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training_args.json in this repo.<|im_start|>system
You are a helpful AI Assistant that provides well-reasoned and detailed responses. You first
think about the reasoning process as an internal monologue and then provide the user with
the answer. Respond in the following format: <think>
...
</think>
<answer>
...
</answer><|im_end|>
<|im_start|>user
You are a Couchbase SQL++ query expert. Given a database schema and a natural language question, generate a syntactically valid SQL++ query that precisely answers the question.
Rules:
- SELECT only the columns explicitly asked for — nothing more, nothing less
- Use the exact bucket, scope, and collection names provided in the database schema
Bucket Name:
`bird_training_bucket`
Scope Name:
`retails`
Database Schema:
{"`bird_training_bucket`.`retails`.`lineitem`": {"properties": {"l_returnflag": {"samples": ["A", "N"], "type": "string"}, "l_linestatus": {"samples": ["O", "F"], "type": "string"}, "l_linenumber": {"samples": [1, 2], "type": "number"}, "l_shipdate": {"samples": ["1994-05-15", "1995-04-13"], "type": "string"}, "l_commitdate": {"samples": ["1994-07-11", "1995-03-30"], "type": "string"}, "l_partkey": {"samples": [12164, 111506], "type": "number"}, "l_orderkey": {"samples": [798279, 368577], "type": "number"}, "l_shipmode": {"samples": ["AIR", "FOB"], "type": "string"}, "l_extendedprice": {"samples": [22687.9, 25797.5], "type": "number"}, "l_comment": {"samples": ["foxes nag. express ", "blithely even "], "type": "string"}, "l_suppkey": {"samples": [2165, 2624], "type": "number"}, "l_discount": {"samples": [0.03, 0.01], "type": "number"}, "l_tax": {"samples": [0.01, 0.02], "type": "number"}, "l_receiptdate": {"samples": ["1994-05-28", "1995-05-10"], "type": "string"}, "l_shipinstruct": {"samples": ["COLLECT COD", "DELIVER IN PERSON"], "type": "string"}, "l_quantity": {"samples": [19, 17], "type": "number"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`orders`": {"properties": {"o_orderpriority": {"samples": ["1-URGENT", "2-HIGH"], "type": "string"}, "o_totalprice": {"samples": [54905.55, 59673.25], "type": "number"}, "o_orderdate": {"samples": ["1992-05-08", "1992-07-01"], "type": "string"}, "o_orderkey": {"samples": [88773, 604867], "type": "number"}, "o_orderstatus": {"samples": ["F", "O"], "type": "string"}, "o_comment": {"samples": ["careful deposits haggle. furi", "bold regular packages boost ac..."], "type": "string"}, "o_clerk": {"samples": ["Clerk#000000090", "Clerk#000000255"], "type": "string"}, "o_shippriority": {"samples": [0], "type": "number"}, "o_custkey": {"samples": [53639, 22844], "type": "number"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`region`": {"properties": {"r_regionkey": {"samples": [0, 1], "type": "number"}, "r_comment": {"samples": ["asymptotes sublate after the r", "accounts cajole carefully acco..."], "type": "string"}, "r_name": {"samples": ["AFRICA", "AMERICA"], "type": "string"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`nation`": {"properties": {"n_name": {"samples": ["CHINA", "FRANCE"], "type": "string"}, "n_nationkey": {"samples": [7, 6], "type": "number"}, "n_regionkey": {"samples": [1, 0], "type": "number"}, "n_comment": {"samples": ["even idle instructions haggle ...", "carefully regular dependencies..."], "type": "string"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`partsupp`": {"properties": {"ps_comment": {"samples": ["final final packages according...", "fluffily unusual accounts acco..."], "type": "string"}, "ps_availqty": {"samples": [1571, 2964], "type": "number"}, "ps_suppkey": {"samples": [711, 1406], "type": "number"}, "ps_supplycost": {"samples": [457.13, 112.45], "type": "number"}, "ps_partkey": {"samples": [40710, 39914], "type": "number"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`supplier`": {"properties": {"s_nationkey": {"samples": [2, 1], "type": "number"}, "s_comment": {"samples": ["express unusual pearls cajole ...", "ironic accounts haggle about t..."], "type": "string"}, "s_phone": {"samples": ["166-376-3565", "178-939-5923"], "type": "string"}, "s_suppkey": {"samples": [5392, 419], "type": "number"}, "s_name": {"samples": ["Supplier#000005392", "Supplier#000000419"], "type": "string"}, "s_address": {"samples": ["Um58g65YsJ,,2h", "HYAHF42X17h15tzGbuLzyKM5GbgobT..."], "type": "string"}, "s_acctbal": {"samples": [170.09, 3551.51], "type": "number"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`customer`": {"properties": {"c_name": {"samples": ["Customer#000060105", "Customer#000063877"], "type": "string"}, "c_comment": {"samples": ["idly quick accounts use quickl...", "carefully bold pinto beans aff..."], "type": "string"}, "c_acctbal": {"samples": [-884.54, -451.31], "type": "number"}, "c_mktsegment": {"samples": ["BUILDING", "AUTOMOBILE"], "type": "string"}, "c_custkey": {"samples": [63877, 60105], "type": "number"}, "c_address": {"samples": [",uyDRfFMsZIJ2qHTfNpLmYhZEe", "YpIY4TGy0djER"], "type": "string"}, "c_nationkey": {"samples": [0, 1], "type": "number"}, "c_phone": {"samples": ["145-860-9523", "261-876-4905"], "type": "string"}}, "type": "object"}, "`bird_training_bucket`.`retails`.`part`": {"properties": {"p_mfgr": {"samples": ["Manufacturer#2", "Manufacturer#1"], "type": "string"}, "p_name": {"samples": ["rose indian tomato antique lin...", "deep firebrick burlywood drab ..."], "type": "string"}, "p_size": {"samples": [16, 22], "type": "number"}, "p_brand": {"samples": ["Brand#21", "Brand#23"], "type": "string"}, "p_comment": {"samples": ["fluffil", "carefully re"], "type": "string"}, "p_type": {"samples": ["LARGE ANODIZED BRASS", "LARGE PLATED BRASS"], "type": "string"}, "p_retailprice": {"samples": [1416.32, 1178.25], "type": "number"}, "p_container": {"samples": ["JUMBO DRUM", "JUMBO BOX"], "type": "string"}, "p_partkey": {"samples": [25253, 21942], "type": "number"}}, "type": "object"}}
This schema describes the structure of the data in the specified bucket and scope. It includes information about the collections, fields, and their data types.
Question:
For orders placed in 1994, show the order number and total price, and label each order as high value if it is over 100000, otherwise label it as regular.<|im_end|>
<|im_start|>assistant