[User] I need the total amount and count of payments for each policy.

[Assistant]
SELECT policy_id,
       COUNT(*) AS payment_count,
       SUM(amount_paid) AS total_paid
FROM insurance.premium_payments
GROUP BY policy_id;

[User] Only include policies where the total_paid is greater than 10000.

[Assistant]
SELECT policy_id,
       COUNT(*) AS payment_count,
       SUM(amount_paid) AS total_paid
FROM insurance.premium_payments
GROUP BY policy_id
HAVING SUM(amount_paid) > 10000;

[User] Now consider only completed payments.

[Assistant]
SELECT policy_id,
       COUNT(*) AS payment_count,
       SUM(amount_paid) AS total_paid
FROM insurance.premium_payments
WHERE status = 'Completed'
GROUP BY policy_id
HAVING SUM(amount_paid) > 10000;

[User] Also include the date of the most recent payment for each policy.

[Assistant]
SELECT t.policy_id,
       t.payment_count,
       t.total_paid,
       lp.last_payment_date
FROM (
  SELECT policy_id,
         COUNT(*) AS payment_count,
         SUM(amount_paid) AS total_paid
  FROM insurance.premium_payments
  WHERE status = 'Completed'
  GROUP BY policy_id
  HAVING SUM(amount_paid) > 10000
) t
JOIN (
  SELECT policy_id,
         MAX(payment_date) AS last_payment_date
  FROM insurance.premium_payments
  WHERE status = 'Completed'
  GROUP BY policy_id
) lp ON t.policy_id = lp.policy_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.premium_payments (
    payment_id character varying(64) NOT NULL, -- unique identifier for the payment
    policy_id character varying(64) NOT NULL, -- identifier of the policy the payment is for (FK to policies)
    customer_id character varying(64) NOT NULL, -- identifier of the customer making the payment (FK to customers)
    payment_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- date the payment was received
    amount_paid numeric(12, 2) NOT NULL, -- amount of the payment
    payment_method character varying(50), -- e.g., Credit Card, Bank Transfer, Check
    transaction_reference character varying(128) UNIQUE, -- reference from payment processor
    due_date date, -- due date for this payment installment
    payment_period_start date, -- start date of the period this payment covers
    payment_period_end date, -- end date of the period this payment covers
    status character varying(30) NOT NULL DEFAULT 'Completed', -- e.g., Completed, Pending, Failed, Refunded
    PRIMARY KEY (payment_id)
)


[User] How many documents have an expiry date within the next 30 days?

[Assistant]
SELECT COUNT(*) AS document_count
FROM government_services.documents
WHERE expiry_date BETWEEN CURRENT_DATE AND (CURRENT_DATE + INTERVAL '30 days');

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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.documents (
    document_id character varying(64) NOT NULL, -- unique identifier for the document instance
    application_id character varying(64), -- FK to applications table (optional, could be linked to citizen directly)
    citizen_id character varying(64) NOT NULL, -- FK to citizens table
    document_type character varying(100) NOT NULL, -- e.g., Passport Scan, Proof of Address, Birth Certificate
    file_reference text NOT NULL, -- reference to the stored file (e.g., S3 URL, internal path)
    upload_timestamp timestamp NOT NULL,
    expiry_date date,
    verification_status character varying(30) DEFAULT 'Pending', -- e.g., Pending, Verified, Rejected
    verified_by_employee_id character varying(64), -- FK to employees table
    verification_timestamp timestamp,
    PRIMARY KEY (document_id)
)
CREATE TABLE government_services.payments ( payment_id character varying(64) NOT NULL, application_id character varying(64), citizen_id character varying(64) NOT NULL, service_id character varying(64), amount numeric(12, 2) NOT NULL, currency character varying(3) NOT NULL DEFAULT 'USD', payment_method character varying(50), payment_provider_reference character varying(128), payment_timestamp timestamp NOT NULL, status character varying(30) NOT NULL, notes text, PRIMARY KEY (payment_id) )
CREATE TABLE government_services.employees ( employee_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, job_title character varying(150) NOT NULL, department character varying(100), work_email character varying(128) NOT NULL UNIQUE, work_phone character varying(32), hire_date date NOT NULL, termination_date date, access_level character varying(50), manager_employee_id character varying(64), PRIMARY KEY (employee_id) )
CREATE TABLE government_services.service_locations ( location_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, location_name character varying(200), address text NOT NULL, city character varying(100), state character varying(50), postal_code character varying(20), latitude numeric(9, 6), longitude numeric(9, 6), operating_hours text, contact_phone character varying(32), is_accessible boolean, PRIMARY KEY (location_id) )
CREATE TABLE government_services.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    citizen_id character varying(64) NOT NULL, -- FK to citizens table
    employee_id character varying(64), -- FK to employees table (optional, if assigned)
    location_id character varying(64), -- FK to service_locations table (if physical)
    service_id character varying(64), -- FK to services table (optional, if related to specific service)
    scheduled_start_time timestamp NOT NULL,
    scheduled_end_time timestamp,
    purpose text NOT NULL, -- reason for the appointment
    status character varying(30) NOT NULL, -- e.g., Scheduled, Completed, Cancelled, No-Show
    booking_method character varying(50), -- e.g., Online, Phone, In-Person
    created_at timestamp NOT NULL, -- when the appointment was booked
    notes text,
    PRIMARY KEY (appointment_id)
)
CREATE TABLE government_services.notifications ( notification_id text PRIMARY KEY, citizen_id text, application_id text, message_subject text, message_body text, channel text, sent_at timestamp, status text, related_entity_type text, related_entity_id text )


[User] Provide a count of notifications, separated by whether they have been read or not.

[Assistant] SELECT CASE WHEN T1.read_at IS NULL THEN 'Unread' ELSE 'Read' END, count(T1.notification_id) FROM trading_platform.notifications AS T1 GROUP BY CASE WHEN T1.read_at IS NULL THEN 'Unread' ELSE 'Read' END

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.notifications ( notification_id.text, user_id.text, message.text, sent_at.timestamp, read_at.timestamp )


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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.tokens ( token_id character varying(64) NOT NULL, contract_address character varying(128) NOT NULL, token_name character varying(128) NOT NULL, token_symbol character varying(32) NOT NULL, decimals integer NOT NULL, total_supply numeric(38,14) NOT NULL, PRIMARY KEY (token_id) )
CREATE TABLE web3.wallets ( wallet_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, address character varying(128) NOT NULL, private_key text NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (wallet_id) )


[User] Count how many appointments have been canceled at each location. Return the location and cancelled_count.

[Assistant]
SELECT location, COUNT(*) AS cancelled_count
FROM legal_services.appointments
WHERE status = 'Canceled'
GROUP BY location;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.clients ( client_id text PRIMARY KEY, first_name text, last_name text, company_name text, email text UNIQUE, phone text, address text, date_registered timestamp, status text )
CREATE TABLE legal_services.lawyers (
    lawyer_id character varying(64) NOT NULL,  -- unique identifier for the lawyer
    first_name character varying(100) NOT NULL, -- lawyer's first name
    last_name character varying(100) NOT NULL, -- lawyer's last name
    bar_number character varying(64) UNIQUE NOT NULL, -- lawyer's bar association number
    firm_id character varying(64), -- FK to law_firms table
    email character varying(128) UNIQUE NOT NULL, -- lawyer's professional email
    phone character varying(32), -- lawyer's contact phone number
    specialization text, -- areas of legal expertise
    hire_date timestamp NOT NULL, -- date the lawyer was hired or joined
    is_partner boolean DEFAULT false, -- flag indicating if the lawyer is a partner
    PRIMARY KEY (lawyer_id)
)
CREATE TABLE legal_services.time_entries (
    entry_id character varying(64) NOT NULL,  -- unique identifier for the time entry
    case_id character varying(64) NOT NULL, -- FK to cases table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table (who performed the work)
    date_worked date NOT NULL, -- date the work was performed
    hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), -- duration of work in hours (e.g., 1.5 for 1h 30m)
    billing_rate numeric(10, 2) NOT NULL, -- hourly rate applied for this entry
    description text NOT NULL, -- detailed description of the work performed
    is_billable boolean DEFAULT true, -- whether this time entry is billable to the client
    is_billed boolean DEFAULT false, -- whether this entry has been included in an invoice
    invoice_id character varying(64), -- FK to invoices table (once billed)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the entry was recorded
    PRIMARY KEY (entry_id)
)
CREATE TABLE legal_services.invoices ( invoice_id.text, invoice_number.text, client_id.text, case_id.text, issue_date.date, due_date.date, total_amount.numeric, amount_paid.numeric, status.text, payment_date.timestamp, notes.text, created_at.timestamp )
CREATE TABLE legal_services.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    client_id character varying(64) NOT NULL, -- FK to clients table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table
    case_id character varying(64), -- FK to cases table (optional, if related to a specific case)
    start_time timestamp NOT NULL, -- scheduled start date and time
    end_time timestamp NOT NULL, -- scheduled end date and time
    location text, -- location of the meeting (address or virtual link)
    subject character varying(255), -- subject or purpose of the appointment
    notes text, -- additional notes for the appointment
    status character varying(50) NOT NULL, -- e.g., Scheduled, Completed, Canceled, Rescheduled
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (appointment_id)
)


[User] Find all medical records where the vitals JSON field contains a blood pressure reading higher than 140/90, and show the patient_id, record_date, and vitals.

[Assistant] SELECT patient_id, record_date, vitals FROM healthcare.medical_records WHERE (vitals->>'systolic')::int > 140 AND (vitals->>'diastolic')::int > 90;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.medical_records ( record_id.text, patient_id.text, appointment_id.text, doctor_id.text, record_date.timestamp, chief_complaint.text, present_illness_history.text, past_medical_history.text, physical_examination_notes.text, assessment.text, treatment_plan.text, vitals.json, created_at.timestamp )


[User] For each chain in the smart money token inflow data, calculate the total number of addresses involved in buy transactions and the total number of addresses involved in sell transactions. Display the chain, total buy addresses, and total sell addresses.

[Assistant] SELECT chain, SUM(CASE WHEN type = 1 THEN address_amount ELSE 0 END) AS total_buy_addresses, SUM(CASE WHEN type = 2 THEN address_amount ELSE 0 END) AS total_sell_addresses FROM smart_money_token_inflow WHERE type IN (1, 2) GROUP BY chain;

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.text, project_id.text, project_name.text, rounds_name.text, investment_value.numeric, investment_date.text, introduction.text, valuation.numeric )
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 token_dexpool_info ( pair_address.text, token_name.text, token_symbol.text, chain.text, price.numeric, price_change_percentage_1h.numeric, price_change_percentage_6h.numeric, price_change_percentage_24h.numeric, makers_24h.numeric, volume_24h.numeric, liquidity.numeric, market_cap.numeric, trend_rank.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_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] Could you provide a summary of the total balance for each account type?

[Assistant] SELECT account_type, SUM(balance) FROM financial_services.accounts GROUP BY account_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 financial_services.accounts ( account_id text, customer_id text, account_number text, account_type text, balance numeric, currency text, opened_date date, status text, interest_rate numeric, last_updated_at timestamp )
CREATE TABLE financial_services.trades ( trade_id text, 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 )


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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.clients ( client_id text PRIMARY KEY, first_name text, last_name text, company_name text, email text UNIQUE, phone text, address text, date_registered timestamp, status text )
CREATE TABLE legal_services.law_firms ( firm_id text PRIMARY KEY, firm_name text, address text, phone text, website text, founded_date date, managing_partner_id text )
CREATE TABLE legal_services.documents ( document_id text PRIMARY KEY, case_id text, document_name text, document_type text, storage_path text, uploaded_by_lawyer_id text, upload_timestamp timestamp, version int, description text )


[User] Can you narrow this down to only show cases where the case type is 'Criminal'?

[Assistant] SELECT case_name, case_number, date_opened FROM legal_services.cases WHERE lead_lawyer_id = 'lawyer_abc' AND status = 'Open' AND case_type = 'Criminal';

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

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

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

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

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


[User] Show the first name, last name, and email for all guests created in 2023.

[Assistant] SELECT first_name, last_name, email FROM guests WHERE created_at >= '2023-01-01' AND created_at < '2024-01-01';

[User] From the previous list, only include guests who have provided a phone number.

[Assistant] SELECT first_name, last_name, email FROM guests WHERE created_at >= '2023-01-01' AND created_at < '2024-01-01' AND phone_number IS NOT NULL AND 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 hospitality_technology.properties (
    property_id character varying(64) NOT NULL,  -- unique identifier for the property (hotel, resort, etc.)
    property_name character varying(255) NOT NULL, -- name of the property
    address_line1 character varying(255) NOT NULL, -- primary address line
    address_line2 character varying(255), -- secondary address line
    city character varying(100) NOT NULL, -- city
    state_province character varying(100), -- state or province
    postal_code character varying(20) NOT NULL, -- zip or postal code
    country_code character varying(3) NOT NULL, -- ISO country code (e.g., USA, CAN)
    phone_number character varying(30), -- main contact phone
    email_address character varying(255), -- main contact email
    property_type character varying(50) NOT NULL, -- e.g., Hotel, Resort, B&B, Motel
    star_rating numeric(2,1), -- star rating (e.g., 4.5)
    timezone character varying(64) NOT NULL, -- IANA timezone ID (e.g., America/New_York)
    manager_staff_id character varying(64), -- FK to staff table for the general manager
    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 (property_id)
)
CREATE TABLE hospitality_technology.rooms ( room_id.text, property_id.text, room_number.text, room_type_id.text, floor.integer, status.text, is_smoking.boolean, features.text, current_condition.text, last_cleaned_at.timestamp )
CREATE TABLE hospitality_technology.room_types ( room_type_id text PRIMARY KEY, property_id text, type_name text, description text, base_rate numeric, max_occupancy int, bed_type text, area_sqft numeric, amenities text )
CREATE TABLE hospitality_technology.guests ( guest_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, email character varying(255) UNIQUE, phone_number character varying(30), date_of_birth date, address_line1 character varying(255), city character varying(100), state_province character varying(100), postal_code character varying(20), country_code character varying(3), preferences text, loyalty_member_id character varying(64) UNIQUE, communication_consent boolean DEFAULT true, created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (guest_id) )
CREATE TABLE hospitality_technology.reservations ( reservation_id text PRIMARY KEY, property_id text, guest_id text, room_id text, room_type_id text, check_in_date date, check_out_date date, actual_check_in_ts timestamp, actual_check_out_ts timestamp, num_adults int, num_children int, status text, booking_source text, rate_plan_id text, total_amount numeric, amount_paid numeric, special_requests text, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.services ( service_id.text, property_id.text, service_name.text, description.text, category.text, price.numeric, unit.text, is_available.boolean, department.text )
CREATE TABLE hospitality_technology.service_orders ( order_id text PRIMARY KEY, reservation_id text, guest_id text, service_id text, staff_id_ordered text, staff_id_delivered text, order_timestamp timestamp, delivery_timestamp timestamp, quantity int, unit_price numeric, total_price numeric, status text, notes text, bill_id text )
CREATE TABLE hospitality_technology.payments ( payment_id text, reservation_id text, guest_id text, bill_id text, amount numeric, currency_code text, payment_method text, card_type text, card_last_four text, transaction_ref text, payment_timestamp timestamp, status text, staff_id_processed text, notes text )
CREATE TABLE hospitality_technology.reviews ( review_id text, property_id text, reservation_id text, guest_id text, rating_overall integer, rating_cleanliness integer, rating_service integer, rating_location integer, rating_value integer, comment text, review_source text, review_date timestamp, is_public boolean, staff_response text, response_staff_id text, response_date timestamp )


[User] For each contract that has received transactions, list its address and the total value of Ether received.

[Assistant] SELECT T1.address, SUM(T2.value) FROM web3.contracts AS T1 JOIN web3.transactions AS T2 ON T1.address = T2.to_address GROUP BY T1.address;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.contracts ( contract_id character varying(64) NOT NULL, address character varying(128) NOT NULL, abi text NOT NULL, bytecode text NOT NULL, deployer_address character varying(128) NOT NULL, deployed_at timestamp NOT NULL, network_id character varying(64) NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (contract_id) )
CREATE TABLE web3.transactions ( transaction_id character varying(64) NOT NULL, from_address character varying(128) NOT NULL, to_address character varying(128), value numeric(38,14) NOT NULL, gas_used integer NOT NULL, gas_price numeric(38,14) NOT NULL, block_number integer NOT NULL, timestamp timestamp NOT NULL, input_data text, status character varying(32) NOT NULL, nonce integer NOT NULL, PRIMARY KEY (transaction_id) )
CREATE TABLE web3.users ( user_id text, username text, email text, password_hash text, created_at timestamp )


[User] 能否帮我统计数据库中每个城市的车站数量？

[Assistant]
SELECT city, COUNT(*) AS station_count
FROM stations
GROUP BY city
ORDER BY station_count DESC;

System:
You are an expert in writing database language. You can write a corresponding database language query to answer the user's question based on the table structure described by the table creation statement.
##Table Structure
// PUT /stations
{
  "mappings": {
    "properties": {
      "station_id": { "type": "keyword" },
      "station_name": {
        "type": "text",
        "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } }
      },
      "city": { "type": "keyword" },
      "state_province": { "type": "keyword" },
      "country_code": { "type": "keyword" },
      "address": { "type": "text" },
      "timezone": { "type": "keyword" },
      "number_of_platforms": { "type": "integer" },
      "created_at": { "type": "date" },
      "last_updated_at": { "type": "date" }
    }
  }
}
// PUT /platforms
{
  "mappings": {
    "properties": {
      "platform_id": { "type": "keyword" },
      "station_id": { "type": "keyword" }, // References stations index
      "platform_number": { "type": "keyword" },
      "track_number": { "type": "keyword" },
      "status": { "type": "keyword" },
      "length_meters": { "type": "scaled_float", "scaling_factor": 100 }, // Or float/double
      "accessible": { "type": "boolean" }
    }
  }
}
// PUT /trains
{
  "mappings": {
    "properties": {
      "train_id": { "type": "keyword" },
      "train_number": { "type": "keyword" },
      "model": { "type": "keyword" },
      "manufacturer": { "type": "keyword" },
      "year_manufactured": { "type": "integer" },
      "capacity": { "type": "integer" },
      "status": { "type": "keyword" },
      "last_maintenance_date": { "type": "date", "format": "yyyy-MM-dd" },
      "next_maintenance_date": { "type": "date", "format": "yyyy-MM-dd" }
    }
  }
}
// PUT /train_cars
{
  "mappings": {
    "properties": {
      "car_id": { "type": "keyword" },
      "train_id": { "type": "keyword" }, // References trains index
      "car_number": { "type": "keyword" },
      "car_type": { "type": "keyword" },
      "class": { "type": "keyword" },
      "capacity": { "type": "integer" },
      "features": { "type": "keyword" } // Array of keywords
    }
  }
}
// PUT /routes
{
  "mappings": {
    "properties": {
      "route_id": { "type": "keyword" },
      "route_name": {
        "type": "text",
        "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } }
      },
      "description": { "type": "text" },
      "origin_station_id": { "type": "keyword" }, // References stations index
      "destination_station_id": { "type": "keyword" }, // References stations index
      "is_active": { "type": "boolean" }
    }
  }
}
// PUT /route_stations
{
  "mappings": {
    "properties": {
      "route_station_id": { "type": "keyword" },
      "route_id": { "type": "keyword" }, // References routes index
      "station_id": { "type": "keyword" }, // References stations index
      "sequence_order": { "type": "integer" },
      "distance_from_previous_km": { "type": "scaled_float", "scaling_factor": 100 },
      "typical_stop_duration_minutes": { "type": "integer" }
    }
  }
}
// --- OR --- Use a 'nested' type within the 'routes' index mapping:
// "stations": {
//   "type": "nested",
//   "properties": {
//     "station_id": { "type": "keyword" },
//     "sequence_order": { "type": "integer" },
//     ...
//    }
// }
// PUT /schedule_stops
{
  "mappings": {
    "properties": {
      "stop_id": { "type": "keyword" },
      "schedule_id": { "type": "keyword" }, // References schedules index
      "station_id": { "type": "keyword" }, // References stations index
      "platform_id": { "type": "keyword" }, // References platforms index
      "sequence_order": { "type": "integer" },
      "scheduled_arrival_time": { "type": "date" },
      "scheduled_departure_time": { "type": "date" },
      "actual_arrival_time": { "type": "date" },
      "actual_departure_time": { "type": "date" },
      "status": { "type": "keyword" }
    }
  }
}
// --- OR --- Use a 'nested' type within the 'schedules' index mapping:
// "stops": {
//   "type": "nested",
//   "properties": { ... }
// }
// PUT /passengers
{
  "mappings": {
    "properties": {
      "passenger_id": { "type": "keyword" },
      "first_name": {
        "type": "text",
        "fields": { "keyword": { "type": "keyword", "ignore_above": 100 } }
      },
      "last_name": {
        "type": "text",
        "fields": { "keyword": { "type": "keyword", "ignore_above": 100 } }
       },
      "email": { "type": "keyword" }, // Often used for exact matches
      "phone_number": { "type": "keyword" },
      "date_of_birth": { "type": "date", "format": "yyyy-MM-dd" },
      "loyalty_program_id": { "type": "keyword" },
      "created_at": { "type": "date" }
    }
  }
}
// PUT /tickets
{
  "mappings": {
    "properties": {
      "ticket_id": { "type": "keyword" },
      "booking_id": { "type": "keyword" }, // References bookings index
      "car_id": { "type": "keyword" }, // References train_cars index
      "seat_number": { "type": "keyword" },
      "ticket_type": { "type": "keyword" },
      "price": { "type": "scaled_float", "scaling_factor": 100 },
      "is_checked_in": { "type": "boolean" },
      "qr_code_data": { "type": "keyword", "index": false } // Often not searched on
    }
  }
}
// --- OR --- Use a 'nested' type within the 'bookings' index mapping.
// PUT /staff
{
  "mappings": {
    "properties": {
      "staff_id": { "type": "keyword" },
      "first_name": {
        "type": "text",
        "fields": { "keyword": { "type": "keyword", "ignore_above": 100 } }
      },
      "last_name": {
        "type": "text",
        "fields": { "keyword": { "type": "keyword", "ignore_above": 100 } }
      },
      "role": { "type": "keyword" },
      "primary_station_id": { "type": "keyword" }, // References stations index
      "employee_number": { "type": "keyword" },
      "hire_date": { "type": "date", "format": "yyyy-MM-dd" },
      "contact_email": { "type": "keyword" },
      "contact_phone": { "type": "keyword" },
      "is_active": { "type": "boolean" }
    }
  }
}
// PUT /maintenance_records
{
  "mappings": {
    "properties": {
      "record_id": { "type": "keyword" },
      "asset_id": { "type": "keyword" }, // ID of the asset
      "asset_type": { "type": "keyword" }, // Type ('Train', 'Car', etc.)
      "maintenance_type": { "type": "keyword" },
      "staff_id": { "type": "keyword" }, // References staff index
      "start_datetime": { "type": "date" },
      "end_datetime": { "type": "date" },
      "description": { "type": "text" },
      "cost": { "type": "scaled_float", "scaling_factor": 100 },
      "status": { "type": "keyword" }
    }
  }
}


[User] Show me projects that completed a fundraising round in 2023 and have an associated token held by centralized exchanges. Display the project name, fundraising amount, the associated token symbol, and the total USD value of that token held by CEXes across all chains and snapshots.

[Assistant] SELECT pfr.project_name, pfr.investment_value, ctb.token_symbol, SUM(ctb.usd_value) AS total_cex_usd_value FROM project_fundraising_record AS pfr JOIN cex_token_balance AS ctb ON pfr.project_name = ctb.token_symbol WHERE pfr.investment_date LIKE '2023%' GROUP BY pfr.project_name, pfr.investment_value, ctb.token_symbol;

[User] Filter these results further to only include fundraising rounds named 'Seed' or 'Series A'.

[Assistant] SELECT pfr.project_name, pfr.investment_value, ctb.token_symbol, SUM(ctb.usd_value) AS total_cex_usd_value FROM project_fundraising_record AS pfr JOIN cex_token_balance AS ctb ON pfr.project_name = ctb.token_symbol WHERE pfr.investment_date LIKE '2023%' AND pfr.rounds_name IN ('Seed', 'Series A') GROUP BY pfr.project_name, pfr.investment_value, ctb.token_symbol;

[User] Order the results by total CEX USD value descending and limit to top 10.

[Assistant] SELECT pfr.project_name, pfr.investment_value, ctb.token_symbol, SUM(ctb.usd_value) AS total_cex_usd_value FROM project_fundraising_record AS pfr JOIN cex_token_balance AS ctb ON pfr.project_name = ctb.token_symbol WHERE pfr.investment_date LIKE '2023%' AND pfr.rounds_name IN ('Seed', 'Series A') GROUP BY pfr.project_name, pfr.investment_value, ctb.token_symbol ORDER BY total_cex_usd_value DESC LIMIT 10;

[User] I got empty results. Maybe the join condition project_name = token_symbol is too strict. Can you try a more flexible match where the token symbol is contained within the project name or vice versa, case-insensitive?

[Assistant] SELECT pfr.project_name, pfr.investment_value, ctb.token_symbol, SUM(ctb.usd_value) AS total_cex_usd_value FROM project_fundraising_record AS pfr JOIN cex_token_balance AS ctb ON LOWER(pfr.project_name) LIKE '%' || LOWER(ctb.token_symbol) || '%' OR LOWER(ctb.token_symbol) LIKE '%' || LOWER(pfr.project_name) || '%' WHERE pfr.investment_date LIKE '2023%' AND pfr.rounds_name IN ('Seed', 'Series A') GROUP BY pfr.project_name, pfr.investment_value, ctb.token_symbol ORDER BY total_cex_usd_value DESC LIMIT 10;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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 cex_token_balance ( snapshot_time character varying(32) NOT NULL,  -- the snapshot time of record, converted from original timestamp chain character varying(128) NOT NULL, -- the chain that the token resides address character varying(128) NOT NULL, -- the address that holds the assets, owned by a CEX exchange character varying(512) NOT NULL, -- a centralized exchange name token_address character varying(128) NOT NULL, -- token contract address token_symbol character varying(512), --token symbol balance numeric(38,10), -- token balance usd_value numeric(38,14), -- value of the token held in USD price double precision, --price of the token in USD ,PRIMARY KEY (snapshot_time, exchange, address, chain, token_address) )


[User] Show me the user ID, username, and email for all users.

[Assistant] SELECT user_id, username, email FROM blockchain.users;

[User] Now, only show the users whose username starts with 'alpha'.

[Assistant] SELECT user_id, username, email FROM blockchain.users WHERE username LIKE 'alpha%';

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


[User] What is the average delivery time in hours for all delivered service orders?

[Assistant]
SELECT AVG(EXTRACT(EPOCH FROM (so.delivery_timestamp - so.order_timestamp)) / 3600) AS avg_delivery_hours
FROM hospitality_technology.service_orders so
WHERE so.status = 'delivered' AND so.delivery_timestamp IS NOT NULL;

[User] Now only include orders delivered after January 1, 2024.

[Assistant]
SELECT AVG(EXTRACT(EPOCH FROM (so.delivery_timestamp - so.order_timestamp)) / 3600) AS avg_delivery_hours
FROM hospitality_technology.service_orders so
WHERE so.status = 'delivered'
  AND so.delivery_timestamp >= '2024-01-01'::timestamp;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.properties ( property_id.text, property_name.text, address_line1.text, address_line2.text, city.text, state_province.text, postal_code.text, country_code.text, phone_number.text, email_address.text, property_type.text, star_rating.numeric, timezone.text, manager_staff_id.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE hospitality_technology.service_orders ( order_id.text, reservation_id.text, guest_id.text, service_id.text, staff_id_ordered.text, staff_id_delivered.text, order_timestamp.timestamp, delivery_timestamp.timestamp, quantity.integer, unit_price.numeric, total_price.numeric, status.text, notes.text, bill_id.text )


[User] Find all wallets that were created on the same day and list their wallet IDs, addresses, and the creation date.

[Assistant] SELECT w1.wallet_id, w1.address, w1.created_at::date AS creation_date FROM web3.wallets w1 JOIN (SELECT created_at::date AS creation_date FROM web3.wallets GROUP BY created_at::date HAVING COUNT(*) > 1) w2 ON w1.created_at::date = w2.creation_date ORDER BY creation_date, w1.wallet_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 web3.wallets (
    wallet_id character varying(64) NOT NULL,  -- unique identifier for the wallet
    user_id character varying(64) NOT NULL, -- identifier of the user owning the wallet
    address character varying(128) NOT NULL, -- address of the wallet
    private_key text NOT NULL, -- private key of the wallet
    created_at timestamp NOT NULL, -- time when the wallet was created
    PRIMARY KEY (wallet_id)
)


[User] List the content and comment ID for all comments made by users with private profiles.

[Assistant] SELECT c.comment_id, c.content FROM social_media.comments AS c JOIN social_media.user_settings AS us ON c.user_id = us.user_id WHERE us.private_profile = TRUE;

[User] Only show comments created in the year 2024.

[Assistant] SELECT c.comment_id, c.content FROM social_media.comments AS c JOIN social_media.user_settings AS us ON c.user_id = us.user_id WHERE us.private_profile = TRUE AND c.created_at >= '2024-01-01' AND c.created_at < '2025-01-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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.conversation_participants ( participant_id text, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )
CREATE TABLE social_media.user_settings ( setting_id text, user_id text, theme text, email_notifications_enabled boolean, push_notifications_enabled boolean, private_profile boolean, updated_at timestamp )


[User] Give me the count of clients who registered in each month of 2023.

[Assistant] SELECT TO_CHAR(date_registered, 'YYYY-MM') AS reg_month, COUNT(*) AS client_count FROM legal_services.clients WHERE date_registered BETWEEN '2023-01-01' AND '2023-12-31' GROUP BY TO_CHAR(date_registered, 'YYYY-MM') ORDER BY reg_month;

[User] Filter to show only months with more than five registrations.

[Assistant] SELECT TO_CHAR(date_registered, 'YYYY-MM') AS reg_month, COUNT(*) AS client_count FROM legal_services.clients WHERE date_registered BETWEEN '2023-01-01' AND '2023-12-31' GROUP BY TO_CHAR(date_registered, 'YYYY-MM') HAVING COUNT(*) > 5 ORDER BY reg_month;

[User] Can you include the average days since registration for those clients up to today?

[Assistant] SELECT TO_CHAR(date_registered, 'YYYY-MM') AS reg_month, COUNT(*) AS client_count, ROUND(AVG((CURRENT_DATE - date_registered)::INT), 2) AS avg_days_since_registration FROM legal_services.clients WHERE date_registered BETWEEN '2023-01-01' AND '2023-12-31' GROUP BY TO_CHAR(date_registered, 'YYYY-MM') HAVING COUNT(*) > 5;

[User] Now order the results by avg_days_since_registration descending.

[Assistant] SELECT TO_CHAR(date_registered, 'YYYY-MM') AS reg_month, COUNT(*) AS client_count, ROUND(AVG((CURRENT_DATE - date_registered)::INT), 2) AS avg_days_since_registration FROM legal_services.clients WHERE date_registered BETWEEN '2023-01-01' AND '2023-12-31' GROUP BY TO_CHAR(date_registered, 'YYYY-MM') HAVING COUNT(*) > 5 ORDER BY avg_days_since_registration DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.clients ( client_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, company_name character varying(200), email character varying(128) UNIQUE NOT NULL, phone character varying(32), address text, date_registered timestamp NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (client_id) )


[User] Show me all patients who have both primary and non-primary insurance plans from the same provider, including their policy numbers and expiration dates.

[Assistant]
SELECT pi1.patient_id, pi1.policy_number AS primary_policy, pi1.expiration_date AS primary_expiry, pi2.policy_number AS non_primary_policy, pi2.expiration_date AS non_primary_expiry
FROM healthcare.patient_insurance pi1
JOIN healthcare.patient_insurance pi2 ON pi1.patient_id = pi2.patient_id AND pi1.plan_id = pi2.plan_id
WHERE pi1.is_primary = true AND pi2.is_primary = false;

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


[User] Show me a list of all bus routes, including their route numbers, type, and the names of both the origin and destination locations.

[Assistant]
SELECT r.route_number, r.type, lo.name AS origin_name, ld.name AS destination_name
FROM transportation.routes r
JOIN transportation.locations lo ON r.origin_location_id = lo.location_id
JOIN transportation.locations ld ON r.destination_location_id = ld.location_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 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.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 )


[User] For each user, retrieve their most recent log entry, including the action and timestamp.

[Assistant] SELECT l.user_id, l.action, l.logged_at FROM trading_platform.logs l JOIN (SELECT user_id, MAX(logged_at) AS max_time FROM trading_platform.logs GROUP BY user_id) m ON l.user_id = m.user_id AND l.logged_at = m.max_time;

[User] Exclude any logs where the action contains the word 'error'.

[Assistant] SELECT l.user_id, l.action, l.logged_at FROM trading_platform.logs l JOIN (SELECT user_id, MAX(logged_at) AS max_time FROM trading_platform.logs GROUP BY user_id) m ON l.user_id = m.user_id AND l.logged_at = m.max_time WHERE l.action NOT ILIKE '%error%';

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

[Assistant]
SELECT cur.vehicle_id,
       cur.license_plate,
       old.vehicle_id AS older_vehicle_id,
       old.year       AS older_vehicle_year
FROM transportation.vehicles cur
JOIN transportation.vehicles old
  ON cur.type = old.type
 AND old.year < cur.year
ORDER BY cur.vehicle_id, old.year DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.vehicles (
    vehicle_id character varying(64) NOT NULL,  -- unique identifier for the vehicle
    license_plate character varying(32) NOT NULL UNIQUE, -- vehicle license plate
    vin character varying(17) UNIQUE, -- vehicle identification number
    make character varying(64) NOT NULL, -- manufacturer of the vehicle
    model character varying(64) NOT NULL, -- model of the vehicle
    year integer NOT NULL, -- manufacturing year
    type character varying(32) NOT NULL, -- type of vehicle (e.g., Bus, Train, Truck, Car, Van)
    capacity integer, -- passenger or cargo capacity
    fuel_type character varying(32) NOT NULL, -- e.g., Diesel, Gasoline, Electric, Hydrogen
    status character varying(32) NOT NULL, -- e.g., Active, Maintenance, Decommissioned
    depot_id character varying(64), -- identifier of the home depot/base
    acquisition_date date, -- date the vehicle was acquired
    PRIMARY KEY (vehicle_id)
)


[User] List all medical record entries where the treatment_plan mentions a medication name. Return patient_id, record_id, and the matching medication_name.

[Assistant]
SELECT mr.patient_id,
       mr.record_id,
       m.medication_name
FROM healthcare.medical_records AS mr
JOIN healthcare.medications AS m
  ON mr.treatment_plan ILIKE '%' || m.medication_name || '%';

[User] Actually, only include medications manufactured by 'Pfizer'.

[Assistant]
SELECT mr.patient_id,
       mr.record_id,
       m.medication_name
FROM healthcare.medical_records AS mr
JOIN healthcare.medications AS m
  ON mr.treatment_plan ILIKE '%' || m.medication_name || '%'
WHERE m.manufacturer = 'Pfizer';

[User] Also sort the results by record_date descending.

[Assistant]
SELECT mr.patient_id,
       mr.record_id,
       m.medication_name
FROM healthcare.medical_records AS mr
JOIN healthcare.medications AS m
  ON mr.treatment_plan ILIKE '%' || m.medication_name || '%'
WHERE m.manufacturer = 'Pfizer'
ORDER BY mr.record_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,  -- 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.doctors (
    doctor_id character varying(64) NOT NULL,  -- unique identifier for the doctor
    first_name character varying(100) NOT NULL, -- doctor's first name
    last_name character varying(100) NOT NULL, -- doctor's last name
    specialty character varying(100) NOT NULL, -- doctor's medical specialty
    license_number character varying(50) UNIQUE NOT NULL, -- doctor's medical license number
    phone_number character varying(20), -- doctor's contact phone
    email character varying(128) UNIQUE, -- doctor's contact email
    hospital_affiliation_id character varying(64), -- FK to hospitals table (optional)
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (doctor_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)
)
CREATE TABLE healthcare.medications (
    medication_id character varying(64) NOT NULL, -- unique identifier for the medication type
    medication_name character varying(255) NOT NULL, -- common or brand name
    generic_name character varying(255), -- generic chemical name
    manufacturer character varying(100), -- drug manufacturer
    ndc_code character varying(20) UNIQUE, -- National Drug Code (optional but useful)
    description text, -- description of the medication
    PRIMARY KEY (medication_id)
)
CREATE TABLE healthcare.insurance_plans (
    plan_id character varying(64) NOT NULL, -- unique identifier for the insurance plan
    plan_name character varying(200) NOT NULL, -- name of the insurance plan
    insurance_provider character varying(100) NOT NULL, -- name of the insurance company
    plan_type character varying(50), -- e.g., PPO, HMO, EPO
    contact_phone character varying(20), -- provider contact number
    website character varying(255), -- provider website
    PRIMARY KEY (plan_id)
)
CREATE TABLE healthcare.patient_insurance (
    patient_insurance_id character varying(64) NOT NULL, -- unique identifier for this patient-plan link
    patient_id character varying(64) NOT NULL, -- FK to patients table
    plan_id character varying(64) NOT NULL, -- FK to insurance_plans table
    policy_number character varying(100) NOT NULL, -- patient's policy number
    group_number character varying(100), -- group number, if applicable
    subscriber_name character varying(200), -- name of the primary policy holder
    effective_date date NOT NULL, -- date the coverage begins
    expiration_date date, -- date the coverage ends (if known)
    is_primary boolean NOT NULL DEFAULT true, -- indicates if this is the primary insurance
    PRIMARY KEY (patient_insurance_id),
    UNIQUE (patient_id, plan_id, policy_number) -- ensure a patient doesn't have the same policy twice
)


[User] What is the total estimated loss for all claims reported in the year 2024?

[Assistant] SELECT SUM(estimated_loss) FROM insurance.claims WHERE EXTRACT(YEAR FROM reported_date) = 2024;

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


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

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

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

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

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

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

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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )


[User] Show me all wallet addresses that belong to user_id 'U1001', along with their private keys.

[Assistant] SELECT address_id, private_key FROM blockchain.wallets WHERE user_id = 'U1001';

[User] Now join this with another table to show the count of transactions for each of these wallet addresses.

[Assistant] Note: The schema only includes the wallets table. Without a transactions table in the schema, this query cannot be executed. Please provide the transactions table structure if you need this analysis.

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


[User] Show me all reservations with more than 2 adults, along with their property names and room types.

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

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

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

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

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

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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.properties ( property_id.text, property_name.text, address_line1.text, address_line2.text, city.text, state_province.text, postal_code.text, country_code.text, phone_number.text, email_address.text, property_type.text, star_rating.numeric, timezone.text, manager_staff_id.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE hospitality_technology.reservations ( reservation_id.text, property_id.text, guest_id.text, room_id.text, room_type_id.text, check_in_date.date, check_out_date.date, actual_check_in_ts.timestamp, actual_check_out_ts.timestamp, num_adults.integer, num_children.integer, status.text, booking_source.text, rate_plan_id.text, total_amount.numeric, amount_paid.numeric, special_requests.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE hospitality_technology.services ( service_id.text, property_id.text, service_name.text, description.text, category.text, price.numeric, unit.text, is_available.boolean, department.text )


[User] Show the usernames of players and a count of how many different item types they have in their inventory.

[Assistant] SELECT T1.username, count(DISTINCT T3.item_type) FROM gaming_technology.players AS T1 JOIN gaming_technology.player_inventory AS T2 ON T1.player_id = T2.player_id JOIN gaming_technology.in_game_items AS T3 ON T2.item_id = T3.item_id GROUP BY T1.username;

[User] Only include players who have 3 or more different item types.

[Assistant] SELECT T1.username, count(DISTINCT T3.item_type) FROM gaming_technology.players AS T1 JOIN gaming_technology.player_inventory AS T2 ON T1.player_id = T2.player_id JOIN gaming_technology.in_game_items AS T3 ON T2.item_id = T3.item_id GROUP BY T1.username HAVING count(DISTINCT T3.item_type) >= 3;

[User] Order the results by the count of unique item types in descending order.

[Assistant] SELECT T1.username, count(DISTINCT T3.item_type) FROM gaming_technology.players AS T1 JOIN gaming_technology.player_inventory AS T2 ON T1.player_id = T2.player_id JOIN gaming_technology.in_game_items AS T3 ON T2.item_id = T3.item_id GROUP BY T1.username HAVING count(DISTINCT T3.item_type) >= 3 ORDER BY count(DISTINCT T3.item_type) DESC;

[User] For these players, could you also show the total quantity of all items they possess?

[Assistant] SELECT T1.username, count(DISTINCT T3.item_type), sum(T2.quantity) FROM gaming_technology.players AS T1 JOIN gaming_technology.player_inventory AS T2 ON T1.player_id = T2.player_id JOIN gaming_technology.in_game_items AS T3 ON T2.item_id = T3.item_id GROUP BY T1.username HAVING count(DISTINCT T3.item_type) >= 3 ORDER BY count(DISTINCT T3.item_type) DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE gaming_technology.players ( player_id uuid, username text, email text, password_hash text, registration_date timestamp with time zone, last_login timestamp with time zone, country_code text, status text, profile_data jsonb )
CREATE TABLE gaming_technology.developers ( developer_id uuid, name text, country text, founded_year integer, website text, created_at timestamp with time zone )
CREATE TABLE gaming_technology.game_sessions ( session_id uuid, player_id uuid, game_id uuid, server_id uuid, start_time timestamp with time zone, end_time timestamp with time zone, duration_seconds integer, score integer, session_data jsonb )
CREATE TABLE gaming_technology.achievements ( achievement_id uuid, game_id uuid, name text, description text, icon_url text, points integer, hidden boolean )
CREATE TABLE gaming_technology.in_game_items ( item_id uuid, game_id uuid, item_name text, item_type text, description text, rarity text, cost_currency text, cost_amount numeric, attributes jsonb )
CREATE TABLE gaming_technology.player_inventory ( inventory_id uuid, player_id uuid, item_id uuid, quantity integer, acquired_at timestamp with time zone, instance_data jsonb )


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

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

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

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

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

[Assistant] SELECT name, symbol, contract_address FROM token_metas WHERE is_erc20 = 1 LIMIT 100;

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


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

[Assistant] SELECT T1.first_name ,  T1.last_name ,  T3.first_name ,  T3.last_name FROM government_services.employees AS T1 JOIN government_services.appointments AS T2 ON T1.employee_id  =  T2.employee_id JOIN government_services.citizens AS T3 ON T2.citizen_id  =  T3.citizen_id

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens ( citizen_id text PRIMARY KEY, national_id_number text, first_name text, last_name text, date_of_birth date, gender text, primary_address text, contact_email text, contact_phone text, registration_date timestamp, is_verified boolean )
CREATE TABLE government_services.agencies ( agency_id text PRIMARY KEY, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )
CREATE TABLE government_services.services ( service_id text PRIMARY KEY, agency_id text, service_name text, description text, category text, eligibility_criteria text, standard_fee numeric, average_processing_time_days int, is_active boolean, online_application_url text )
CREATE TABLE government_services.applications ( application_id text PRIMARY KEY, citizen_id text, service_id text, submitted_at timestamp, status text, last_updated_at timestamp, assigned_employee_id text, decision_date date, notes text, reference_number text )
CREATE TABLE government_services.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text PRIMARY KEY, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees ( employee_id text PRIMARY KEY, agency_id text, first_name text, last_name text, job_title text, department text, work_email text, work_phone text, hire_date date, termination_date date, access_level text, manager_employee_id text )
CREATE TABLE government_services.appointments ( appointment_id text PRIMARY KEY, citizen_id text, employee_id text, location_id text, service_id text, scheduled_start_time timestamp, scheduled_end_time timestamp, purpose text, status text, booking_method text, created_at timestamp, notes text )
CREATE TABLE government_services.notifications ( notification_id text PRIMARY KEY, citizen_id text, application_id text, message_subject text, message_body text, channel text, sent_at timestamp, status text, related_entity_type text, related_entity_id text )


[User] List all transactions together with the event names they triggered (if any), showing transaction id, value, and event name. If a transaction does not have events, include it with a NULL event name.

[Assistant]
SELECT t.transaction_id, t.value, e.event_name
FROM web3.transactions t
LEFT JOIN web3.events e ON t.transaction_id = e.transaction_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 web3.contracts ( contract_id text, address text, abi text, bytecode text, deployer_address text, deployed_at timestamp, network_id text, status text )
CREATE TABLE web3.events ( event_id text, contract_id text, event_name text, data text, emitted_at timestamp, transaction_id text, log_index integer )
CREATE TABLE web3.transactions ( transaction_id text, from_address text, to_address text, value numeric, gas_used integer, gas_price numeric, block_number integer, timestamp timestamp, input_data text, status text, nonce integer )
CREATE TABLE web3.tokens ( token_id text, contract_address text, token_name text, token_symbol text, decimals integer, total_supply numeric )
CREATE TABLE web3.token_transfers ( transfer_id text, token_id text, from_address text, to_address text, value numeric, transaction_id text, log_index integer )
CREATE TABLE web3.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )


[User] Get a list of all distinct specialties found among the doctors.

[Assistant] SELECT DISTINCT specialty FROM healthcare.doctors;

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.doctors ( doctor_id text, first_name text, last_name text, specialty text, license_number text, phone_number text, email text, hospital_affiliation_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE healthcare.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.insurance_plans ( plan_id text, plan_name text, insurance_provider text, plan_type text, contact_phone text, website text )


[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] Show me the top 5 narratives by market cap, along with their 24-hour trading volume and 7-day price change percentage.

[Assistant] SELECT narrative.text, volume_24h.numeric, price_change_percentage_7d.numeric FROM narrative_info ORDER BY market_cap.numeric DESC LIMIT 5;

[User] Can you also include the top 3 coins for each of these narratives?

[Assistant] SELECT narrative.text, volume_24h.numeric, price_change_percentage_7d.numeric, top_3_coins.text FROM narrative_info ORDER BY market_cap.numeric 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 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 )


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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens ( citizen_id text, national_id_number text, first_name text, last_name text, date_of_birth date, gender text, primary_address text, contact_email text, contact_phone text, registration_date timestamp, is_verified boolean )


[User] 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] Count the number of policies issued in each calendar year, and show the year and the count.

[Assistant] SELECT EXTRACT(YEAR FROM issued_at), COUNT(*) FROM insurance.policies WHERE issued_at IS NOT NULL GROUP BY 1 ORDER BY 1;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.customers ( customer_id text, first_name text, last_name text, date_of_birth date, ssn_hash text, address_line1 text, address_line2 text, city text, state text, zip_code text, country text, phone_number text, email text, created_at timestamp, updated_at timestamp, status text )
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.insurance_products ( product_id text, product_name text, product_type text, description text, base_premium numeric, coverage_details text, underwriting_rules text, is_active boolean, created_at timestamp, updated_at timestamp )
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] I want a summary of each asset showing the total number of trades executed and the average trade price, including asset name and symbol.

[Assistant]
SELECT a.asset_id,
       a.name,
       a.symbol,
       COUNT(t.trade_id) AS trades_count,
       AVG(t.price) AS avg_price
FROM trading_platform.assets a
LEFT JOIN trading_platform.trades t ON a.asset_id = t.asset_id
GROUP BY a.asset_id, a.name, a.symbol;

[User] Actually, exclude trades before '2024-05-01'.

[Assistant]
SELECT a.asset_id,
       a.name,
       a.symbol,
       COUNT(t.trade_id) AS trades_count,
       AVG(t.price) AS avg_price
FROM trading_platform.assets a
LEFT JOIN trading_platform.trades t ON a.asset_id = t.asset_id
  AND t.traded_at >= '2024-05-01'
GROUP BY a.asset_id, a.name, a.symbol;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.trades ( trade_id text, order_id text, buyer_id text, seller_id text, asset_id text, quantity numeric, price numeric, traded_at timestamp )
CREATE TABLE trading_platform.assets ( asset_id text, name text, symbol text, type text )
CREATE TABLE trading_platform.utxos ( utxo_id text, transaction_id text, output_index integer, address text, amount numeric, spent boolean )
CREATE TABLE trading_platform.peers ( peer_id text, ip_address text, port integer, last_seen timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text, asset_id text, key text, value text )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id text, user_id text, status text, reviewed_at timestamp )


[User] Retrieve all room types with a base_rate above 150 for each property.

[Assistant]
SELECT property_id, type_name, base_rate
FROM hospitality_technology.room_types
WHERE base_rate > 150;

[User] Also filter to only include room types with max_occupancy >= 3.

[Assistant]
SELECT property_id, type_name, base_rate
FROM hospitality_technology.room_types
WHERE base_rate > 150
  AND max_occupancy >= 3;

[User] Finally, show guest first and last names of guests created after '2023-01-01' who could book these room types.

[Assistant]
SELECT g.first_name, g.last_name, rt.property_id, rt.type_name, rt.base_rate
FROM hospitality_technology.room_types rt
CROSS JOIN hospitality_technology.guests g
WHERE rt.base_rate > 150
  AND rt.max_occupancy >= 3
  AND g.created_at > '2023-01-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.room_types (
    room_type_id character varying(64) NOT NULL, -- unique identifier for the room type
    property_id character varying(64) NOT NULL, -- FK to properties table (type might be property-specific)
    type_name character varying(100) NOT NULL, -- e.g., Standard King, Deluxe Queen, Executive Suite
    description text, -- description of the room type
    base_rate numeric(10, 2) NOT NULL, -- standard price per night
    max_occupancy integer NOT NULL, -- maximum number of guests
    bed_type character varying(50), -- e.g., King, Queen, 2 Doubles, Twin
    area_sqft numeric(8,2), -- size of the room in square feet
    amenities text, -- comma-separated list or JSON of amenities
    PRIMARY KEY (room_type_id),
    FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id)
)
CREATE TABLE hospitality_technology.guests ( guest_id text PRIMARY KEY, first_name text, last_name text, email text, phone_number text, date_of_birth date, address_line1 text, city text, state_province text, postal_code text, country_code text, preferences text, loyalty_member_id text, communication_consent boolean, created_at timestamp, updated_at timestamp )


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

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

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


[User] List plan_id, plan_name, and contact_phone for all insurance plans whose website ends with '.org' and that have at least one other plan with the same contact_phone.

[Assistant]
SELECT a.plan_id, a.plan_name, a.contact_phone
FROM healthcare.insurance_plans a
JOIN healthcare.insurance_plans b
  ON a.contact_phone = b.contact_phone
  AND a.plan_id <> b.plan_id
WHERE a.website LIKE '%.org';

[User] Now sort by website descending and limit the results to 5 rows.

[Assistant]
SELECT a.plan_id, a.plan_name, a.contact_phone
FROM healthcare.insurance_plans a
JOIN healthcare.insurance_plans b
  ON a.contact_phone = b.contact_phone
  AND a.plan_id <> b.plan_id
WHERE a.website LIKE '%.org'
ORDER BY a.website 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 healthcare.insurance_plans ( plan_id.text, plan_name.text, insurance_provider.text, plan_type.text, contact_phone.text, website.text )


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

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

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


[User] Show me all customers (customer_id, first_name, last_name) who have made trades in the last 30 days, along with the total trade amount for each customer, sorted by total trade amount in descending order.

[Assistant] SELECT c.customer_id, c.first_name, c.last_name, SUM(t.total_amount) AS total_trade_amount FROM financial_services.customers c JOIN financial_services.accounts a ON c.customer_id = a.customer_id JOIN financial_services.trades t ON a.account_id = t.account_id WHERE t.trade_timestamp >= CURRENT_DATE - INTERVAL '30 days' GROUP BY c.customer_id, c.first_name, c.last_name ORDER BY total_trade_amount DESC;

[User] Now modify the query to only include trades executed on the 'NYSE' venue and include the trade count for each customer.

[Assistant] SELECT c.customer_id, c.first_name, c.last_name, SUM(t.total_amount) AS total_trade_amount, COUNT(t.trade_id) AS trade_count FROM financial_services.customers c JOIN financial_services.accounts a ON c.customer_id = a.customer_id JOIN financial_services.trades t ON a.account_id = t.account_id WHERE t.trade_timestamp >= CURRENT_DATE - INTERVAL '30 days' AND t.execution_venue = 'NYSE' GROUP BY c.customer_id, c.first_name, c.last_name ORDER BY total_trade_amount 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 character varying(64) NOT NULL,  -- unique identifier for the customer
    first_name character varying(100) NOT NULL, -- customer's first name
    last_name character varying(100) NOT NULL, -- customer's last name
    date_of_birth date NOT NULL, -- customer's date of birth
    ssn_hash character varying(128), -- hashed social security number (or national ID)
    address text NOT NULL, -- customer's primary address
    city character varying(100) NOT NULL,
    state character varying(50) NOT NULL,
    zip_code character varying(20) NOT NULL,
    country character varying(50) NOT NULL,
    email character varying(128) UNIQUE, -- customer's email address
    phone_number character varying(32),
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of customer record creation
    status character varying(32) NOT NULL, -- e.g., Active, Inactive, Pending Verification
    risk_profile character varying(50), -- e.g., Low, Medium, High
    PRIMARY KEY (customer_id)
)
CREATE TABLE financial_services.securities (
    security_id character varying(64) NOT NULL, -- unique identifier for the security
    ticker_symbol character varying(20) NOT NULL UNIQUE, -- stock ticker or fund symbol
    isin_code character varying(12) UNIQUE, -- International Securities Identification Number
    cusip_code character varying(9) UNIQUE, -- CUSIP number
    security_name text NOT NULL, -- full name of the security
    security_type character varying(50) NOT NULL, -- e.g., Stock, Bond, ETF, Mutual Fund, Option, Future
    exchange character varying(50), -- primary exchange where traded (e.g., NYSE, NASDAQ)
    currency character varying(3) NOT NULL, -- currency the security is denominated in
    issuer_name character varying(255), -- name of the issuing entity
    sector character varying(100), -- industry sector
    last_updated timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (security_id)
)
CREATE TABLE financial_services.trades (
    trade_id character varying(64) NOT NULL, -- unique identifier for the trade
    account_id character varying(64) NOT NULL, -- investment account executing the trade
    security_id character varying(64) NOT NULL, -- security being traded
    order_id character varying(64), -- related order ID if applicable
    trade_type character varying(10) NOT NULL, -- 'Buy' or 'Sell'
    quantity numeric(19, 8) NOT NULL, -- number of units traded
    price_per_unit numeric(19, 8) NOT NULL, -- price per unit of the security
    total_amount numeric(19, 4) NOT NULL, -- total value of the trade (quantity * price)
    commission numeric(10, 4), -- commission fee charged for the trade
    trade_timestamp timestamp NOT NULL, -- exact time the trade was executed
    settlement_date date, -- date the trade settles
    status character varying(32) NOT NULL, -- e.g., Executed, Settled, Cancelled
    execution_venue character varying(100), -- where the trade was executed
    PRIMARY KEY (trade_id),
    FOREIGN KEY (account_id) REFERENCES financial_services.accounts(account_id),
    FOREIGN KEY (security_id) REFERENCES financial_services.securities(security_id)
)
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,  -- unique identifier for the employee
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    job_title character varying(100) NOT NULL, -- e.g., Teller, Branch Manager, Financial Advisor, Analyst
    department character varying(100), -- e.g., Retail Banking, Wealth Management, IT
    branch_id character varying(64), -- Identifier for the branch they work at (if applicable)
    email character varying(128) NOT NULL UNIQUE,
    phone_extension character varying(20),
    hire_date date NOT NULL,
    termination_date date, -- Date of termination, null if currently employed
    manager_id character varying(64), -- Self-referencing key for manager relationship
    status character varying(32) NOT NULL, -- e.g., Active, Terminated, On Leave
    PRIMARY KEY (employee_id),
    FOREIGN KEY (branch_id) REFERENCES financial_services.branches(branch_id), -- Assuming a branches table exists
    FOREIGN KEY (manager_id) REFERENCES financial_services.employees(employee_id)
)