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 hospitality_technology.reservations ( reservation_id.text, property_id.text, guest_id.text, room_id.text, room_type_id.text, check_in_date.date, check_out_date.date, actual_check_in_ts.timestamp, actual_check_out_ts.timestamp, num_adults.integer, num_children.integer, status.text, booking_source.text, rate_plan_id.text, total_amount.numeric, amount_paid.numeric, special_requests.text, created_at.timestamp, updated_at.timestamp )
##Table Structure
CREATE TABLE insurance.agents ( agent_id text PRIMARY KEY, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )
##Table Structure
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id.text, patient_id.text, plan_id.text, policy_number.text, group_number.text, subscriber_name.text, effective_date.date, expiration_date.date, is_primary.boolean )
##Table Structure
CREATE TABLE hospitality_technology.reservations ( reservation_id.text, property_id.text, guest_id.text, room_id.text, room_type_id.text, check_in_date.date, check_out_date.date, actual_check_in_ts.timestamp, actual_check_out_ts.timestamp, num_adults.integer, num_children.integer, status.text, booking_source.text, rate_plan_id.text, total_amount.numeric, amount_paid.numeric, special_requests.text, created_at.timestamp, updated_at.timestamp )
##Table Structure
CREATE TABLE government_services.citizens ( citizen_id text PRIMARY KEY, national_id_number text, first_name text, last_name text, date_of_birth date, gender text, primary_address text, contact_email text, contact_phone text, registration_date timestamp, is_verified boolean )
CREATE TABLE government_services.agencies ( agency_id text PRIMARY KEY, agency_name text, jurisdiction_level text, primary_contact_email text, main_phone_number text, website_url text, established_date date, parent_agency_id text )
CREATE TABLE government_services.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text PRIMARY KEY, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.service_locations ( location_id text PRIMARY KEY, agency_id text, location_name text, address text, city text, state text, postal_code text, latitude numeric, longitude numeric, operating_hours text, contact_phone text, is_accessible boolean )
CREATE TABLE government_services.appointments ( appointment_id text PRIMARY KEY, citizen_id text, employee_id text, location_id text, service_id text, scheduled_start_time timestamp, scheduled_end_time timestamp, purpose text, status text, booking_method text, created_at timestamp, notes text )
##Table Structure
CREATE TABLE social_media.posts ( post_id character varying(64) NOT NULL, user_id character varying(64) NOT NULL, content text, media_url text, media_type character varying(20), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, visibility character varying(20) NOT NULL DEFAULT 'public', location_lat numeric(9,6), location_lon numeric(9,6), PRIMARY KEY (post_id) )
##Table Structure
CREATE TABLE healthcare.medications ( medication_id text PRIMARY KEY, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )

[User] List properties where actual check-in occurred later than the scheduled check-in date. Show the property ID and the count of such reservations.

[Assistant] SELECT property_id, COUNT(*) FROM reservations WHERE actual_check_in_ts > check_in_date GROUP BY property_id;

[User] Now, only show properties where the delay happened for more than 5 reservations.

[Assistant] SELECT property_id, COUNT(*) FROM reservations WHERE actual_check_in_ts > check_in_date GROUP BY property_id HAVING COUNT(*) > 5;

[User] Find all agents with their managers where the agent's commission rate is above 0.10.

[Assistant]
SELECT a.agent_id,
       a.first_name || ' ' || a.last_name AS agent_name,
       m.agent_id AS manager_id,
       m.first_name || ' ' || m.last_name AS manager_name
FROM insurance.agents a
JOIN insurance.agents m ON a.manager_id = m.agent_id
WHERE a.commission_rate > 0.1;

[User] Exclude any pairs where the manager is not currently active.

[Assistant]
SELECT a.agent_id,
       a.first_name || ' ' || a.last_name AS agent_name,
       m.agent_id AS manager_id,
       m.first_name || ' ' || m.last_name AS manager_name
FROM insurance.agents a
JOIN insurance.agents m ON a.manager_id = m.agent_id
WHERE a.commission_rate > 0.1
  AND m.status = 'active';

[User] I need a list showing each patient along with their current primary insurance policy number and their immediately previous primary policy number.

[Assistant]
SELECT ci.patient_id,
       ci.policy_number AS current_policy,
       pi.policy_number AS previous_policy
FROM healthcare.patient_insurance ci
LEFT JOIN healthcare.patient_insurance pi
  ON ci.patient_id = pi.patient_id
  AND pi.is_primary = TRUE
  AND pi.effective_date < ci.effective_date
WHERE ci.is_primary = TRUE
  AND (ci.expiration_date IS NULL OR ci.expiration_date > CURRENT_DATE)
  AND pi.effective_date = (
      SELECT MAX(pii.effective_date)
      FROM healthcare.patient_insurance pii
      WHERE pii.patient_id = ci.patient_id
        AND pii.is_primary = TRUE
        AND pii.effective_date < ci.effective_date
  );

[User] Actually, I only want to include previous policies that have an expiration_date set.

[Assistant]
SELECT ci.patient_id,
       ci.policy_number AS current_policy,
       pi.policy_number AS previous_policy
FROM healthcare.patient_insurance ci
LEFT JOIN healthcare.patient_insurance pi
  ON ci.patient_id = pi.patient_id
  AND pi.is_primary = TRUE
  AND pi.expiration_date IS NOT NULL
  AND pi.effective_date = (
      SELECT MAX(pii.effective_date)
      FROM healthcare.patient_insurance pii
      WHERE pii.patient_id = ci.patient_id
        AND pii.is_primary = TRUE
        AND pii.expiration_date IS NOT NULL
        AND pii.effective_date < ci.effective_date
  )
WHERE ci.is_primary = TRUE
  AND (ci.expiration_date IS NULL OR ci.expiration_date > CURRENT_DATE);

[User] Show me each guest's reservation count and average stay length in days.

[Assistant]
SELECT guest_id,
       COUNT(*) AS reservation_count,
       AVG(check_out_date - check_in_date) AS avg_stay_days
FROM hospitality_technology.reservations
GROUP BY guest_id;

[User] Filter to only include guests with more than 3 reservations.

[Assistant]
SELECT guest_id,
       COUNT(*) AS reservation_count,
       AVG(check_out_date - check_in_date) AS avg_stay_days
FROM hospitality_technology.reservations
GROUP BY guest_id
HAVING COUNT(*) > 3;

[User] Also join this with a subquery to display the total amount paid per guest.

[Assistant]
SELECT s.guest_id,
       s.reservation_count,
       s.avg_stay_days,
       p.total_amount_paid
FROM (
  SELECT guest_id,
         COUNT(*) AS reservation_count,
         AVG(check_out_date - check_in_date) AS avg_stay_days
  FROM hospitality_technology.reservations
  GROUP BY guest_id
  HAVING COUNT(*) > 3
) s
JOIN (
  SELECT guest_id,
         SUM(amount_paid) AS total_amount_paid
  FROM hospitality_technology.reservations
  GROUP BY guest_id
) p
  ON s.guest_id = p.guest_id;

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

[Assistant] SELECT DISTINCT T1.first_name, T1.last_name FROM government_services.citizens AS T1 INNER JOIN government_services.documents AS T2 ON T1.citizen_id = T2.citizen_id WHERE T2.expiry_date < CURRENT_DATE;

[User] How many posts are marked with 'unlisted' visibility?

[Assistant] SELECT COUNT(*) FROM social_media.posts WHERE visibility = 'unlisted';

[User] List the medication IDs and names for all entries where the description is missing or empty.

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

[User] For those medications, please also show the manufacturer and sort the results by medication name in ascending order.

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


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 gaming_technology.in_game_items ( item_id.uuid, game_id.uuid, item_name.text, item_type.text, description.text, rarity.text, cost_currency.text, cost_amount.numeric, attributes.jsonb )
##Table Structure
CREATE TABLE healthcare.patients ( patient_id text PRIMARY KEY, first_name text, last_name text, date_of_birth date, gender text, address text, phone_number text, email text, emergency_contact_name text, emergency_contact_phone text, created_at timestamp, updated_at timestamp )
CREATE TABLE healthcare.doctors ( doctor_id text PRIMARY KEY, first_name text, last_name text, specialty text, license_number text, phone_number text, email text, hospital_affiliation_id text, created_at timestamp, updated_at timestamp )
CREATE TABLE healthcare.medical_records ( record_id text PRIMARY KEY, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )
CREATE TABLE healthcare.diagnoses ( diagnosis_id text 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 PRIMARY KEY, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )
CREATE TABLE healthcare.prescriptions ( prescription_id text PRIMARY KEY, record_id text, patient_id text, doctor_id text, medication_id text, dosage text, frequency text, route text, start_date date, end_date date, quantity_dispensed numeric, refills_allowed int, prescription_date timestamp )
##Table Structure
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)
)
##Table Structure
CREATE TABLE insurance.claims ( claim_id text PRIMARY KEY, policy_id text, customer_id text, incident_date timestamp, reported_date timestamp, description text, estimated_loss numeric, status text, settlement_amount numeric, settlement_date date, claim_handler_id text, police_report_number text )
CREATE TABLE insurance.insurance_products ( product_id text PRIMARY KEY, product_name text, product_type text, description text, base_premium numeric, coverage_details text, underwriting_rules text, is_active boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE insurance.agents ( agent_id text 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 )
##Table Structure
CREATE TABLE insurance.claim_documents (
    document_id character varying(64) NOT NULL, -- unique identifier for the document
    claim_id character varying(64) NOT NULL, -- identifier of the claim this document relates to (FK to claims)
    document_type character varying(50) NOT NULL, -- e.g., Police Report, Photo, Invoice, Medical Bill
    file_name character varying(255) NOT NULL, -- original name of the uploaded file
    file_path character varying(512) NOT NULL, -- storage path (e.g., S3 URL, network path)
    file_size_bytes integer, -- size of the file in bytes
    mime_type character varying(100), -- MIME type of the file (e.g., 'image/jpeg', 'application/pdf')
    uploaded_by character varying(64), -- identifier of the user/system who uploaded (FK to users/customers)
    uploaded_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- time of upload
    description text, -- optional description of the document
    PRIMARY KEY (document_id)
)
##Table Structure
CREATE TABLE healthcare.appointments (
    appointment_id character varying(64) NOT NULL, -- unique identifier for the appointment
    patient_id character varying(64) NOT NULL, -- FK to patients table
    doctor_id character varying(64) NOT NULL, -- FK to doctors table
    appointment_time timestamp with time zone NOT NULL, -- date and time of the appointment
    duration_minutes integer NOT NULL, -- expected duration in minutes
    reason text, -- reason for the visit
    status character varying(32) NOT NULL, -- e.g., Scheduled, Completed, Cancelled, No-show
    location_id character varying(64), -- FK to a potential locations/clinics table
    notes text, -- notes related to scheduling
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (appointment_id)
)

[User] I want to see pairs of items from the same game that share the same rarity but are of different types. Show each pair's names and types.

[Assistant]
SELECT a.game_id,
       a.item_name AS item1_name,
       a.item_type AS item1_type,
       b.item_name AS item2_name,
       b.item_type AS item2_type
FROM gaming_technology.in_game_items a
JOIN gaming_technology.in_game_items b
  ON a.game_id = b.game_id
 AND a.rarity = b.rarity
 AND a.item_type <> b.item_type
 AND a.item_id < b.item_id;

[User] Also include cost_currency and cost_amount for each item in the output.

[Assistant]
SELECT a.game_id,
       a.item_name AS item1_name,
       a.item_type AS item1_type,
       a.cost_currency AS item1_currency,
       a.cost_amount   AS item1_cost,
       b.item_name AS item2_name,
       b.item_type AS item2_type,
       b.cost_currency AS item2_currency,
       b.cost_amount   AS item2_cost
FROM gaming_technology.in_game_items a
JOIN gaming_technology.in_game_items b
  ON a.game_id = b.game_id
 AND a.rarity = b.rarity
 AND a.item_type <> b.item_type
 AND a.item_id < b.item_id;

[User] List the medication names which have never been prescribed to any patient.

[Assistant]
SELECT m.medication_name
FROM healthcare.medications m
LEFT JOIN healthcare.prescriptions p ON m.medication_id = p.medication_id
WHERE p.prescription_id IS NULL;

[User] Find pairs of token transfers within the same transaction and for the same token, where the value of one transfer is exactly twice the value of the other. Show the transaction ID, token ID, and both transfer IDs and their values.

[Assistant]
SELECT
  t1.transaction_id,
  t1.token_id,
  t1.transfer_id AS transfer_id_1,
  t1.value AS value_1,
  t2.transfer_id AS transfer_id_2,
  t2.value AS value_2
FROM web3.token_transfers AS t1
JOIN web3.token_transfers AS t2
  ON t1.transaction_id = t2.transaction_id
  AND t1.token_id = t2.token_id
  AND t1.transfer_id < t2.transfer_id
WHERE
  t1.value = 2 * t2.value
  OR t2.value = 2 * t1.value;

[User] Show me the product name, product type, and the first and last name of all agents who have sold policies of each insurance product.

[Assistant]
SELECT ip.product_name, ip.product_type, a.first_name, a.last_name
FROM insurance.policies p
JOIN insurance.insurance_products ip ON p.product_id = ip.product_id
JOIN insurance.agents a ON p.agent_id = a.agent_id;

[User] Find the earliest uploaded document for each claim. Show the claim_id, document_id, file_name, and uploaded_at.

[Assistant]
SELECT cd.claim_id, cd.document_id, cd.file_name, cd.uploaded_at
FROM insurance.claim_documents cd
INNER JOIN (
  SELECT claim_id, MIN(uploaded_at) AS min_uploaded_at
  FROM insurance.claim_documents
  GROUP BY claim_id
) latest_docs
ON cd.claim_id = latest_docs.claim_id AND cd.uploaded_at = latest_docs.min_uploaded_at;

[User] List the total number of appointments for each status and also show the latest appointment_time for each status.

[Assistant]
SELECT status, COUNT(*) AS total_appointments, MAX(appointment_time) AS latest_appointment_time
FROM healthcare.appointments
GROUP BY status;


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 narrative_info ( narrative text, top_3_coins text, price_change_percentage_1h numeric, price_change_percentage_24h numeric, price_change_percentage_7d numeric, market_cap numeric, volume_24h numeric, trend_rank numeric, token_num numeric )
CREATE TABLE cex_token_balance ( snapshot_time text, chain text, address text, exchange text, token_address text, token_symbol text, balance numeric, usd_value numeric, price numeric )
CREATE TABLE smart_money_profit ( address text, rank numeric, profit numeric, roi numeric, realized_ratio numeric, most_profit_token text, last_trade_time text, chain text )
CREATE TABLE smart_money_token_inflow ( token_address text, token_symbol text, token_amount numeric, usd_value numeric, avg_price numeric, type numeric, address_amount numeric, narrative text, chain text )
##Table Structure
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) )
##Table Structure
CREATE TABLE insurance.claims ( claim_id text PRIMARY KEY, policy_id text, customer_id text, incident_date timestamp, reported_date timestamp, description text, estimated_loss numeric, status text, settlement_amount numeric, settlement_date date, claim_handler_id text, police_report_number text )
CREATE TABLE insurance.insurance_products ( product_id text PRIMARY KEY, 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 )
##Table Structure
CREATE TABLE transportation.routes ( route_id text, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes integer, type text )
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id.text, license_plate.text, vin.text, make.text, model.text, year.integer, type.text, capacity.integer, fuel_type.text, status.text, depot_id.text, acquisition_date.date )
##Table Structure
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 )
##Table Structure
CREATE TABLE legal_services.law_firms ( firm_id text PRIMARY KEY, firm_name text, address text, phone text, website text, founded_date date, managing_partner_id text )
##Table Structure
CREATE TABLE government_services.agencies ( agency_id character varying(64) NOT NULL, agency_name character varying(255) NOT NULL, jurisdiction_level character varying(50) NOT NULL, 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), PRIMARY KEY (agency_id) )
##Table Structure
CREATE TABLE gaming_technology.player_achievements ( player_achievement_id.uuid, player_id.uuid, achievement_id.uuid, unlocked_at.timestamptz )
##Table Structure
CREATE TABLE social_media.conversations ( conversation_id text PRIMARY KEY, created_at timestamp, last_message_at timestamp, is_group_chat bool, group_name text )

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

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

[User] I need to retrieve asset IDs along with their category and website metadata values for assets that have both entries.

[Assistant]
SELECT m_cat.asset_id,
       m_cat.value AS category,
       m_web.value AS website_url
FROM trading_platform.metadata m_cat
JOIN trading_platform.metadata m_web
  ON m_cat.asset_id = m_web.asset_id
WHERE m_cat.key = 'category'
  AND m_web.key = 'website';

[User] Actually, filter to include only those assets where the category value is 'defi'.

[Assistant]
SELECT m_cat.asset_id,
       m_cat.value AS category,
       m_web.value AS website_url
FROM trading_platform.metadata m_cat
JOIN trading_platform.metadata m_web
  ON m_cat.asset_id = m_web.asset_id
WHERE m_cat.key = 'category'
  AND m_web.key = 'website'
  AND m_cat.value = 'defi';

[User] List all insurance products with their product name and base premium, where the product description contains the word 'accident'.

[Assistant] SELECT product_name, base_premium FROM insurance.insurance_products WHERE description ILIKE '%accident%';

[User] Find pairs of distinct routes that share the same destination location but start from different origins. Include the route ID and route number for both routes and the shared destination location ID.

[Assistant]
SELECT
  r1.route_id AS route1_id,
  r1.route_number AS route1_number,
  r2.route_id AS route2_id,
  r2.route_number AS route2_number,
  r1.destination_location_id AS shared_destination_location_id
FROM transportation.routes AS r1
JOIN transportation.routes AS r2
  ON r1.destination_location_id = r2.destination_location_id
  AND r1.route_id < r2.route_id
WHERE
  r1.origin_location_id != r2.origin_location_id;

[User] Find all vehicles that share the same make and model but were manufactured in different years. Show both vehicle IDs, the make, model, and their respective years.

[Assistant]
SELECT v1.vehicle_id AS vehicle1_id,
       v2.vehicle_id AS vehicle2_id,
       v1.make,
       v1.model,
       v1.year AS year1,
       v2.year AS year2
FROM transportation.vehicles v1
JOIN transportation.vehicles v2
  ON v1.make = v2.make
  AND v1.model = v2.model
  AND v1.year <> v2.year
  AND v1.vehicle_id < v2.vehicle_id;

[User] Find the application IDs for applications that have received notifications through both 'Email' and 'SMS' channels.

[Assistant] SELECT application_id FROM government_services.notifications WHERE channel IN ('Email', 'SMS') GROUP BY application_id HAVING COUNT(DISTINCT channel) = 2;

[User] List all pairs of law firms founded in the same year, showing both firm names and their shared founding year.

[Assistant]
SELECT lf1.firm_name AS firm1, lf2.firm_name AS firm2, EXTRACT(YEAR FROM lf1.founded_date) AS founded_year
FROM legal_services.law_firms lf1
JOIN legal_services.law_firms lf2
  ON EXTRACT(YEAR FROM lf1.founded_date) = EXTRACT(YEAR FROM lf2.founded_date)
  AND lf1.firm_id < lf2.firm_id;

[User] Show each agency along with its parent agency’s name and jurisdiction level.

[Assistant] SELECT child.agency_id, child.agency_name, child.jurisdiction_level, parent.agency_name AS parent_agency_name, parent.jurisdiction_level AS parent_jurisdiction_level FROM government_services.agencies AS child LEFT JOIN government_services.agencies AS parent ON child.parent_agency_id = parent.agency_id;

[User] Show me the earliest unlock date for each achievement along with the player_id who unlocked it.

[Assistant] SELECT achievement_id, player_id, MIN(unlocked_at) AS earliest_unlock FROM gaming_technology.player_achievements GROUP BY achievement_id, player_id;

[User] Actually, for each achievement, I only want to see the player who was the very first to unlock it and the corresponding date.

[Assistant] SELECT pa.achievement_id, pa.player_id, pa.unlocked_at AS earliest_unlock FROM gaming_technology.player_achievements pa INNER JOIN ( SELECT achievement_id, MIN(unlocked_at) AS min_unlocked_at FROM gaming_technology.player_achievements GROUP BY achievement_id ) first_unlock ON pa.achievement_id = first_unlock.achievement_id AND pa.unlocked_at = first_unlock.min_unlocked_at;

[User] How many group conversations are there?

[Assistant] SELECT COUNT(*) FROM social_media.conversations WHERE is_group_chat = TRUE;


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 government_services.citizens ( citizen_id character varying(64) NOT NULL, national_id_number character varying(128) NOT NULL UNIQUE, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, date_of_birth date NOT NULL, gender character varying(20), primary_address text NOT NULL, contact_email character varying(128) UNIQUE, contact_phone character varying(32), registration_date timestamp NOT NULL, is_verified boolean DEFAULT false, PRIMARY KEY (citizen_id) )
##Table Structure
CREATE TABLE blockchain.blocks ( block_id.text, previous_block_id.text, timestamp.timestamp, nonce.integer, merkle_root.text, difficulty.integer )
CREATE TABLE blockchain.transactions (
    transaction_id character varying(64) NOT NULL,  -- unique identifier for the transaction
    block_id character varying(64) NOT NULL, -- identifier of the block containing the transaction
    sender_address character varying(128) NOT NULL, -- address of the sender
    receiver_address character varying(128) NOT NULL, -- address of the receiver
    amount numeric(38,14) NOT NULL, -- amount transferred
    timestamp timestamp NOT NULL, -- time when the transaction was created
    signature text NOT NULL, -- digital signature of the transaction
    PRIMARY KEY (transaction_id)
)
CREATE TABLE blockchain.addresses ( address_id character varying(128) NOT NULL, public_key text NOT NULL, balance numeric(38,14) NOT NULL, PRIMARY KEY (address_id) )
CREATE TABLE blockchain.wallets ( wallet_id.text, user_id.text, address_id.text, private_key.text )
CREATE TABLE blockchain.users ( user_id character varying(64) NOT NULL, username character varying(128) NOT NULL, email character varying(128) NOT NULL, password_hash text NOT NULL, PRIMARY KEY (user_id) )
CREATE TABLE blockchain.smart_contracts ( contract_id character varying(64) NOT NULL, creator_address character varying(128) NOT NULL, code text NOT NULL, timestamp timestamp NOT NULL, PRIMARY KEY (contract_id) )
##Table Structure
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id text, patient_id text, plan_id text, policy_number text, group_number text, subscriber_name text, effective_date date, expiration_date date, is_primary boolean )
##Table Structure
CREATE TABLE hospitality_technology.staff ( staff_id text PRIMARY KEY, property_id text, first_name text, last_name text, position text, work_email text, work_phone text, hire_date date, termination_date date, is_active boolean, access_level int, manager_id text, created_at timestamp )
CREATE TABLE hospitality_technology.services ( service_id character varying(64) NOT NULL, property_id character varying(64) NOT NULL, service_name character varying(150) NOT NULL, description text, category character varying(100), price numeric(10, 2) NOT NULL, unit character varying(30), is_available boolean NOT NULL DEFAULT true, department character varying(100), PRIMARY KEY (service_id), FOREIGN KEY (property_id) REFERENCES hospitality_technology.properties(property_id) )
CREATE TABLE hospitality_technology.payments ( payment_id.text, reservation_id.text, guest_id.text, bill_id.text, amount.numeric, currency_code.text, payment_method.text, card_type.text, card_last_four.text, transaction_ref.text, payment_timestamp.timestamp, status.text, staff_id_processed.text, notes.text )
CREATE TABLE hospitality_technology.reviews ( review_id text PRIMARY KEY, property_id text, reservation_id text, guest_id text, rating_overall int, rating_cleanliness int, rating_service int, rating_location int, rating_value int, comment text, review_source text, review_date timestamp, is_public boolean, staff_response text, response_staff_id text, response_date timestamp )
##Table Structure
CREATE TABLE web3.contracts ( contract_id character varying(64) NOT NULL, address character varying(128) NOT NULL, abi text NOT NULL, bytecode text NOT NULL, deployer_address character varying(128) NOT NULL, deployed_at timestamp NOT NULL, network_id character varying(64) NOT NULL, status character varying(32) NOT NULL, PRIMARY KEY (contract_id) )
CREATE TABLE web3.tokens ( token_id character varying(64) NOT NULL, contract_address character varying(128) NOT NULL, token_name character varying(128) NOT NULL, token_symbol character varying(32) NOT NULL, decimals integer NOT NULL, total_supply numeric(38,14) NOT NULL, PRIMARY KEY (token_id) )
CREATE TABLE web3.token_transfers ( transfer_id character varying(64) NOT NULL, token_id character varying(64) NOT NULL, from_address character varying(128) NOT NULL, to_address character varying(128) NOT NULL, value numeric(38,14) NOT NULL, transaction_id character varying(64) NOT NULL, log_index integer NOT NULL, PRIMARY KEY (transfer_id) )
CREATE TABLE web3.users ( user_id character varying(64) NOT NULL, username character varying(128) NOT NULL, email character varying(128) NOT NULL, password_hash text NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (user_id) )
##Table Structure
CREATE TABLE healthcare.diagnoses ( diagnosis_id.text, record_id.text, patient_id.text, doctor_id.text, diagnosis_code.text, code_type.text, description.text, diagnosis_date.date, status.text, is_chronic.boolean )

[User] Which cities are listed as primary_address for citizens who have a verified account? Can you show the city names and the number of verified citizens in each city?

[Assistant] SELECT SPLIT_PART(primary_address, ',', 1) AS city, COUNT(*) AS verified_citizen_count FROM government_services.citizens WHERE is_verified = true GROUP BY city;

[User] Actually, could you only include cities with more than 10 verified citizens? And order them by the number of verified citizens in descending order.

[Assistant] SELECT SPLIT_PART(primary_address, ',', 1) AS city, COUNT(*) AS verified_citizen_count FROM government_services.citizens WHERE is_verified = true GROUP BY city HAVING COUNT(*) > 10 ORDER BY verified_citizen_count DESC;

[User] Retrieve the username and email for every user, along with the wallet ID and associated address ID for any wallets they own.

[Assistant]
SELECT
    u.username,
    u.email,
    w.wallet_id,
    w.address_id
FROM
    blockchain.users AS u
LEFT JOIN
    blockchain.wallets AS w ON u.user_id = w.user_id;

[User] Can you list all patients who switched their primary insurance plan, including the patient_id, old plan_id, new plan_id, and the date of the switch?

[Assistant]
SELECT p1.patient_id,
       p1.plan_id   AS old_plan_id,
       p2.plan_id   AS new_plan_id,
       p2.effective_date AS change_date
FROM healthcare.patient_insurance p1
JOIN healthcare.patient_insurance p2
  ON p1.patient_id = p2.patient_id
 AND p1.is_primary = TRUE
 AND p2.is_primary = TRUE
 AND p1.effective_date < p2.effective_date;

[User] Actually, only include switches where both the old and new policies have a non-null group_number.

[Assistant]
SELECT p1.patient_id,
       p1.plan_id   AS old_plan_id,
       p2.plan_id   AS new_plan_id,
       p2.effective_date AS change_date
FROM healthcare.patient_insurance p1
JOIN healthcare.patient_insurance p2
  ON p1.patient_id = p2.patient_id
 AND p1.is_primary = TRUE
 AND p2.is_primary = TRUE
 AND p1.effective_date < p2.effective_date
WHERE p1.group_number IS NOT NULL
  AND p2.group_number IS NOT NULL;

[User] Show all public reviews that have a comment.

[Assistant] SELECT review_id, property_id, guest_id, rating_overall, comment FROM reviews WHERE is_public = TRUE AND comment IS NOT NULL AND comment != '';

[User] From those, only show reviews with an overall rating of 5.

[Assistant] SELECT review_id, property_id, guest_id, rating_overall, comment FROM reviews WHERE is_public = TRUE AND comment IS NOT NULL AND comment != '' AND rating_overall = 5;

[User] For each deployer address, show the total supply of all tokens created by the contracts they deployed.

[Assistant]
SELECT c.deployer_address, SUM(t.total_supply) AS total_token_supply
FROM web3.contracts c
JOIN web3.tokens t ON c.address = t.contract_address
GROUP BY c.deployer_address;

[User] List the diagnosis_id, patient_id, and doctor_id for all diagnoses with status 'Pending' and is_chronic set to TRUE.

[Assistant] SELECT diagnosis_id, patient_id, doctor_id FROM healthcare.diagnoses WHERE status = 'Pending' AND is_chronic = TRUE;


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 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)
)
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.orders ( order_id text, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades ( trade_id text, order_id text, buyer_id text, seller_id text, asset_id text, quantity numeric, price numeric, traded_at timestamp )
CREATE TABLE trading_platform.assets ( asset_id text, name text, symbol text, type text )
CREATE TABLE trading_platform.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.metadata ( metadata_id text, asset_id text, key text, value text )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id text, user_id text, status text, reviewed_at timestamp )
CREATE TABLE trading_platform.logs ( log_id text, user_id text, action text, details text, logged_at timestamp )
##Table Structure
CREATE TABLE government_services.service_locations (
    location_id character varying(64) NOT NULL, -- unique identifier for the physical location
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    location_name character varying(200), -- e.g., Downtown DMV Office
    address text NOT NULL,
    city character varying(100),
    state character varying(50),
    postal_code character varying(20),
    latitude numeric(9, 6),
    longitude numeric(9, 6),
    operating_hours text, -- description of opening times
    contact_phone character varying(32),
    is_accessible boolean, -- accessibility information (e.g., wheelchair access)
    PRIMARY KEY (location_id)
)
##Table Structure
  "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));"
##Table Structure
CREATE TABLE healthcare.prescriptions ( prescription_id.text, record_id.text, patient_id.text, doctor_id.text, medication_id.text, dosage.text, frequency.text, route.text, start_date.date, end_date.date, quantity_dispensed.numeric, refills_allowed.integer, prescription_date.timestamp )
##Table Structure
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] Calculate for each player the timespan between their earliest and latest achievement unlocks.

[Assistant]
SELECT pa_min.player_id,
       pa_max.max_time - pa_min.min_time AS span
FROM (
  SELECT player_id,
         MIN(unlocked_at) AS min_time
  FROM gaming_technology.player_achievements
  GROUP BY player_id
) pa_min
JOIN (
  SELECT player_id,
         MAX(unlocked_at) AS max_time
  FROM gaming_technology.player_achievements
  GROUP BY player_id
) pa_max
  ON pa_min.player_id = pa_max.player_id;

[User] Exclude players who only have one achievement.

[Assistant]
WITH extremes AS (
  SELECT player_id,
         MIN(unlocked_at) AS min_time,
         MAX(unlocked_at) AS max_time,
         COUNT(*) AS cnt
  FROM gaming_technology.player_achievements
  GROUP BY player_id
  HAVING COUNT(*) > 1
)
SELECT player_id,
       max_time - min_time AS span
FROM extremes;

[User] Also only keep players where the span is greater than 30 days.

[Assistant]
WITH extremes AS (
  SELECT player_id,
         MIN(unlocked_at) AS min_time,
         MAX(unlocked_at) AS max_time,
         COUNT(*) AS cnt
  FROM gaming_technology.player_achievements
  GROUP BY player_id
  HAVING COUNT(*) > 1
)
SELECT player_id,
       max_time - min_time AS span
FROM extremes
WHERE max_time - min_time > INTERVAL '30 days';

[User] List user IDs with approved KYC status and the addresses of their wallets.

[Assistant] SELECT DISTINCT w.user_id, w.address FROM trading_platform.wallets w JOIN trading_platform.kyc_audit k ON w.user_id = k.user_id WHERE k.status = 'approved';

[User] From that list, also show the total number of unspent UTXOs associated with each wallet address.

[Assistant] SELECT w.user_id, w.address, COUNT(u.utxo_id) AS unspent_utxo_count FROM trading_platform.wallets w JOIN trading_platform.kyc_audit k ON w.user_id = k.user_id JOIN trading_platform.utxos u ON w.address = u.address WHERE k.status = 'approved' AND u.spent = FALSE GROUP BY w.user_id, w.address;

[User] Find all service locations in the city of 'Albany' that are accessible. Show their IDs, names, and contact phone numbers along with their address.

[Assistant] SELECT location_id, location_name, contact_phone, address FROM government_services.service_locations WHERE city = 'Albany' AND is_accessible = TRUE;

[User] What is the total USD value of tokens held by CEX addresses on the 'Ethereum' chain for the most recent snapshot time?

[Assistant]
WITH latest_snapshot AS (
  SELECT max(snapshot_time) as max_time
  FROM cex_token_balance
)
SELECT sum(usd_value)
FROM cex_token_balance ctb
JOIN latest_snapshot ls ON ctb.snapshot_time = ls.max_time
WHERE chain = 'Ethereum';

[User] Can you break down this total value by `exchange`, showing the top 3 exchanges by total USD value for that same latest snapshot on Ethereum?

[Assistant]
WITH latest_snapshot AS (
  SELECT max(snapshot_time) as max_time
  FROM cex_token_balance
)
SELECT exchange, sum(usd_value) as total_usd_value
FROM cex_token_balance ctb
JOIN latest_snapshot ls ON ctb.snapshot_time = ls.max_time
WHERE chain = 'Ethereum'
GROUP BY exchange
ORDER BY total_usd_value DESC
LIMIT 3;

[User] What is the average quantity_dispensed per route for prescriptions with start_date in 2024? Return route and avg_quantity.

[Assistant]
SELECT route,
       AVG(quantity_dispensed) AS avg_quantity
FROM healthcare.prescriptions
WHERE start_date >= '2024-01-01'
GROUP BY route;

[User] Refine to only include routes with more than 20 prescriptions and round avg_quantity to two decimal places.

[Assistant]
SELECT route,
       ROUND(AVG(quantity_dispensed), 2) AS avg_quantity
FROM healthcare.prescriptions
WHERE start_date >= '2024-01-01'
GROUP BY route
HAVING COUNT(*) > 20;

[User] Which claim ID has the highest number of documents associated with it?

[Assistant] SELECT claim_id FROM insurance.claim_documents GROUP BY claim_id ORDER BY COUNT(*) DESC LIMIT 1;

[User] Show me the file name, document type, file size, and uploaded time for all documents belonging to that claim ID.

[Assistant] SELECT file_name, document_type, file_size_bytes, uploaded_at FROM insurance.claim_documents WHERE claim_id = (SELECT claim_id FROM insurance.claim_documents GROUP BY claim_id ORDER BY COUNT(*) DESC LIMIT 1);


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 legal_services.time_entries (
    entry_id character varying(64) NOT NULL,  -- unique identifier for the time entry
    case_id character varying(64) NOT NULL, -- FK to cases table
    lawyer_id character varying(64) NOT NULL, -- FK to lawyers table (who performed the work)
    date_worked date NOT NULL, -- date the work was performed
    hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), -- duration of work in hours (e.g., 1.5 for 1h 30m)
    billing_rate numeric(10, 2) NOT NULL, -- hourly rate applied for this entry
    description text NOT NULL, -- detailed description of the work performed
    is_billable boolean DEFAULT true, -- whether this time entry is billable to the client
    is_billed boolean DEFAULT false, -- whether this entry has been included in an invoice
    invoice_id character varying(64), -- FK to invoices table (once billed)
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- when the entry was recorded
    PRIMARY KEY (entry_id)
)
##Table Structure
CREATE TABLE trading_platform.users ( user_id character varying(64) NOT NULL, username character varying(128) NOT NULL, email character varying(128) NOT NULL, password_hash text NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (user_id) )
CREATE TABLE trading_platform.wallets ( wallet_id text PRIMARY KEY, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.orders ( order_id text PRIMARY KEY, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades (
    trade_id character varying(64) NOT NULL,  -- unique identifier for the trade
    order_id character varying(64) NOT NULL, -- identifier of the order that led to the trade
    buyer_id character varying(64) NOT NULL, -- identifier of the buyer
    seller_id character varying(64) NOT NULL, -- identifier of the seller
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the trade
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    traded_at timestamp NOT NULL, -- time when the trade was executed
    PRIMARY KEY (trade_id)
)
CREATE TABLE trading_platform.assets ( asset_id character varying(64) NOT NULL, name character varying(128) NOT NULL, symbol character varying(32) NOT NULL, type character varying(32) NOT NULL, PRIMARY KEY (asset_id) )
CREATE TABLE trading_platform.dapps ( dapp_id character varying(64) NOT NULL, name character varying(128) NOT NULL, description text NOT NULL, url character varying(256) NOT NULL, PRIMARY KEY (dapp_id) )
CREATE TABLE trading_platform.peers ( peer_id.text, ip_address.text, port.integer, last_seen.timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text PRIMARY KEY, asset_id text, key text, value text )
CREATE TABLE trading_platform.kyc_audit (
    kyc_audit_id character varying(64) NOT NULL,  -- unique identifier for the KYC audit
    user_id character varying(64) NOT NULL, -- identifier of the user being audited
    status character varying(32) NOT NULL, -- status of the KYC audit (e.g., pending, approved, rejected)
    reviewed_at timestamp NOT NULL, -- time when the KYC audit was reviewed
    PRIMARY KEY (kyc_audit_id)
)
CREATE TABLE trading_platform.logs ( log_id text PRIMARY KEY, user_id text, action text, details text, logged_at timestamp )
##Table Structure
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )
CREATE TABLE transportation.routes ( route_id text, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes integer, type text )
##Table Structure
CREATE TABLE insurance.customers ( customer_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, date_of_birth date NOT NULL, ssn_hash character varying(128), address_line1 character varying(255) NOT NULL, address_line2 character varying(255), city character varying(100) NOT NULL, state character varying(50) NOT NULL, zip_code character varying(20) NOT NULL, country character varying(50) NOT NULL DEFAULT 'USA', phone_number character varying(30), email character varying(128) UNIQUE, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp, status character varying(20) NOT NULL DEFAULT 'Active', PRIMARY KEY (customer_id) )
##Table Structure
Use Hashes. Key pattern: 'component:<component_id>'. Example: HSET component:LGSTRUT01 part_number "PN-5521-A" component_name "Landing Gear Strut" material_id "mat:TI64" supplier_id "sup:ACME_AERO" ... Consider Sets for reverse lookups (e.g., 'material_components:<material_id>' -> Set<component_id>).
##Table Structure
CREATE TABLE blockchain.users ( user_id character varying(64) NOT NULL, username character varying(128) NOT NULL, email character varying(128) NOT NULL, password_hash text NOT NULL, PRIMARY KEY (user_id) )

[User] List all time entries where the description includes the word 'email', showing the entry ID, date worked, hours spent, and description.

[Assistant] SELECT entry_id, date_worked, hours_spent, description FROM legal_services.time_entries WHERE description ILIKE '%email%';

[User] For each peer port, count how many peers have used that port.

[Assistant]
SELECT port,
       COUNT(*) AS peer_count
FROM trading_platform.peers
GROUP BY port;

[User] Retrieve the route number and description for routes whose estimated duration exceeds 120 minutes.

[Assistant]
SELECT route_number, description
FROM transportation.routes
WHERE estimated_duration_minutes > 120;

[User] Also, filter to include only routes with distance greater than 200 km and order by distance_km descending.

[Assistant]
SELECT route_number, description
FROM transportation.routes
WHERE estimated_duration_minutes > 120
  AND distance_km > 200
ORDER BY distance_km DESC;

[User] How many customers are there in each state?

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

[User] I need to find all components associated with a specific supplier. Can you help with that?

[Assistant]
HGETALL component:<component_id>
IF HGET component:<component_id> supplier_id = 'sup:ACME_AERO' THEN INCLUDE

[User] Can you also show me the material ID for each of these components?

[Assistant]
HGETALL component:<component_id>
IF HGET component:<component_id> supplier_id = 'sup:ACME_AERO' THEN INCLUDE
HGET component:<component_id> material_id

[User] What if I want to exclude components with a specific material ID?

[Assistant]
HGETALL component:<component_id>
IF HGET component:<component_id> supplier_id = 'sup:ACME_AERO' THEN INCLUDE
HGET component:<component_id> material_id
IF HGET component:<component_id> material_id != 'mat:TI64' THEN INCLUDE

[User] Can you add the component name to the result as well?

[Assistant]
HGETALL component:<component_id>
IF HGET component:<component_id> supplier_id = 'sup:ACME_AERO' THEN INCLUDE
HGET component:<component_id> material_id
IF HGET component:<component_id> material_id != 'mat:TI64' THEN INCLUDE
HGET component:<component_id> component_name

[User] How many unique email domains are there among all registered users?

[Assistant] SELECT COUNT(DISTINCT SUBSTRING(email FROM '@(.*)$')) AS unique_domains FROM blockchain.users;

[User] Can you list these domains along with the count of users for each domain?

[Assistant] SELECT SUBSTRING(email FROM '@(.*)$') AS domain, COUNT(*) AS user_count FROM blockchain.users GROUP BY domain;

[User] Now show only domains that have more than 10 users.

[Assistant] SELECT SUBSTRING(email FROM '@(.*)$') AS domain, COUNT(*) AS user_count FROM blockchain.users GROUP BY domain HAVING COUNT(*) > 10;


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 transportation.locations ( location_id text PRIMARY KEY, name text, type text, address_line1 text, city text, state_province text, postal_code text, country text, latitude numeric, longitude numeric, timezone text )
##Table Structure
CREATE TABLE insurance.customers ( customer_id text, first_name text, last_name text, date_of_birth date, ssn_hash text, address_line1 text, address_line2 text, city text, state text, zip_code text, country text, phone_number text, email text, created_at timestamp, updated_at timestamp, status text )
CREATE TABLE insurance.policies ( policy_id text, customer_id text, product_id text, agent_id text, policy_number text, start_date date, end_date date, premium_amount numeric, coverage_limit numeric, deductible numeric, status text, issued_at timestamp, cancellation_date date, cancellation_reason text )
CREATE TABLE insurance.insurance_products ( product_id text, product_name text, product_type text, description text, base_premium numeric, coverage_details text, underwriting_rules text, is_active boolean, created_at timestamp, updated_at timestamp )
CREATE TABLE insurance.premium_payments ( payment_id text, 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 )
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 )
CREATE TABLE insurance.policy_beneficiaries ( beneficiary_id text, policy_id text, customer_id text, first_name text, last_name text, relationship text, percentage_share numeric, contact_info text, added_at timestamp )
##Table Structure
CREATE TABLE financial_services.customers ( customer_id text PRIMARY KEY, first_name text, last_name text, date_of_birth date, ssn_hash text, address text, city text, state text, zip_code text, country text, email text, phone_number text, created_at timestamp, status text, risk_profile text )
##Table Structure
CREATE TABLE web3.token_transfers ( transfer_id text PRIMARY KEY, token_id text, from_address text, to_address text, value numeric, transaction_id text, log_index int )
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id character varying(64) NOT NULL, license_plate character varying(32) NOT NULL UNIQUE, vin character varying(17) UNIQUE, make character varying(64) NOT NULL, model character varying(64) NOT NULL, year integer NOT NULL, type character varying(32) NOT NULL, capacity integer, fuel_type character varying(32) NOT NULL, status character varying(32) NOT NULL, depot_id character varying(64), acquisition_date date, PRIMARY KEY (vehicle_id) )
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id text PRIMARY KEY, license_plate text, vin text, make text, model text, year int, type text, capacity int, fuel_type text, status text, depot_id text, acquisition_date date )
CREATE TABLE transportation.locations ( location_id text PRIMARY KEY, name text, type text, address_line1 text, city text, state_province text, postal_code text, country text, latitude numeric, longitude numeric, timezone text )
CREATE TABLE transportation.maintenance_logs ( log_id.text, vehicle_id.text, service_date.date, odometer_reading.integer, service_type.text, description.text, cost.numeric, mechanic_name.text, next_service_due_date.date )
CREATE TABLE transportation.fuel_logs (
    fuel_log_id character varying(64) NOT NULL,  -- unique identifier for the fuel log entry
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle fueled
    trip_id character varying(64), -- optional: identifier of the trip during which fueling occurred
    log_timestamp timestamp with time zone NOT NULL, -- time when fueling occurred
    fuel_type character varying(32) NOT NULL, -- type of fuel added (matches vehicle's fuel type)
    quantity numeric(10, 3) NOT NULL, -- amount of fuel added (e.g., Liters, Gallons, kWh)
    unit character varying(16) NOT NULL, -- unit of quantity (e.g., L, gal, kWh)
    cost_per_unit numeric(8, 4), -- price per unit of fuel
    total_cost numeric(10, 2) NOT NULL, -- total cost of the fuel purchase
    odometer_reading integer, -- vehicle mileage at time of fueling
    location_id character varying(64), -- identifier of the fueling station/location
    PRIMARY KEY (fuel_log_id)
)

[User] Find all cities that contain at least one location of type 'Depot' and at least one location of type 'Station'.

[Assistant] SELECT city FROM transportation.locations WHERE type IN ('Depot', 'Station') GROUP BY city HAVING COUNT(DISTINCT CASE WHEN type = 'Depot' THEN location_id END) > 0 AND COUNT(DISTINCT CASE WHEN type = 'Station' THEN location_id END) > 0;

[User] What is the total amount paid across all premium payments for payments marked as 'Failed'?

[Assistant] SELECT sum(amount_paid) FROM insurance.premium_payments WHERE status = 'Failed';

[User] Show all active customers who live in the same zip_code.

[Assistant]
SELECT a.customer_id AS cust1,
       b.customer_id AS cust2,
       a.zip_code
FROM financial_services.customers a
JOIN financial_services.customers b
  ON a.zip_code = b.zip_code
 AND a.customer_id < b.customer_id
WHERE a.status = 'Active'
  AND b.status = 'Active';

[User] Please ensure we don't list duplicate pairs and order by zip_code and cust1.

[Assistant]
SELECT a.customer_id AS cust1,
       b.customer_id AS cust2,
       a.zip_code
FROM financial_services.customers a
JOIN financial_services.customers b
  ON a.zip_code = b.zip_code
 AND a.customer_id < b.customer_id
WHERE a.status = 'Active'
  AND b.status = 'Active'
ORDER BY a.zip_code, a.customer_id;

[User] Include the city and state in the result as well.

[Assistant]
SELECT a.customer_id AS cust1,
       b.customer_id AS cust2,
       a.zip_code,
       a.city,
       a.state
FROM financial_services.customers a
JOIN financial_services.customers b
  ON a.zip_code = b.zip_code
 AND a.customer_id < b.customer_id
WHERE a.status = 'Active'
  AND b.status = 'Active'
ORDER BY a.zip_code, a.customer_id;

[User] Find token transfers within the same transaction where the recipient of an earlier transfer (based on log_index) becomes the sender of a later transfer. List the transaction ID, the earlier transfer ID, the later transfer ID, the shared address, and the value transferred in both cases.

[Assistant] SELECT t1.transaction_id, t1.transfer_id AS earlier_transfer_id, t2.transfer_id AS later_transfer_id, t1.to_address AS shared_address, t1.value AS earlier_transfer_value, t2.value AS later_transfer_value FROM web3.token_transfers AS t1 JOIN web3.token_transfers AS t2 ON t1.transaction_id = t2.transaction_id WHERE t1.to_address = t2.from_address AND t1.log_index < t2.log_index;

[User] List all pairs of vehicles with the same make and model but different manufacture years. Include each vehicle's ID, make, model, and both years.

[Assistant]
SELECT v1.vehicle_id AS vehicle1_id, v2.vehicle_id AS vehicle2_id, v1.make, v1.model, v1.year AS year1, v2.year AS year2
FROM transportation.vehicles v1
JOIN transportation.vehicles v2
  ON v1.make = v2.make
  AND v1.model = v2.model
  AND v1.year <> v2.year
  AND v1.vehicle_id < v2.vehicle_id
ORDER BY v1.make, v1.model, v1.year;

[User] List each vehicle along with the city of the station where it had its most recent fueling and the timestamp of that fueling.

[Assistant]
SELECT v.vehicle_id,
       v.license_plate,
       l.city AS last_fuel_city,
       MAX(f.log_timestamp) AS last_fuel_time
FROM transportation.vehicles v
JOIN transportation.fuel_logs f
  ON v.vehicle_id = f.vehicle_id
JOIN transportation.locations l
  ON f.location_id = l.location_id
GROUP BY v.vehicle_id, v.license_plate, l.city
ORDER BY last_fuel_time 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 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 character varying(64) NOT NULL, user_id character varying(64) NOT NULL, content text, media_url text, media_type character varying(20), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, visibility character varying(20) NOT NULL DEFAULT 'public', location_lat numeric(9,6), location_lon numeric(9,6), PRIMARY KEY (post_id) )
CREATE TABLE social_media.post_hashtags (
    post_hashtag_id character varying(64) NOT NULL, -- unique identifier for the post-hashtag link
    post_id character varying(64) NOT NULL, -- identifier of the post (FK to posts.post_id)
    hashtag_id character varying(64) NOT NULL, -- identifier of the hashtag (FK to hashtags.hashtag_id)
    PRIMARY KEY (post_hashtag_id),
    CONSTRAINT unique_post_hashtag UNIQUE (post_id, hashtag_id) -- prevent duplicate tags on a post
)
CREATE TABLE social_media.messages ( message_id text PRIMARY KEY, conversation_id text, sender_user_id text, content text, media_url text, media_type text, sent_at timestamp, read_at timestamp )
CREATE TABLE social_media.conversation_participants ( participant_id text PRIMARY KEY, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )
CREATE TABLE social_media.notifications ( notification_id.text, recipient_user_id.text, sender_user_id.text, notification_type.text, target_entity_id.text, target_entity_type.text, created_at.timestamp, read_at.timestamp )
CREATE TABLE social_media.user_settings ( setting_id text, user_id text, theme text, email_notifications_enabled boolean, push_notifications_enabled boolean, private_profile boolean, updated_at timestamp )
##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)
)
##Table Structure
CREATE TABLE healthcare.medical_records ( record_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, appointment_id character varying(64) UNIQUE, doctor_id character varying(64) NOT NULL, record_date timestamp with time zone NOT NULL, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals jsonb, created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (record_id) )
CREATE TABLE healthcare.prescriptions ( prescription_id character varying(64) NOT NULL, record_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, doctor_id character varying(64) NOT NULL, medication_id character varying(64) NOT NULL, dosage character varying(100) NOT NULL, frequency character varying(100) NOT NULL, route character varying(50), start_date date NOT NULL, end_date date, quantity_dispensed numeric(10,2), refills_allowed integer NOT NULL DEFAULT 0, prescription_date timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (prescription_id) )
##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 )
##Table Structure
CREATE TABLE trading_platform.orders ( order_id text, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, key character varying(128) NOT NULL, value text NOT NULL, PRIMARY KEY (metadata_id) )

[User] List all posts along with the user emails of the authors.

[Assistant]
SELECT p.post_id, p.content, u.email
FROM social_media.posts p
JOIN social_media.users u ON p.user_id = u.user_id;

[User] Show the count of citizens grouped by their verification status.

[Assistant] SELECT is_verified, COUNT(*) FROM government_services.citizens GROUP BY is_verified;

[User] Now, only include citizens who registered after January 1, 2023.

[Assistant] SELECT is_verified, COUNT(*) FROM government_services.citizens WHERE registration_date >= '2023-01-01' GROUP BY is_verified;

[User] Show me the record_id, patient_id, prescription_id, medication_id, start_date, and the systolic blood pressure from the associated medical record for all prescriptions.

[Assistant]
SELECT p.prescription_id,
       p.medication_id,
       p.start_date,
       m.record_id,
       m.patient_id,
       (m.vitals->'blood_pressure'->>'systolic')::int AS systolic_bp
FROM healthcare.prescriptions p
JOIN healthcare.medical_records m
  ON p.record_id = m.record_id;

[User] Actually, only include those where the systolic blood pressure is greater than 140.

[Assistant]
SELECT p.prescription_id,
       p.medication_id,
       p.start_date,
       m.record_id,
       m.patient_id,
       (m.vitals->'blood_pressure'->>'systolic')::int AS systolic_bp
FROM healthcare.prescriptions p
JOIN healthcare.medical_records m
  ON p.record_id = m.record_id
WHERE (m.vitals->'blood_pressure'->>'systolic')::int > 140;

[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

[User] For each asset, show the total quantity ordered with order status 'completed'.

[Assistant] SELECT asset_id, SUM(quantity) AS total_completed_quantity FROM trading_platform.orders WHERE status = 'completed' GROUP BY asset_id;

[User] Add the count of completed orders for each asset as well.

[Assistant] SELECT asset_id, COUNT(*) AS completed_order_count, SUM(quantity) AS total_completed_quantity FROM trading_platform.orders WHERE status = 'completed' GROUP BY asset_id;

[User] Actually, can you include only those assets that have associated metadata with the key 'category'?

[Assistant] SELECT o.asset_id, COUNT(*) AS completed_order_count, SUM(o.quantity) AS total_completed_quantity FROM trading_platform.orders o INNER JOIN trading_platform.metadata m ON o.asset_id = m.asset_id AND m.key = 'category' WHERE o.status = 'completed' GROUP BY o.asset_id;

[User] Could you also provide the value of the 'category' metadata in the result for each asset?

[Assistant] SELECT o.asset_id, m.value AS category, COUNT(*) AS completed_order_count, SUM(o.quantity) AS total_completed_quantity FROM trading_platform.orders o INNER JOIN trading_platform.metadata m ON o.asset_id = m.asset_id AND m.key = 'category' WHERE o.status = 'completed' GROUP BY o.asset_id, m.value;


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 legal_services.time_entries ( entry_id text PRIMARY KEY, case_id text, lawyer_id text, date_worked date, hours_spent numeric, billing_rate numeric, description text, is_billable bool, is_billed bool, invoice_id text, created_at timestamp )
##Table Structure
CREATE TABLE trading_platform.assets ( asset_id text PRIMARY KEY, name text, symbol text, type text )
##Table Structure
CREATE TABLE legal_services.lawyers ( lawyer_id.text, first_name.text, last_name.text, bar_number.text, firm_id.text, email.text, phone.text, specialization.text, hire_date.timestamp, is_partner.boolean )
CREATE TABLE legal_services.invoices ( invoice_id text, invoice_number text, client_id text, case_id text, issue_date date, due_date date, total_amount numeric, amount_paid numeric, status text, payment_date timestamp, notes text, created_at timestamp )
##Table Structure
CREATE TABLE hospitality_technology.service_orders ( order_id.text, reservation_id.text, guest_id.text, service_id.text, staff_id_ordered.text, staff_id_delivered.text, order_timestamp.timestamp, delivery_timestamp.timestamp, quantity.integer, unit_price.numeric, total_price.numeric, status.text, notes.text, bill_id.text )
##Table Structure
CREATE TABLE insurance.insurance_products (
    product_id character varying(64) NOT NULL, -- unique identifier for the insurance product
    product_name character varying(150) NOT NULL, -- name of the insurance product (e.g., 'Comprehensive Auto Insurance')
    product_type character varying(50) NOT NULL, -- category like 'Auto', 'Home', 'Life', 'Health', 'Travel'
    description text, -- detailed description of the product
    base_premium numeric(10, 2) NOT NULL, -- starting premium before adjustments
    coverage_details text, -- details about what is covered (could be JSON or structured text)
    underwriting_rules text, -- rules used for assessing risk and eligibility
    is_active boolean NOT NULL DEFAULT true, -- whether the product is currently offered
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    updated_at timestamp,
    PRIMARY KEY (product_id)
)
##Table Structure
CREATE TABLE web3.events ( event_id.text, contract_id.text, event_name.text, data.text, emitted_at.timestamp, transaction_id.text, log_index.integer )
CREATE TABLE web3.transactions ( transaction_id character varying(64) NOT NULL, from_address character varying(128) NOT NULL, to_address character varying(128), value numeric(38,14) NOT NULL, gas_used integer NOT NULL, gas_price numeric(38,14) NOT NULL, block_number integer NOT NULL, timestamp timestamp NOT NULL, input_data text, status character varying(32) NOT NULL, nonce integer NOT NULL, PRIMARY KEY (transaction_id) )
CREATE TABLE web3.tokens ( token_id.text, contract_address.text, token_name.text, token_symbol.text, decimals.integer, total_supply.numeric )
CREATE TABLE web3.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE web3.users ( user_id text PRIMARY KEY, username text, email text, password_hash text, created_at timestamp )
##Table Structure
CREATE TABLE gaming_technology.games ( game_id.uuid, title.text, developer_id.uuid, publisher_id.uuid, genre.text, release_date.date, description.text, platform.text, engine.text, website.text )
CREATE TABLE gaming_technology.player_inventory ( inventory_id.uuid, player_id.uuid, item_id.uuid, quantity.integer, acquired_at.timestamptz, instance_data.jsonb )
##Table Structure
CREATE TABLE healthcare.patients ( patient_id text PRIMARY KEY, 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 )

[User] Show the invoice_id and total hours logged for each invoice.

[Assistant] SELECT invoice_id, SUM(hours_spent) AS total_hours FROM legal_services.time_entries WHERE invoice_id IS NOT NULL GROUP BY invoice_id;

[User] Only include invoices with more than 10 total hours.

[Assistant] SELECT invoice_id, SUM(hours_spent) AS total_hours FROM legal_services.time_entries WHERE invoice_id IS NOT NULL GROUP BY invoice_id HAVING SUM(hours_spent) > 10;

[User] Show the names and types of all assets whose symbol is exactly 3 characters long.

[Assistant] SELECT name, type, symbol FROM trading_platform.assets WHERE LENGTH(symbol) = 3;

[User] Also, I want to order the results alphabetically by asset name.

[Assistant] SELECT name, type, symbol FROM trading_platform.assets WHERE LENGTH(symbol) = 3 ORDER BY name ASC;

[User] Actually, can you only show assets of type 'token' in the result?

[Assistant] SELECT name, type, symbol FROM trading_platform.assets WHERE LENGTH(symbol) = 3 AND type = 'token' ORDER BY name ASC;

[User] Now, just return the asset name and symbol for these tokens, sorted by symbol descending.

[Assistant] SELECT name, symbol FROM trading_platform.assets WHERE LENGTH(symbol) = 3 AND type = 'token' ORDER BY symbol DESC;

[User] List all pairs of lawyers who share the same last name but have different first names. Show the first name, last name, and lawyer ID for both lawyers in each pair.

[Assistant] SELECT l1.first_name AS lawyer1_first_name, l1.last_name AS lawyer1_last_name, l1.lawyer_id AS lawyer1_id, l2.first_name AS lawyer2_first_name, l2.last_name AS lawyer2_last_name, l2.lawyer_id AS lawyer2_id FROM legal_services.lawyers AS l1 JOIN legal_services.lawyers AS l2 ON l1.last_name = l2.last_name AND l1.lawyer_id < l2.lawyer_id WHERE l1.first_name <> l2.first_name;

[User] For each staff member who delivered at least one service order, show their staff_id_delivered and the total revenue (sum of total_price) of orders they delivered.

[Assistant]
SELECT staff_id_delivered, SUM(total_price) AS total_revenue
FROM hospitality_technology.service_orders
WHERE staff_id_delivered IS NOT NULL
GROUP BY staff_id_delivered;

[User] Show me the product ID, name, and description for insurance products where the description contains the word 'policy'.

[Assistant] SELECT product_id, product_name, description FROM insurance.insurance_products WHERE description LIKE '%policy%';

[User] Add the product type and base premium to the output for these products.

[Assistant] SELECT product_id, product_name, description, product_type, base_premium FROM insurance.insurance_products WHERE description LIKE '%policy%';

[User] Show the top 5 contracts by number of events emitted, including contract_id and event_count.

[Assistant]
SELECT contract_id,
       COUNT(event_id) AS event_count
FROM web3.events
GROUP BY contract_id
ORDER BY event_count DESC
LIMIT 5;

[User] Actually, include the earliest and latest emitted_at timestamps for those contracts.

[Assistant]
SELECT contract_id,
       COUNT(event_id) AS event_count,
       MIN(emitted_at) AS first_event,
       MAX(emitted_at) AS last_event
FROM web3.events
GROUP BY contract_id
ORDER BY event_count DESC
LIMIT 5;

[User] Could you list each player and the title of the games for which they have acquired items?

[Assistant] SELECT DISTINCT pi.player_id, g.title FROM gaming_technology.player_inventory pi JOIN gaming_technology.games g ON pi.item_id = g.game_id;

[User] Filter this list to only include acquisitions made after January 1st, 2023.

[Assistant] SELECT DISTINCT pi.player_id, g.title FROM gaming_technology.player_inventory pi JOIN gaming_technology.games g ON pi.item_id = g.game_id WHERE pi.acquired_at >= '2023-01-01';

[User] For these player and game combinations, can you also show the total quantity of items they acquired for that specific game?

[Assistant] SELECT pi.player_id, g.title, SUM(pi.quantity) AS total_quantity_for_game FROM gaming_technology.player_inventory pi JOIN gaming_technology.games g ON pi.item_id = g.game_id WHERE pi.acquired_at >= '2023-01-01' GROUP BY pi.player_id, g.title;

[User] How many patients are there in each gender category?

[Assistant]
SELECT gender, COUNT(*) AS patient_count
FROM healthcare.patients
GROUP BY gender;

[User] Now only include genders with more than 100 patients.

[Assistant]
SELECT gender, COUNT(*) AS patient_count
FROM healthcare.patients
GROUP BY gender
HAVING COUNT(*) > 100;


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 transportation.fuel_logs ( fuel_log_id.text, vehicle_id.text, trip_id.text, log_timestamp.timestamp, fuel_type.text, quantity.numeric, unit.text, cost_per_unit.numeric, total_cost.numeric, odometer_reading.integer, location_id.text )
##Table Structure
CREATE TABLE social_media.conversation_participants ( participant_id text, conversation_id text, user_id text, joined_at timestamp, last_read_at timestamp )
CREATE TABLE social_media.user_settings ( setting_id text, user_id text, theme text, email_notifications_enabled boolean, push_notifications_enabled boolean, private_profile boolean, updated_at timestamp )
##Table Structure
CREATE TABLE hospitality_technology.room_types ( room_type_id text, property_id text, type_name text, description text, base_rate numeric, max_occupancy integer, bed_type text, area_sqft numeric, amenities text )
CREATE TABLE hospitality_technology.service_orders ( order_id text, reservation_id text, guest_id text, service_id text, staff_id_ordered text, staff_id_delivered text, order_timestamp timestamp, delivery_timestamp timestamp, quantity integer, unit_price numeric, total_price numeric, status text, notes text, bill_id text )
CREATE TABLE hospitality_technology.payments ( payment_id text, reservation_id text, guest_id text, bill_id text, amount numeric, currency_code text, payment_method text, card_type text, card_last_four text, transaction_ref text, payment_timestamp timestamp, status text, staff_id_processed text, notes text )
##Table Structure
CREATE TABLE legal_services.cases ( case_id.text, case_number.text, case_name.text, client_id.text, lead_lawyer_id.text, case_type.text, status.text, date_opened.timestamp, date_closed.timestamp, description.text, court_jurisdiction.text )
##Table Structure
CREATE TABLE trading_platform.users ( user_id character varying(64) NOT NULL, username character varying(128) NOT NULL, email character varying(128) NOT NULL, password_hash text NOT NULL, created_at timestamp NOT NULL, PRIMARY KEY (user_id) )
CREATE TABLE trading_platform.orders ( order_id text PRIMARY KEY, user_id text, wallet_id text, asset_id text, order_type text, quantity numeric, price numeric, status text, created_at timestamp )
CREATE TABLE trading_platform.trades (
    trade_id character varying(64) NOT NULL,  -- unique identifier for the trade
    order_id character varying(64) NOT NULL, -- identifier of the order that led to the trade
    buyer_id character varying(64) NOT NULL, -- identifier of the buyer
    seller_id character varying(64) NOT NULL, -- identifier of the seller
    asset_id character varying(64) NOT NULL, -- identifier of the asset being traded
    quantity numeric(38,14) NOT NULL, -- quantity of the asset in the trade
    price numeric(38,14) NOT NULL, -- price per unit of the asset
    traded_at timestamp NOT NULL, -- time when the trade was executed
    PRIMARY KEY (trade_id)
)
CREATE TABLE trading_platform.assets ( asset_id character varying(64) NOT NULL, name character varying(128) NOT NULL, symbol character varying(32) NOT NULL, type character varying(32) NOT NULL, PRIMARY KEY (asset_id) )
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 character varying(64) NOT NULL, name character varying(128) NOT NULL, description text NOT NULL, url character varying(256) NOT NULL, PRIMARY KEY (dapp_id) )
CREATE TABLE trading_platform.peers ( peer_id.text, ip_address.text, port.integer, last_seen.timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text PRIMARY KEY, asset_id text, key text, value text )
CREATE TABLE trading_platform.kyc_audit (
    kyc_audit_id character varying(64) NOT NULL,  -- unique identifier for the KYC audit
    user_id character varying(64) NOT NULL, -- identifier of the user being audited
    status character varying(32) NOT NULL, -- status of the KYC audit (e.g., pending, approved, rejected)
    reviewed_at timestamp NOT NULL, -- time when the KYC audit was reviewed
    PRIMARY KEY (kyc_audit_id)
)
CREATE TABLE trading_platform.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 )
##Table Structure
CREATE TABLE insurance.customers ( customer_id text, first_name text, last_name text, date_of_birth date, ssn_hash text, address_line1 text, address_line2 text, city text, state text, zip_code text, country text, phone_number text, email text, created_at timestamp, updated_at timestamp, status text )

[User] Calculate the monthly total quantity of fuel consumed and the average cost_per_unit for each fuel_type in 2023.

[Assistant]
SELECT date_trunc('month', log_timestamp) AS month,
       fuel_type,
       SUM(quantity)      AS total_quantity,
       AVG(cost_per_unit) AS avg_cost_per_unit
FROM transportation.fuel_logs
WHERE log_timestamp >= '2023-01-01'
  AND log_timestamp <  '2024-01-01'
GROUP BY 1, fuel_type
ORDER BY 1, fuel_type;

[User] Now limit the results to fuel types where the total_quantity exceeds 1000 units in that month.

[Assistant]
SELECT month,
       fuel_type,
       total_quantity,
       avg_cost_per_unit
FROM (
  SELECT date_trunc('month', log_timestamp) AS month,
         fuel_type,
         SUM(quantity)      AS total_quantity,
         AVG(cost_per_unit) AS avg_cost_per_unit
  FROM transportation.fuel_logs
  WHERE log_timestamp >= '2023-01-01'
    AND log_timestamp <  '2024-01-01'
  GROUP BY 1, fuel_type
) sub
WHERE total_quantity > 1000
ORDER BY month, fuel_type;

[User] Show me the usernames of users who have joined more than one conversation, and list the conversation IDs for each user.

[Assistant]
SELECT user_id, ARRAY_AGG(conversation_id) AS conversation_ids
FROM social_media.conversation_participants
GROUP BY user_id
HAVING COUNT(DISTINCT conversation_id) > 1;

[User] Instead of user IDs, can you show me only the unique count of conversations each user joined, and sort the results by that count descending?

[Assistant]
SELECT user_id, COUNT(DISTINCT conversation_id) AS unique_conversation_count
FROM social_media.conversation_participants
GROUP BY user_id
ORDER BY unique_conversation_count DESC;

[User] Get the count of service orders and total payment amount for each reservation.

[Assistant]
SELECT so.reservation_id,
       COUNT(*) AS order_count,
       SUM(p.amount) AS total_payment
FROM hospitality_technology.service_orders so
JOIN hospitality_technology.payments p
  ON so.reservation_id = p.reservation_id
GROUP BY so.reservation_id
ORDER BY total_payment DESC;

[User] Actually, show only those reservations where the total number of service orders exceeds 3.

[Assistant]
SELECT so.reservation_id,
       COUNT(*) AS order_count,
       SUM(p.amount) AS total_payment
FROM hospitality_technology.service_orders so
JOIN hospitality_technology.payments p
  ON so.reservation_id = p.reservation_id
GROUP BY so.reservation_id
HAVING COUNT(*) > 3
ORDER BY total_payment DESC;

[User] List all cases opened in the 'State Court' jurisdiction in the year 2023, including their name, number, and client ID.

[Assistant] SELECT case_name, case_number, client_id FROM legal_services.cases WHERE court_jurisdiction = 'State Court' AND date_opened >= '2023-01-01' AND date_opened < '2024-01-01';

[User] Which DApps have the word 'exchange' in their description?

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

[User] List pairs of customers who live in the same city. Return both customer IDs, their full names, and the city.

[Assistant] SELECT c1.customer_id AS customer1_id, c1.first_name || ' ' || c1.last_name AS customer1_name, c2.customer_id AS customer2_id, c2.first_name || ' ' || c2.last_name AS customer2_name, c1.city FROM insurance.customers c1 JOIN insurance.customers c2 ON c1.city = c2.city AND c1.customer_id < c2.customer_id;


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 transportation.vehicles ( vehicle_id text PRIMARY KEY, license_plate text, vin text, make text, model text, year int, type text, capacity int, fuel_type text, status text, depot_id text, acquisition_date date )
CREATE TABLE transportation.drivers ( driver_id text PRIMARY KEY, employee_id text, first_name text, last_name text, license_number text, license_expiry_date date, contact_number text, email text, hire_date date, status text )
CREATE TABLE transportation.routes ( route_id text PRIMARY KEY, route_number text, description text, origin_location_id text, destination_location_id text, distance_km numeric, estimated_duration_minutes int, type text )
CREATE TABLE transportation.trips ( trip_id text PRIMARY KEY, route_id text, vehicle_id text, driver_id text, scheduled_departure timestamp, actual_departure timestamp, scheduled_arrival timestamp, actual_arrival timestamp, origin_location_id text, destination_location_id text, status text, passenger_count int, cargo_manifest_id text )
CREATE TABLE transportation.locations ( location_id text PRIMARY KEY, name text, type text, address_line1 text, city text, state_province text, postal_code text, country text, latitude numeric, longitude numeric, timezone text )
CREATE TABLE transportation.maintenance_logs ( log_id text PRIMARY KEY, vehicle_id text, service_date date, odometer_reading int, service_type text, description text, cost numeric, mechanic_name text, next_service_due_date date )
CREATE TABLE transportation.fuel_logs ( fuel_log_id text PRIMARY KEY, vehicle_id text, trip_id text, log_timestamp timestamp, fuel_type text, quantity numeric, unit text, cost_per_unit numeric, total_cost numeric, odometer_reading int, location_id text )
CREATE TABLE transportation.bookings ( booking_id text PRIMARY KEY, passenger_id text, trip_id text, seat_number text, booking_time timestamp, status text, fare numeric, payment_transaction_id text, special_requests text )
##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, patient_id text, appointment_id text, doctor_id text, record_date timestamp, chief_complaint text, present_illness_history text, past_medical_history text, physical_examination_notes text, assessment text, treatment_plan text, vitals text, created_at timestamp )
CREATE TABLE healthcare.diagnoses ( diagnosis_id text, record_id text, patient_id text, doctor_id text, diagnosis_code text, code_type text, description text, diagnosis_date date, status text, is_chronic boolean )
CREATE TABLE healthcare.medications ( medication_id text, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )
CREATE TABLE healthcare.prescriptions ( prescription_id text, record_id text, patient_id text, doctor_id text, medication_id text, dosage text, frequency text, route text, start_date date, end_date date, quantity_dispensed numeric, refills_allowed integer, prescription_date timestamp )
CREATE TABLE healthcare.insurance_plans ( plan_id text, plan_name text, insurance_provider text, plan_type text, contact_phone text, website text )
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id text, patient_id text, plan_id text, policy_number text, group_number text, subscriber_name text, effective_date date, expiration_date date, is_primary boolean )
##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 )
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id text, user_id text, address text, private_key text, created_at timestamp )
CREATE TABLE trading_platform.trades ( trade_id text, order_id text, buyer_id text, seller_id text, asset_id text, quantity numeric, price numeric, traded_at timestamp )
CREATE TABLE trading_platform.assets ( asset_id text, name text, symbol text, type text )
CREATE TABLE trading_platform.utxos ( utxo_id text, transaction_id text, output_index integer, address text, amount numeric, spent boolean )
CREATE TABLE trading_platform.peers ( peer_id text, ip_address text, port integer, last_seen timestamp )
CREATE TABLE trading_platform.metadata ( metadata_id text, asset_id text, key text, value text )
CREATE TABLE trading_platform.kyc_audit ( kyc_audit_id text, user_id text, status text, reviewed_at timestamp )
##Table Structure
CREATE TABLE legal_services.cases ( case_id text, case_number text, case_name text, client_id text, lead_lawyer_id text, case_type text, status text, date_opened timestamp, date_closed timestamp, description text, court_jurisdiction text )

[User] Retrieve the vehicle_id, make, model, and the next_service_due_date for each vehicle based on the most recent maintenance log.

[Assistant] SELECT DISTINCT ON (ml.vehicle_id) v.vehicle_id, v.make, v.model, ml.next_service_due_date FROM transportation.maintenance_logs ml JOIN transportation.vehicles v ON v.vehicle_id = ml.vehicle_id ORDER BY ml.vehicle_id, ml.service_date DESC;

[User] Now, only include vehicles with status 'Active' and whose next_service_due_date is within the next 30 days, ordering by next_service_due_date ascending.

[Assistant] SELECT v.vehicle_id, v.make, v.model, ml.next_service_due_date FROM transportation.vehicles v JOIN (SELECT DISTINCT ON (vehicle_id) vehicle_id, next_service_due_date FROM transportation.maintenance_logs ORDER BY vehicle_id, service_date DESC) ml ON v.vehicle_id = ml.vehicle_id WHERE v.status = 'Active' AND ml.next_service_due_date BETWEEN current_date AND current_date + INTERVAL '30 days' ORDER BY ml.next_service_due_date ASC;

[User] How many patients are there in each gender category?

[Assistant]
SELECT gender,
       COUNT(*) AS patient_count
FROM healthcare.patients
GROUP BY gender;

[User] Only include categories with more than 50 patients.

[Assistant]
SELECT gender,
       COUNT(*) AS patient_count
FROM healthcare.patients
GROUP BY gender
HAVING COUNT(*) > 50;

[User] List tokens that have a 24-hour trading volume greater than $10,000,000 and a negative price change percentage over the last 24 hours. Show the token symbol, chain, total volume, and the 24-hour price change percentage.

[Assistant] SELECT token_symbol, chain, total_volume, price_change_percentage_24h FROM token_basic_info WHERE CAST(REPLACE(total_volume, ',', '') AS numeric) > 10000000 AND price_change_percentage_24h < 0

[User] From those results, filter further to only include tokens with a market cap rank of 100 or better. Order the results by 24-hour trading volume in descending order.

[Assistant] SELECT token_symbol, chain, total_volume, price_change_percentage_24h FROM token_basic_info WHERE CAST(REPLACE(total_volume, ',', '') AS numeric) > 10000000 AND price_change_percentage_24h < 0 AND market_cap_rank IS NOT NULL AND market_cap_rank <= 100 ORDER BY CAST(REPLACE(total_volume, ',', '') AS numeric) DESC

[User] I want a summary of each asset showing the total number of trades executed and the average trade price, including asset name and symbol.

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

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

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

[User] List the names and numbers of cases that were opened in June 2024.

[Assistant] SELECT case_name, case_number FROM legal_services.cases WHERE date_opened >= '2024-06-01' AND date_opened < '2024-07-01';