[User] Show me the top 5 ERC20 tokens with the highest total supply, along with their names and contract addresses, but only include tokens where the price is greater than $0.10.

[Assistant] SELECT tm.name, tm.contract_address, tm.total_supply FROM token_metas tm JOIN token_prices_latest tpl ON tm.contract_address = tpl.address WHERE tm.is_erc20 = 1 AND tpl.price > 0.10 ORDER BY CAST(tm.total_supply AS decimal) DESC LIMIT 5;

[User] Can you also include the symbol and decimals for these tokens?

[Assistant] SELECT tm.name, tm.symbol, tm.contract_address, tm.total_supply, tm.decimals FROM token_metas tm JOIN token_prices_latest tpl ON tm.contract_address = tpl.address WHERE tm.is_erc20 = 1 AND tpl.price > 0.10 ORDER BY CAST(tm.total_supply AS decimal) DESC LIMIT 5;

[User] Now filter these results to only show tokens with decimals equal to 18.

[Assistant] SELECT tm.name, tm.symbol, tm.contract_address, tm.total_supply, tm.decimals FROM token_metas tm JOIN token_prices_latest tpl ON tm.contract_address = tpl.address WHERE tm.is_erc20 = 1 AND tpl.price > 0.10 AND tm.decimals = 18 ORDER BY CAST(tm.total_supply AS decimal) DESC LIMIT 5;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE token_metas ( block_timestamp timestamp(6) NOT NULL, block_number bigint NOT NULL, transaction_hash varchar NOT NULL, transaction_index bigint NOT NULL, from_address varchar NOT NULL, contract_address varchar NOT NULL, symbol varchar NOT NULL, total_supply varchar NOT NULL, name varchar NOT NULL, decimals bigint NOT NULL, is_erc20 integer NOT NULL, is_erc721 integer NOT NULL, is_erc1155 integer NOT NULL, is_proxy integer NOT NULL, extra_info varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE erc1155_approval_for_all ( block_number bigint NOT NULL, block_timestamp timestamp(3) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar(66) NOT NULL, log_index integer NOT NULL, contract_address varchar(42) NOT NULL )
CREATE TABLE erc20_balances ( block_number bigint NOT NULL, contract_address varchar NOT NULL, wallet_address varchar NOT NULL, amount varchar NOT NULL, pk varchar NOT NULL )
CREATE TABLE erc20_balances_historical ( block_number bigint NOT NULL, contract_address varchar NOT NULL, wallet_address varchar NOT NULL, amount varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE nft_holders ( block_number bigint NOT NULL, contract_address varchar NOT NULL, wallet_address varchar NOT NULL, token_id varchar NOT NULL, contract_type varchar NOT NULL, amount varchar NOT NULL, pk varchar NOT NULL )
CREATE TABLE nft_holder_historical ( block_number bigint NOT NULL, contract_address varchar NOT NULL, wallet_address varchar NOT NULL, token_id varchar NOT NULL, contract_type varchar NOT NULL, amount varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE sui_coins ( object_id varchar NOT NULL, status varchar NOT NULL, coin_type varchar NOT NULL, balance varchar NOT NULL, owner varchar NOT NULL )
CREATE TABLE sui_coins_metadata ( object_id varchar NOT NULL, coin_type varchar NOT NULL, status varchar NOT NULL, decimals bigint NOT NULL, description varchar NOT NULL, icon_url varchar NOT NULL, symbol varchar NOT NULL, name varchar NOT NULL )
CREATE TABLE sui_nfts ( object_id varchar NOT NULL, status varchar NOT NULL, collection_type varchar NOT NULL, package_id varchar NOT NULL, previous_transaction varchar NOT NULL, display varchar NOT NULL, owner varchar NOT NULL, name varchar NOT NULL )
CREATE TABLE nft_metadata ( blockchain varchar NOT NULL, contract_address varchar NOT NULL, token_id varchar NOT NULL, contract_name varchar NOT NULL, erc_type varchar NOT NULL, amount bigint NOT NULL, minter varchar NOT NULL, owner varchar NOT NULL, mint_block_number bigint NOT NULL, mint_time bigint NOT NULL, mint_transaction_hash varchar NOT NULL, mint_price varchar NOT NULL, token_uri varchar NOT NULL, metadata varchar NOT NULL, name varchar NOT NULL, image_uri varchar NOT NULL, traits varchar NOT NULL, updated_at bigint NOT NULL, status varchar NOT NULL, rarity_score real NOT NULL, rarity_rank integer NOT NULL, unique_attribute_count integer NOT NULL, pk integer NOT NULL )
CREATE TABLE nft_collections ( blockchain varchar NOT NULL, contract_address varchar NOT NULL, name varchar NOT NULL, symbol varchar NOT NULL, deploy_block_number bigint NOT NULL, deploy_block_time bigint NOT NULL, erc_type varchar NOT NULL, owner varchar NOT NULL, traits varchar NOT NULL, description varchar NOT NULL, slug varchar NOT NULL, media_info varchar NOT NULL, image_url varchar NOT NULL, banner_image_url varchar NOT NULL, updated_at bigint NOT NULL, banner varchar NOT NULL, token_count bigint NOT NULL, floor_price varchar NOT NULL, floor_price_symbol varchar NOT NULL, floor_price_contract varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE token_prices ( uuid varchar(36) NOT NULL, blockchain varchar(36) NOT NULL, address varchar(42) NOT NULL, decimals bigint NOT NULL, symbol varchar(36) NOT NULL, price real NOT NULL, timestamp timestamp(6) NOT NULL )
CREATE TABLE token_prices_latest ( blockchain varchar(36) NOT NULL, address varchar(42) NOT NULL, decimals bigint NOT NULL, symbol varchar(36) NOT NULL, price real NOT NULL, timestamp timestamp(6) NOT NULL )
CREATE TABLE erc20_approval ( block_number bigint NOT NULL, block_timestamp timestamp(6) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar NOT NULL, log_index integer NOT NULL, contract_address varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE token_balances ( block_number bigint NOT NULL, block_timestamp timestamp(3) NOT NULL, tick varchar NOT NULL, wallet_address varchar(42) NOT NULL, total_supply decimal(38,0) NOT NULL, amount decimal(38,0) NOT NULL )
CREATE TABLE token_info ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, tick varchar NOT NULL, max_supply decimal(38,0) NOT NULL, lim decimal(38,0) NOT NULL, wlim decimal(38,0) NOT NULL, dec integer NOT NULL, creator varchar(42) NOT NULL )
CREATE TABLE token_activities ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, log_index integer NOT NULL, type varchar NOT NULL, tick varchar NOT NULL, id varchar(255) NOT NULL, amt decimal(38,0) NOT NULL, from_address varchar(42) NOT NULL, to_address varchar(42) NOT NULL )
CREATE TABLE mud_holesky_redstone ( address varchar NOT NULL, table_id varchar NOT NULL, key_bytes varchar NOT NULL, key0 varchar NOT NULL, key1 varchar NOT NULL, static_data varchar NOT NULL, encoded_lengths varchar NOT NULL, dynamic_data varchar NOT NULL, is_deleted boolean NOT NULL, block_number bigint NOT NULL, log_index bigint NOT NULL )
CREATE TABLE token_balances_bitcoin ( block_number bigint NOT NULL, block_timestamp timestamp(3) NOT NULL, tick varchar(255) NOT NULL, wallet_address varchar(42) NOT NULL, total_supply varchar NOT NULL, amount varchar NOT NULL )
CREATE TABLE token_activities_bitcoin ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, log_index integer NOT NULL, type varchar(20) NOT NULL, tick varchar(255) NOT NULL, id varchar(255) NOT NULL, amt decimal(38,0) NOT NULL, from_address varchar(62) NOT NULL, to_address varchar(62) NOT NULL )
CREATE TABLE token_activities_avalanche ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, log_index integer NOT NULL, type varchar(20) NOT NULL, tick varchar(255) NOT NULL, id varchar(255) NOT NULL, amt decimal(38,0) NOT NULL, from_address varchar(42) NOT NULL, to_address varchar(42) NOT NULL )
CREATE TABLE token_balances_avalanche ( block_number bigint NOT NULL, block_timestamp timestamp(3) NOT NULL, tick varchar(20) NOT NULL, wallet_address varchar(42) NOT NULL, total_supply decimal(38,0) NOT NULL, amount decimal(38,0) NOT NULL )
CREATE TABLE token_info_avalanche ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, tick varchar(20) NOT NULL, max_supply decimal(38,0) NOT NULL, lim decimal(38,0) NOT NULL, wlim decimal(38,0) NOT NULL, dec integer NOT NULL, creator varchar(42) NOT NULL, minted decimal(38,0) NOT NULL, holders decimal(38,0) NOT NULL, txs decimal(38,0) NOT NULL, updated_timestamp timestamp(3) NOT NULL, completed_timestamp timestamp(3) NOT NULL, id varchar(255) NOT NULL )


[User] Show me each service order along with the next order placed by the same guest, including both order IDs and the time difference in minutes between the two orders.

[Assistant]
SELECT a.order_id,
       b.order_id AS next_order_id,
       EXTRACT(EPOCH FROM (b.order_timestamp - a.order_timestamp)) / 60 AS diff_minutes
FROM hospitality_technology.service_orders a
JOIN hospitality_technology.service_orders b
  ON a.guest_id = b.guest_id
 AND b.order_timestamp > a.order_timestamp;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.service_orders ( order_id.text, reservation_id.text, guest_id.text, service_id.text, staff_id_ordered.text, staff_id_delivered.text, order_timestamp.timestamp, delivery_timestamp.timestamp, quantity.integer, unit_price.numeric, total_price.numeric, status.text, notes.text, bill_id.text )


[User] 能否帮我统计特定车站(station_id 为 'station_xyz')的所有工作人员数量？

[Assistant]
MATCH (s:Station {station_id: 'station_xyz'})<-[:BASED_AT]-(staff:Staff)
RETURN COUNT(staff) AS total_staff

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
// Node Label: :Station
// Properties:
//   station_id: String (Constraint: UNIQUE)
//   station_name: String
//   city: String (Index recommended)
//   state_province: String
//   country_code: String
//   address: String
//   timezone: String
//   number_of_platforms: Integer
//   created_at: DateTime
//   last_updated_at: DateTime
// Example Cypher CREATE:
// CREATE (:Station {station_id: 'station_xyz', station_name: 'Grand Central Terminal', city: 'New York', ...})
// Node Label: :Platform
// Properties:
//   platform_id: String (Constraint: UNIQUE)
//   platform_number: String
//   track_number: String
//   status: String
//   length_meters: Float
//   accessible: Boolean
// Relationship: (:Platform)-[:LOCATED_AT]->(:Station)
// Example Cypher CREATE:
// MATCH (s:Station {station_id: 'station_xyz'})
// CREATE (p:Platform {platform_id: 'plat_123', ...})-[:LOCATED_AT]->(s)
// Node Label: :Train
// Properties:
//   train_id: String (Constraint: UNIQUE)
//   train_number: String (Constraint: UNIQUE)
//   model: String
//   manufacturer: String
//   year_manufactured: Integer
//   capacity: Integer
//   status: String
//   last_maintenance_date: Date
//   next_maintenance_date: Date
// Example Cypher CREATE:
// CREATE (:Train {train_id: 'train_789', train_number: 'Acela 2151', ...})
// Node Label: :TrainCar
// Properties:
//   car_id: String (Constraint: UNIQUE)
//   car_number: String
//   car_type: String
//   class: String
//   capacity: Integer
//   features: String (Or List<String> if driver supports)
// Relationship: (:TrainCar)-[:PART_OF_TRAIN]->(:Train)
// Example Cypher CREATE:
// MATCH (t:Train {train_id: 'train_789'})
// CREATE (c:TrainCar {car_id: 'car_abc', ...})-[:PART_OF_TRAIN]->(t)
// Node Label: :Route
// Properties:
//   route_id: String (Constraint: UNIQUE)
//   route_name: String
//   description: String
//   is_active: Boolean
// Relationships:
//   (:Route)-[:STARTS_AT]->(:Station)
//   (:Route)-[:ENDS_AT]->(:Station)
// Example Cypher CREATE:
// MATCH (origin:Station {station_id: 'station_bos'}), (dest:Station {station_id: 'station_was'})
// CREATE (r:Route {route_id: 'route_ne_corr', ...})-[:STARTS_AT]->(origin), (r)-[:ENDS_AT]->(dest)
// Relationship: (:Route)-[rel:HAS_STOP]->(:Station)
// Relationship Properties on :HAS_STOP:
//   sequence_order: Integer
//   distance_from_previous_km: Float
//   typical_stop_duration_minutes: Integer
// Example Cypher CREATE:
// MATCH (r:Route {route_id: 'route_ne_corr'}), (s:Station {station_id: 'station_pvd'})
// CREATE (r)-[:HAS_STOP {sequence_order: 2, distance_from_previous_km: 70.5, ...}]->(s)
// Node Label: :ScheduledTrip (or just :Trip)
// Properties:
//   schedule_id: String (Constraint: UNIQUE)
//   departure_datetime: DateTime
//   arrival_datetime: DateTime
//   status: String
//   notes: String
// Relationships:
//   (:ScheduledTrip)-[:USES_TRAIN]->(:Train)
//   (:ScheduledTrip)-[:FOLLOWS_ROUTE]->(:Route)
// Example Cypher CREATE:
// MATCH (t:Train {train_id: 'train_789'}), (r:Route {route_id: 'route_ne_corr'})
// CREATE (sched:ScheduledTrip {schedule_id: 'sched_1122', ...})-[:USES_TRAIN]->(t), (sched)-[:FOLLOWS_ROUTE]->(r)
// Relationship: (:ScheduledTrip)-[rel:SCHEDULED_STOP]->(:Station)
// Relationship Properties on :SCHEDULED_STOP:
//   sequence_order: Integer
//   platform_id: String (references Platform node if modeled, or just store ID)
//   scheduled_arrival_time: DateTime
//   scheduled_departure_time: DateTime
//   actual_arrival_time: DateTime
//   actual_departure_time: DateTime
//   status: String
// Example Cypher CREATE:
// MATCH (sched:ScheduledTrip {schedule_id: 'sched_1122'}), (s:Station {station_id: 'station_pvd'})
// CREATE (sched)-[:SCHEDULED_STOP {sequence_order: 2, platform_id: 'plat_pvd_1', ...}]->(s)
// Node Label: :Passenger
// Properties:
//   passenger_id: String (Constraint: UNIQUE)
//   first_name: String
//   last_name: String
//   email: String (Constraint: UNIQUE, if not null)
//   phone_number: String (Constraint: UNIQUE, if not null)
//   date_of_birth: Date
//   loyalty_program_id: String
//   created_at: DateTime
// Example Cypher CREATE:
// CREATE (:Passenger {passenger_id: 'pass_pqr', first_name: 'Alice', ...})
// Node Label: :Booking
// Properties:
//   booking_id: String (Constraint: UNIQUE)
//   booking_datetime: DateTime
//   status: String
//   total_price: Float
//   currency_code: String
//   special_requests: String
// Relationships:
//   (:Passenger)-[:MADE_BOOKING]->(:Booking)
//   (:Booking)-[:FOR_TRIP]->(:ScheduledTrip)
// Example Cypher CREATE:
// MATCH (p:Passenger {passenger_id: 'pass_pqr'}), (sched:ScheduledTrip {schedule_id: 'sched_1122'})
// CREATE (p)-[:MADE_BOOKING]->(b:Booking {booking_id: 'book_zyx', ...})-[:FOR_TRIP]->(sched)
// Node Label: :Ticket
// Properties:
//   ticket_id: String (Constraint: UNIQUE)
//   seat_number: String
//   ticket_type: String
//   price: Float
//   is_checked_in: Boolean
//   qr_code_data: String
// Relationships:
//   (:Ticket)-[:PART_OF_BOOKING]->(:Booking)
//   (:Ticket)-[:ASSIGNED_TO_CAR]->(:TrainCar)
// Example Cypher CREATE:
// MATCH (b:Booking {booking_id: 'book_zyx'}), (c:TrainCar {car_id: 'car_abc'})
// CREATE (t:Ticket {ticket_id: 'tkt_1a2b', ...})-[:PART_OF_BOOKING]->(b), (t)-[:ASSIGNED_TO_CAR]->(c)
// Node Label: :Staff
// Properties:
//   staff_id: String (Constraint: UNIQUE)
//   first_name: String
//   last_name: String
//   role: String
//   employee_number: String (Constraint: UNIQUE)
//   hire_date: Date
//   contact_email: String (Constraint: UNIQUE, if not null)
//   contact_phone: String
//   is_active: Boolean
// Relationship (Optional):
//   (:Staff)-[:BASED_AT]->(:Station)
// Example Cypher CREATE:
// CREATE (:Staff {staff_id: 'staff_mno', first_name: 'Bob', ...})
// OPTIONAL MATCH (s:Station {station_id: 'station_xyz'}) // If primary_station_id exists
// WITH s, staff_mno // Need to get the created staff node reference
// WHERE s IS NOT NULL
// CREATE (staff_mno)-[:BASED_AT]->(s)


[User] Count the number of law firms founded in each decade. Show the decade (e.g., 1990s, 2000s) and the count.

[Assistant] SELECT CONCAT(FLOOR(EXTRACT(YEAR FROM founded_date) / 10) * 10, 's') AS decade, COUNT(*) AS firm_count FROM law_firms WHERE founded_date IS NOT NULL GROUP BY decade ORDER BY decade;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##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.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.documents ( document_id text PRIMARY KEY, case_id text, document_name text, document_type text, storage_path text, uploaded_by_lawyer_id text, upload_timestamp timestamp, version int, description text )


[User] List the patient ID and subscriber name for all patients who have both at least one diagnosis recorded and at least one primary insurance policy.

[Assistant] SELECT DISTINCT pi.patient_id, pi.subscriber_name FROM healthcare.patient_insurance pi JOIN healthcare.diagnoses d ON pi.patient_id = d.patient_id WHERE pi.is_primary = true;

[User] Refine this list to only include patients whose most recent diagnosis is marked as chronic.

[Assistant] WITH LatestDiagnosis AS ( SELECT patient_id, diagnosis_id, diagnosis_date, is_chronic, ROW_NUMBER() OVER(PARTITION BY patient_id ORDER BY diagnosis_date DESC) as rn FROM healthcare.diagnoses ) SELECT DISTINCT pi.patient_id, pi.subscriber_name FROM healthcare.patient_insurance pi JOIN LatestDiagnosis ld ON pi.patient_id = ld.patient_id WHERE pi.is_primary = true AND ld.rn = 1 AND ld.is_chronic = true;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.diagnoses (
    diagnosis_id character varying(64) NOT NULL, -- unique identifier for the diagnosis entry
    record_id character varying(64) NOT NULL, -- FK linking to the specific medical record entry
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to doctors table (diagnosing doctor)
    diagnosis_code character varying(20) NOT NULL, -- standard code (e.g., ICD-10)
    code_type character varying(10) NOT NULL DEFAULT 'ICD-10', -- type of code used
    description text, -- textual description of the diagnosis
    diagnosis_date date NOT NULL, -- date the diagnosis was made
    status character varying(32) NOT NULL, -- e.g., Active, Resolved, Ruled Out
    is_chronic boolean DEFAULT false, -- flag for chronic conditions
    PRIMARY KEY (diagnosis_id)
)
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id.text, patient_id.text, plan_id.text, policy_number.text, group_number.text, subscriber_name.text, effective_date.date, expiration_date.date, is_primary.boolean )


[User] List the full names and dates of birth for all patients who do not have a phone number on record.

[Assistant] SELECT first_name, last_name, date_of_birth FROM healthcare.patients WHERE phone_number IS NULL OR TRIM(phone_number) = '';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.patients ( patient_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, date_of_birth date NOT NULL, gender character varying(10), address text, phone_number character varying(20), email character varying(128) UNIQUE, emergency_contact_name character varying(200), emergency_contact_phone character varying(20), created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (patient_id) )
CREATE TABLE healthcare.appointments ( appointment_id.text, patient_id.text, doctor_id.text, appointment_time.timestamp, duration_minutes.integer, reason.text, status.text, location_id.text, notes.text, created_at.timestamp )
CREATE TABLE healthcare.diagnoses (
    diagnosis_id character varying(64) NOT NULL, -- unique identifier for the diagnosis entry
    record_id character varying(64) NOT NULL, -- FK linking to the specific medical record entry
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to doctors table (diagnosing doctor)
    diagnosis_code character varying(20) NOT NULL, -- standard code (e.g., ICD-10)
    code_type character varying(10) NOT NULL DEFAULT 'ICD-10', -- type of code used
    description text, -- textual description of the diagnosis
    diagnosis_date date NOT NULL, -- date the diagnosis was made
    status character varying(32) NOT NULL, -- e.g., Active, Resolved, Ruled Out
    is_chronic boolean DEFAULT false, -- flag for chronic conditions
    PRIMARY KEY (diagnosis_id)
)
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 )
CREATE TABLE healthcare.insurance_plans ( plan_id text, plan_name text, insurance_provider text, plan_type text, contact_phone text, website text )
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id.text, patient_id.text, plan_id.text, policy_number.text, group_number.text, subscriber_name.text, effective_date.date, expiration_date.date, is_primary.boolean )


[User] List the usernames of players who own at least one item from the game with title 'Game Title X'.

[Assistant] SELECT DISTINCT T1.username FROM players AS T1 INNER JOIN player_inventory AS T2 ON T1.player_id = T2.player_id INNER JOIN items AS T3 ON T2.item_id = T3.item_id INNER JOIN games AS T4 ON T3.game_id = T4.game_id WHERE T4.title = 'Game Title X';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE gaming_technology.player_inventory ( inventory_id uuid NOT NULL DEFAULT gen_random_uuid(), player_id uuid NOT NULL, item_id uuid NOT NULL, quantity integer NOT NULL DEFAULT 1, acquired_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, instance_data jsonb, PRIMARY KEY (inventory_id) )


[User] List all patients who have insurance plans with group numbers, showing their patient IDs and the count of such plans per patient.

[Assistant] SELECT patient_id, COUNT(*) AS plan_count FROM healthcare.patient_insurance WHERE group_number IS NOT NULL GROUP BY patient_id;

[User] Actually, I only need patients who have more than 2 such plans.

[Assistant] SELECT patient_id, COUNT(*) AS plan_count FROM healthcare.patient_insurance WHERE group_number IS NOT NULL GROUP BY patient_id HAVING COUNT(*) > 2;

[User] Can you also include the earliest effective date among these plans for each patient?

[Assistant] SELECT patient_id, COUNT(*) AS plan_count, MIN(effective_date) AS earliest_effective_date FROM healthcare.patient_insurance WHERE group_number IS NOT NULL GROUP BY patient_id HAVING COUNT(*) > 2;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.patient_insurance (
    patient_insurance_id character varying(64) NOT NULL, -- unique identifier for this patient-plan link
    patient_id character varying(64) NOT NULL, -- FK to patients table
    plan_id character varying(64) NOT NULL, -- FK to insurance_plans table
    policy_number character varying(100) NOT NULL, -- patient's policy number
    group_number character varying(100), -- group number, if applicable
    subscriber_name character varying(200), -- name of the primary policy holder
    effective_date date NOT NULL, -- date the coverage begins
    expiration_date date, -- date the coverage ends (if known)
    is_primary boolean NOT NULL DEFAULT true, -- indicates if this is the primary insurance
    PRIMARY KEY (patient_insurance_id),
    UNIQUE (patient_id, plan_id, policy_number) -- ensure a patient doesn't have the same policy twice
)


[User] List all claims that were reported more than 30 days after the incident date.

[Assistant] SELECT claim_id, policy_id, customer_id, incident_date, reported_date FROM insurance.claims WHERE DATEDIFF(reported_date, incident_date) > 30;

[User] Now show only claims that are still pending (status = 'pending').

[Assistant] SELECT claim_id, policy_id, customer_id, incident_date, reported_date FROM insurance.claims WHERE DATEDIFF(reported_date, incident_date) > 30 AND status = 'pending';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.claims ( claim_id.text, policy_id.text, customer_id.text, incident_date.timestamp, reported_date.timestamp, description.text, estimated_loss.numeric, status.text, settlement_amount.numeric, settlement_date.date, claim_handler_id.text, police_report_number.text )


[User] Show me all distinct dosage forms used in prescriptions.

[Assistant] SELECT DISTINCT dosage FROM healthcare.prescriptions;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.prescriptions ( prescription_id text PRIMARY KEY, 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 int, prescription_date timestamp )


[User] Give me a list of the usernames and email addresses of users who have participated in at least one conversation.

[Assistant]
SELECT DISTINCT u.username, u.email
FROM social_media.users u
JOIN social_media.conversation_participants cp ON u.user_id = cp.user_id;

[User] Only include users who joined any conversation after March 1, 2024.

[Assistant]
SELECT DISTINCT u.username, u.email
FROM social_media.users u
JOIN social_media.conversation_participants cp ON u.user_id = cp.user_id
WHERE cp.joined_at > '2024-03-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users ( user_id character varying(64) NOT NULL, username character varying(50) NOT NULL UNIQUE, email character varying(128) NOT NULL UNIQUE, password_hash text NOT NULL, full_name character varying(100), profile_picture_url text, bio text, location character varying(100), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, is_verified boolean NOT NULL DEFAULT false, PRIMARY KEY (user_id) )
CREATE TABLE social_media.posts ( post_id.text, user_id.text, content.text, media_url.text, media_type.text, created_at.timestamp, updated_at.timestamp, visibility.text, location_lat.numeric, location_lon.numeric )
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.hashtags ( hashtag_id.text, tag_name.text, created_at.timestamp )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id.text, post_id.text, hashtag_id.text )
CREATE TABLE social_media.conversations ( conversation_id character varying(64) NOT NULL, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, last_message_at timestamp, is_group_chat boolean NOT NULL DEFAULT false, group_name character varying(100), PRIMARY KEY (conversation_id) )
CREATE TABLE social_media.conversation_participants ( participant_id text PRIMARY KEY, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )


[User] List all customers who reside in New York and were created in the system before 2023.

[Assistant] SELECT customer_id, first_name, last_name, created_at FROM insurance.customers WHERE state = 'NY' AND created_at < '2023-01-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.customers ( customer_id.text, first_name.text, last_name.text, date_of_birth.date, ssn_hash.text, address_line1.text, address_line2.text, city.text, state.text, zip_code.text, country.text, phone_number.text, email.text, created_at.timestamp, updated_at.timestamp, status.text )


[User] How many policies were canceled in the previous month, grouped by cancellation reason?

[Assistant]
SELECT cancellation_reason,
       COUNT(*) AS canceled_count
FROM insurance.policies
WHERE cancellation_date BETWEEN date_trunc('month', CURRENT_DATE) - INTERVAL '1 month'
                             AND date_trunc('month', CURRENT_DATE) - INTERVAL '1 day'
GROUP BY cancellation_reason;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.policies ( policy_id text, customer_id text, product_id text, agent_id text, policy_number text, start_date date, end_date date, premium_amount numeric, coverage_limit numeric, deductible numeric, status text, issued_at timestamp, cancellation_date date, cancellation_reason text )


[User] What is the current market cap and 7-day price change percentage for the top 3 narratives by trend rank?

[Assistant] SELECT narrative, market_cap, price_change_percentage_7d FROM narrative_info ORDER BY trend_rank ASC LIMIT 3;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##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 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 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] Find cases where an address received tokens in one transfer and then sent tokens in another. List the receive transfer_id, the send transfer_id, the address, and both transfer values.

[Assistant]
SELECT recv.transfer_id AS receive_transfer_id,
       send.transfer_id AS send_transfer_id,
       recv.to_address AS address,
       recv.value       AS received_value,
       send.value       AS sent_value
FROM web3.token_transfers recv
JOIN web3.token_transfers send
  ON recv.to_address = send.from_address;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.token_transfers (
    transfer_id character varying(64) NOT NULL,  -- unique identifier for the transfer
    token_id character varying(64) NOT NULL, -- identifier of the token being transferred
    from_address character varying(128) NOT NULL, -- address of the sender
    to_address character varying(128) NOT NULL, -- address of the receiver
    value numeric(38,14) NOT NULL, -- amount of tokens transferred
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction containing the transfer
    log_index integer NOT NULL, -- index of the transfer log in the transaction
    PRIMARY KEY (transfer_id)
)


[User] Could you list each game title along with its developer's name and the total number of servers hosting it?

[Assistant]
SELECT g.title, d.name AS developer_name, COUNT(s.server_id) AS server_count
FROM gaming_technology.games g
LEFT JOIN gaming_technology.developers d ON g.developer_id = d.developer_id
LEFT JOIN gaming_technology.servers s ON g.game_id = s.game_id
GROUP BY g.title, d.name;

[User] Actually, please include only servers with status = 'online' and exclude games with zero online servers.

[Assistant]
SELECT g.title, d.name AS developer_name, COUNT(s.server_id) AS server_count
FROM gaming_technology.games g
JOIN gaming_technology.developers d ON g.developer_id = d.developer_id
JOIN gaming_technology.servers s ON g.game_id = s.game_id
WHERE s.status = 'online'
GROUP BY g.title, d.name;

[User] I want to see only developers based in 'USA'.

[Assistant]
SELECT g.title, d.name AS developer_name, COUNT(s.server_id) AS server_count
FROM gaming_technology.games g
JOIN gaming_technology.developers d ON g.developer_id = d.developer_id
JOIN gaming_technology.servers s ON g.game_id = s.game_id AND s.status = 'online'
WHERE d.country = 'USA'
GROUP BY g.title, d.name;

[User] Finally, sort the results by server_count in descending order.

[Assistant]
SELECT g.title, d.name AS developer_name, COUNT(s.server_id) AS server_count
FROM gaming_technology.games g
JOIN gaming_technology.developers d ON g.developer_id = d.developer_id
JOIN gaming_technology.servers s ON g.game_id = s.game_id AND s.status = 'online'
WHERE d.country = 'USA'
GROUP BY g.title, d.name
ORDER BY server_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE gaming_technology.games ( game_id uuid, 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 timestamp with time zone )
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 timestamp with time zone )
CREATE TABLE gaming_technology.achievements ( achievement_id uuid, game_id uuid, name text, description text, icon_url text, points integer, hidden boolean )
CREATE TABLE gaming_technology.player_achievements ( player_achievement_id uuid, player_id uuid, achievement_id uuid, unlocked_at timestamp with time zone )
CREATE TABLE gaming_technology.in_game_items ( item_id uuid, game_id uuid, item_name text, item_type text, description text, rarity text, cost_currency text, cost_amount numeric, attributes jsonb )
CREATE TABLE gaming_technology.player_inventory ( inventory_id uuid, player_id uuid, item_id uuid, quantity integer, acquired_at timestamp with time zone, instance_data jsonb )


[User] I want the list of participants in group chats who have unread messages, including conversation ID, group name, user ID, and the timestamp of the last message that the user hasn’t read.

[Assistant]
SELECT cp.conversation_id,
       c.group_name,
       cp.user_id,
       c.last_message_at
FROM social_media.conversations c
JOIN social_media.conversation_participants cp
  ON c.conversation_id = cp.conversation_id
WHERE c.is_group_chat = true
  AND (cp.last_read_at IS NULL OR cp.last_read_at < c.last_message_at);

[User] Now, only include those group chats where the last unread message was sent in the past 7 days.

[Assistant]
SELECT cp.conversation_id,
       c.group_name,
       cp.user_id,
       c.last_message_at
FROM social_media.conversations c
JOIN social_media.conversation_participants cp
  ON c.conversation_id = cp.conversation_id
WHERE c.is_group_chat = true
  AND (cp.last_read_at IS NULL OR cp.last_read_at < c.last_message_at)
  AND c.last_message_at >= now() - INTERVAL '7 days';

[User] Also calculate the delay in hours between the last message and the user's last read time and include it as unread_delay_hours.

[Assistant]
SELECT cp.conversation_id,
       c.group_name,
       cp.user_id,
       c.last_message_at,
       EXTRACT(EPOCH FROM (c.last_message_at - COALESCE(cp.last_read_at, '1970-01-01'))) / 3600 AS unread_delay_hours
FROM social_media.conversations c
JOIN social_media.conversation_participants cp
  ON c.conversation_id = cp.conversation_id
WHERE c.is_group_chat = true
  AND (cp.last_read_at IS NULL OR cp.last_read_at < c.last_message_at)
  AND c.last_message_at >= now() - INTERVAL '7 days';

[User] Finally, order the results by unread_delay_hours descending and limit the output to 10 records.

[Assistant]
SELECT cp.conversation_id,
       c.group_name,
       cp.user_id,
       c.last_message_at,
       EXTRACT(EPOCH FROM (c.last_message_at - COALESCE(cp.last_read_at, '1970-01-01'))) / 3600 AS unread_delay_hours
FROM social_media.conversations c
JOIN social_media.conversation_participants cp
  ON c.conversation_id = cp.conversation_id
WHERE c.is_group_chat = true
  AND (cp.last_read_at IS NULL OR cp.last_read_at < c.last_message_at)
  AND c.last_message_at >= now() - INTERVAL '7 days'
ORDER BY unread_delay_hours DESC
LIMIT 10;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
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, user_id text, post_id text, comment_id text, created_at timestamp )
CREATE TABLE social_media.follows ( follow_id text, follower_user_id text, following_user_id text, created_at timestamp )
CREATE TABLE social_media.messages ( message_id text, conversation_id text, sender_user_id text, content text, media_url text, media_type text, sent_at timestamp, read_at timestamp )
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 )


[User] List all combinations of manufacturers and generic names. For each combination, display the manufacturer, generic_name, and the number of medications.

[Assistant] SELECT manufacturer, generic_name, COUNT(*) AS medication_count FROM healthcare.medications GROUP BY manufacturer, generic_name;

[User] Only show combinations where there are at least 3 medications and exclude rows where generic_name is missing.

[Assistant] SELECT manufacturer, generic_name, COUNT(*) AS medication_count FROM healthcare.medications WHERE generic_name IS NOT NULL AND generic_name <> '' GROUP BY manufacturer, generic_name HAVING COUNT(*) >= 3;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.medications ( medication_id character varying(64) NOT NULL, medication_name character varying(255) NOT NULL, generic_name character varying(255), manufacturer character varying(100), ndc_code character varying(20) UNIQUE, description text, PRIMARY KEY (medication_id) )


[User] For each player, show the player_id and the count of inventory items they acquired with a quantity greater than 1.

[Assistant] SELECT player_id, COUNT(inventory_id) AS items_qty_gt_1_count FROM gaming_technology.player_inventory WHERE quantity > 1 GROUP BY player_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE gaming_technology.players ( player_id uuid NOT NULL DEFAULT gen_random_uuid(), username character varying(100) NOT NULL UNIQUE, email character varying(255) NOT NULL UNIQUE, password_hash text NOT NULL, registration_date timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, last_login timestamp with time zone, country_code character(2), status character varying(20) NOT NULL DEFAULT 'active', profile_data jsonb, PRIMARY KEY (player_id) )
CREATE TABLE gaming_technology.games ( game_id uuid NOT NULL DEFAULT gen_random_uuid(), title character varying(200) NOT NULL, developer_id uuid NOT NULL, publisher_id uuid, genre character varying(100), release_date date, description text, platform character varying(50) NOT NULL, engine character varying(100), website character varying(255), PRIMARY KEY (game_id) )
CREATE TABLE gaming_technology.servers ( server_id uuid NOT NULL DEFAULT gen_random_uuid(), game_id uuid NOT NULL, server_name character varying(150), region character varying(50) NOT NULL, ip_address character varying(45), port integer, current_players integer NOT NULL DEFAULT 0, max_players integer NOT NULL, status character varying(30) NOT NULL DEFAULT 'offline', last_heartbeat timestamp with time zone, PRIMARY KEY (server_id) )
CREATE TABLE gaming_technology.in_game_items ( item_id uuid NOT NULL DEFAULT gen_random_uuid(), game_id uuid NOT NULL, item_name character varying(150) NOT NULL, item_type character varying(50) NOT NULL, description text, rarity character varying(30), cost_currency character varying(10), cost_amount numeric(12, 2), attributes jsonb, PRIMARY KEY (item_id) )
CREATE TABLE gaming_technology.player_inventory ( inventory_id uuid NOT NULL DEFAULT gen_random_uuid(), player_id uuid NOT NULL, item_id uuid NOT NULL, quantity integer NOT NULL DEFAULT 1, acquired_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, instance_data jsonb, PRIMARY KEY (inventory_id) )


[User] For each NFT collection deployed on Ethereum, count the number of distinct wallets that have ever held any token from that collection.

[Assistant]
SELECT
  nc.contract_address,
  nc.name,
  COUNT(DISTINCT nh.wallet_address) AS holder_count
FROM nft_collections nc
JOIN nft_holder_historical nh
  ON nc.contract_address = nh.contract_address
WHERE nc.blockchain = 'Ethereum'
GROUP BY nc.contract_address, nc.name;

[User] Include each collection's token_count and floor_price from nft_collections.

[Assistant]
SELECT
  nc.contract_address,
  nc.name,
  nc.token_count,
  nc.floor_price,
  COUNT(DISTINCT nh.wallet_address) AS holder_count
FROM nft_collections nc
JOIN nft_holder_historical nh
  ON nc.contract_address = nh.contract_address
WHERE nc.blockchain = 'Ethereum'
GROUP BY
  nc.contract_address,
  nc.name,
  nc.token_count,
  nc.floor_price;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE erc20_balances ( block_number.bigint, contract_address.text, wallet_address.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_metadata ( object_id varchar, coin_type varchar, status varchar, decimals bigint, description varchar, icon_url varchar, symbol varchar, name varchar )
CREATE TABLE sui_nfts ( object_id varchar, status varchar, collection_type varchar, package_id varchar, previous_transaction varchar, display varchar, owner varchar, name varchar )
CREATE TABLE nft_collections (
    blockchain varchar NOT NULL, -- blockchain fields for the functionType  in contract
    contract_address varchar NOT NULL, -- Contract address(with bloom filter)
    name varchar NOT NULL, -- name fields for the functionType  in contract
    symbol varchar NOT NULL, -- symbol fields for the functionType  in contract
    deploy_block_number bigint NOT NULL, -- deploy_block_number fields for the functionType  in contract
    deploy_block_time bigint NOT NULL, -- deploy_block_time fields for the functionType  in contract
    erc_type varchar NOT NULL, -- The type of token
    owner varchar NOT NULL, -- owner fields for the functionType  in contract
    traits varchar NOT NULL, -- traits fields for the functionType  in contract
    description varchar NOT NULL, -- description fields for the functionType  in contract
    slug varchar NOT NULL, -- slug fields for the functionType  in contract
    media_info varchar NOT NULL, -- media_info fields for the functionType  in contract
    image_url varchar NOT NULL, -- image_url fields for the functionType  in contract
    banner_image_url varchar NOT NULL, -- banner_image_url fields for the functionType  in contract
    updated_at bigint NOT NULL, -- updated_at fields for the functionType  in contract
    banner varchar NOT NULL, -- banner fields for the functionType  in contract
    token_count bigint NOT NULL, -- token_count fields for the functionType  in contract
    floor_price varchar NOT NULL, -- floor_price fields for the functionType  in contract
    floor_price_symbol varchar NOT NULL, -- floor_price_symbol fields for the functionType  in contract
    floor_price_contract varchar NOT NULL, -- floor_price_contract fields for the functionType  in contract
    pk integer NOT NULL  -- Partition key for the table(floor(deploy_block_time / 1000 / 86400 / 30))
)
CREATE TABLE token_prices ( uuid varchar, blockchain varchar, address varchar, decimals bigint, symbol varchar, 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_info (
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the inscription (matches block_timestamp in transactions table)
    block_number bigint NOT NULL, -- Block number containing the inscription (matches block_number in transactions table)
    tx_index integer NOT NULL, -- Index of the transaction containing the inscription (matches transaction_index in transactions table)
    tx_hash varchar(66) NOT NULL, -- Unique identifier of the transaction containing the inscription (matches hash in transactions table)
    tick varchar NOT NULL, -- Token tick
    max_supply decimal(38,0) NOT NULL, -- Max supply
    lim decimal(38,0) NOT NULL, -- Limit of each mint
    wlim decimal(38,0) NOT NULL, -- Limit of each address can maximum mint
    dec integer NOT NULL, -- Decimal for minimum divie
    creator varchar(42) NOT NULL  -- Address originating the inscription (matches from_address in transactions table)
)
CREATE TABLE token_balances_bitcoin ( block_number bigint, block_timestamp timestamp, tick varchar, wallet_address varchar, total_supply varchar, amount varchar )
CREATE TABLE token_activities_avalanche ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, log_index integer NOT NULL, type varchar(20) NOT NULL, tick varchar(255) NOT NULL, id varchar(255) NOT NULL, amt decimal(38,0) NOT NULL, from_address varchar(42) NOT NULL, to_address varchar(42) NOT NULL )
CREATE TABLE token_balances_avalanche ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )


[User] List service orders placed in the last 7 days, showing order_id, service_name, guest full name, and order_timestamp.

[Assistant]
SELECT so.order_id, s.service_name, g.first_name || ' ' || g.last_name AS guest_name, so.order_timestamp
FROM hospitality_technology.service_orders so
JOIN hospitality_technology.services s ON so.service_id = s.service_id
JOIN hospitality_technology.guests g ON so.guest_id = g.guest_id
WHERE so.order_timestamp >= current_date - INTERVAL '7 days';

[User] Filter to only those orders with status 'Delivered' and sort by delivery_timestamp ascending.

[Assistant]
SELECT so.order_id, s.service_name, g.first_name || ' ' || g.last_name AS guest_name, so.order_timestamp, so.delivery_timestamp
FROM hospitality_technology.service_orders so
JOIN hospitality_technology.services s ON so.service_id = s.service_id
JOIN hospitality_technology.guests g ON so.guest_id = g.guest_id
WHERE so.order_timestamp >= current_date - INTERVAL '7 days'
  AND so.status = 'Delivered'
ORDER BY so.delivery_timestamp ASC;

[User] Also include the staff member who delivered the service as delivered_by (full name) and limit to 10 records.

[Assistant]
SELECT so.order_id, s.service_name, g.first_name || ' ' || g.last_name AS guest_name, so.order_timestamp, so.delivery_timestamp, st.first_name || ' ' || st.last_name AS delivered_by
FROM hospitality_technology.service_orders so
JOIN hospitality_technology.services s ON so.service_id = s.service_id
JOIN hospitality_technology.guests g ON so.guest_id = g.guest_id
JOIN hospitality_technology.staff st ON so.staff_id_delivered = st.staff_id
WHERE so.order_timestamp >= current_date - INTERVAL '7 days'
  AND so.status = 'Delivered'
ORDER BY so.delivery_timestamp ASC
LIMIT 10;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.rooms ( room_id.text, property_id.text, room_number.text, room_type_id.text, floor.integer, status.text, is_smoking.boolean, features.text, current_condition.text, last_cleaned_at.timestamp )
CREATE TABLE hospitality_technology.room_types ( room_type_id.text, property_id.text, type_name.text, description.text, base_rate.numeric, max_occupancy.integer, bed_type.text, area_sqft.numeric, amenities.text )
CREATE TABLE hospitality_technology.guests ( guest_id.text, 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, 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.integer, num_children.integer, 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, 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.integer, manager_id.text, created_at.timestamp )
CREATE TABLE hospitality_technology.services ( service_id.text, 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, reservation_id.text, guest_id.text, service_id.text, staff_id_ordered.text, staff_id_delivered.text, order_timestamp.timestamp, delivery_timestamp.timestamp, quantity.integer, unit_price.numeric, total_price.numeric, status.text, notes.text, bill_id.text )
CREATE TABLE hospitality_technology.payments ( payment_id.text, 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 )
CREATE TABLE hospitality_technology.reviews ( review_id.text, property_id.text, reservation_id.text, guest_id.text, rating_overall.integer, rating_cleanliness.integer, rating_service.integer, rating_location.integer, rating_value.integer, comment.text, review_source.text, review_date.timestamp, is_public.boolean, staff_response.text, response_staff_id.text, response_date.timestamp )


[User] Show me assets along with their associated 'symbol' metadata value. Assume an assets table with asset_id exists.

[Assistant] SELECT a.asset_id, m.value FROM assets a JOIN metadata m ON a.asset_id = m.asset_id WHERE m.key = 'symbol'

[User] Now, also include the 'name' metadata value for these assets in the same result.

[Assistant] SELECT a.asset_id, m_symbol.value AS symbol, m_name.value AS name FROM assets a LEFT JOIN metadata m_symbol ON a.asset_id = m_symbol.asset_id AND m_symbol.key = 'symbol' LEFT JOIN metadata m_name ON a.asset_id = m_name.asset_id AND m_name.key = 'name'

[User] For assets that have both 'symbol' and 'name' metadata, list the asset ID and the count of *all* metadata entries they have.

[Assistant] SELECT a.asset_id, COUNT(m_all.metadata_id) FROM assets a JOIN metadata m_symbol ON a.asset_id = m_symbol.asset_id AND m_symbol.key = 'symbol' JOIN metadata m_name ON a.asset_id = m_name.asset_id AND m_name.key = 'name' JOIN metadata m_all ON a.asset_id = m_all.asset_id GROUP BY a.asset_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 trading_platform.utxos ( utxo_id text PRIMARY KEY, transaction_id text, output_index int, address text, amount numeric, spent boolean )
CREATE TABLE trading_platform.dapps ( dapp_id text PRIMARY KEY, name text, description text, url text )
CREATE TABLE trading_platform.peers ( peer_id text PRIMARY KEY, ip_address text, port int, last_seen timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text PRIMARY KEY, asset_id text, key text, value text )
CREATE TABLE trading_platform.notifications ( notification_id text PRIMARY KEY, user_id text, message text, sent_at timestamp, read_at timestamp )


[User] List all assets mentioned in DApp descriptions along with the DApp name and URL.

[Assistant]
SELECT a.name AS asset_name,
       a.symbol AS asset_symbol,
       d.name AS dapp_name,
       d.url
FROM trading_platform.assets a
JOIN trading_platform.dapps d
  ON d.description ILIKE '%' || a.symbol || '%';

[User] Actually, only include assets of type 'cryptocurrency'.

[Assistant]
SELECT a.name AS asset_name,
       a.symbol AS asset_symbol,
       d.name AS dapp_name,
       d.url
FROM trading_platform.assets a
JOIN trading_platform.dapps d
  ON d.description ILIKE '%' || a.symbol || '%'
WHERE a.type = 'cryptocurrency';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
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 character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)


[User] List all token symbols that have a positive ROI and a Realized Ratio greater than 0.7. Show their token symbol, chain, ROI, and Realized Ratio.

[Assistant] SELECT token_symbol, chain, roi, realized_ratio FROM smart_money_token_performance WHERE roi > 0 AND realized_ratio > 0.7;

[User] For those tokens, can you also display their PNL and Net Flow?

[Assistant] SELECT token_symbol, chain, roi, realized_ratio, pnl, net_flow FROM smart_money_token_performance WHERE roi > 0 AND realized_ratio > 0.7;

[User] Refine the results further to only include tokens where the PNL is greater than $500.

[Assistant] SELECT token_symbol, chain, roi, realized_ratio, pnl, net_flow FROM smart_money_token_performance WHERE roi > 0 AND realized_ratio > 0.7 AND pnl > 500;

[User] From these filtered tokens, find the token with the highest PNL on each chain. Display chain, token symbol, PNL, ROI, Realized Ratio, and Net Flow.

[Assistant] SELECT chain, token_symbol, pnl, roi, realized_ratio, net_flow FROM ( SELECT token_symbol, chain, pnl, roi, realized_ratio, net_flow, ROW_NUMBER() OVER(PARTITION BY chain ORDER BY pnl DESC) as rn FROM smart_money_token_performance WHERE roi > 0 AND realized_ratio > 0.7 AND pnl > 500 ) ranked_filtered_performance WHERE rn = 1;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE smart_money_token_performance ( token_address character varying(100) NOT NULL, token_symbol character varying(100), pnl numeric(38,2), net_flow numeric(38,2), avg_cost numeric(38,16), price double precision, realized_ratio numeric(10,2), roi numeric(10,2), chain character varying(100) )


[User] Show each route's route_id and the total number of completed trips associated with it.

[Assistant]
SELECT route_id, COUNT(*) AS completed_trip_count
FROM transportation.trips
WHERE status = 'Completed'
GROUP BY route_id;

[User] Now, only include routes with more than 5 completed trips and order by completed_trip_count descending.

[Assistant]
SELECT route_id, COUNT(*) AS completed_trip_count
FROM transportation.trips
WHERE status = 'Completed'
GROUP BY route_id
HAVING COUNT(*) > 5
ORDER BY completed_trip_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##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 text, 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 )
CREATE TABLE transportation.trips ( trip_id text, route_id text, vehicle_id text, driver_id text, scheduled_departure timestamp, actual_departure timestamp, scheduled_arrival timestamp, actual_arrival timestamp, origin_location_id text, destination_location_id text, status text, passenger_count integer, cargo_manifest_id text )
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 text, vehicle_id text, service_date date, odometer_reading integer, service_type text, description text, cost numeric, mechanic_name text, next_service_due_date date )
CREATE TABLE transportation.passengers ( passenger_id text, first_name text, last_name text, email text, phone_number text, date_of_birth date, loyalty_program_id text, created_at timestamp )


[User] List all clients along with their case_number and case_type for cases that are currently 'Open'.

[Assistant]
SELECT c.first_name, c.last_name, c.email, cs.case_number, cs.case_type
FROM legal_services.clients AS c
JOIN legal_services.cases AS cs
  ON c.client_id = cs.client_id
WHERE cs.status = 'Open';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.clients ( client_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, company_name character varying(200), email character varying(128) UNIQUE NOT NULL, phone character varying(32), address text, date_registered timestamp NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (client_id) )
CREATE TABLE legal_services.lawyers ( lawyer_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, bar_number character varying(64) UNIQUE NOT NULL, firm_id character varying(64), email character varying(128) UNIQUE NOT NULL, phone character varying(32), specialization text, hire_date timestamp NOT NULL, is_partner boolean DEFAULT false, PRIMARY KEY (lawyer_id) )
CREATE TABLE legal_services.law_firms ( firm_id character varying(64) NOT NULL, firm_name character varying(200) NOT NULL, address text NOT NULL, phone character varying(32), website character varying(255), founded_date date, managing_partner_id character varying(64), PRIMARY KEY (firm_id) )
CREATE TABLE legal_services.cases ( case_id character varying(64) NOT NULL, case_number character varying(100) UNIQUE, case_name text NOT NULL, client_id character varying(64) NOT NULL, lead_lawyer_id character varying(64) NOT NULL, case_type character varying(100) NOT NULL, status character varying(50) NOT NULL, date_opened timestamp NOT NULL, date_closed timestamp, description text, court_jurisdiction character varying(128), PRIMARY KEY (case_id) )
CREATE TABLE legal_services.documents ( document_id character varying(64) NOT NULL, case_id character varying(64) NOT NULL, document_name character varying(255) NOT NULL, document_type character varying(100), storage_path text NOT NULL, uploaded_by_lawyer_id character varying(64), upload_timestamp timestamp NOT NULL, version integer DEFAULT 1, description text, PRIMARY KEY (document_id) )
CREATE TABLE legal_services.time_entries ( entry_id character varying(64) NOT NULL, case_id character varying(64) NOT NULL, lawyer_id character varying(64) NOT NULL, date_worked date NOT NULL, hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), billing_rate numeric(10, 2) NOT NULL, description text NOT NULL, is_billable boolean DEFAULT true, is_billed boolean DEFAULT false, invoice_id character varying(64), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (entry_id) )
CREATE TABLE legal_services.appointments ( appointment_id character varying(64) NOT NULL, client_id character varying(64) NOT NULL, lawyer_id character varying(64) NOT NULL, case_id character varying(64), start_time timestamp NOT NULL, end_time timestamp NOT NULL, location text, subject character varying(255), notes text, status character varying(50) NOT NULL, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (appointment_id) )


[User] How many lawyers who are partners were hired in each year? Show the hire year and the count.

[Assistant] SELECT strftime('%Y', hire_date) AS hire_year ,  count(lawyer_id) FROM legal_services.lawyers WHERE is_partner  =  true GROUP BY hire_year

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
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)
)


[User] How many likes were given to comments in June 2024?

[Assistant]
SELECT COUNT(*) AS comment_likes_count
FROM social_media.likes
WHERE comment_id IS NOT NULL
  AND DATE_TRUNC('month', created_at) = '2024-06-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.comments ( comment_id character varying(64) NOT NULL, post_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, parent_comment_id character varying(64), content text NOT NULL, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (comment_id) )
CREATE TABLE social_media.likes ( like_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, post_id character varying(64), comment_id character varying(64), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (like_id), CONSTRAINT unique_user_like UNIQUE (user_id, post_id, comment_id), CONSTRAINT check_like_target CHECK (post_id IS NOT NULL OR comment_id IS NOT NULL) )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id character varying(64) NOT NULL, post_id character varying(64) NOT NULL, hashtag_id character varying(64) NOT NULL, PRIMARY KEY (post_hashtag_id), CONSTRAINT unique_post_hashtag UNIQUE (post_id, hashtag_id) )
CREATE TABLE social_media.conversations ( conversation_id character varying(64) NOT NULL, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, last_message_at timestamp, is_group_chat boolean NOT NULL DEFAULT false, group_name character varying(100), PRIMARY KEY (conversation_id) )
CREATE TABLE social_media.notifications ( notification_id character varying(64) NOT NULL, recipient_user_id character varying(64) NOT NULL, sender_user_id character varying(64), notification_type character varying(30) NOT NULL, target_entity_id character varying(64), target_entity_type character varying(20), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, read_at timestamp, PRIMARY KEY (notification_id) )
CREATE TABLE social_media.user_settings ( setting_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL UNIQUE, theme character varying(20) DEFAULT 'light', email_notifications_enabled boolean DEFAULT true, push_notifications_enabled boolean DEFAULT true, private_profile boolean DEFAULT false, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (setting_id) )


[User] What is the total revenue generated by ticket sales at the station with ID 'ST101' for the past month?

[Assistant] I'm sorry, but I can't provide information on the revenue generated by ticket sales as this data is not available in the current database table. The table only contains details about station information such as name, location, and platform count. If you have another question or need assistance with something else related to the station data, I'm happy to help.

System:
You are an SQL statement expert and you can refuse the user's question if the question is not related to the table structure. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE train_station_management.stations ( station_id.text, station_name.text, city.text, state_province.text, country_code.text, address.text, timezone.text, number_of_platforms.integer, created_at.timestamp, last_updated_at.timestamp )


[User] Give me a breakdown of the number of reviews per day for the last 14 days, including the review_date and review count.

[Assistant]
SELECT DATE(review_date) AS review_day, COUNT(*) AS review_count
FROM hospitality_technology.reviews
WHERE review_date >= CURRENT_DATE - INTERVAL '14 days'
GROUP BY DATE(review_date)
ORDER BY review_day ASC;

[User] Add the number of public reviews for each day in a separate column named public_review_count.

[Assistant]
SELECT DATE(review_date) AS review_day,
       COUNT(*) AS review_count,
       SUM(CASE WHEN is_public THEN 1 ELSE 0 END) AS public_review_count
FROM hospitality_technology.reviews
WHERE review_date >= CURRENT_DATE - INTERVAL '14 days'
GROUP BY DATE(review_date)
ORDER BY review_day ASC;

[User] Now, also include the number of reviews per day with a rating_overall below 3 as a column called low_rating_count.

[Assistant]
SELECT DATE(review_date) AS review_day,
       COUNT(*) AS review_count,
       SUM(CASE WHEN is_public THEN 1 ELSE 0 END) AS public_review_count,
       SUM(CASE WHEN rating_overall < 3 THEN 1 ELSE 0 END) AS low_rating_count
FROM hospitality_technology.reviews
WHERE review_date >= CURRENT_DATE - INTERVAL '14 days'
GROUP BY DATE(review_date)
ORDER BY review_day ASC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.reviews ( review_id text, property_id text, reservation_id text, guest_id text, rating_overall integer, rating_cleanliness integer, rating_service integer, rating_location integer, rating_value integer, comment text, review_source text, review_date timestamp, is_public boolean, staff_response text, response_staff_id text, response_date timestamp )


[User] What are the personal contact details of the staff member associated with staff_id 'STAFF789' who worked on a specific maintenance record?

[Assistant] I'm sorry, but I can't provide personal contact details of staff members as this information is not stored in the maintenance_records table and is outside the scope of the available data.

System:
You are an SQL statement expert and you can refuse the user's question if the question is not related to the table structure. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE train_station_management.maintenance_records ( record_id text, asset_id text, asset_type text, maintenance_type text, staff_id text, start_datetime timestamp, end_datetime timestamp, description text, cost numeric, status text )


[User] For each security exchange, what is the average daily high price and the total volume recorded in market data for securities listed on that exchange over the past 6 months? Include the exchange name.

[Assistant] SELECT T2.exchange, AVG(T1.high_price) AS avg_daily_high_price, SUM(T1.volume) AS total_volume FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id WHERE T1.data_timestamp >= CURRENT_DATE - INTERVAL '6 months' GROUP BY T2.exchange;

[User] Only include exchanges where the total volume is greater than 10,000,000.

[Assistant] SELECT T2.exchange, AVG(T1.high_price) AS avg_daily_high_price, SUM(T1.volume) AS total_volume FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id WHERE T1.data_timestamp >= CURRENT_DATE - INTERVAL '6 months' GROUP BY T2.exchange HAVING SUM(T1.volume) > 10000000;

[User] Also, only show results for securities with a security type of 'Equity'.

[Assistant] SELECT T2.exchange, AVG(T1.high_price) AS avg_daily_high_price, SUM(T1.volume) AS total_volume FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id WHERE T1.data_timestamp >= CURRENT_DATE - INTERVAL '6 months' AND T2.security_type = 'Equity' GROUP BY T2.exchange HAVING SUM(T1.volume) > 10000000;

[User] Finally, order the results by average high price descending and show only the top 5 exchanges.

[Assistant] SELECT T2.exchange, AVG(T1.high_price) AS avg_daily_high_price, SUM(T1.volume) AS total_volume FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id WHERE T1.data_timestamp >= CURRENT_DATE - INTERVAL '6 months' AND T2.security_type = 'Equity' GROUP BY T2.exchange HAVING SUM(T1.volume) > 10000000 ORDER BY avg_daily_high_price DESC LIMIT 5;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
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)
)


[User] Show me the top 3 tokens by USD value inflow where smart money was buying (type = 1), along with their chain information.

[Assistant] SELECT token_symbol, chain, usd_value FROM smart_money_token_inflow WHERE type = 1 ORDER BY usd_value DESC LIMIT 3;

[User] Can you filter these results to only include tokens from the Ethereum chain?

[Assistant] SELECT token_symbol, chain, usd_value FROM smart_money_token_inflow WHERE type = 1 AND chain = 'Ethereum' ORDER BY usd_value DESC LIMIT 3;

[User] Now include the average price for these tokens as well.

[Assistant] SELECT token_symbol, chain, usd_value, avg_price FROM smart_money_token_inflow WHERE type = 1 AND chain = 'Ethereum' ORDER BY usd_value DESC LIMIT 3;

[User] Finally, order these results by average price instead of USD value.

[Assistant] SELECT token_symbol, chain, usd_value, avg_price FROM smart_money_token_inflow WHERE type = 1 AND chain = 'Ethereum' ORDER BY avg_price DESC LIMIT 3;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
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_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] Find any two claims made by the same customer on the same day. Return customer_id, the two claim IDs, and the incident date.

[Assistant]
SELECT c1.customer_id,
       c1.claim_id AS claim1_id,
       c2.claim_id AS claim2_id,
       DATE(c1.incident_date) AS incident_date
FROM insurance.claims c1
JOIN insurance.claims c2
  ON c1.customer_id = c2.customer_id
 AND DATE(c1.incident_date) = DATE(c2.incident_date)
 AND c1.claim_id < c2.claim_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.claims ( claim_id text, policy_id text, customer_id text, incident_date timestamp, reported_date timestamp, description text, estimated_loss numeric, status text, settlement_amount numeric, settlement_date date, claim_handler_id text, police_report_number text )


[User] For each patient, find the next appointment after each one. Return patient_id, appointment_id, next_appointment_id, and the waiting time in minutes between them.

[Assistant]
SELECT A.patient_id,
       A.appointment_id AS current_id,
       B.appointment_id AS next_id,
       EXTRACT(EPOCH FROM (B.appointment_time - A.appointment_time)) / 60 AS wait_minutes
FROM healthcare.appointments A
JOIN healthcare.appointments B
  ON A.patient_id = B.patient_id
 AND B.appointment_time = (
       SELECT MIN(appointment_time)
       FROM healthcare.appointments
       WHERE patient_id = A.patient_id
         AND appointment_time > A.appointment_time
   );

[User] Now include only the pairs where the waiting time is less than 30 minutes.

[Assistant]
SELECT A.patient_id,
       A.appointment_id AS current_id,
       B.appointment_id AS next_id,
       EXTRACT(EPOCH FROM (B.appointment_time - A.appointment_time)) / 60 AS wait_minutes
FROM healthcare.appointments A
JOIN healthcare.appointments B
  ON A.patient_id = B.patient_id
 AND B.appointment_time = (
       SELECT MIN(appointment_time)
       FROM healthcare.appointments
       WHERE patient_id = A.patient_id
         AND appointment_time > A.appointment_time
   )
WHERE EXTRACT(EPOCH FROM (B.appointment_time - A.appointment_time)) / 60 < 30;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.appointments ( appointment_id text PRIMARY KEY, patient_id text, doctor_id text, appointment_time timestamp, duration_minutes int, reason text, status text, location_id text, notes text, created_at timestamp )


[User] How many documents are there for each document_type? Show document_type and count ordered by the count in descending order.

[Assistant]
SELECT document_type,
       COUNT(*) AS count
FROM legal_services.documents
GROUP BY document_type
ORDER BY count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.documents ( document_id.text, case_id.text, document_name.text, document_type.text, storage_path.text, uploaded_by_lawyer_id.text, upload_timestamp.timestamp, version.integer, description.text )


[User] List pairs of citizens who share the same email domain.

[Assistant]
SELECT c1.first_name AS first1,
       c1.last_name AS last1,
       c2.first_name AS first2,
       c2.last_name AS last2,
       SPLIT_PART(c1.contact_email, '@', 2) AS domain
FROM government_services.citizens c1
JOIN government_services.citizens c2
  ON SPLIT_PART(c1.contact_email, '@', 2) = SPLIT_PART(c2.contact_email, '@', 2)
 AND c1.citizen_id < c2.citizen_id
WHERE c1.contact_email IS NOT NULL
  AND c2.contact_email IS NOT NULL;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens (
    citizen_id character varying(64) NOT NULL,  -- unique identifier for the citizen
    national_id_number character varying(128) NOT NULL UNIQUE, -- official national identification number
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    date_of_birth date NOT NULL,
    gender character varying(20),
    primary_address text NOT NULL, -- full primary residential address
    contact_email character varying(128) UNIQUE,
    contact_phone character varying(32),
    registration_date timestamp NOT NULL, -- when the citizen profile was created
    is_verified boolean DEFAULT false, -- whether identity has been officially verified
    PRIMARY KEY (citizen_id)
)


[User] List all auto loans (loan_id, principal_amount, interest_rate) where the current principal balance is less than 40% of the original principal amount, along with the account_id and the difference between principal_amount and current_principal_balance.

[Assistant] SELECT loan_id, principal_amount, interest_rate, account_id, (principal_amount - current_principal_balance) AS amount_paid FROM financial_services.loans WHERE loan_type = 'Auto' AND current_principal_balance < (0.4 * principal_amount);

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE financial_services.loans ( loan_id character varying(64) NOT NULL, account_id character varying(64) NOT NULL UNIQUE, loan_type character varying(50) NOT NULL, principal_amount numeric(19, 4) NOT NULL, current_principal_balance numeric(19, 4) NOT NULL, interest_rate numeric(6, 4) NOT NULL, term_months integer NOT NULL, origination_date date NOT NULL, maturity_date date NOT NULL, monthly_payment numeric(12, 4), collateral_description text, status character varying(32) NOT NULL, PRIMARY KEY (loan_id), FOREIGN KEY (account_id) REFERENCES financial_services.accounts(account_id) )


[User] Show me the list of hashtags that have been used, along with the time they were first used.

[Assistant]
SELECT tag_name, created_at
FROM social_media.hashtags;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(50) NOT NULL UNIQUE, -- user's unique handle
    email character varying(128) NOT NULL UNIQUE, -- user's email address
    password_hash text NOT NULL, -- hashed password
    full_name character varying(100), -- user's full name
    profile_picture_url text, -- URL to the profile picture
    bio text, -- short user biography
    location character varying(100), -- user's location
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of account creation
    updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of last profile update
    is_verified boolean NOT NULL DEFAULT false, -- verification status
    PRIMARY KEY (user_id)
)
CREATE TABLE social_media.comments (
    comment_id character varying(64) NOT NULL, -- unique identifier for the comment
    post_id character varying(64) NOT NULL, -- identifier of the post being commented on (FK to posts.post_id)
    user_id character varying(64) NOT NULL, -- identifier of the user who made the comment (FK to users.user_id)
    parent_comment_id character varying(64), -- identifier of the parent comment if it's a reply (FK to comments.comment_id)
    content text NOT NULL, -- textual content of the comment
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of comment creation
    updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of last comment edit
    PRIMARY KEY (comment_id)
)
CREATE TABLE social_media.likes (
    like_id character varying(64) NOT NULL, -- unique identifier for the like
    user_id character varying(64) NOT NULL, -- identifier of the user who liked (FK to users.user_id)
    post_id character varying(64), -- identifier of the post being liked (FK to posts.post_id, nullable)
    comment_id character varying(64), -- identifier of the comment being liked (FK to comments.comment_id, nullable)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of when the like occurred
    PRIMARY KEY (like_id),
    CONSTRAINT unique_user_like UNIQUE (user_id, post_id, comment_id), -- prevent duplicate likes
    CONSTRAINT check_like_target CHECK (post_id IS NOT NULL OR comment_id IS NOT NULL) -- ensure it likes something
)
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, -- unique identifier for the hashtag
    tag_name character varying(100) NOT NULL UNIQUE, -- the actual hashtag text (without '#')
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp when the hashtag was first used
    PRIMARY KEY (hashtag_id)
)
CREATE TABLE social_media.post_hashtags (
    post_hashtag_id character varying(64) NOT NULL, -- unique identifier for the post-hashtag link
    post_id character varying(64) NOT NULL, -- identifier of the post (FK to posts.post_id)
    hashtag_id character varying(64) NOT NULL, -- identifier of the hashtag (FK to hashtags.hashtag_id)
    PRIMARY KEY (post_hashtag_id),
    CONSTRAINT unique_post_hashtag UNIQUE (post_id, hashtag_id) -- prevent duplicate tags on a post
)
CREATE TABLE social_media.messages (
    message_id character varying(64) NOT NULL, -- unique identifier for the message
    conversation_id character varying(64) NOT NULL, -- identifier for the conversation thread (FK to conversations.conversation_id)
    sender_user_id character varying(64) NOT NULL, -- identifier of the sender (FK to users.user_id)
    content text, -- textual content of the message
    media_url text, -- URL to attached media (image/video)
    media_type character varying(20), -- type of media ('image', 'video', null)
    sent_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp when message was sent
    read_at timestamp, -- timestamp when message was read by recipient(s)
    PRIMARY KEY (message_id)
)
CREATE TABLE social_media.conversations (
    conversation_id character varying(64) NOT NULL, -- unique identifier for the conversation
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp when conversation was initiated
    last_message_at timestamp, -- timestamp of the last message in the conversation
    is_group_chat boolean NOT NULL DEFAULT false, -- indicates if it's a group chat or direct message
    group_name character varying(100), -- name of the group chat (if applicable)
    PRIMARY KEY (conversation_id)
)
CREATE TABLE social_media.conversation_participants (
    participant_id character varying(64) NOT NULL, -- unique identifier for the participant entry
    conversation_id character varying(64) NOT NULL, -- identifier of the conversation (FK to conversations.conversation_id)
    user_id character varying(64) NOT NULL, -- identifier of the user in the conversation (FK to users.user_id)
    joined_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp when user joined the conversation
    last_read_at timestamp, -- timestamp indicating up to when the user has read messages
    PRIMARY KEY (participant_id),
    CONSTRAINT unique_user_conversation UNIQUE (conversation_id, user_id) -- prevent user being added multiple times
)
CREATE TABLE social_media.notifications (
    notification_id character varying(64) NOT NULL, -- unique identifier for the notification
    recipient_user_id character varying(64) NOT NULL, -- user receiving the notification (FK to users.user_id)
    sender_user_id character varying(64), -- user triggering the notification (FK to users.user_id, can be null for system notifications)
    notification_type character varying(30) NOT NULL, -- type of notification ('like', 'comment', 'follow', 'mention', 'message')
    target_entity_id character varying(64), -- ID of the related entity (post_id, comment_id, user_id, conversation_id)
    target_entity_type character varying(20), -- type of the related entity ('post', 'comment', 'user', 'conversation')
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp notification was created
    read_at timestamp, -- timestamp notification was marked as read
    PRIMARY KEY (notification_id)
)
CREATE TABLE social_media.user_settings (
    setting_id character varying(64) NOT NULL, -- unique identifier for the setting entry
    user_id character varying(64) NOT NULL UNIQUE, -- user the settings belong to (FK to users.user_id)
    theme character varying(20) DEFAULT 'light', -- UI theme ('light', 'dark')
    email_notifications_enabled boolean DEFAULT true, -- enable/disable email notifications
    push_notifications_enabled boolean DEFAULT true, -- enable/disable push notifications
    private_profile boolean DEFAULT false, -- is the user profile private
    updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of last setting change
    PRIMARY KEY (setting_id)
)


[User] List each guest’s full name and the total number of service orders they have placed, ordered by order count descending.

[Assistant]
SELECT g.guest_id,
       g.first_name || ' ' || g.last_name AS full_name,
       COUNT(so.order_id) AS order_count
FROM hospitality_technology.guests g
LEFT JOIN hospitality_technology.service_orders so
  ON g.guest_id = so.guest_id
GROUP BY g.guest_id, full_name
ORDER BY order_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
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, 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 integer, num_children integer, 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.service_orders ( order_id.text, reservation_id.text, guest_id.text, service_id.text, staff_id_ordered.text, staff_id_delivered.text, order_timestamp.timestamp, delivery_timestamp.timestamp, quantity.integer, unit_price.numeric, total_price.numeric, status.text, notes.text, bill_id.text )
CREATE TABLE hospitality_technology.reviews ( review_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, reservation_id character varying(64) UNIQUE, guest_id character varying(64) NOT NULL, rating_overall integer, rating_cleanliness integer, rating_service integer, rating_location integer, rating_value integer, comment text, review_source character varying(100), review_date timestamp with time zone NOT NULL DEFAULT current_timestamp, is_public boolean DEFAULT true, staff_response text, response_staff_id character varying(64), response_date timestamp with time zone, PRIMARY KEY (review_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id), FOREIGN KEY (reservation_id) REFERENCES hospitality_technology.reservations(reservation_id), FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id), FOREIGN KEY (response_staff_id) REFERENCES hospitality_technology.staff(staff_id) )