[User] Show the usernames of users who have followers and the total count of followers for each.

[Assistant] SELECT T1.username, COUNT(T2.follower_user_id) AS follower_count FROM social_media.users AS T1 JOIN social_media.follows AS T2 ON T1.user_id = T2.following_user_id GROUP BY T1.user_id, T1.username;

[User] Modify to only include users whose accounts were created after '2023-01-01'.

[Assistant] SELECT T1.username, COUNT(T2.follower_user_id) AS follower_count FROM social_media.users AS T1 JOIN social_media.follows AS T2 ON T1.user_id = T2.following_user_id WHERE T1.created_at > '2023-01-01' GROUP BY T1.user_id, T1.username;

[User] Order the results by follower count in descending order and limit to the top 10.

[Assistant] SELECT T1.username, COUNT(T2.follower_user_id) AS follower_count FROM social_media.users AS T1 JOIN social_media.follows AS T2 ON T1.user_id = T2.following_user_id WHERE T1.created_at > '2023-01-01' GROUP BY T1.user_id, T1.username ORDER BY follower_count DESC LIMIT 10;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.users ( user_id.text, username.text, email.text, password_hash.text, full_name.text, profile_picture_url.text, bio.text, location.text, created_at.timestamp, updated_at.timestamp, is_verified.boolean )
CREATE TABLE social_media.posts ( post_id.text, user_id.text, content.text, media_url.text, media_type.text, created_at.timestamp, updated_at.timestamp, visibility.text, location_lat.numeric, location_lon.numeric )
CREATE TABLE social_media.comments ( comment_id.text, post_id.text, user_id.text, parent_comment_id.text, content.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE social_media.likes ( like_id.text, user_id.text, post_id.text, comment_id.text, created_at.timestamp )
CREATE TABLE social_media.follows ( follow_id.text, follower_user_id.text, following_user_id.text, created_at.timestamp )
CREATE TABLE social_media.conversation_participants ( participant_id.text, conversation_id.text, user_id.text, joined_at.timestamp, last_read_at.timestamp )


[User] I want to see each active agent and the total premium_amount of the policies they sold in 2024.

[Assistant]
SELECT a.agent_id, a.first_name, a.last_name, SUM(p.premium_amount) AS total_premium
FROM insurance.agents a
JOIN insurance.policies p ON a.agent_id = p.agent_id
WHERE p.issued_at >= '2024-01-01'::timestamp
  AND p.issued_at < '2025-01-01'::timestamp
  AND a.status = 'Active'
GROUP BY a.agent_id, a.first_name, a.last_name;

[User] Actually, only include agents whose policies have coverage_limit above 100000.

[Assistant]
SELECT a.agent_id, a.first_name, a.last_name, SUM(p.premium_amount) AS total_premium
FROM insurance.agents a
JOIN insurance.policies p ON a.agent_id = p.agent_id
WHERE p.issued_at >= '2024-01-01'::timestamp
  AND p.issued_at < '2025-01-01'::timestamp
  AND a.status = 'Active'
  AND p.coverage_limit > 100000
GROUP BY a.agent_id, a.first_name, a.last_name;

[User] Also, show the most recent policy start_date for each agent as latest_start.

[Assistant]
SELECT a.agent_id, a.first_name, a.last_name, SUM(p.premium_amount) AS total_premium, MAX(p.start_date) AS latest_start
FROM insurance.agents a
JOIN insurance.policies p ON a.agent_id = p.agent_id
WHERE p.issued_at >= '2024-01-01'::timestamp
  AND p.issued_at < '2025-01-01'::timestamp
  AND a.status = 'Active'
  AND p.coverage_limit > 100000
GROUP BY a.agent_id, a.first_name, a.last_name;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE 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) )
CREATE TABLE insurance.policies ( policy_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, product_id character varying(64) NOT NULL, agent_id character varying(64), policy_number character varying(100) NOT NULL UNIQUE, start_date date NOT NULL, end_date date NOT NULL, premium_amount numeric(12, 2) NOT NULL, coverage_limit numeric(15, 2) NOT NULL, deductible numeric(10, 2) NOT NULL, status character varying(30) NOT NULL, issued_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, cancellation_date date, cancellation_reason text, PRIMARY KEY (policy_id) )
CREATE TABLE insurance.claims ( claim_id.text, policy_id.text, customer_id.text, incident_date.timestamp, reported_date.timestamp, description.text, estimated_loss.numeric, status.text, settlement_amount.numeric, settlement_date.date, claim_handler_id.text, police_report_number.text )
CREATE TABLE insurance.agents ( agent_id text, first_name text, last_name text, agency_name text, license_number text, license_state text, contact_email text, contact_phone text, hire_date date, termination_date date, status text, commission_rate numeric, manager_id text )
CREATE TABLE insurance.premium_payments (
    payment_id character varying(64) NOT NULL, -- unique identifier for the payment
    policy_id character varying(64) NOT NULL, -- identifier of the policy the payment is for (FK to policies)
    customer_id character varying(64) NOT NULL, -- identifier of the customer making the payment (FK to customers)
    payment_date timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- date the payment was received
    amount_paid numeric(12, 2) NOT NULL, -- amount of the payment
    payment_method character varying(50), -- e.g., Credit Card, Bank Transfer, Check
    transaction_reference character varying(128) UNIQUE, -- reference from payment processor
    due_date date, -- due date for this payment installment
    payment_period_start date, -- start date of the period this payment covers
    payment_period_end date, -- end date of the period this payment covers
    status character varying(30) NOT NULL DEFAULT 'Completed', -- e.g., Completed, Pending, Failed, Refunded
    PRIMARY KEY (payment_id)
)


[User] Retrieve each citizen's first_name, last_name, and their most recent notification's message_subject and sent_at, only for notifications sent via 'Email'.

[Assistant]
SELECT c.first_name,
       c.last_name,
       n.message_subject,
       n.sent_at
FROM government_services.citizens c
JOIN (
  SELECT DISTINCT ON (citizen_id)
         citizen_id,
         message_subject,
         sent_at
  FROM government_services.notifications
  WHERE channel = 'Email'
  ORDER BY citizen_id, sent_at DESC
) n ON c.citizen_id = n.citizen_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens ( citizen_id character varying(64) NOT NULL, national_id_number character varying(128) NOT NULL UNIQUE, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, date_of_birth date NOT NULL, gender character varying(20), primary_address text NOT NULL, contact_email character varying(128) UNIQUE, contact_phone character varying(32), registration_date timestamp NOT NULL, is_verified boolean DEFAULT false, PRIMARY KEY (citizen_id) )
CREATE TABLE government_services.employees ( employee_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, first_name character varying(100) NOT NULL, last_name character varying(100) NOT NULL, job_title character varying(150) NOT NULL, department character varying(100), work_email character varying(128) NOT NULL UNIQUE, work_phone character varying(32), hire_date date NOT NULL, termination_date date, access_level character varying(50), manager_employee_id character varying(64), PRIMARY KEY (employee_id) )
CREATE TABLE government_services.service_locations ( location_id character varying(64) NOT NULL, agency_id character varying(64) NOT NULL, location_name character varying(200), address text NOT NULL, city character varying(100), state character varying(50), postal_code character varying(20), latitude numeric(9, 6), longitude numeric(9, 6), operating_hours text, contact_phone character varying(32), is_accessible boolean, PRIMARY KEY (location_id) )
CREATE TABLE government_services.appointments ( appointment_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, employee_id character varying(64), location_id character varying(64), service_id character varying(64), scheduled_start_time timestamp NOT NULL, scheduled_end_time timestamp, purpose text NOT NULL, status character varying(30) NOT NULL, booking_method character varying(50), created_at timestamp NOT NULL, notes text, PRIMARY KEY (appointment_id) )
CREATE TABLE government_services.notifications ( notification_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, application_id character varying(64), message_subject character varying(255), message_body text NOT NULL, channel character varying(30) NOT NULL, sent_at timestamp NOT NULL, status character varying(30) NOT NULL, related_entity_type character varying(50), related_entity_id character varying(64), PRIMARY KEY (notification_id) )


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

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

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


[User] How many beneficiaries has each unique relationship type? List relationship and the count.

[Assistant]
SELECT relationship, COUNT(*) AS beneficiary_count
FROM insurance.policy_beneficiaries
GROUP BY relationship;

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


[User] For each user, show their user ID and the count of unique wallet addresses they own.

[Assistant] SELECT user_id, COUNT(DISTINCT address) FROM wallets GROUP BY user_id;

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


[User] Can you help me get the total number of operational platforms across all stations?

[Assistant] db.platforms.countDocuments({ status: 'Operational' });

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
// db.createCollection('platforms')
// Optional: db.platforms.createIndex({ platform_id: 1 }, { unique: true })
// Optional: db.platforms.createIndex({ station_id: 1 })
{
  _id: ObjectId(),
  platform_id: "plat_123", // String (unique)
  station_id: "station_xyz", // String (references stations.station_id)
  platform_number: "1A", // String
  track_number: "T1", // String
  status: "Operational", // String ('Operational', 'Maintenance', 'Closed')
  length_meters: 250.50, // Decimal128 or Double
  accessible: true // Boolean
}
// db.createCollection('routes')
// Optional: db.routes.createIndex({ route_id: 1 }, { unique: true })
{
  _id: ObjectId(),
  route_id: "route_ne_corr", // String (unique)
  route_name: "Northeast Corridor", // String
  description: "High-speed rail linking Boston and Washington D.C.", // String
  origin_station_id: "station_bos", // String (references stations.station_id)
  destination_station_id: "station_was", // String (references stations.station_id)
  is_active: true // Boolean
}
// db.createCollection('route_stations')
// Optional: db.route_stations.createIndex({ route_station_id: 1 }, { unique: true })
// Optional: db.route_stations.createIndex({ route_id: 1, sequence_order: 1 }, { unique: true })
{
  _id: ObjectId(),
  route_station_id: "rs_ne_1", // String (unique)
  route_id: "route_ne_corr", // String (references routes.route_id)
  station_id: "station_bos", // String (references stations.station_id)
  sequence_order: 1, // Int32
  distance_from_previous_km: null, // Decimal128 or Double (null for first stop)
  typical_stop_duration_minutes: null // Int32 (null for origin/destination or if no stop)
}
// --- OR --- Embed within the Route document:
// {
//   _id: ObjectId(), route_id: "route_ne_corr", ...,
//   stations: [
//     { station_id: "station_bos", sequence_order: 1, distance_from_previous_km: null, typical_stop_duration_minutes: null },
//     { station_id: "station_pvd", sequence_order: 2, distance_from_previous_km: 70.5, typical_stop_duration_minutes: 5 },
//     ...
//   ]
// }
// db.createCollection('schedules')
// Optional: db.schedules.createIndex({ schedule_id: 1 }, { unique: true })
// Optional: db.schedules.createIndex({ route_id: 1, departure_datetime: 1 })
{
  _id: ObjectId(),
  schedule_id: "sched_1122", // String (unique)
  train_id: "train_789", // String (references trains.train_id)
  route_id: "route_ne_corr", // String (references routes.route_id)
  departure_datetime: ISODate("2024-05-10T08:00:00-04:00"), // Date (with timezone)
  arrival_datetime: ISODate("2024-05-10T15:30:00-04:00"), // Date (with timezone)
  status: "Scheduled", // String ('Scheduled', 'On Time', 'Delayed', 'Cancelled', 'Arrived')
  notes: "Track work expected near Philadelphia" // String
}
// db.createCollection('schedule_stops')
// Optional: db.schedule_stops.createIndex({ stop_id: 1 }, { unique: true })
// Optional: db.schedule_stops.createIndex({ schedule_id: 1, sequence_order: 1 }, { unique: true })
{
  _id: ObjectId(),
  stop_id: "stop_sched1122_1", // String (unique)
  schedule_id: "sched_1122", // String (references schedules.schedule_id)
  station_id: "station_bos", // String (references stations.station_id)
  platform_id: "plat_bos_3", // String (references platforms.platform_id, nullable)
  sequence_order: 1, // Int32
  scheduled_arrival_time: null, // Date
  scheduled_departure_time: ISODate("2024-05-10T08:00:00-04:00"), // Date
  actual_arrival_time: null, // Date
  actual_departure_time: ISODate("2024-05-10T08:01:00-04:00"), // Date
  status: "On Time" // String
}
// --- OR --- Embed within the Schedule document using an array 'stops'
// db.createCollection('passengers')
// Optional: db.passengers.createIndex({ passenger_id: 1 }, { unique: true })
// Optional: db.passengers.createIndex({ email: 1 }, { unique: true, sparse: true })
// Optional: db.passengers.createIndex({ phone_number: 1 }, { unique: true, sparse: true })
{
  _id: ObjectId(),
  passenger_id: "pass_pqr", // String (unique)
  first_name: "Alice", // String
  last_name: "Smith", // String
  email: "alice.smith@example.com", // String (unique, sparse)
  phone_number: "+15551234567", // String (unique, sparse)
  date_of_birth: ISODate("1990-03-20"), // Date
  loyalty_program_id: "LOYALTY123", // String
  created_at: ISODate("2023-02-01T11:00:00Z") // Date
}
// db.createCollection('staff')
// Optional: db.staff.createIndex({ staff_id: 1 }, { unique: true })
// Optional: db.staff.createIndex({ employee_number: 1 }, { unique: true })
// Optional: db.staff.createIndex({ contact_email: 1 }, { unique: true, sparse: true })
{
  _id: ObjectId(),
  staff_id: "staff_mno", // String (unique)
  first_name: "Bob", // String
  last_name: "Jones", // String
  role: "Conductor", // String
  primary_station_id: null, // String (references stations.station_id, nullable)
  employee_number: "E12345", // String (unique)
  hire_date: ISODate("2018-06-01"), // Date
  contact_email: "bob.jones@example-rail.com", // String (unique, sparse)
  contact_phone: "+15559876543", // String
  is_active: true // Boolean
}


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

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

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

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

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

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

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


[User] List the content and sent time for messages sent by user 'U101'.

[Assistant] SELECT content, sent_at FROM social_media.messages WHERE sender_user_id = 'U101';

[User] Could you also include the group name for those messages and only show messages sent in group chats?

[Assistant] SELECT m.content, m.sent_at, c.name AS group_name FROM social_media.messages m JOIN social_media.conversations c ON m.conversation_id = c.conversation_id WHERE m.sender_user_id = 'U101' AND c.type = 'group';

[User] Now filter to include only messages sent in June 2024 and order them by sent time descending.

[Assistant] SELECT m.content, m.sent_at, c.name AS group_name FROM social_media.messages m JOIN social_media.conversations c ON m.conversation_id = c.conversation_id WHERE m.sender_user_id = 'U101' AND c.type = 'group' AND m.sent_at >= '2024-06-01' AND m.sent_at < '2024-07-01' ORDER BY m.sent_at DESC;

[User] Also limit the results to the top 15.

[Assistant] SELECT m.content, m.sent_at, c.name AS group_name FROM social_media.messages m JOIN social_media.conversations c ON m.conversation_id = c.conversation_id WHERE m.sender_user_id = 'U101' AND c.type = 'group' AND m.sent_at >= '2024-06-01' AND m.sent_at < '2024-07-01' ORDER BY m.sent_at DESC LIMIT 15;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.messages (
    message_id character varying(64) NOT NULL, -- unique identifier for the message
    conversation_id character varying(64) NOT NULL, -- identifier for the conversation thread (FK to conversations.conversation_id)
    sender_user_id character varying(64) NOT NULL, -- identifier of the sender (FK to users.user_id)
    content text, -- textual content of the message
    media_url text, -- URL to attached media (image/video)
    media_type character varying(20), -- type of media ('image', 'video', null)
    sent_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp when message was sent
    read_at timestamp, -- timestamp when message was read by recipient(s)
    PRIMARY KEY (message_id)
)


[User] Show me the top 5 users who have interacted with DApps, along with the count of distinct DApps they interacted with and their wallet addresses.

[Assistant] SELECT w.user_id, COUNT(DISTINCT d.dapp_id) AS dapp_count, w.address FROM trading_platform.wallets w JOIN trading_platform.dapps d ON 1=1 GROUP BY w.user_id, w.address ORDER BY dapp_count DESC LIMIT 5;

[User] This query doesn't properly show DApp interactions. Please modify it to correctly join with a table that records user-DApp interactions.

[Assistant] I notice there's no interaction table in the provided schema. Without a table recording user-DApp interactions, I cannot generate this query accurately. Would you like to see users who have wallets and DApps separately instead?

[User] You're right. Instead, show me users who have wallets but have never interacted with any DApps, along with their wallet addresses.

[Assistant] SELECT w.user_id, w.address FROM trading_platform.wallets w WHERE NOT EXISTS (SELECT 1 FROM trading_platform.dapps d WHERE 1=1) GROUP BY w.user_id, w.address;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.wallets ( wallet_id.text, user_id.text, address.text, private_key.text, created_at.timestamp )
CREATE TABLE trading_platform.trades ( trade_id character varying(64) NOT NULL, order_id character varying(64) NOT NULL, buyer_id character varying(64) NOT NULL, seller_id character varying(64) NOT NULL, asset_id character varying(64) NOT NULL, quantity numeric(38,14) NOT NULL, price numeric(38,14) NOT NULL, traded_at timestamp NOT NULL, PRIMARY KEY (trade_id) )
CREATE TABLE trading_platform.assets ( asset_id.text, name.text, symbol.text, type.text )
CREATE TABLE trading_platform.dapps (
    dapp_id character varying(64) NOT NULL,  -- unique identifier for the DApp
    name character varying(128) NOT NULL, -- name of the DApp
    description text NOT NULL, -- description of the DApp
    url character varying(256) NOT NULL, -- URL of the DApp
    PRIMARY KEY (dapp_id)
)
CREATE TABLE trading_platform.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] How many appointments were created in the last 24 hours?

[Assistant] SELECT COUNT(*) FROM healthcare.appointments WHERE created_at >= NOW() - INTERVAL '24 hours';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.appointments ( appointment_id character varying(64) NOT NULL, patient_id character varying(64) NOT NULL, doctor_id character varying(64) NOT NULL, appointment_time timestamp with time zone NOT NULL, duration_minutes integer NOT NULL, reason text, status character varying(32) NOT NULL, location_id character varying(64), notes text, created_at timestamp with time zone NOT NULL DEFAULT current_timestamp, PRIMARY KEY (appointment_id) )


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

[Assistant] SELECT patient_id, record_date, vitals FROM healthcare.medical_records WHERE (vitals->>'blood_pressure_systolic')::integer > 140;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.medical_records (
    record_id character varying(64) NOT NULL,  -- unique identifier for the medical record entry
    patient_id character varying(64) NOT NULL, -- FK to patients table
    appointment_id character varying(64) UNIQUE, -- FK to appointments table (can be null if record not tied to specific appt)
    doctor_id character varying(64) NOT NULL, -- FK to doctors table (doctor creating the record)
    record_date timestamp with time zone NOT NULL, -- date the record/observation was made
    chief_complaint text, -- patient's primary reason for visit
    present_illness_history text, -- detailed history of the current issue
    past_medical_history text, -- relevant past conditions/surgeries
    physical_examination_notes text, -- findings from the physical exam
    assessment text, -- doctor's assessment/diagnosis summary
    treatment_plan text, -- planned course of action
    vitals jsonb, -- store vitals like BP, HR, Temp as structured JSON
    created_at timestamp with time zone NOT NULL DEFAULT current_timestamp,
    PRIMARY KEY (record_id)
)


[User] Find pairs of insurance policies where the plan_id is the same, but they belong to different patients. Show the plan_id, and the patient_id and policy_number for both policies in the pair.

[Assistant] SELECT T1.plan_id, T1.patient_id AS patient_id_1, T1.policy_number AS policy_number_1, T2.patient_id AS patient_id_2, T2.policy_number AS policy_number_2 FROM healthcare.patient_insurance AS T1 JOIN healthcare.patient_insurance AS T2 ON T1.plan_id = T2.plan_id WHERE T1.patient_id <> T2.patient_id AND T1.patient_insurance_id < T2.patient_insurance_id;

[User] Refine this to only include policies that are currently active (expiration_date IS NULL or > CURRENT_DATE) for both policies in the pair.

[Assistant] SELECT T1.plan_id, T1.patient_id AS patient_id_1, T1.policy_number AS policy_number_1, T2.patient_id AS patient_id_2, T2.policy_number AS policy_number_2 FROM healthcare.patient_insurance AS T1 JOIN healthcare.patient_insurance AS T2 ON T1.plan_id = T2.plan_id WHERE T1.patient_id <> T2.patient_id AND T1.patient_insurance_id < T2.patient_insurance_id AND (T1.expiration_date IS NULL OR T1.expiration_date > CURRENT_DATE) AND (T2.expiration_date IS NULL OR T2.expiration_date > CURRENT_DATE);

[User] Also, only show pairs where one policy is primary and the other is not primary (is_primary = TRUE for one, is_primary = FALSE for the other).

[Assistant] SELECT T1.plan_id, T1.patient_id AS patient_id_1, T1.policy_number AS policy_number_1, T2.patient_id AS patient_id_2, T2.policy_number AS policy_number_2 FROM healthcare.patient_insurance AS T1 JOIN healthcare.patient_insurance AS T2 ON T1.plan_id = T2.plan_id WHERE T1.patient_id <> T2.patient_id AND T1.patient_insurance_id < T2.patient_insurance_id AND (T1.expiration_date IS NULL OR T1.expiration_date > CURRENT_DATE) AND (T2.expiration_date IS NULL OR T2.expiration_date > CURRENT_DATE) AND ((T1.is_primary = TRUE AND T2.is_primary = FALSE) OR (T1.is_primary = FALSE AND T2.is_primary = TRUE));

[User] Filter further to only show pairs where the shared plan_id starts with 'HMO'.

[Assistant] SELECT T1.plan_id, T1.patient_id AS patient_id_1, T1.policy_number AS policy_number_1, T2.patient_id AS patient_id_2, T2.policy_number AS policy_number_2 FROM healthcare.patient_insurance AS T1 JOIN healthcare.patient_insurance AS T2 ON T1.plan_id = T2.plan_id WHERE T1.patient_id <> T2.patient_id AND T1.patient_insurance_id < T2.patient_insurance_id AND (T1.expiration_date IS NULL OR T1.expiration_date > CURRENT_DATE) AND (T2.expiration_date IS NULL OR T2.expiration_date > CURRENT_DATE) AND ((T1.is_primary = TRUE AND T2.is_primary = FALSE) OR (T1.is_primary = FALSE AND T2.is_primary = TRUE)) AND T1.plan_id LIKE 'HMO%';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.patient_insurance ( patient_insurance_id.text, patient_id.text, plan_id.text, policy_number.text, group_number.text, subscriber_name.text, effective_date.date, expiration_date.date, is_primary.boolean )


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

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

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

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

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

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

[User] Now order the results by avg_days_since_registration descending.

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

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


[User] Find all pairs of transactions where both transactions have the same nonce and from_address, but different transaction_id. Show both transaction IDs, the shared from_address, shared nonce, and their block numbers.

[Assistant]
SELECT t1.transaction_id AS transaction_id_1, t2.transaction_id AS transaction_id_2, t1.from_address, t1.nonce, t1.block_number AS block_number_1, t2.block_number AS block_number_2
FROM web3.transactions t1
JOIN web3.transactions t2
  ON t1.from_address = t2.from_address
 AND t1.nonce = t2.nonce
 AND t1.transaction_id < t2.transaction_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.transactions (
    transaction_id character varying(64) NOT NULL,  -- unique identifier for the transaction
    from_address character varying(128) NOT NULL, -- address of the sender
    to_address character varying(128), -- address of the receiver (can be null for contract deployment)
    value numeric(38,14) NOT NULL, -- value transferred
    gas_used integer NOT NULL, -- amount of gas used by the transaction
    gas_price numeric(38,14) NOT NULL, -- price of gas at the time of the transaction
    block_number integer NOT NULL, -- block number containing the transaction
    timestamp timestamp NOT NULL, -- time when the transaction was mined
    input_data text, -- input data of the transaction (can be null)
    status character varying(32) NOT NULL, -- status of the transaction (e.g., success, failed)
    nonce integer NOT NULL, -- nonce of the sender at the time of the transaction
    PRIMARY KEY (transaction_id)
)


[User] List the email addresses and phone numbers of all active customers.

[Assistant]
SELECT email, phone_number
FROM insurance.customers
WHERE status = 'Active';

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


[User] What is the detailed repair history of the equipment used by the staff with staff_id 'STAFF123' during maintenance tasks?

[Assistant] I'm sorry, but I can't provide information on the detailed repair history of equipment used by staff members. The data in the maintenance_records table only includes information about maintenance tasks, such as record_id, asset_id, maintenance type, and staff_id, but does not cover equipment repair histories.

System:
You are an SQL statement expert and you can refuse the user's question if the question is not related to the table structure. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE train_station_management.maintenance_records ( record_id.text, asset_id.text, asset_type.text, maintenance_type.text, staff_id.text, start_datetime.timestamp, end_datetime.timestamp, description.text, cost.numeric, status.text )


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

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

System:
You are an SQL statement expert and you can refuse the user's question if the question is not related to the table structure. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE train_station_management.platforms ( platform_id text, station_id text, platform_number text, track_number text, status text, length_meters numeric, accessible boolean )


[User] How many time entries does each client have? Provide the client's first and last name along with the count, sorted by count descending.

[Assistant] SELECT c.first_name, c.last_name, COUNT(te.entry_id) AS entry_count FROM legal_services.clients c JOIN legal_services.time_entries te ON c.client_id = te.lawyer_id GROUP BY c.first_name, c.last_name ORDER BY entry_count DESC;

[User] Actually, include only clients with more than 2 entries and also show the average billing_rate for those entries.

[Assistant] SELECT c.first_name, c.last_name, COUNT(te.entry_id) AS entry_count, AVG(te.billing_rate) AS avg_billing_rate FROM legal_services.clients c JOIN legal_services.time_entries te ON c.client_id = te.lawyer_id GROUP BY c.first_name, c.last_name HAVING COUNT(te.entry_id) > 2 ORDER BY entry_count DESC;

[User] Also, sort the results by average billing rate in ascending order.

[Assistant] SELECT c.first_name, c.last_name, COUNT(te.entry_id) AS entry_count, AVG(te.billing_rate) AS avg_billing_rate FROM legal_services.clients c JOIN legal_services.time_entries te ON c.client_id = te.lawyer_id GROUP BY c.first_name, c.last_name HAVING COUNT(te.entry_id) > 2 ORDER BY avg_billing_rate ASC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE legal_services.clients ( client_id text, first_name text, last_name text, company_name text, email text, phone text, address text, date_registered timestamp, status text )
CREATE TABLE legal_services.time_entries ( entry_id character varying(64) NOT NULL, case_id character varying(64) NOT NULL, lawyer_id character varying(64) NOT NULL, date_worked date NOT NULL, hours_spent numeric(5, 2) NOT NULL CHECK (hours_spent > 0), billing_rate numeric(10, 2) NOT NULL, description text NOT NULL, is_billable boolean DEFAULT true, is_billed boolean DEFAULT false, invoice_id character varying(64), created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (entry_id) )


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

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

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

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

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


[User] I need a list of active drivers with their names and contact details.

[Assistant] SELECT driver_id, first_name, last_name, contact_number, email FROM transportation.drivers WHERE status = 'Active';

[User] Actually, include their hire_date and filter to drivers hired before '2022-01-01'.

[Assistant] SELECT driver_id, first_name, last_name, contact_number, email, hire_date FROM transportation.drivers WHERE status = 'Active' AND hire_date < '2022-01-01';

[User] Now sort by hire_date descending and limit to the first 10 records.

[Assistant] SELECT driver_id, first_name, last_name, contact_number, email, hire_date FROM transportation.drivers WHERE status = 'Active' AND hire_date < '2022-01-01' ORDER BY hire_date DESC LIMIT 10;

[User] Also add the license_expiry_date to each record.

[Assistant] SELECT driver_id, first_name, last_name, contact_number, email, hire_date, license_expiry_date FROM transportation.drivers WHERE status = 'Active' AND hire_date < '2022-01-01' ORDER BY hire_date DESC LIMIT 10;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.drivers ( driver_id.text, employee_id.text, first_name.text, last_name.text, license_number.text, license_expiry_date.date, contact_number.text, email.text, hire_date.date, status.text )


[User] Which customers have more than one account? Please include customer_id and the number of accounts they hold.

[Assistant] SELECT customer_id, COUNT(account_id) AS account_count FROM financial_services.accounts GROUP BY customer_id HAVING COUNT(account_id) > 1;

[User] Can you also show the account_types for each customer in the result?

[Assistant] SELECT customer_id, COUNT(account_id) AS account_count, STRING_AGG(DISTINCT account_type, ', ') AS account_types FROM financial_services.accounts GROUP BY customer_id HAVING COUNT(account_id) > 1;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE financial_services.accounts ( account_id character varying(64) NOT NULL, customer_id character varying(64) NOT NULL, account_number character varying(128) NOT NULL UNIQUE, account_type character varying(50) NOT NULL, balance numeric(19, 4) NOT NULL DEFAULT 0.00, currency character varying(3) NOT NULL, opened_date date NOT NULL, status character varying(32) NOT NULL, interest_rate numeric(5, 4), last_updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, PRIMARY KEY (account_id), FOREIGN KEY (customer_id) REFERENCES financial_services.customers(customer_id) )


[User] I want to find the top 5 wallets by USD value of their ERC20 holdings. Show wallet_address, token symbol, and USD value based on the latest price.

[Assistant]
SELECT b.wallet_address, p.symbol, SUM(CAST(b.amount AS numeric) * p.price) AS usd_value
FROM erc20_balances b
JOIN token_prices_latest p ON b.contract_address = p.address
GROUP BY b.wallet_address, p.symbol
ORDER BY usd_value DESC
LIMIT 5;

[User] Include the decimals from the price table in the output.

[Assistant]
SELECT b.wallet_address, p.symbol, p.decimals,
       SUM(CAST(b.amount AS numeric) * p.price) AS usd_value
FROM erc20_balances b
JOIN token_prices_latest p ON b.contract_address = p.address
GROUP BY b.wallet_address, p.symbol, p.decimals
ORDER BY usd_value DESC
LIMIT 5;

[User] Only consider wallets where the USD value is greater than 1000 and limit to top 3 entries.

[Assistant]
SELECT b.wallet_address, p.symbol, p.decimals,
       SUM(CAST(b.amount AS numeric) * p.price) AS usd_value
FROM erc20_balances b
JOIN token_prices_latest p ON b.contract_address = p.address
GROUP BY b.wallet_address, p.symbol, p.decimals
HAVING SUM(CAST(b.amount AS numeric) * p.price) > 1000
ORDER BY usd_value DESC
LIMIT 3;

[User] Group the total USD value per wallet across all tokens instead of per token, then list top 3 wallets.

[Assistant]
SELECT b.wallet_address,
       SUM(CAST(b.amount AS numeric) * p.price) AS total_usd_value
FROM erc20_balances b
JOIN token_prices_latest p ON b.contract_address = p.address
GROUP BY b.wallet_address
HAVING SUM(CAST(b.amount AS numeric) * p.price) > 1000
ORDER BY total_usd_value DESC
LIMIT 3;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE erc1155_approval_for_all (
    block_number bigint NOT NULL, -- Block number containing the transaction
    block_timestamp timestamp(3) NOT NULL, -- Timestamp of the block containing the transaction
    transaction_index integer NOT NULL, -- Index of the transaction within the block
    transaction_hash varchar(66) NOT NULL, -- Transaction hash
    log_index integer NOT NULL, -- Log index
    contract_address varchar(42) NOT NULL  -- Event contract address
)
CREATE TABLE erc20_balances ( block_number bigint, contract_address varchar, wallet_address varchar, amount varchar, pk varchar )
CREATE TABLE erc20_balances_historical ( block_number bigint, contract_address text, wallet_address text, amount text, pk integer )
CREATE TABLE nft_holders ( block_number.bigint, contract_address.text, wallet_address.text, token_id.text, contract_type.text, amount.text, pk.text )
CREATE TABLE sui_coins ( object_id varchar NOT NULL, status varchar NOT NULL, coin_type varchar NOT NULL, balance varchar NOT NULL, owner varchar NOT NULL )
CREATE TABLE sui_coins_metadata (
    object_id varchar NOT NULL, -- object id of the coin metadata object
    coin_type varchar NOT NULL, -- coin type, eg. 0x...66::reap_token::REAP_TOKEN
    status varchar NOT NULL, -- coin status, eg. exists, deleted
    decimals bigint NOT NULL, -- decimals of the coin
    description varchar NOT NULL, -- description of the coin
    icon_url varchar NOT NULL, -- icon url of the coin
    symbol varchar NOT NULL, -- symbol of the coin
    name varchar NOT NULL  -- name of the coin
)
CREATE TABLE token_prices_latest ( blockchain.text, address.text, decimals.bigint, symbol.text, price.real, timestamp.timestamp )
CREATE TABLE erc20_approval ( block_number.bigint, block_timestamp.timestamp, transaction_index.integer, transaction_hash.text, log_index.integer, contract_address.text, pk.integer )
CREATE TABLE token_activities ( block_timestamp.timestamp, block_number.bigint, tx_index.integer, tx_hash.text, log_index.integer, type.text, tick.text, id.text, amt.decimal, from_address.text, to_address.text )
CREATE TABLE token_balances_bitcoin (
    block_number bigint NOT NULL, -- Block number containing the transaction
    block_timestamp timestamp(3) NOT NULL, -- Block timestamp containing the transaction
    tick varchar(255) NOT NULL, -- Ticker: Identifier of the inscription
    wallet_address varchar(42) NOT NULL, -- Address of owner
    total_supply varchar NOT NULL, -- Max supply: Set max supply of the inscription
    amount varchar NOT NULL  -- The balance of wallet balance at the corresponding block height
)
CREATE TABLE token_info_avalanche ( block_timestamp timestamp, block_number bigint, tx_index integer, tx_hash varchar, tick varchar, max_supply decimal, lim decimal, wlim decimal, dec integer, creator varchar, minted decimal, holders decimal, txs decimal, updated_timestamp timestamp, completed_timestamp timestamp, id varchar )


[User] Show me all trips that were completed with vehicles manufactured after 2020, including the vehicle make and model.

[Assistant] SELECT t.trip_id, v.make, v.model FROM transportation.trips t JOIN transportation.vehicles v ON t.vehicle_id = v.vehicle_id WHERE t.status = 'Completed' AND v.year > 2020;

[User] Now include the driver's first and last name for these trips, and filter to only show trips with passenger counts greater than 5.

[Assistant] SELECT t.trip_id, v.make, v.model, d.first_name, d.last_name FROM transportation.trips t JOIN transportation.vehicles v ON t.vehicle_id = v.vehicle_id JOIN transportation.drivers d ON t.driver_id = d.driver_id WHERE t.status = 'Completed' AND v.year > 2020 AND t.passenger_count > 5;

[User] Can you order these results by the vehicle make in ascending order and then by passenger count in descending order?

[Assistant] SELECT t.trip_id, v.make, v.model, d.first_name, d.last_name, t.passenger_count FROM transportation.trips t JOIN transportation.vehicles v ON t.vehicle_id = v.vehicle_id JOIN transportation.drivers d ON t.driver_id = d.driver_id WHERE t.status = 'Completed' AND v.year > 2020 AND t.passenger_count > 5 ORDER BY v.make ASC, t.passenger_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.vehicles ( vehicle_id character varying(64) NOT NULL, license_plate character varying(32) NOT NULL UNIQUE, vin character varying(17) UNIQUE, make character varying(64) NOT NULL, model character varying(64) NOT NULL, year integer NOT NULL, type character varying(32) NOT NULL, capacity integer, fuel_type character varying(32) NOT NULL, status character varying(32) NOT NULL, depot_id character varying(64), acquisition_date date, PRIMARY KEY (vehicle_id) )
CREATE TABLE transportation.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.trips (
    trip_id character varying(64) NOT NULL,  -- unique identifier for a specific trip instance
    route_id character varying(64), -- identifier of the route being followed (can be null for ad-hoc trips)
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle used
    driver_id character varying(64) NOT NULL, -- identifier of the driver operating
    scheduled_departure timestamp with time zone NOT NULL, -- planned departure time
    actual_departure timestamp with time zone, -- actual departure time
    scheduled_arrival timestamp with time zone NOT NULL, -- planned arrival time
    actual_arrival timestamp with time zone, -- actual arrival time
    origin_location_id character varying(64) NOT NULL, -- actual starting location (could differ from route origin)
    destination_location_id character varying(64) NOT NULL, -- actual ending location (could differ from route destination)
    status character varying(32) NOT NULL, -- e.g., Scheduled, In Progress, Completed, Delayed, Cancelled
    passenger_count integer, -- number of passengers (if applicable)
    cargo_manifest_id character varying(64), -- link to cargo details (if applicable)
    PRIMARY KEY (trip_id)
)
CREATE TABLE transportation.locations (
    location_id character varying(64) NOT NULL,  -- unique identifier for the location
    name character varying(255) NOT NULL, -- name of the location (e.g., Central Station, Depot Alpha, Pier 7)
    type character varying(64) NOT NULL, -- e.g., Station, Stop, Depot, Port, Airport, Customer Address
    address_line1 character varying(255), -- street address
    city character varying(128), -- city name
    state_province character varying(128), -- state or province
    postal_code character varying(32), -- postal code
    country character varying(64) NOT NULL, -- country name
    latitude numeric(9, 6), -- geographic latitude
    longitude numeric(9, 6), -- geographic longitude
    timezone character varying(64), -- IANA timezone name (e.g., America/New_York)
    PRIMARY KEY (location_id)
)
CREATE TABLE transportation.maintenance_logs (
    log_id character varying(64) NOT NULL,  -- unique identifier for the maintenance record
    vehicle_id character varying(64) NOT NULL, -- identifier of the vehicle serviced
    service_date date NOT NULL, -- date the service was performed
    odometer_reading integer, -- vehicle mileage at time of service
    service_type character varying(128) NOT NULL, -- type of service (e.g., Oil Change, Tire Rotation, Engine Repair)
    description text NOT NULL, -- detailed description of work done
    cost numeric(10, 2), -- cost of the service
    mechanic_name character varying(128), -- name or ID of the mechanic/shop
    next_service_due_date date, -- recommended date for next service
    PRIMARY KEY (log_id)
)
CREATE TABLE transportation.passengers (
    passenger_id character varying(64) NOT NULL,  -- unique identifier for the passenger
    first_name character varying(128) NOT NULL, -- passenger's first name
    last_name character varying(128) NOT NULL, -- passenger's last name
    email character varying(128) UNIQUE, -- email address
    phone_number character varying(32) UNIQUE, -- phone number
    date_of_birth date, -- passenger's date of birth
    loyalty_program_id character varying(64), -- identifier for loyalty program membership
    created_at timestamp with time zone NOT NULL, -- time when the passenger record was created
    PRIMARY KEY (passenger_id)
)
CREATE TABLE transportation.bookings ( booking_id character varying(64) NOT NULL, passenger_id character varying(64) NOT NULL, trip_id character varying(64) NOT NULL, seat_number character varying(16), booking_time timestamp with time zone NOT NULL, status character varying(32) NOT NULL, fare numeric(10, 2) NOT NULL, payment_transaction_id character varying(128), special_requests text, PRIMARY KEY (booking_id) )


[User] For each vehicle, list the vehicle_id and the total number of trips it has performed.

[Assistant] SELECT vehicle_id, COUNT(*) AS trip_count FROM transportation.trips GROUP BY vehicle_id;

[User] Can you limit this to only vehicles that have more than 10 trips?

[Assistant] SELECT vehicle_id, COUNT(*) AS trip_count FROM transportation.trips GROUP BY vehicle_id HAVING COUNT(*) > 10;

[User] In addition, for these vehicles, can you show the driver_id who has driven the highest number of trips for each vehicle?

[Assistant] SELECT vehicle_id, driver_id, trip_driver_count FROM (SELECT vehicle_id, driver_id, COUNT(*) AS trip_driver_count, ROW_NUMBER() OVER (PARTITION BY vehicle_id ORDER BY COUNT(*) DESC) as rn FROM transportation.trips GROUP BY vehicle_id, driver_id) t WHERE rn = 1 AND vehicle_id IN (SELECT vehicle_id FROM transportation.trips GROUP BY vehicle_id HAVING COUNT(*) > 10);

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE transportation.trips ( trip_id character varying(64) NOT NULL, route_id character varying(64), vehicle_id character varying(64) NOT NULL, driver_id character varying(64) NOT NULL, scheduled_departure timestamp with time zone NOT NULL, actual_departure timestamp with time zone, scheduled_arrival timestamp with time zone NOT NULL, actual_arrival timestamp with time zone, origin_location_id character varying(64) NOT NULL, destination_location_id character varying(64) NOT NULL, status character varying(32) NOT NULL, passenger_count integer, cargo_manifest_id character varying(64), PRIMARY KEY (trip_id) )


[User] Calculate the average number of days between when an incident occurred and when the claim was reported, but only for claims that were settled in the year 2023.

[Assistant]
SELECT
  AVG(EXTRACT(EPOCH FROM (reported_date - incident_date)) / 86400.0)::numeric(10, 2)
FROM
  insurance.claims
WHERE
  settlement_date IS NOT NULL AND EXTRACT(YEAR FROM settlement_date) = 2023;

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


[User] Provide a report of each user with their username and the count of all log entries from the last 30 days.

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

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

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

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

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

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

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

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


[User] List the content and creation time of all posts made in the last 7 days.

[Assistant] SELECT content, created_at FROM social_media.posts WHERE created_at >= NOW() - INTERVAL '7 day';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.posts ( post_id.text, user_id.text, content.text, media_url.text, media_type.text, created_at.timestamp, updated_at.timestamp, visibility.text, location_lat.numeric, location_lon.numeric )


[User] Find the total number of documents uploaded by each citizen along with their first and last names.

[Assistant]
SELECT c.citizen_id, c.first_name, c.last_name, COUNT(d.document_id) AS document_count
FROM government_services.citizens c
LEFT JOIN government_services.documents d ON c.citizen_id = d.citizen_id
GROUP BY c.citizen_id, c.first_name, c.last_name;

[User] Actually, I only want to include those citizens who have uploaded documents in the last 30 days.

[Assistant]
SELECT c.citizen_id, c.first_name, c.last_name, COUNT(d.document_id) AS document_count
FROM government_services.citizens c
JOIN government_services.documents d ON c.citizen_id = d.citizen_id
WHERE d.upload_timestamp >= NOW() - INTERVAL '30 days'
GROUP BY c.citizen_id, c.first_name, c.last_name;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens (
    citizen_id character varying(64) NOT NULL,  -- unique identifier for the citizen
    national_id_number character varying(128) NOT NULL UNIQUE, -- official national identification number
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    date_of_birth date NOT NULL,
    gender character varying(20),
    primary_address text NOT NULL, -- full primary residential address
    contact_email character varying(128) UNIQUE,
    contact_phone character varying(32),
    registration_date timestamp NOT NULL, -- when the citizen profile was created
    is_verified boolean DEFAULT false, -- whether identity has been officially verified
    PRIMARY KEY (citizen_id)
)
CREATE TABLE government_services.services (
    service_id character varying(64) NOT NULL, -- unique identifier for the service
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    service_name character varying(255) NOT NULL, -- name of the service (e.g., Driver's License Renewal)
    description text,
    category character varying(100), -- e.g., Licensing, Benefits, Taxation, Permits
    eligibility_criteria text, -- description of who is eligible
    standard_fee numeric(10, 2) DEFAULT 0.00, -- typical fee for the service
    average_processing_time_days integer, -- estimated processing time
    is_active boolean DEFAULT true, -- whether the service is currently offered
    online_application_url character varying(255),
    PRIMARY KEY (service_id)
)
CREATE TABLE government_services.documents ( document_id text PRIMARY KEY, application_id text, citizen_id text, document_type text, file_reference text, upload_timestamp timestamp, expiry_date date, verification_status text, verified_by_employee_id text, verification_timestamp timestamp )
CREATE TABLE government_services.payments ( payment_id text, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees (
    employee_id character varying(64) NOT NULL, -- unique identifier for the government employee
    agency_id character varying(64) NOT NULL, -- FK to agencies table
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    job_title character varying(150) NOT NULL,
    department character varying(100),
    work_email character varying(128) NOT NULL UNIQUE,
    work_phone character varying(32),
    hire_date date NOT NULL,
    termination_date date, -- null if currently employed
    access_level character varying(50), -- Role or permission level
    manager_employee_id character varying(64), -- FK to self for reporting structure
    PRIMARY KEY (employee_id)
)
CREATE TABLE government_services.appointments ( appointment_id character varying(64) NOT NULL, citizen_id character varying(64) NOT NULL, employee_id character varying(64), location_id character varying(64), service_id character varying(64), scheduled_start_time timestamp NOT NULL, scheduled_end_time timestamp, purpose text NOT NULL, status character varying(30) NOT NULL, booking_method character varying(50), created_at timestamp NOT NULL, notes text, PRIMARY KEY (appointment_id) )


[User] For each lawyer, show their first name, last name, and the total number of documents they have uploaded, along with the names of the law firms they belong to.

[Assistant]
SELECT l.first_name, l.last_name, f.firm_name, COUNT(d.document_id) AS document_count
FROM legal_services.lawyers l
LEFT JOIN legal_services.law_firms f ON l.firm_id = f.firm_id
LEFT JOIN legal_services.documents d ON l.lawyer_id = d.uploaded_by_lawyer_id
GROUP BY l.lawyer_id, l.first_name, l.last_name, f.firm_name;

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


[User] For each chain, show the total token_amount and usd_value for selling transactions (type=2).

[Assistant]
SELECT chain, SUM(token_amount) AS total_sold_amount, SUM(usd_value) AS total_sold_usd_value
FROM smart_money_token_inflow
WHERE type = 2
GROUP BY chain;

[User] Can you break down these results further by narrative as well?

[Assistant]
SELECT chain, narrative, SUM(token_amount) AS total_sold_amount, SUM(usd_value) AS total_sold_usd_value
FROM smart_money_token_inflow
WHERE type = 2
GROUP BY chain, narrative;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE smart_money_token_inflow ( token_address character varying(100) NOT NULL, -- the token's address token_symbol character varying(100), -- the tokens's symbol token_amount numeric(38,2), -- the absolute value of the amount if user bought minus  the amount user sold of this token usd_value numeric(38,2), -- the absolute usd value of the bought token minus sold token avg_price numeric(38,6), -- the average cost price of user spent on this token type int, -- the direction of the trade on this token. 1 means buying, 2 means selling address_amount integer, -- the amount of the user bought this token narrative character varying(100), -- the category or narrative of the token chain character varying(100), -- the chain that the token resides ,PRIMARY KEY (token_address, chain) )


[User] List all patients with active chronic diagnoses, including their diagnosis descriptions and dates.

[Assistant] SELECT p.patient_id, p.first_name, p.last_name, d.description, d.diagnosis_date FROM healthcare.patients p JOIN healthcare.diagnoses d ON p.patient_id = d.patient_id WHERE d.status = 'Active' AND d.is_chronic = true;

[User] Actually, I only need patients who were diagnosed in the last year.

[Assistant] SELECT p.patient_id, p.first_name, p.last_name, d.description, d.diagnosis_date FROM healthcare.patients p JOIN healthcare.diagnoses d ON p.patient_id = d.patient_id WHERE d.status = 'Active' AND d.is_chronic = true AND d.diagnosis_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR);

[User] Can you also include the diagnosing doctor's last name?

[Assistant] SELECT p.patient_id, p.first_name, p.last_name, d.description, d.diagnosis_date, doc.last_name AS doctor_last_name FROM healthcare.patients p JOIN healthcare.diagnoses d ON p.patient_id = d.patient_id JOIN healthcare.doctors doc ON d.doctor_id = doc.doctor_id WHERE d.status = 'Active' AND d.is_chronic = true AND d.diagnosis_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR);

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.patients ( patient_id.text, first_name.text, last_name.text, date_of_birth.date, gender.text, address.text, phone_number.text, email.text, emergency_contact_name.text, emergency_contact_phone.text, created_at.timestamp, updated_at.timestamp )
CREATE TABLE healthcare.appointments ( appointment_id.text, patient_id.text, doctor_id.text, appointment_time.timestamp, duration_minutes.integer, reason.text, status.text, location_id.text, notes.text, created_at.timestamp )
CREATE TABLE healthcare.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.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 )


[User] Retrieve the distinct generic_name values and the number of medications for each generic_name, sorted by the count descending.

[Assistant]
SELECT generic_name,
       COUNT(*) AS medication_count
FROM healthcare.medications
GROUP BY generic_name
ORDER BY medication_count DESC;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.medications ( medication_id text, medication_name text, generic_name text, manufacturer text, ndc_code text, description text )


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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE trading_platform.logs ( log_id text PRIMARY KEY, user_id text, action text, details text, logged_at timestamp )


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

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

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

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

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE financial_services.customers (
    customer_id character varying(64) NOT NULL,  -- unique identifier for the customer
    first_name character varying(100) NOT NULL, -- customer's first name
    last_name character varying(100) NOT NULL, -- customer's last name
    date_of_birth date NOT NULL, -- customer's date of birth
    ssn_hash character varying(128), -- hashed social security number (or national ID)
    address text NOT NULL, -- customer's primary address
    city character varying(100) NOT NULL,
    state character varying(50) NOT NULL,
    zip_code character varying(20) NOT NULL,
    country character varying(50) NOT NULL,
    email character varying(128) UNIQUE, -- customer's email address
    phone_number character varying(32),
    created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, -- timestamp of customer record creation
    status character varying(32) NOT NULL, -- e.g., Active, Inactive, Pending Verification
    risk_profile character varying(50), -- e.g., Low, Medium, High
    PRIMARY KEY (customer_id)
)
CREATE TABLE financial_services.securities (
    security_id character varying(64) NOT NULL, -- unique identifier for the security
    ticker_symbol character varying(20) NOT NULL UNIQUE, -- stock ticker or fund symbol
    isin_code character varying(12) UNIQUE, -- International Securities Identification Number
    cusip_code character varying(9) UNIQUE, -- CUSIP number
    security_name text NOT NULL, -- full name of the security
    security_type character varying(50) NOT NULL, -- e.g., Stock, Bond, ETF, Mutual Fund, Option, Future
    exchange character varying(50), -- primary exchange where traded (e.g., NYSE, NASDAQ)
    currency character varying(3) NOT NULL, -- currency the security is denominated in
    issuer_name character varying(255), -- name of the issuing entity
    sector character varying(100), -- industry sector
    last_updated timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (security_id)
)
CREATE TABLE financial_services.trades (
    trade_id character varying(64) NOT NULL, -- unique identifier for the trade
    account_id character varying(64) NOT NULL, -- investment account executing the trade
    security_id character varying(64) NOT NULL, -- security being traded
    order_id character varying(64), -- related order ID if applicable
    trade_type character varying(10) NOT NULL, -- 'Buy' or 'Sell'
    quantity numeric(19, 8) NOT NULL, -- number of units traded
    price_per_unit numeric(19, 8) NOT NULL, -- price per unit of the security
    total_amount numeric(19, 4) NOT NULL, -- total value of the trade (quantity * price)
    commission numeric(10, 4), -- commission fee charged for the trade
    trade_timestamp timestamp NOT NULL, -- exact time the trade was executed
    settlement_date date, -- date the trade settles
    status character varying(32) NOT NULL, -- e.g., Executed, Settled, Cancelled
    execution_venue character varying(100), -- where the trade was executed
    PRIMARY KEY (trade_id),
    FOREIGN KEY (account_id) REFERENCES financial_services.accounts(account_id),
    FOREIGN KEY (security_id) REFERENCES financial_services.securities(security_id)
)
CREATE TABLE financial_services.market_data (
    data_point_id bigserial NOT NULL, -- auto-incrementing primary key
    security_id character varying(64) NOT NULL, -- identifier for the security
    data_timestamp timestamp NOT NULL, -- timestamp for the data point (e.g., end of day, intraday)
    open_price numeric(19, 8), -- opening price for the period
    high_price numeric(19, 8), -- highest price during the period
    low_price numeric(19, 8), -- lowest price during the period
    close_price numeric(19, 8) NOT NULL, -- closing price for the period
    adjusted_close_price numeric(19, 8), -- closing price adjusted for dividends and splits
    volume bigint, -- trading volume during the period
    source character varying(50), -- source of the market data (e.g., Bloomberg, Refinitiv)
    PRIMARY KEY (data_point_id),
    UNIQUE (security_id, data_timestamp), -- Ensure unique data point per security per time
    FOREIGN KEY (security_id) REFERENCES financial_services.securities(security_id)
)
CREATE TABLE financial_services.employees (
    employee_id character varying(64) NOT NULL,  -- unique identifier for the employee
    first_name character varying(100) NOT NULL,
    last_name character varying(100) NOT NULL,
    job_title character varying(100) NOT NULL, -- e.g., Teller, Branch Manager, Financial Advisor, Analyst
    department character varying(100), -- e.g., Retail Banking, Wealth Management, IT
    branch_id character varying(64), -- Identifier for the branch they work at (if applicable)
    email character varying(128) NOT NULL UNIQUE,
    phone_extension character varying(20),
    hire_date date NOT NULL,
    termination_date date, -- Date of termination, null if currently employed
    manager_id character varying(64), -- Self-referencing key for manager relationship
    status character varying(32) NOT NULL, -- e.g., Active, Terminated, On Leave
    PRIMARY KEY (employee_id),
    FOREIGN KEY (branch_id) REFERENCES financial_services.branches(branch_id), -- Assuming a branches table exists
    FOREIGN KEY (manager_id) REFERENCES financial_services.employees(employee_id)
)


[User] How many users does each user follow? Show the follower user ID and the count.

[Assistant] SELECT follower_user_id, count(*) FROM social_media.follows GROUP BY follower_user_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE social_media.follows ( follow_id text, follower_user_id text, following_user_id text, created_at timestamp )


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

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

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


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

[Assistant] SELECT w1.wallet_id, w1.address, w1.created_at::date AS creation_date FROM web3.wallets w1 JOIN (SELECT created_at::date AS creation_date FROM web3.wallets GROUP BY created_at::date HAVING COUNT(*) > 1) w2 ON w1.created_at::date = w2.creation_date ORDER BY creation_date, w1.wallet_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE web3.wallets (
    wallet_id character varying(64) NOT NULL,  -- unique identifier for the wallet
    user_id character varying(64) NOT NULL, -- identifier of the user owning the wallet
    address character varying(128) NOT NULL, -- address of the wallet
    private_key text NOT NULL, -- private key of the wallet
    created_at timestamp NOT NULL, -- time when the wallet was created
    PRIMARY KEY (wallet_id)
)


[User] Show me all diagnoses that correspond to a medication based on matching the diagnosis_code with the medication's NDC code, and include diagnosis_id, patient_id, diagnosis_date, medication_name, and status.

[Assistant]
SELECT d.diagnosis_id, d.patient_id, d.diagnosis_date, m.medication_name, d.status
FROM healthcare.diagnoses AS d
JOIN healthcare.medications AS m
  ON d.diagnosis_code = m.ndc_code;

[User] Only include those records where the diagnosis status is 'Active'.

[Assistant]
SELECT d.diagnosis_id, d.patient_id, d.diagnosis_date, m.medication_name, d.status
FROM healthcare.diagnoses AS d
JOIN healthcare.medications AS m
  ON d.diagnosis_code = m.ndc_code
WHERE d.status = 'Active';

[User] Now refine to only chronic cases.

[Assistant]
SELECT d.diagnosis_id, d.patient_id, d.diagnosis_date, m.medication_name, d.status
FROM healthcare.diagnoses AS d
JOIN healthcare.medications AS m
  ON d.diagnosis_code = m.ndc_code
WHERE d.status = 'Active'
  AND d.is_chronic = TRUE;

[User] Finally, limit to diagnoses made after January 1, 2023.

[Assistant]
SELECT d.diagnosis_id, d.patient_id, d.diagnosis_date, m.medication_name, d.status
FROM healthcare.diagnoses AS d
JOIN healthcare.medications AS m
  ON d.diagnosis_code = m.ndc_code
WHERE d.status = 'Active'
  AND d.is_chronic = TRUE
  AND d.diagnosis_date > '2023-01-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE healthcare.diagnoses ( diagnosis_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, diagnosis_code character varying(20) NOT NULL, code_type character varying(10) NOT NULL DEFAULT 'ICD-10', description text, diagnosis_date date NOT NULL, status character varying(32) NOT NULL, is_chronic boolean DEFAULT false, PRIMARY KEY (diagnosis_id) )
CREATE TABLE healthcare.medications (
    medication_id character varying(64) NOT NULL, -- unique identifier for the medication type
    medication_name character varying(255) NOT NULL, -- common or brand name
    generic_name character varying(255), -- generic chemical name
    manufacturer character varying(100), -- drug manufacturer
    ndc_code character varying(20) UNIQUE, -- National Drug Code (optional but useful)
    description text, -- description of the medication
    PRIMARY KEY (medication_id)
)
CREATE TABLE healthcare.insurance_plans ( plan_id.text, plan_name.text, insurance_provider.text, plan_type.text, contact_phone.text, website.text )


[User] List the first and last name of each citizen along with the city and state of the service location for their agency.

[Assistant]
SELECT c.first_name, c.last_name, sl.city, sl.state
FROM government_services.citizens c
JOIN government_services.payments p ON c.citizen_id = p.citizen_id
JOIN government_services.employees e ON p.application_id IS NOT NULL AND e.agency_id IS NOT NULL
JOIN government_services.service_locations sl ON e.agency_id = sl.agency_id;

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE government_services.citizens ( citizen_id text, national_id_number text, first_name text, last_name text, date_of_birth date, gender text, primary_address text, contact_email text, contact_phone text, registration_date timestamp, is_verified boolean )
CREATE TABLE government_services.payments ( payment_id text, application_id text, citizen_id text, service_id text, amount numeric, currency text, payment_method text, payment_provider_reference text, payment_timestamp timestamp, status text, notes text )
CREATE TABLE government_services.employees ( employee_id text, agency_id text, first_name text, last_name text, job_title text, department text, work_email text, work_phone text, hire_date date, termination_date date, access_level text, manager_employee_id text )
CREATE TABLE government_services.service_locations ( location_id text, agency_id text, location_name text, address text, city text, state text, postal_code text, latitude numeric, longitude numeric, operating_hours text, contact_phone text, is_accessible boolean )


[User] Show me reviews from 'Expedia' that have an overall rating of 1 or 2.

[Assistant] SELECT review_id, property_id, guest_id, rating_overall, review_date, comment FROM hospitality_technology.reviews WHERE review_source = 'Expedia' AND rating_overall <= 2;

[User] Actually, only include those submitted in the second half of 2023.

[Assistant] SELECT review_id, property_id, guest_id, rating_overall, review_date, comment FROM hospitality_technology.reviews WHERE review_source = 'Expedia' AND rating_overall <= 2 AND review_date >= '2023-07-01' AND review_date < '2024-01-01';

System:
You are an SQL statement expert. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the user's question.
##Table Structure
CREATE TABLE hospitality_technology.reviews ( review_id.text, property_id.text, reservation_id.text, guest_id.text, rating_overall.integer, rating_cleanliness.integer, rating_service.integer, rating_location.integer, rating_value.integer, comment.text, review_source.text, review_date.timestamp, is_public.boolean, staff_response.text, response_staff_id.text, response_date.timestamp )