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

[Assistant]
SELECT e.first_name || ' ' || e.last_name AS full_name,
       COUNT(*) AS verified_count
FROM government_services.documents d
JOIN government_services.employees e
  ON d.verified_by_employee_id = e.employee_id
WHERE d.verification_status = 'Verified'
GROUP BY e.first_name, e.last_name
ORDER BY verified_count DESC
LIMIT 5;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens (
    citizen_id character varying(64) NOT NULL,  -- unique identifier for the citizen
    national_id_number character varying(128) NOT NULL UNIQUE, -- official national identification number
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    date_of_birth date NOT NULL,
    gender character varying(20),
    primary_address text NOT NULL, -- full primary residential address
    contact_email character varying(128) UNIQUE,
    contact_phone character varying(32),
    registration_date timestamp NOT NULL, -- when the citizen profile was created
    is_verified boolean DEFAULT false, -- whether identity has been officially verified
    PRIMARY KEY (citizen_id)
)
CREATE TABLE government_services.agencies ( agency_id text, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )
CREATE TABLE government_services.applications ( application_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, service_id character varying(64) NOT NULL, submitted_at timestamp NOT NULL, status character varying(50) NOT NULL, last_updated_at timestamp NOT NULL, assigned_employee_id character varying(64), decision_date date, notes text, reference_number character varying(100) UNIQUE, PRIMARY KEY (application_id) )
CREATE TABLE government_services.documents ( document_id text, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees ( employee_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, job_title character varying(150) NOT NULL, department character varying(100), work_email character varying(128) NOT NULL UNIQUE, work_phone character varying(32), hire_date date NOT NULL, termination_date date, access_level character varying(50), manager_employee_id character varying(64), PRIMARY KEY (employee_id) )
CREATE TABLE government_services.service_locations (
    location_id character varying(64) NOT NULL, -- unique identifier for the physical location
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    location_name character varying(200), -- e.g., Downtown DMV Office
    address text NOT NULL,
    city character varying(100),
    state character varying(50),
    postal_code character varying(20),
    latitude numeric(9, 6),
    longitude numeric(9, 6),
    operating_hours text, -- description of opening times
    contact_phone character varying(32),
    is_accessible boolean, -- accessibility information (e.g., wheelchair access)
    PRIMARY KEY (location_id)
)
CREATE TABLE government_services.notifications ( notification_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, application_id character varying(64), message_subject character varying(255), message_body text NOT NULL, channel character varying(30) NOT NULL, sent_at timestamp NOT NULL, status character varying(30) NOT NULL, related_entity_type character varying(50), related_entity_id character varying(64), PRIMARY KEY (notification_id) )


[User] I want to see the total sum of transaction amounts and their average amount for each transaction_type along with the total number of transactions, grouped by currency.

[Assistant] SELECT transaction_type, currency, COUNT(*) AS total_transactions, SUM(amount) AS total_amount, AVG(amount) AS average_amount FROM financial_services.transactions GROUP BY transaction_type, currency;

[User] Can you filter out transactions where the status is not 'SUCCESSFUL' or 'PENDING'?

[Assistant] SELECT transaction_type, currency, COUNT(*) AS total_transactions, SUM(amount) AS total_amount, AVG(amount) AS average_amount FROM financial_services.transactions WHERE status IN ('SUCCESSFUL', 'PENDING') GROUP BY transaction_type, currency;

[User] Also, show only the results where the total_amount is greater than 10000.

[Assistant] SELECT transaction_type, currency, COUNT(*) AS total_transactions, SUM(amount) AS total_amount, AVG(amount) AS average_amount FROM financial_services.transactions WHERE status IN ('SUCCESSFUL', 'PENDING') GROUP BY transaction_type, currency HAVING SUM(amount) > 10000;

[User] Sort the results by average_amount in ascending order.

[Assistant] SELECT transaction_type, currency, COUNT(*) AS total_transactions, SUM(amount) AS total_amount, AVG(amount) AS average_amount FROM financial_services.transactions WHERE status IN ('SUCCESSFUL', 'PENDING') GROUP BY transaction_type, currency HAVING SUM(amount) > 10000 ORDER BY average_amount ASC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE financial_services.transactions ( transaction_id text, account_id text, related_account_id text, transaction_type text, amount numeric, currency text, transaction_date timestamp, effective_date date, description text, status text, reference_number text )


[User] 能否帮我查询特定列车行程(schedule_id 为 'sched_001')的详细信息，包括列车出发和到达时间，以及该行程所属路线的ID和相关乘客信息？

[Assistant]
SELECT s.schedule_id, s.train_id, s.route_id, s.departure_datetime, s.arrival_datetime, s.status, p.passenger_id, p.first_name, p.last_name, p.email
FROM schedules s
LEFT JOIN passengers p ON s.schedule_id = (SELECT schedule_id FROM bookings WHERE passenger_id = p.passenger_id)
WHERE s.schedule_id = 'sched_001';

[User] 能否将结果限制在状态为‘Scheduled’的行程上，并且只显示乘客的姓名和电子邮件？

[Assistant]
SELECT s.schedule_id, s.train_id, s.route_id, s.departure_datetime, s.arrival_datetime, s.status, p.passenger_id, p.first_name, p.last_name, p.email
FROM schedules s
LEFT JOIN passengers p ON s.schedule_id = (SELECT schedule_id FROM bookings WHERE passenger_id = p.passenger_id)
WHERE s.schedule_id = 'sched_001' AND s.status = 'Scheduled';

[User] 能否再加入行程的备注信息，并按出发时间降序排列？

[Assistant]
SELECT s.schedule_id, s.train_id, s.route_id, s.departure_datetime, s.arrival_datetime, s.status, s.notes, p.passenger_id, p.first_name, p.last_name, p.email
FROM schedules s
LEFT JOIN passengers p ON s.schedule_id = (SELECT schedule_id FROM bookings WHERE passenger_id = p.passenger_id)
WHERE s.schedule_id = 'sched_001' AND s.status = 'Scheduled'
ORDER BY s.departure_datetime DESC;

[User] 如果没有关联的乘客信息，能否只显示行程信息？

[Assistant]
SELECT s.schedule_id, s.train_id, s.route_id, s.departure_datetime, s.arrival_datetime, s.status, s.notes, p.passenger_id, p.first_name, p.last_name, p.email
FROM schedules s
LEFT JOIN passengers p ON s.schedule_id = (SELECT schedule_id FROM bookings WHERE passenger_id = p.passenger_id)
WHERE s.schedule_id = 'sched_001' AND s.status = 'Scheduled'
ORDER BY s.departure_datetime 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 /schedules
{
  "mappings": {
    "properties": {
      "schedule_id": { "type": "keyword" },
      "train_id": { "type": "keyword" }, // References trains index
      "route_id": { "type": "keyword" }, // References routes index
      "departure_datetime": { "type": "date" }, // ISO 8601 format recommended
      "arrival_datetime": { "type": "date" },
      "status": { "type": "keyword" },
      "notes": { "type": "text" }
    }
  }
}
// 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" }
    }
  }
}


[User] Show me all users who have placed orders but have no trades, along with their order count and average order quantity.

[Assistant] SELECT u.user_id, u.email, COUNT(o.order_id) AS order_count, AVG(o.quantity) AS avg_order_quantity FROM trading_platform.users u JOIN trading_platform.orders o ON u.user_id = o.user_id LEFT JOIN trading_platform.trades t ON o.order_id = t.order_id WHERE t.trade_id IS NULL GROUP BY u.user_id, u.email

[User] Now modify the query to only include users who have placed more than 3 orders and show their earliest order date.

[Assistant] SELECT u.user_id, u.email, COUNT(o.order_id) AS order_count, AVG(o.quantity) AS avg_order_quantity, MIN(o.created_at) AS earliest_order_date FROM trading_platform.users u JOIN trading_platform.orders o ON u.user_id = o.user_id LEFT JOIN trading_platform.trades t ON o.order_id = t.order_id WHERE t.trade_id IS NULL GROUP BY u.user_id, u.email HAVING COUNT(o.order_id) > 3

[User] Actually, I want to see these results grouped by order_type as well, and only for buy orders.

[Assistant] SELECT u.user_id, u.email, o.order_type, COUNT(o.order_id) AS order_count, AVG(o.quantity) AS avg_order_quantity, MIN(o.created_at) AS earliest_order_date FROM trading_platform.users u JOIN trading_platform.orders o ON u.user_id = o.user_id LEFT JOIN trading_platform.trades t ON o.order_id = t.order_id WHERE t.trade_id IS NULL AND o.order_type = 'buy' GROUP BY u.user_id, u.email, o.order_type HAVING COUNT(o.order_id) > 3

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, created_at timestamp )
CREATE TABLE trading_platform.wallets ( wallet_id text PRIMARY KEY, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.orders ( order_id text PRIMARY KEY, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades ( trade_id text PRIMARY KEY, order_id text, buyer_id text, seller_id text, asset_id text, quantity numeric, price numeric, traded_at timestamp )
CREATE TABLE trading_platform.peers ( peer_id text PRIMARY KEY, ip_address text, port int, last_seen timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text PRIMARY KEY, asset_id text, key text, value text )
CREATE TABLE trading_platform.logs ( log_id text PRIMARY KEY, user_id text, action text, details text, logged_at timestamp )
CREATE TABLE trading_platform.notifications ( notification_id text PRIMARY KEY, user_id text, message text, sent_at timestamp, read_at timestamp )


[User] What is the total sum of all amounts for all UTXOs in the system, regardless of whether they are spent or unspent?

[Assistant] SELECT SUM(amount) FROM trading_platform.utxos

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, created_at timestamp )
CREATE TABLE trading_platform.wallets (
    wallet_id character varying(64) NOT NULL,  -- unique identifier for the wallet
    user_id character varying(64) NOT NULL, -- identifier of the user owning the wallet
    address character varying(128) NOT NULL, -- address of the wallet
    private_key text NOT NULL, -- private key of the wallet
    created_at timestamp NOT NULL, -- time when the wallet was created
    PRIMARY KEY (wallet_id)
)
CREATE TABLE trading_platform.orders ( order_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, wallet_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, order_type character varying(32) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, status character varying(32) NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (order_id) )
CREATE TABLE trading_platform.trades ( trade_id text PRIMARY KEY, 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 character varying(64) NOT NULL,  -- unique identifier for the asset
    name character varying(128) NOT NULL, -- name of the asset
    symbol character varying(32) NOT NULL, -- symbol of the asset
    type character varying(32) NOT NULL, -- type of the asset (e.g., cryptocurrency, stock)
    PRIMARY KEY (asset_id)
)
CREATE TABLE trading_platform.utxos (
    utxo_id character varying(64) NOT NULL,  -- unique identifier for the UTXO
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that created the UTXO
    output_index integer NOT NULL, -- index of the output in the transaction
    address character varying(128) NOT NULL, -- address that can spend the UTXO
    amount numeric(38,14) NOT NULL, -- amount of the asset in the UTXO
    spent boolean NOT NULL, -- whether the UTXO has been spent
    PRIMARY KEY (utxo_id)
)
CREATE TABLE trading_platform.dapps ( dapp_id.text, name.text, description.text, url.text )
CREATE TABLE trading_platform.metadata (
    metadata_id character varying(64) NOT NULL,  -- unique identifier for the metadata
    asset_id character varying(64) NOT NULL, -- identifier of the asset the metadata is associated with
    key character varying(128) NOT NULL, -- key of the metadata
    value text NOT NULL, -- value of the metadata
    PRIMARY KEY (metadata_id)
)
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id.text, user_id.text, status.text, reviewed_at.timestamp )
CREATE TABLE trading_platform.logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the log entry
    user_id character varying(64), -- identifier of the user associated with the log entry
    action character varying(128) NOT NULL, -- action performed
    details text NOT NULL, -- details of the action
    logged_at timestamp NOT NULL, -- time when the log entry was created
    PRIMARY KEY (log_id)
)
CREATE TABLE trading_platform.notifications ( notification_id.text, user_id.text, message.text, sent_at.timestamp, read_at.timestamp )


[User] I need to check the inventory status of components, including their batch details and warehouse location.

[Assistant]
MATCH (i:InventoryBatch)-[:IS_INSTANCE_OF]->(c:Component)
RETURN c.component_id, c.component_name, i.inventory_record_id, i.quantity, i.location_warehouse, i.location_bin, i.received_date, i.batch_number

[User] Can you filter this to show only batches with a quantity less than 50?

[Assistant]
MATCH (i:InventoryBatch)-[:IS_INSTANCE_OF]->(c:Component)
WHERE i.quantity < 50
RETURN c.component_id, c.component_name, i.inventory_record_id, i.quantity, i.location_warehouse, i.location_bin, i.received_date, i.batch_number

[User] What if I want to exclude batches with an expiry date before 2024?

[Assistant]
MATCH (i:InventoryBatch)-[:IS_INSTANCE_OF]->(c:Component)
WHERE i.quantity < 50 AND i.expiry_date >= date('2024-01-01')
RETURN c.component_id, c.component_name, i.inventory_record_id, i.quantity, i.location_warehouse, i.location_bin, i.received_date, i.batch_number

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

[Assistant]
MATCH (i:InventoryBatch)-[:IS_INSTANCE_OF]->(c:Component)
WHERE i.quantity < 50 AND i.expiry_date >= date('2024-01-01')
RETURN c.component_id, c.component_name, i.inventory_record_id, i.quantity, i.location_warehouse, i.location_bin, i.received_date, i.batch_number
ORDER BY i.received_date 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
Node Label ':Component'. Properties: { component_id: String (Constraint: UNIQUE), part_number: String (Constraint: UNIQUE), component_name: String, description: String, weight_kg: Float, cost_usd: Float, criticality_level: String }. Relationships: (:Component)-[:MADE_OF]->(:Material {material_id}), (:Component)-[:SUPPLIED_BY]->(:Supplier {supplier_id}). Index on component_id, part_number.
Node Label ':Supplier'. Properties: { supplier_id: String (Constraint: UNIQUE), supplier_name: String, address: String, country: String, contact_person: String, contact_email: String, quality_rating: Float, certified_date: Date }. Index on supplier_id.
Node Label ':Material'. Properties: { material_id: String (Constraint: UNIQUE), material_name: String, specification: String, description: String, density_kg_m3: Float, tensile_strength_mpa: Integer }. Index on material_id.
Node Label ':AssemblyLine'. Properties: { line_id: String (Constraint: UNIQUE), line_name: String, location_building: String, location_area: String, capacity_units_per_month: Integer, status: String }. Relationship: (:AssemblyLine)-[:BUILDS_MODEL]->(:AircraftModel {model_id}). Index on line_id.
Node Label ':AssemblyStep'. Properties: { step_id: String (Constraint: UNIQUE), step_number: Integer, step_name: String, description: String, standard_duration_hours: Float, required_skill_level: String, workstation: String }. Relationship: (:AssemblyLine {line_id})-[:HAS_STEP {sequence: <step_number>}]->(:AssemblyStep). Index on step_id.
Node Label ':AircraftBuild'. Properties: { build_id: String (Constraint: UNIQUE), serial_number: String (Constraint: UNIQUE), build_start_date: Datetime, estimated_completion_date: Date, actual_completion_date: Datetime, current_status: String, customer_order_id: String }. Relationships: (:AircraftBuild)-[:IS_MODEL]->(:AircraftModel {model_id}), (:AircraftBuild)-[:ASSEMBLED_ON]->(:AssemblyLine {line_id}). Index on build_id, serial_number, current_status.
Node Label ':Inspection'. Properties: { inspection_id: String (Constraint: UNIQUE), inspection_type: String, inspection_timestamp: Datetime, result: String, remarks: String }. Relationships: (:AircraftBuild {build_id})-[:UNDERWENT]->(:Inspection), (:Inspection)-[:PERFORMED_BY]->(:Employee {employee_id}), (:Inspection)-[:INSPECTED_COMPONENT]->(:Component {component_id}) (optional), (:Inspection)-[:FOLLOWED_STEP]->(:AssemblyStep {step_id}) (optional). Index on inspection_id.
Node Label ':Employee'. Properties: { employee_id: String (Constraint: UNIQUE), first_name: String, last_name: String, job_title: String, skill_certifications: String[], hire_date: Date, employment_status: String }. Relationships: (:Employee)-[:ASSIGNED_TO]->(:AssemblyLine {line_id}), (:Employee)-[:REPORTS_TO]->(:Employee {employee_id as supervisor_id}). Index on employee_id.
Node Label ':InventoryBatch'. Properties: { inventory_record_id: String (Constraint: UNIQUE), quantity: Integer, location_warehouse: String, location_bin: String, received_date: Datetime, expiry_date: Date, batch_number: String, last_updated: Datetime }. Relationship: (:InventoryBatch)-[:IS_INSTANCE_OF]->(:Component {component_id}). Index on inventory_record_id, component_id.


[User] List the medication_name and manufacturer for all medications where the description is null or an empty string.

[Assistant] SELECT medication_name, manufacturer FROM healthcare.medications WHERE description IS NULL OR description = '';

[User] Now, refine the query to only include medications whose ndc_code starts with '5'.

[Assistant] SELECT medication_name, manufacturer FROM healthcare.medications WHERE (description IS NULL OR description = '') AND ndc_code LIKE '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.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.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.medications (
    medication_id character varying(64) NOT NULL, -- unique identifier for the medication type
    medication_name character varying(255) NOT NULL, -- common or brand name
    generic_name character varying(255), -- generic chemical name
    manufacturer character varying(100), -- drug manufacturer
    ndc_code character varying(20) UNIQUE, -- National Drug Code (optional but useful)
    description text, -- description of the medication
    PRIMARY KEY (medication_id)
)
CREATE TABLE healthcare.prescriptions (
    prescription_id character varying(64) NOT NULL, -- unique identifier for the prescription
    record_id character varying(64) NOT NULL, -- FK linking to the medical record where it was prescribed
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to prescribing doctor
    medication_id character varying(64) NOT NULL, -- FK to medications table
    dosage character varying(100) NOT NULL, -- e.g., '100mg', '1 tablet'
    frequency character varying(100) NOT NULL, -- e.g., 'Once daily', 'Twice a day with meals'
    route character varying(50), -- e.g., 'Oral', 'Topical', 'Intravenous'
    start_date date NOT NULL, -- date prescription begins
    end_date date, -- date prescription ends (if applicable)
    quantity_dispensed numeric(10,2), -- amount dispensed (e.g., number of tablets)
    refills_allowed integer NOT NULL DEFAULT 0, -- number of allowed refills
    prescription_date timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (prescription_id)
)
CREATE TABLE healthcare.insurance_plans (
    plan_id character varying(64) NOT NULL, -- unique identifier for the insurance plan
    plan_name character varying(200) NOT NULL, -- name of the insurance plan
    insurance_provider character varying(100) NOT NULL, -- name of the insurance company
    plan_type character varying(50), -- e.g., PPO, HMO, EPO
    contact_phone character varying(20), -- provider contact number
    website character varying(255), -- provider website
    PRIMARY KEY (plan_id)
)
CREATE TABLE healthcare.patient_insurance (
    patient_insurance_id character varying(64) NOT NULL, -- unique identifier for this patient-plan link
    patient_id character varying(64) NOT NULL, -- FK to patients table
    plan_id character varying(64) NOT NULL, -- FK to insurance_plans table
    policy_number character varying(100) NOT NULL, -- patient's policy number
    group_number character varying(100), -- group number, if applicable
    subscriber_name character varying(200), -- name of the primary policy holder
    effective_date date NOT NULL, -- date the coverage begins
    expiration_date date, -- date the coverage ends (if known)
    is_primary boolean NOT NULL DEFAULT true, -- indicates if this is the primary insurance
    PRIMARY KEY (patient_insurance_id),
    UNIQUE (patient_id, plan_id, policy_number) -- ensure a patient doesn't have the same policy twice
)


[User] List all agents who have been terminated, showing their full name, agency name, and termination date.

[Assistant]
SELECT first_name, last_name, agency_name, termination_date
FROM insurance.agents
WHERE status <> 'Active';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.agents ( agent_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, agency_name character varying(150), license_number character varying(100) NOT NULL UNIQUE, license_state character varying(50) NOT NULL, contact_email character varying(128) UNIQUE, contact_phone character varying(30), hire_date date, termination_date date, status character varying(20) NOT NULL DEFAULT 'Active', commission_rate numeric(5, 4) NOT NULL DEFAULT 0.05, manager_id character varying(64), PRIMARY KEY (agent_id) )


[User] List all servers, showing their name, region, and current number of players.

[Assistant] SELECT server_name, region, current_players FROM gaming_technology.servers;

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

[Assistant] SELECT server_name, region, current_players FROM gaming_technology.servers WHERE status IN ('online', 'idle');

[User] For these servers, show the average number of current players across the servers in each region.

[Assistant] SELECT region, avg(current_players) FROM gaming_technology.servers WHERE status IN ('online', 'idle') GROUP BY region;

[User] Only show regions where the average number of players is greater than 50.

[Assistant] SELECT region, avg(current_players) FROM gaming_technology.servers WHERE status IN ('online', 'idle') GROUP BY region HAVING avg(current_players) > 50;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE gaming_technology.players ( player_id uuid PRIMARY KEY, username text, email text, password_hash text, registration_date timestamptz, last_login timestamptz, country_code text, status text, profile_data jsonb )
CREATE TABLE gaming_technology.games ( game_id.uuid, title.text, developer_id.uuid, publisher_id.uuid, genre.text, release_date.date, description.text, platform.text, engine.text, website.text )
CREATE TABLE gaming_technology.developers ( developer_id uuid PRIMARY KEY, name text, country text, founded_year int, website text, created_at timestamptz )
CREATE TABLE gaming_technology.game_sessions ( session_id uuid PRIMARY KEY, player_id uuid, game_id uuid, server_id uuid, start_time timestamptz, end_time timestamptz, duration_seconds int, score int, session_data jsonb )
CREATE TABLE gaming_technology.servers ( server_id.uuid, game_id.uuid, server_name.text, region.text, ip_address.text, port.integer, current_players.integer, max_players.integer, status.text, last_heartbeat.timestamptz )
CREATE TABLE gaming_technology.player_achievements ( player_achievement_id.uuid, player_id.uuid, achievement_id.uuid, unlocked_at.timestamptz )
CREATE TABLE gaming_technology.in_game_items ( item_id uuid PRIMARY KEY, 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 NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for an inventory entry
    player_id uuid NOT NULL, -- FK linking to the player owning the item
    item_id uuid NOT NULL, -- FK linking to the item definition
    quantity integer NOT NULL DEFAULT 1, -- number of items held (for stackable items)
    acquired_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the item was acquired
    instance_data jsonb, -- data specific to this instance (e.g., weapon mods, durability)
    PRIMARY KEY (inventory_id),
    -- Optional unique constraint if items are non-stackable or unique instances
    -- UNIQUE (player_id, item_id) -- Use if quantity is always 1
    -- FOREIGN KEY (player_id) REFERENCES gaming_technology.players(player_id),
    -- FOREIGN KEY (item_id) REFERENCES gaming_technology.in_game_items(item_id)
)


[User] Compute the total invoiced amount and average payment delay (in days) by status for invoices issued between 2024-01-01 and 2024-06-30.

[Assistant]
SELECT status,
       SUM(total_amount) AS total_invoiced,
       AVG(EXTRACT(day FROM (payment_date::date - issue_date))) AS avg_payment_delay_days
  FROM legal_services.invoices
 WHERE issue_date BETWEEN '2024-01-01' AND '2024-06-30'
 GROUP BY status;

[User] Also show the count of invoices per status.

[Assistant]
SELECT status,
       SUM(total_amount) AS total_invoiced,
       AVG(EXTRACT(day FROM (payment_date::date - issue_date))) AS avg_payment_delay_days,
       COUNT(*) AS invoice_count
  FROM legal_services.invoices
 WHERE issue_date BETWEEN '2024-01-01' AND '2024-06-30'
 GROUP BY status;

[User] Exclude statuses where total_invoiced is less than 10000.

[Assistant]
SELECT status,
       SUM(total_amount) AS total_invoiced,
       AVG(EXTRACT(day FROM (payment_date::date - issue_date))) AS avg_payment_delay_days,
       COUNT(*) AS invoice_count
  FROM legal_services.invoices
 WHERE issue_date BETWEEN '2024-01-01' AND '2024-06-30'
 GROUP BY status
HAVING SUM(total_amount) >= 10000;

[User] Finally, order the results by avg_payment_delay_days ascending.

[Assistant]
SELECT status,
       SUM(total_amount) AS total_invoiced,
       AVG(EXTRACT(day FROM (payment_date::date - issue_date))) AS avg_payment_delay_days,
       COUNT(*) AS invoice_count
  FROM legal_services.invoices
 WHERE issue_date BETWEEN '2024-01-01' AND '2024-06-30'
 GROUP BY status
HAVING SUM(total_amount) >= 10000
 ORDER BY avg_payment_delay_days ASC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.invoices ( invoice_id text PRIMARY KEY, invoice_number text UNIQUE, client_id text, case_id text, issue_date date, due_date date, total_amount numeric, amount_paid numeric, status text, payment_date timestamp, notes text, created_at timestamp )


[User] Show the total number of customers in each state.

[Assistant]
SELECT
  state,
  COUNT(customer_id)
FROM insurance.customers
GROUP BY
  state;

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.claims (
    claim_id character varying(64) NOT NULL, -- unique identifier for the claim
    policy_id character varying(64) NOT NULL, -- identifier of the policy under which the claim is made (FK to policies)
    customer_id character varying(64) NOT NULL, -- identifier of the customer making the claim (FK to customers)
    incident_date timestamp NOT NULL, -- date and time of the incident leading to the claim
    reported_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- date the claim was reported
    description text NOT NULL, -- detailed description of the incident and claim
    estimated_loss numeric(15, 2), -- initial estimated cost of the loss
    status character varying(30) NOT NULL, -- e.g., Filed, Processing, Under Review, Approved, Denied, Settled
    settlement_amount numeric(15, 2), -- final amount paid out
    settlement_date date,
    claim_handler_id character varying(64), -- identifier for the employee handling the claim (FK to employees/adjusters)
    police_report_number character varying(100),
    PRIMARY KEY (claim_id)
)
CREATE TABLE insurance.insurance_products (
    product_id character varying(64) NOT NULL, -- unique identifier for the insurance product
    product_name character varying(150) NOT NULL, -- name of the insurance product (e.g., 'Comprehensive Auto Insurance')
    product_type character varying(50) NOT NULL, -- category like 'Auto', 'Home', 'Life', 'Health', 'Travel'
    description text, -- detailed description of the product
    base_premium numeric(10, 2) NOT NULL, -- starting premium before adjustments
    coverage_details text, -- details about what is covered (could be JSON or structured text)
    underwriting_rules text, -- rules used for assessing risk and eligibility
    is_active boolean NOT NULL DEFAULT true, -- whether the product is currently offered
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    updated_at timestamp,
    PRIMARY KEY (product_id)
)
CREATE TABLE insurance.claim_documents ( document_id character varying(64) NOT NULL, claim_id character varying(64) NOT NULL, document_type character varying(50) NOT NULL, file_name character varying(255) NOT NULL, file_path character varying(512) NOT NULL, file_size_bytes integer, mime_type character varying(100), uploaded_by character varying(64), uploaded_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, description text, PRIMARY KEY (document_id) )


[User] Show me the top 5 users by the total number of trades they participated in as buyers, along with their wallet addresses.

[Assistant] SELECT u.user_id, u.username, w.address, COUNT(t.trade_id) AS trade_count FROM trading_platform.users u JOIN trading_platform.trades t ON u.user_id = t.buyer_id JOIN trading_platform.wallets w ON u.user_id = w.user_id GROUP BY u.user_id, w.address ORDER BY trade_count DESC LIMIT 5;

[User] Now modify the query to only include trades that happened in the last 30 days.

[Assistant] SELECT u.user_id, u.username, w.address, COUNT(t.trade_id) AS trade_count FROM trading_platform.users u JOIN trading_platform.trades t ON u.user_id = t.buyer_id JOIN trading_platform.wallets w ON u.user_id = w.user_id WHERE t.traded_at >= NOW() - INTERVAL '30 days' GROUP BY u.user_id, w.address ORDER BY trade_count DESC LIMIT 5;

[User] Actually, I want to see the total trade volume (quantity * price) for each of these users instead of just the count.

[Assistant] SELECT u.user_id, u.username, w.address, SUM(t.quantity * t.price) AS total_volume FROM trading_platform.users u JOIN trading_platform.trades t ON u.user_id = t.buyer_id JOIN trading_platform.wallets w ON u.user_id = w.user_id WHERE t.traded_at >= NOW() - INTERVAL '30 days' GROUP BY u.user_id, w.address ORDER BY total_volume DESC LIMIT 5;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(128) NOT NULL, -- username of the user
    email character varying(128) NOT NULL, -- email address of the user
    password_hash text NOT NULL, -- hashed password of the user
    created_at timestamp NOT NULL, -- time when the user account was created
    PRIMARY KEY (user_id)
)
CREATE TABLE trading_platform.wallets (
    wallet_id character varying(64) NOT NULL,  -- unique identifier for the wallet
    user_id character varying(64) NOT NULL, -- identifier of the user owning the wallet
    address character varying(128) NOT NULL, -- address of the wallet
    private_key text NOT NULL, -- private key of the wallet
    created_at timestamp NOT NULL, -- time when the wallet was created
    PRIMARY KEY (wallet_id)
)
CREATE TABLE trading_platform.orders (
    order_id character varying(64) NOT NULL,  -- unique identifier for the order
    user_id character varying(64) NOT NULL, -- identifier of the user placing the order
    wallet_id character varying(64) NOT NULL, -- identifier of the wallet used for the order
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    order_type character varying(32) NOT NULL, -- type of the order (e.g., buy, sell)
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the order
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    status character varying(32) NOT NULL, -- status of the order (e.g., open, filled, canceled)
    created_at timestamp NOT NULL, -- time when the order was created
    PRIMARY KEY (order_id)
)
CREATE TABLE trading_platform.trades (
    trade_id character varying(64) NOT NULL,  -- unique identifier for the trade
    order_id character varying(64) NOT NULL, -- identifier of the order that led to the trade
    buyer_id character varying(64) NOT NULL, -- identifier of the buyer
    seller_id character varying(64) NOT NULL, -- identifier of the seller
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the trade
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    traded_at timestamp NOT NULL, -- time when the trade was executed
    PRIMARY KEY (trade_id)
)
CREATE TABLE trading_platform.assets (
    asset_id character varying(64) NOT NULL,  -- unique identifier for the asset
    name character varying(128) NOT NULL, -- name of the asset
    symbol character varying(32) NOT NULL, -- symbol of the asset
    type character varying(32) NOT NULL, -- type of the asset (e.g., cryptocurrency, stock)
    PRIMARY KEY (asset_id)
)
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
CREATE TABLE trading_platform.peers (
    peer_id character varying(64) NOT NULL,  -- unique identifier for the peer
    ip_address character varying(15) NOT NULL, -- IP address of the peer
    port integer NOT NULL, -- port number of the peer
    last_seen timestamp NOT NULL, -- last time the peer was active
    PRIMARY KEY (peer_id)
)
CREATE TABLE trading_platform.metadata (
    metadata_id character varying(64) NOT NULL,  -- unique identifier for the metadata
    asset_id character varying(64) NOT NULL, -- identifier of the asset the metadata is associated with
    key character varying(128) NOT NULL, -- key of the metadata
    value text NOT NULL, -- value of the metadata
    PRIMARY KEY (metadata_id)
)
CREATE TABLE trading_platform.kyc_audit (
    kyc_audit_id character varying(64) NOT NULL,  -- unique identifier for the KYC audit
    user_id character varying(64) NOT NULL, -- identifier of the user being audited
    status character varying(32) NOT NULL, -- status of the KYC audit (e.g., pending, approved, rejected)
    reviewed_at timestamp NOT NULL, -- time when the KYC audit was reviewed
    PRIMARY KEY (kyc_audit_id)
)
CREATE TABLE trading_platform.logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the log entry
    user_id character varying(64), -- identifier of the user associated with the log entry
    action character varying(128) NOT NULL, -- action performed
    details text NOT NULL, -- details of the action
    logged_at timestamp NOT NULL, -- time when the log entry was created
    PRIMARY KEY (log_id)
)


[User] List each group conversation with its group name and the number of verified users who have posted in it.

[Assistant]
SELECT c.conversation_id, c.group_name, COUNT(DISTINCT u.user_id) AS verified_posters
FROM social_media.conversations c
JOIN social_media.posts p ON p.location_lat IS NOT NULL -- Simulate posts linked to conversation (since no mapping, using location as a proxy)
JOIN social_media.users u ON p.user_id = u.user_id AND u.is_verified = true
WHERE c.is_group_chat = true
GROUP BY c.conversation_id, c.group_name;

[User] Actually, only show groups created after May 1, 2024.

[Assistant]
SELECT c.conversation_id, c.group_name, COUNT(DISTINCT u.user_id) AS verified_posters
FROM social_media.conversations c
JOIN social_media.posts p ON p.location_lat IS NOT NULL -- Simulate posts linked to conversation (since no mapping, using location as a proxy)
JOIN social_media.users u ON p.user_id = u.user_id AND u.is_verified = true
WHERE c.is_group_chat = true AND c.created_at > '2024-05-01'
GROUP BY c.conversation_id, c.group_name;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users ( user_id text, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified boolean )
CREATE TABLE social_media.posts ( post_id text, user_id text, content text, media_url text, media_type text, created_at timestamp, updated_at timestamp, visibility text, location_lat numeric, location_lon numeric )
CREATE TABLE social_media.hashtags ( hashtag_id text PRIMARY KEY, tag_name text, created_at timestamp )
CREATE TABLE social_media.conversations ( conversation_id.text, created_at.timestamp, last_message_at.timestamp, is_group_chat.boolean, group_name.text )
CREATE TABLE social_media.user_settings ( setting_id text PRIMARY KEY, user_id text, theme text, email_notifications_enabled bool, push_notifications_enabled bool, private_profile bool, updated_at timestamp )


[User] Retrieve the policy_number, start_date, end_date, premium_amount, and corresponding product_name for policies with a coverage_limit greater than 500000.

[Assistant]
SELECT p.policy_number, p.start_date, p.end_date, p.premium_amount, ip.product_name
FROM insurance.policies p
JOIN insurance.insurance_products ip ON p.product_id = ip.product_id
WHERE p.coverage_limit > 500000;

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


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

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

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

[Assistant] SELECT pfr.project_name, pfr.valuation, tbi.token_symbol, tbi.price, tbi.total_volume FROM project_fundraising_record pfr LEFT JOIN token_basic_info tbi ON pfr.project_name = tbi.token_name WHERE pfr.investment_date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) AND pfr.valuation > 100000000 ORDER BY pfr.valuation DESC LIMIT 5;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
 "CREATE TABLE project_fundraising_record (",
    "id character varying(32) NOT NULL,  -- fundraising record id",
    "project_id character varying(32) NOT NULL, -- the invested project's id",
    "project_name character varying(128) NOT NULL, -- name of the invested project",
    "rounds_name character varying(32), -- name of the fundraising round",
    "investment_value numeric(38,14), -- amount of the fundraising in USD",
    "investment_date character varying(128), -- the date of the investment happened",
    "introduction character varying(128), -- the introduction of the invested project",
    "valuation numeric(38,14), -- the valuation of the project in USD when invested",

CREATE TABLE token_basic_info ( coin_id character varying(100) NOT NULL, -- the id of the token token_name character varying(100) NOT NULL, -- the token's name token_symbol character varying(100) NOT NULL, -- the token's symbol token_address character varying(100) NOT NULL, -- the token's address chain text, -- the chain that the token resides price double precision, -- the current price of the token price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days highest_price_24h double precision, -- the highest price of the token in 24 hours lowest_price_24h double precision,  -- the lowest price of the token in 24 hours market_cap double precision, -- the market cap of the token market_cap_rank bigint, -- the rank of the token market cap in desc market_cap_change_percentage_24h text, -- the percentage of market cap changes in 24 hours total_volume text, -- the trade volum of the token both in decentralized exchange(DEX) and centralized exchange(CEX) narrative text, -- the category or narrative of the token trend_rank biging, -- the trending rank of the token, value 1 expresses the most popular token. ,PRIMARY KEY (coin_id, chain) )
CREATE TABLE narrative_info ( narrative character varying(512) NOT NULL, -- the id of narrative top_3_coins text, -- the top 3 tokens in the narrative price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour in the narrative price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours in the narrative price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days in the narrative market_cap double precision, -- the market cap of the narrative volume_24h double precision, -- the trade volume of the narrative trend_rank bigint, -- the trending rank of the narrative, value 1 expresses the most popular narrative token_num bigint, -- total token number in the narrative ,PRIMARY KEY (narrative) )
CREATE TABLE token_dexpool_info ( pair_address character varying(512) NOT NULL, token_name character varying(100) NOT NULL, token_symbol character varying(100) NOT NULL, chain text, price double precision, price_change_percentage_1h double precision, price_change_percentage_6h double precision, price_change_percentage_24h double precision, makers_24h double precision, volume_24h double precision, liquidity double precision, market_cap double precision, trend_rank bigint )
CREATE TABLE smart_money_profit ( address character varying(100) NOT NULL, rank INT, profit numeric(38,6), roi numeric(38,2), realized_ratio numeric(38,2), most_profit_token character varying(100), last_trade_time character varying(100), chain character varying(100) )
  "CREATE TABLE smart_money_token_performance (",
    "token_address character varying(100) NOT NULL, -- the token's address",
    "token_symbol character varying(100), -- the tokens's symbol",
    "pnl numeric(38,2), -- the profit users made on this token",
    "net_flow numeric(38,2), -- the netflow of the token, means the money user spent minus the the money user sold of this token",
    "avg_cost numeric(38,16), -- the average cost price of user spent on this token",
    "price double precision, -- the current price of the token",
    "realized_ratio numeric(10,2), -- the ratio user sold of the token",
    "roi numeric(10,2), -- the roi users made of this token",
    "chain character varying(100), -- the chain that the token resides",
    "PRIMARY KEY (token_address, chain));",

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


[User] Return the number of top-level comments and the number of replies in the comments table.

[Assistant]
SELECT
  SUM(CASE WHEN parent_comment_id IS NULL THEN 1 ELSE 0 END) AS top_level_comments,
  SUM(CASE WHEN parent_comment_id IS NOT NULL THEN 1 ELSE 0 END) AS reply_comments
FROM social_media.comments;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users ( user_id text, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified boolean )
CREATE TABLE social_media.posts ( post_id text, user_id text, content text, media_url text, media_type text, created_at timestamp, updated_at timestamp, visibility text, location_lat numeric, location_lon numeric )
CREATE TABLE social_media.comments ( comment_id text, post_id text, user_id text, parent_comment_id text, content text, created_at timestamp, updated_at timestamp )
CREATE TABLE social_media.follows ( follow_id text, follower_user_id text, following_user_id text, created_at timestamp )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id text, post_id text, hashtag_id text )
CREATE TABLE social_media.conversations ( conversation_id text, created_at timestamp, last_message_at timestamp, is_group_chat boolean, group_name text )
CREATE TABLE social_media.notifications ( notification_id text, recipient_user_id text, sender_user_id text, notification_type text, target_entity_id text, target_entity_type text, created_at timestamp, read_at timestamp )


[User] Show me the names and URLs of all DApps where the description contains the word 'wallet'.

[Assistant] SELECT name, url FROM trading_platform.dapps WHERE description ILIKE '%wallet%';

[User] I also want to see their dapp_id included in the result.

[Assistant] SELECT dapp_id, name, url FROM trading_platform.dapps WHERE description ILIKE '%wallet%';

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.dapps ( dapp_id.text, name.text, description.text, url.text )


[User] Show the tokens with a negative net flow this month on all chains.

[Assistant] SELECT token_symbol, chain, net_flow FROM smart_money_token_performance WHERE net_flow < 0 AND date_trunc('month', CURRENT_DATE) = date_trunc('month', now());

[User] Order them by net flow ascending and only show the bottom 5.

[Assistant] SELECT token_symbol, chain, net_flow FROM smart_money_token_performance WHERE net_flow < 0 AND date_trunc('month', CURRENT_DATE) = date_trunc('month', now()) ORDER BY net_flow ASC 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 smart_money_token_performance ( token_address character varying(100) NOT NULL, token_symbol character varying(100), pnl numeric(38,2), net_flow numeric(38,2), avg_cost numeric(38,16), price double precision, realized_ratio numeric(10,2), roi numeric(10,2), chain character varying(100) )


[User] For each block number, show the highest transaction value and the status of the transaction with the highest value.

[Assistant]
SELECT t.block_number, t.value AS max_value, t.status
FROM web3.transactions t
JOIN (
  SELECT block_number, MAX(value) AS max_value
  FROM web3.transactions
  GROUP BY block_number
) mv
  ON t.block_number = mv.block_number AND t.value = mv.max_value;

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.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 )


[User] Show the name, symbol, and type of each asset, along with the total number of orders placed for each asset.

[Assistant]
SELECT a.name, a.symbol, a.type, COUNT(o.order_id) AS order_count
FROM trading_platform.assets a
LEFT JOIN trading_platform.orders o ON a.asset_id = o.asset_id
GROUP BY a.asset_id, a.name, a.symbol, a.type;

[User] Only include assets that have at least 10 orders, and order the result by order_count descending.

[Assistant]
SELECT a.name, a.symbol, a.type, COUNT(o.order_id) AS order_count
FROM trading_platform.assets a
LEFT JOIN trading_platform.orders o ON a.asset_id = o.asset_id
GROUP BY a.asset_id, a.name, a.symbol, a.type
HAVING COUNT(o.order_id) >= 10
ORDER BY order_count DESC;

[User] Instead of all orders, only consider orders with status 'open'.

[Assistant]
SELECT a.name, a.symbol, a.type, COUNT(o.order_id) AS open_order_count
FROM trading_platform.assets a
LEFT JOIN trading_platform.orders o ON a.asset_id = o.asset_id AND o.status = 'open'
GROUP BY a.asset_id, a.name, a.symbol, a.type
HAVING COUNT(o.order_id) >= 10
ORDER BY open_order_count DESC;

[User] The SQL doesn't work because some assets have no open orders, but I want to include those assets with a count of 0. Please update the query accordingly.

[Assistant]
SELECT a.name, a.symbol, a.type, COUNT(o.order_id) AS open_order_count
FROM trading_platform.assets a
LEFT JOIN trading_platform.orders o ON a.asset_id = o.asset_id AND o.status = 'open'
GROUP BY a.asset_id, a.name, a.symbol, a.type
HAVING COUNT(o.order_id) >= 10 OR COUNT(o.order_id) = 0
ORDER BY open_order_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id.text, user_id.text, address.text, private_key.text, created_at.timestamp )
CREATE TABLE trading_platform.orders ( order_id.text, user_id.text, wallet_id.text, asset_id.text, order_type.text, quantity.numeric, price.numeric, status.text, created_at.timestamp )
CREATE TABLE trading_platform.trades (
    trade_id character varying(64) NOT NULL,  -- unique identifier for the trade
    order_id character varying(64) NOT NULL, -- identifier of the order that led to the trade
    buyer_id character varying(64) NOT NULL, -- identifier of the buyer
    seller_id character varying(64) NOT NULL, -- identifier of the seller
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the trade
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    traded_at timestamp NOT NULL, -- time when the trade was executed
    PRIMARY KEY (trade_id)
)
CREATE TABLE trading_platform.assets ( asset_id text, name text, symbol text, type text )
CREATE TABLE trading_platform.dapps ( dapp_id text PRIMARY KEY, name text, description text, url text )
CREATE TABLE trading_platform.kyc_audit (
    kyc_audit_id character varying(64) NOT NULL,  -- unique identifier for the KYC audit
    user_id character varying(64) NOT NULL, -- identifier of the user being audited
    status character varying(32) NOT NULL, -- status of the KYC audit (e.g., pending, approved, rejected)
    reviewed_at timestamp NOT NULL, -- time when the KYC audit was reviewed
    PRIMARY KEY (kyc_audit_id)
)
CREATE TABLE trading_platform.notifications ( notification_id.text, user_id.text, message.text, sent_at.timestamp, read_at.timestamp )


[User] Find all patients who have insurance plans with group numbers, showing their patient IDs and the count of such plans per patient, ordered by count in descending order.

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

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


[User] List all transaction IDs, sender addresses, and amounts for transactions received by '0xFEDCBA9876543210FEDCBA9876543210FEDCBA98' between '2023-01-01' and '2023-03-31'.

[Assistant] SELECT transaction_id, sender_address, amount FROM blockchain.transactions WHERE receiver_address = '0xFEDCBA9876543210FEDCBA9876543210FEDCBA98' AND timestamp BETWEEN '2023-01-01' AND '2023-03-31';

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.transactions (
    transaction_id character varying(64) NOT NULL,  -- unique identifier for the transaction
    block_id character varying(64) NOT NULL, -- identifier of the block containing the transaction
    sender_address character varying(128) NOT NULL, -- address of the sender
    receiver_address character varying(128) NOT NULL, -- address of the receiver
    amount numeric(38,14) NOT NULL, -- amount transferred
    timestamp timestamp NOT NULL, -- time when the transaction was created
    signature text NOT NULL, -- digital signature of the transaction
    PRIMARY KEY (transaction_id)
)


[User] List the service_id, service_name, and agency_id for all active services that have an online application URL provided.

[Assistant]
SELECT service_id,
       service_name,
       agency_id
FROM government_services.services
WHERE is_active = TRUE
  AND online_application_url IS NOT NULL;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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.services ( service_id text, agency_id text, service_name text, description text, category text, eligibility_criteria text, standard_fee numeric, average_processing_time_days integer, is_active boolean, online_application_url text )
CREATE TABLE government_services.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.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 report of each user with their username and the count of all log entries from the last 30 days.

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

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

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

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

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

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

[Assistant]
SELECT u.user_id,
       u.username,
       COUNT(l.log_id) AS log_count,
       MIN(l.logged_at) AS first_log_date
FROM trading_platform.users u
JOIN trading_platform.logs l
  ON u.user_id = l.user_id
WHERE l.logged_at >= CURRENT_DATE - INTERVAL '30 days'
  AND l.action ILIKE '%trade%'
GROUP BY u.user_id, u.username
ORDER BY log_count DESC
LIMIT 5;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(128) NOT NULL, -- username of the user
    email character varying(128) NOT NULL, -- email address of the user
    password_hash text NOT NULL, -- hashed password of the user
    created_at timestamp NOT NULL, -- time when the user account was created
    PRIMARY KEY (user_id)
)
CREATE TABLE trading_platform.orders (
    order_id character varying(64) NOT NULL,  -- unique identifier for the order
    user_id character varying(64) NOT NULL, -- identifier of the user placing the order
    wallet_id character varying(64) NOT NULL, -- identifier of the wallet used for the order
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    order_type character varying(32) NOT NULL, -- type of the order (e.g., buy, sell)
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the order
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    status character varying(32) NOT NULL, -- status of the order (e.g., open, filled, canceled)
    created_at timestamp NOT NULL, -- time when the order was created
    PRIMARY KEY (order_id)
)
CREATE TABLE trading_platform.utxos (
    utxo_id character varying(64) NOT NULL,  -- unique identifier for the UTXO
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that created the UTXO
    output_index integer NOT NULL, -- index of the output in the transaction
    address character varying(128) NOT NULL, -- address that can spend the UTXO
    amount numeric(38,14) NOT NULL, -- amount of the asset in the UTXO
    spent boolean NOT NULL, -- whether the UTXO has been spent
    PRIMARY KEY (utxo_id)
)
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
CREATE TABLE trading_platform.peers (
    peer_id character varying(64) NOT NULL,  -- unique identifier for the peer
    ip_address character varying(15) NOT NULL, -- IP address of the peer
    port integer NOT NULL, -- port number of the peer
    last_seen timestamp NOT NULL, -- last time the peer was active
    PRIMARY KEY (peer_id)
)
CREATE TABLE trading_platform.logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the log entry
    user_id character varying(64), -- identifier of the user associated with the log entry
    action character varying(128) NOT NULL, -- action performed
    details text NOT NULL, -- details of the action
    logged_at timestamp NOT NULL, -- time when the log entry was created
    PRIMARY KEY (log_id)
)


[User] I need to identify pairs of verified documents submitted by the same citizen. For each pair, display the citizen_id, the earlier document_id with its verification timestamp, and the later document_id with its verification timestamp.

[Assistant]
SELECT
  d1.citizen_id,
  d1.document_id AS earlier_document_id,
  d1.verification_timestamp AS earlier_verification,
  d2.document_id AS later_document_id,
  d2.verification_timestamp AS later_verification
FROM government_services.documents d1
JOIN government_services.documents d2
  ON d1.citizen_id = d2.citizen_id
  AND d1.verification_timestamp < d2.verification_timestamp
WHERE d1.verification_status = 'Verified'
  AND d2.verification_status = 'Verified';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.documents ( document_id character varying(64) NOT NULL, application_id character varying(64), citizen_id character varying(64) NOT NULL, document_type character varying(100) NOT NULL, file_reference text NOT NULL, upload_timestamp timestamp NOT NULL, expiry_date date, verification_status character varying(30) DEFAULT 'Pending', verified_by_employee_id character varying(64), verification_timestamp timestamp, PRIMARY KEY (document_id) )


[User] Show a list of clients whose status is 'inactive', including their first and last name, email, phone, and date registered.

[Assistant]
SELECT first_name, last_name, email, phone, date_registered
FROM legal_services.clients
WHERE status = 'inactive';

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.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 character varying(64) NOT NULL,  -- unique identifier for the document
    case_id character varying(64) NOT NULL, -- FK to cases table
    document_name character varying(255) NOT NULL, -- name of the document file
    document_type character varying(100), -- e.g., Pleading, Contract, Evidence, Correspondence
    storage_path text NOT NULL, -- path or reference to the document storage location
    uploaded_by_lawyer_id character varying(64), -- FK to lawyers table (who uploaded it)
    upload_timestamp timestamp NOT NULL, -- time the document was uploaded
    version integer DEFAULT 1, -- document version number
    description text, -- brief description or notes about the document
    PRIMARY KEY (document_id)
)
CREATE TABLE legal_services.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.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] List the first name and last name of the driver and the license plate of the vehicle used for each trip.

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

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

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

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


[User] Show the full names and contact emails of all citizens who have applied for services with a standard fee greater than 100.

[Assistant]
SELECT c.first_name || ' ' || c.last_name AS full_name, c.contact_email
FROM government_services.citizens c
JOIN government_services.services s ON c.citizen_id IS NOT NULL -- Replace with actual application linking table if exists
WHERE s.standard_fee > 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 government_services.citizens ( citizen_id character varying(64) NOT NULL, national_id_number character varying(128) NOT NULL UNIQUE, 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, contact_email character varying(128) UNIQUE, contact_phone character varying(32), registration_date timestamp NOT NULL, is_verified boolean DEFAULT false, PRIMARY KEY (citizen_id) )
CREATE TABLE government_services.services ( service_id.text, agency_id.text, service_name.text, description.text, category.text, eligibility_criteria.text, standard_fee.numeric, average_processing_time_days.integer, is_active.boolean, online_application_url.text )


[User] Show me each guest's full name and the number of unique properties they have made reservations for.

[Assistant]
SELECT g.first_name || ' ' || g.last_name AS full_name,
       COUNT(DISTINCT r.property_id) AS property_count
FROM hospitality_technology.guests g
JOIN hospitality_technology.reservations r
  ON g.guest_id = r.guest_id
GROUP BY full_name;

[User] Only include guests who have booked at least 2 different properties.

[Assistant]
SELECT g.first_name || ' ' || g.last_name AS full_name,
       COUNT(DISTINCT r.property_id) AS property_count
FROM hospitality_technology.guests g
JOIN hospitality_technology.reservations r
  ON g.guest_id = r.guest_id
GROUP BY full_name
HAVING COUNT(DISTINCT r.property_id) >= 2;

[User] Also calculate their average total_amount per reservation and sort by that average in descending order.

[Assistant]
SELECT g.first_name || ' ' || g.last_name AS full_name,
       COUNT(DISTINCT r.property_id) AS property_count,
       AVG(r.total_amount)       AS avg_total_per_reservation
FROM hospitality_technology.guests g
JOIN hospitality_technology.reservations r
  ON g.guest_id = r.guest_id
GROUP BY full_name
HAVING COUNT(DISTINCT r.property_id) >= 2
ORDER BY avg_total_per_reservation DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.properties ( property_id character varying(64) NOT NULL, property_name character varying(255) NOT NULL, address_line1 character varying(255) NOT NULL, address_line2 character varying(255), city character varying(100) NOT NULL, state_province character varying(100), postal_code character varying(20) NOT NULL, country_code character varying(3) NOT NULL, phone_number character varying(30), email_address character varying(255), property_type character varying(50) NOT NULL, star_rating numeric(2,1), timezone character varying(64) NOT NULL, manager_staff_id character varying(64), created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (property_id) )
CREATE TABLE hospitality_technology.rooms ( room_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, room_number character varying(10) NOT NULL, room_type_id character varying(64) NOT NULL, floor integer, status character varying(50) NOT NULL, is_smoking boolean NOT NULL DEFAULT false, features text, current_condition text, last_cleaned_at timestamp with time zone, PRIMARY KEY (room_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id), FOREIGN KEY (room_type_id) REFERENCES hospitality_technology.room_types(room_type_id) )
CREATE TABLE hospitality_technology.room_types ( room_type_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, type_name character varying(100) NOT NULL, description text, base_rate numeric(10, 2) NOT NULL, max_occupancy integer NOT NULL, bed_type character varying(50), area_sqft numeric(8,2), amenities text, PRIMARY KEY (room_type_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id) )
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 character varying(64) NOT NULL, property_id character varying(64) NOT NULL, guest_id character varying(64) NOT NULL, room_id character varying(64), room_type_id character varying(64) NOT NULL, check_in_date date NOT NULL, check_out_date date NOT NULL, actual_check_in_ts timestamp with time zone, actual_check_out_ts timestamp with time zone, num_adults integer NOT NULL, num_children integer DEFAULT 0, status character varying(50) NOT NULL, booking_source character varying(100), rate_plan_id character varying(64), total_amount numeric(12, 2), amount_paid numeric(12, 2) DEFAULT 0.00, special_requests text, created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, updated_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (reservation_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id), FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id), FOREIGN KEY (room_id) REFERENCES hospitality_technology.rooms(room_id), FOREIGN KEY (room_type_id) REFERENCES hospitality_technology.room_types(room_type_id) )
CREATE TABLE hospitality_technology.payments ( payment_id character varying(64) NOT NULL, reservation_id character varying(64), guest_id character varying(64) NOT NULL, bill_id character varying(64), amount numeric(12,2) NOT NULL, currency_code character varying(3) NOT NULL, payment_method character varying(50) NOT NULL, card_type character varying(50), card_last_four character varying(4), transaction_ref character varying(128), payment_timestamp timestamp with time zone NOT NULL DEFAULT current_timestamp, status character varying(50) NOT NULL, staff_id_processed character varying(64), notes text, PRIMARY KEY (payment_id), FOREIGN KEY (reservation_id) REFERENCES hospitality_technology.reservations(reservation_id), FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id), FOREIGN KEY (staff_id_processed) REFERENCES hospitality_technology.staff(staff_id) )
CREATE TABLE hospitality_technology.reviews ( review_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, reservation_id character varying(64) UNIQUE, guest_id character varying(64) NOT NULL, rating_overall integer, rating_cleanliness integer, rating_service integer, rating_location integer, rating_value integer, comment text, review_source character varying(100), review_date timestamp with time zone NOT NULL DEFAULT current_timestamp, is_public boolean DEFAULT true, staff_response text, response_staff_id character varying(64), response_date timestamp with time zone, PRIMARY KEY (review_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id), FOREIGN KEY (reservation_id) REFERENCES hospitality_technology.reservations(reservation_id), FOREIGN KEY (guest_id) REFERENCES hospitality_technology.guests(guest_id), FOREIGN KEY (response_staff_id) REFERENCES hospitality_technology.staff(staff_id) )


[User] List each claim_handler_id along with the number of claims they've handled and the total settlement_amount they've paid out.

[Assistant]
SELECT claim_handler_id,
       COUNT(*) AS total_claims,
       SUM(settlement_amount) AS total_settlement
FROM insurance.claims
GROUP BY claim_handler_id;

[User] In addition, include the claim_id of the single claim with the highest settlement_amount for each handler.

[Assistant]
SELECT ag.claim_handler_id,
       ag.total_claims,
       ag.total_settlement,
       c_max.claim_id               AS max_settlement_claim_id,
       c_max.settlement_amount      AS max_settlement_amount
FROM (
  SELECT claim_handler_id,
         COUNT(*) AS total_claims,
         SUM(settlement_amount) AS total_settlement
  FROM insurance.claims
  GROUP BY claim_handler_id
) ag
JOIN insurance.claims c_max
  ON c_max.claim_handler_id = ag.claim_handler_id
  AND c_max.settlement_amount = (
    SELECT MAX(settlement_amount)
    FROM insurance.claims
    WHERE claim_handler_id = ag.claim_handler_id
  );

[User] Only include handlers who have managed at least 3 claims and have a non-null claim_handler_id.

[Assistant]
SELECT ag.claim_handler_id,
       ag.total_claims,
       ag.total_settlement,
       c_max.claim_id               AS max_settlement_claim_id,
       c_max.settlement_amount      AS max_settlement_amount
FROM (
  SELECT claim_handler_id,
         COUNT(*) AS total_claims,
         SUM(settlement_amount) AS total_settlement
  FROM insurance.claims
  GROUP BY claim_handler_id
  HAVING COUNT(*) >= 3
     AND claim_handler_id IS NOT NULL
) ag
JOIN insurance.claims c_max
  ON c_max.claim_handler_id = ag.claim_handler_id
  AND c_max.settlement_amount = (
    SELECT MAX(settlement_amount)
    FROM insurance.claims
    WHERE claim_handler_id = ag.claim_handler_id
  );

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

[Assistant]
SELECT ag.claim_handler_id,
       ag.total_claims,
       ag.total_settlement,
       c_max.claim_id               AS max_settlement_claim_id,
       c_max.settlement_amount      AS max_settlement_amount
FROM (
  SELECT claim_handler_id,
         COUNT(*) AS total_claims,
         SUM(settlement_amount) AS total_settlement
  FROM insurance.claims
  GROUP BY claim_handler_id
  HAVING COUNT(*) >= 3
     AND claim_handler_id IS NOT NULL
) ag
JOIN insurance.claims c_max
  ON c_max.claim_handler_id = ag.claim_handler_id
  AND c_max.settlement_amount = (
    SELECT MAX(settlement_amount)
    FROM insurance.claims
    WHERE claim_handler_id = ag.claim_handler_id
  )
ORDER BY ag.total_settlement DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE insurance.claims (
    claim_id character varying(64) NOT NULL, -- unique identifier for the claim
    policy_id character varying(64) NOT NULL, -- identifier of the policy under which the claim is made (FK to policies)
    customer_id character varying(64) NOT NULL, -- identifier of the customer making the claim (FK to customers)
    incident_date timestamp NOT NULL, -- date and time of the incident leading to the claim
    reported_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- date the claim was reported
    description text NOT NULL, -- detailed description of the incident and claim
    estimated_loss numeric(15, 2), -- initial estimated cost of the loss
    status character varying(30) NOT NULL, -- e.g., Filed, Processing, Under Review, Approved, Denied, Settled
    settlement_amount numeric(15, 2), -- final amount paid out
    settlement_date date,
    claim_handler_id character varying(64), -- identifier for the employee handling the claim (FK to employees/adjusters)
    police_report_number character varying(100),
    PRIMARY KEY (claim_id)
)


[User] Show the number of reservations and the sum total_amount for each property.

[Assistant]
SELECT p.property_id, p.property_name, COUNT(r.reservation_id) AS reservation_count, SUM(r.total_amount) AS total_revenue
FROM hospitality_technology.properties p
LEFT JOIN hospitality_technology.reservations r ON p.property_id = r.property_id
GROUP BY p.property_id, p.property_name;

[User] Return only those properties with at least 50 reservations.

[Assistant]
SELECT p.property_id, p.property_name, COUNT(r.reservation_id) AS reservation_count, SUM(r.total_amount) AS total_revenue
FROM hospitality_technology.properties p
LEFT JOIN hospitality_technology.reservations r ON p.property_id = r.property_id
GROUP BY p.property_id, p.property_name
HAVING COUNT(r.reservation_id) >= 50;

[User] Additionally, only include properties in cities that start with the letter 'S' and order by total revenue descending.

[Assistant]
SELECT p.property_id, p.property_name, COUNT(r.reservation_id) AS reservation_count, SUM(r.total_amount) AS total_revenue
FROM hospitality_technology.properties p
LEFT JOIN hospitality_technology.reservations r ON p.property_id = r.property_id
WHERE p.city LIKE 'S%'
GROUP BY p.property_id, p.property_name
HAVING COUNT(r.reservation_id) >= 50
ORDER BY total_revenue DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.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.room_types ( room_type_id text, property_id text, type_name text, description text, base_rate numeric, max_occupancy integer, bed_type text, area_sqft numeric, amenities text )
CREATE TABLE hospitality_technology.guests ( guest_id text, first_name text, last_name text, email text, phone_number text, date_of_birth date, address_line1 text, city text, state_province text, postal_code text, country_code text, preferences text, loyalty_member_id text, communication_consent boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE hospitality_technology.reservations ( reservation_id text, property_id text, guest_id text, room_id text, room_type_id text, check_in_date date, check_out_date date, actual_check_in_ts timestamp, actual_check_out_ts timestamp, num_adults integer, num_children integer, status text, booking_source text, rate_plan_id text, total_amount numeric, amount_paid numeric, special_requests text, created_at timestamp, updated_at timestamp )


[User] Show me all chronic diagnoses along with their descriptions and the patient IDs, sorted by diagnosis date in descending order.

[Assistant] SELECT patient_id, description, diagnosis_date FROM healthcare.diagnoses WHERE is_chronic = true ORDER BY diagnosis_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.diagnoses ( diagnosis_id text PRIMARY KEY, record_id text, patient_id text, doctor_id text, diagnosis_code text, code_type text, description text, diagnosis_date date, status text, is_chronic boolean )


[User] What is the maintenance schedule for platform 3 at station DEF for the next month?

[Assistant] I'm sorry, but I don't have access to the maintenance schedule for platforms. The data I have only includes static information about platform details such as ID, station, number, track, status, length, and accessibility. For maintenance schedules, you may need to consult the station management or relevant department.

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.platforms ( platform_id text, station_id text, platform_number text, track_number text, status text, length_meters numeric, accessible boolean )