[User] Find all documents of type 'Correspondence' uploaded in 2023. Show the document name, upload timestamp, and the name of the case it belongs to.

[Assistant] SELECT T1.document_name, T1.upload_timestamp, T2.case_name FROM legal_services.documents AS T1 JOIN legal_services.cases AS T2 ON T1.case_id = T2.case_id WHERE T1.document_type = 'Correspondence' AND EXTRACT(YEAR FROM T1.upload_timestamp) = 2023;

[User] Now, only show the documents for cases handled by lawyer with ID 'lawyer_001'.

[Assistant] SELECT T1.document_name, T1.upload_timestamp, T2.case_name FROM legal_services.documents AS T1 JOIN legal_services.cases AS T2 ON T1.case_id = T2.case_id WHERE T1.document_type = 'Correspondence' AND EXTRACT(YEAR FROM T1.upload_timestamp) = 2023 AND T2.lead_lawyer_id = 'lawyer_001';

[User] Additionally, include the first and last name of the lawyer who actually uploaded the document, and sort the results by upload timestamp descending.

[Assistant] SELECT T1.document_name, T1.upload_timestamp, T2.case_name, T3.first_name, T3.last_name FROM legal_services.documents AS T1 JOIN legal_services.cases AS T2 ON T1.case_id = T2.case_id JOIN legal_services.lawyers AS T3 ON T1.uploaded_by_lawyer_id = T3.lawyer_id WHERE T1.document_type = 'Correspondence' AND EXTRACT(YEAR FROM T1.upload_timestamp) = 2023 AND T2.lead_lawyer_id = 'lawyer_001' ORDER BY T1.upload_timestamp 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.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.cases ( case_id.text, case_number.text, case_name.text, client_id.text, lead_lawyer_id.text, case_type.text, status.text, date_opened.timestamp, date_closed.timestamp, description.text, court_jurisdiction.text )
CREATE TABLE legal_services.documents (
    document_id character varying(64) NOT NULL,  -- unique identifier for the document
    case_id character varying(64) NOT NULL, -- FK to cases table
    document_name character varying(255) NOT NULL, -- name of the document file
    document_type character varying(100), -- e.g., Pleading, Contract, Evidence, Correspondence
    storage_path text NOT NULL, -- path or reference to the document storage location
    uploaded_by_lawyer_id character varying(64), -- FK to lawyers table (who uploaded it)
    upload_timestamp timestamp NOT NULL, -- time the document was uploaded
    version integer DEFAULT 1, -- document version number
    description text, -- brief description or notes about the document
    PRIMARY KEY (document_id)
)
CREATE TABLE legal_services.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    client_id character varying(64) NOT NULL, -- FK to clients table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table
    case_id character varying(64), -- FK to cases table (optional, if related to a specific case)
    start_time timestamp NOT NULL, -- scheduled start date and time
    end_time timestamp NOT NULL, -- scheduled end date and time
    location text, -- location of the meeting (address or virtual link)
    subject character varying(255), -- subject or purpose of the appointment
    notes text, -- additional notes for the appointment
    status character varying(50) NOT NULL, -- e.g., Scheduled, Completed, Canceled, Rescheduled
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (appointment_id)
)


[User] For each game_id, calculate the average points of achievements that have been unlocked at least once.

[Assistant] SELECT a.game_id, AVG(a.points) AS average_unlocked_points FROM gaming_technology.achievements a JOIN gaming_technology.player_achievements pa ON a.achievement_id = pa.achievement_id GROUP BY a.game_id;

[User] Only include games where the average unlocked achievement points is greater than 50.

[Assistant] SELECT a.game_id, AVG(a.points) AS average_unlocked_points FROM gaming_technology.achievements a JOIN gaming_technology.player_achievements pa ON a.achievement_id = pa.achievement_id GROUP BY a.game_id HAVING AVG(a.points) > 50;

[User] Also include the total number of unique players who unlocked achievements in each of these games.

[Assistant] SELECT a.game_id, AVG(a.points) AS average_unlocked_points, COUNT(DISTINCT pa.player_id) AS unique_players_unlocked FROM gaming_technology.achievements a JOIN gaming_technology.player_achievements pa ON a.achievement_id = pa.achievement_id GROUP BY a.game_id HAVING AVG(a.points) > 50;

[User] Order the results by the total number of unique players descending.

[Assistant] SELECT a.game_id, AVG(a.points) AS average_unlocked_points, COUNT(DISTINCT pa.player_id) AS unique_players_unlocked FROM gaming_technology.achievements a JOIN gaming_technology.player_achievements pa ON a.achievement_id = pa.achievement_id GROUP BY a.game_id HAVING AVG(a.points) > 50 ORDER BY unique_players_unlocked 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.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.timestamptz )
CREATE TABLE gaming_technology.player_inventory ( inventory_id.uuid, player_id.uuid, item_id.uuid, quantity.integer, acquired_at.timestamptz, instance_data.jsonb )


[User] Find all wallets created by users in the last 7 days along with any tokens that have a total supply greater than 10 million, showing the wallet address and token details.

[Assistant] SELECT w.address AS wallet_address, t.token_name, t.token_symbol, t.total_supply, t.contract_address FROM web3.wallets w JOIN web3.tokens t ON t.total_supply > 10000000 WHERE w.created_at >= CURRENT_DATE - INTERVAL '7 days';

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.tokens ( token_id character varying(64) NOT NULL, contract_address character varying(128) NOT NULL, token_name character varying(128) NOT NULL, token_symbol character varying(32) NOT NULL, decimals integer NOT NULL, total_supply numeric(38,14) NOT NULL, PRIMARY KEY (token_id) )
CREATE TABLE web3.wallets ( wallet_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, address character varying(128) NOT NULL, private_key text NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (wallet_id) )


[User] Find all smart contracts where the code length is greater than 1000 characters.

[Assistant] SELECT contract_id, creator_address, timestamp FROM blockchain.smart_contracts WHERE LENGTH(code) > 1000;

[User] Now group these by creator_address and show the count of such contracts per creator.

[Assistant] SELECT creator_address, COUNT(*) AS long_code_contracts FROM blockchain.smart_contracts WHERE LENGTH(code) > 1000 GROUP BY creator_address;

[User] Can you order the results by the count in descending order?

[Assistant] SELECT creator_address, COUNT(*) AS long_code_contracts FROM blockchain.smart_contracts WHERE LENGTH(code) > 1000 GROUP BY creator_address ORDER BY long_code_contracts DESC;

[User] Now show only creators who have more than 3 such contracts.

[Assistant] SELECT creator_address, COUNT(*) AS long_code_contracts FROM blockchain.smart_contracts WHERE LENGTH(code) > 1000 GROUP BY creator_address HAVING COUNT(*) > 3 ORDER BY long_code_contracts 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 blockchain.smart_contracts ( contract_id text PRIMARY KEY, creator_address text, code text, timestamp timestamp )


[User] Find the contract address and name for all NFT collections listed on the 'Ethereum' blockchain.

[Assistant] SELECT contract_address, name FROM nft_collections WHERE blockchain = 'Ethereum'

[User] For these collections, can you show the count of unique wallet addresses holding NFTs in each collection by joining with nft_holders?

[Assistant] SELECT T1.contract_address, T1.name, COUNT(DISTINCT T2.wallet_address) AS unique_holder_count FROM nft_collections AS T1 JOIN nft_holders AS T2 ON T1.contract_address = T2.contract_address WHERE T1.blockchain = 'Ethereum' GROUP BY T1.contract_address, T1.name

[User] Please filter the results to only include collections that have more than 100 unique holders.

[Assistant] SELECT T1.contract_address, T1.name, COUNT(DISTINCT T2.wallet_address) AS unique_holder_count FROM nft_collections AS T1 JOIN nft_holders AS T2 ON T1.contract_address = T2.contract_address WHERE T1.blockchain = 'Ethereum' GROUP BY T1.contract_address, T1.name HAVING COUNT(DISTINCT T2.wallet_address) > 100

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 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 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 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 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] Calculate the monthly total quantity of fuel consumed and the average cost_per_unit for each fuel_type in 2023.

[Assistant]
SELECT date_trunc('month', log_timestamp) AS month,
       fuel_type,
       SUM(quantity)      AS total_quantity,
       AVG(cost_per_unit) AS avg_cost_per_unit
FROM transportation.fuel_logs
WHERE log_timestamp >= '2023-01-01'
  AND log_timestamp <  '2024-01-01'
GROUP BY 1, fuel_type
ORDER BY 1, fuel_type;

[User] Now limit the results to fuel types where the total_quantity exceeds 1000 units in that month.

[Assistant]
SELECT month,
       fuel_type,
       total_quantity,
       avg_cost_per_unit
FROM (
  SELECT date_trunc('month', log_timestamp) AS month,
         fuel_type,
         SUM(quantity)      AS total_quantity,
         AVG(cost_per_unit) AS avg_cost_per_unit
  FROM transportation.fuel_logs
  WHERE log_timestamp >= '2023-01-01'
    AND log_timestamp <  '2024-01-01'
  GROUP BY 1, fuel_type
) sub
WHERE total_quantity > 1000
ORDER BY month, fuel_type;

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.fuel_logs ( fuel_log_id.text, vehicle_id.text, trip_id.text, log_timestamp.timestamp, fuel_type.text, quantity.numeric, unit.text, cost_per_unit.numeric, total_cost.numeric, odometer_reading.integer, location_id.text )


[User] Find appointments that are longer than 30 minutes.

[Assistant] SELECT * FROM legal_services.appointments WHERE end_time IS NOT NULL AND start_time IS NOT NULL AND end_time > start_time + INTERVAL '30 minutes'

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.appointments ( appointment_id.text, client_id.text, lawyer_id.text, case_id.text, start_time.timestamp, end_time.timestamp, location.text, subject.text, notes.text, status.text, created_at.timestamp )


[User] List the first and last names of employees and the full name of the citizens for whom they have scheduled appointments.

[Assistant] SELECT T1.first_name ,  T1.last_name ,  T3.first_name ,  T3.last_name FROM government_services.employees AS T1 JOIN government_services.appointments AS T2 ON T1.employee_id  =  T2.employee_id JOIN government_services.citizens AS T3 ON T2.citizen_id  =  T3.citizen_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 government_services.citizens ( citizen_id text PRIMARY KEY, national_id_number text, first_name text, last_name text, date_of_birth date, gender text, primary_address text, contact_email text, contact_phone text, registration_date timestamp, is_verified boolean )
CREATE TABLE government_services.agencies ( agency_id text PRIMARY KEY, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )
CREATE TABLE government_services.services ( service_id text PRIMARY KEY, agency_id text, service_name text, description text, category text, eligibility_criteria text, standard_fee numeric, average_processing_time_days int, is_active boolean, online_application_url text )
CREATE TABLE government_services.applications ( application_id text PRIMARY KEY, citizen_id text, service_id text, submitted_at timestamp, status text, last_updated_at timestamp, assigned_employee_id text, decision_date date, notes text, reference_number text )
CREATE TABLE government_services.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text PRIMARY KEY, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees ( employee_id text PRIMARY KEY, agency_id text, first_name text, last_name text, job_title text, department text, work_email text, work_phone text, hire_date date, termination_date date, access_level text, manager_employee_id text )
CREATE TABLE government_services.appointments ( appointment_id text PRIMARY KEY, citizen_id text, employee_id text, location_id text, service_id text, scheduled_start_time timestamp, scheduled_end_time timestamp, purpose text, status text, booking_method text, created_at timestamp, notes text )
CREATE TABLE government_services.notifications ( notification_id text PRIMARY KEY, citizen_id text, application_id text, message_subject text, message_body text, channel text, sent_at timestamp, status text, related_entity_type text, related_entity_id text )


[User] Show me all trips that were delayed by more than 1 hour, including their vehicle and driver IDs, along with the origin and destination location IDs.

[Assistant] SELECT trip_id, vehicle_id, driver_id, origin_location_id, destination_location_id FROM transportation.trips WHERE EXTRACT(EPOCH FROM (actual_departure - scheduled_departure))/3600 > 1 AND status = 'Completed';

[User] Now include the passenger count for these trips, but only show trips that had more than 5 passengers.

[Assistant] SELECT trip_id, vehicle_id, driver_id, origin_location_id, destination_location_id, passenger_count FROM transportation.trips WHERE EXTRACT(EPOCH FROM (actual_departure - scheduled_departure))/3600 > 1 AND status = 'Completed' AND passenger_count > 5;

[User] Can you order these results by the delay time in descending order, showing the longest delays first?

[Assistant] SELECT trip_id, vehicle_id, driver_id, origin_location_id, destination_location_id, passenger_count, (actual_departure - scheduled_departure) AS delay_time FROM transportation.trips WHERE EXTRACT(EPOCH FROM (actual_departure - scheduled_departure))/3600 > 1 AND status = 'Completed' AND passenger_count > 5 ORDER BY delay_time 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.trips (
    trip_id character varying(64) NOT NULL,  -- unique identifier for a specific trip instance
    route_id character varying(64), -- identifier of the route being followed (can be null for ad-hoc trips)
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle used
    driver_id character varying(64) NOT NULL, -- identifier of the driver operating
    scheduled_departure timestamp with time zone NOT NULL, -- planned departure time
    actual_departure timestamp with time zone, -- actual departure time
    scheduled_arrival timestamp with time zone NOT NULL, -- planned arrival time
    actual_arrival timestamp with time zone, -- actual arrival time
    origin_location_id character varying(64) NOT NULL, -- actual starting location (could differ from route origin)
    destination_location_id character varying(64) NOT NULL, -- actual ending location (could differ from route destination)
    status character varying(32) NOT NULL, -- e.g., Scheduled, In Progress, Completed, Delayed, Cancelled
    passenger_count integer, -- number of passengers (if applicable)
    cargo_manifest_id character varying(64), -- link to cargo details (if applicable)
    PRIMARY KEY (trip_id)
)


[User] Show the email address and the creation date for every user, ordered by their username alphabetically.

[Assistant] SELECT email, created_at FROM trading_platform.users ORDER BY username 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 trading_platform.users ( user_id.text, username.text, email.text, password_hash.text, created_at.timestamp )


[User] Show me all properties in California with a star rating above 4.0, along with their room types and base rates.

[Assistant] SELECT p.property_id, p.property_name, p.star_rating, r.room_type_id, r.features FROM hospitality_technology.properties p JOIN hospitality_technology.rooms r ON p.property_id = r.property_id WHERE p.state_province = 'California' AND p.star_rating > 4.0;

[User] Now, filter the results to only include rooms that are currently available and have a non-smoking policy.

[Assistant] SELECT p.property_id, p.property_name, p.star_rating, r.room_type_id, r.features FROM hospitality_technology.properties p JOIN hospitality_technology.rooms r ON p.property_id = r.property_id WHERE p.state_province = 'California' AND p.star_rating > 4.0 AND r.status = 'available' AND r.is_smoking = false;

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.properties ( property_id text, property_name text, address_line1 text, address_line2 text, city text, state_province text, postal_code text, country_code text, phone_number text, email_address text, property_type text, star_rating numeric, timezone text, manager_staff_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.rooms ( room_id text, 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.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] 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 usernames and user IDs of all users whose bio contains the word 'developer'.

[Assistant]
SELECT user_id, username
FROM social_media.users
WHERE bio ILIKE '%developer%';

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.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] What is the current location of train number Acela 2151?

[Assistant] I'm sorry, but I don't have access to real-time location data for trains. The database only contains static information such as train ID, model, capacity, and maintenance schedules. For current location updates, please check with the train operator or a tracking service.

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.trains (
    train_id character varying(64) NOT NULL, -- Unique identifier for the train set
    train_number character varying(32) NOT NULL, -- Operational number of the train (e.g., 'Acela 2151')
    model character varying(128), -- Model of the train (e.g., 'Siemens Velaro')
    manufacturer character varying(128), -- Manufacturer of the train
    year_manufactured integer, -- Year the train was built
    capacity integer NOT NULL, -- Total passenger capacity
    status character varying(32) NOT NULL DEFAULT 'Active', -- e.g., Active, Maintenance, Retired
    last_maintenance_date date, -- Date of last scheduled maintenance
    next_maintenance_date date, -- Date of next scheduled maintenance
    PRIMARY KEY (train_id),
    UNIQUE (train_number)
)


[User] I need the total traded value (quantity * price) for each buyer and asset symbol for trades after '2024-06-01'. List buyer_id, asset symbol, and total_value.

[Assistant]
SELECT t.buyer_id, m.value AS asset_symbol, SUM(t.quantity * t.price) AS total_value
FROM trading_platform.trades t
JOIN trading_platform.metadata m ON t.asset_id = m.asset_id AND m.key = 'symbol'
WHERE t.traded_at > '2024-06-01'
GROUP BY t.buyer_id, m.value;

[User] Only include results where total_value > 10000, and order by total_value descending.

[Assistant]
SELECT t.buyer_id, m.value AS asset_symbol, SUM(t.quantity * t.price) AS total_value
FROM trading_platform.trades t
JOIN trading_platform.metadata m ON t.asset_id = m.asset_id AND m.key = 'symbol'
WHERE t.traded_at > '2024-06-01'
GROUP BY t.buyer_id, m.value
HAVING SUM(t.quantity * t.price) > 10000
ORDER BY total_value 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 trading_platform.orders ( order_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, wallet_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, order_type character varying(32) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, status character varying(32) NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (order_id) )
CREATE TABLE trading_platform.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )
CREATE TABLE trading_platform.peers ( peer_id character varying(64) NOT NULL, ip_address character varying(15) NOT NULL, port integer NOT NULL, last_seen timestamp NOT NULL, PRIMARY KEY (peer_id) )
CREATE TABLE trading_platform.metadata ( metadata_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, key character varying(128) NOT NULL, value text NOT NULL, PRIMARY KEY (metadata_id) )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, status character varying(32) NOT NULL, reviewed_at timestamp NOT NULL, PRIMARY KEY (kyc_audit_id) )
CREATE TABLE trading_platform.logs ( log_id character varying(64) NOT NULL, user_id character varying(64), action character varying(128) NOT NULL, details text NOT NULL, logged_at timestamp NOT NULL, PRIMARY KEY (log_id) )
CREATE TABLE trading_platform.notifications ( notification_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, message text NOT NULL, sent_at timestamp NOT NULL, read_at timestamp, PRIMARY KEY (notification_id) )


[User] List the document ID, document type, and the full name of the citizen who submitted the document, but only for documents submitted for applications with a status of 'Approved'.

[Assistant] SELECT T1.document_id, T1.document_type, T3.first_name, T3.last_name FROM government_services.documents AS T1 JOIN government_services.applications AS T2 ON T1.application_id = T2.application_id JOIN government_services.citizens AS T3 ON T1.citizen_id = T3.citizen_id WHERE T2.status = 'Approved';

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.documents ( document_id.text, application_id.text, citizen_id.text, document_type.text, file_reference.text, upload_timestamp.timestamp, expiry_date.date, verification_status.text, verified_by_employee_id.text, verification_timestamp.timestamp )


[User] Retrieve the vehicle_id, make, model, and the next_service_due_date for each vehicle based on the most recent maintenance log.

[Assistant] SELECT DISTINCT ON (ml.vehicle_id) v.vehicle_id, v.make, v.model, ml.next_service_due_date FROM transportation.maintenance_logs ml JOIN transportation.vehicles v ON v.vehicle_id = ml.vehicle_id ORDER BY ml.vehicle_id, ml.service_date DESC;

[User] Now, only include vehicles with status 'Active' and whose next_service_due_date is within the next 30 days, ordering by next_service_due_date ascending.

[Assistant] SELECT v.vehicle_id, v.make, v.model, ml.next_service_due_date FROM transportation.vehicles v JOIN (SELECT DISTINCT ON (vehicle_id) vehicle_id, next_service_due_date FROM transportation.maintenance_logs ORDER BY vehicle_id, service_date DESC) ml ON v.vehicle_id = ml.vehicle_id WHERE v.status = 'Active' AND ml.next_service_due_date BETWEEN current_date AND current_date + INTERVAL '30 days' ORDER BY ml.next_service_due_date 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 transportation.vehicles ( vehicle_id text PRIMARY KEY, license_plate text, vin text, make text, model text, year int, type text, capacity int, fuel_type text, status text, depot_id text, acquisition_date date )
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )
CREATE TABLE transportation.routes ( route_id text PRIMARY KEY, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes int, type text )
CREATE TABLE transportation.trips ( trip_id text PRIMARY KEY, 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 int, cargo_manifest_id text )
CREATE TABLE transportation.locations ( location_id text PRIMARY KEY, 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 PRIMARY KEY, vehicle_id text, service_date date, odometer_reading int, service_type text, description text, cost numeric, mechanic_name text, next_service_due_date date )
CREATE TABLE transportation.fuel_logs ( fuel_log_id text PRIMARY KEY, vehicle_id text, trip_id text, log_timestamp timestamp, fuel_type text, quantity numeric, unit text, cost_per_unit numeric, total_cost numeric, odometer_reading int, location_id text )
CREATE TABLE transportation.bookings ( booking_id text PRIMARY KEY, passenger_id text, trip_id text, seat_number text, booking_time timestamp, status text, fare numeric, payment_transaction_id text, special_requests text )


[User] For each user, show their username and how many unique conversations they have sent at least one message in where the conversation is a group chat.

[Assistant]
SELECT u.username, COUNT(DISTINCT m.conversation_id) AS group_chats_messaged_in
FROM social_media.users u
JOIN social_media.messages m ON u.user_id = m.sender_user_id
JOIN social_media.conversations c ON m.conversation_id = c.conversation_id
WHERE c.is_group_chat = TRUE
GROUP BY u.username;

[User] Instead, show only users who have sent messages in more than one group chat, and include their email addresses.

[Assistant]
SELECT u.username, u.email, COUNT(DISTINCT m.conversation_id) AS group_chats_messaged_in
FROM social_media.users u
JOIN social_media.messages m ON u.user_id = m.sender_user_id
JOIN social_media.conversations c ON m.conversation_id = c.conversation_id
WHERE c.is_group_chat = TRUE
GROUP BY u.username, u.email
HAVING COUNT(DISTINCT m.conversation_id) > 1;

[User] Also add the most recent message time sent by each user in these group chats.

[Assistant]
SELECT u.username, u.email, COUNT(DISTINCT m.conversation_id) AS group_chats_messaged_in, MAX(m.sent_at) AS last_message_time
FROM social_media.users u
JOIN social_media.messages m ON u.user_id = m.sender_user_id
JOIN social_media.conversations c ON m.conversation_id = c.conversation_id
WHERE c.is_group_chat = TRUE
GROUP BY u.username, u.email
HAVING COUNT(DISTINCT m.conversation_id) > 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 social_media.users ( user_id text, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified boolean )
CREATE TABLE social_media.posts ( post_id.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.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 text, user_id text, post_id text, comment_id text, created_at timestamp )
CREATE TABLE social_media.follows ( follow_id character varying(64) NOT NULL, follower_user_id character varying(64) NOT NULL, following_user_id character varying(64) NOT NULL, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (follow_id), CONSTRAINT unique_follow UNIQUE (follower_user_id, following_user_id) )
CREATE TABLE social_media.hashtags ( hashtag_id character varying(64) NOT NULL, tag_name character varying(100) NOT NULL UNIQUE, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (hashtag_id) )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id 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.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 text PRIMARY KEY, created_at timestamp, last_message_at timestamp, is_group_chat bool, group_name text )
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.text, recipient_user_id.text, sender_user_id.text, notification_type.text, target_entity_id.text, target_entity_type.text, created_at.timestamp, read_at.timestamp )


[User] Calculate the total quantity traded for each day in the dataset.

[Assistant] SELECT DATE_TRUNC('day', traded_at) AS trade_day, SUM(quantity) AS total_daily_quantity FROM trading_platform.trades GROUP BY DATE_TRUNC('day', traded_at) ORDER BY trade_day;

[User] Could you also include the total trade value (quantity * price) for each day in that report?

[Assistant] SELECT DATE_TRUNC('day', traded_at) AS trade_day, SUM(quantity) AS total_daily_quantity, SUM(quantity * price) AS total_daily_value FROM trading_platform.trades GROUP BY DATE_TRUNC('day', traded_at) ORDER BY trade_day;

[User] Now, for each day, show how the total quantity compares to the overall average daily quantity across all days in the dataset.

[Assistant] WITH DailySummary AS (SELECT DATE_TRUNC('day', traded_at) AS trade_day, SUM(quantity) AS total_daily_quantity FROM trading_platform.trades GROUP BY DATE_TRUNC('day', traded_at)) SELECT trade_day, total_daily_quantity, total_daily_quantity - AVG(total_daily_quantity) OVER () AS quantity_difference_from_average FROM DailySummary ORDER BY trade_day;

[User] Finally, only show the days where the total quantity was higher than the overall average daily quantity.

[Assistant] WITH DailySummary AS (SELECT DATE_TRUNC('day', traded_at) AS trade_day, SUM(quantity) AS total_daily_quantity FROM trading_platform.trades GROUP BY DATE_TRUNC('day', traded_at)) SELECT trade_day, total_daily_quantity FROM DailySummary WHERE total_daily_quantity > (SELECT AVG(total_daily_quantity) FROM DailySummary) ORDER BY trade_day;

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.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )


[User] List all vehicles and their last maintenance service date along with the odometer reading, including only those that have not had a fuel refill in the past 30 days.

[Assistant]
SELECT m.vehicle_id,
       m.last_service_date,
       m.last_odometer
FROM (
  SELECT l.vehicle_id,
         MAX(l.service_date) AS last_service_date,
         (SELECT odometer_reading
          FROM transportation.maintenance_logs
          WHERE vehicle_id = l.vehicle_id
          ORDER BY service_date DESC
          LIMIT 1) AS last_odometer
  FROM transportation.maintenance_logs l
  GROUP BY l.vehicle_id
) AS m
LEFT JOIN (
  SELECT fl.vehicle_id,
         MAX(fl.log_timestamp) AS last_fuel_date
  FROM transportation.fuel_logs fl
  GROUP BY fl.vehicle_id
) AS f ON m.vehicle_id = f.vehicle_id
WHERE COALESCE(f.last_fuel_date, '1900-01-01'::timestamp) < NOW() - INTERVAL '30 days';

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.routes ( route_id character varying(64) NOT NULL, route_number character varying(32) NOT NULL UNIQUE, description text, origin_location_id character varying(64) NOT NULL, destination_location_id character varying(64) NOT NULL, distance_km numeric(10, 2), estimated_duration_minutes integer, type character varying(32) NOT NULL, PRIMARY KEY (route_id) )
CREATE TABLE transportation.trips ( trip_id character varying(64) NOT NULL, route_id character varying(64), vehicle_id character varying(64) NOT NULL, driver_id character varying(64) NOT NULL, scheduled_departure timestamp with time zone NOT NULL, actual_departure timestamp with time zone, scheduled_arrival timestamp with time zone NOT NULL, actual_arrival timestamp with time zone, origin_location_id character varying(64) NOT NULL, destination_location_id character varying(64) NOT NULL, status character varying(32) NOT NULL, passenger_count integer, cargo_manifest_id character varying(64), PRIMARY KEY (trip_id) )
CREATE TABLE transportation.locations ( location_id character varying(64) NOT NULL, name character varying(255) NOT NULL, type character varying(64) NOT NULL, address_line1 character varying(255), city character varying(128), state_province character varying(128), postal_code character varying(32), country character varying(64) NOT NULL, latitude numeric(9, 6), longitude numeric(9, 6), timezone character varying(64), PRIMARY KEY (location_id) )
CREATE TABLE transportation.maintenance_logs ( log_id character varying(64) NOT NULL, vehicle_id character varying(64) NOT NULL, service_date date NOT NULL, odometer_reading integer, service_type character varying(128) NOT NULL, description text NOT NULL, cost numeric(10, 2), mechanic_name character varying(128), next_service_due_date date, PRIMARY KEY (log_id) )
CREATE TABLE transportation.fuel_logs ( fuel_log_id character varying(64) NOT NULL, vehicle_id character varying(64) NOT NULL, trip_id character varying(64), log_timestamp timestamp with time zone NOT NULL, fuel_type character varying(32) NOT NULL, quantity numeric(10, 3) NOT NULL, unit character varying(16) NOT NULL, cost_per_unit numeric(8, 4), total_cost numeric(10, 2) NOT NULL, odometer_reading integer, location_id character varying(64), PRIMARY KEY (fuel_log_id) )
CREATE TABLE transportation.passengers ( passenger_id character varying(64) NOT NULL, first_name character varying(128) NOT NULL, last_name character varying(128) NOT NULL, email character varying(128) UNIQUE, phone_number character varying(32) UNIQUE, date_of_birth date, loyalty_program_id character varying(64), created_at timestamp with time zone NOT NULL, PRIMARY KEY (passenger_id) )
CREATE TABLE transportation.bookings ( booking_id character varying(64) NOT NULL, passenger_id character varying(64) NOT NULL, trip_id character varying(64) NOT NULL, seat_number character varying(16), booking_time timestamp with time zone NOT NULL, status character varying(32) NOT NULL, fare numeric(10, 2) NOT NULL, payment_transaction_id character varying(128), special_requests text, PRIMARY KEY (booking_id) )


[User] What is the current market price of a Boeing 737 MAX aircraft?

[Assistant] I'm sorry, but I don't have access to the current market price of aircraft models. The data I have is limited to technical specifications and general information about aircraft models such as passenger capacity, range, and status. For pricing information, you may need to consult with manufacturers or industry reports.

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 manufacturing.aircraft_models (
    model_id character varying(64) NOT NULL,  -- unique identifier for the aircraft model
    model_name character varying(128) NOT NULL, -- commercial name of the model (e.g., 737 MAX, A320neo)
    manufacturer character varying(128) NOT NULL, -- manufacturer name (e.g., Boeing, Airbus)
    passenger_capacity integer, -- typical passenger capacity
    max_range_km integer, -- maximum flight range in kilometers
    engine_type character varying(100), -- type of engines used
    wingspan_m numeric(6,2), -- wingspan in meters
    status character varying(50) NOT NULL, -- e.g., 'In Production', 'Development', 'Discontinued'
    first_flight_date date, -- date of the model's first flight
    PRIMARY KEY (model_id)
)


[User] List all medical records, showing the record ID, record date, and the full name of the doctor who created the record. Include the patient ID as well.

[Assistant] SELECT mr.record_id, mr.record_date, mr.patient_id, d.first_name, d.last_name FROM healthcare.medical_records mr JOIN doctors d ON mr.doctor_id = d.doctor_id;

[User] Refine this to only include records where the chief_complaint is not null or empty and the doctor's specialty is 'Cardiology'.

[Assistant] SELECT mr.record_id, mr.record_date, mr.patient_id, d.first_name, d.last_name FROM healthcare.medical_records mr JOIN doctors d ON mr.doctor_id = d.doctor_id WHERE (mr.chief_complaint IS NOT NULL AND mr.chief_complaint != '') AND d.specialty = 'Cardiology';

[User] Also, sort the results by record_date in descending order and limit the output to the top 10 records.

[Assistant] SELECT mr.record_id, mr.record_date, mr.patient_id, d.first_name, d.last_name FROM healthcare.medical_records mr JOIN doctors d ON mr.doctor_id = d.doctor_id WHERE (mr.chief_complaint IS NOT NULL AND mr.chief_complaint != '') AND d.specialty = 'Cardiology' ORDER BY mr.record_date 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 healthcare.medical_records (
    record_id character varying(64) NOT NULL,  -- unique identifier for the medical record entry
    patient_id character varying(64) NOT NULL, -- FK to patients table
    appointment_id character varying(64) UNIQUE, -- FK to appointments table (can be null if record not tied to specific appt)
    doctor_id character varying(64) NOT NULL, -- FK to doctors table (doctor creating the record)
    record_date timestamp with time zone NOT NULL, -- date the record/observation was made
    chief_complaint text, -- patient's primary reason for visit
    present_illness_history text, -- detailed history of the current issue
    past_medical_history text, -- relevant past conditions/surgeries
    physical_examination_notes text, -- findings from the physical exam
    assessment text, -- doctor's assessment/diagnosis summary
    treatment_plan text, -- planned course of action
    vitals jsonb, -- store vitals like BP, HR, Temp as structured JSON
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (record_id)
)


[User] Provide a list of all vehicles and the total quantity of fuel refueled for each vehicle.

[Assistant] SELECT T1.license_plate, sum(T2.quantity) FROM transportation.vehicles AS T1 JOIN transportation.fuel_logs AS T2 ON T1.vehicle_id = T2.vehicle_id GROUP BY T1.license_plate

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 PRIMARY KEY, license_plate text, vin text, make text, model text, year int, type text, capacity int, fuel_type text, status text, depot_id text, acquisition_date date )
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )
CREATE TABLE transportation.routes ( route_id text PRIMARY KEY, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes int, type text )
CREATE TABLE transportation.trips ( trip_id text PRIMARY KEY, 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 int, cargo_manifest_id text )
CREATE TABLE transportation.fuel_logs ( fuel_log_id text PRIMARY KEY, vehicle_id text, trip_id text, log_timestamp timestamp, fuel_type text, quantity numeric, unit text, cost_per_unit numeric, total_cost numeric, odometer_reading int, location_id text )
CREATE TABLE transportation.passengers ( passenger_id text PRIMARY KEY, first_name text, last_name text, email text, phone_number text, date_of_birth date, loyalty_program_id text, created_at timestamp )


[User] For each security issuer, show the count of market data points and the average close price for their securities.

[Assistant] SELECT T2.issuer_name, COUNT(T1.*) AS data_point_count, AVG(T1.close_price) AS avg_close_price FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id GROUP BY T2.issuer_name;

[User] Only include issuers who have more than 1000 market data points in total.

[Assistant] SELECT T2.issuer_name, COUNT(T1.*) AS data_point_count, AVG(T1.close_price) AS avg_close_price FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id GROUP BY T2.issuer_name HAVING COUNT(T1.*) > 1000;

[User] Also, include the average volume for each issuer and sort the results by average close price descending.

[Assistant] SELECT T2.issuer_name, COUNT(T1.*) AS data_point_count, AVG(T1.close_price) AS avg_close_price, AVG(T1.volume) AS avg_volume FROM financial_services.market_data AS T1 JOIN financial_services.securities AS T2 ON T1.security_id = T2.security_id GROUP BY T2.issuer_name HAVING COUNT(T1.*) > 1000 ORDER BY avg_close_price 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 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] List patient_id, full name, policy_number, plan_type, and insurance_provider for all active primary insurance policies.

[Assistant]
SELECT pi.patient_id,
       p.first_name,
       p.last_name,
       pi.policy_number,
       ip.plan_type,
       ip.insurance_provider
FROM healthcare.patient_insurance pi
JOIN healthcare.patients p
  ON p.patient_id = pi.patient_id
JOIN healthcare.insurance_plans ip
  ON ip.plan_id = pi.plan_id
WHERE pi.is_primary = TRUE
  AND pi.effective_date <= CURRENT_DATE
  AND pi.expiration_date >= CURRENT_DATE;

[User] Now also restrict to policies expiring within the next 30 days.

[Assistant]
SELECT pi.patient_id,
       p.first_name,
       p.last_name,
       pi.policy_number,
       ip.plan_type,
       ip.insurance_provider
FROM healthcare.patient_insurance pi
JOIN healthcare.patients p
  ON p.patient_id = pi.patient_id
JOIN healthcare.insurance_plans ip
  ON ip.plan_id = pi.plan_id
WHERE pi.is_primary = TRUE
  AND pi.effective_date <= CURRENT_DATE
  AND pi.expiration_date BETWEEN CURRENT_DATE AND CURRENT_DATE + INTERVAL '30 days';

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 text, first_name text, last_name text, date_of_birth date, gender text, address text, phone_number text, email text, emergency_contact_name text, emergency_contact_phone text, created_at timestamp, updated_at timestamp )
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.medical_records ( record_id text, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )
CREATE TABLE healthcare.diagnoses ( diagnosis_id text, record_id text, patient_id text, doctor_id text, diagnosis_code text, code_type text, description text, diagnosis_date date, status text, is_chronic boolean )
CREATE TABLE healthcare.medications ( medication_id text, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )
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 all events and any token transfers that occurred in the same transaction, showing event_id, event_name, transfer_id, and token_symbol.

[Assistant]
SELECT
  e.event_id,
  e.event_name,
  tt.transfer_id,
  tk.token_symbol
FROM web3.events e
LEFT JOIN web3.token_transfers tt
  ON e.transaction_id = tt.transaction_id
LEFT JOIN web3.tokens tk
  ON tt.token_id = tk.token_id
ORDER BY e.transaction_id, e.log_index;

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.contracts ( contract_id character varying(64) NOT NULL, address character varying(128) NOT NULL, abi text NOT NULL, bytecode text NOT NULL, deployer_address character varying(128) NOT NULL, deployed_at timestamp NOT NULL, network_id character varying(64) NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (contract_id) )
CREATE TABLE web3.events ( event_id.text, contract_id.text, event_name.text, data.text, emitted_at.timestamp, transaction_id.text, log_index.integer )
CREATE TABLE web3.tokens (
    token_id character varying(64) NOT NULL,  -- unique identifier for the token
    contract_address character varying(128) NOT NULL, -- address of the token contract
    token_name character varying(128) NOT NULL, -- name of the token
    token_symbol character varying(32) NOT NULL, -- symbol of the token
    decimals integer NOT NULL, -- number of decimals for the token
    total_supply numeric(38,14) NOT NULL, -- total supply of the token
    PRIMARY KEY (token_id)
)
CREATE TABLE web3.token_transfers ( transfer_id text PRIMARY KEY, token_id text, from_address text, to_address text, value numeric, transaction_id text, log_index int )
CREATE TABLE web3.users ( user_id text, username text, email text, password_hash text, created_at timestamp )


[User] List smart money addresses, their chain, and profit for those who have incurred a loss. Order the results by the magnitude of the loss (smallest profit value first).

[Assistant] SELECT address, chain, profit FROM smart_money_profit WHERE profit < 0 ORDER BY profit ASC;

[User] From that list, show only the addresses that have a rank worse than 500 (rank number greater than 500).

[Assistant] SELECT address, chain, profit FROM smart_money_profit WHERE profit < 0 AND rank > 500 ORDER BY profit ASC;

[User] Further refine the list to include only addresses on the 'Arbitrum' chain.

[Assistant] SELECT address, chain, profit FROM smart_money_profit WHERE profit < 0 AND rank > 500 AND chain = 'Arbitrum' ORDER BY profit ASC;

[User] Based on the filtered list (loss, rank worse than 500, Arbitrum chain), what is the average profit?

[Assistant] SELECT AVG(profit) FROM smart_money_profit WHERE profit < 0 AND rank > 500 AND chain = 'Arbitrum';

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 smart_money_profit ( address character varying(100) NOT NULL, rank INT, profit numeric(38,6), roi numeric(38,2), realized_ratio numeric(38,2), most_profit_token character varying(100), last_trade_time character varying(100), chain character varying(100) )


[User] Get the number of direct reports for each manager, showing manager_id and report_count.

[Assistant]
SELECT manager_id,
       COUNT(*) AS report_count
FROM hospitality_technology.staff
WHERE manager_id IS NOT NULL
GROUP BY manager_id;

[User] Exclude managers who have fewer than 2 direct reports.

[Assistant]
SELECT manager_id,
       COUNT(*) AS report_count
FROM hospitality_technology.staff
WHERE manager_id IS NOT NULL
GROUP BY manager_id
HAVING COUNT(*) >= 2;

[User] Also include the manager's full name alongside their ID.

[Assistant]
SELECT m.staff_id AS manager_id,
       m.first_name || ' ' || m.last_name AS manager_full_name,
       COUNT(s.staff_id) AS report_count
FROM hospitality_technology.staff s
JOIN hospitality_technology.staff m
  ON s.manager_id = m.staff_id
GROUP BY m.staff_id, m.first_name, m.last_name
HAVING COUNT(s.staff_id) >= 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 hospitality_technology.staff ( staff_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, position character varying(100) NOT NULL, work_email character varying(255) UNIQUE, work_phone character varying(30), hire_date date NOT NULL, termination_date date, is_active boolean NOT NULL DEFAULT true, access_level integer NOT NULL, manager_id character varying(64), created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (staff_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id), FOREIGN KEY (manager_id) REFERENCES hospitality_technology.staff(staff_id) )


[User] Show each wallet address that has received token transfers of more than one type of token, along with the count of token types received.

[Assistant]
SELECT tt.to_address, COUNT(DISTINCT tt.token_id) AS token_type_count
FROM web3.token_transfers tt
GROUP BY tt.to_address
HAVING COUNT(DISTINCT tt.token_id) > 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 web3.contracts ( contract_id text PRIMARY KEY, address text, abi text, bytecode text, deployer_address text, deployed_at timestamp, network_id text, status text )
CREATE TABLE web3.events ( event_id character varying(64) NOT NULL, contract_id character varying(64) NOT NULL, event_name character varying(128) NOT NULL, data text NOT NULL, emitted_at timestamp NOT NULL, transaction_id character varying(64) NOT NULL, log_index integer NOT NULL, PRIMARY KEY (event_id) )
CREATE TABLE web3.tokens (
    token_id character varying(64) NOT NULL,  -- unique identifier for the token
    contract_address character varying(128) NOT NULL, -- address of the token contract
    token_name character varying(128) NOT NULL, -- name of the token
    token_symbol character varying(32) NOT NULL, -- symbol of the token
    decimals integer NOT NULL, -- number of decimals for the token
    total_supply numeric(38,14) NOT NULL, -- total supply of the token
    PRIMARY KEY (token_id)
)
CREATE TABLE web3.token_transfers ( transfer_id character varying(64) NOT NULL, token_id character varying(64) NOT NULL, from_address character varying(128) NOT NULL, to_address character varying(128) NOT NULL, value numeric(38,14) NOT NULL, transaction_id character varying(64) NOT NULL, log_index integer NOT NULL, PRIMARY KEY (transfer_id) )
CREATE TABLE web3.wallets (
    wallet_id character varying(64) NOT NULL,  -- unique identifier for the wallet
    user_id character varying(64) NOT NULL, -- identifier of the user owning the wallet
    address character varying(128) NOT NULL, -- address of the wallet
    private_key text NOT NULL, -- private key of the wallet
    created_at timestamp NOT NULL, -- time when the wallet was created
    PRIMARY KEY (wallet_id)
)
CREATE TABLE web3.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(128) NOT NULL, -- username of the user
    email character varying(128) NOT NULL, -- email address of the user
    password_hash text NOT NULL, -- hashed password of the user
    created_at timestamp NOT NULL, -- time when the user account was created
    PRIMARY KEY (user_id)
)


[User] Can you help me get the total number of operational platforms across all stations?

[Assistant] db.platforms.countDocuments({ status: 'Operational' });

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
// db.createCollection('platforms')
// Optional: db.platforms.createIndex({ platform_id: 1 }, { unique: true })
// Optional: db.platforms.createIndex({ station_id: 1 })
{
  _id: ObjectId(),
  platform_id: "plat_123", // String (unique)
  station_id: "station_xyz", // String (references stations.station_id)
  platform_number: "1A", // String
  track_number: "T1", // String
  status: "Operational", // String ('Operational', 'Maintenance', 'Closed')
  length_meters: 250.50, // Decimal128 or Double
  accessible: true // Boolean
}
// db.createCollection('routes')
// Optional: db.routes.createIndex({ route_id: 1 }, { unique: true })
{
  _id: ObjectId(),
  route_id: "route_ne_corr", // String (unique)
  route_name: "Northeast Corridor", // String
  description: "High-speed rail linking Boston and Washington D.C.", // String
  origin_station_id: "station_bos", // String (references stations.station_id)
  destination_station_id: "station_was", // String (references stations.station_id)
  is_active: true // Boolean
}
// db.createCollection('route_stations')
// Optional: db.route_stations.createIndex({ route_station_id: 1 }, { unique: true })
// Optional: db.route_stations.createIndex({ route_id: 1, sequence_order: 1 }, { unique: true })
{
  _id: ObjectId(),
  route_station_id: "rs_ne_1", // String (unique)
  route_id: "route_ne_corr", // String (references routes.route_id)
  station_id: "station_bos", // String (references stations.station_id)
  sequence_order: 1, // Int32
  distance_from_previous_km: null, // Decimal128 or Double (null for first stop)
  typical_stop_duration_minutes: null // Int32 (null for origin/destination or if no stop)
}
// --- OR --- Embed within the Route document:
// {
//   _id: ObjectId(), route_id: "route_ne_corr", ...,
//   stations: [
//     { station_id: "station_bos", sequence_order: 1, distance_from_previous_km: null, typical_stop_duration_minutes: null },
//     { station_id: "station_pvd", sequence_order: 2, distance_from_previous_km: 70.5, typical_stop_duration_minutes: 5 },
//     ...
//   ]
// }
// db.createCollection('schedules')
// Optional: db.schedules.createIndex({ schedule_id: 1 }, { unique: true })
// Optional: db.schedules.createIndex({ route_id: 1, departure_datetime: 1 })
{
  _id: ObjectId(),
  schedule_id: "sched_1122", // String (unique)
  train_id: "train_789", // String (references trains.train_id)
  route_id: "route_ne_corr", // String (references routes.route_id)
  departure_datetime: ISODate("2024-05-10T08:00:00-04:00"), // Date (with timezone)
  arrival_datetime: ISODate("2024-05-10T15:30:00-04:00"), // Date (with timezone)
  status: "Scheduled", // String ('Scheduled', 'On Time', 'Delayed', 'Cancelled', 'Arrived')
  notes: "Track work expected near Philadelphia" // String
}
// db.createCollection('schedule_stops')
// Optional: db.schedule_stops.createIndex({ stop_id: 1 }, { unique: true })
// Optional: db.schedule_stops.createIndex({ schedule_id: 1, sequence_order: 1 }, { unique: true })
{
  _id: ObjectId(),
  stop_id: "stop_sched1122_1", // String (unique)
  schedule_id: "sched_1122", // String (references schedules.schedule_id)
  station_id: "station_bos", // String (references stations.station_id)
  platform_id: "plat_bos_3", // String (references platforms.platform_id, nullable)
  sequence_order: 1, // Int32
  scheduled_arrival_time: null, // Date
  scheduled_departure_time: ISODate("2024-05-10T08:00:00-04:00"), // Date
  actual_arrival_time: null, // Date
  actual_departure_time: ISODate("2024-05-10T08:01:00-04:00"), // Date
  status: "On Time" // String
}
// --- OR --- Embed within the Schedule document using an array 'stops'
// db.createCollection('passengers')
// Optional: db.passengers.createIndex({ passenger_id: 1 }, { unique: true })
// Optional: db.passengers.createIndex({ email: 1 }, { unique: true, sparse: true })
// Optional: db.passengers.createIndex({ phone_number: 1 }, { unique: true, sparse: true })
{
  _id: ObjectId(),
  passenger_id: "pass_pqr", // String (unique)
  first_name: "Alice", // String
  last_name: "Smith", // String
  email: "alice.smith@example.com", // String (unique, sparse)
  phone_number: "+15551234567", // String (unique, sparse)
  date_of_birth: ISODate("1990-03-20"), // Date
  loyalty_program_id: "LOYALTY123", // String
  created_at: ISODate("2023-02-01T11:00:00Z") // Date
}
// db.createCollection('staff')
// Optional: db.staff.createIndex({ staff_id: 1 }, { unique: true })
// Optional: db.staff.createIndex({ employee_number: 1 }, { unique: true })
// Optional: db.staff.createIndex({ contact_email: 1 }, { unique: true, sparse: true })
{
  _id: ObjectId(),
  staff_id: "staff_mno", // String (unique)
  first_name: "Bob", // String
  last_name: "Jones", // String
  role: "Conductor", // String
  primary_station_id: null, // String (references stations.station_id, nullable)
  employee_number: "E12345", // String (unique)
  hire_date: ISODate("2018-06-01"), // Date
  contact_email: "bob.jones@example-rail.com", // String (unique, sparse)
  contact_phone: "+15559876543", // String
  is_active: true // Boolean
}


[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] List all beneficiaries who do not have any contact information provided. Show beneficiary_id, first_name, and last_name.

[Assistant] SELECT beneficiary_id, first_name, last_name FROM insurance.policy_beneficiaries WHERE contact_info IS NULL OR contact_info = ''

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.policy_beneficiaries ( beneficiary_id text, policy_id text, customer_id text, first_name text, last_name text, relationship text, percentage_share numeric, contact_info text, added_at timestamp )


[User] Can you show me the total number of passengers registered in the database?

[Assistant] db.passengers.countDocuments({})

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
// db.createCollection('passengers')
// Optional: db.passengers.createIndex({ passenger_id: 1 }, { unique: true })
// Optional: db.passengers.createIndex({ email: 1 }, { unique: true, sparse: true })
// Optional: db.passengers.createIndex({ phone_number: 1 }, { unique: true, sparse: true })
{
  _id: ObjectId(),
  passenger_id: "pass_pqr", // String (unique)
  first_name: "Alice", // String
  last_name: "Smith", // String
  email: "alice.smith@example.com", // String (unique, sparse)
  phone_number: "+15551234567", // String (unique, sparse)
  date_of_birth: ISODate("1990-03-20"), // Date
  loyalty_program_id: "LOYALTY123", // String
  created_at: ISODate("2023-02-01T11:00:00Z") // Date
}


[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] For each vehicle, list its vehicle_id, license_plate, and any older vehicle of the same type (showing older_vehicle_id and older year).

[Assistant]
SELECT cur.vehicle_id,
       cur.license_plate,
       old.vehicle_id AS older_vehicle_id,
       old.year       AS older_vehicle_year
FROM transportation.vehicles cur
JOIN transportation.vehicles old
  ON cur.type = old.type
 AND old.year < cur.year
ORDER BY cur.vehicle_id, old.year 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 character varying(64) NOT NULL,  -- unique identifier for the vehicle
    license_plate character varying(32) NOT NULL UNIQUE, -- vehicle license plate
    vin character varying(17) UNIQUE, -- vehicle identification number
    make character varying(64) NOT NULL, -- manufacturer of the vehicle
    model character varying(64) NOT NULL, -- model of the vehicle
    year integer NOT NULL, -- manufacturing year
    type character varying(32) NOT NULL, -- type of vehicle (e.g., Bus, Train, Truck, Car, Van)
    capacity integer, -- passenger or cargo capacity
    fuel_type character varying(32) NOT NULL, -- e.g., Diesel, Gasoline, Electric, Hydrogen
    status character varying(32) NOT NULL, -- e.g., Active, Maintenance, Decommissioned
    depot_id character varying(64), -- identifier of the home depot/base
    acquisition_date date, -- date the vehicle was acquired
    PRIMARY KEY (vehicle_id)
)


[User] List all tokens with a price below $1 and a 24-hour trading volume over $5 million.

[Assistant] SELECT token_name, token_symbol, price, total_volume FROM token_basic_info WHERE price < 1 AND total_volume::numeric > 5000000;

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, token_name character varying(100) NOT NULL, token_symbol character varying(100) NOT NULL, token_address character varying(100) NOT NULL, chain text, price double precision, price_change_percentage_1h double precision, price_change_percentage_24h double precision, price_change_percentage_7d double precision, highest_price_24h double precision, lowest_price_24h double precision, market_cap double precision, market_cap_rank bigint, market_cap_change_percentage_24h text, total_volume text, narrative text, trend_rank bigint )


[User] Find the top 5 employees who have verified the most documents. Display the employee full name and the count of verified documents, ordered by count descending.

[Assistant]
SELECT e.first_name || ' ' || e.last_name AS full_name,
       COUNT(*) AS verified_count
FROM government_services.documents d
JOIN government_services.employees e
  ON d.verified_by_employee_id = e.employee_id
WHERE d.verification_status = 'Verified'
GROUP BY e.first_name, e.last_name
ORDER BY verified_count 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 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)
)
CREATE TABLE government_services.agencies ( agency_id text, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )
CREATE TABLE government_services.applications ( application_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, service_id character varying(64) NOT NULL, submitted_at timestamp NOT NULL, status character varying(50) NOT NULL, last_updated_at timestamp NOT NULL, assigned_employee_id character varying(64), decision_date date, notes text, reference_number character varying(100) UNIQUE, PRIMARY KEY (application_id) )
CREATE TABLE government_services.documents ( document_id text, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees ( employee_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, job_title character varying(150) NOT NULL, department character varying(100), work_email character varying(128) NOT NULL UNIQUE, work_phone character varying(32), hire_date date NOT NULL, termination_date date, access_level character varying(50), manager_employee_id character varying(64), PRIMARY KEY (employee_id) )
CREATE TABLE government_services.service_locations (
    location_id character varying(64) NOT NULL, -- unique identifier for the physical location
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    location_name character varying(200), -- e.g., Downtown DMV Office
    address text NOT NULL,
    city character varying(100),
    state character varying(50),
    postal_code character varying(20),
    latitude numeric(9, 6),
    longitude numeric(9, 6),
    operating_hours text, -- description of opening times
    contact_phone character varying(32),
    is_accessible boolean, -- accessibility information (e.g., wheelchair access)
    PRIMARY KEY (location_id)
)
CREATE TABLE government_services.notifications ( notification_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, application_id character varying(64), message_subject character varying(255), message_body text NOT NULL, channel character varying(30) NOT NULL, sent_at timestamp NOT NULL, status character varying(30) NOT NULL, related_entity_type character varying(50), related_entity_id character varying(64), PRIMARY KEY (notification_id) )


[User] List the IDs of posts and their respective number of hashtags for posts that have two or more hashtags.

[Assistant]
SELECT post_id, COUNT(hashtag_id) AS hashtag_count
FROM social_media.post_hashtags
GROUP BY post_id
HAVING COUNT(hashtag_id) >= 2;

[User] Order the results by hashtag_count descending, and show only the top 10.

[Assistant]
SELECT post_id, COUNT(hashtag_id) AS hashtag_count
FROM social_media.post_hashtags
GROUP BY post_id
HAVING COUNT(hashtag_id) >= 2
ORDER BY hashtag_count 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 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] Show me the user_id and number of conversations they have joined. Only include users who joined more than one conversation.

[Assistant]
SELECT user_id, COUNT(DISTINCT conversation_id) AS conversations_joined
FROM social_media.conversation_participants
GROUP BY user_id
HAVING COUNT(DISTINCT conversation_id) > 1;

[User] Add the time they joined their most recent conversation as latest_joined_at.

[Assistant]
SELECT user_id, COUNT(DISTINCT conversation_id) AS conversations_joined, MAX(joined_at) AS latest_joined_at
FROM social_media.conversation_participants
GROUP BY user_id
HAVING COUNT(DISTINCT conversation_id) > 1;

[User] Also, show the IDs of the conversations for each user as a comma-separated list.

[Assistant]
SELECT user_id,
  COUNT(DISTINCT conversation_id) AS conversations_joined,
  MAX(joined_at) AS latest_joined_at,
  STRING_AGG(DISTINCT conversation_id, ',') AS conversation_ids
FROM social_media.conversation_participants
GROUP BY user_id
HAVING COUNT(DISTINCT conversation_id) > 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 social_media.post_hashtags ( post_hashtag_id text, post_id text, hashtag_id text )
CREATE TABLE social_media.conversation_participants ( participant_id text, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )


[User] Can you list each server along with its game title and how many players it can still accommodate (max_players - current_players)?

[Assistant]
SELECT s.server_id,
       s.server_name,
       g.title AS game_title,
       (s.max_players - s.current_players) AS available_slots
FROM gaming_technology.servers s
JOIN gaming_technology.games g ON s.game_id = g.game_id;

[User] Only include servers that are currently 'online' or 'idle'.

[Assistant]
SELECT s.server_id,
       s.server_name,
       g.title AS game_title,
       (s.max_players - s.current_players) AS available_slots
FROM gaming_technology.servers s
JOIN gaming_technology.games g ON s.game_id = g.game_id
WHERE s.status IN ('online', 'idle');

[User] Now show only those with available_slots greater than 10, sorted by available_slots descending.

[Assistant]
SELECT s.server_id,
       s.server_name,
       g.title AS game_title,
       (s.max_players - s.current_players) AS available_slots
FROM gaming_technology.servers s
JOIN gaming_technology.games g ON s.game_id = g.game_id
WHERE s.status IN ('online', 'idle')
  AND (s.max_players - s.current_players) > 10
ORDER BY available_slots DESC;

[User] Finally, include the game's release_date and only for games released after 2022-01-01.

[Assistant]
SELECT s.server_id,
       s.server_name,
       g.title AS game_title,
       g.release_date,
       (s.max_players - s.current_players) AS available_slots
FROM gaming_technology.servers s
JOIN gaming_technology.games g ON s.game_id = g.game_id
WHERE s.status IN ('online', 'idle')
  AND (s.max_players - s.current_players) > 10
  AND g.release_date > '2022-01-01'
ORDER BY available_slots 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 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, game_id.uuid, server_name.text, region.text, ip_address.text, port.integer, current_players.integer, max_players.integer, status.text, last_heartbeat.timestamptz )
CREATE TABLE gaming_technology.player_achievements ( player_achievement_id uuid NOT NULL DEFAULT gen_random_uuid(), player_id uuid NOT NULL, achievement_id uuid NOT NULL, unlocked_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (player_achievement_id), UNIQUE (player_id, achievement_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] Please list all law firms with their names and address, and also indicate the year they were founded.

[Assistant] SELECT firm_name, address, EXTRACT(YEAR FROM founded_date) AS founded_year FROM legal_services.law_firms;

[User] Just show those founded before 2015.

[Assistant] SELECT firm_name, address, EXTRACT(YEAR FROM founded_date) AS founded_year FROM legal_services.law_firms WHERE founded_date < '2015-01-01';

[User] Can you order them by founded_year descending?

[Assistant] SELECT firm_name, address, EXTRACT(YEAR FROM founded_date) AS founded_year FROM legal_services.law_firms WHERE founded_date < '2015-01-01' ORDER BY founded_year DESC;

[User] Finally, only include firms with a non-null address.

[Assistant] SELECT firm_name, address, EXTRACT(YEAR FROM founded_date) AS founded_year FROM legal_services.law_firms WHERE founded_date < '2015-01-01' AND address IS NOT NULL ORDER BY founded_year 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.law_firms ( firm_id.text, firm_name.text, address.text, phone.text, website.text, founded_date.date, managing_partner_id.text )


[User] For the 'DeFi' narrative, what is the average ROI and the total net inflow (usd_value where type=1) from smart money token inflow?

[Assistant]
SELECT AVG(sm.roi) AS avg_roi, SUM(smt.usd_value) AS total_net_inflow
FROM smart_money_token_inflow smt
JOIN smart_money_profit sm ON smt.chain = sm.chain
WHERE smt.narrative = 'DeFi' AND smt.type = 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 token_basic_info ( coin_id text, token_name text, token_symbol text, token_address text, chain text, price numeric, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, highest_price_24h numeric, lowest_price_24h numeric, market_cap numeric, market_cap_rank numeric, market_cap_change_percentage_24h text, total_volume text, narrative text, trend_rank numeric )
CREATE TABLE narrative_info ( narrative text, top_3_coins text, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, market_cap numeric, volume_24h numeric, trend_rank numeric, token_num numeric )
CREATE TABLE cex_token_balance ( snapshot_time text, chain text, address text, exchange text, token_address text, token_symbol text, balance numeric, usd_value numeric, price numeric )
CREATE TABLE smart_money_profit ( address text, rank numeric, profit numeric, roi numeric, realized_ratio numeric, most_profit_token text, last_trade_time text, chain text )
CREATE TABLE smart_money_token_inflow ( token_address text, token_symbol text, token_amount numeric, usd_value numeric, avg_price numeric, type numeric, address_amount numeric, narrative text, chain text )