[User] Find all medical records where the treatment plan includes 'physical therapy' and the patient has an active primary insurance plan, showing the patient ID, record date, and insurance provider details.

[Assistant] SELECT mr.patient_id, mr.record_date, ip.insurance_provider, ip.plan_name, pi.policy_number FROM healthcare.medical_records mr JOIN healthcare.patients p ON mr.patient_id = p.patient_id JOIN healthcare.patient_insurance pi ON p.patient_id = pi.patient_id AND pi.is_primary = true JOIN healthcare.insurance_plans ip ON pi.plan_id = ip.plan_id WHERE mr.treatment_plan LIKE '%physical therapy%' AND (pi.expiration_date IS NULL OR pi.expiration_date > CURRENT_DATE);

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.patients ( patient_id text, first_name text, last_name text, date_of_birth date, gender text, address text, phone_number text, email text, emergency_contact_name text, emergency_contact_phone text, created_at timestamp, updated_at timestamp )
CREATE TABLE healthcare.appointments ( appointment_id text, patient_id text, doctor_id text, appointment_time timestamp, duration_minutes integer, reason text, status text, location_id text, notes text, created_at timestamp )
CREATE TABLE healthcare.medical_records ( record_id text PRIMARY KEY, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )
CREATE TABLE healthcare.diagnoses ( diagnosis_id text PRIMARY KEY, record_id text, patient_id text, doctor_id text, diagnosis_code text, code_type text, description text, diagnosis_date date, status text, is_chronic boolean )
CREATE TABLE healthcare.medications ( medication_id text, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )
CREATE TABLE healthcare.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, patient_id character varying(64) NOT NULL, plan_id character varying(64) NOT NULL, policy_number character varying(100) NOT NULL, group_number character varying(100), subscriber_name character varying(200), effective_date date NOT NULL, expiration_date date, is_primary boolean NOT NULL DEFAULT true, PRIMARY KEY (patient_insurance_id), UNIQUE (patient_id, plan_id, policy_number) )


[User] Show me the balances held by the 'Coinbase' exchange. For each token, list the token symbol, balance, and the current price from the token basic info table.

[Assistant] SELECT ctb.token_symbol, ctb.balance, tbi.price FROM cex_token_balance ctb JOIN token_basic_info tbi ON ctb.token_address = tbi.token_address AND ctb.chain = tbi.chain WHERE ctb.exchange = 'Coinbase';

[User] Include the USD value of the balance (balance * current price) and order the results by this calculated USD value in descending order.

[Assistant] SELECT ctb.token_symbol, ctb.balance, tbi.price, (ctb.balance * tbi.price) AS current_usd_value FROM cex_token_balance ctb JOIN token_basic_info tbi ON ctb.token_address = tbi.token_address AND ctb.chain = tbi.chain WHERE ctb.exchange = 'Coinbase' ORDER BY current_usd_value 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
CREATE TABLE token_basic_info ( coin_id.text, token_name.text, token_symbol.text, token_address.text, chain.text, price.numeric, price_change_percentage_1h.numeric, price_change_percentage_24h.numeric, price_change_percentage_7d.numeric, highest_price_24h.numeric, lowest_price_24h.numeric, market_cap.numeric, market_cap_rank.numeric, market_cap_change_percentage_24h.text, total_volume.text, narrative.text, trend_rank.numeric )
CREATE TABLE cex_token_balance ( snapshot_time.text, chain.text, address.text, exchange.text, token_address.text, token_symbol.text, balance.numeric, usd_value.numeric, price.numeric )
CREATE TABLE smart_money_token_inflow ( token_address.text, token_symbol.text, token_amount.numeric, usd_value.numeric, avg_price.numeric, type.numeric, address_amount.numeric, narrative.text, chain.text )


[User] List all active policies, showing the policy number, the customer's full name, and the agent's full name who sold the policy.

[Assistant] SELECT T1.policy_number, T2.first_name, T2.last_name, T3.first_name, T3.last_name FROM policies AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id JOIN agents AS T3 ON T1.agent_id = T3.agent_id WHERE T1.status = 'active'

[User] Can you also add the product name and the policy's premium amount to the results?

[Assistant] SELECT T1.policy_number, T2.first_name AS customer_first_name, T2.last_name AS customer_last_name, T3.first_name AS agent_first_name, T3.last_name AS agent_last_name, T4.product_name, T1.premium_amount FROM policies AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id JOIN agents AS T3 ON T1.agent_id = T3.agent_id JOIN insurance_products AS T4 ON T1.product_id = T4.product_id WHERE T1.status = 'active'

[User] Actually, filter those results to only include policies with a premium amount greater than 5000 and only sold by agents whose license state is 'CA'.

[Assistant] SELECT T1.policy_number, T2.first_name AS customer_first_name, T2.last_name AS customer_last_name, T3.first_name AS agent_first_name, T3.last_name AS agent_last_name, T4.product_name, T1.premium_amount FROM policies AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id JOIN agents AS T3 ON T1.agent_id = T3.agent_id JOIN insurance_products AS T4 ON T1.product_id = T4.product_id WHERE T1.status = 'active' AND T1.premium_amount > 5000 AND T3.license_state = 'CA'

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 PRIMARY KEY, first_name text, last_name text, date_of_birth date, ssn_hash text, address_line1 text, address_line2 text, city text, state text, zip_code text, country text, phone_number text, email text, created_at timestamp, updated_at timestamp, status text )
CREATE TABLE insurance.policies ( policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, product_id character varying(64) NOT NULL, agent_id character varying(64), policy_number character varying(100) NOT NULL UNIQUE, start_date date NOT NULL, end_date date NOT NULL, premium_amount numeric(12, 2) NOT NULL, coverage_limit numeric(15, 2) NOT NULL, deductible numeric(10, 2) NOT NULL, status character varying(30) NOT NULL, issued_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, cancellation_date date, cancellation_reason text, PRIMARY KEY (policy_id) )
CREATE TABLE insurance.claims ( claim_id character varying(64) NOT NULL, policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, incident_date timestamp NOT NULL, reported_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, description text NOT NULL, estimated_loss numeric(15, 2), status character varying(30) NOT NULL, settlement_amount numeric(15, 2), settlement_date date, claim_handler_id character varying(64), police_report_number character varying(100), PRIMARY KEY (claim_id) )
CREATE TABLE insurance.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )
CREATE TABLE insurance.premium_payments ( payment_id text PRIMARY KEY, policy_id text, customer_id text, payment_date timestamp, amount_paid numeric, payment_method text, transaction_reference text, due_date date, payment_period_start date, payment_period_end date, status text )


[User] List all pairs of wallets that were created within 10 minutes of each other, showing both wallet IDs, the user_id, and both creation timestamps.

[Assistant]
SELECT
  w1.wallet_id AS wallet1_id,
  w2.wallet_id AS wallet2_id,
  w1.user_id,
  w1.created_at AS created_at1,
  w2.created_at AS created_at2
FROM web3.wallets w1
JOIN web3.wallets w2
  ON w1.user_id = w2.user_id
  AND w1.wallet_id < w2.wallet_id
  AND ABS(EXTRACT(EPOCH FROM (w1.created_at - w2.created_at))) <= 600;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )


[User] List all applications that have at least one document with a verification status of 'Verified'. Show the application reference number and the name of the service associated with the application.

[Assistant]
SELECT
  T1.reference_number,
  T2.service_name
FROM government_services.applications AS T1
INNER JOIN government_services.services AS T2
  ON T1.service_id = T2.service_id
WHERE EXISTS (
  SELECT
    1
  FROM government_services.documents AS T3
  WHERE
    T3.application_id = T1.application_id AND T3.verification_status = 'Verified'
);

[User] Now, only include applications that were submitted in the year 2024.

[Assistant]
SELECT
  T1.reference_number,
  T2.service_name
FROM government_services.applications AS T1
INNER JOIN government_services.services AS T2
  ON T1.service_id = T2.service_id
WHERE EXISTS (
  SELECT
    1
  FROM government_services.documents AS T3
  WHERE
    T3.application_id = T1.application_id AND T3.verification_status = 'Verified'
)
AND EXTRACT(YEAR FROM T1.submitted_at) = 2024;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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 character varying(64) NOT NULL, -- unique identifier for the agency
    agency_name character varying(255) NOT NULL, -- full name of the government agency
    jurisdiction_level character varying(50) NOT NULL, -- e.g., Federal, State, County, City
    primary_contact_email character varying(128),
    main_phone_number character varying(32),
    website_url character varying(255),
    established_date date,
    parent_agency_id character varying(64), -- FK to self for hierarchical structure
    PRIMARY KEY (agency_id)
)
CREATE TABLE government_services.services (
    service_id character varying(64) NOT NULL, -- unique identifier for the service
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    service_name character varying(255) NOT NULL, -- name of the service (e.g., Driver's License Renewal)
    description text,
    category character varying(100), -- e.g., Licensing, Benefits, Taxation, Permits
    eligibility_criteria text, -- description of who is eligible
    standard_fee numeric(10, 2) DEFAULT 0.00, -- typical fee for the service
    average_processing_time_days integer, -- estimated processing time
    is_active boolean DEFAULT true, -- whether the service is currently offered
    online_application_url character varying(255),
    PRIMARY KEY (service_id)
)
CREATE TABLE government_services.documents (
    document_id 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.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 character varying(64) NOT NULL, -- unique identifier for the notification
    citizen_id character varying(64) NOT NULL, -- FK to citizens table
    application_id character varying(64), -- FK to applications table (optional)
    message_subject character varying(255),
    message_body text NOT NULL,
    channel character varying(30) NOT NULL, -- e.g., Email, SMS, Portal Message, Mail
    sent_at timestamp NOT NULL,
    status character varying(30) NOT NULL, -- e.g., Queued, Sent, Delivered, Failed, Read
    related_entity_type character varying(50), -- e.g., Application, Appointment, Document Request
    related_entity_id character varying(64), -- ID of the related entity
    PRIMARY KEY (notification_id)
)


[User] For each doctor, count the number of chronic diagnoses they have made. Show the doctor's full name and the count.

[Assistant] SELECT doc.first_name, doc.last_name, COUNT(d.diagnosis_id) FROM healthcare.doctors doc JOIN healthcare.diagnoses d ON doc.doctor_id = d.doctor_id WHERE d.is_chronic = TRUE GROUP BY doc.doctor_id, doc.first_name, doc.last_name ORDER BY COUNT(d.diagnosis_id) 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.doctors ( doctor_id text, first_name text, last_name text, specialty text, license_number text, phone_number text, email text, hospital_affiliation_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE healthcare.diagnoses (
    diagnosis_id character varying(64) NOT NULL, -- unique identifier for the diagnosis entry
    record_id character varying(64) NOT NULL, -- FK linking to the specific medical record entry
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to doctors table (diagnosing doctor)
    diagnosis_code character varying(20) NOT NULL, -- standard code (e.g., ICD-10)
    code_type character varying(10) NOT NULL DEFAULT 'ICD-10', -- type of code used
    description text, -- textual description of the diagnosis
    diagnosis_date date NOT NULL, -- date the diagnosis was made
    status character varying(32) NOT NULL, -- e.g., Active, Resolved, Ruled Out
    is_chronic boolean DEFAULT false, -- flag for chronic conditions
    PRIMARY KEY (diagnosis_id)
)
CREATE TABLE healthcare.insurance_plans ( plan_id text, plan_name text, insurance_provider text, plan_type text, contact_phone text, website text )


[User] What is the current job satisfaction level or feedback from staff members working at a specific train station?

[Assistant] I'm sorry, but I can't provide information on job satisfaction levels or feedback from staff members as this data is not included in the staff table.

System:
You are an SQL statement expert and you can refuse the user's question if the question is not related to the table structure. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE train_station_management.staff ( staff_id.text, first_name.text, last_name.text, role.text, primary_station_id.text, employee_number.text, hire_date.date, contact_email.text, contact_phone.text, is_active.boolean )


[User] Find the total transfer volume for each Avalanche token over the past 7 days and include the token's creator.

[Assistant]
SELECT a.tick,
       i.creator,
       SUM(a.amt) AS total_volume
FROM token_activities_avalanche a
JOIN token_info_avalanche i
  ON a.tick = i.tick
WHERE a.block_timestamp >= NOW() - INTERVAL '7 days'
GROUP BY a.tick, i.creator;

[User] Only include tokens with total_volume > 10000 and sort by total_volume descending.

[Assistant]
SELECT a.tick,
       i.creator,
       SUM(a.amt) AS total_volume
FROM token_activities_avalanche a
JOIN token_info_avalanche i
  ON a.tick = i.tick
WHERE a.block_timestamp >= NOW() - INTERVAL '7 days'
GROUP BY a.tick, i.creator
HAVING SUM(a.amt) > 10000
ORDER BY total_volume DESC;

[User] Limit the results to the top 5 tokens.

[Assistant]
SELECT a.tick,
       i.creator,
       SUM(a.amt) AS total_volume
FROM token_activities_avalanche a
JOIN token_info_avalanche i
  ON a.tick = i.tick
WHERE a.block_timestamp >= NOW() - INTERVAL '7 days'
GROUP BY a.tick, i.creator
HAVING SUM(a.amt) > 10000
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 token_metas ( block_timestamp timestamp, block_number bigint, transaction_hash varchar, transaction_index bigint, from_address varchar, contract_address varchar, symbol varchar, total_supply varchar, name varchar, decimals bigint, is_erc20 integer, is_erc721 integer, is_erc1155 integer, is_proxy integer, extra_info varchar, pk integer )
CREATE TABLE erc1155_approval_for_all ( block_number bigint NOT NULL, block_timestamp timestamp(3) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar(66) NOT NULL, log_index integer NOT NULL, contract_address varchar(42) NOT NULL )
CREATE TABLE erc20_balances_historical (
    block_number bigint NOT NULL, -- Block number containing the transaction
    contract_address varchar NOT NULL, -- Event contract address
    wallet_address varchar NOT NULL, -- The wallet address for the contract
    amount varchar NOT NULL, -- Wallet's on-chain balance at the corresponding block height
    pk integer NOT NULL  -- Partition key for the table(floor(block_number / 7200))
)
CREATE TABLE nft_holders (
    block_number bigint NOT NULL, -- Block number containing the transaction
    contract_address varchar NOT NULL, -- Event contract address
    wallet_address varchar NOT NULL, -- The wallet address for the contract(with bloom filter)
    token_id varchar NOT NULL, -- NFT token id
    contract_type varchar NOT NULL, -- NFT contract type
    amount varchar NOT NULL, -- Number of held NFTs
    pk varchar NOT NULL  -- The last string partition of the contract.
)
CREATE TABLE nft_holder_historical ( block_number.bigint, contract_address.text, wallet_address.text, token_id.text, contract_type.text, amount.text, pk.integer )
CREATE TABLE sui_coins ( object_id text, status text, coin_type text, balance text, owner text )
CREATE TABLE sui_nfts ( object_id varchar, status varchar, collection_type varchar, package_id varchar, previous_transaction varchar, display varchar, owner varchar, name varchar )
CREATE TABLE nft_collections (
    blockchain varchar NOT NULL, -- blockchain fields for the functionType  in contract
    contract_address varchar NOT NULL, -- Contract address(with bloom filter)
    name varchar NOT NULL, -- name fields for the functionType  in contract
    symbol varchar NOT NULL, -- symbol fields for the functionType  in contract
    deploy_block_number bigint NOT NULL, -- deploy_block_number fields for the functionType  in contract
    deploy_block_time bigint NOT NULL, -- deploy_block_time fields for the functionType  in contract
    erc_type varchar NOT NULL, -- The type of token
    owner varchar NOT NULL, -- owner fields for the functionType  in contract
    traits varchar NOT NULL, -- traits fields for the functionType  in contract
    description varchar NOT NULL, -- description fields for the functionType  in contract
    slug varchar NOT NULL, -- slug fields for the functionType  in contract
    media_info varchar NOT NULL, -- media_info fields for the functionType  in contract
    image_url varchar NOT NULL, -- image_url fields for the functionType  in contract
    banner_image_url varchar NOT NULL, -- banner_image_url fields for the functionType  in contract
    updated_at bigint NOT NULL, -- updated_at fields for the functionType  in contract
    banner varchar NOT NULL, -- banner fields for the functionType  in contract
    token_count bigint NOT NULL, -- token_count fields for the functionType  in contract
    floor_price varchar NOT NULL, -- floor_price fields for the functionType  in contract
    floor_price_symbol varchar NOT NULL, -- floor_price_symbol fields for the functionType  in contract
    floor_price_contract varchar NOT NULL, -- floor_price_contract fields for the functionType  in contract
    pk integer NOT NULL  -- Partition key for the table(floor(deploy_block_time / 1000 / 86400 / 30))
)
CREATE TABLE token_prices ( uuid varchar, blockchain varchar, address varchar, decimals bigint, symbol varchar, price real, timestamp timestamp )
CREATE TABLE token_prices_latest (
    blockchain varchar(36) NOT NULL, -- blockchain fields for the functionType  in contract
    address varchar(42) NOT NULL, -- address fields for the functionType  in contract
    decimals bigint NOT NULL, -- decimals fields for the functionType  in contract
    symbol varchar(36) NOT NULL, -- symbol fields for the functionType  in contract
    price real NOT NULL, -- price fields for the functionType  in contract
    timestamp timestamp(6) NOT NULL  -- timestamp fields for the functionType  in contract
)
CREATE TABLE erc20_approval ( block_number bigint, block_timestamp timestamp, transaction_index integer, transaction_hash text, log_index integer, contract_address text, pk integer )
CREATE TABLE token_balances ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )
CREATE TABLE token_info (
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the inscription (matches block_timestamp in transactions table)
    block_number bigint NOT NULL, -- Block number containing the inscription (matches block_number in transactions table)
    tx_index integer NOT NULL, -- Index of the transaction containing the inscription (matches transaction_index in transactions table)
    tx_hash varchar(66) NOT NULL, -- Unique identifier of the transaction containing the inscription (matches hash in transactions table)
    tick varchar NOT NULL, -- Token tick
    max_supply decimal(38,0) NOT NULL, -- Max supply
    lim decimal(38,0) NOT NULL, -- Limit of each mint
    wlim decimal(38,0) NOT NULL, -- Limit of each address can maximum mint
    dec integer NOT NULL, -- Decimal for minimum divie
    creator varchar(42) NOT NULL  -- Address originating the inscription (matches from_address in transactions table)
)
CREATE TABLE token_activities ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE mud_holesky_redstone ( address.text, table_id.text, key_bytes.text, key0.text, key1.text, static_data.text, encoded_lengths.text, dynamic_data.text, is_deleted.boolean, block_number.bigint, log_index.bigint )
CREATE TABLE token_info_bitcoin ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, tick varchar(255) NOT NULL, max_supply decimal(38,0) NOT NULL, lim decimal(38,0) NOT NULL, wlim decimal(38,0) NOT NULL, dec integer NOT NULL, creator varchar(42) NOT NULL )
CREATE TABLE token_activities_avalanche ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, log_index integer NOT NULL, type varchar(20) NOT NULL, tick varchar(255) NOT NULL, id varchar(255) NOT NULL, amt decimal(38,0) NOT NULL, from_address varchar(42) NOT NULL, to_address varchar(42) NOT NULL )
CREATE TABLE token_info_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text, minted decimal, holders decimal, txs decimal, updated_timestamp timestamp, completed_timestamp timestamp, id text )


[User] Show me all patients who have been prescribed medications with dosage greater than 100mg, along with their full names and the medication details, including the prescribing doctor's last name.

[Assistant] SELECT p.first_name, p.last_name, m.medication_name, m.generic_name, pr.dosage, d.last_name AS doctor_last_name FROM healthcare.patients p JOIN healthcare.prescriptions pr ON p.patient_id = pr.patient_id JOIN healthcare.medications m ON pr.medication_id = m.medication_id JOIN healthcare.doctors d ON pr.doctor_id = d.doctor_id WHERE pr.dosage LIKE '%100mg%' OR CAST(SUBSTRING(pr.dosage FROM '([0-9]+)') AS INTEGER) > 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 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.medical_records (
    record_id character varying(64) NOT NULL,  -- unique identifier for the medical record entry
    patient_id character varying(64) NOT NULL, -- FK to patients table
    appointment_id character varying(64) UNIQUE, -- FK to appointments table (can be null if record not tied to specific appt)
    doctor_id character varying(64) NOT NULL, -- FK to doctors table (doctor creating the record)
    record_date timestamp with time zone NOT NULL, -- date the record/observation was made
    chief_complaint text, -- patient's primary reason for visit
    present_illness_history text, -- detailed history of the current issue
    past_medical_history text, -- relevant past conditions/surgeries
    physical_examination_notes text, -- findings from the physical exam
    assessment text, -- doctor's assessment/diagnosis summary
    treatment_plan text, -- planned course of action
    vitals jsonb, -- store vitals like BP, HR, Temp as structured JSON
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (record_id)
)
CREATE TABLE healthcare.diagnoses (
    diagnosis_id 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)
)


[User] List all log entries associated with users who have participated in any trade, showing the log details and the trade ID.

[Assistant] SELECT T1.log_id, T1.action, T1.details, T1.logged_at, T2.trade_id, T2.buyer_id, T2.seller_id FROM logs AS T1 JOIN trades AS T2 ON T1.user_id = T2.buyer_id OR T1.user_id = T2.seller_id;

[User] Only show logs and trades that occurred in the last week.

[Assistant] SELECT T1.log_id, T1.action, T1.details, T1.logged_at, T2.trade_id, T2.buyer_id, T2.seller_id FROM logs AS T1 JOIN trades AS T2 ON T1.user_id = T2.buyer_id OR T1.user_id = T2.seller_id WHERE T1.logged_at >= datetime('now', '-7 days') AND T2.traded_at >= datetime('now', '-7 days');

[User] Can you instead provide a count of such log entries per user who traded, for the last week?

[Assistant] SELECT T1.user_id, COUNT(DISTINCT T1.log_id) AS log_count FROM logs AS T1 JOIN trades AS T2 ON T1.user_id = T2.buyer_id OR T1.user_id = T2.seller_id WHERE T1.logged_at >= datetime('now', '-7 days') AND T2.traded_at >= datetime('now', '-7 days') GROUP BY T1.user_id;

[User] Also include the total number of trades for each user in the same period and sort by trade count descending.

[Assistant] SELECT T1.user_id, COUNT(DISTINCT T1.log_id) AS log_count, COUNT(DISTINCT T2.trade_id) AS trade_count FROM logs AS T1 JOIN trades AS T2 ON T1.user_id = T2.buyer_id OR T1.user_id = T2.seller_id WHERE T1.logged_at >= datetime('now', '-7 days') AND T2.traded_at >= datetime('now', '-7 days') GROUP BY T1.user_id ORDER BY trade_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.trades ( trade_id.text, order_id.text, buyer_id.text, seller_id.text, asset_id.text, quantity.numeric, price.numeric, traded_at.timestamp )
CREATE TABLE trading_platform.utxos ( utxo_id.text, transaction_id.text, output_index.integer, address.text, amount.numeric, spent.boolean )
CREATE TABLE trading_platform.dapps ( dapp_id.text, name.text, description.text, url.text )
CREATE TABLE trading_platform.peers ( peer_id.text, ip_address.text, port.integer, last_seen.timestamp )
CREATE TABLE trading_platform.logs ( log_id.text, user_id.text, action.text, details.text, logged_at.timestamp )


[User] List the names of employees and the agency they work for who have scheduled at least one appointment. Show the employee's first name, last name, and agency_id.

[Assistant]
SELECT DISTINCT e.first_name, e.last_name, e.agency_id
FROM government_services.employees e
JOIN government_services.appointments a ON e.employee_id = a.employee_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.services ( service_id text, agency_id text, service_name text, description text, category text, eligibility_criteria text, standard_fee numeric, average_processing_time_days integer, is_active boolean, online_application_url text )
CREATE TABLE government_services.applications ( application_id text, citizen_id text, service_id text, submitted_at timestamp, status text, last_updated_at timestamp, assigned_employee_id text, decision_date date, notes text, reference_number text )
CREATE TABLE government_services.payments ( payment_id text, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees ( employee_id text, agency_id text, first_name text, last_name text, job_title text, department text, work_email text, work_phone text, hire_date date, termination_date date, access_level text, manager_employee_id text )
CREATE TABLE government_services.appointments ( appointment_id text, citizen_id text, employee_id text, location_id text, service_id text, scheduled_start_time timestamp, scheduled_end_time timestamp, purpose text, status text, booking_method text, created_at timestamp, notes text )
CREATE TABLE government_services.notifications ( notification_id text, citizen_id text, application_id text, message_subject text, message_body text, channel text, sent_at timestamp, status text, related_entity_type text, related_entity_id text )


[User] Show me the top 5 NFT collections with the highest token count on Ethereum, along with their names, symbols, and floor prices.

[Assistant] SELECT n.name, n.symbol, n.floor_price, n.token_count FROM nft_collections n WHERE n.blockchain = 'ethereum' ORDER BY n.token_count DESC LIMIT 5;

[User] Now, join this with the nft_metadata table to include the average rarity score for each collection.

[Assistant] SELECT n.name, n.symbol, n.floor_price, n.token_count, AVG(m.rarity_score) as avg_rarity_score FROM nft_collections n JOIN nft_metadata m ON n.contract_address = m.contract_address WHERE n.blockchain = 'ethereum' GROUP BY n.name, n.symbol, n.floor_price, n.token_count ORDER BY n.token_count DESC LIMIT 5;

[User] Can you filter these results to only show collections with an average rarity score greater than 80?

[Assistant] SELECT n.name, n.symbol, n.floor_price, n.token_count, AVG(m.rarity_score) as avg_rarity_score FROM nft_collections n JOIN nft_metadata m ON n.contract_address = m.contract_address WHERE n.blockchain = 'ethereum' GROUP BY n.name, n.symbol, n.floor_price, n.token_count HAVING AVG(m.rarity_score) > 80 ORDER BY n.token_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 token_metas ( block_timestamp timestamp, block_number bigint, transaction_hash text, transaction_index bigint, from_address text, contract_address text, symbol text, total_supply text, name text, decimals bigint, is_erc20 integer, is_erc721 integer, is_erc1155 integer, is_proxy integer, extra_info text, pk integer )
CREATE TABLE erc1155_approval_for_all ( block_number bigint, block_timestamp timestamp, transaction_index integer, transaction_hash text, log_index integer, contract_address text )
CREATE TABLE erc20_balances ( block_number bigint, contract_address text, wallet_address text, amount text, pk text )
CREATE TABLE sui_coins ( object_id text, status text, coin_type text, balance text, owner text )
CREATE TABLE sui_coins_metadata ( object_id text, coin_type text, status text, decimals bigint, description text, icon_url text, symbol text, name text )
CREATE TABLE sui_nfts ( object_id text, status text, collection_type text, package_id text, previous_transaction text, display text, owner text, name text )
CREATE TABLE nft_metadata ( blockchain text, contract_address text, token_id text, contract_name text, erc_type text, amount bigint, minter text, owner text, mint_block_number bigint, mint_time bigint, mint_transaction_hash text, mint_price text, token_uri text, metadata text, name text, image_uri text, traits text, updated_at bigint, status text, rarity_score real, rarity_rank integer, unique_attribute_count integer, pk integer )
CREATE TABLE nft_collections ( blockchain text, contract_address text, name text, symbol text, deploy_block_number bigint, deploy_block_time bigint, erc_type text, owner text, traits text, description text, slug text, media_info text, image_url text, banner_image_url text, updated_at bigint, banner text, token_count bigint, floor_price text, floor_price_symbol text, floor_price_contract text, pk integer )
CREATE TABLE token_prices ( uuid text, blockchain text, address text, decimals bigint, symbol text, price real, timestamp timestamp )
CREATE TABLE token_prices_latest ( blockchain text, address text, decimals bigint, symbol text, price real, timestamp timestamp )
CREATE TABLE token_balances ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )
CREATE TABLE token_info ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text )
CREATE TABLE token_activities ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, log_index integer, type text, tick text, id text, amt decimal, from_address text, to_address text )
CREATE TABLE mud_holesky_redstone ( address text, table_id text, key_bytes text, key0 text, key1 text, static_data text, encoded_lengths text, dynamic_data text, is_deleted boolean, block_number bigint, log_index bigint )
CREATE TABLE token_balances_bitcoin ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply text, amount text )
CREATE TABLE token_activities_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, log_index integer, type text, tick text, id text, amt decimal, from_address text, to_address text )
CREATE TABLE token_balances_avalanche ( block_number bigint, block_timestamp timestamp, tick text, wallet_address text, total_supply decimal, amount decimal )
CREATE TABLE token_info_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text, minted decimal, holders decimal, txs decimal, updated_timestamp timestamp, completed_timestamp timestamp, id text )


[User] Could you provide the total number of game sessions and the number of distinct players for each game genre? Display the genre, session count, and player count.

[Assistant] SELECT g.genre, COUNT(gs.session_id) AS session_count, COUNT(DISTINCT gs.player_id) AS player_count FROM gaming_technology.game_sessions AS gs JOIN gaming_technology.games AS g ON gs.game_id = g.game_id WHERE g.genre IS NOT NULL GROUP BY g.genre ORDER BY g.genre;

[User] Thanks. Can you modify the query to only include games that were released after the year 2020?

[Assistant] SELECT g.genre, COUNT(gs.session_id) AS session_count, COUNT(DISTINCT gs.player_id) AS player_count FROM gaming_technology.game_sessions AS gs JOIN gaming_technology.games AS g ON gs.game_id = g.game_id WHERE g.genre IS NOT NULL AND g.release_date >= '2021-01-01' GROUP BY g.genre ORDER BY g.genre;

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 NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for the player
    username character varying(100) NOT NULL UNIQUE, -- player's chosen display name
    email character varying(255) NOT NULL UNIQUE, -- player's email address for login/recovery
    password_hash text NOT NULL, -- securely hashed password
    registration_date timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the player account was created
    last_login timestamp with time zone, -- timestamp of the last successful login
    country_code character(2), -- player's country (ISO 3166-1 alpha-2)
    status character varying(20) NOT NULL DEFAULT 'active', -- account status (e.g., active, banned, suspended)
    profile_data jsonb, -- flexible field for avatar url, bio, preferences etc.
    PRIMARY KEY (player_id)
)
CREATE TABLE gaming_technology.games (
    game_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for the game
    title character varying(200) NOT NULL, -- official title of the game
    developer_id uuid NOT NULL, -- FK linking to the developers table
    publisher_id uuid, -- FK linking to a potential publishers table (optional)
    genre character varying(100), -- primary genre (e.g., RPG, FPS, Strategy)
    release_date date, -- official release date
    description text, -- short description or synopsis of the game
    platform character varying(50) NOT NULL, -- primary platform (e.g., PC, PlayStation 5, Xbox Series X, Mobile)
    engine character varying(100), -- game engine used (e.g., Unreal Engine 5, Unity)
    website character varying(255), -- official website URL
    PRIMARY KEY (game_id)
    -- FOREIGN KEY (developer_id) REFERENCES gaming_technology.developers(developer_id) -- Example FK constraint
)
CREATE TABLE gaming_technology.game_sessions (
    session_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for the game session
    player_id uuid NOT NULL, -- FK linking to the players table
    game_id uuid NOT NULL, -- FK linking to the games table
    server_id uuid, -- FK linking to the servers table (nullable for single-player)
    start_time timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the session began
    end_time timestamp with time zone, -- when the session ended (null if ongoing)
    duration_seconds integer, -- calculated duration of the session in seconds
    score integer, -- player's score for the session, if applicable
    session_data jsonb, -- flexible field for session-specific info (e.g., map played, character used)
    PRIMARY KEY (session_id)
    -- FOREIGN KEY (player_id) REFERENCES gaming_technology.players(player_id),
    -- FOREIGN KEY (game_id) REFERENCES gaming_technology.games(game_id),
    -- FOREIGN KEY (server_id) REFERENCES gaming_technology.servers(server_id)
)
CREATE TABLE gaming_technology.servers (
    server_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for the game server instance
    game_id uuid NOT NULL, -- FK linking to the game this server hosts
    server_name character varying(150), -- display name for the server
    region character varying(50) NOT NULL, -- geographical region (e.g., us-east-1, eu-west-2)
    ip_address character varying(45), -- IP address (IPv4 or IPv6)
    port integer, -- network port number
    current_players integer NOT NULL DEFAULT 0, -- number of players currently connected
    max_players integer NOT NULL, -- maximum player capacity
    status character varying(30) NOT NULL DEFAULT 'offline', -- server status (e.g., online, offline, maintenance)
    last_heartbeat timestamp with time zone, -- last time the server reported its status
    PRIMARY KEY (server_id)
    -- FOREIGN KEY (game_id) REFERENCES gaming_technology.games(game_id)
)
CREATE TABLE gaming_technology.achievements (
    achievement_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for an achievement definition
    game_id uuid NOT NULL, -- FK linking to the game the achievement belongs to
    name character varying(150) NOT NULL, -- name of the achievement
    description text NOT NULL, -- how to unlock the achievement
    icon_url character varying(255), -- URL for the achievement's icon
    points integer DEFAULT 0, -- points awarded for unlocking (optional)
    hidden boolean DEFAULT false, -- whether the achievement details are hidden until unlocked
    PRIMARY KEY (achievement_id)
    -- FOREIGN KEY (game_id) REFERENCES gaming_technology.games(game_id)
)
CREATE TABLE gaming_technology.player_achievements (
    player_achievement_id uuid NOT NULL DEFAULT gen_random_uuid(), -- unique identifier for this unlock instance
    player_id uuid NOT NULL, -- FK linking to the player who unlocked it
    achievement_id uuid NOT NULL, -- FK linking to the achievement definition
    unlocked_at timestamp with time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the achievement was unlocked
    PRIMARY KEY (player_achievement_id),
    UNIQUE (player_id, achievement_id) -- Ensure a player can only unlock an achievement once
    -- FOREIGN KEY (player_id) REFERENCES gaming_technology.players(player_id),
    -- FOREIGN KEY (achievement_id) REFERENCES gaming_technology.achievements(achievement_id)
)


[User] List all rooms, including their room number, the name of the property they belong to, and their room type name, specifically for rooms with 'Maintenance' status.

[Assistant] SELECT T1.room_number, T2.property_name, T3.type_name FROM rooms AS T1 JOIN properties AS T2 ON T1.property_id = T2.property_id JOIN room_types AS T3 ON T1.room_type_id = T3.room_type_id WHERE T1.status = 'Maintenance'

[User] Also include the floor number and filter to only show rooms located on floors 5 or higher. Sort the results by property name and then by floor.

[Assistant] SELECT T1.room_number, T2.property_name, T3.type_name, T1.floor FROM rooms AS T1 JOIN properties AS T2 ON T1.property_id = T2.property_id JOIN room_types AS T3 ON T1.room_type_id = T3.room_type_id WHERE T1.status = 'Maintenance' AND T1.floor >= 5 ORDER BY T2.property_name, T1.floor

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.rooms (
    room_id character varying(64) NOT NULL,  -- unique identifier for the room
    property_id character varying(64) NOT NULL, -- FK to properties table
    room_number character varying(10) NOT NULL, -- room number identifier (e.g., '101', 'Suite 2B')
    room_type_id character varying(64) NOT NULL, -- FK to room_types table
    floor integer, -- floor number the room is on
    status character varying(50) NOT NULL, -- e.g., Available, Occupied, Cleaning, OutOfOrder, Maintenance
    is_smoking boolean NOT NULL DEFAULT false, -- smoking allowed flag
    features text, -- description of features (e.g., Balcony, Sea View, Jacuzzi)
    current_condition text, -- notes on room condition
    last_cleaned_at timestamp with time zone, -- timestamp of last cleaning
    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)
)


[User] Find the names of service locations where services categorized as 'Licensing' have had appointments scheduled.

[Assistant] SELECT DISTINCT T1.location_name FROM service_locations AS T1 JOIN appointments AS T2 ON T1.location_id = T2.location_id JOIN services AS T3 ON T2.service_id = T3.service_id WHERE T3.category = 'Licensing';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.services (
    service_id character varying(64) NOT NULL, -- unique identifier for the service
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    service_name character varying(255) NOT NULL, -- name of the service (e.g., Driver's License Renewal)
    description text,
    category character varying(100), -- e.g., Licensing, Benefits, Taxation, Permits
    eligibility_criteria text, -- description of who is eligible
    standard_fee numeric(10, 2) DEFAULT 0.00, -- typical fee for the service
    average_processing_time_days integer, -- estimated processing time
    is_active boolean DEFAULT true, -- whether the service is currently offered
    online_application_url character varying(255),
    PRIMARY KEY (service_id)
)
CREATE TABLE government_services.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.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)
)


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

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

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

[Assistant]
SELECT t.buyer_id, m.value AS asset_symbol, SUM(t.quantity * t.price) AS total_value
FROM trading_platform.trades t
JOIN trading_platform.metadata m ON t.asset_id = m.asset_id AND m.key = 'symbol'
WHERE t.traded_at > '2024-06-01'
GROUP BY t.buyer_id, m.value
HAVING SUM(t.quantity * t.price) > 10000
ORDER BY total_value DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.orders ( order_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, wallet_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, order_type character varying(32) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, status character varying(32) NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (order_id) )
CREATE TABLE trading_platform.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )
CREATE TABLE trading_platform.peers ( peer_id character varying(64) NOT NULL, ip_address character varying(15) NOT NULL, port integer NOT NULL, last_seen timestamp NOT NULL, PRIMARY KEY (peer_id) )
CREATE TABLE trading_platform.metadata ( metadata_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, key character varying(128) NOT NULL, value text NOT NULL, PRIMARY KEY (metadata_id) )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, status character varying(32) NOT NULL, reviewed_at timestamp NOT NULL, PRIMARY KEY (kyc_audit_id) )
CREATE TABLE trading_platform.logs ( log_id character varying(64) NOT NULL, user_id character varying(64), action character varying(128) NOT NULL, details text NOT NULL, logged_at timestamp NOT NULL, PRIMARY KEY (log_id) )
CREATE TABLE trading_platform.notifications ( notification_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, message text NOT NULL, sent_at timestamp NOT NULL, read_at timestamp, PRIMARY KEY (notification_id) )


[User] Show me the top 5 NFT collections with the highest floor price on Ethereum, along with their names and contract addresses.

[Assistant] SELECT name, contract_address, floor_price FROM nft_collections WHERE blockchain = 'ethereum' ORDER BY CAST(floor_price AS decimal) DESC LIMIT 5;

[User] Can you also include the banner image URL and filter to only show ERC721 collections?

[Assistant] SELECT name, contract_address, floor_price, banner_image_url FROM nft_collections WHERE blockchain = 'ethereum' AND erc_type = 'ERC721' ORDER BY CAST(floor_price AS decimal) DESC LIMIT 5;

[User] I think there's a typo in your query - it should be 'nft_collections' not 'nft_collections'. Also, can you join this with the nft_metadata table to include the average rarity score for these collections?

[Assistant] SELECT nc.name, nc.contract_address, nc.floor_price, nc.banner_image_url, AVG(nm.rarity_score) as avg_rarity_score FROM nft_collections nc JOIN nft_metadata nm ON nc.contract_address = nm.contract_address WHERE nc.blockchain = 'ethereum' AND nc.erc_type = 'ERC721' GROUP BY nc.name, nc.contract_address, nc.floor_price, nc.banner_image_url ORDER BY CAST(nc.floor_price AS decimal) 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 erc1155_approval_for_all (
    block_number bigint NOT NULL, -- Block number containing the transaction
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the transaction
    transaction_index integer NOT NULL, -- Index of the transaction within the block
    transaction_hash varchar(66) NOT NULL, -- Transaction hash
    log_index integer NOT NULL, -- Log index
    contract_address varchar(42) NOT NULL  -- Event contract address
)
CREATE TABLE erc20_balances ( block_number.bigint, contract_address.text, wallet_address.text, amount.text, pk.text )
CREATE TABLE erc20_balances_historical ( block_number bigint NOT NULL, contract_address varchar NOT NULL, wallet_address varchar NOT NULL, amount varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE nft_metadata (
    blockchain varchar NOT NULL, -- blockchain fields for the functionType  in contract
    contract_address varchar NOT NULL, -- Contract address(with bloom filter)
    token_id varchar NOT NULL, -- The number of the token
    contract_name varchar NOT NULL, -- contract_name fields for the functionType  in contract
    erc_type varchar NOT NULL, -- The type of token
    amount bigint NOT NULL, -- amount fields for the functionType  in contract
    minter varchar NOT NULL, -- minter fields for the functionType  in contract
    owner varchar NOT NULL, -- owner fields for the functionType  in contract
    mint_block_number bigint NOT NULL, -- mint_block_number fields for the functionType  in contract
    mint_time bigint NOT NULL, -- mint_time fields for the functionType  in contract
    mint_transaction_hash varchar NOT NULL, -- mint_transaction_hash fields for the functionType  in contract
    mint_price varchar NOT NULL, -- mint_price fields for the functionType  in contract
    token_uri varchar NOT NULL, -- token_uri fields for the functionType  in contract
    metadata varchar NOT NULL, -- metadata fields for the functionType  in contract
    name varchar NOT NULL, -- name fields for the functionType  in contract
    image_uri varchar NOT NULL, -- image_uri fields for the functionType  in contract
    traits varchar NOT NULL, -- traits fields for the functionType  in contract
    updated_at bigint NOT NULL, -- updated_at fields for the functionType  in contract
    status varchar NOT NULL, -- status fields for the functionType  in contract
    rarity_score real NOT NULL, -- rarity_score fields for the functionType  in contract
    rarity_rank integer NOT NULL, -- rarity_rank fields for the functionType  in contract
    unique_attribute_count integer NOT NULL, -- unique_attribute_count fields for the functionType  in contract
    pk integer NOT NULL  -- Partition key for the table(floor(mint_time / 1000 / 86400 / 30))
)
CREATE TABLE nft_collections ( blockchain.text, contract_address.text, name.text, symbol.text, deploy_block_number.bigint, deploy_block_time.bigint, erc_type.text, owner.text, traits.text, description.text, slug.text, media_info.text, image_url.text, banner_image_url.text, updated_at.bigint, banner.text, token_count.bigint, floor_price.text, floor_price_symbol.text, floor_price_contract.text, pk.integer )
CREATE TABLE token_prices ( uuid varchar(36) NOT NULL, blockchain varchar(36) NOT NULL, address varchar(42) NOT NULL, decimals bigint NOT NULL, symbol varchar(36) NOT NULL, price real NOT NULL, timestamp timestamp(6) NOT NULL )
CREATE TABLE erc20_approval ( block_number bigint NOT NULL, block_timestamp timestamp(6) NOT NULL, transaction_index integer NOT NULL, transaction_hash varchar NOT NULL, log_index integer NOT NULL, contract_address varchar NOT NULL, pk integer NOT NULL )
CREATE TABLE token_info ( block_timestamp timestamp(3) NOT NULL, block_number bigint NOT NULL, tx_index integer NOT NULL, tx_hash varchar(66) NOT NULL, tick varchar NOT NULL, max_supply decimal(38,0) NOT NULL, lim decimal(38,0) NOT NULL, wlim decimal(38,0) NOT NULL, dec integer NOT NULL, creator varchar(42) NOT NULL )
CREATE TABLE mud_holesky_redstone (
    address varchar NOT NULL, -- address fields for the functionType  in contract
    table_id varchar NOT NULL, -- table_id fields for the functionType  in contract
    key_bytes varchar NOT NULL, -- key_bytes fields for the functionType  in contract
    key0 varchar NOT NULL, -- key0 fields for the functionType  in contract
    key1 varchar NOT NULL, -- key1 fields for the functionType  in contract
    static_data varchar NOT NULL, -- static_data fields for the functionType  in contract
    encoded_lengths varchar NOT NULL, -- encoded_lengths fields for the functionType  in contract
    dynamic_data varchar NOT NULL, -- dynamic_data fields for the functionType  in contract
    is_deleted boolean NOT NULL, -- is_deleted fields for the functionType  in contract
    block_number bigint NOT NULL, -- Block number uniquely identifying the block
    log_index bigint NOT NULL  -- Index of the log within the transaction
)
CREATE TABLE token_info_bitcoin ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash varchar, tick varchar, max_supply decimal, lim decimal, wlim decimal, dec integer, creator varchar )
CREATE TABLE token_info_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash text, tick text, max_supply decimal, lim decimal, wlim decimal, dec integer, creator text, minted decimal, holders decimal, txs decimal, updated_timestamp timestamp, completed_timestamp timestamp, id text )


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

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

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

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

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

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

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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE project_fundraising_record ( id character varying(32) NOT NULL, project_id character varying(32) NOT NULL, project_name character varying(128) NOT NULL, rounds_name character varying(32), investment_value numeric(38,14), investment_date character varying(128), introduction character varying(128), valuation numeric(38,14) )
CREATE TABLE token_basic_info ( coin_id text, token_name text, token_symbol text, token_address text, chain text, price numeric, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, highest_price_24h numeric, lowest_price_24h numeric, market_cap numeric, market_cap_rank numeric, market_cap_change_percentage_24h text, total_volume text, narrative text, trend_rank numeric )
 "CREATE TABLE narrative_info (",
    "narrative character varying(512) NOT NULL, -- the id of narrative",
    "top_3_coins text, -- the top 3 tokens in the narrative",
    "price_change_percentage_1h double precision, -- change in value divided by the absolute price value of the original token price in 1 hour in the narrative",
    "price_change_percentage_24h double precision, -- change in value divided by the absolute price value of the original token price in 24 hours in the narrative",
    "price_change_percentage_7d double precision, -- change in value divided by the absolute price value of the original token price in 7 days in the narrative",
    "market_cap double precision, -- the market cap of the narrative",
    "volume_24h double precision, -- the trade volume of the narrative",
    "trend_rank bigint, -- the trending rank of the narrative, value 1 expresses the most popular narrative",
    "token_num bigint, -- total token number in the narrative",
    ",PRIMARY KEY (narrative));"

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

CREATE TABLE smart_money_token_performance ( token_address text, token_symbol text, pnl numeric, net_flow numeric, avg_cost numeric, price numeric, realized_ratio numeric, roi numeric, chain text )
CREATE TABLE smart_money_token_inflow ( token_address text, token_symbol text, token_amount numeric, usd_value numeric, avg_price numeric, type numeric, address_amount numeric, narrative text, chain text )


[User] List all insurance products that have a base premium greater than 1000 and are currently active, showing product name, type, and base premium.

[Assistant] SELECT product_name, product_type, base_premium FROM insurance.insurance_products WHERE base_premium > 1000 AND is_active = TRUE

[User] Now, find policies associated with these products that were issued in 2024, showing the policy number and its premium amount.

[Assistant] SELECT p.policy_number, p.premium_amount FROM insurance.policies AS p JOIN insurance.insurance_products AS ip ON p.product_id = ip.product_id WHERE ip.base_premium > 1000 AND ip.is_active = TRUE AND date_part('year', p.issued_at) = 2024

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


[User] List all pairs of clients who registered on the same day, showing each client's first_name, last_name, and the registration date.

[Assistant] SELECT c1.first_name AS first_name_1, c1.last_name AS last_name_1, c2.first_name AS first_name_2, c2.last_name AS last_name_2, DATE(c1.date_registered) AS registration_date FROM legal_services.clients c1 JOIN legal_services.clients c2 ON DATE(c1.date_registered) = DATE(c2.date_registered) AND c1.client_id < c2.client_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.clients ( client_id text, first_name text, last_name text, company_name text, email text, phone text, address text, date_registered timestamp, status text )


[User] Show me a list of comments and the names of hashtags associated with the posts those comments are on.

[Assistant] SELECT T1.comment_id, T3.tag_name FROM comments AS T1 JOIN post_hashtags AS T2 ON T1.post_id = T2.post_id JOIN hashtags AS T3 ON T2.hashtag_id = T3.hashtag_id;

[User] Can you also include the content of the comment and filter the results to only show comments on posts tagged with 'photography'?

[Assistant] SELECT T1.comment_id, T1.content, T3.tag_name FROM comments AS T1 JOIN post_hashtags AS T2 ON T1.post_id = T2.post_id JOIN hashtags AS T3 ON T2.hashtag_id = T3.hashtag_id WHERE T3.tag_name = 'photography';

[User] Please only list comments that are top-level, meaning they are not replies to other comments.

[Assistant] SELECT T1.comment_id, T1.content, T3.tag_name FROM comments AS T1 JOIN post_hashtags AS T2 ON T1.post_id = T2.post_id JOIN hashtags AS T3 ON T2.hashtag_id = T3.hashtag_id WHERE T3.tag_name = 'photography' AND T1.parent_comment_id IS NULL;

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


[User] Which narrative and chain combination saw the highest total USD buy value in the first half of 2023? Also list the total token amount bought for each.

[Assistant]
SELECT narrative, chain, SUM(usd_value) AS total_usd_bought, SUM(token_amount) AS total_token_bought
FROM smart_money_token_inflow
WHERE type = 1 AND to_char(cast(token_address AS text), 'YYYY-MM-DD') >= '2023-01-01'
  AND to_char(cast(token_address AS text), 'YYYY-MM-DD') <= '2023-06-30'
GROUP BY narrative, chain
ORDER BY total_usd_bought DESC
LIMIT 1;

[User] Can you show the top 5 combinations instead of just the top one?

[Assistant]
SELECT narrative, chain, SUM(usd_value) AS total_usd_bought, SUM(token_amount) AS total_token_bought
FROM smart_money_token_inflow
WHERE type = 1 AND to_char(cast(token_address AS text), 'YYYY-MM-DD') >= '2023-01-01'
  AND to_char(cast(token_address AS text), 'YYYY-MM-DD') <= '2023-06-30'
GROUP BY narrative, chain
ORDER BY total_usd_bought DESC
LIMIT 5;

[User] Please add the average price paid for each narrative-chain pair in the result.

[Assistant]
SELECT narrative, chain, SUM(usd_value) AS total_usd_bought, SUM(token_amount) AS total_token_bought, AVG(avg_price) AS avg_price
FROM smart_money_token_inflow
WHERE type = 1 AND to_char(cast(token_address AS text), 'YYYY-MM-DD') >= '2023-01-01'
  AND to_char(cast(token_address AS text), 'YYYY-MM-DD') <= '2023-06-30'
GROUP BY narrative, chain
ORDER BY total_usd_bought DESC
LIMIT 5;

[User] Now limit only to combinations where the total token amount bought is greater than 1000.

[Assistant]
SELECT narrative, chain, SUM(usd_value) AS total_usd_bought, SUM(token_amount) AS total_token_bought, AVG(avg_price) AS avg_price
FROM smart_money_token_inflow
WHERE type = 1 AND to_char(cast(token_address AS text), 'YYYY-MM-DD') >= '2023-01-01'
  AND to_char(cast(token_address AS text), 'YYYY-MM-DD') <= '2023-06-30'
GROUP BY narrative, chain
HAVING SUM(token_amount) > 1000
ORDER BY total_usd_bought 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 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] Show each contract's address along with the total number of events it has emitted and the total number of transactions sent to it.

[Assistant]
SELECT
  c.address,
  COUNT(e.event_id) AS event_count,
  COUNT(t.transaction_id) AS tx_count
FROM web3.contracts c
LEFT JOIN web3.events e
  ON c.contract_id = e.contract_id
LEFT JOIN web3.transactions t
  ON c.address = t.to_address
GROUP BY c.address;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.contracts (
    contract_id character varying(64) NOT NULL,  -- unique identifier for the contract
    address character varying(128) NOT NULL, -- address of the deployed contract
    abi text NOT NULL, -- application binary interface of the contract
    bytecode text NOT NULL, -- bytecode of the contract
    deployer_address character varying(128) NOT NULL, -- address of the deployer
    deployed_at timestamp NOT NULL, -- time when the contract was deployed
    network_id character varying(64) NOT NULL, -- identifier of the network where the contract is deployed
    status character varying(32) NOT NULL, -- status of the contract (e.g., active, deprecated)
    PRIMARY KEY (contract_id)
)
CREATE TABLE web3.events (
    event_id character varying(64) NOT NULL,  -- unique identifier for the event
    contract_id character varying(64) NOT NULL, -- identifier of the contract emitting the event
    event_name character varying(128) NOT NULL, -- name of the event
    data text NOT NULL, -- data payload of the event
    emitted_at timestamp NOT NULL, -- time when the event was emitted
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction that triggered the event
    log_index integer NOT NULL, -- index of the event log in the transaction
    PRIMARY KEY (event_id)
)
CREATE TABLE web3.transactions (
    transaction_id character varying(64) NOT NULL,  -- unique identifier for the transaction
    from_address character varying(128) NOT NULL, -- address of the sender
    to_address character varying(128), -- address of the receiver (can be null for contract deployment)
    value numeric(38,14) NOT NULL, -- value transferred
    gas_used integer NOT NULL, -- amount of gas used by the transaction
    gas_price numeric(38,14) NOT NULL, -- price of gas at the time of the transaction
    block_number integer NOT NULL, -- block number containing the transaction
    timestamp timestamp NOT NULL, -- time when the transaction was mined
    input_data text, -- input data of the transaction (can be null)
    status character varying(32) NOT NULL, -- status of the transaction (e.g., success, failed)
    nonce integer NOT NULL, -- nonce of the sender at the time of the transaction
    PRIMARY KEY (transaction_id)
)
CREATE TABLE web3.tokens (
    token_id character varying(64) NOT NULL,  -- unique identifier for the token
    contract_address character varying(128) NOT NULL, -- address of the token contract
    token_name character varying(128) NOT NULL, -- name of the token
    token_symbol character varying(32) NOT NULL, -- symbol of the token
    decimals integer NOT NULL, -- number of decimals for the token
    total_supply numeric(38,14) NOT NULL, -- total supply of the token
    PRIMARY KEY (token_id)
)
CREATE TABLE web3.token_transfers (
    transfer_id character varying(64) NOT NULL,  -- unique identifier for the transfer
    token_id character varying(64) NOT NULL, -- identifier of the token being transferred
    from_address character varying(128) NOT NULL, -- address of the sender
    to_address character varying(128) NOT NULL, -- address of the receiver
    value numeric(38,14) NOT NULL, -- amount of tokens transferred
    transaction_id character varying(64) NOT NULL, -- identifier of the transaction containing the transfer
    log_index integer NOT NULL, -- index of the transfer log in the transaction
    PRIMARY KEY (transfer_id)
)
CREATE TABLE web3.users (
    user_id character varying(64) NOT NULL,  -- unique identifier for the user
    username character varying(128) NOT NULL, -- username of the user
    email character varying(128) NOT NULL, -- email address of the user
    password_hash text NOT NULL, -- hashed password of the user
    created_at timestamp NOT NULL, -- time when the user account was created
    PRIMARY KEY (user_id)
)


[User] Find all nodes that were last seen in the last 30 days and have port numbers between 8000 and 9000.

[Assistant] SELECT node_id, ip_address, port FROM blockchain.nodes WHERE last_seen >= NOW() - INTERVAL '30 days' AND port BETWEEN 8000 AND 9000

[User] Can you also show the count of transactions sent from wallet addresses that share the same IP as these nodes?

[Assistant] This query isn't possible with the current schema as there's no relationship between nodes IP addresses and wallet addresses.

[User] Then just show me nodes that share the same IP address along with how many nodes share each IP.

[Assistant] SELECT ip_address, COUNT(*) as node_count FROM blockchain.nodes GROUP BY ip_address HAVING COUNT(*) > 1

[User] Now filter this to only show IP addresses with more than 3 nodes and include the earliest and latest last_seen timestamps.

[Assistant] SELECT ip_address, COUNT(*) as node_count, MIN(last_seen) as earliest_seen, MAX(last_seen) as latest_seen FROM blockchain.nodes GROUP BY ip_address HAVING COUNT(*) > 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 blockchain.transactions ( transaction_id text, block_id text, sender_address text, receiver_address text, amount numeric, timestamp timestamp, signature text )
CREATE TABLE blockchain.nodes ( node_id text, ip_address text, port integer, last_seen timestamp )
CREATE TABLE blockchain.wallets ( wallet_id text, user_id text, address_id text, private_key text )
CREATE TABLE blockchain.smart_contracts ( contract_id text, creator_address text, code text, timestamp timestamp )


[User] Find documents that have the same document_name but are associated with different cases. Show the document name and the two different case IDs.

[Assistant] SELECT d1.document_name, d1.case_id AS case_id_1, d2.case_id AS case_id_2 FROM legal_services.documents AS d1 JOIN legal_services.documents AS d2 ON d1.document_name = d2.document_name WHERE d1.case_id <> d2.case_id AND d1.document_id < d2.document_id;

[User] Actually, only show pairs where at least one of the documents is of document_type 'Contract'.

[Assistant] SELECT d1.document_name, d1.case_id AS case_id_1, d2.case_id AS case_id_2 FROM legal_services.documents AS d1 JOIN legal_services.documents AS d2 ON d1.document_name = d2.document_name WHERE d1.case_id <> d2.case_id AND d1.document_id < d2.document_id AND (d1.document_type = 'Contract' OR d2.document_type = 'Contract');

[User] Also, only include pairs where both documents were uploaded in the year 2024.

[Assistant] SELECT d1.document_name, d1.case_id AS case_id_1, d2.case_id AS case_id_2 FROM legal_services.documents AS d1 JOIN legal_services.documents AS d2 ON d1.document_name = d2.document_name WHERE d1.case_id <> d2.case_id AND d1.document_id < d2.document_id AND (d1.document_type = 'Contract' OR d2.document_type = 'Contract') AND YEAR(d1.upload_timestamp) = 2024 AND YEAR(d2.upload_timestamp) = 2024;

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


[User] 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] For each NFT collection on Ethereum, calculate the number of unique tokens and the average rarity_score. Show contract_address, token_count, and avg_rarity.

[Assistant]
SELECT nm.contract_address,
       COUNT(DISTINCT nm.token_id) AS token_count,
       AVG(nm.rarity_score) AS avg_rarity
FROM nft_metadata nm
WHERE nm.blockchain = 'Ethereum'
GROUP BY nm.contract_address
ORDER BY avg_rarity DESC;

[User] Now only include collections with token_count > 100 and avg_rarity > 80.

[Assistant]
SELECT nm.contract_address,
       COUNT(DISTINCT nm.token_id) AS token_count,
       AVG(nm.rarity_score) AS avg_rarity
FROM nft_metadata nm
WHERE nm.blockchain = 'Ethereum'
GROUP BY nm.contract_address
HAVING COUNT(DISTINCT nm.token_id) > 100
   AND AVG(nm.rarity_score) > 80
ORDER BY avg_rarity DESC;

[User] Also include the number of unique holders from nft_holders by joining on contract_address.

[Assistant]
WITH stats AS (
  SELECT contract_address,
         COUNT(DISTINCT token_id) AS token_count,
         AVG(rarity_score) AS avg_rarity
  FROM nft_metadata
  WHERE blockchain = 'Ethereum'
  GROUP BY contract_address
  HAVING COUNT(DISTINCT token_id) > 100
     AND AVG(rarity_score) > 80
)
SELECT s.contract_address,
       s.token_count,
       s.avg_rarity,
       COUNT(DISTINCT nh.wallet_address) AS holder_count
FROM stats s
JOIN nft_holders nh ON s.contract_address = nh.contract_address
GROUP BY s.contract_address, s.token_count, s.avg_rarity
ORDER BY s.avg_rarity DESC;

[User] Finally, sort by holder_count descending and limit to top 10.

[Assistant]
WITH stats AS (
  SELECT contract_address,
         COUNT(DISTINCT token_id) AS token_count,
         AVG(rarity_score) AS avg_rarity
  FROM nft_metadata
  WHERE blockchain = 'Ethereum'
  GROUP BY contract_address
  HAVING COUNT(DISTINCT token_id) > 100
     AND AVG(rarity_score) > 80
)
SELECT s.contract_address,
       s.token_count,
       s.avg_rarity,
       COUNT(DISTINCT nh.wallet_address) AS holder_count
FROM stats s
JOIN nft_holders nh ON s.contract_address = nh.contract_address
GROUP BY s.contract_address, s.token_count, s.avg_rarity
ORDER BY holder_count DESC
LIMIT 10;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE token_metas ( block_timestamp.timestamp, block_number.bigint, transaction_hash.text, transaction_index.bigint, from_address.text, contract_address.text, symbol.text, total_supply.text, name.text, decimals.bigint, is_erc20.integer, is_erc721.integer, is_erc1155.integer, is_proxy.integer, extra_info.text, pk.integer )
CREATE TABLE erc1155_approval_for_all ( block_number.bigint, block_timestamp.timestamp, transaction_index.integer, transaction_hash.text, log_index.integer, contract_address.text )
CREATE TABLE erc20_balances ( block_number.bigint, contract_address.text, wallet_address.text, amount.text, pk.text )
CREATE TABLE erc20_balances_historical ( block_number.bigint, contract_address.text, wallet_address.text, amount.text, pk.integer )
CREATE TABLE nft_holders ( block_number.bigint, contract_address.text, wallet_address.text, token_id.text, contract_type.text, amount.text, pk.text )
CREATE TABLE sui_coins ( object_id.text, status.text, coin_type.text, balance.text, owner.text )
CREATE TABLE sui_coins_metadata ( object_id.text, coin_type.text, status.text, decimals.bigint, description.text, icon_url.text, symbol.text, name.text )
CREATE TABLE sui_nfts ( object_id.text, status.text, collection_type.text, package_id.text, previous_transaction.text, display.text, owner.text, name.text )
CREATE TABLE nft_metadata ( blockchain.text, contract_address.text, token_id.text, contract_name.text, erc_type.text, amount.bigint, minter.text, owner.text, mint_block_number.bigint, mint_time.bigint, mint_transaction_hash.text, mint_price.text, token_uri.text, metadata.text, name.text, image_uri.text, traits.text, updated_at.bigint, status.text, rarity_score.real, rarity_rank.integer, unique_attribute_count.integer, pk.integer )
CREATE TABLE token_prices ( uuid.text, blockchain.text, address.text, decimals.bigint, symbol.text, price.real, timestamp.timestamp )
CREATE TABLE token_prices_latest ( blockchain.text, address.text, decimals.bigint, symbol.text, price.real, timestamp.timestamp )
CREATE TABLE token_info ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, tick.text, max_supply.decimal, lim.decimal, wlim.decimal, dec.integer, creator.text )
CREATE TABLE token_activities ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_balances_bitcoin ( block_number.bigint, block_timestamp.timestamp, tick.text, wallet_address.text, total_supply.text, amount.text )
CREATE TABLE token_info_bitcoin ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, tick.text, max_supply.decimal, lim.decimal, wlim.decimal, dec.integer, creator.text )
CREATE TABLE token_activities_bitcoin ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_activities_avalanche ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_balances_avalanche ( block_number.bigint, block_timestamp.timestamp, tick.text, wallet_address.text, total_supply.decimal, amount.decimal )
CREATE TABLE token_info_avalanche ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, tick.text, max_supply.decimal, lim.decimal, wlim.decimal, dec.integer, creator.text, minted.decimal, holders.decimal, txs.decimal, updated_timestamp.timestamp, completed_timestamp.timestamp, id.text )


[User] Show me the usernames and email addresses of users who have used hashtags in their posts along with the hashtag names they have used.

[Assistant]
SELECT u.username, u.email, h.tag_name
FROM social_media.users u
JOIN social_media.posts p ON u.user_id = p.user_id
JOIN social_media.post_hashtags ph ON p.post_id = ph.post_id
JOIN social_media.hashtags h ON ph.hashtag_id = h.hashtag_id
GROUP BY u.username, u.email, h.tag_name;

[User] Only include users who have used more than one unique hashtag in their posts.

[Assistant]
SELECT u.username, u.email, COUNT(DISTINCT h.tag_name) AS unique_hashtag_count
FROM social_media.users u
JOIN social_media.posts p ON u.user_id = p.user_id
JOIN social_media.post_hashtags ph ON p.post_id = ph.post_id
JOIN social_media.hashtags h ON ph.hashtag_id = h.hashtag_id
GROUP BY u.username, u.email
HAVING COUNT(DISTINCT h.tag_name) > 1;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users ( user_id text, username text, email text, password_hash text, full_name text, profile_picture_url text, bio text, location text, created_at timestamp, updated_at timestamp, is_verified boolean )
CREATE TABLE social_media.posts ( post_id.text, user_id.text, content.text, media_url.text, media_type.text, created_at.timestamp, updated_at.timestamp, visibility.text, location_lat.numeric, location_lon.numeric )
CREATE TABLE social_media.likes ( like_id text, user_id text, post_id text, comment_id text, created_at timestamp )
CREATE TABLE social_media.follows ( follow_id character varying(64) NOT NULL, follower_user_id character varying(64) NOT NULL, following_user_id character varying(64) NOT NULL, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (follow_id), CONSTRAINT unique_follow UNIQUE (follower_user_id, following_user_id) )
CREATE TABLE social_media.hashtags ( hashtag_id character varying(64) NOT NULL, tag_name character varying(100) NOT NULL UNIQUE, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (hashtag_id) )
CREATE TABLE social_media.post_hashtags ( post_hashtag_id character varying(64) NOT NULL, post_id character varying(64) NOT NULL, hashtag_id character varying(64) NOT NULL, PRIMARY KEY (post_hashtag_id), CONSTRAINT unique_post_hashtag UNIQUE (post_id, hashtag_id) )
CREATE TABLE social_media.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] Show each user's username and the total number of notifications they have received.

[Assistant] SELECT T1.username, count(T2.notification_id) FROM users AS T1 LEFT JOIN notifications AS T2 ON T1.user_id = T2.user_id GROUP BY T1.user_id, T1.username

[User] Filter the results to only include users who have received notifications.

[Assistant] SELECT T1.username, count(T2.notification_id) FROM users AS T1 JOIN notifications AS T2 ON T1.user_id = T2.user_id GROUP BY T1.user_id, T1.username

[User] Only show users who have received notifications AND have at least one log entry.

[Assistant] SELECT T1.username, count(distinct T2.notification_id), count(distinct T3.log_id) FROM users AS T1 JOIN notifications AS T2 ON T1.user_id = T2.user_id JOIN logs AS T3 ON T1.user_id = T3.user_id GROUP BY T1.user_id, T1.username

[User] The previous query excluded users who have notifications but no logs, or logs but no notifications. Please include all users who have either received notifications OR have logged an action. Show their username, total notification count (0 if none), and total log count (0 if none).

[Assistant] SELECT T1.username, count(distinct T2.notification_id), count(distinct T3.log_id) FROM users AS T1 LEFT JOIN notifications AS T2 ON T1.user_id = T2.user_id LEFT JOIN logs AS T3 ON T1.user_id = T3.user_id GROUP BY T1.user_id, T1.username

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.users ( user_id.text, username.text, email.text, password_hash.text, created_at.timestamp )
CREATE TABLE trading_platform.peers ( peer_id.text, ip_address.text, port.integer, last_seen.timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, key character varying(128) NOT NULL, value text NOT NULL, PRIMARY KEY (metadata_id) )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id.text, user_id.text, status.text, reviewed_at.timestamp )
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, user_id text, message text, sent_at timestamp, read_at timestamp )