System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE train_station_management.train_cars (
    car_id character varying(64) NOT NULL, -- Unique identifier for the train car
    train_id character varying(64) NOT NULL, -- Foreign key referencing trains
    car_number character varying(10) NOT NULL, -- Identifier of the car within the train set
    car_type character varying(64) NOT NULL, -- e.g., Locomotive, Passenger, Sleeper, Dining, Baggage
    class character varying(32), -- e.g., First, Business, Economy (null for non-passenger cars)
    capacity integer, -- Passenger capacity of this specific car (null for non-passenger cars)
    features text, -- Comma-separated list of features (e.g., 'WiFi', 'Power Outlet', 'Accessible Restroom')
    PRIMARY KEY (car_id),
    FOREIGN KEY (train_id) REFERENCES train_station_management.trains(train_id)
)
CREATE TABLE train_station_management.routes (
    route_id character varying(64) NOT NULL, -- Unique identifier for the route
    route_name character varying(128) NOT NULL, -- Name of the route (e.g., 'Northeast Corridor')
    description text, -- Description of the route
    origin_station_id character varying(64) NOT NULL, -- Starting station
    destination_station_id character varying(64) NOT NULL, -- Final station
    is_active boolean NOT NULL DEFAULT true, -- Is the route currently operational?
    PRIMARY KEY (route_id),
    FOREIGN KEY (origin_station_id) REFERENCES train_station_management.stations(station_id),
    FOREIGN KEY (destination_station_id) REFERENCES train_station_management.stations(station_id)
)
CREATE TABLE train_station_management.route_stations (
    route_station_id character varying(64) NOT NULL, -- Unique ID for this route-station link
    route_id character varying(64) NOT NULL, -- Foreign key referencing routes
    station_id character varying(64) NOT NULL, -- Foreign key referencing stations
    sequence_order integer NOT NULL, -- Order of the station in the route (1 for origin, 2, 3...)
    distance_from_previous_km numeric(10, 2), -- Distance from the previous station in the sequence
    typical_stop_duration_minutes integer, -- Typical dwell time at this station
    PRIMARY KEY (route_station_id),
    UNIQUE (route_id, station_id),
    UNIQUE (route_id, sequence_order),
    FOREIGN KEY (route_id) REFERENCES train_station_management.routes(route_id),
    FOREIGN KEY (station_id) REFERENCES train_station_management.stations(station_id)
)
CREATE TABLE train_station_management.schedules (
    schedule_id character varying(64) NOT NULL, -- Unique identifier for a specific scheduled trip
    train_id character varying(64) NOT NULL, -- Foreign key referencing the train used
    route_id character varying(64) NOT NULL, -- Foreign key referencing the route taken
    departure_datetime timestamp with time zone NOT NULL, -- Scheduled departure time from origin station
    arrival_datetime timestamp with time zone NOT NULL, -- Scheduled arrival time at destination station
    status character varying(32) NOT NULL DEFAULT 'Scheduled', -- e.g., Scheduled, On Time, Delayed, Cancelled, Arrived
    notes text, -- Any notes regarding this specific trip (e.g., reason for delay)
    PRIMARY KEY (schedule_id),
    FOREIGN KEY (train_id) REFERENCES train_station_management.trains(train_id),
    FOREIGN KEY (route_id) REFERENCES train_station_management.routes(route_id)
)
CREATE TABLE train_station_management.passengers (
    passenger_id character varying(64) NOT NULL, -- Unique identifier for the passenger
    first_name character varying(100) NOT NULL, -- Passenger's first name
    last_name character varying(100) NOT NULL, -- Passenger's last name
    email character varying(128) UNIQUE, -- Passenger's email address
    phone_number character varying(32) UNIQUE, -- Passenger's phone number
    date_of_birth date, -- Passenger's date of birth
    loyalty_program_id character varying(64), -- ID for loyalty program, if applicable
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- When the passenger record was created
    PRIMARY KEY (passenger_id)
)
CREATE TABLE train_station_management.bookings (
    booking_id character varying(64) NOT NULL, -- Unique identifier for the booking
    passenger_id character varying(64) NOT NULL, -- Foreign key referencing the passenger
    schedule_id character varying(64) NOT NULL, -- Foreign key referencing the scheduled trip
    booking_datetime timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- When the booking was made
    status character varying(32) NOT NULL DEFAULT 'Confirmed', -- e.g., Confirmed, Cancelled, Pending
    total_price numeric(12, 2) NOT NULL, -- Total price for all tickets in this booking
    currency_code character varying(3) NOT NULL DEFAULT 'USD', -- Currency of the price
    special_requests text, -- Any special requests (e.g., wheelchair assistance)
    PRIMARY KEY (booking_id),
    FOREIGN KEY (passenger_id) REFERENCES train_station_management.passengers(passenger_id),
    FOREIGN KEY (schedule_id) REFERENCES train_station_management.schedules(schedule_id)
)
CREATE TABLE train_station_management.staff (
    staff_id character varying(64) NOT NULL, -- Unique identifier for the staff member
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    role character varying(64) NOT NULL, -- e.g., Station Master, Ticket Agent, Conductor, Engineer, Maintenance Crew
    primary_station_id character varying(64), -- Base station for the staff member (nullable for mobile staff)
    employee_number character varying(32) UNIQUE NOT NULL, -- Unique employee identifier
    hire_date date NOT NULL,
    contact_email character varying(128) UNIQUE,
    contact_phone character varying(32),
    is_active boolean NOT NULL DEFAULT true, -- Is the staff member currently employed?
    PRIMARY KEY (staff_id),
    FOREIGN KEY (primary_station_id) REFERENCES train_station_management.stations(station_id)
)

[User] Can you help me get the total number of passenger cars for each train car type in the database?

[Assistant]
SELECT car_type, COUNT(*) as total_cars
FROM train_station_management.train_cars
WHERE car_type = 'Passenger'
GROUP BY car_type;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE token_basic_info ( coin_id character varying(100) NOT NULL, -- the id of the token token_name character varying(100) NOT NULL, -- the token's name token_symbol character varying(100) NOT NULL, -- the token's symbol token_address character varying(100) NOT NULL, -- the token's address chain text, -- the chain that the token resides price double precision, -- the current price of the token price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days highest_price_24h double precision, -- the highest price of the token in 24 hours lowest_price_24h double precision,  -- the lowest price of the token in 24 hours market_cap double precision, -- the market cap of the token market_cap_rank bigint, -- the rank of the token market cap in desc market_cap_change_percentage_24h text, -- the percentage of market cap changes in 24 hours total_volume text, -- the trade volum of the token both in decentralized exchange(DEX) and centralized exchange(CEX) narrative text, -- the category or narrative of the token trend_rank biging, -- the trending rank of the token, value 1 expresses the most popular token. ,PRIMARY KEY (coin_id, chain) )
CREATE TABLE narrative_info ( narrative character varying(512) NOT NULL, -- the id of narrative top_3_coins text, -- the top 3 tokens in the narrative price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour in the narrative price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours in the narrative price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days in the narrative market_cap double precision, -- the market cap of the narrative volume_24h double precision, -- the trade volume of the narrative trend_rank bigint, -- the trending rank of the narrative, value 1 expresses the most popular narrative token_num bigint, -- total token number in the narrative ,PRIMARY KEY (narrative) )
CREATE TABLE smart_money_profit ( address character varying(100) NOT NULL, -- the user's address rank INT, -- the rank of the address in trade performance, value 1 expresses the best address. profit numeric(38,6), -- the profit user made in a month roi numeric(38,2), -- the roi of the user in a month realized_ratio numeric(38,2), -- the percentage of the user's realized profit most_profit_token character varying(100), -- the token symbol of the user's most profitable trade last_trade_time character varying(100), -- the last trade time of the user chain character varying(100), -- the chain that the address resides PRIMARY KEY (address, chain) )
CREATE TABLE smart_money_token_performance ( token_address character varying(100) NOT NULL, -- the token's address token_symbol character varying(100), -- the tokens's symbol pnl numeric(38,2), -- the profit users made on this token net_flow numeric(38,2), -- the netflow of the token, means the money user spent minus the the money user sold of this token avg_cost numeric(38,16), -- the average cost price of user spent on this token price double precision, -- the current price of the token realized_ratio numeric(10,2), -- the ratio user sold of the token roi numeric(10,2), -- the roi users made of this token chain character varying(100), -- the chain that the token resides PRIMARY KEY (token_address, chain) )
CREATE TABLE smart_money_token_inflow ( token_address character varying(100) NOT NULL, -- the token's address token_symbol character varying(100), -- the tokens's symbol token_amount numeric(38,2), -- the absolute value of the amount if user bought minus  the amount user sold of this token usd_value numeric(38,2), -- the absolute usd value of the bought token minus sold token avg_price numeric(38,6), -- the average cost price of user spent on this token type int, -- the direction of the trade on this token. 1 means buying, 2 means selling address_amount integer, -- the amount of the user bought this token narrative character varying(100), -- the category or narrative of the token chain character varying(100), -- the chain that the token resides ,PRIMARY KEY (token_address, chain) )

[User] For each narrative in smart_money_token_inflow, calculate the total usd_value and avg_price from buy transactions (type=1) and include the narrative's token count from narrative_info. Show narrative, chain, total_usd_value, avg_price, and token_num, ordered by total_usd_value descending, limit to 5.

[Assistant]
SELECT i.narrative, i.chain, SUM(i.usd_value) AS total_usd_value, AVG(i.avg_price) AS avg_price, ni.token_num
FROM smart_money_token_inflow AS i
JOIN narrative_info AS ni ON i.narrative = ni.narrative
WHERE i.type = 1
GROUP BY i.narrative, i.chain, ni.token_num
ORDER BY total_usd_value DESC
LIMIT 5;

[User] Please filter results to only include narratives where the total token_amount exceeds 1000.

[Assistant]
SELECT i.narrative, i.chain, SUM(i.usd_value) AS total_usd_value, AVG(i.avg_price) AS avg_price, ni.token_num
FROM smart_money_token_inflow AS i
JOIN narrative_info AS ni ON i.narrative = ni.narrative
WHERE i.type = 1
GROUP BY i.narrative, i.chain, ni.token_num
HAVING SUM(i.token_amount) > 1000
ORDER BY total_usd_value DESC
LIMIT 5;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE transportation.locations ( location_id text, name text, type text, address_line1 text, city text, state_province text, postal_code text, country text, latitude numeric, longitude numeric, timezone text )
CREATE TABLE transportation.maintenance_logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the maintenance record
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle serviced
    service_date date NOT NULL, -- date the service was performed
    odometer_reading integer, -- vehicle mileage at time of service
    service_type character varying(128) NOT NULL, -- type of service (e.g., Oil Change, Tire Rotation, Engine Repair)
    description text NOT NULL, -- detailed description of work done
    cost numeric(10, 2), -- cost of the service
    mechanic_name character varying(128), -- name or ID of the mechanic/shop
    next_service_due_date date, -- recommended date for next service
    PRIMARY KEY (log_id)
)
CREATE TABLE transportation.fuel_logs (
    fuel_log_id character varying(64) NOT NULL,  -- unique identifier for the fuel log entry
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle fueled
    trip_id character varying(64), -- optional: identifier of the trip during which fueling occurred
    log_timestamp timestamp with time zone NOT NULL, -- time when fueling occurred
    fuel_type character varying(32) NOT NULL, -- type of fuel added (matches vehicle's fuel type)
    quantity numeric(10, 3) NOT NULL, -- amount of fuel added (e.g., Liters, Gallons, kWh)
    unit character varying(16) NOT NULL, -- unit of quantity (e.g., L, gal, kWh)
    cost_per_unit numeric(8, 4), -- price per unit of fuel
    total_cost numeric(10, 2) NOT NULL, -- total cost of the fuel purchase
    odometer_reading integer, -- vehicle mileage at time of fueling
    location_id character varying(64), -- identifier of the fueling station/location
    PRIMARY KEY (fuel_log_id)
)
CREATE TABLE transportation.passengers (
    passenger_id character varying(64) NOT NULL,  -- unique identifier for the passenger
    first_name character varying(128) NOT NULL, -- passenger's first name
    last_name character varying(128) NOT NULL, -- passenger's last name
    email character varying(128) UNIQUE, -- email address
    phone_number character varying(32) UNIQUE, -- phone number
    date_of_birth date, -- passenger's date of birth
    loyalty_program_id character varying(64), -- identifier for loyalty program membership
    created_at timestamp with time zone NOT NULL, -- time when the passenger record was created
    PRIMARY KEY (passenger_id)
)
CREATE TABLE transportation.bookings ( booking_id character varying(64) NOT NULL, passenger_id character varying(64) NOT NULL, trip_id character varying(64) NOT NULL, seat_number character varying(16), booking_time timestamp with time zone NOT NULL, status character varying(32) NOT NULL, fare numeric(10, 2) NOT NULL, payment_transaction_id character varying(128), special_requests text, PRIMARY KEY (booking_id) )

[User] Show all maintenance logs including the vehicle ID, service date, service type, and cost.

[Assistant] SELECT vehicle_id, service_date, service_type, cost FROM transportation.maintenance_logs;

[User] Only include records where the service type is 'Repair'.

[Assistant] SELECT vehicle_id, service_date, service_type, cost FROM transportation.maintenance_logs WHERE service_type = 'Repair';

[User] Also include the mechanic's name and only show logs from the year 2022.

[Assistant] SELECT vehicle_id, service_date, service_type, cost, mechanic_name FROM transportation.maintenance_logs WHERE service_type = 'Repair' AND service_date >= '2022-01-01' AND service_date < '2023-01-01';

[User] Actually, show logs from 2023 instead of 2022.

[Assistant] SELECT vehicle_id, service_date, service_type, cost, mechanic_name FROM transportation.maintenance_logs WHERE service_type = 'Repair' AND service_date >= '2023-01-01' AND service_date < '2024-01-01';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE hospitality_technology.service_orders ( order_id text PRIMARY KEY, reservation_id text, guest_id text, service_id text, staff_id_ordered text, staff_id_delivered text, order_timestamp timestamp, delivery_timestamp timestamp, quantity int, unit_price numeric, total_price numeric, status text, notes text, bill_id text )

[User] Get the total_quantity and total_revenue (sum of total_price) for each staff member who placed orders (staff_id_ordered).

[Assistant]
SELECT staff_id_ordered,
       SUM(quantity) AS total_quantity,
       SUM(total_price) AS total_revenue
FROM hospitality_technology.service_orders
GROUP BY staff_id_ordered;

[User] Filter to staff who have delivered at least one order (staff_id_delivered is not null).

[Assistant]
SELECT staff_id_ordered,
       SUM(quantity) AS total_quantity,
       SUM(total_price) AS total_revenue
FROM hospitality_technology.service_orders
WHERE staff_id_delivered IS NOT NULL
GROUP BY staff_id_ordered;

[User] For these staff members, list each order along with the previous order they placed, including first_order_timestamp and second_order_timestamp, and the time difference in hours.

[Assistant]
SELECT t1.staff_id_ordered,
       t1.order_id AS first_order_id,
       t2.order_id AS second_order_id,
       t1.order_timestamp AS first_order_timestamp,
       t2.order_timestamp AS second_order_timestamp,
       EXTRACT(EPOCH FROM (t2.order_timestamp - t1.order_timestamp)) / 3600 AS hours_diff
FROM hospitality_technology.service_orders t1
JOIN hospitality_technology.service_orders t2
  ON t1.staff_id_ordered = t2.staff_id_ordered
 AND t2.order_timestamp > t1.order_timestamp
 AND NOT EXISTS (
       SELECT 1 FROM hospitality_technology.service_orders t3
       WHERE t3.staff_id_ordered = t1.staff_id_ordered
         AND t3.order_timestamp > t1.order_timestamp
         AND t3.order_timestamp < t2.order_timestamp
   )
WHERE t1.staff_id_delivered IS NOT NULL
  AND t2.staff_id_delivered IS NOT NULL
ORDER BY t1.staff_id_ordered, t1.order_timestamp;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE social_media.conversation_participants ( participant_id.text, conversation_id.text, user_id.text, joined_at.timestamp, last_read_at.timestamp )

[User] Show me all participants who joined any conversation before January 1st, 2024. Return participant_id, user_id, conversation_id and the joined_at timestamp.

[Assistant] SELECT participant_id, user_id, conversation_id, joined_at FROM social_media.conversation_participants WHERE joined_at < '2024-01-01';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE legal_services.clients ( client_id text PRIMARY KEY, first_name text, last_name text, company_name text, email text UNIQUE, phone text, address text, date_registered timestamp, status text )
CREATE TABLE legal_services.lawyers (
    lawyer_id character varying(64) NOT NULL,  -- unique identifier for the lawyer
    first_name character varying(100) NOT NULL, -- lawyer's first name
    last_name character varying(100) NOT NULL, -- lawyer's last name
    bar_number character varying(64) UNIQUE NOT NULL, -- lawyer's bar association number
    firm_id character varying(64), -- FK to law_firms table
    email character varying(128) UNIQUE NOT NULL, -- lawyer's professional email
    phone character varying(32), -- lawyer's contact phone number
    specialization text, -- areas of legal expertise
    hire_date timestamp NOT NULL, -- date the lawyer was hired or joined
    is_partner boolean DEFAULT false, -- flag indicating if the lawyer is a partner
    PRIMARY KEY (lawyer_id)
)
CREATE TABLE legal_services.law_firms ( firm_id text PRIMARY KEY, firm_name text, address text, phone text, website text, founded_date date, managing_partner_id text )
CREATE TABLE legal_services.cases ( case_id.text, case_number.text, case_name.text, client_id.text, lead_lawyer_id.text, case_type.text, status.text, date_opened.timestamp, date_closed.timestamp, description.text, court_jurisdiction.text )
CREATE TABLE legal_services.documents (
    document_id character varying(64) NOT NULL,  -- unique identifier for the document
    case_id character varying(64) NOT NULL, -- FK to cases table
    document_name character varying(255) NOT NULL, -- name of the document file
    document_type character varying(100), -- e.g., Pleading, Contract, Evidence, Correspondence
    storage_path text NOT NULL, -- path or reference to the document storage location
    uploaded_by_lawyer_id character varying(64), -- FK to lawyers table (who uploaded it)
    upload_timestamp timestamp NOT NULL, -- time the document was uploaded
    version integer DEFAULT 1, -- document version number
    description text, -- brief description or notes about the document
    PRIMARY KEY (document_id)
)
CREATE TABLE legal_services.time_entries (
    entry_id character varying(64) NOT NULL,  -- unique identifier for the time entry
    case_id character varying(64) NOT NULL, -- FK to cases table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table (who performed the work)
    date_worked date NOT NULL, -- date the work was performed
    hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), -- duration of work in hours (e.g., 1.5 for 1h 30m)
    billing_rate numeric(10, 2) NOT NULL, -- hourly rate applied for this entry
    description text NOT NULL, -- detailed description of the work performed
    is_billable boolean DEFAULT true, -- whether this time entry is billable to the client
    is_billed boolean DEFAULT false, -- whether this entry has been included in an invoice
    invoice_id character varying(64), -- FK to invoices table (once billed)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the entry was recorded
    PRIMARY KEY (entry_id)
)
CREATE TABLE legal_services.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    client_id character varying(64) NOT NULL, -- FK to clients table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table
    case_id character varying(64), -- FK to cases table (optional, if related to a specific case)
    start_time timestamp NOT NULL, -- scheduled start date and time
    end_time timestamp NOT NULL, -- scheduled end date and time
    location text, -- location of the meeting (address or virtual link)
    subject character varying(255), -- subject or purpose of the appointment
    notes text, -- additional notes for the appointment
    status character varying(50) NOT NULL, -- e.g., Scheduled, Completed, Canceled, Rescheduled
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (appointment_id)
)

[User] Show the total number of documents uploaded for each lawyer. Display the lawyer's first and last name and the document count.

[Assistant]
SELECT l.first_name, l.last_name, COUNT(d.document_id) AS document_count
FROM legal_services.lawyers l
JOIN legal_services.documents d ON l.lawyer_id = d.uploaded_by_lawyer_id
GROUP BY l.lawyer_id, l.first_name, l.last_name;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE project_fundraising_record ( id character varying(32) NOT NULL, project_id character varying(32) NOT NULL, project_name character varying(128) NOT NULL, rounds_name character varying(32), investment_value numeric(38,14), investment_date character varying(128), introduction character varying(128), valuation numeric(38,14) )
CREATE TABLE token_basic_info ( coin_id text, token_name text, token_symbol text, token_address text, chain text, price numeric, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, highest_price_24h numeric, lowest_price_24h numeric, market_cap numeric, market_cap_rank numeric, market_cap_change_percentage_24h text, total_volume text, narrative text, trend_rank numeric )
 "CREATE TABLE narrative_info (",
    "narrative character varying(512) NOT NULL, -- the id of narrative",
    "top_3_coins text, -- the top 3 tokens in the narrative",
    "price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour in the narrative",
    "price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours in the narrative",
    "price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days in the narrative",
    "market_cap double precision, -- the market cap of the narrative",
    "volume_24h double precision, -- the trade volume of the narrative",
    "trend_rank bigint, -- the trending rank of the narrative, value 1 expresses the most popular narrative",
    "token_num bigint, -- total token number in the narrative",
    ",PRIMARY KEY (narrative));"

CREATE TABLE token_dexpool_info ( pair_address character varying(512) NOT NULL, -- the id of dexpool token_name character varying(100) NOT NULL, -- the name of the token in the dexpool token_symbol character varying(100) NOT NULL, -- the token's symbol chain text, -- the chain that the dexpool resides price double precision, -- the current price of the token price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour price_change_percentage_6h double precision, -- change in value divided by the absolute price value of the original token price in 6 hours price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours makers_24h double precision, -- the makers of the dex pool in 24 hours volume_24h double precision, -- the trade volume of the dex pool in 24 hours liquidity double precision, -- the liquidity of the dex pool market_cap double precision, -- the market cap of the token trend_rank bigint, -- the rank of token in the dex pool of recent trending, value 1 expresses the most popular token. ,PRIMARY KEY (pair_address, chain) )
  "CREATE TABLE cex_token_balance (",
    "snapshot_time character varying(32) NOT NULL,  -- the snapshot time of record, converted from original timestamp",
    "chain character varying(128) NOT NULL, -- the chain that the token resides",
    "address character varying(128) NOT NULL, -- the address that holds the assets, owned by a CEX",
    "exchange character varying(512) NOT NULL, -- a centralized exchange name",
    "token_address character varying(128) NOT NULL, -- token contract address",
    "token_symbol character varying(512), --token symbol",
    "balance numeric(38,10), -- token balance",
    "usd_value numeric(38,14), -- value of the token held in USD",
    "price double precision, --price of the token in USD",
    ",PRIMARY KEY (snapshot_time, exchange, address, chain, token_address));"

CREATE TABLE smart_money_profit ( address character varying(100) NOT NULL, -- the user's address rank INT, -- the rank of the address in trade performance, value 1 expresses the best address. profit numeric(38,6), -- the profit user made in a month roi numeric(38,2), -- the roi of the user in a month realized_ratio numeric(38,2), -- the percentage of the user's realized profit most_profit_token character varying(100), -- the token symbol of the user's most profitable trade last_trade_time character varying(100), -- the last trade time of the user chain character varying(100), -- the chain that the address resides PRIMARY KEY (address, chain) )
CREATE TABLE smart_money_token_performance ( token_address text, token_symbol text, pnl numeric, net_flow numeric, avg_cost numeric, price numeric, realized_ratio numeric, roi numeric, chain text )

[User] Show all tokens on the 'Arbitrum' chain from DEX pools that have a 24-hour trading volume between $100,000 and $500,000. Display token symbol, price, and volume_24h.

[Assistant]
SELECT
  token_symbol,
  price,
  volume_24h
FROM token_dexpool_info
WHERE
  chain = 'Arbitrum' AND volume_24h BETWEEN 100000 AND 500000;

[User] Include their liquidity and 6-hour price change percentage in the results.

[Assistant]
SELECT
  token_symbol,
  price,
  volume_24h,
  liquidity,
  price_change_percentage_6h
FROM token_dexpool_info
WHERE
  chain = 'Arbitrum' AND volume_24h BETWEEN 100000 AND 500000;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE gaming_technology.game_sessions ( session_id uuid PRIMARY KEY, player_id uuid, game_id uuid, server_id uuid, start_time timestamptz, end_time timestamptz, duration_seconds int, score int, session_data jsonb )
CREATE TABLE gaming_technology.servers ( server_id.uuid, game_id.uuid, server_name.text, region.text, ip_address.text, port.integer, current_players.integer, max_players.integer, status.text, last_heartbeat.timestamptz )

[User] List for each game the server with the highest current player count and also show how many sessions that server has hosted. Include game_id, server_name, current_players, and session_count.

[Assistant] WITH session_counts AS ( SELECT s.server_id, s.game_id, s.server_name, s.current_players, COUNT(gs.session_id) AS session_count FROM gaming_technology.servers s LEFT JOIN gaming_technology.game_sessions gs ON s.server_id = gs.server_id GROUP BY s.server_id, s.game_id, s.server_name, s.current_players ), ranked AS ( SELECT sc.*, ROW_NUMBER() OVER (PARTITION BY sc.game_id ORDER BY sc.current_players DESC) AS rn FROM session_counts sc ) SELECT game_id, server_name, current_players, session_count FROM ranked WHERE rn = 1;

[User] Only include games where that top server has hosted at least 50 sessions.

[Assistant] WITH session_counts AS ( SELECT s.server_id, s.game_id, s.server_name, s.current_players, COUNT(gs.session_id) AS session_count FROM gaming_technology.servers s LEFT JOIN gaming_technology.game_sessions gs ON s.server_id = gs.server_id GROUP BY s.server_id, s.game_id, s.server_name, s.current_players HAVING COUNT(gs.session_id) >= 50 ), ranked AS ( SELECT sc.*, ROW_NUMBER() OVER (PARTITION BY sc.game_id ORDER BY sc.current_players DESC) AS rn FROM session_counts sc ) SELECT game_id, server_name, current_players, session_count FROM ranked WHERE rn = 1;

[User] Also display the region of the selected server.

[Assistant] WITH session_counts AS ( SELECT s.server_id, s.game_id, s.server_name, s.region, s.current_players, COUNT(gs.session_id) AS session_count FROM gaming_technology.servers s LEFT JOIN gaming_technology.game_sessions gs ON s.server_id = gs.server_id GROUP BY s.server_id, s.game_id, s.server_name, s.region, s.current_players HAVING COUNT(gs.session_id) >= 50 ), ranked AS ( SELECT sc.*, ROW_NUMBER() OVER (PARTITION BY sc.game_id ORDER BY sc.current_players DESC) AS rn FROM session_counts sc ) SELECT game_id, server_name, region, current_players, session_count FROM ranked WHERE rn = 1;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE web3.users ( user_id.text, username.text, email.text, password_hash.text, created_at.timestamp )

[User] For each user, show how many users registered after them. Return the user_id, username, and the count of later registrants.

[Assistant] SELECT u1.user_id, u1.username, COUNT(u2.user_id) AS later_user_count FROM web3.users u1 LEFT JOIN web3.users u2 ON u2.created_at > u1.created_at GROUP BY u1.user_id, u1.username ORDER BY u1.user_id;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE gaming_technology.players ( player_id uuid PRIMARY KEY, username text, email text, password_hash text, registration_date timestamptz, last_login timestamptz, country_code text, status text, profile_data jsonb )

[User] Can you give me a count of players for each player status?

[Assistant] SELECT status, COUNT(player_id) FROM gaming_technology.players GROUP BY status;

[User] Now, only show me the statuses that have fewer than 100 players.

[Assistant] SELECT status, COUNT(player_id) FROM gaming_technology.players GROUP BY status HAVING COUNT(player_id) < 100;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE token_metas ( block_timestamp timestamp, block_number bigint, transaction_hash text, transaction_index bigint, from_address text, contract_address text, symbol text, total_supply text, name text, decimals bigint, is_erc20 integer, is_erc721 integer, is_erc1155 integer, is_proxy integer, extra_info text, pk integer )
CREATE TABLE erc1155_approval_for_all ( block_number bigint, block_timestamp timestamp, transaction_index integer, transaction_hash text, log_index integer, contract_address text )
CREATE TABLE erc20_balances ( block_number bigint, contract_address text, wallet_address text, amount text, pk text )
CREATE TABLE erc20_balances_historical ( block_number bigint, contract_address text, wallet_address text, amount text, pk integer )
CREATE TABLE nft_holders ( block_number bigint, contract_address text, wallet_address text, token_id text, contract_type text, amount text, pk text )
CREATE TABLE nft_holder_historical ( block_number bigint, contract_address text, wallet_address text, token_id text, contract_type text, amount text, pk integer )
CREATE TABLE sui_coins ( object_id text, status text, coin_type text, balance text, owner text )
CREATE TABLE sui_coins_metadata ( object_id text, coin_type text, status text, decimals bigint, description text, icon_url text, symbol text, name text )
CREATE TABLE nft_metadata ( blockchain text, contract_address text, token_id text, contract_name text, erc_type text, amount bigint, minter text, owner text, mint_block_number bigint, mint_time bigint, mint_transaction_hash text, mint_price text, token_uri text, metadata text, name text, image_uri text, traits text, updated_at bigint, status text, rarity_score real, rarity_rank integer, unique_attribute_count integer, pk integer )
CREATE TABLE nft_collections ( blockchain text, contract_address text, name text, symbol text, deploy_block_number bigint, deploy_block_time bigint, erc_type text, owner text, traits text, description text, slug text, media_info text, image_url text, banner_image_url text, updated_at bigint, banner text, token_count bigint, floor_price text, floor_price_symbol text, floor_price_contract text, pk integer )
CREATE TABLE token_prices ( uuid text, blockchain text, address text, decimals bigint, symbol text, price real, timestamp timestamp )
CREATE TABLE token_prices_latest ( blockchain text, address text, decimals bigint, symbol text, price real, timestamp timestamp )
CREATE TABLE erc20_approval ( block_number bigint, block_timestamp timestamp, transaction_index integer, transaction_hash text, log_index integer, contract_address text, pk integer )
CREATE TABLE token_balances ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )
CREATE TABLE token_info ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text )
CREATE TABLE token_balances_bitcoin ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply text, amount text )
CREATE TABLE token_info_bitcoin ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text )
CREATE TABLE token_activities_bitcoin ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, log_index integer, type text, tick text, id text, amt decimal, from_address text, to_address text )
CREATE TABLE token_activities_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, log_index integer, type text, tick text, id text, amt decimal, from_address text, to_address text )
CREATE TABLE token_balances_avalanche ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )
CREATE TABLE token_info_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text, minted decimal, holders decimal, txs decimal, updated_timestamp timestamp, completed_timestamp timestamp, id text )

[User] Show me the top 5 NFT collections on Ethereum with the highest number of unique owners, along with their names and floor prices.

[Assistant] SELECT nc.name, nc.floor_price, COUNT(DISTINCT nh.wallet_address) AS unique_owners FROM nft_collections nc JOIN nft_holders nh ON nc.contract_address = nh.contract_address WHERE nc.blockchain = 'Ethereum' GROUP BY nc.name, nc.floor_price ORDER BY unique_owners DESC LIMIT 5;

[User] Can you modify the query to also include the banner image URL and filter to only show collections with a floor price greater than 0.5 ETH?

[Assistant] SELECT nc.name, nc.floor_price, nc.banner_image_url, COUNT(DISTINCT nh.wallet_address) AS unique_owners FROM nft_collections nc JOIN nft_holders nh ON nc.contract_address = nh.contract_address WHERE nc.blockchain = 'Ethereum' AND CAST(nc.floor_price AS decimal) > 0.5 GROUP BY nc.name, nc.floor_price, nc.banner_image_url ORDER BY unique_owners DESC LIMIT 5;

[User] Now join this with the nft_metadata table to include the average rarity score for these collections.

[Assistant] SELECT nc.name, nc.floor_price, nc.banner_image_url, AVG(nm.rarity_score) AS avg_rarity_score, COUNT(DISTINCT nh.wallet_address) AS unique_owners FROM nft_collections nc JOIN nft_holders nh ON nc.contract_address = nh.contract_address JOIN nft_metadata nm ON nc.contract_address = nm.contract_address WHERE nc.blockchain = 'Ethereum' AND CAST(nc.floor_price AS decimal) > 0.5 GROUP BY nc.name, nc.floor_price, nc.banner_image_url ORDER BY unique_owners DESC LIMIT 5;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE hospitality_technology.properties ( property_id text PRIMARY KEY, property_name text, address_line1 text, address_line2 text, city text, state_province text, postal_code text, country_code text, phone_number text, email_address text, property_type text, star_rating numeric, timezone text, manager_staff_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.rooms ( room_id text PRIMARY KEY, property_id text, room_number text, room_type_id text, floor int, status text, is_smoking boolean, features text, current_condition text, last_cleaned_at timestamp )
CREATE TABLE hospitality_technology.room_types ( room_type_id text PRIMARY KEY, property_id text, type_name text, description text, base_rate numeric, max_occupancy int, bed_type text, area_sqft numeric, amenities text )
CREATE TABLE hospitality_technology.guests ( guest_id text PRIMARY KEY, first_name text, last_name text, email text, phone_number text, date_of_birth date, address_line1 text, city text, state_province text, postal_code text, country_code text, preferences text, loyalty_member_id text, communication_consent boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.reservations ( reservation_id text PRIMARY KEY, property_id text, guest_id text, room_id text, room_type_id text, check_in_date date, check_out_date date, actual_check_in_ts timestamp, actual_check_out_ts timestamp, num_adults int, num_children int, status text, booking_source text, rate_plan_id text, total_amount numeric, amount_paid numeric, special_requests text, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.staff ( staff_id text PRIMARY KEY, property_id text, first_name text, last_name text, position text, work_email text, work_phone text, hire_date date, termination_date date, is_active boolean, access_level int, manager_id text, created_at timestamp )
CREATE TABLE hospitality_technology.services ( service_id text PRIMARY KEY, property_id text, service_name text, description text, category text, price numeric, unit text, is_available boolean, department text )
CREATE TABLE hospitality_technology.service_orders ( order_id text PRIMARY KEY, reservation_id text, guest_id text, service_id text, staff_id_ordered text, staff_id_delivered text, order_timestamp timestamp, delivery_timestamp timestamp, quantity int, unit_price numeric, total_price numeric, status text, notes text, bill_id text )
CREATE TABLE hospitality_technology.payments ( payment_id text PRIMARY KEY, reservation_id text, guest_id text, bill_id text, amount numeric, currency_code text, payment_method text, card_type text, card_last_four text, transaction_ref text, payment_timestamp timestamp, status text, staff_id_processed text, notes text )

[User] For each staff member who placed a service order, show their full name and the total revenue generated from those orders.

[Assistant] SELECT S.first_name, S.last_name, SUM(SO.total_price) AS total_generated_revenue FROM hospitality_technology.staff AS S JOIN hospitality_technology.service_orders AS SO ON S.staff_id = SO.staff_id_ordered GROUP BY S.staff_id, S.first_name, S.last_name;

[User] Only show staff members whose placed orders generated more than 500 in total revenue.

[Assistant] SELECT S.first_name, S.last_name, SUM(SO.total_price) AS total_generated_revenue FROM hospitality_technology.staff AS S JOIN hospitality_technology.service_orders AS SO ON S.staff_id = SO.staff_id_ordered GROUP BY S.staff_id, S.first_name, S.last_name HAVING SUM(SO.total_price) > 500;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE blockchain.transactions (
    transaction_id character varying(64) NOT NULL,  -- unique identifier for the transaction
    block_id character varying(64) NOT NULL, -- identifier of the block containing the transaction
    sender_address character varying(128) NOT NULL, -- address of the sender
    receiver_address character varying(128) NOT NULL, -- address of the receiver
    amount numeric(38,14) NOT NULL, -- amount transferred
    timestamp timestamp NOT NULL, -- time when the transaction was created
    signature text NOT NULL, -- digital signature of the transaction
    PRIMARY KEY (transaction_id)
)

[User] Show me transactions where the sender and receiver addresses are the same. List transaction_id, amount, and timestamp.

[Assistant] SELECT transaction_id, amount, timestamp FROM blockchain.transactions WHERE sender_address = receiver_address;

[User] Now filter these transactions to those that occurred in May 2023 with an amount greater than 1000.

[Assistant] SELECT transaction_id, amount, timestamp FROM blockchain.transactions WHERE sender_address = receiver_address AND timestamp >= '2023-05-01' AND timestamp < '2023-06-01' AND amount > 1000;

[User] For these filtered transactions, count how many times each unique address appears as both sender and receiver.

[Assistant] SELECT sender_address, COUNT(*) FROM blockchain.transactions WHERE sender_address = receiver_address AND timestamp >= '2023-05-01' AND timestamp < '2023-06-01' AND amount > 1000 GROUP BY sender_address;

[User] Order the results by the count in descending order.

[Assistant] SELECT sender_address, COUNT(*) FROM blockchain.transactions WHERE sender_address = receiver_address AND timestamp >= '2023-05-01' AND timestamp < '2023-06-01' AND amount > 1000 GROUP BY sender_address ORDER BY COUNT(*) DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE token_metas ( block_timestamp.timestamp, block_number.bigint, transaction_hash.text, transaction_index.bigint, from_address.text, contract_address.text, symbol.text, total_supply.text, name.text, decimals.bigint, is_erc20.integer, is_erc721.integer, is_erc1155.integer, is_proxy.integer, extra_info.text, pk.integer )
CREATE TABLE erc1155_approval_for_all ( block_number.bigint, block_timestamp.timestamp, transaction_index.integer, transaction_hash.text, log_index.integer, contract_address.text )
CREATE TABLE erc20_balances_historical ( block_number.bigint, contract_address.text, wallet_address.text, amount.text, pk.integer )
CREATE TABLE nft_holders ( block_number.bigint, contract_address.text, wallet_address.text, token_id.text, contract_type.text, amount.text, pk.text )
CREATE TABLE nft_holder_historical ( block_number.bigint, contract_address.text, wallet_address.text, token_id.text, contract_type.text, amount.text, pk.integer )
CREATE TABLE sui_coins ( object_id.text, status.text, coin_type.text, balance.text, owner.text )
CREATE TABLE sui_coins_metadata ( object_id.text, coin_type.text, status.text, decimals.bigint, description.text, icon_url.text, symbol.text, name.text )
CREATE TABLE sui_nfts ( object_id.text, status.text, collection_type.text, package_id.text, previous_transaction.text, display.text, owner.text, name.text )
CREATE TABLE nft_metadata ( blockchain.text, contract_address.text, token_id.text, contract_name.text, erc_type.text, amount.bigint, minter.text, owner.text, mint_block_number.bigint, mint_time.bigint, mint_transaction_hash.text, mint_price.text, token_uri.text, metadata.text, name.text, image_uri.text, traits.text, updated_at.bigint, status.text, rarity_score.real, rarity_rank.integer, unique_attribute_count.integer, pk.integer )
CREATE TABLE nft_collections ( blockchain.text, contract_address.text, name.text, symbol.text, deploy_block_number.bigint, deploy_block_time.bigint, erc_type.text, owner.text, traits.text, description.text, slug.text, media_info.text, image_url.text, banner_image_url.text, updated_at.bigint, banner.text, token_count.bigint, floor_price.text, floor_price_symbol.text, floor_price_contract.text, pk.integer )
CREATE TABLE token_prices_latest ( blockchain.text, address.text, decimals.bigint, symbol.text, price.real, timestamp.timestamp )
CREATE TABLE token_balances ( block_number.bigint, block_timestamp.timestamp, tick.text, wallet_address.text, total_supply.decimal, amount.decimal )
CREATE TABLE token_info ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, tick.text, max_supply.decimal, lim.decimal, wlim.decimal, dec.integer, creator.text )
CREATE TABLE token_activities ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE mud_holesky_redstone ( address.text, table_id.text, key_bytes.text, key0.text, key1.text, static_data.text, encoded_lengths.text, dynamic_data.text, is_deleted.boolean, block_number.bigint, log_index.bigint )
CREATE TABLE token_balances_bitcoin ( block_number.bigint, block_timestamp.timestamp, tick.text, wallet_address.text, total_supply.text, amount.text )
CREATE TABLE token_activities_bitcoin ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_activities_avalanche ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_balances_avalanche ( block_number.bigint, block_timestamp.timestamp, tick.text, wallet_address.text, total_supply.decimal, amount.decimal )
CREATE TABLE token_info_avalanche ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, tick.text, max_supply.decimal, lim.decimal, wlim.decimal, dec.integer, creator.text, minted.decimal, holders.decimal, txs.decimal, updated_timestamp.timestamp, completed_timestamp.timestamp, id.text )

[User] List all NFTs minted in the last 30 days, including their contract address, token id, and minter address.

[Assistant] SELECT contract_address, token_id, minter FROM nft_metadata WHERE mint_time >= (strftime('%s', 'now') - 2592000);

[User] Can you add the current owner and the NFT's name from the metadata as well?

[Assistant] SELECT contract_address, token_id, minter, owner, name FROM nft_metadata WHERE mint_time >= (strftime('%s', 'now') - 2592000);

[User] Now, for each of those NFTs, show the collection name by joining with nft_collections.

[Assistant] SELECT nm.contract_address, nm.token_id, nm.minter, nm.owner, nm.name AS nft_name, nc.name AS collection_name FROM nft_metadata nm JOIN nft_collections nc ON nm.contract_address = nc.contract_address WHERE nm.mint_time >= (strftime('%s', 'now') - 2592000);

[User] Only include NFTs whose rarity_score is above 80 and order by rarity_score descending.

[Assistant] SELECT nm.contract_address, nm.token_id, nm.minter, nm.owner, nm.name AS nft_name, nc.name AS collection_name, nm.rarity_score FROM nft_metadata nm JOIN nft_collections nc ON nm.contract_address = nc.contract_address WHERE nm.mint_time >= (strftime('%s', 'now') - 2592000) AND nm.rarity_score > 80 ORDER BY nm.rarity_score DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE trading_platform.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, created_at timestamp )
CREATE TABLE trading_platform.orders ( order_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, wallet_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, order_type character varying(32) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, status character varying(32) NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (order_id) )
CREATE TABLE trading_platform.trades ( trade_id text PRIMARY KEY, order_id text, buyer_id text, seller_id text, asset_id text, quantity numeric, price numeric, traded_at timestamp )
CREATE TABLE trading_platform.assets (
    asset_id character varying(64) NOT NULL,  -- unique identifier for the asset
    name character varying(128) NOT NULL, -- name of the asset
    symbol character varying(32) NOT NULL, -- symbol of the asset
    type character varying(32) NOT NULL, -- type of the asset (e.g., cryptocurrency, stock)
    PRIMARY KEY (asset_id)
)
CREATE TABLE trading_platform.utxos (
    utxo_id character varying(64) NOT NULL,  -- unique identifier for the UTXO
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that created the UTXO
    output_index integer NOT NULL, -- index of the output in the transaction
    address character varying(128) NOT NULL, -- address that can spend the UTXO
    amount numeric(38,14) NOT NULL, -- amount of the asset in the UTXO
    spent boolean NOT NULL, -- whether the UTXO has been spent
    PRIMARY KEY (utxo_id)
)
CREATE TABLE trading_platform.dapps ( dapp_id.text, name.text, description.text, url.text )
CREATE TABLE trading_platform.peers ( peer_id character varying(64) NOT NULL, ip_address character varying(15) NOT NULL, port integer NOT NULL, last_seen timestamp NOT NULL, PRIMARY KEY (peer_id) )
CREATE TABLE trading_platform.metadata (
    metadata_id character varying(64) NOT NULL,  -- unique identifier for the metadata
    asset_id character varying(64) NOT NULL, -- identifier of the asset the metadata is associated with
    key character varying(128) NOT NULL, -- key of the metadata
    value text NOT NULL, -- value of the metadata
    PRIMARY KEY (metadata_id)
)

[User] Show the details of all UTXOs with an amount greater than 5, ordered by amount descending.

[Assistant]
SELECT utxo_id, transaction_id, output_index, address, amount, spent
FROM trading_platform.utxos
WHERE amount > 5
ORDER BY amount DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE government_services.applications ( application_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, service_id character varying(64) NOT NULL, submitted_at timestamp NOT NULL, status character varying(50) NOT NULL, last_updated_at timestamp NOT NULL, assigned_employee_id character varying(64), decision_date date, notes text, reference_number character varying(100) UNIQUE, PRIMARY KEY (application_id) )

[User] List the reference number and status for applications where the notes contain the keyword 'urgent'.

[Assistant] SELECT reference_number, status FROM government_services.applications WHERE notes ILIKE '%urgent%';

[User] Among those, show only the applications with a status of 'Pending'.

[Assistant] SELECT reference_number, status FROM government_services.applications WHERE notes ILIKE '%urgent%' AND status = 'Pending';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )

[User] Find all pairs of drivers who share the same status. Include both driver_ids, full names, and the shared status.

[Assistant] SELECT d1.driver_id AS driver1_id, d1.first_name || ' ' || d1.last_name AS driver1_name, d2.driver_id AS driver2_id, d2.first_name || ' ' || d2.last_name AS driver2_name, d1.status FROM transportation.drivers d1 JOIN transportation.drivers d2 ON d1.status = d2.status AND d1.driver_id < d2.driver_id;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE hospitality_technology.payments (
    payment_id character varying(64) NOT NULL,  -- unique identifier for the payment transaction
    reservation_id character varying(64), -- FK to reservations (if payment is for a stay)
    guest_id character varying(64) NOT NULL, -- FK to guests (who paid)
    bill_id character varying(64), -- FK to bills/invoices this payment applies to
    amount numeric(12,2) NOT NULL, -- amount of the payment
    currency_code character varying(3) NOT NULL, -- ISO currency code (e.g., USD, EUR)
    payment_method character varying(50) NOT NULL, -- e.g., CreditCard, Cash, BankTransfer, Points, Voucher
    card_type character varying(50), -- e.g., Visa, MasterCard, Amex (if CC)
    card_last_four character varying(4), -- last 4 digits of CC (if CC)
    transaction_ref character varying(128), -- reference ID from payment gateway or processor
    payment_timestamp timestamp with time zone NOT NULL DEFAULT current_timestamp, -- when the payment occurred
    status character varying(50) NOT NULL, -- e.g., Pending, Succeeded, Failed, Refunded, Disputed
    staff_id_processed character varying(64), -- FK to staff (who processed the payment)
    notes text, -- notes about the payment
    PRIMARY KEY (payment_id),
    FOREIGN KEY (reservation_id) REFERENCES hospitality_technology.reservations(reservation_id),
    FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id),
    FOREIGN KEY (staff_id_processed) REFERENCES hospitality_technology.staff(staff_id)
)

[User] List all reservations that have made multiple payment transactions. Return reservation_id and payment_id for each occurrence.

[Assistant]
SELECT DISTINCT p1.reservation_id, p1.payment_id
FROM hospitality_technology.payments p1
JOIN hospitality_technology.payments p2
  ON p1.reservation_id = p2.reservation_id
  AND p1.payment_id != p2.payment_id
ORDER BY p1.reservation_id, p1.payment_id;

[User] Now show only those reservation groups where at least one payment has status 'Failed'.

[Assistant]
SELECT DISTINCT p1.reservation_id, p1.payment_id
FROM hospitality_technology.payments p1
JOIN hospitality_technology.payments p2
  ON p1.reservation_id = p2.reservation_id
WHERE EXISTS (
    SELECT 1 FROM hospitality_technology.payments pm
    WHERE pm.reservation_id = p1.reservation_id AND pm.status = 'Failed'
)
ORDER BY p1.reservation_id, p1.payment_id;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE government_services.notifications ( notification_id.text, citizen_id.text, application_id.text, message_subject.text, message_body.text, channel.text, sent_at.timestamp, status.text, related_entity_type.text, related_entity_id.text )

[User] For each application that has at least one failed notification, provide the application ID, the total number of notifications received for that application, and the count of failed notifications.

[Assistant] SELECT application_id, COUNT(*) AS total_notifications, COUNT(CASE WHEN status = 'Failed' THEN 1 END) AS failed_notifications FROM government_services.notifications GROUP BY application_id HAVING COUNT(CASE WHEN status = 'Failed' THEN 1 END) > 0;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE healthcare.prescriptions ( prescription_id.text, record_id.text, patient_id.text, doctor_id.text, medication_id.text, dosage.text, frequency.text, route.text, start_date.date, end_date.date, quantity_dispensed.numeric, refills_allowed.integer, prescription_date.timestamp )

[User] Find pairs of prescriptions for the same patient with overlapping periods. Show p1.prescription_id, p2.prescription_id, patient_id, and the overlap duration in days where the overlap is greater than 15 days.

[Assistant]
SELECT p1.prescription_id AS prescription_id_1,
       p2.prescription_id AS prescription_id_2,
       p1.patient_id,
       (LEAST(p1.end_date, p2.end_date) - GREATEST(p1.start_date, p2.start_date)) AS overlap_days
FROM healthcare.prescriptions p1
JOIN healthcare.prescriptions p2
  ON p1.patient_id = p2.patient_id
 AND p1.prescription_id < p2.prescription_id
WHERE LEAST(p1.end_date, p2.end_date) >= GREATEST(p1.start_date, p2.start_date)
  AND (LEAST(p1.end_date, p2.end_date) - GREATEST(p1.start_date, p2.start_date)) > 15;

[User] Actually, only consider pairs where both prescriptions allow refills.

[Assistant]
SELECT p1.prescription_id AS prescription_id_1,
       p2.prescription_id AS prescription_id_2,
       p1.patient_id,
       (LEAST(p1.end_date, p2.end_date) - GREATEST(p1.start_date, p2.start_date)) AS overlap_days
FROM healthcare.prescriptions p1
JOIN healthcare.prescriptions p2
  ON p1.patient_id = p2.patient_id
 AND p1.prescription_id < p2.prescription_id
WHERE LEAST(p1.end_date, p2.end_date) >= GREATEST(p1.start_date, p2.start_date)
  AND (LEAST(p1.end_date, p2.end_date) - GREATEST(p1.start_date, p2.start_date)) > 15
  AND p1.refills_allowed > 0
  AND p2.refills_allowed > 0;

[User] Also, limit the results to overlaps that start in 2024 and order by overlap_days descending.

[Assistant]
SELECT p1.prescription_id AS prescription_id_1,
       p2.prescription_id AS prescription_id_2,
       p1.patient_id,
       (LEAST(p1.end_date, p2.end_date) - GREATEST(p1.start_date, p2.start_date)) AS overlap_days
FROM healthcare.prescriptions p1
JOIN healthcare.prescriptions p2
  ON p1.patient_id = p2.patient_id
 AND p1.prescription_id < p2.prescription_id
WHERE LEAST(p1.end_date, p2.end_date) >= GREATEST(p1.start_date, p2.start_date)
  AND (LEAST(p1.end_date, p2.end_date) - GREATEST(p1.start_date, p2.start_date)) > 15
  AND p1.refills_allowed > 0
  AND p2.refills_allowed > 0
  AND GREATEST(p1.start_date, p2.start_date) >= '2024-01-01'
ORDER BY overlap_days DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE government_services.service_locations ( location_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, location_name character varying(200), address text NOT NULL, city character varying(100), state character varying(50), postal_code character varying(20), latitude numeric(9, 6), longitude numeric(9, 6), operating_hours text, contact_phone character varying(32), is_accessible boolean, PRIMARY KEY (location_id) )
CREATE TABLE government_services.appointments ( appointment_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, employee_id character varying(64), location_id character varying(64), service_id character varying(64), scheduled_start_time timestamp NOT NULL, scheduled_end_time timestamp, purpose text NOT NULL, status character varying(30) NOT NULL, booking_method character varying(50), created_at timestamp NOT NULL, notes text, PRIMARY KEY (appointment_id) )

[User] List the number of appointments for each booking method.

[Assistant]
SELECT
  a.booking_method,
  COUNT(*) AS appointment_count
FROM appointments a
GROUP BY a.booking_method;

[User] Filter this to only include booking methods that have more than 50 appointments.

[Assistant]
SELECT
  a.booking_method,
  COUNT(*) AS appointment_count
FROM appointments a
GROUP BY a.booking_method
HAVING COUNT(*) > 50;

[User] Also only consider appointments that are scheduled in the state of 'Texas'.

[Assistant]
SELECT
  a.booking_method,
  COUNT(*) AS appointment_count
FROM appointments a
JOIN service_locations sl
  ON a.location_id = sl.location_id
WHERE sl.state = 'Texas'
GROUP BY a.booking_method
HAVING COUNT(*) > 50;

[User] Now show the results ordered by appointment_count descending and limit to top 3 methods.

[Assistant]
SELECT
  a.booking_method,
  COUNT(*) AS appointment_count
FROM appointments a
JOIN service_locations sl
  ON a.location_id = sl.location_id
WHERE sl.state = 'Texas'
GROUP BY a.booking_method
HAVING COUNT(*) > 50
ORDER BY appointment_count DESC
LIMIT 3;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE web3.users ( user_id character varying(64) NOT NULL, username character varying(128) NOT NULL, email character varying(128) NOT NULL, password_hash text NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (user_id) )

[User] For each user, find the previous user by registration time. List current user_id and username, previous user_id and username, and the time difference in minutes between their registrations.

[Assistant]
SELECT u.user_id AS current_user_id,
       u.username AS current_username,
       p.user_id AS previous_user_id,
       p.username AS previous_username,
       EXTRACT(EPOCH FROM (u.created_at - p.created_at)) / 60 AS diff_minutes
FROM web3.users u
JOIN web3.users p
  ON p.created_at = (
    SELECT MAX(created_at)
    FROM web3.users
    WHERE created_at < u.created_at
  )
ORDER BY u.created_at;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE government_services.service_locations ( location_id text, agency_id text, location_name text, address text, city text, state text, postal_code text, latitude numeric, longitude numeric, operating_hours text, contact_phone text, is_accessible boolean )

[User] Find the service locations that are not accessible and located in the state of 'California'. List their name, address, and city.

[Assistant] SELECT location_name ,  address ,  city FROM government_services.service_locations WHERE is_accessible = false AND state = 'California'


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE gaming_technology.achievements ( achievement_id.uuid, game_id.uuid, name.text, description.text, icon_url.text, points.integer, hidden.boolean )

[User] List all achievements with points greater than 100, showing achievement_id, name, and points.

[Assistant]
SELECT achievement_id, name, points
FROM gaming_technology.achievements
WHERE points > 100;

[User] Filter further to only include visible achievements and also return the description.

[Assistant]
SELECT achievement_id, name, description, points
FROM gaming_technology.achievements
WHERE points > 100
  AND hidden = FALSE;

[User] Now group by game_id to find how many such high-point visible achievements each game has.

[Assistant]
SELECT game_id,
       COUNT(*) AS high_point_visible_count
FROM gaming_technology.achievements
WHERE points > 100
  AND hidden = FALSE
GROUP BY game_id;

[User] Only include games with at least 2 of these achievements and order by that count descending.

[Assistant]
SELECT game_id,
       COUNT(*) AS high_point_visible_count
FROM gaming_technology.achievements
WHERE points > 100
  AND hidden = FALSE
GROUP BY game_id
HAVING COUNT(*) >= 2
ORDER BY high_point_visible_count DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE legal_services.lawyers ( lawyer_id.text, first_name.text, last_name.text, bar_number.text, firm_id.text, email.text, phone.text, specialization.text, hire_date.timestamp, is_partner.boolean )
CREATE TABLE legal_services.law_firms ( firm_id.text, firm_name.text, address.text, phone.text, website.text, founded_date.date, managing_partner_id.text )
CREATE TABLE legal_services.cases ( case_id.text, case_number.text, case_name.text, client_id.text, lead_lawyer_id.text, case_type.text, status.text, date_opened.timestamp, date_closed.timestamp, description.text, court_jurisdiction.text )
CREATE TABLE legal_services.time_entries ( entry_id.text, case_id.text, lawyer_id.text, date_worked.date, hours_spent.numeric, billing_rate.numeric, description.text, is_billable.boolean, is_billed.boolean, invoice_id.text, created_at.timestamp )
CREATE TABLE legal_services.appointments ( appointment_id.text, client_id.text, lawyer_id.text, case_id.text, start_time.timestamp, end_time.timestamp, location.text, subject.text, notes.text, status.text, created_at.timestamp )

[User] Show me the names of all law firms and the total number of lawyers associated with each firm.

[Assistant] SELECT T1.firm_name, count(T2.lawyer_id) FROM legal_services.law_firms AS T1 JOIN legal_services.lawyers AS T2 ON T1.firm_id = T2.firm_id GROUP BY T1.firm_id, T1.firm_name


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE gaming_technology.games ( game_id uuid PRIMARY KEY, title text, developer_id uuid, publisher_id uuid, genre text, release_date date, description text, platform text, engine text, website text )
CREATE TABLE gaming_technology.developers ( developer_id.uuid, name.text, country.text, founded_year.integer, website.text, created_at.timestamptz )
CREATE TABLE gaming_technology.game_sessions ( session_id uuid NOT NULL DEFAULT gen_random_uuid(), player_id uuid NOT NULL, game_id uuid NOT NULL, server_id uuid, start_time timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, end_time timestamp with time zone, duration_seconds integer, score integer, session_data jsonb, PRIMARY KEY (session_id) )
CREATE TABLE gaming_technology.player_achievements ( player_achievement_id uuid PRIMARY KEY, player_id uuid, achievement_id uuid, unlocked_at timestamptz )
CREATE TABLE gaming_technology.player_inventory ( inventory_id uuid PRIMARY KEY, player_id uuid, item_id uuid, quantity int, acquired_at timestamptz, instance_data jsonb )

[User] Show me all players who have unlocked any achievements in games released after 2020, and include the player's ID, achievement ID, the game's title, and the unlock date.

[Assistant]
SELECT pa.player_id, pa.achievement_id, g.title, pa.unlocked_at
FROM gaming_technology.player_achievements pa
JOIN gaming_technology.achievements a ON pa.achievement_id = a.achievement_id
JOIN gaming_technology.games g ON a.game_id = g.game_id
WHERE g.release_date > '2020-12-31';

[User] Add the developer's name to each result as well.

[Assistant]
SELECT pa.player_id, pa.achievement_id, g.title, pa.unlocked_at, d.name AS developer_name
FROM gaming_technology.player_achievements pa
JOIN gaming_technology.achievements a ON pa.achievement_id = a.achievement_id
JOIN gaming_technology.games g ON a.game_id = g.game_id
JOIN gaming_technology.developers d ON g.developer_id = d.developer_id
WHERE g.release_date > '2020-12-31';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE trading_platform.users ( user_id.text, username.text, email.text, password_hash.text, created_at.timestamp )
CREATE TABLE trading_platform.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.orders ( order_id text, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )
CREATE TABLE trading_platform.assets ( asset_id text, name text, symbol text, type text )
CREATE TABLE trading_platform.dapps ( dapp_id text, name text, description text, url text )
CREATE TABLE trading_platform.peers ( peer_id.text, ip_address.text, port.integer, last_seen.timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, key character varying(128) NOT NULL, value text NOT NULL, PRIMARY KEY (metadata_id) )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id.text, user_id.text, status.text, reviewed_at.timestamp )
CREATE TABLE trading_platform.logs ( log_id text PRIMARY KEY, user_id text, action text, details text, logged_at timestamp )
CREATE TABLE trading_platform.notifications ( notification_id text, user_id text, message text, sent_at timestamp, read_at timestamp )

[User] List all unique actions that have been logged in the system.

[Assistant] SELECT DISTINCT action FROM trading_platform.logs;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id text, license_plate text, vin text, make text, model text, year integer, type text, capacity integer, fuel_type text, status text, depot_id text, acquisition_date date )
CREATE TABLE transportation.drivers (
    driver_id character varying(64) NOT NULL,  -- unique identifier for the driver
    employee_id character varying(64) NOT NULL UNIQUE, -- employee reference number
    first_name character varying(128) NOT NULL, -- driver's first name
    last_name character varying(128) NOT NULL, -- driver's last name
    license_number character varying(64) NOT NULL UNIQUE, -- driving license number
    license_expiry_date date NOT NULL, -- expiry date of the license
    contact_number character varying(32), -- phone number
    email character varying(128) UNIQUE, -- email address
    hire_date date NOT NULL, -- date the driver was hired
    status character varying(32) NOT NULL, -- e.g., Active, On Leave, Terminated
    PRIMARY KEY (driver_id)
)
CREATE TABLE transportation.fuel_logs ( fuel_log_id text, vehicle_id text, trip_id text, log_timestamp timestamp, fuel_type text, quantity numeric, unit text, cost_per_unit numeric, total_cost numeric, odometer_reading integer, location_id text )
CREATE TABLE transportation.bookings ( booking_id character varying(64) NOT NULL, passenger_id character varying(64) NOT NULL, trip_id character varying(64) NOT NULL, seat_number character varying(16), booking_time timestamp with time zone NOT NULL, status character varying(32) NOT NULL, fare numeric(10, 2) NOT NULL, payment_transaction_id character varying(128), special_requests text, PRIMARY KEY (booking_id) )

[User] For each vehicle, show vehicle_id, make, model, the earliest and latest fuel log IDs with their timestamps.

[Assistant]
WITH extremes AS (
  SELECT vehicle_id,
         MIN(log_timestamp) AS first_ts,
         MAX(log_timestamp) AS last_ts
  FROM transportation.fuel_logs
  GROUP BY vehicle_id
)
SELECT v.vehicle_id,
       v.make,
       v.model,
       fl1.fuel_log_id   AS first_log_id,
       extremes.first_ts AS first_log_timestamp,
       fl2.fuel_log_id   AS last_log_id,
       extremes.last_ts  AS last_log_timestamp
FROM extremes
JOIN transportation.vehicles v
  ON v.vehicle_id = extremes.vehicle_id
JOIN transportation.fuel_logs fl1
  ON fl1.vehicle_id = extremes.vehicle_id
 AND fl1.log_timestamp = extremes.first_ts
JOIN transportation.fuel_logs fl2
  ON fl2.vehicle_id = extremes.vehicle_id
 AND fl2.log_timestamp = extremes.last_ts;

[User] Also include the cost difference between the latest and earliest total_cost as cost_diff.

[Assistant]
WITH extremes AS (
  SELECT vehicle_id,
         MIN(log_timestamp) AS first_ts,
         MAX(log_timestamp) AS last_ts
  FROM transportation.fuel_logs
  GROUP BY vehicle_id
)
SELECT v.vehicle_id,
       v.make,
       v.model,
       fl1.fuel_log_id   AS first_log_id,
       extremes.first_ts AS first_log_timestamp,
       fl2.fuel_log_id   AS last_log_id,
       extremes.last_ts  AS last_log_timestamp,
       (fl2.total_cost - fl1.total_cost) AS cost_diff
FROM extremes
JOIN transportation.vehicles v
  ON v.vehicle_id = extremes.vehicle_id
JOIN transportation.fuel_logs fl1
  ON fl1.vehicle_id = extremes.vehicle_id
 AND fl1.log_timestamp = extremes.first_ts
JOIN transportation.fuel_logs fl2
  ON fl2.vehicle_id = extremes.vehicle_id
 AND fl2.log_timestamp = extremes.last_ts;

[User] Only include vehicles with at least two fuel log entries and cost_diff > 100, and order by cost_diff DESC.

[Assistant]
WITH extremes AS (
  SELECT vehicle_id,
         MIN(log_timestamp) AS first_ts,
         MAX(log_timestamp) AS last_ts,
         COUNT(*) AS log_count
  FROM transportation.fuel_logs
  GROUP BY vehicle_id
  HAVING COUNT(*) >= 2
)
SELECT v.vehicle_id,
       v.make,
       v.model,
       fl1.fuel_log_id   AS first_log_id,
       extremes.first_ts AS first_log_timestamp,
       fl2.fuel_log_id   AS last_log_id,
       extremes.last_ts  AS last_log_timestamp,
       (fl2.total_cost - fl1.total_cost) AS cost_diff
FROM extremes
JOIN transportation.vehicles v
  ON v.vehicle_id = extremes.vehicle_id
JOIN transportation.fuel_logs fl1
  ON fl1.vehicle_id = extremes.vehicle_id
 AND fl1.log_timestamp = extremes.first_ts
JOIN transportation.fuel_logs fl2
  ON fl2.vehicle_id = extremes.vehicle_id
 AND fl2.log_timestamp = extremes.last_ts
WHERE (fl2.total_cost - fl1.total_cost) > 100
ORDER BY cost_diff DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE legal_services.lawyers ( lawyer_id.text, first_name.text, last_name.text, bar_number.text, firm_id.text, email.text, phone.text, specialization.text, hire_date.timestamp, is_partner.boolean )
CREATE TABLE legal_services.law_firms ( firm_id text, firm_name text, address text, phone text, website text, founded_date date, managing_partner_id text )
CREATE TABLE legal_services.time_entries (
    entry_id character varying(64) NOT NULL,  -- unique identifier for the time entry
    case_id character varying(64) NOT NULL, -- FK to cases table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table (who performed the work)
    date_worked date NOT NULL, -- date the work was performed
    hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), -- duration of work in hours (e.g., 1.5 for 1h 30m)
    billing_rate numeric(10, 2) NOT NULL, -- hourly rate applied for this entry
    description text NOT NULL, -- detailed description of the work performed
    is_billable boolean DEFAULT true, -- whether this time entry is billable to the client
    is_billed boolean DEFAULT false, -- whether this entry has been included in an invoice
    invoice_id character varying(64), -- FK to invoices table (once billed)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the entry was recorded
    PRIMARY KEY (entry_id)
)
CREATE TABLE legal_services.invoices ( invoice_id.text, invoice_number.text, client_id.text, case_id.text, issue_date.date, due_date.date, total_amount.numeric, amount_paid.numeric, status.text, payment_date.timestamp, notes.text, created_at.timestamp )

[User] Show me the full name and specialization of all lawyers, along with the name of the law firm they work for.

[Assistant] SELECT T1.first_name, T1.last_name, T1.specialization, T2.firm_name FROM legal_services.lawyers AS T1 JOIN legal_services.law_firms AS T2 ON T1.firm_id = T2.firm_id;

[User] Only include lawyers who are partners.

[Assistant] SELECT T1.first_name, T1.last_name, T1.specialization, T2.firm_name FROM legal_services.lawyers AS T1 JOIN legal_services.law_firms AS T2 ON T1.firm_id = T2.firm_id WHERE T1.is_partner = TRUE;

[User] Filter the list to include only partners with a recorded bar number.

[Assistant] SELECT T1.first_name, T1.last_name, T1.specialization, T2.firm_name FROM legal_services.lawyers AS T1 JOIN legal_services.law_firms AS T2 ON T1.firm_id = T2.firm_id WHERE T1.is_partner = TRUE AND T1.bar_number IS NOT NULL;


[User] Find pairs of notifications for the same citizen where one was sent via 'Email' and another via 'SMS'. Display citizen_id, email_notification_id, sms_notification_id, email_sent_at, and sms_sent_at.

[Assistant]
SELECT e.citizen_id,
       e.notification_id AS email_notification_id,
       s.notification_id AS sms_notification_id,
       e.sent_at           AS email_sent_at,
       s.sent_at           AS sms_sent_at
FROM government_services.notifications e
JOIN government_services.notifications s
  ON e.citizen_id = s.citizen_id
 AND e.channel = 'Email'
 AND s.channel = 'SMS';


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE social_media.users ( user_id text, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified boolean )
CREATE TABLE social_media.posts ( post_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, content text, media_url text, media_type character varying(20), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, visibility character varying(20) NOT NULL DEFAULT 'public', location_lat numeric(9,6), location_lon numeric(9,6), PRIMARY KEY (post_id) )
CREATE TABLE social_media.comments ( comment_id.text, post_id.text, user_id.text, parent_comment_id.text, content.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE social_media.likes ( like_id text PRIMARY KEY, user_id text, post_id text, comment_id text, created_at timestamp )
CREATE TABLE social_media.follows (
    follow_id character varying(64) NOT NULL, -- unique identifier for the follow relationship
    follower_user_id character varying(64) NOT NULL, -- identifier of the user who is following (FK to users.user_id)
    following_user_id character varying(64) NOT NULL, -- identifier of the user being followed (FK to users.user_id)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of when the follow started
    PRIMARY KEY (follow_id),
    CONSTRAINT unique_follow UNIQUE (follower_user_id, following_user_id) -- prevent duplicate follows
)
CREATE TABLE social_media.hashtags ( hashtag_id character varying(64) NOT NULL, tag_name character varying(100) NOT NULL UNIQUE, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (hashtag_id) )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id text PRIMARY KEY, post_id text, hashtag_id text )
CREATE TABLE social_media.conversations ( conversation_id.text, created_at.timestamp, last_message_at.timestamp, is_group_chat.boolean, group_name.text )
CREATE TABLE social_media.conversation_participants ( participant_id.text, conversation_id.text, user_id.text, joined_at.timestamp, last_read_at.timestamp )
CREATE TABLE social_media.notifications ( notification_id.text, recipient_user_id.text, sender_user_id.text, notification_type.text, target_entity_id.text, target_entity_type.text, created_at.timestamp, read_at.timestamp )
CREATE TABLE social_media.user_settings ( setting_id.text, user_id.text, theme.text, email_notifications_enabled.boolean, push_notifications_enabled.boolean, private_profile.boolean, updated_at.timestamp )

[User] List all users who have never followed anyone, showing their username, full name, email, and account creation date.

[Assistant]
SELECT u.username,
       u.full_name,
       u.email,
       u.created_at
FROM social_media.users AS u
LEFT JOIN social_media.follows AS f
  ON u.user_id = f.follower_user_id
WHERE f.follow_id IS NULL;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE financial_services.customers ( customer_id text PRIMARY KEY, first_name text, last_name text, date_of_birth date, ssn_hash text, address text, city text, state text, zip_code text, country text, email text, phone_number text, created_at timestamp, status text, risk_profile text )
CREATE TABLE financial_services.accounts ( account_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, account_number character varying(128) NOT NULL UNIQUE, account_type character varying(50) NOT NULL, balance numeric(19, 4) NOT NULL DEFAULT 0.00, currency character varying(3) NOT NULL, opened_date date NOT NULL, status character varying(32) NOT NULL, interest_rate numeric(5, 4), last_updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (account_id), FOREIGN KEY (customer_id) REFERENCES financial_services.customers(customer_id) )
CREATE TABLE financial_services.transactions ( transaction_id character varying(64) NOT NULL, account_id character varying(64) NOT NULL, related_account_id character varying(64), transaction_type character varying(50) NOT NULL, amount numeric(19, 4) NOT NULL, currency character varying(3) NOT NULL, transaction_date timestamp NOT NULL, effective_date date NOT NULL, description text, status character varying(32) NOT NULL, reference_number character varying(128), PRIMARY KEY (transaction_id), FOREIGN KEY (account_id) REFERENCES financial_services.accounts(account_id), FOREIGN KEY (related_account_id) REFERENCES financial_services.accounts(account_id) )
CREATE TABLE financial_services.trades ( trade_id text PRIMARY KEY, account_id text, security_id text, order_id text, trade_type text, quantity numeric, price_per_unit numeric, total_amount numeric, commission numeric, trade_timestamp timestamp, settlement_date date, status text, execution_venue text )
CREATE TABLE financial_services.market_data (
    data_point_id bigserial NOT NULL, -- auto-incrementing primary key
    security_id character varying(64) NOT NULL, -- identifier for the security
    data_timestamp timestamp NOT NULL, -- timestamp for the data point (e.g., end of day, intraday)
    open_price numeric(19, 8), -- opening price for the period
    high_price numeric(19, 8), -- highest price during the period
    low_price numeric(19, 8), -- lowest price during the period
    close_price numeric(19, 8) NOT NULL, -- closing price for the period
    adjusted_close_price numeric(19, 8), -- closing price adjusted for dividends and splits
    volume bigint, -- trading volume during the period
    source character varying(50), -- source of the market data (e.g., Bloomberg, Refinitiv)
    PRIMARY KEY (data_point_id),
    UNIQUE (security_id, data_timestamp), -- Ensure unique data point per security per time
    FOREIGN KEY (security_id) REFERENCES financial_services.securities(security_id)
)
CREATE TABLE financial_services.employees ( employee_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, job_title character varying(100) NOT NULL, department character varying(100), branch_id character varying(64), email character varying(128) NOT NULL UNIQUE, phone_extension character varying(20), hire_date date NOT NULL, termination_date date, manager_id character varying(64), status character varying(32) NOT NULL, PRIMARY KEY (employee_id), FOREIGN KEY (branch_id) REFERENCES financial_services.branches(branch_id), FOREIGN KEY (manager_id) REFERENCES financial_services.employees(employee_id) )
CREATE TABLE financial_services.loans ( loan_id.text, account_id.text, loan_type.text, principal_amount.numeric, current_principal_balance.numeric, interest_rate.numeric, term_months.integer, origination_date.date, maturity_date.date, monthly_payment.numeric, collateral_description.text, status.text )

[User] Show me a summary of customers with their total account balance and the count of accounts.

[Assistant] SELECT c.first_name, c.last_name, COUNT(a.account_id) AS account_count, SUM(a.balance) AS total_account_balance FROM financial_services.customers AS c JOIN financial_services.accounts AS a ON c.customer_id = a.customer_id GROUP BY c.customer_id, c.first_name, c.last_name;

[User] Filter the results to only include customers where the combined balance across all their accounts exceeds 5000.

[Assistant] SELECT c.first_name, c.last_name, COUNT(a.account_id) AS account_count, SUM(a.balance) AS total_account_balance FROM financial_services.customers AS c JOIN financial_services.accounts AS a ON c.customer_id = a.customer_id GROUP BY c.customer_id, c.first_name, c.last_name HAVING SUM(a.balance) > 5000;

[User] Please modify the query to only count and sum balances for accounts with status 'ACTIVE'.

[Assistant] SELECT c.first_name, c.last_name, COUNT(CASE WHEN a.status = 'ACTIVE' THEN a.account_id ELSE NULL END) AS active_account_count, SUM(CASE WHEN a.status = 'ACTIVE' THEN a.balance ELSE 0 END) AS total_active_account_balance FROM financial_services.customers AS c JOIN financial_services.accounts AS a ON c.customer_id = a.customer_id GROUP BY c.customer_id, c.first_name, c.last_name HAVING SUM(CASE WHEN a.status = 'ACTIVE' THEN a.balance ELSE 0 END) > 5000;

[User] Order the results by customer last name, then first name.

[Assistant] SELECT c.first_name, c.last_name, COUNT(CASE WHEN a.status = 'ACTIVE' THEN a.account_id ELSE NULL END) AS active_account_count, SUM(CASE WHEN a.status = 'ACTIVE' THEN a.balance ELSE 0 END) AS total_active_account_balance FROM financial_services.customers AS c JOIN financial_services.accounts AS a ON c.customer_id = a.customer_id GROUP BY c.customer_id, c.first_name, c.last_name HAVING SUM(CASE WHEN a.status = 'ACTIVE' THEN a.balance ELSE 0 END) > 5000 ORDER BY c.last_name ASC, c.first_name ASC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
 "CREATE TABLE token_basic_info (",
    "coin_id character varying(100) NOT NULL, -- the id of the token",
    "token_name character varying(100) NOT NULL, -- the token's name",
    "token_symbol character varying(100) NOT NULL, -- the token's symbol",
    "token_address character varying(100) NOT NULL, -- the token's address",
    "chain text, -- the chain that the token resides",
    "price double precision, -- the current price of the token",
    "price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour",
    "price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours",
    "price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days",
    "highest_price_24h double precision, -- the highest price of the token in 24 hours",
    "lowest_price_24h double precision,  -- the lowest price of the token in 24 hours",
    "market_cap double precision, -- the market cap of the token",
    "market_cap_rank bigint, -- the rank of the token market cap in desc",
    "market_cap_change_percentage_24h text, -- the percentage of market cap changes in 24 hours",
    "total_volume text, -- the trade volum of the token both in decentralized exchange(DEX) and centralized exchange(CEX)",
    "narrative text, -- the category or narrative of the token",
    "trend_rank biging, -- the trending rank of the token, value 1 expresses the most popular token.",
    ",PRIMARY KEY (coin_id, chain));",

[User] Which is the token with the largest difference between its highest and lowest price in the last 24h on each chain, and what is the token's symbol and current price?

[Assistant]
SELECT chain, token_symbol, price, (highest_price_24h - lowest_price_24h) AS price_diff_24h
FROM token_basic_info
WHERE (chain, highest_price_24h - lowest_price_24h) IN (
  SELECT chain, MAX(highest_price_24h - lowest_price_24h) AS diff
  FROM token_basic_info
  GROUP BY chain
)
ORDER BY price_diff_24h DESC;

[User] Could you also include the percentage change over 24 hours for each token in the result?

[Assistant]
SELECT chain, token_symbol, price, price_change_percentage_24h, (highest_price_24h - lowest_price_24h) AS price_diff_24h
FROM token_basic_info
WHERE (chain, highest_price_24h - lowest_price_24h) IN (
  SELECT chain, MAX(highest_price_24h - lowest_price_24h) AS diff
  FROM token_basic_info
  GROUP BY chain
)
ORDER BY price_diff_24h DESC;

[User] I'm only interested in tokens where this price difference exceeds $5. Can you filter for that?

[Assistant]
SELECT chain, token_symbol, price, price_change_percentage_24h, (highest_price_24h - lowest_price_24h) AS price_diff_24h
FROM token_basic_info
WHERE (chain, highest_price_24h - lowest_price_24h) IN (
  SELECT chain, MAX(highest_price_24h - lowest_price_24h) AS diff
  FROM token_basic_info
  GROUP BY chain
)
AND (highest_price_24h - lowest_price_24h) > 5
ORDER BY price_diff_24h DESC;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE social_media.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified bool )

[User] List usernames and the length of their 'bio' field for users whose 'is_verified' status is true.

[Assistant] SELECT username, LENGTH(bio) AS bio_length FROM social_media.users WHERE is_verified IS TRUE;


System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
CREATE TABLE financial_services.accounts ( account_id.text, customer_id.text, account_number.text, account_type.text, balance.numeric, currency.text, opened_date.date, status.text, interest_rate.numeric, last_updated_at.timestamp )

[User] Find customers who have accounts in more than one currency. List their customer_id and the count of distinct currencies they hold accounts in.

[Assistant] SELECT customer_id, COUNT(DISTINCT currency) AS distinct_currency_count FROM financial_services.accounts GROUP BY customer_id HAVING COUNT(DISTINCT currency) > 1

[User] For these customers, also list the average balance across all their accounts.

[Assistant] SELECT customer_id, COUNT(DISTINCT currency) AS distinct_currency_count, AVG(balance) AS average_balance FROM financial_services.accounts GROUP BY customer_id HAVING COUNT(DISTINCT currency) > 1

[User] Sort the results by the number of distinct currencies in descending order.

[Assistant] SELECT customer_id, COUNT(DISTINCT currency) AS distinct_currency_count, AVG(balance) AS average_balance FROM financial_services.accounts GROUP BY customer_id HAVING COUNT(DISTINCT currency) > 1 ORDER BY distinct_currency_count DESC