasi dei valori a valori specifici archiviati nelle colonne Bigtable utilizzando la corrispondenza esatta delle stringhe senza distinzione tra maiuscole e minuscole. Ad esempio, se un utente chiede voli per "Raleigh-Durham", la ricerca per valore mappa questa richiesta al valore del database memorizzato "Raleigh-durham" (codice aeroporto RDU).

Per generare il contesto di ricerca del valore, segui questi passaggi:

  1. Inserisci il seguente prompt nell'infrastruttura agentica.

    Generate a case-insensitive value search on table "airports" for column "info['city']" with concept "Airport City" using match function "EXACT_MATCH_STRINGS".
  2. Rivedi la definizione della ricerca del valore generata. Puoi salvare la definizione della ricerca di valori come nuovo file di set di contesto o aggiungerla a un file di set di contesto esistente.

  3. Invia un prompt all'agente con Append the context to context_set.json. In questo modo, la definizione della ricerca del valore viene aggiunta al file di contesto creato nella sezione precedente.

  4. Inserisci l'istanza del database e il nome del database per cui è stato generato il file del set di contesto.

    Il file di contesto esistente viene aggiornato con la definizione di ricerca del valore, con i seguenti contenuti:

    {
      "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."
        }
      ]
    }
    

Carica il file del set di contesti in QueryData

In questa sezione caricherai il file del set di contesti in QueryData, in modo da migliorare le funzionalità di generazione SQL di QueryData nel tuo database.

Per caricare il contesto, segui questi passaggi:

  1. Nella console Google Cloud , vai alla pagina Bigtable.

    Vai a Bigtable

  2. Seleziona un'istanza dall'elenco.

  3. Nel menu di navigazione, fai clic su Bigtable Studio.

  4. Nel riquadro Explorer, in Set di contesto e accanto al set di contesto flights-assistant, fai clic sull'icona Visualizza azioni ().

  5. Fai clic su Modifica set di contesti.

  6. Fai clic su Sfoglia nella sezione Carica file di contesto, quindi seleziona il file del set di contesto generato in precedenza.

  7. Fai clic su Salva.

Genera una query SQL utilizzando QueryData

In questa sezione utilizzerai il file del set di contesto che hai caricato per porre domande in linguaggio naturale. In questo modo puoi verificare che QueryData comprenda e applichi correttamente le definizioni di termini come nighttime traffic e altre frasi correlate.

Per generare query SQL, segui questi passaggi:

  1. Nel riquadro Explorer, accanto al set di contesto, fai clic su Visualizza azioni ().
  2. Fai clic su Set di contesti di test.
  3. Nell'editor di query, fai clic su Genera SQL utilizzando QueryData con: flights-assistant.
  4. Per generare una query SQL, inserisci la seguente domanda in linguaggio naturale, quindi fai clic su Genera.

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

    La query SQL generata è simile alla seguente:

    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;
    

    Questa è la stessa domanda che hai aggiunto al contesto di QueryData. Osserva che QueryData ora può interpretare con precisione il termine nighttime traffic.

    Sebbene il contesto provenga da una domanda specifica, QueryData lo utilizza per migliorare la generazione di SQL per un'ampia gamma di domande simili.

  5. Nella finestra Genera SQL utilizzando QueryData con: flights-assistant, fai clic su Modifica.

  6. Inserisci la seguente domanda simile per generare una query SQL e fai clic su Aggiorna.

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

    Poiché la domanda sostituisce il termine nighttime traffic con un termine simile, evening traffic, QueryData fornisce una risposta coerente a questa domanda applicando la stessa interpretazione.

    La query SQL generata è simile alla seguente:

    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. Nella finestra Genera SQL utilizzando QueryData con: flights-assistant, fai clic su Modifica.

  8. Inserisci la seguente domanda per generare una query SQL, quindi fai clic su Aggiorna.

    Show me flights to Raleigh-Durham
    

    La query SQL generata è simile alla seguente:

    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;
    

    Osserva che QueryData ora può mappare con precisione Raleigh-Durham al valore memorizzato "Raleigh-durham" (RDU).

Integra QueryData con la tua applicazione

In questa sezione creerai un agente per i dati per un'applicazione di ricerca di voli. Questo agente per i dati fornisce un'interfaccia di conversazione per le tabelle flights e airports che hai creato in precedenza. Spiega inoltre come creare e integrare questo agente per i dati nella tua applicazione utilizzando l'Agent Development Kit (ADK), lo strumento MCP QueryData di Gemini Data Analytics e un set di contesti per migliorare la qualità delle risposte.

  1. Scarica MCP Toolbox versione 1.14.0 o successive. MCP Toolbox espone l'agente per i dati come strumento a cui le applicazioni possono connettersi. MCP Toolbox è diverso dall'agente di context engineering che hai installato in precedenza, che genera il contesto.

  2. Configura le Credenziali predefinite dell'applicazione (ADC).

    gcloud auth application-default login
  3. Trova l'ID del set di contesti che hai creato in precedenza. Per saperne di più su come trovare l'ID del set di contesti, consulta Trova l'ID del set di contesti.

  4. Aggiungi quanto segue alla configurazione di tools.yaml per connetterti all'agente per i dati utilizzando MCP Toolbox. Per saperne di più, consulta Origine Gemini Data Analytics e Strumento QueryData di Gemini Data Analytics.

    ---
    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
    

    Sostituisci quanto segue:

    • PROJECT_ID: il tuo ID progetto Google Cloud .
    • REGION_ID: la regione del tuo cluster Bigtable (ad esempio, us-central1).
    • INSTANCE_ID: l'ID dell'istanza Bigtable.
    • CONTEXT_SET_ID: l'ID del set di contesti. Per saperne di più su come trovare l'ID del set di contesti, consulta Trova l'ID del set di contesti.
  5. Esegui il server MCP Toolbox con il file tools.yaml.

    ./toolbox --config PATH_TO_TOOLS_YAML

    Sostituisci PATH_TO_TOOLS_YAML con il percorso del file tools.yaml che hai creato in precedenza.

  6. Crea un'applicazione ADK che richiama lo strumento QueryData di Gemini Data Analytics utilizzando l'SDK Python di MCP Toolbox. Per saperne di più su come utilizzare l'SDK Python di MCP Toolbox, consulta la guida rapida per Toolbox e per Python ADK, consulta la guida rapida per ADK.

    1. Crea una directory in cui archiviare l'applicazione, ad esempio flight-assistant-app.
    2. Cambia la directory impostandola su flight-assistant-app.

      mkdir flight-assistant-app
      cd flight-assistant-app
    3. Esegui questi comandi nella directory flight-assistant-app per creare un ambiente virtuale e installare i componenti richiesti.

      uv init
      uv add google-adk toolbox-core google-genai
    4. Configura un agente ADK.

      1. Crea un agente ADK.

        uv run adk create my_agent
      2. Seleziona il modello gemini-2.5-flash o uno più recente.

      3. Seleziona Google AI e inserisci la tua chiave API Gemini. Per saperne di più su come trovare la tua chiave API, consulta Utilizza le chiavi API Gemini. (In alternativa, se non hai bisogno di una prova senza costi, puoi selezionare Vertex AI e specificare un progetto Google Cloud con fatturazione abilitata).

    5. Sostituisci i contenuti del file agent.py con il seguente codice dell'applicazione di esempio Flight Data Assistant.

      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]),
      )
      
  7. Per avviare l'applicazione, esegui i seguenti comandi nella directory flight-assistant-app. Accedi al server web ADK all'indirizzo http://127.0.0.1:8000.

    uv run adk web --port 8000
  8. Inserisci un testo qualsiasi, ad esempio hello, per iniziare a interagire con l'agente.

    L'agente ADK risponde alle domande generali e chiama gli strumenti MCP richiesti.

  9. Inserisci la seguente domanda relativa ai voli.

    How many flights depart from the west side?
    

    Lo strumento MCP viene chiamato per rispondere a questa domanda. Poiché il database non definisce the west side, QueryData presuppone un elenco di aeroporti della West Coast e restituisce il numero di voli e la spiegazione, che l'agente utilizza per chiarire l'ipotesi nella sua risposta:

    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. Inserisci una domanda simile a quella nel template di query generato per l'agente.

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

    In base al contesto QueryData aggiunto in precedenza, lo strumento MCP comprende che evening traffic si verifica tra le 17:00 e le 19:00. Lo strumento MCP restituisce i dati associati che l'agente può utilizzare per creare la sua risposta.

    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. Inserisci una domanda basata sul tipo di concetto che hai aggiunto nel contesto dell'agente QueryData.

    Show me flights to Raleigh-Durham
    

    In base al contesto di ricerca del valore aggiunto in precedenza, l'agente comprende che "Raleigh-Durham" corrisponde alla città memorizzata "Raleigh-durham" (codice aeroporto RDU) e restituisce i dati associati che l'agente utilizzerà per creare la risposta.

    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.
    

Esegui l'iterazione delle prestazioni dell'agente

La UI web dell'ADK ti consente di esaminare la richiesta e la risposta dello strumento MCP QueryData di Gemini Data Analytics. Puoi utilizzare questa risposta per osservare le risposte dello strumento, come la query SQL generata, il set di risultati, la spiegazione dell'intent, la domanda di disambiguazione e la risposta in linguaggio naturale, per verificare la correttezza delle risposte dell'agente.

Ad esempio, per il testo di input How many flights depart from the west side? che hai inserito in precedenza, fai clic sul fumetto dell'agente. Nella scheda Evento nel riquadro di navigazione a sinistra, espandi functionResponse per visualizzare la seguente risposta.

{"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)."}"}

Perfeziona l'accuratezza della risposta

Puoi perfezionare continuamente l'accuratezza delle risposte dello strumento QueryData di Gemini Data Analytics aggiungendo ulteriore contesto. Utilizza l'agente di progettazione del contesto per generare il contesto, quindi carica il file del set di contesti aggiornato nell'agente per i dati flights-assistant esistente. Per saperne di più, consulta Gestisci i set di contesto in Bigtable Studio. La console acquisisce immediatamente il nuovo contesto dopo il caricamento, consentendoti di migliorare l'accuratezza dell'agente senza tempi di inattività dell'applicazione.

Più agenti

Nel tuo ambiente di sviluppo, puoi eseguire test A/B su più contesti di agenti per i dati assegnando nomi distinti agli strumenti nel file tools.yaml. Ad esempio, puoi creare configurazioni tools.yaml univoche definendo due strumenti cloud-gemini-data-analytics-query con nomi diversi, come cloud_gda_query_tool_v1 e cloud_gda_query_tool_v2. Questa configurazione ti consente di implementare la logica dell'applicazione che seleziona in modo programmatico la versione del contesto richiesta scegliendo il nome dello strumento corrispondente.

L'esempio tools.yaml seguente mostra come configurare più agenti per i dati per un'origine database:

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: ...

Sostituisci quanto segue:

  • PROJECT_ID: il tuo ID progetto Google Cloud .
  • V1_YOUR_CONTEXT_SET_ID: l'ID del set di contesto per la versione 1.
  • V2_YOUR_CONTEXT_SET_ID: l'ID del set di contesto per la versione 2.
  • DB_SOURCE: le configurazioni dell'origine del database.

Esegui la pulizia

Al termine di questo tutorial, elimina le risorse che hai creato per evitare l'addebito di costi ricorrenti. Le seguenti sezioni descrivono come eliminare queste risorse.

Elimina il set di contesti

Prima di eliminare l'istanza, elimina il set di contesti che hai creato.

  1. Nella console Google Cloud , vai alla pagina Bigtable.

    Vai a Bigtable

  2. Seleziona un'istanza dall'elenco.

  3. Nel menu di navigazione, fai clic su Bigtable Studio.

  4. Nel riquadro Explorer, accanto al set di contesto, fai clic su Visualizza azioni ().

  5. Fai clic su Elimina set di contesti.

  6. Nella finestra Elimina set di contesti, inserisci flights-assistant.

  7. Fai clic su Conferma.

Elimina l'istanza

Quando elimini l'istanza che hai creato nella sezione Prima di iniziare, elimini anche tutti gli oggetti che hai creato.

  1. Nella console Google Cloud , vai alla pagina Bigtable.

    Vai a Bigtable

  2. Fai clic sul nome dell'istanza che vuoi eliminare, ad esempio Test Instance.

  3. Fai clic su Elimina istanza.

  4. Conferma di voler eliminare l'istanza inserendo l'ID istanza e facendo clic su Elimina.

Passaggi successivi