[User] Which NFTs minted in the past 14 days on Ethereum have a rarity_score above 70? For each, show contract address, token ID, name, and minter.

[Assistant]
SELECT contract_address, token_id, name, minter
FROM nft_metadata
WHERE blockchain = 'Ethereum'
  AND mint_time >= (extract(epoch from now()) - 14*24*60*60)
  AND rarity_score > 70;

[User] For these NFTs, can you also include the collection name and symbol by joining with the nft_collections table?

[Assistant]
SELECT nm.contract_address, nm.token_id, nm.name, nm.minter, nc.name AS collection_name, nc.symbol
FROM nft_metadata nm
JOIN nft_collections nc
  ON nm.blockchain = nc.blockchain AND nm.contract_address = nc.contract_address
WHERE nm.blockchain = 'Ethereum'
  AND nm.mint_time >= (extract(epoch from now()) - 14*24*60*60)
  AND nm.rarity_score > 70;

[User] Can you filter only those collections where the erc_type is 'ERC1155'?

[Assistant]
SELECT nm.contract_address, nm.token_id, nm.name, nm.minter, nc.name AS collection_name, nc.symbol
FROM nft_metadata nm
JOIN nft_collections nc
  ON nm.blockchain = nc.blockchain AND nm.contract_address = nc.contract_address
WHERE nm.blockchain = 'Ethereum'
  AND nm.mint_time >= (extract(epoch from now()) - 14*24*60*60)
  AND nm.rarity_score > 70
  AND nc.erc_type = 'ERC1155';

[User] Now, also include the owner for each NFT, and order the results by rarity_rank ascending.

[Assistant]
SELECT nm.contract_address, nm.token_id, nm.name, nm.minter, nm.owner, nc.name AS collection_name, nc.symbol
FROM nft_metadata nm
JOIN nft_collections nc
  ON nm.blockchain = nc.blockchain AND nm.contract_address = nc.contract_address
WHERE nm.blockchain = 'Ethereum'
  AND nm.mint_time >= (extract(epoch from now()) - 14*24*60*60)
  AND nm.rarity_score > 70
  AND nc.erc_type = 'ERC1155'
ORDER BY nm.rarity_rank 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 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 sui_coins ( object_id varchar NOT NULL, status varchar NOT NULL, coin_type varchar NOT NULL, balance varchar NOT NULL, owner varchar NOT NULL )
CREATE TABLE sui_coins_metadata (
    object_id varchar NOT NULL, -- object id of the coin metadata object
    coin_type varchar NOT NULL, -- coin type, eg. 0x...66::reap_token::REAP_TOKEN
    status varchar NOT NULL, -- coin status, eg. exists, deleted
    decimals bigint NOT NULL, -- decimals of the coin
    description varchar NOT NULL, -- description of the coin
    icon_url varchar NOT NULL, -- icon url of the coin
    symbol varchar NOT NULL, -- symbol of the coin
    name varchar NOT NULL  -- name of the coin
)
CREATE TABLE sui_nfts ( object_id text, status text, collection_type text, package_id text, previous_transaction text, display text, owner text, name text )
CREATE TABLE nft_metadata ( blockchain text, contract_address text, token_id text, contract_name text, erc_type text, amount bigint, minter text, owner text, mint_block_number bigint, mint_time bigint, mint_transaction_hash text, mint_price text, token_uri text, metadata text, name text, image_uri text, traits text, updated_at bigint, status text, rarity_score real, rarity_rank integer, unique_attribute_count integer, pk integer )
CREATE TABLE nft_collections ( blockchain 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 text, blockchain text, address text, decimals bigint, symbol text, price real, timestamp timestamp )
CREATE TABLE token_prices_latest (
    blockchain varchar(36) NOT NULL, -- blockchain fields for the functionType  in contract
    address varchar(42) NOT NULL, -- address fields for the functionType  in contract
    decimals bigint NOT NULL, -- decimals fields for the functionType  in contract
    symbol varchar(36) NOT NULL, -- symbol fields for the functionType  in contract
    price real NOT NULL, -- price fields for the functionType  in contract
    timestamp timestamp(6) NOT NULL  -- timestamp fields for the functionType  in contract
)
CREATE TABLE erc20_approval ( block_number bigint NOT NULL, block_timestamp timestamp(6) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar NOT NULL, log_index integer NOT NULL, contract_address varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE token_balances ( block_number.bigint, block_timestamp.timestamp, tick.text, wallet_address.text, total_supply.decimal, amount.decimal )
CREATE TABLE token_info (
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the inscription (matches block_timestamp in transactions table)
    block_number bigint NOT NULL, -- Block number containing the inscription (matches block_number in transactions table)
    tx_index integer NOT NULL, -- Index of the transaction containing the inscription (matches transaction_index in transactions table)
    tx_hash varchar(66) NOT NULL, -- Unique identifier of the transaction containing the inscription (matches hash in transactions table)
    tick varchar NOT NULL, -- Token tick
    max_supply decimal(38,0) NOT NULL, -- Max supply
    lim decimal(38,0) NOT NULL, -- Limit of each mint
    wlim decimal(38,0) NOT NULL, -- Limit of each address can maximum mint
    dec integer NOT NULL, -- Decimal for minimum divie
    creator varchar(42) NOT NULL  -- Address originating the inscription (matches from_address in transactions table)
)
CREATE TABLE mud_holesky_redstone (
    address varchar NOT NULL, -- address fields for the functionType  in contract
    table_id varchar NOT NULL, -- table_id fields for the functionType  in contract
    key_bytes varchar NOT NULL, -- key_bytes fields for the functionType  in contract
    key0 varchar NOT NULL, -- key0 fields for the functionType  in contract
    key1 varchar NOT NULL, -- key1 fields for the functionType  in contract
    static_data varchar NOT NULL, -- static_data fields for the functionType  in contract
    encoded_lengths varchar NOT NULL, -- encoded_lengths fields for the functionType  in contract
    dynamic_data varchar NOT NULL, -- dynamic_data fields for the functionType  in contract
    is_deleted boolean NOT NULL, -- is_deleted fields for the functionType  in contract
    block_number bigint NOT NULL, -- Block number uniquely identifying the block
    log_index bigint NOT NULL  -- Index of the log within the transaction
)
CREATE TABLE token_info_bitcoin ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, tick.text, max_supply.decimal, lim.decimal, wlim.decimal, dec.integer, creator.text )
CREATE TABLE token_activities_avalanche (
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the inscription (matches block_timestamp in transactions table)
    block_number bigint NOT NULL, -- Block number containing the inscription (matches block_number in transactions table)
    tx_index integer NOT NULL, -- Index of the transaction containing the inscription (matches transaction_index in transactions table)
    tx_hash varchar(66) NOT NULL, -- Unique identifier of the transaction containing the inscription (matches hash in transactions table)
    log_index integer NOT NULL, -- Index of the log within the transaction
    type varchar(20) NOT NULL, -- Operation: Type of event (deploy, mint, transfer, list)
    tick varchar(255) NOT NULL, -- Ticker: Identifier of the inscription
    id varchar(255) NOT NULL, -- Unique identifier of the inscription
    amt decimal(38,0) NOT NULL, -- Amount to mint: States the amount of the inscription to operation. When operation is mint, has to be less or equal to "lim"
    from_address varchar(42) NOT NULL, -- Address sending the inscription
    to_address varchar(42) NOT NULL  -- Address receiving the inscription
)
CREATE TABLE token_balances_avalanche ( block_number bigint, block_timestamp timestamp, tick varchar, wallet_address varchar, total_supply decimal, amount decimal )


[User] What are the environmental impact assessments for the production of the Airbus A350 model?

[Assistant] I'm sorry, but I don't have access to data regarding the environmental impact assessments for the production of specific aircraft models like the Airbus A350. My information is limited to the technical specifications and basic details stored in the database, such as model name, manufacturer, and capacity. If you have a question related to the available data, I'd be happy to assist.

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 text PRIMARY KEY, model_name text, manufacturer text, passenger_capacity int, max_range_km int, engine_type text, wingspan_m numeric, status text, first_flight_date date )


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

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

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


[User] List all pairs of citizens who registered on the same date. Include each citizen's full name and the shared registration date.

[Assistant]
SELECT c1.first_name || ' ' || c1.last_name AS full_name_1,
       c2.first_name || ' ' || c2.last_name AS full_name_2,
       DATE(c1.registration_date) AS registration_date
FROM government_services.citizens c1
JOIN government_services.citizens c2
  ON DATE(c1.registration_date) = DATE(c2.registration_date)
  AND c1.citizen_id < c2.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, 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 )


[User] List each patient's active insurance policy and the number of prescriptions they have during that policy. Show patient_id, plan_id, policy_number, and prescription_count.

[Assistant]
SELECT pi.patient_id, pi.plan_id, pi.policy_number, COUNT(p.prescription_id) AS prescription_count
FROM healthcare.patient_insurance pi
LEFT JOIN healthcare.prescriptions p
  ON pi.patient_id = p.patient_id
  AND DATE(p.prescription_date) BETWEEN pi.effective_date AND COALESCE(pi.expiration_date, CURRENT_DATE)
GROUP BY pi.patient_id, pi.plan_id, pi.policy_number;

[User] Only include patients with more than 5 prescriptions.

[Assistant]
SELECT pi.patient_id, pi.plan_id, pi.policy_number, COUNT(p.prescription_id) AS prescription_count
FROM healthcare.patient_insurance pi
LEFT JOIN healthcare.prescriptions p
  ON pi.patient_id = p.patient_id
  AND DATE(p.prescription_date) BETWEEN pi.effective_date AND COALESCE(pi.expiration_date, CURRENT_DATE)
GROUP BY pi.patient_id, pi.plan_id, pi.policy_number
HAVING COUNT(p.prescription_id) > 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 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.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.patient_insurance ( patient_insurance_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, plan_id character varying(64) NOT NULL, policy_number character varying(100) NOT NULL, group_number character varying(100), subscriber_name character varying(200), effective_date date NOT NULL, expiration_date date, is_primary boolean NOT NULL DEFAULT true, PRIMARY KEY (patient_insurance_id), UNIQUE (patient_id, plan_id, policy_number) )


[User] For each chain, which token had the highest number of smart money addresses buying it this week? Show the token symbol and narrative too.

[Assistant] SELECT chain, token_symbol, narrative, MAX(address_amount) AS max_buyers FROM smart_money_token_inflow WHERE type = 1 AND DATE_TRUNC('week', CURRENT_DATE) = DATE_TRUNC('week', CURRENT_DATE) GROUP BY chain, token_symbol, narrative;

[User] I got an error, I think the filter for the week may be wrong. Please revise the query so that it only counts buys from the current week.

[Assistant] SELECT chain, token_symbol, narrative, address_amount AS buyers FROM smart_money_token_inflow WHERE type = 1 AND EXTRACT(week FROM CURRENT_DATE) = EXTRACT(week FROM CURRENT_DATE) AND EXTRACT(year FROM CURRENT_DATE) = EXTRACT(year FROM CURRENT_DATE) ORDER BY chain, buyers 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 smart_money_token_inflow ( token_address character varying(100) NOT NULL, -- the token's address token_symbol character varying(100), -- the tokens's symbol token_amount numeric(38,2), -- the absolute value of the amount if user bought minus  the amount user sold of this token usd_value numeric(38,2), -- the absolute usd value of the bought token minus sold token avg_price numeric(38,6), -- the average cost price of user spent on this token type int, -- the direction of the trade on this token. 1 means buying, 2 means selling address_amount integer, -- the amount of the user bought this token narrative character varying(100), -- the category or narrative of the token chain character varying(100), -- the chain that the token resides ,PRIMARY KEY (token_address, chain) )


[User] Could you list all pairs of developers that are based in the same country and share the same website domain?

[Assistant]
SELECT
  d1.name AS developer1_name,
  d2.name AS developer2_name,
  d1.country,
  d1.website
FROM
  gaming_technology.developers AS d1
JOIN
  gaming_technology.developers AS d2 ON d1.country = d2.country
  AND d1.website = d2.website
  AND d1.developer_id < d2.developer_id
WHERE
  d1.country IS NOT NULL
  AND d1.website IS NOT NULL AND d1.website != '';

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.developers (
    developer_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for the developer studio
    name character varying(150) NOT NULL UNIQUE, -- name of the development studio
    country character varying(100), -- country where the studio is based
    founded_year integer, -- year the studio was founded
    website character varying(255), -- developer's official website
    created_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (developer_id)
)


[User] List all ERC20 tokens where the price is between $1 and $10, including their names, symbols, and contract addresses.

[Assistant] SELECT tm.name, tm.symbol, tm.contract_address FROM token_metas tm JOIN token_prices_latest tpl ON tm.contract_address = tpl.contract_address WHERE tm.is_erc20 = 1 AND tpl.price BETWEEN 1 AND 10;

[User] I think there's an error in your query - the token_prices_latest table isn't in the schema. Can you modify it to use the token_balances table instead?

[Assistant] SELECT tm.name, tm.symbol, tm.contract_address FROM token_metas tm JOIN token_balances tb ON tm.contract_address = tb.wallet_address WHERE tm.is_erc20 = 1 AND CAST(tb.amount AS decimal) BETWEEN 1 AND 10;

[User] That doesn't seem right either. Let's just get the basic ERC20 token information without price filtering for now.

[Assistant] SELECT name, symbol, contract_address FROM token_metas WHERE is_erc20 = 1 LIMIT 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, block_number.bigint, transaction_hash.text, transaction_index.bigint, from_address.text, contract_address.text, symbol.text, total_supply.text, name.text, decimals.bigint, is_erc20.integer, is_erc721.integer, is_erc1155.integer, is_proxy.integer, extra_info.text, pk.integer )
CREATE TABLE erc1155_approval_for_all ( block_number bigint NOT NULL, block_timestamp timestamp(3) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar(66) NOT NULL, log_index integer NOT NULL, contract_address varchar(42) NOT NULL )
CREATE TABLE erc20_balances ( block_number bigint NOT NULL, contract_address varchar NOT NULL, wallet_address varchar NOT NULL, amount varchar NOT NULL, pk varchar NOT NULL )
CREATE TABLE erc20_balances_historical ( block_number bigint, contract_address text, wallet_address text, amount text, pk integer )
CREATE TABLE nft_holders ( block_number bigint, contract_address text, wallet_address text, token_id text, contract_type text, amount text, pk text )
CREATE TABLE nft_holder_historical ( block_number.bigint, contract_address.text, wallet_address.text, token_id.text, contract_type.text, amount.text, pk.integer )
CREATE TABLE sui_nfts ( object_id text, status text, collection_type text, package_id text, previous_transaction text, display text, owner text, name text )
CREATE TABLE nft_collections ( blockchain text, contract_address text, name text, symbol text, deploy_block_number bigint, deploy_block_time bigint, erc_type text, owner text, traits text, description text, slug text, media_info text, image_url text, banner_image_url text, updated_at bigint, banner text, token_count bigint, floor_price text, floor_price_symbol text, floor_price_contract text, pk integer )
CREATE TABLE erc20_approval ( block_number bigint NOT NULL, block_timestamp timestamp(6) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar NOT NULL, log_index integer NOT NULL, contract_address varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE token_balances ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )
CREATE TABLE token_info (
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the inscription (matches block_timestamp in transactions table)
    block_number bigint NOT NULL, -- Block number containing the inscription (matches block_number in transactions table)
    tx_index integer NOT NULL, -- Index of the transaction containing the inscription (matches transaction_index in transactions table)
    tx_hash varchar(66) NOT NULL, -- Unique identifier of the transaction containing the inscription (matches hash in transactions table)
    tick varchar NOT NULL, -- Token tick
    max_supply decimal(38,0) NOT NULL, -- Max supply
    lim decimal(38,0) NOT NULL, -- Limit of each mint
    wlim decimal(38,0) NOT NULL, -- Limit of each address can maximum mint
    dec integer NOT NULL, -- Decimal for minimum divie
    creator varchar(42) NOT NULL  -- Address originating the inscription (matches from_address in transactions table)
)
CREATE TABLE token_activities ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash varchar, log_index integer, type varchar, tick varchar, id varchar, amt decimal, from_address varchar, to_address varchar )
CREATE TABLE mud_holesky_redstone ( address varchar NOT NULL, table_id varchar NOT NULL, key_bytes varchar NOT NULL, key0 varchar NOT NULL, key1 varchar NOT NULL, static_data varchar NOT NULL, encoded_lengths varchar NOT NULL, dynamic_data varchar NOT NULL, is_deleted boolean NOT NULL, block_number bigint NOT NULL, log_index bigint NOT NULL )
CREATE TABLE token_balances_bitcoin ( block_number bigint, block_timestamp timestamp, tick varchar, wallet_address varchar, total_supply varchar, amount varchar )
CREATE TABLE token_info_bitcoin ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash varchar, tick varchar, max_supply decimal, lim decimal, wlim decimal, dec integer, creator varchar )
CREATE TABLE token_activities_avalanche ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_balances_avalanche (
    block_number bigint NOT NULL, -- Block number containing the transaction
    block_timestamp timestamp(3) NOT NULL, -- Block timestamp containing the transaction
    tick varchar(20) NOT NULL, -- Ticker: Identifier of the inscription
    wallet_address varchar(42) NOT NULL, -- Address of owner
    total_supply decimal(38,0) NOT NULL, -- Max supply: Set max supply of the inscription
    amount decimal(38,0) NOT NULL  -- The balance of wallet balance at the corresponding block height
)
CREATE TABLE token_info_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash varchar, tick varchar, max_supply decimal, lim decimal, wlim decimal, dec integer, creator varchar, minted decimal, holders decimal, txs decimal, updated_timestamp timestamp, completed_timestamp timestamp, id varchar )


[User] List the first name and last name of the driver and the license plate of the vehicle used for each trip.

[Assistant] SELECT T1.first_name , T1.last_name , T3.license_plate FROM transportation.drivers AS T1 JOIN transportation.trips AS T2 ON T1.driver_id = T2.driver_id JOIN transportation.vehicles AS T3 ON T2.vehicle_id = T3.vehicle_id

[User] Now, restrict this list to only include trips where the vehicle's fuel type is 'Electric'.

[Assistant] SELECT T1.first_name , T1.last_name , T3.license_plate FROM transportation.drivers AS T1 JOIN transportation.trips AS T2 ON T1.driver_id = T2.driver_id JOIN transportation.vehicles AS T3 ON T2.vehicle_id = T3.vehicle_id WHERE T3.fuel_type = 'Electric'

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id.text, license_plate.text, vin.text, make.text, model.text, year.integer, type.text, capacity.integer, fuel_type.text, status.text, depot_id.text, acquisition_date.date )
CREATE TABLE transportation.drivers ( driver_id.text, employee_id.text, first_name.text, last_name.text, license_number.text, license_expiry_date.date, contact_number.text, email.text, hire_date.date, status.text )
CREATE TABLE transportation.routes ( route_id.text, route_number.text, description.text, origin_location_id.text, destination_location_id.text, distance_km.numeric, estimated_duration_minutes.integer, type.text )
CREATE TABLE transportation.trips ( trip_id.text, route_id.text, vehicle_id.text, driver_id.text, scheduled_departure.timestamp, actual_departure.timestamp, scheduled_arrival.timestamp, actual_arrival.timestamp, origin_location_id.text, destination_location_id.text, status.text, passenger_count.integer, cargo_manifest_id.text )
CREATE TABLE transportation.maintenance_logs ( log_id.text, vehicle_id.text, service_date.date, odometer_reading.integer, service_type.text, description.text, cost.numeric, mechanic_name.text, next_service_due_date.date )
CREATE TABLE transportation.fuel_logs ( fuel_log_id.text, vehicle_id.text, trip_id.text, log_timestamp.timestamp, fuel_type.text, quantity.numeric, unit.text, cost_per_unit.numeric, total_cost.numeric, odometer_reading.integer, location_id.text )
CREATE TABLE transportation.passengers ( passenger_id.text, first_name.text, last_name.text, email.text, phone_number.text, date_of_birth.date, loyalty_program_id.text, created_at.timestamp )
CREATE TABLE transportation.bookings ( booking_id.text, 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 guest, list reservation_id, guest_id, check_in_date, and the next reservation_id and its check_in_date.

[Assistant]
SELECT r1.reservation_id,
       r1.guest_id,
       r1.check_in_date,
       r2.reservation_id AS next_reservation_id,
       r2.check_in_date   AS next_check_in_date
FROM reservations r1
LEFT JOIN reservations r2
  ON r1.guest_id = r2.guest_id
 AND r2.check_in_date = (
       SELECT MIN(check_in_date)
       FROM reservations
       WHERE guest_id = r1.guest_id
         AND check_in_date > r1.check_in_date
     );

[User] Only include guests who have at least two reservations.

[Assistant]
SELECT r1.reservation_id,
       r1.guest_id,
       r1.check_in_date,
       r2.reservation_id AS next_reservation_id,
       r2.check_in_date   AS next_check_in_date
FROM reservations r1
LEFT JOIN reservations r2
  ON r1.guest_id = r2.guest_id
 AND r2.check_in_date = (
       SELECT MIN(check_in_date)
       FROM reservations
       WHERE guest_id = r1.guest_id
         AND check_in_date > r1.check_in_date
     )
WHERE r1.guest_id IN (
  SELECT guest_id
  FROM reservations
  GROUP BY guest_id
  HAVING COUNT(*) >= 2
);

[User] Also, only show next reservations that occur within 30 days of the current reservation.

[Assistant]
SELECT r1.reservation_id,
       r1.guest_id,
       r1.check_in_date,
       r2.reservation_id AS next_reservation_id,
       r2.check_in_date   AS next_check_in_date
FROM reservations r1
LEFT JOIN reservations r2
  ON r1.guest_id = r2.guest_id
 AND r2.check_in_date = (
       SELECT MIN(check_in_date)
       FROM reservations
       WHERE guest_id = r1.guest_id
         AND check_in_date > r1.check_in_date
     )
   AND r2.check_in_date <= r1.check_in_date + INTERVAL '30 days'
WHERE r1.guest_id IN (
  SELECT guest_id
  FROM reservations
  GROUP BY guest_id
  HAVING COUNT(*) >= 2
);

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.reservations ( reservation_id text, property_id text, guest_id text, room_id text, room_type_id text, check_in_date date, check_out_date date, actual_check_in_ts timestamp, actual_check_out_ts timestamp, num_adults integer, num_children integer, status text, booking_source text, rate_plan_id text, total_amount numeric, amount_paid numeric, special_requests text, created_at timestamp, updated_at timestamp )


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

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

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

 "CREATE TABLE narrative_info (",
    "narrative character varying(512) NOT NULL, -- the id of narrative",
    "top_3_coins text, -- the top 3 tokens in the narrative",
    "price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour in the narrative",
    "price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours in the narrative",
    "price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days in the narrative",
    "market_cap double precision, -- the market cap of the narrative",
    "volume_24h double precision, -- the trade volume of the narrative",
    "trend_rank bigint, -- the trending rank of the narrative, value 1 expresses the most popular narrative",
    "token_num bigint, -- total token number in the narrative",
    ",PRIMARY KEY (narrative));"

  "CREATE TABLE cex_token_balance (",
    "snapshot_time character varying(32) NOT NULL,  -- the snapshot time of record, converted from original timestamp",
    "chain character varying(128) NOT NULL, -- the chain that the token resides",
    "address character varying(128) NOT NULL, -- the address that holds the assets, owned by a CEX",
    "exchange character varying(512) NOT NULL, -- a centralized exchange name",
    "token_address character varying(128) NOT NULL, -- token contract address",
    "token_symbol character varying(512), --token symbol",
    "balance numeric(38,10), -- token balance",
    "usd_value numeric(38,14), -- value of the token held in USD",
    "price double precision, --price of the token in USD",
    ",PRIMARY KEY (snapshot_time, exchange, address, chain, token_address));"

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

  "CREATE TABLE smart_money_token_performance (",
    "token_address character varying(100) NOT NULL, -- the token's address",
    "token_symbol character varying(100), -- the tokens's symbol",
    "pnl numeric(38,2), -- the profit users made on this token",
    "net_flow numeric(38,2), -- the netflow of the token, means the money user spent minus the the money user sold of this token",
    "avg_cost numeric(38,16), -- the average cost price of user spent on this token",
    "price double precision, -- the current price of the token",
    "realized_ratio numeric(10,2), -- the ratio user sold of the token",
    "roi numeric(10,2), -- the roi users made of this token",
    "chain character varying(100), -- the chain that the token resides",
    "PRIMARY KEY (token_address, chain));",

  "CREATE TABLE smart_money_token_inflow (",
    "token_address character varying(100) NOT NULL, -- the token's address",
    "token_symbol character varying(100), -- the tokens's symbol",
    "token_amount numeric(38,2), -- the absolute value of the amount if user bought minus  the amount user sold of this token",
    "usd_value numeric(38,2), -- the absolute usd value of the bought token minus sold token",
    "avg_price numeric(38,6), -- the average cost price of user spent on this token",
    "type int, -- the direction of the trade on this token. 1 means buying, 2 means selling",
    "address_amount integer, -- the amount of the user bought this token",
    "narrative character varying(100), -- the category or narrative of the token",
    "chain character varying(100), -- the chain that the token resides",
    ",PRIMARY KEY (token_address, chain)",


[User] Count how many posts have media attachments.

[Assistant] SELECT count(*) FROM social_media.posts WHERE media_url IS NOT NULL

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified bool )
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 text PRIMARY KEY, post_id text, user_id text, parent_comment_id text, content text, created_at timestamp, updated_at timestamp )
CREATE TABLE social_media.follows ( follow_id text PRIMARY KEY, follower_user_id text, following_user_id text, created_at timestamp )
CREATE TABLE social_media.hashtags ( hashtag_id.text, tag_name.text, created_at.timestamp )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id 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 text PRIMARY KEY, conversation_id text, sender_user_id text, content text, media_url text, media_type text, sent_at timestamp, read_at timestamp )
CREATE TABLE social_media.conversations ( conversation_id text, created_at timestamp, last_message_at timestamp, is_group_chat boolean, group_name text )
CREATE TABLE social_media.conversation_participants ( participant_id text, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )
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, 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 all reservations with more than 2 adults, along with their property names and room types.

[Assistant] SELECT r.reservation_id, p.property_name, rt.room_type_name, r.check_in_date, r.check_out_date, r.num_adults FROM hospitality_technology.reservations r JOIN hospitality_technology.properties p ON r.property_id = p.property_id JOIN hospitality_technology.room_types rt ON r.room_type_id = rt.room_type_id WHERE r.num_adults > 2;

[User] Now, include only reservations with a total amount over $500 and order them by check-in date.

[Assistant] SELECT r.reservation_id, p.property_name, rt.room_type_name, r.check_in_date, r.check_out_date, r.num_adults, r.total_amount FROM hospitality_technology.reservations r JOIN hospitality_technology.properties p ON r.property_id = p.property_id JOIN hospitality_technology.room_types rt ON r.room_type_id = rt.room_type_id WHERE r.num_adults > 2 AND r.total_amount > 500 ORDER BY r.check_in_date;

[User] The query is missing the guest ID. Can you include that as well?

[Assistant] SELECT r.reservation_id, r.guest_id, p.property_name, rt.room_type_name, r.check_in_date, r.check_out_date, r.num_adults, r.total_amount FROM hospitality_technology.reservations r JOIN hospitality_technology.properties p ON r.property_id = p.property_id JOIN hospitality_technology.room_types rt ON r.room_type_id = rt.room_type_id WHERE r.num_adults > 2 AND r.total_amount > 500 ORDER BY r.check_in_date;

[User] Actually, I need to see only reservations from properties with a star rating of 4.0 or higher.

[Assistant] SELECT r.reservation_id, r.guest_id, p.property_name, rt.room_type_name, r.check_in_date, r.check_out_date, r.num_adults, r.total_amount, p.star_rating FROM hospitality_technology.reservations r JOIN hospitality_technology.properties p ON r.property_id = p.property_id JOIN hospitality_technology.room_types rt ON r.room_type_id = rt.room_type_id WHERE r.num_adults > 2 AND r.total_amount > 500 AND p.star_rating >= 4.0 ORDER BY r.check_in_date;

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 character varying(64) NOT NULL, property_name character varying(255) NOT NULL, address_line1 character varying(255) NOT NULL, address_line2 character varying(255), city character varying(100) NOT NULL, state_province character varying(100), postal_code character varying(20) NOT NULL, country_code character varying(3) NOT NULL, phone_number character varying(30), email_address character varying(255), property_type character varying(50) NOT NULL, star_rating numeric(2,1), timezone character varying(64) NOT NULL, manager_staff_id character varying(64), created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (property_id) )
CREATE TABLE hospitality_technology.rooms ( room_id text PRIMARY KEY, property_id text, room_number text, room_type_id text, floor int, status text, is_smoking boolean, features text, current_condition text, last_cleaned_at timestamp )
CREATE TABLE hospitality_technology.guests ( guest_id text, first_name text, last_name text, email text, phone_number text, date_of_birth date, address_line1 text, city text, state_province text, postal_code text, country_code text, preferences text, loyalty_member_id text, communication_consent boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.reservations ( reservation_id.text, property_id.text, guest_id.text, room_id.text, room_type_id.text, check_in_date.date, check_out_date.date, actual_check_in_ts.timestamp, actual_check_out_ts.timestamp, num_adults.integer, num_children.integer, status.text, booking_source.text, rate_plan_id.text, total_amount.numeric, amount_paid.numeric, special_requests.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE hospitality_technology.staff ( staff_id text, property_id text, first_name text, last_name text, position text, work_email text, work_phone text, hire_date date, termination_date date, is_active boolean, access_level integer, manager_id text, created_at timestamp )
CREATE TABLE hospitality_technology.services ( service_id text PRIMARY KEY, property_id text, service_name text, description text, category text, price numeric, unit text, is_available boolean, department text )
CREATE TABLE hospitality_technology.service_orders ( order_id character varying(64) NOT NULL, reservation_id character varying(64), guest_id character varying(64) NOT NULL, service_id character varying(64) NOT NULL, staff_id_ordered character varying(64), staff_id_delivered character varying(64), order_timestamp timestamp with time zone NOT NULL DEFAULT current_timestamp, delivery_timestamp timestamp with time zone, quantity integer NOT NULL DEFAULT 1, unit_price numeric(10, 2) NOT NULL, total_price numeric(12, 2) NOT NULL, status character varying(50) NOT NULL, notes text, bill_id character varying(64), PRIMARY KEY (order_id), FOREIGN KEY (reservation_id) REFERENCES hospitality_technology.reservations(reservation_id), FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id), FOREIGN KEY (service_id) REFERENCES hospitality_technology.services(service_id), FOREIGN KEY (staff_id_ordered) REFERENCES hospitality_technology.staff(staff_id), FOREIGN KEY (staff_id_delivered) REFERENCES hospitality_technology.staff(staff_id) )
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 character varying(64) NOT NULL, property_id character varying(64) NOT NULL, reservation_id character varying(64) UNIQUE, guest_id character varying(64) NOT NULL, rating_overall integer, rating_cleanliness integer, rating_service integer, rating_location integer, rating_value integer, comment text, review_source character varying(100), review_date timestamp with time zone NOT NULL DEFAULT current_timestamp, is_public boolean DEFAULT true, staff_response text, response_staff_id character varying(64), response_date timestamp with time zone, PRIMARY KEY (review_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id), FOREIGN KEY (reservation_id) REFERENCES hospitality_technology.reservations(reservation_id), FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id), FOREIGN KEY (response_staff_id) REFERENCES hospitality_technology.staff(staff_id) )


[User] For each group chat, list its ID, name, creation time, and the creation time of the next group chat created after it, ordered by creation time.

[Assistant] SELECT conversation_id, group_name, created_at, LEAD(created_at) OVER (ORDER BY created_at) AS next_group_chat_created_at FROM social_media.conversations WHERE is_group_chat = true ORDER BY created_at;

[User] Only show pairs where the next group chat was created within 48 hours of the current one, and also include the time difference in hours.

[Assistant] WITH RankedGroupChats AS ( SELECT conversation_id, group_name, created_at, LEAD(created_at) OVER (ORDER BY created_at) AS next_group_chat_created_at FROM social_media.conversations WHERE is_group_chat = true ) SELECT conversation_id, group_name, created_at, next_group_chat_created_at, EXTRACT(EPOCH FROM (next_group_chat_created_at - created_at)) / 3600 AS time_difference_hours FROM RankedGroupChats WHERE next_group_chat_created_at IS NOT NULL AND EXTRACT(EPOCH FROM (next_group_chat_created_at - created_at)) <= 48 * 3600 ORDER BY created_at;

[User] Further refine: Only include group chats whose names contain 'Discuss'.

[Assistant] WITH RankedGroupChats AS ( SELECT conversation_id, group_name, created_at, LEAD(created_at) OVER (ORDER BY created_at) AS next_group_chat_created_at FROM social_media.conversations WHERE is_group_chat = true ) SELECT conversation_id, group_name, created_at, next_group_chat_created_at, EXTRACT(EPOCH FROM (next_group_chat_created_at - created_at)) / 3600 AS time_difference_hours FROM RankedGroupChats WHERE next_group_chat_created_at IS NOT NULL AND EXTRACT(EPOCH FROM (next_group_chat_created_at - created_at)) <= 48 * 3600 AND group_name LIKE '%Discuss%' ORDER BY created_at;

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.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) )


[User] Find the product type that has the lowest average base premium among all product types that have at least 5 active products. Display the product type and its average base premium.

[Assistant] SELECT product_type, AVG(base_premium) AS average_premium FROM insurance.insurance_products WHERE is_active = TRUE GROUP BY product_type HAVING COUNT(product_id) >= 5 ORDER BY AVG(base_premium) ASC LIMIT 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 insurance.insurance_products ( product_id.text, product_name.text, product_type.text, description.text, base_premium.numeric, coverage_details.text, underwriting_rules.text, is_active.boolean, created_at.timestamp, updated_at.timestamp )


[User] List all accounts for customers who have at least one account with a balance over 10000 and another account with a balance under 1000. Show customer_id, account_id, account_type, balance, and currency.

[Assistant] SELECT account_id ,  customer_id ,  account_type ,  balance ,  currency FROM financial_services.accounts WHERE customer_id IN ( SELECT T1.customer_id FROM financial_services.accounts AS T1 JOIN financial_services.accounts AS T2 ON T1.customer_id  =  T2.customer_id WHERE T1.balance  >  10000 AND T2.balance  <  1000 )

[User] Actually, I only want to see the accounts that meet the specific balance criteria (over 10k or under 1k), not all accounts for those customers. And only include accounts where the status is 'Open'.

[Assistant] SELECT account_id ,  customer_id ,  account_type ,  balance ,  currency FROM financial_services.accounts WHERE customer_id IN ( SELECT T1.customer_id FROM financial_services.accounts AS T1 JOIN financial_services.accounts AS T2 ON T1.customer_id  =  T2.customer_id WHERE T1.balance  >  10000 AND T2.balance  <  1000 ) AND (balance  >  10000 OR balance  <  1000) AND status  =  'Open'

[User] Could you also include the opened_date and sort the results by customer_id, then by balance descending?

[Assistant] SELECT account_id ,  customer_id ,  account_type ,  balance ,  currency ,  opened_date FROM financial_services.accounts WHERE customer_id IN ( SELECT T1.customer_id FROM financial_services.accounts AS T1 JOIN financial_services.accounts AS T2 ON T1.customer_id  =  T2.customer_id WHERE T1.balance  >  10000 AND T2.balance  <  1000 ) AND (balance  >  10000 OR balance  <  1000) AND status  =  'Open' ORDER BY customer_id ASC ,  balance 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.accounts ( account_id text, customer_id text, account_number text, account_type text, balance numeric, currency text, opened_date date, status text, interest_rate numeric, last_updated_at timestamp )


[User] List the first_name, last_name, and email of all clients whose email domain is 'lawfirm.com'.

[Assistant]
SELECT first_name,
       last_name,
       email
FROM legal_services.clients
WHERE split_part(email, '@', 2) = 'lawfirm.com';

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.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.text, case_id.text, document_name.text, document_type.text, storage_path.text, uploaded_by_lawyer_id.text, upload_timestamp.timestamp, version.integer, description.text )
CREATE TABLE legal_services.time_entries ( entry_id text PRIMARY KEY, case_id text, lawyer_id text, date_worked date, hours_spent numeric, billing_rate numeric, description text, is_billable bool, is_billed bool, invoice_id text, created_at timestamp )
CREATE TABLE legal_services.invoices ( invoice_id text PRIMARY KEY, invoice_number text UNIQUE, client_id text, case_id text, issue_date date, due_date date, total_amount numeric, amount_paid numeric, status text, payment_date timestamp, notes text, created_at timestamp )


[User] Provide every combination of medication name and insurance plan name.

[Assistant]
SELECT m.medication_name, p.plan_name
FROM healthcare.medications AS m
CROSS JOIN healthcare.insurance_plans AS p;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.diagnoses ( diagnosis_id character varying(64) NOT NULL, record_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, doctor_id character varying(64) NOT NULL, diagnosis_code character varying(20) NOT NULL, code_type character varying(10) NOT NULL DEFAULT 'ICD-10', description text, diagnosis_date date NOT NULL, status character varying(32) NOT NULL, is_chronic boolean DEFAULT false, PRIMARY KEY (diagnosis_id) )
CREATE TABLE healthcare.medications (
    medication_id character varying(64) NOT NULL, -- unique identifier for the medication type
    medication_name character varying(255) NOT NULL, -- common or brand name
    generic_name character varying(255), -- generic chemical name
    manufacturer character varying(100), -- drug manufacturer
    ndc_code character varying(20) UNIQUE, -- National Drug Code (optional but useful)
    description text, -- description of the medication
    PRIMARY KEY (medication_id)
)
CREATE TABLE healthcare.insurance_plans ( plan_id.text, plan_name.text, insurance_provider.text, plan_type.text, contact_phone.text, website.text )


[User] For each fundraising round in 2022 and 2023, list the round name, the year, the total investment_value, and the count of distinct projects. Also include the average market_cap of associated tokens by matching project_name to token_symbol in token_basic_info.

[Assistant]
SELECT p.rounds_name,
  SUBSTRING(p.investment_date FROM 1 FOR 4) AS year,
  SUM(p.investment_value) AS total_investment,
  COUNT(DISTINCT p.project_id) AS project_count,
  AVG(t.market_cap) AS avg_market_cap
FROM project_fundraising_record p
JOIN token_basic_info t
  ON LOWER(p.project_name) = LOWER(t.token_symbol)
WHERE SUBSTRING(p.investment_date FROM 1 FOR 4) IN ('2022','2023')
GROUP BY p.rounds_name, SUBSTRING(p.investment_date FROM 1 FOR 4);

[User] The join returns no rows. Please change the join to match when token_symbol is contained within project_name, case-insensitive.

[Assistant]
SELECT p.rounds_name,
  SUBSTRING(p.investment_date FROM 1 FOR 4) AS year,
  SUM(p.investment_value) AS total_investment,
  COUNT(DISTINCT p.project_id) AS project_count,
  AVG(t.market_cap) AS avg_market_cap
FROM project_fundraising_record p
JOIN token_basic_info t
  ON LOWER(p.project_name) LIKE '%' || LOWER(t.token_symbol) || '%'
WHERE SUBSTRING(p.investment_date FROM 1 FOR 4) IN ('2022','2023')
GROUP BY p.rounds_name, SUBSTRING(p.investment_date FROM 1 FOR 4);

[User] Now only include rounds where the total investment_value exceeds 5000000.

[Assistant]
SELECT p.rounds_name,
  SUBSTRING(p.investment_date FROM 1 FOR 4) AS year,
  SUM(p.investment_value) AS total_investment,
  COUNT(DISTINCT p.project_id) AS project_count,
  AVG(t.market_cap) AS avg_market_cap
FROM project_fundraising_record p
JOIN token_basic_info t
  ON LOWER(p.project_name) LIKE '%' || LOWER(t.token_symbol) || '%'
WHERE SUBSTRING(p.investment_date FROM 1 FOR 4) IN ('2022','2023')
GROUP BY p.rounds_name, SUBSTRING(p.investment_date FROM 1 FOR 4)
HAVING SUM(p.investment_value) > 5000000;

[User] Finally, order the results by total_investment descending.

[Assistant]
SELECT p.rounds_name,
  SUBSTRING(p.investment_date FROM 1 FOR 4) AS year,
  SUM(p.investment_value) AS total_investment,
  COUNT(DISTINCT p.project_id) AS project_count,
  AVG(t.market_cap) AS avg_market_cap
FROM project_fundraising_record p
JOIN token_basic_info t
  ON LOWER(p.project_name) LIKE '%' || LOWER(t.token_symbol) || '%'
WHERE SUBSTRING(p.investment_date FROM 1 FOR 4) IN ('2022','2023')
GROUP BY p.rounds_name, SUBSTRING(p.investment_date FROM 1 FOR 4)
HAVING SUM(p.investment_value) > 5000000
ORDER BY total_investment 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 project_fundraising_record ( id character varying(32) NOT NULL, project_id character varying(32) NOT NULL, project_name character varying(128) NOT NULL, rounds_name character varying(32), investment_value numeric(38,14), investment_date character varying(128), introduction character varying(128), valuation numeric(38,14) )
CREATE TABLE token_basic_info ( coin_id text, token_name text, token_symbol text, token_address text, chain text, price numeric, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, highest_price_24h numeric, lowest_price_24h numeric, market_cap numeric, market_cap_rank numeric, market_cap_change_percentage_24h text, total_volume text, narrative text, trend_rank numeric )
 "CREATE TABLE narrative_info (",
    "narrative character varying(512) NOT NULL, -- the id of narrative",
    "top_3_coins text, -- the top 3 tokens in the narrative",
    "price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour in the narrative",
    "price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours in the narrative",
    "price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days in the narrative",
    "market_cap double precision, -- the market cap of the narrative",
    "volume_24h double precision, -- the trade volume of the narrative",
    "trend_rank bigint, -- the trending rank of the narrative, value 1 expresses the most popular narrative",
    "token_num bigint, -- total token number in the narrative",
    ",PRIMARY KEY (narrative));"

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

CREATE TABLE smart_money_token_performance ( token_address text, token_symbol text, pnl numeric, net_flow numeric, avg_cost numeric, price numeric, realized_ratio numeric, roi numeric, chain text )
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 )


[User] For each route type, show the total number of trips taken and the total distance covered across all trips for that type.

[Assistant] SELECT T1.type, COUNT(T2.trip_id), SUM(T1.distance_km) FROM transportation.routes AS T1 JOIN transportation.trips AS T2 ON T1.route_id = T2.route_id GROUP BY T1.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.vehicles ( vehicle_id.text, license_plate.text, vin.text, make.text, model.text, year.integer, type.text, capacity.integer, fuel_type.text, status.text, depot_id.text, acquisition_date.date )
CREATE TABLE transportation.drivers ( driver_id.text, employee_id.text, first_name.text, last_name.text, license_number.text, license_expiry_date.date, contact_number.text, email.text, hire_date.date, status.text )
CREATE TABLE transportation.routes ( route_id.text, route_number.text, description.text, origin_location_id.text, destination_location_id.text, distance_km.numeric, estimated_duration_minutes.integer, type.text )
CREATE TABLE transportation.trips ( trip_id.text, route_id.text, vehicle_id.text, driver_id.text, scheduled_departure.timestamp, actual_departure.timestamp, scheduled_arrival.timestamp, actual_arrival.timestamp, origin_location_id.text, destination_location_id.text, status.text, passenger_count.integer, cargo_manifest_id.text )
CREATE TABLE transportation.fuel_logs ( fuel_log_id.text, vehicle_id.text, trip_id.text, log_timestamp.timestamp, fuel_type.text, quantity.numeric, unit.text, cost_per_unit.numeric, total_cost.numeric, odometer_reading.integer, location_id.text )
CREATE TABLE transportation.bookings ( booking_id.text, passenger_id.text, trip_id.text, seat_number.text, booking_time.timestamp, status.text, fare.numeric, payment_transaction_id.text, special_requests.text )


[User] List the plan_id, plan_name, and plan_type for all insurance plans where the insurance_provider is 'Humana'.

[Assistant]
SELECT
  plan_id,
  plan_name,
  plan_type
FROM healthcare.insurance_plans
WHERE
  insurance_provider = 'Humana';

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 character varying(64) NOT NULL, -- unique identifier for the appointment
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to doctors table
    appointment_time timestamp with time zone NOT NULL, -- date and time of the appointment
    duration_minutes integer NOT NULL, -- expected duration in minutes
    reason text, -- reason for the visit
    status character varying(32) NOT NULL, -- e.g., Scheduled, Completed, Cancelled, No-show
    location_id character varying(64), -- FK to a potential locations/clinics table
    notes text, -- notes related to scheduling
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (appointment_id)
)
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)
)
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 PRIMARY KEY, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )
CREATE TABLE healthcare.prescriptions ( prescription_id character varying(64) NOT NULL, record_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, doctor_id character varying(64) NOT NULL, medication_id character varying(64) NOT NULL, dosage character varying(100) NOT NULL, frequency character varying(100) NOT NULL, route character varying(50), start_date date NOT NULL, end_date date, quantity_dispensed numeric(10,2), refills_allowed integer NOT NULL DEFAULT 0, prescription_date timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (prescription_id) )
CREATE TABLE healthcare.insurance_plans (
    plan_id character varying(64) NOT NULL, -- unique identifier for the insurance plan
    plan_name character varying(200) NOT NULL, -- name of the insurance plan
    insurance_provider character varying(100) NOT NULL, -- name of the insurance company
    plan_type character varying(50), -- e.g., PPO, HMO, EPO
    contact_phone character varying(20), -- provider contact number
    website character varying(255), -- provider website
    PRIMARY KEY (plan_id)
)


[User] List the appointment ID, subject, and duration in minutes for all completed appointments.

[Assistant] SELECT appointment_id, subject, EXTRACT(EPOCH FROM (end_time - start_time))/60 AS duration_minutes FROM legal_services.appointments WHERE status = 'Completed';

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] Provide a report of each user with their username and the count of all log entries from the last 30 days.

[Assistant]
SELECT u.user_id, u.username, COUNT(l.log_id) AS log_count
FROM trading_platform.users u
LEFT JOIN trading_platform.logs l
  ON u.user_id = l.user_id
  AND l.logged_at >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY u.user_id, u.username;

[User] Actually, show only logs where the action includes the word 'trade'.

[Assistant]
SELECT u.user_id, u.username, COUNT(l.log_id) AS log_count
FROM trading_platform.users u
JOIN trading_platform.logs l
  ON u.user_id = l.user_id
WHERE l.logged_at >= CURRENT_DATE - INTERVAL '30 days'
  AND l.action ILIKE '%trade%'
GROUP BY u.user_id, u.username;

[User] Also include the earliest log date for each user in that period.

[Assistant]
SELECT u.user_id,
       u.username,
       COUNT(l.log_id) AS log_count,
       MIN(l.logged_at) AS first_log_date
FROM trading_platform.users u
JOIN trading_platform.logs l
  ON u.user_id = l.user_id
WHERE l.logged_at >= CURRENT_DATE - INTERVAL '30 days'
  AND l.action ILIKE '%trade%'
GROUP BY u.user_id, u.username;

[User] Finally, sort the results by log_count descending and limit to the top 5 users.

[Assistant]
SELECT u.user_id,
       u.username,
       COUNT(l.log_id) AS log_count,
       MIN(l.logged_at) AS first_log_date
FROM trading_platform.users u
JOIN trading_platform.logs l
  ON u.user_id = l.user_id
WHERE l.logged_at >= CURRENT_DATE - INTERVAL '30 days'
  AND l.action ILIKE '%trade%'
GROUP BY u.user_id, u.username
ORDER BY log_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 trading_platform.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)
)
CREATE TABLE trading_platform.orders (
    order_id character varying(64) NOT NULL,  -- unique identifier for the order
    user_id character varying(64) NOT NULL, -- identifier of the user placing the order
    wallet_id character varying(64) NOT NULL, -- identifier of the wallet used for the order
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    order_type character varying(32) NOT NULL, -- type of the order (e.g., buy, sell)
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the order
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    status character varying(32) NOT NULL, -- status of the order (e.g., open, filled, canceled)
    created_at timestamp NOT NULL, -- time when the order was created
    PRIMARY KEY (order_id)
)
CREATE TABLE trading_platform.utxos (
    utxo_id character varying(64) NOT NULL,  -- unique identifier for the UTXO
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that created the UTXO
    output_index integer NOT NULL, -- index of the output in the transaction
    address character varying(128) NOT NULL, -- address that can spend the UTXO
    amount numeric(38,14) NOT NULL, -- amount of the asset in the UTXO
    spent boolean NOT NULL, -- whether the UTXO has been spent
    PRIMARY KEY (utxo_id)
)
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
CREATE TABLE trading_platform.peers (
    peer_id character varying(64) NOT NULL,  -- unique identifier for the peer
    ip_address character varying(15) NOT NULL, -- IP address of the peer
    port integer NOT NULL, -- port number of the peer
    last_seen timestamp NOT NULL, -- last time the peer was active
    PRIMARY KEY (peer_id)
)
CREATE TABLE trading_platform.logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the log entry
    user_id character varying(64), -- identifier of the user associated with the log entry
    action character varying(128) NOT NULL, -- action performed
    details text NOT NULL, -- details of the action
    logged_at timestamp NOT NULL, -- time when the log entry was created
    PRIMARY KEY (log_id)
)


[User] Show me all documents uploaded by lawyers from law firms located in 'New York'. Include the document name, upload timestamp, the first and last name of the uploading lawyer, and the firm name.

[Assistant] SELECT d.document_name, d.upload_timestamp, l.first_name AS lawyer_first_name, l.last_name AS lawyer_last_name, lf.firm_name FROM documents AS d JOIN lawyers AS l ON d.uploaded_by_lawyer_id = l.lawyer_id JOIN law_firms AS lf ON l.firm_id = lf.firm_id WHERE lf.address LIKE '%New York%';

[User] Okay, but only show documents where the document type is 'Contract'.

[Assistant] SELECT d.document_name, d.upload_timestamp, l.first_name AS lawyer_first_name, l.last_name AS lawyer_last_name, lf.firm_name FROM documents AS d JOIN lawyers AS l ON d.uploaded_by_lawyer_id = l.lawyer_id JOIN law_firms AS lf ON l.firm_id = lf.firm_id WHERE lf.address LIKE '%New York%' AND d.document_type = 'Contract';

[User] Also, sort the results by upload timestamp descending and include the document version.

[Assistant] SELECT d.document_name, d.upload_timestamp, d.version, l.first_name AS lawyer_first_name, l.last_name AS lawyer_last_name, lf.firm_name FROM documents AS d JOIN lawyers AS l ON d.uploaded_by_lawyer_id = l.lawyer_id JOIN law_firms AS lf ON l.firm_id = lf.firm_id WHERE lf.address LIKE '%New York%' AND d.document_type = 'Contract' ORDER BY d.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.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] Count the number of prescriptions each doctor has written for medications manufactured by 'Pfizer' in the last 6 months.

[Assistant]
SELECT p.doctor_id, COUNT(*) AS prescription_count
FROM healthcare.prescriptions p
JOIN healthcare.medications m ON p.medication_id = m.medication_id
WHERE m.manufacturer = 'Pfizer'
  AND p.prescription_date >= CURRENT_DATE - INTERVAL '6 months'
GROUP BY p.doctor_id;

[User] Actually, please include the doctor's full name instead of the ID, and order the results by prescription_count descending.

[Assistant]
SELECT p.doctor_id,
       d.first_name || ' ' || d.last_name AS doctor_name,
       COUNT(*) AS prescription_count
FROM healthcare.prescriptions p
JOIN healthcare.medications m ON p.medication_id = m.medication_id
JOIN healthcare.doctors d ON p.doctor_id = d.doctor_id
WHERE m.manufacturer = 'Pfizer'
  AND p.prescription_date >= CURRENT_DATE - INTERVAL '6 months'
GROUP BY p.doctor_id, doctor_name
ORDER BY prescription_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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.doctors ( doctor_id text, first_name text, last_name text, specialty text, license_number text, phone_number text, email text, hospital_affiliation_id 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.medications (
    medication_id character varying(64) NOT NULL, -- unique identifier for the medication type
    medication_name character varying(255) NOT NULL, -- common or brand name
    generic_name character varying(255), -- generic chemical name
    manufacturer character varying(100), -- drug manufacturer
    ndc_code character varying(20) UNIQUE, -- National Drug Code (optional but useful)
    description text, -- description of the medication
    PRIMARY KEY (medication_id)
)
CREATE TABLE healthcare.prescriptions ( prescription_id text, record_id text, patient_id text, doctor_id text, medication_id text, dosage text, frequency text, route text, start_date date, end_date date, quantity_dispensed numeric, refills_allowed integer, prescription_date timestamp )
CREATE TABLE healthcare.insurance_plans ( plan_id text, plan_name text, insurance_provider text, plan_type text, contact_phone text, website text )
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id text, patient_id text, plan_id text, policy_number text, group_number text, subscriber_name text, effective_date date, expiration_date date, is_primary boolean )


[User] Show me all events emitted by contracts where the event name contains 'Approval', along with the contract ID and transaction ID, sorted by emitted timestamp in descending order.

[Assistant] SELECT event_id, contract_id, event_name, transaction_id, emitted_at FROM web3.events WHERE event_name LIKE '%Approval%' ORDER BY emitted_at 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 web3.events (
    event_id character varying(64) NOT NULL,  -- unique identifier for the event
    contract_id character varying(64) NOT NULL, -- identifier of the contract emitting the event
    event_name character varying(128) NOT NULL, -- name of the event
    data text NOT NULL, -- data payload of the event
    emitted_at timestamp NOT NULL, -- time when the event was emitted
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that triggered the event
    log_index integer NOT NULL, -- index of the event log in the transaction
    PRIMARY KEY (event_id)
)


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

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

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


[User] List the names of citizens who have submitted applications for services with a standard fee greater than 50.

[Assistant] SELECT DISTINCT T1.first_name, T1.last_name FROM government_services.citizens AS T1 JOIN government_services.applications AS T2 ON T1.citizen_id = T2.citizen_id JOIN government_services.services AS T3 ON T2.service_id = T3.service_id WHERE T3.standard_fee > 50;

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, 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.services (
    service_id character varying(64) NOT NULL, -- unique identifier for the service
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    service_name character varying(255) NOT NULL, -- name of the service (e.g., Driver's License Renewal)
    description text,
    category character varying(100), -- e.g., Licensing, Benefits, Taxation, Permits
    eligibility_criteria text, -- description of who is eligible
    standard_fee numeric(10, 2) DEFAULT 0.00, -- typical fee for the service
    average_processing_time_days integer, -- estimated processing time
    is_active boolean DEFAULT true, -- whether the service is currently offered
    online_application_url character varying(255),
    PRIMARY KEY (service_id)
)
CREATE TABLE government_services.applications ( application_id text, 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.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, 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.service_locations ( location_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, location_name character varying(200), address text NOT NULL, city character varying(100), state character varying(50), postal_code character varying(20), latitude numeric(9, 6), longitude numeric(9, 6), operating_hours text, contact_phone character varying(32), is_accessible boolean, PRIMARY KEY (location_id) )
CREATE TABLE government_services.appointments ( appointment_id.text, 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 )


[User] List the username and email of users whose first wallet creation date is the same day as their user registration date.

[Assistant] SELECT u.username, u.email FROM web3.users u JOIN (SELECT user_id, MIN(created_at) as first_wallet_created_at FROM web3.wallets GROUP BY user_id) w ON u.user_id = w.user_id WHERE DATE(u.created_at) = DATE(w.first_wallet_created_at);

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.events (
    event_id character varying(64) NOT NULL,  -- unique identifier for the event
    contract_id character varying(64) NOT NULL, -- identifier of the contract emitting the event
    event_name character varying(128) NOT NULL, -- name of the event
    data text NOT NULL, -- data payload of the event
    emitted_at timestamp NOT NULL, -- time when the event was emitted
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that triggered the event
    log_index integer NOT NULL, -- index of the event log in the transaction
    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.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] 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] Show me the top 5 users who have interacted with DApps, along with the count of distinct DApps they interacted with and their wallet addresses.

[Assistant] SELECT w.user_id, COUNT(DISTINCT d.dapp_id) AS dapp_count, w.address FROM trading_platform.wallets w JOIN trading_platform.dapps d ON 1=1 GROUP BY w.user_id, w.address ORDER BY dapp_count DESC LIMIT 5;

[User] This query doesn't properly show DApp interactions. Please modify it to correctly join with a table that records user-DApp interactions.

[Assistant] I notice there's no interaction table in the provided schema. Without a table recording user-DApp interactions, I cannot generate this query accurately. Would you like to see users who have wallets and DApps separately instead?

[User] You're right. Instead, show me users who have wallets but have never interacted with any DApps, along with their wallet addresses.

[Assistant] SELECT w.user_id, w.address FROM trading_platform.wallets w WHERE NOT EXISTS (SELECT 1 FROM trading_platform.dapps d WHERE 1=1) GROUP BY w.user_id, w.address;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id.text, user_id.text, address.text, private_key.text, created_at.timestamp )
CREATE TABLE trading_platform.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )
CREATE TABLE trading_platform.assets ( asset_id.text, name.text, symbol.text, type.text )
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
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) )


[User] What is the current salary of employee with ID 'EMP123'?

[Assistant] I'm sorry, but I can't provide information about an employee's salary as it is not included in the data available in the 'employees' table.

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.employees (
    employee_id character varying(64) NOT NULL, -- unique identifier for the employee
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    job_title character varying(128) NOT NULL, -- e.g., 'Aircraft Mechanic', 'Quality Inspector', 'Assembly Technician'
    skill_certifications text, -- comma-separated list or JSON of certifications
    hire_date date NOT NULL,
    assigned_line_id character varying(64), -- FK to the assembly line the employee is currently assigned to (can be null)
    employment_status character varying(50) NOT NULL, -- e.g., 'Active', 'On Leave', 'Terminated'
    supervisor_employee_id character varying(64), -- FK to the employee's supervisor (self-reference, nullable)
    PRIMARY KEY (employee_id)
)