[User] Show me all patients who have been prescribed medications with dosage greater than 200mg, along with their full names and the medication details, including the prescribing doctor's last name.

[Assistant] SELECT p.first_name, p.last_name, m.medication_name, m.description, pr.dosage, d.last_name AS doctor_last_name FROM healthcare.patients p JOIN healthcare.prescriptions pr ON p.patient_id = pr.patient_id JOIN healthcare.medications m ON pr.medication_id = m.medication_id JOIN healthcare.doctors d ON pr.doctor_id = d.doctor_id WHERE CAST(SUBSTRING(pr.dosage FROM '[0-9]+') AS INTEGER) > 200;

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 PRIMARY KEY, 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.medical_records ( record_id text PRIMARY KEY, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )
CREATE TABLE healthcare.diagnoses ( diagnosis_id text, record_id text, patient_id text, doctor_id text, diagnosis_code text, code_type text, description text, diagnosis_date date, status text, is_chronic boolean )
CREATE TABLE healthcare.medications ( medication_id character varying(64) NOT NULL, medication_name character varying(255) NOT NULL, generic_name character varying(255), manufacturer character varying(100), ndc_code character varying(20) UNIQUE, description text, PRIMARY KEY (medication_id) )
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 text PRIMARY KEY, plan_name text, insurance_provider text, plan_type text, contact_phone text, website text )
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] List the total number of notifications sent through each channel for appointments.

[Assistant]
SELECT n.channel, COUNT(*) AS notification_count
FROM government_services.notifications n
WHERE n.related_entity_type = 'Appointment'
GROUP BY n.channel;

[User] Please only include notifications that were sent after March 1, 2024.

[Assistant]
SELECT n.channel, COUNT(*) AS notification_count
FROM government_services.notifications n
WHERE n.related_entity_type = 'Appointment' AND n.sent_at > '2024-03-01'
GROUP BY n.channel;

[User] Exclude any channels where the count is less than 5.

[Assistant]
SELECT n.channel, COUNT(*) AS notification_count
FROM government_services.notifications n
WHERE n.related_entity_type = 'Appointment' AND n.sent_at > '2024-03-01'
GROUP BY n.channel
HAVING COUNT(*) >= 5;

[User] Can you order the results by notification_count in ascending order?

[Assistant]
SELECT n.channel, COUNT(*) AS notification_count
FROM government_services.notifications n
WHERE n.related_entity_type = 'Appointment' AND n.sent_at > '2024-03-01'
GROUP BY n.channel
HAVING COUNT(*) >= 5
ORDER BY notification_count 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 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.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.appointments ( appointment_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, employee_id character varying(64), location_id character varying(64), service_id character varying(64), scheduled_start_time timestamp NOT NULL, scheduled_end_time timestamp, purpose text NOT NULL, status character varying(30) NOT NULL, booking_method character varying(50), created_at timestamp NOT NULL, notes text, PRIMARY KEY (appointment_id) )
CREATE TABLE government_services.notifications (
    notification_id character varying(64) NOT NULL, -- unique identifier for the notification
    citizen_id character varying(64) NOT NULL, -- FK to citizens table
    application_id character varying(64), -- FK to applications table (optional)
    message_subject character varying(255),
    message_body text NOT NULL,
    channel character varying(30) NOT NULL, -- e.g., Email, SMS, Portal Message, Mail
    sent_at timestamp NOT NULL,
    status character varying(30) NOT NULL, -- e.g., Queued, Sent, Delivered, Failed, Read
    related_entity_type character varying(50), -- e.g., Application, Appointment, Document Request
    related_entity_id character varying(64), -- ID of the related entity
    PRIMARY KEY (notification_id)
)


[User] What is the average age of customers created in the last year?

[Assistant] SELECT AVG(DATE_PART('year', CURRENT_DATE) - DATE_PART('year', date_of_birth)) FROM financial_services.customers WHERE created_at >= CURRENT_DATE - INTERVAL '1 year';

[User] Also show the count of such customers.

[Assistant] SELECT AVG(DATE_PART('year', CURRENT_DATE) - DATE_PART('year', date_of_birth)) AS average_age, COUNT(*) AS customer_count FROM financial_services.customers WHERE created_at >= CURRENT_DATE - INTERVAL '1 year';

[User] Only include customers whose email is not null.

[Assistant] SELECT AVG(DATE_PART('year', CURRENT_DATE) - DATE_PART('year', date_of_birth)) AS average_age, COUNT(*) AS customer_count FROM financial_services.customers WHERE created_at >= CURRENT_DATE - INTERVAL '1 year' AND email IS NOT NULL;

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


[User] Show me the top 5 projects by valuation that completed fundraising rounds in the last 12 months, along with their token symbol and price from the token_basic_info table.

[Assistant] SELECT pfr.project_name, pfr.valuation, tbi.token_symbol, tbi.price FROM project_fundraising_record pfr LEFT JOIN token_basic_info tbi ON pfr.project_name = tbi.token_name WHERE pfr.investment_date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) ORDER BY pfr.valuation DESC LIMIT 5;

[User] Can you also include the 24-hour trading volume for these projects' tokens and filter to only include projects with valuation over $100 million?

[Assistant] SELECT pfr.project_name, pfr.valuation, tbi.token_symbol, tbi.price, tbi.total_volume FROM project_fundraising_record pfr LEFT JOIN token_basic_info tbi ON pfr.project_name = tbi.token_name WHERE pfr.investment_date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) AND pfr.valuation > 100000000 ORDER BY pfr.valuation 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 project_fundraising_record (",
    "id character varying(32) NOT NULL,  -- fundraising record id",
    "project_id character varying(32) NOT NULL, -- the invested project's id",
    "project_name character varying(128) NOT NULL, -- name of the invested project",
    "rounds_name character varying(32), -- name of the fundraising round",
    "investment_value numeric(38,14), -- amount of the fundraising in USD",
    "investment_date character varying(128), -- the date of the investment happened",
    "introduction character varying(128), -- the introduction of the invested project",
    "valuation numeric(38,14), -- the valuation of the project in USD when invested",

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 token_dexpool_info ( pair_address character varying(512) NOT NULL, token_name character varying(100) NOT NULL, token_symbol character varying(100) NOT NULL, chain text, price double precision, price_change_percentage_1h double precision, price_change_percentage_6h double precision, price_change_percentage_24h double precision, makers_24h double precision, volume_24h double precision, liquidity double precision, market_cap double precision, trend_rank bigint )
CREATE TABLE smart_money_profit ( address character varying(100) NOT NULL, rank INT, profit numeric(38,6), roi numeric(38,2), realized_ratio numeric(38,2), most_profit_token character varying(100), last_trade_time character varying(100), chain character varying(100) )
  "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] 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 last 20 messages that have a media_url, showing message_id, sender_user_id, media_type, and sent_at, ordered by sent_at descending.

[Assistant]
SELECT message_id,
       sender_user_id,
       media_type,
       sent_at
FROM social_media.messages
WHERE media_url IS NOT NULL
ORDER BY sent_at DESC
LIMIT 20;

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.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)
)


[User] List each payment method, the total amount paid, and the number of payments for each method for services in the 'Education' category.

[Assistant]
SELECT p.payment_method, SUM(p.amount) AS total_amount, COUNT(p.payment_id) AS payment_count
FROM government_services.payments p
JOIN government_services.services s ON p.service_id = s.service_id
WHERE s.category = 'Education'
GROUP BY p.payment_method;

[User] Only include payment methods with total amounts greater than 1000.

[Assistant]
SELECT p.payment_method, SUM(p.amount) AS total_amount, COUNT(p.payment_id) AS payment_count
FROM government_services.payments p
JOIN government_services.services s ON p.service_id = s.service_id
WHERE s.category = 'Education'
GROUP BY p.payment_method
HAVING SUM(p.amount) > 1000;

[User] Exclude payments that are not completed.

[Assistant]
SELECT p.payment_method, SUM(p.amount) AS total_amount, COUNT(p.payment_id) AS payment_count
FROM government_services.payments p
JOIN government_services.services s ON p.service_id = s.service_id
WHERE s.category = 'Education' AND p.status = 'Completed'
GROUP BY p.payment_method
HAVING SUM(p.amount) > 1000;

[User] Show only the payment method with the highest total paid.

[Assistant]
SELECT payment_method, total_amount, payment_count FROM (
  SELECT p.payment_method, SUM(p.amount) AS total_amount, COUNT(p.payment_id) AS payment_count,
         RANK() OVER (ORDER BY SUM(p.amount) DESC) AS method_rank
  FROM government_services.payments p
  JOIN government_services.services s ON p.service_id = s.service_id
  WHERE s.category = 'Education' AND p.status = 'Completed'
  GROUP BY p.payment_method
  HAVING SUM(p.amount) > 1000
) ranked
WHERE method_rank = 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 government_services.agencies ( agency_id.text, agency_name.text, jurisdiction_level.text, primary_contact_email.text, main_phone_number.text, website_url.text, established_date.date, parent_agency_id.text )
CREATE TABLE government_services.services ( service_id.text, agency_id.text, service_name.text, description.text, category.text, eligibility_criteria.text, standard_fee.numeric, average_processing_time_days.integer, is_active.boolean, online_application_url.text )
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.documents ( document_id.text, application_id.text, citizen_id.text, document_type.text, file_reference.text, upload_timestamp.timestamp, expiry_date.date, verification_status.text, verified_by_employee_id.text, verification_timestamp.timestamp )
CREATE TABLE government_services.payments ( payment_id.text, application_id.text, citizen_id.text, service_id.text, amount.numeric, currency.text, payment_method.text, payment_provider_reference.text, payment_timestamp.timestamp, status.text, notes.text )
CREATE TABLE government_services.employees ( employee_id.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.text, agency_id.text, location_name.text, address.text, city.text, state.text, postal_code.text, latitude.numeric, longitude.numeric, operating_hours.text, contact_phone.text, is_accessible.boolean )
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 )
CREATE TABLE government_services.notifications ( notification_id.text, citizen_id.text, application_id.text, message_subject.text, message_body.text, channel.text, sent_at.timestamp, status.text, related_entity_type.text, related_entity_id.text )


[User] For each case type, calculate the average time to close cases in days, only including cases that have been closed.

[Assistant]
SELECT case_type,
       AVG(EXTRACT(EPOCH FROM (date_closed - date_opened)) / 86400) AS avg_close_days
FROM legal_services.cases
WHERE status = 'Closed'
  AND date_closed IS NOT NULL
GROUP BY case_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 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 )


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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.appointments ( appointment_id.text, client_id.text, lawyer_id.text, case_id.text, start_time.timestamp, end_time.timestamp, location.text, subject.text, notes.text, status.text, created_at.timestamp )


[User] For each passenger, compute the count of bookings and average fare for bookings made in February 2024.

[Assistant]
SELECT p.passenger_id, COUNT(b.booking_id) AS booking_count, AVG(b.fare) AS avg_fare
FROM transportation.passengers p
JOIN transportation.bookings b ON p.passenger_id = b.passenger_id
WHERE b.booking_time >= '2024-02-01' AND b.booking_time < '2024-03-01'
GROUP BY p.passenger_id;

[User] I need to see the passengers' first and last names instead of IDs and only include those with an average fare greater than 75.

[Assistant]
SELECT p.first_name, p.last_name, COUNT(b.booking_id) AS booking_count, AVG(b.fare) AS avg_fare
FROM transportation.passengers p
JOIN transportation.bookings b ON p.passenger_id = b.passenger_id
WHERE b.booking_time >= '2024-02-01' AND b.booking_time < '2024-03-01'
GROUP BY p.first_name, p.last_name
HAVING AVG(b.fare) > 75;

[User] Also, order the results by booking_count descending and limit the output to the top 5 passengers.

[Assistant]
SELECT p.first_name, p.last_name, COUNT(b.booking_id) AS booking_count, AVG(b.fare) AS avg_fare
FROM transportation.passengers p
JOIN transportation.bookings b ON p.passenger_id = b.passenger_id
WHERE b.booking_time >= '2024-02-01' AND b.booking_time < '2024-03-01'
GROUP BY p.first_name, p.last_name
HAVING AVG(b.fare) > 75
ORDER BY booking_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 transportation.vehicles ( vehicle_id character varying(64) NOT NULL, license_plate character varying(32) NOT NULL UNIQUE, vin character varying(17) UNIQUE, make character varying(64) NOT NULL, model character varying(64) NOT NULL, year integer NOT NULL, type character varying(32) NOT NULL, capacity integer, fuel_type character varying(32) NOT NULL, status character varying(32) NOT NULL, depot_id character varying(64), acquisition_date date, PRIMARY KEY (vehicle_id) )
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )
CREATE TABLE transportation.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] Show me the total payment amount processed by each staff member for EUR payments, including their staff_id_processed and the count of successful transactions.

[Assistant]
SELECT staff_id_processed, SUM(amount) AS total_amount_eur, COUNT(*) AS successful_transactions
FROM hospitality_technology.payments
WHERE currency_code = 'EUR' AND status = 'Succeeded'
GROUP BY staff_id_processed;

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.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 )


[User] Show me all items of rarity 'Epic', displaying the item's name and type, along with the title of the game it is part of.

[Assistant] SELECT igi.item_name, igi.item_type, g.title FROM gaming_technology.in_game_items igi JOIN gaming_technology.games g ON igi.game_id = g.game_id WHERE igi.rarity = 'Epic';

[User] Only include games released after the year 2020.

[Assistant] SELECT igi.item_name, igi.item_type, g.title FROM gaming_technology.in_game_items igi JOIN gaming_technology.games g ON igi.game_id = g.game_id WHERE igi.rarity = 'Epic' AND g.release_date > '2020-12-31';

[User] For these items, also show the total quantity of each item across all player inventories.

[Assistant] SELECT igi.item_name, igi.item_type, g.title, SUM(pi.quantity) AS total_inventory_quantity FROM gaming_technology.in_game_items igi JOIN gaming_technology.games g ON igi.game_id = g.game_id JOIN gaming_technology.player_inventory pi ON igi.item_id = pi.item_id WHERE igi.rarity = 'Epic' AND g.release_date > '2020-12-31' GROUP BY igi.item_name, igi.item_type, g.title;

[User] Only show items where the total inventory quantity is at least 100.

[Assistant] SELECT igi.item_name, igi.item_type, g.title, SUM(pi.quantity) AS total_inventory_quantity FROM gaming_technology.in_game_items igi JOIN gaming_technology.games g ON igi.game_id = g.game_id JOIN gaming_technology.player_inventory pi ON igi.item_id = pi.item_id WHERE igi.rarity = 'Epic' AND g.release_date > '2020-12-31' GROUP BY igi.item_name, igi.item_type, g.title HAVING SUM(pi.quantity) >= 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 gaming_technology.player_inventory (
    inventory_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for an inventory entry
    player_id uuid NOT NULL, -- FK linking to the player owning the item
    item_id uuid NOT NULL, -- FK linking to the item definition
    quantity integer NOT NULL DEFAULT 1, -- number of items held (for stackable items)
    acquired_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the item was acquired
    instance_data jsonb, -- data specific to this instance (e.g., weapon mods, durability)
    PRIMARY KEY (inventory_id),
    -- Optional unique constraint if items are non-stackable or unique instances
    -- UNIQUE (player_id, item_id) -- Use if quantity is always 1
    -- FOREIGN KEY (player_id) REFERENCES gaming_technology.players(player_id),
    -- FOREIGN KEY (item_id) REFERENCES gaming_technology.in_game_items(item_id)
)


[User] List all appointments that are currently scheduled and show their appointment time.

[Assistant] SELECT appointment_id, patient_id, doctor_id, appointment_time FROM healthcare.appointments WHERE status = 'Scheduled';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.patients ( patient_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, date_of_birth date NOT NULL, gender character varying(10), address text, phone_number character varying(20), email character varying(128) UNIQUE, emergency_contact_name character varying(200), emergency_contact_phone character varying(20), created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (patient_id) )
CREATE TABLE healthcare.appointments ( appointment_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, doctor_id character varying(64) NOT NULL, appointment_time timestamp with time zone NOT NULL, duration_minutes integer NOT NULL, reason text, status character varying(32) NOT NULL, location_id character varying(64), notes text, created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (appointment_id) )
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] Get the number of agents grouped by status. Return status and agent_count.

[Assistant]
SELECT status,
       COUNT(*) AS agent_count
  FROM insurance.agents
 GROUP BY status;

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.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )


[User] Retrieve each agent's ID, full name, and the count of 'Pending' policies they have sold with a premium_amount greater than 2000. Order the results by the policy count descending.

[Assistant]
SELECT a.agent_id,
       a.first_name || ' ' || a.last_name AS agent_name,
       COUNT(p.policy_id) AS pending_policy_count
FROM insurance.agents a
JOIN insurance.policies p ON a.agent_id = p.agent_id
WHERE p.status = 'Pending'
  AND p.premium_amount > 2000
GROUP BY a.agent_id, agent_name
ORDER BY pending_policy_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 insurance.policies ( policy_id text, customer_id text, product_id text, agent_id text, policy_number text, start_date date, end_date date, premium_amount numeric, coverage_limit numeric, deductible numeric, status text, issued_at timestamp, cancellation_date date, cancellation_reason text )
CREATE TABLE insurance.claims (
    claim_id character varying(64) NOT NULL, -- unique identifier for the claim
    policy_id character varying(64) NOT NULL, -- identifier of the policy under which the claim is made (FK to policies)
    customer_id character varying(64) NOT NULL, -- identifier of the customer making the claim (FK to customers)
    incident_date timestamp NOT NULL, -- date and time of the incident leading to the claim
    reported_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- date the claim was reported
    description text NOT NULL, -- detailed description of the incident and claim
    estimated_loss numeric(15, 2), -- initial estimated cost of the loss
    status character varying(30) NOT NULL, -- e.g., Filed, Processing, Under Review, Approved, Denied, Settled
    settlement_amount numeric(15, 2), -- final amount paid out
    settlement_date date,
    claim_handler_id character varying(64), -- identifier for the employee handling the claim (FK to employees/adjusters)
    police_report_number character varying(100),
    PRIMARY KEY (claim_id)
)
CREATE TABLE insurance.agents ( agent_id text, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )
CREATE TABLE insurance.policy_beneficiaries ( beneficiary_id text, policy_id text, customer_id text, first_name text, last_name text, relationship text, percentage_share numeric, contact_info text, added_at timestamp )


[User] Provide a summary of transactions by status, showing the count and the total amount for each status.

[Assistant] SELECT status, COUNT(*) AS transaction_count, SUM(amount) AS total_amount FROM financial_services.transactions GROUP BY status;

[User] Only include statuses where the total transaction count exceeds 5.

[Assistant] SELECT status, COUNT(*) AS transaction_count, SUM(amount) AS total_amount FROM financial_services.transactions GROUP BY status HAVING COUNT(*) > 5;

[User] Sort the results by transaction count descending.

[Assistant] SELECT status, COUNT(*) AS transaction_count, SUM(amount) AS total_amount FROM financial_services.transactions GROUP BY status HAVING COUNT(*) > 5 ORDER BY transaction_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 financial_services.customers ( customer_id text PRIMARY KEY, first_name text, last_name text, date_of_birth date, ssn_hash text, address text, city text, state text, zip_code text, country text, email text, phone_number text, created_at timestamp, status text, risk_profile text )
CREATE TABLE financial_services.accounts ( account_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, account_number character varying(128) NOT NULL UNIQUE, account_type character varying(50) NOT NULL, balance numeric(19, 4) NOT NULL DEFAULT 0.00, currency character varying(3) NOT NULL, opened_date date NOT NULL, status character varying(32) NOT NULL, interest_rate numeric(5, 4), last_updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (account_id), FOREIGN KEY (customer_id) REFERENCES financial_services.customers(customer_id) )
CREATE TABLE financial_services.transactions ( transaction_id character varying(64) NOT NULL, account_id character varying(64) NOT NULL, related_account_id character varying(64), transaction_type character varying(50) NOT NULL, amount numeric(19, 4) NOT NULL, currency character varying(3) NOT NULL, transaction_date timestamp NOT NULL, effective_date date NOT NULL, description text, status character varying(32) NOT NULL, reference_number character varying(128), PRIMARY KEY (transaction_id), FOREIGN KEY (account_id) REFERENCES financial_services.accounts(account_id), FOREIGN KEY (related_account_id) REFERENCES financial_services.accounts(account_id) )
CREATE TABLE financial_services.trades ( trade_id text PRIMARY KEY, account_id text, security_id text, order_id text, trade_type text, quantity numeric, price_per_unit numeric, total_amount numeric, commission numeric, trade_timestamp timestamp, settlement_date date, status text, execution_venue text )
CREATE TABLE financial_services.market_data (
    data_point_id bigserial NOT NULL, -- auto-incrementing primary key
    security_id character varying(64) NOT NULL, -- identifier for the security
    data_timestamp timestamp NOT NULL, -- timestamp for the data point (e.g., end of day, intraday)
    open_price numeric(19, 8), -- opening price for the period
    high_price numeric(19, 8), -- highest price during the period
    low_price numeric(19, 8), -- lowest price during the period
    close_price numeric(19, 8) NOT NULL, -- closing price for the period
    adjusted_close_price numeric(19, 8), -- closing price adjusted for dividends and splits
    volume bigint, -- trading volume during the period
    source character varying(50), -- source of the market data (e.g., Bloomberg, Refinitiv)
    PRIMARY KEY (data_point_id),
    UNIQUE (security_id, data_timestamp), -- Ensure unique data point per security per time
    FOREIGN KEY (security_id) REFERENCES financial_services.securities(security_id)
)
CREATE TABLE financial_services.employees ( employee_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, job_title character varying(100) NOT NULL, department character varying(100), branch_id character varying(64), email character varying(128) NOT NULL UNIQUE, phone_extension character varying(20), hire_date date NOT NULL, termination_date date, manager_id character varying(64), status character varying(32) NOT NULL, PRIMARY KEY (employee_id), FOREIGN KEY (branch_id) REFERENCES financial_services.branches(branch_id), FOREIGN KEY (manager_id) REFERENCES financial_services.employees(employee_id) )
CREATE TABLE financial_services.loans ( loan_id.text, account_id.text, loan_type.text, principal_amount.numeric, current_principal_balance.numeric, interest_rate.numeric, term_months.integer, origination_date.date, maturity_date.date, monthly_payment.numeric, collateral_description.text, status.text )


[User] List the top 3 tokens by net flow on the Binance chain, including their symbol and average cost.

[Assistant] SELECT token_symbol, net_flow, avg_cost FROM smart_money_token_performance WHERE chain = 'Binance' ORDER BY net_flow DESC LIMIT 3;

[User] Actually, I want to see tokens with a positive net flow and ROI above 20%.

[Assistant] SELECT token_symbol, net_flow, avg_cost FROM smart_money_token_performance WHERE chain = 'Binance' AND net_flow > 0 AND roi > 20 ORDER BY net_flow DESC LIMIT 3;

[User] Can you also include the current price and order by ROI instead?

[Assistant] SELECT token_symbol, net_flow, avg_cost, price FROM smart_money_token_performance WHERE chain = 'Binance' AND net_flow > 0 AND roi > 20 ORDER BY roi DESC LIMIT 3;

[User] Now filter these results to only include tokens with a price above $1.

[Assistant] SELECT token_symbol, net_flow, avg_cost, price FROM smart_money_token_performance WHERE chain = 'Binance' AND net_flow > 0 AND roi > 20 AND price > 1 ORDER BY roi DESC LIMIT 3;

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


[User] For each asset, calculate the total quantity and average price of orders that have status 'filled'.

[Assistant]
SELECT o.asset_id,
       SUM(o.quantity) AS total_quantity,
       AVG(o.price)     AS average_price
FROM trading_platform.orders o
WHERE o.status = 'filled'
GROUP BY o.asset_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 trading_platform.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 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.assets (
    asset_id character varying(64) NOT NULL,  -- unique identifier for the asset
    name character varying(128) NOT NULL, -- name of the asset
    symbol character varying(32) NOT NULL, -- symbol of the asset
    type character varying(32) NOT NULL, -- type of the asset (e.g., cryptocurrency, stock)
    PRIMARY KEY (asset_id)
)
CREATE TABLE trading_platform.utxos (
    utxo_id character varying(64) NOT NULL,  -- unique identifier for the UTXO
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that created the UTXO
    output_index integer NOT NULL, -- index of the output in the transaction
    address character varying(128) NOT NULL, -- address that can spend the UTXO
    amount numeric(38,14) NOT NULL, -- amount of the asset in the UTXO
    spent boolean NOT NULL, -- whether the UTXO has been spent
    PRIMARY KEY (utxo_id)
)
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
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.metadata (
    metadata_id character varying(64) NOT NULL,  -- unique identifier for the metadata
    asset_id character varying(64) NOT NULL, -- identifier of the asset the metadata is associated with
    key character varying(128) NOT NULL, -- key of the metadata
    value text NOT NULL, -- value of the metadata
    PRIMARY KEY (metadata_id)
)
CREATE TABLE trading_platform.kyc_audit (
    kyc_audit_id character varying(64) NOT NULL,  -- unique identifier for the KYC audit
    user_id character varying(64) NOT NULL, -- identifier of the user being audited
    status character varying(32) NOT NULL, -- status of the KYC audit (e.g., pending, approved, rejected)
    reviewed_at timestamp NOT NULL, -- time when the KYC audit was reviewed
    PRIMARY KEY (kyc_audit_id)
)
CREATE TABLE trading_platform.notifications (
    notification_id character varying(64) NOT NULL,  -- unique identifier for the notification
    user_id character varying(64) NOT NULL, -- identifier of the user receiving the notification
    message text NOT NULL, -- message of the notification
    sent_at timestamp NOT NULL, -- time when the notification was sent
    read_at timestamp, -- time when the notification was read
    PRIMARY KEY (notification_id)
)


[User] Count the number of logs for each action type.

[Assistant]
SELECT action,
       COUNT(*) AS count
FROM trading_platform.logs
GROUP BY action;

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.logs ( log_id text PRIMARY KEY, user_id text, action text, details text, logged_at timestamp )


[User] For each event, display its event_id, the event_id of the previous event in the same transaction (if any), and the log_index of both events.

[Assistant]
SELECT curr.event_id   AS current_event_id,
       prev.event_id   AS previous_event_id,
       curr.log_index  AS current_log_index,
       prev.log_index  AS previous_log_index,
       curr.transaction_id
FROM web3.events curr
LEFT JOIN web3.events prev
  ON curr.transaction_id = prev.transaction_id
 AND curr.log_index = prev.log_index + 1;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.events ( event_id character varying(64) NOT NULL, contract_id character varying(64) NOT NULL, event_name character varying(128) NOT NULL, data text NOT NULL, emitted_at timestamp NOT NULL, transaction_id character varying(64) NOT NULL, log_index integer NOT NULL, PRIMARY KEY (event_id) )


[User] Show me all notifications that are related to posts created by users who have a verified profile. Include the notification type, the recipient username, and the post ID.

[Assistant]
SELECT
  n.notification_type,
  u_recipient.username AS recipient_username,
  n.target_entity_id AS post_id
FROM social_media.notifications AS n
JOIN social_media.posts AS p
  ON n.target_entity_id = p.post_id
JOIN social_media.users AS u_creator
  ON p.user_id = u_creator.user_id
JOIN social_media.users AS u_recipient
  ON n.recipient_user_id = u_recipient.user_id
WHERE
  n.target_entity_type = 'post' AND u_creator.is_verified = true;

[User] Actually, I only want to see notifications of type 'like' or 'comment'.

[Assistant]
SELECT
  n.notification_type,
  u_recipient.username AS recipient_username,
  n.target_entity_id AS post_id
FROM social_media.notifications AS n
JOIN social_media.posts AS p
  ON n.target_entity_id = p.post_id
JOIN social_media.users AS u_creator
  ON p.user_id = u_creator.user_id
JOIN social_media.users AS u_recipient
  ON n.recipient_user_id = u_recipient.user_id
WHERE
  n.target_entity_type = 'post' AND u_creator.is_verified = true AND n.notification_type IN ('like', 'comment');

[User] Can you also include the creation timestamp of the notification and order the results with the most recent notifications first?

[Assistant]
SELECT
  n.notification_type,
  u_recipient.username AS recipient_username,
  n.target_entity_id AS post_id,
  n.created_at AS notification_created_at
FROM social_media.notifications AS n
JOIN social_media.posts AS p
  ON n.target_entity_id = p.post_id
JOIN social_media.users AS u_creator
  ON p.user_id = u_creator.user_id
JOIN social_media.users AS u_recipient
  ON n.recipient_user_id = u_recipient.user_id
WHERE
  n.target_entity_type = 'post' AND u_creator.is_verified = true AND n.notification_type IN ('like', 'comment')
ORDER BY
  n.created_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 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.posts (
    post_id character varying(64) NOT NULL, -- unique identifier for the post
    user_id character varying(64) NOT NULL, -- identifier of the user who created the post (FK to users.user_id)
    content text, -- textual content of the post
    media_url text, -- URL to attached media (image/video)
    media_type character varying(20), -- type of media ('image', 'video', null)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of post creation
    updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of last post edit
    visibility character varying(20) NOT NULL DEFAULT 'public', -- visibility ('public', 'friends', 'private')
    location_lat numeric(9,6), -- latitude of post location
    location_lon numeric(9,6), -- longitude of post location
    PRIMARY KEY (post_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.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)
)


[User] Show me all electric vehicles that have completed trips in the last month, along with the count of trips each vehicle has completed.

[Assistant] SELECT v.vehicle_id, v.make, v.model, COUNT(t.trip_id) AS trip_count FROM transportation.vehicles v JOIN transportation.trips t ON v.vehicle_id = t.vehicle_id WHERE v.fuel_type = 'electric' AND t.status = 'completed' AND t.actual_arrival >= NOW() - INTERVAL '1 month' GROUP BY v.vehicle_id, v.make, v.model ORDER BY trip_count DESC;

[User] Now include the average passenger count for these trips per vehicle.

[Assistant] SELECT v.vehicle_id, v.make, v.model, COUNT(t.trip_id) AS trip_count, AVG(t.passenger_count) AS avg_passengers FROM transportation.vehicles v JOIN transportation.trips t ON v.vehicle_id = t.vehicle_id WHERE v.fuel_type = 'electric' AND t.status = 'completed' AND t.actual_arrival >= NOW() - INTERVAL '1 month' GROUP BY v.vehicle_id, v.make, v.model ORDER BY trip_count DESC;

[User] Filter this to only show vehicles that have completed more than 5 trips and had an average passenger count greater than 10.

[Assistant] SELECT v.vehicle_id, v.make, v.model, COUNT(t.trip_id) AS trip_count, AVG(t.passenger_count) AS avg_passengers FROM transportation.vehicles v JOIN transportation.trips t ON v.vehicle_id = t.vehicle_id WHERE v.fuel_type = 'electric' AND t.status = 'completed' AND t.actual_arrival >= NOW() - INTERVAL '1 month' GROUP BY v.vehicle_id, v.make, v.model HAVING COUNT(t.trip_id) > 5 AND AVG(t.passenger_count) > 10 ORDER BY trip_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id character varying(64) NOT NULL, license_plate character varying(32) NOT NULL UNIQUE, vin character varying(17) UNIQUE, make character varying(64) NOT NULL, model character varying(64) NOT NULL, year integer NOT NULL, type character varying(32) NOT NULL, capacity integer, fuel_type character varying(32) NOT NULL, status character varying(32) NOT NULL, depot_id character varying(64), acquisition_date date, PRIMARY KEY (vehicle_id) )
CREATE TABLE transportation.trips ( trip_id character varying(64) NOT NULL, route_id character varying(64), vehicle_id character varying(64) NOT NULL, driver_id character varying(64) NOT NULL, scheduled_departure timestamp with time zone NOT NULL, actual_departure timestamp with time zone, scheduled_arrival timestamp with time zone NOT NULL, actual_arrival timestamp with time zone, origin_location_id character varying(64) NOT NULL, destination_location_id character varying(64) NOT NULL, status character varying(32) NOT NULL, passenger_count integer, cargo_manifest_id character varying(64), PRIMARY KEY (trip_id) )
CREATE TABLE transportation.fuel_logs ( fuel_log_id character varying(64) NOT NULL, vehicle_id character varying(64) NOT NULL, trip_id character varying(64), log_timestamp timestamp with time zone NOT NULL, fuel_type character varying(32) NOT NULL, quantity numeric(10, 3) NOT NULL, unit character varying(16) NOT NULL, cost_per_unit numeric(8, 4), total_cost numeric(10, 2) NOT NULL, odometer_reading integer, location_id character varying(64), PRIMARY KEY (fuel_log_id) )
CREATE TABLE transportation.bookings ( booking_id character varying(64) NOT NULL, passenger_id character varying(64) NOT NULL, trip_id character varying(64) NOT NULL, seat_number character varying(16), booking_time timestamp with time zone NOT NULL, status character varying(32) NOT NULL, fare numeric(10, 2) NOT NULL, payment_transaction_id character varying(128), special_requests text, PRIMARY KEY (booking_id) )


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

[Assistant]
SELECT AVG(sm.roi) AS avg_roi, SUM(smt.usd_value) AS total_net_inflow
FROM smart_money_token_inflow smt
JOIN smart_money_profit sm ON smt.chain = sm.chain
WHERE smt.narrative = 'DeFi' AND smt.type = 1;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE token_basic_info ( coin_id text, token_name text, token_symbol text, token_address text, chain text, price numeric, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, highest_price_24h numeric, lowest_price_24h numeric, market_cap numeric, market_cap_rank numeric, market_cap_change_percentage_24h text, total_volume text, narrative text, trend_rank numeric )
CREATE TABLE narrative_info ( narrative text, top_3_coins text, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, market_cap numeric, volume_24h numeric, trend_rank numeric, token_num numeric )
CREATE TABLE cex_token_balance ( snapshot_time text, chain text, address text, exchange text, token_address text, token_symbol text, balance numeric, usd_value numeric, price numeric )
CREATE TABLE smart_money_profit ( address text, rank numeric, profit numeric, roi numeric, realized_ratio numeric, most_profit_token text, last_trade_time text, chain text )
CREATE TABLE smart_money_token_inflow ( token_address text, token_symbol text, token_amount numeric, usd_value numeric, avg_price numeric, type numeric, address_amount numeric, narrative text, chain text )


[User] For each route, show the route_number, origin and destination location names with their cities, and the average departure delay (in minutes) for trips where actual_departure was later than scheduled_departure.

[Assistant]
SELECT r.route_number,
       lo.name       AS origin_name,
       lo.city       AS origin_city,
       ld.name       AS destination_name,
       ld.city       AS destination_city,
       AVG(EXTRACT(EPOCH FROM (t.actual_departure - t.scheduled_departure)) / 60) AS avg_delay_minutes
FROM transportation.routes r
JOIN transportation.trips t
  ON r.route_id = t.route_id
JOIN transportation.locations lo
  ON r.origin_location_id = lo.location_id
JOIN transportation.locations ld
  ON r.destination_location_id = ld.location_id
WHERE t.actual_departure > t.scheduled_departure
GROUP BY r.route_number, origin_name, origin_city, destination_name, destination_city;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.vehicles (
    vehicle_id character varying(64) NOT NULL,  -- unique identifier for the vehicle
    license_plate character varying(32) NOT NULL UNIQUE, -- vehicle license plate
    vin character varying(17) UNIQUE, -- vehicle identification number
    make character varying(64) NOT NULL, -- manufacturer of the vehicle
    model character varying(64) NOT NULL, -- model of the vehicle
    year integer NOT NULL, -- manufacturing year
    type character varying(32) NOT NULL, -- type of vehicle (e.g., Bus, Train, Truck, Car, Van)
    capacity integer, -- passenger or cargo capacity
    fuel_type character varying(32) NOT NULL, -- e.g., Diesel, Gasoline, Electric, Hydrogen
    status character varying(32) NOT NULL, -- e.g., Active, Maintenance, Decommissioned
    depot_id character varying(64), -- identifier of the home depot/base
    acquisition_date date, -- date the vehicle was acquired
    PRIMARY KEY (vehicle_id)
)
CREATE TABLE transportation.drivers ( driver_id character varying(64) NOT NULL, employee_id character varying(64) NOT NULL UNIQUE, first_name character varying(128) NOT NULL, last_name character varying(128) NOT NULL, license_number character varying(64) NOT NULL UNIQUE, license_expiry_date date NOT NULL, contact_number character varying(32), email character varying(128) UNIQUE, hire_date date NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (driver_id) )
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 character varying(64) NOT NULL,  -- unique identifier for a specific trip instance
    route_id character varying(64), -- identifier of the route being followed (can be null for ad-hoc trips)
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle used
    driver_id character varying(64) NOT NULL, -- identifier of the driver operating
    scheduled_departure timestamp with time zone NOT NULL, -- planned departure time
    actual_departure timestamp with time zone, -- actual departure time
    scheduled_arrival timestamp with time zone NOT NULL, -- planned arrival time
    actual_arrival timestamp with time zone, -- actual arrival time
    origin_location_id character varying(64) NOT NULL, -- actual starting location (could differ from route origin)
    destination_location_id character varying(64) NOT NULL, -- actual ending location (could differ from route destination)
    status character varying(32) NOT NULL, -- e.g., Scheduled, In Progress, Completed, Delayed, Cancelled
    passenger_count integer, -- number of passengers (if applicable)
    cargo_manifest_id character varying(64), -- link to cargo details (if applicable)
    PRIMARY KEY (trip_id)
)
CREATE TABLE transportation.locations ( location_id.text, name.text, type.text, address_line1.text, city.text, state_province.text, postal_code.text, country.text, latitude.numeric, longitude.numeric, timezone.text )
CREATE TABLE transportation.passengers ( passenger_id text PRIMARY KEY, first_name text, last_name text, email text, phone_number text, date_of_birth date, loyalty_program_id text, created_at timestamp )
CREATE TABLE transportation.bookings (
    booking_id character varying(64) NOT NULL,  -- unique identifier for the booking
    passenger_id character varying(64) NOT NULL, -- identifier of the passenger making the booking
    trip_id character varying(64) NOT NULL, -- identifier of the trip being booked
    seat_number character varying(16), -- assigned seat number (if applicable)
    booking_time timestamp with time zone NOT NULL, -- time when the booking was made
    status character varying(32) NOT NULL, -- e.g., Confirmed, Cancelled, Pending Payment
    fare numeric(10, 2) NOT NULL, -- price paid for the booking
    payment_transaction_id character varying(128), -- reference to the payment transaction
    special_requests text, -- any special requests from the passenger
    PRIMARY KEY (booking_id)
)


[User] List each patient's first and last name along with their total number of appointments in 2024.

[Assistant]
SELECT p.first_name, p.last_name, COUNT(a.appointment_id) AS appointment_count
FROM healthcare.patients p
LEFT JOIN healthcare.appointments a
  ON p.patient_id = a.patient_id
  AND a.appointment_time BETWEEN '2024-01-01' AND '2024-12-31'
GROUP BY p.first_name, p.last_name;

[User] Now exclude all 'Cancelled' appointments from the count.

[Assistant]
SELECT p.first_name, p.last_name, COUNT(a.appointment_id) AS appointment_count
FROM healthcare.patients p
LEFT JOIN healthcare.appointments a
  ON p.patient_id = a.patient_id
  AND a.appointment_time BETWEEN '2024-01-01' AND '2024-12-31'
  AND a.status <> 'Cancelled'
GROUP BY p.first_name, p.last_name;

[User] Also, only show patients who have more than 2 appointments and sort the result by appointment_count in descending order.

[Assistant]
SELECT p.first_name, p.last_name, COUNT(a.appointment_id) AS appointment_count
FROM healthcare.patients p
LEFT JOIN healthcare.appointments a
  ON p.patient_id = a.patient_id
  AND a.appointment_time BETWEEN '2024-01-01' AND '2024-12-31'
  AND a.status <> 'Cancelled'
GROUP BY p.first_name, p.last_name
HAVING COUNT(a.appointment_id) > 2
ORDER BY appointment_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 character varying(64) NOT NULL,  -- unique identifier for the patient
    first_name character varying(100) NOT NULL, -- patient's first name
    last_name character varying(100) NOT NULL, -- patient's last name
    date_of_birth date NOT NULL, -- patient's date of birth
    gender character varying(10), -- patient's gender (e.g., Male, Female, Other)
    address text, -- patient's home address
    phone_number character varying(20), -- patient's phone number
    email character varying(128) UNIQUE, -- patient's email address
    emergency_contact_name character varying(200), -- name of emergency contact
    emergency_contact_phone character varying(20), -- phone number of emergency contact
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, -- record creation time
    updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, -- record last update time
    PRIMARY KEY (patient_id)
)
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)
)


[User] For each agent, show their agent_id, first and last name, and the total estimated loss for all claims they have handled as a claim handler.

[Assistant]
SELECT a.agent_id, a.first_name, a.last_name, SUM(c.estimated_loss) AS total_estimated_loss
FROM insurance.agents a
JOIN insurance.claims c ON a.agent_id = c.claim_handler_id
GROUP BY a.agent_id, a.first_name, a.last_name;

[User] Actually, please only show agents with a total estimated loss above 100000.

[Assistant]
SELECT a.agent_id, a.first_name, a.last_name, SUM(c.estimated_loss) AS total_estimated_loss
FROM insurance.agents a
JOIN insurance.claims c ON a.agent_id = c.claim_handler_id
GROUP BY a.agent_id, a.first_name, a.last_name
HAVING SUM(c.estimated_loss) > 100000;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.policies ( policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, product_id character varying(64) NOT NULL, agent_id character varying(64), policy_number character varying(100) NOT NULL UNIQUE, start_date date NOT NULL, end_date date NOT NULL, premium_amount numeric(12, 2) NOT NULL, coverage_limit numeric(15, 2) NOT NULL, deductible numeric(10, 2) NOT NULL, status character varying(30) NOT NULL, issued_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, cancellation_date date, cancellation_reason text, PRIMARY KEY (policy_id) )
CREATE TABLE insurance.claims ( claim_id character varying(64) NOT NULL, policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, incident_date timestamp NOT NULL, reported_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, description text NOT NULL, estimated_loss numeric(15, 2), status character varying(30) NOT NULL, settlement_amount numeric(15, 2), settlement_date date, claim_handler_id character varying(64), police_report_number character varying(100), PRIMARY KEY (claim_id) )
CREATE TABLE insurance.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )


[User] List the usernames and user IDs of all users whose bio contains the word 'developer'.

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

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


[User] Find all pairs of policies for the same customer where their coverage periods overlap. Show customer_id, policy1_id, policy2_id, overlap_start, and overlap_end.

[Assistant]
SELECT p1.customer_id,
       p1.policy_id AS policy1_id,
       p2.policy_id AS policy2_id,
       GREATEST(p1.start_date, p2.start_date) AS overlap_start,
       LEAST(p1.end_date, p2.end_date) AS overlap_end
FROM insurance.policies p1
JOIN insurance.policies p2
  ON p1.customer_id = p2.customer_id
 AND p1.policy_id < p2.policy_id
 AND p1.start_date <= p2.end_date
 AND p2.start_date <= p1.end_date;

[User] Actually, I only want those overlapping pairs where both policies are currently active.

[Assistant]
SELECT p1.customer_id,
       p1.policy_id AS policy1_id,
       p2.policy_id AS policy2_id,
       GREATEST(p1.start_date, p2.start_date) AS overlap_start,
       LEAST(p1.end_date, p2.end_date) AS overlap_end
FROM insurance.policies p1
JOIN insurance.policies p2
  ON p1.customer_id = p2.customer_id
 AND p1.policy_id < p2.policy_id
 AND p1.start_date <= p2.end_date
 AND p2.start_date <= p1.end_date
WHERE p1.status = 'active'
  AND p2.status = 'active';

[User] Also include the policy numbers for both policies in the output.

[Assistant]
SELECT p1.customer_id,
       p1.policy_id AS policy1_id,
       p1.policy_number AS policy1_number,
       p2.policy_id AS policy2_id,
       p2.policy_number AS policy2_number,
       GREATEST(p1.start_date, p2.start_date) AS overlap_start,
       LEAST(p1.end_date, p2.end_date) AS overlap_end
FROM insurance.policies p1
JOIN insurance.policies p2
  ON p1.customer_id = p2.customer_id
 AND p1.policy_id < p2.policy_id
 AND p1.start_date <= p2.end_date
 AND p2.start_date <= p1.end_date
WHERE p1.status = 'active'
  AND p2.status = 'active';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.policies ( policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, product_id character varying(64) NOT NULL, agent_id character varying(64), policy_number character varying(100) NOT NULL UNIQUE, start_date date NOT NULL, end_date date NOT NULL, premium_amount numeric(12, 2) NOT NULL, coverage_limit numeric(15, 2) NOT NULL, deductible numeric(10, 2) NOT NULL, status character varying(30) NOT NULL, issued_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, cancellation_date date, cancellation_reason text, PRIMARY KEY (policy_id) )


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

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

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


[User] I need a report of patients who have received prescriptions for medications manufactured by 'Pfizer'. Include patient ID, first name, last name, medication_name, and prescription_date.

[Assistant]
SELECT p.patient_id,
       p.first_name,
       p.last_name,
       m.medication_name,
       pr.prescription_date
FROM healthcare.patients AS p
JOIN healthcare.prescriptions AS pr ON p.patient_id = pr.patient_id
JOIN healthcare.medications AS m ON pr.medication_id = m.medication_id
WHERE m.manufacturer = 'Pfizer';

[User] Actually, only include prescriptions with a dosage containing 'mg' and sort by prescription_date descending.

[Assistant]
SELECT p.patient_id,
       p.first_name,
       p.last_name,
       m.medication_name,
       pr.prescription_date
FROM healthcare.patients AS p
JOIN healthcare.prescriptions AS pr ON p.patient_id = pr.patient_id
JOIN healthcare.medications AS m ON pr.medication_id = m.medication_id
WHERE m.manufacturer = 'Pfizer'
  AND pr.dosage ILIKE '%mg%'
ORDER BY pr.prescription_date DESC;

[User] Also, include the patient's primary insurance policy number and plan name in the report.

[Assistant]
SELECT p.patient_id,
       p.first_name,
       p.last_name,
       m.medication_name,
       pr.prescription_date,
       pi.policy_number,
       ip.plan_name
FROM healthcare.patients AS p
JOIN healthcare.prescriptions AS pr ON p.patient_id = pr.patient_id
JOIN healthcare.medications AS m ON pr.medication_id = m.medication_id
JOIN healthcare.patient_insurance AS pi
  ON p.patient_id = pi.patient_id AND pi.is_primary = true
JOIN healthcare.insurance_plans AS ip ON pi.plan_id = ip.plan_id
WHERE m.manufacturer = 'Pfizer'
  AND pr.dosage ILIKE '%mg%'
ORDER BY pr.prescription_date 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 character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, date_of_birth date NOT NULL, gender character varying(10), address text, phone_number character varying(20), email character varying(128) UNIQUE, emergency_contact_name character varying(200), emergency_contact_phone character varying(20), created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (patient_id) )
CREATE TABLE healthcare.appointments ( appointment_id text, patient_id text, doctor_id text, appointment_time timestamp, duration_minutes integer, reason text, status text, location_id text, notes text, created_at timestamp )
CREATE TABLE healthcare.medical_records ( record_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, appointment_id character varying(64) UNIQUE, doctor_id character varying(64) NOT NULL, record_date timestamp with time zone NOT NULL, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals jsonb, created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (record_id) )
CREATE TABLE healthcare.diagnoses ( diagnosis_id text PRIMARY KEY, record_id text, patient_id text, doctor_id text, diagnosis_code text, code_type text, description text, diagnosis_date date, status text, is_chronic boolean )
CREATE TABLE healthcare.medications ( medication_id text, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )
CREATE TABLE healthcare.prescriptions ( prescription_id.text, record_id.text, patient_id.text, doctor_id.text, medication_id.text, dosage.text, frequency.text, route.text, start_date.date, end_date.date, quantity_dispensed.numeric, refills_allowed.integer, prescription_date.timestamp )
CREATE TABLE healthcare.insurance_plans ( plan_id.text, plan_name.text, insurance_provider.text, plan_type.text, contact_phone.text, website.text )
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id 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] What is the current market price of a Boeing 737 MAX aircraft?

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

System:
You are an SQL statement expert and you can refuse the user's question if the question is not related to the table structure. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE manufacturing.aircraft_models (
    model_id character varying(64) NOT NULL,  -- unique identifier for the aircraft model
    model_name character varying(128) NOT NULL, -- commercial name of the model (e.g., 737 MAX, A320neo)
    manufacturer character varying(128) NOT NULL, -- manufacturer name (e.g., Boeing, Airbus)
    passenger_capacity integer, -- typical passenger capacity
    max_range_km integer, -- maximum flight range in kilometers
    engine_type character varying(100), -- type of engines used
    wingspan_m numeric(6,2), -- wingspan in meters
    status character varying(50) NOT NULL, -- e.g., 'In Production', 'Development', 'Discontinued'
    first_flight_date date, -- date of the model's first flight
    PRIMARY KEY (model_id)
)


[User] List the full name (first name and last name) of all citizens who have uploaded documents whose expiry date is in the past.

[Assistant] SELECT DISTINCT T1.first_name, T1.last_name FROM government_services.citizens AS T1 INNER JOIN government_services.documents AS T2 ON T1.citizen_id = T2.citizen_id WHERE T2.expiry_date < CURRENT_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 government_services.citizens ( citizen_id text PRIMARY KEY, national_id_number text, first_name text, last_name text, date_of_birth date, gender text, primary_address text, contact_email text, contact_phone text, registration_date timestamp, is_verified boolean )
CREATE TABLE government_services.agencies ( agency_id text PRIMARY KEY, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )
CREATE TABLE government_services.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text PRIMARY KEY, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.service_locations ( location_id text PRIMARY KEY, agency_id text, location_name text, address text, city text, state text, postal_code text, latitude numeric, longitude numeric, operating_hours text, contact_phone text, is_accessible boolean )
CREATE TABLE government_services.appointments ( appointment_id text PRIMARY KEY, citizen_id text, employee_id text, location_id text, service_id text, scheduled_start_time timestamp, scheduled_end_time timestamp, purpose text, status text, booking_method text, created_at timestamp, notes text )


[User] Show the names and cities of all service locations, along with the agency ID, for locations whose postal code starts with '10'.

[Assistant] SELECT location_name, city, agency_id FROM government_services.service_locations WHERE postal_code LIKE '10%';

[User] Actually, only include those locations that are marked as accessible.

[Assistant] SELECT location_name, city, agency_id FROM government_services.service_locations WHERE postal_code LIKE '10%' AND is_accessible = TRUE;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.service_locations (
    location_id character varying(64) NOT NULL, -- unique identifier for the physical location
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    location_name character varying(200), -- e.g., Downtown DMV Office
    address text NOT NULL,
    city character varying(100),
    state character varying(50),
    postal_code character varying(20),
    latitude numeric(9, 6),
    longitude numeric(9, 6),
    operating_hours text, -- description of opening times
    contact_phone character varying(32),
    is_accessible boolean, -- accessibility information (e.g., wheelchair access)
    PRIMARY KEY (location_id)
)