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  1. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_attempt_1.metadata.json +43 -0
  2. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_attempt_2.metadata.json +43 -0
  3. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_prompt_attempt_2.txt +182 -0
  4. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_response_attempt_1.txt +4 -0
  5. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_response_attempt_2.txt +4 -0
  6. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_stderr_attempt_2.txt +0 -0
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  9. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/conversation.jsonl +4 -0
  10. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/session_summary.json +25 -0
  11. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_attempt_1.metadata.json +43 -0
  12. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_attempt_2.metadata.json +45 -0
  13. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_prompt_attempt_1.txt +180 -0
  14. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_prompt_attempt_2.txt +180 -0
  15. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_1.raw.txt +4 -0
  16. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_1.txt +4 -0
  17. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_2.raw.txt +4 -0
  18. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_2.txt +1 -0
  19. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_stderr_attempt_1.txt +0 -0
  20. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_stderr_attempt_2.txt +0 -0
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+ "attempt": 2,
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_prompt_attempt_2.txt ADDED
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1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
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+ Rules:
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+ - Use only the provided table and columns.
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+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
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+ - Prefer the planned template and bound roles when provided.
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+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
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+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
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+ - Quote identifiers with double quotes.
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+ - Return no markdown and no extra prose.
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+
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+ Dataset context:
13
+ Dataset context for SQL QA:
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+ - dataset_id: c20
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+ - dataset_name: C20
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+ - table_name: c20
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+ - table_layout: single-table dataset (do not assume joins).
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+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
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+ - task_type: classification
20
+ - target_column: class
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+ - main_row_count: 44819
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+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
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+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
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+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
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+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
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+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
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+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
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+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
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+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_tpcds_within_group_share",
136
+ "template_name": "Within-Group Share of Total",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "item_col",
143
+ "measure_col"
144
+ ]
145
+ }
146
+ ]
147
+
148
+ Problem instance:
149
+ {
150
+ "dataset_id": "c20",
151
+ "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=black_piece0_rank, measure_col=black_piece0_strength.",
152
+ "planned_template_id": "tpl_tpcds_within_group_share",
153
+ "bindings": {
154
+ "group_col": "black_piece0_rank",
155
+ "measure_col": "black_piece0_strength",
156
+ "item_col": "class",
157
+ "top_k": 13,
158
+ "top_n": 4,
159
+ "num_tiles": 10,
160
+ "percentile_value": 0.9,
161
+ "z_threshold": 2.0,
162
+ "fraction_threshold": 0.1,
163
+ "baseline_multiplier": 1.5,
164
+ "baseline_fraction": 0.1,
165
+ "min_group_size": 5,
166
+ "min_support": 5,
167
+ "measure_threshold": 6.0,
168
+ "time_grain": "month",
169
+ "lookback_rows": 3,
170
+ "current_period_start": "'2024-01-01'",
171
+ "current_period_end": "'2024-04-01'",
172
+ "previous_period_start": "'2023-10-01'",
173
+ "previous_period_end": "'2024-01-01'",
174
+ "drift_ratio_threshold": 0.8
175
+ },
176
+ "can_vary": [],
177
+ "must_fix": [],
178
+ "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
179
+ }
180
+
181
+ Repair context:
182
+ {}
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_35b8cad3a22642f0/cli/sql_stderr_attempt_2.txt ADDED
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+ {
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+ "engine": "v2-cli:codex",
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+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
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+ "ai_cli_calls": 2,
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+ "usage_summary": {
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+ "dataset_id": "c20",
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+ "model": "v2-cli:codex",
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+ "run_id": "v2q_c20_f7b65c68a1da564a",
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+ "api_calls": 0,
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+ "estimated_output_tokens": 0,
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+ "estimated_total_tokens": 0,
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+ "usage_source": "ai_cli_json_usage",
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+ "cli_elapsed_ms_total": 11949.34,
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+ "sql_execution_elapsed_ms_total": 14.41,
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+ "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/conversation.jsonl",
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+ "note": "Executed through a local AI CLI with structured usage metadata."
24
+ }
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_attempt_1.metadata.json ADDED
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1
+ {
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+ "attempt": 1,
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+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:04:26.867264+00:00",
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+ "stderr_metrics": {
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+ },
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+ "text_metrics": {
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+ "chars": 280,
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+ "bytes_utf8": 280,
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+ "lines": 4,
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+ },
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+ "usage": {}
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+ },
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+ "status": "failed",
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+ "error": "AI CLI command failed with exit code 1: ",
39
+ "prompt_path": "cli/sql_prompt_attempt_1.txt",
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+ "response_path": "cli/sql_response_attempt_1.txt",
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+ "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
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+ "stderr_path": "cli/sql_stderr_attempt_1.txt"
43
+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_attempt_2.metadata.json ADDED
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1
+ {
2
+ "attempt": 2,
3
+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:04:30.806273+00:00",
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+ "elapsed_ms": 9011.74,
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+ "cached_input_tokens": 12032,
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+ }
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+ },
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+ "prompt_path": "cli/sql_prompt_attempt_2.txt",
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+ "response_path": "cli/sql_response_attempt_2.txt",
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+ "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
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+ "stderr_path": "cli/sql_stderr_attempt_2.txt"
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_prompt_attempt_1.txt ADDED
@@ -0,0 +1,180 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_h2o_group_sum",
136
+ "template_name": "Grouped Numeric Sum",
137
+ "primary_family": "subgroup_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=black_piece0_file, measure_col=black_piece0_file.",
151
+ "planned_template_id": "tpl_h2o_group_sum",
152
+ "bindings": {
153
+ "group_col": "black_piece0_file",
154
+ "measure_col": "black_piece0_file",
155
+ "top_k": 14,
156
+ "top_n": 3,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.1,
161
+ "baseline_multiplier": 1.5,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 5,
165
+ "measure_threshold": 5.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,180 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_h2o_group_sum",
136
+ "template_name": "Grouped Numeric Sum",
137
+ "primary_family": "subgroup_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=black_piece0_file, measure_col=black_piece0_file.",
151
+ "planned_template_id": "tpl_h2o_group_sum",
152
+ "bindings": {
153
+ "group_col": "black_piece0_file",
154
+ "measure_col": "black_piece0_file",
155
+ "top_k": 14,
156
+ "top_n": 3,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.1,
161
+ "baseline_multiplier": 1.5,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 5,
165
+ "measure_threshold": 5.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_1.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e40fb-3b75-7fa0-84d1-6bba2becb8fa"}
2
+ {"type":"turn.started"}
3
+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
4
+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_1.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e40fb-3b75-7fa0-84d1-6bba2becb8fa"}
2
+ {"type":"turn.started"}
3
+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
4
+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_2.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e40fb-4af7-7d80-84a6-42542534bab4"}
2
+ {"type":"turn.started"}
3
+ {"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"black_piece0_file\\\", SUM(CAST(\\\"black_piece0_file\\\" AS NUMERIC)) AS total_measure\\nFROM \\\"c20\\\"\\nGROUP BY \\\"black_piece0_file\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned Grouped Numeric Sum template with group_col and measure_col both bound to \\\"black_piece0_file\\\". Applied CAST to NUMERIC because the schema stores this numeric-discrete field as TEXT in SQLite.\"}"}}
4
+ {"type":"turn.completed","usage":{"input_tokens":13807,"cached_input_tokens":12032,"output_tokens":332,"reasoning_output_tokens":220}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_response_attempt_2.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ {"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"black_piece0_file\", SUM(CAST(\"black_piece0_file\" AS NUMERIC)) AS total_measure\nFROM \"c20\"\nGROUP BY \"black_piece0_file\"\nORDER BY total_measure DESC;","notes":"Used the planned Grouped Numeric Sum template with group_col and measure_col both bound to \"black_piece0_file\". Applied CAST to NUMERIC because the schema stores this numeric-discrete field as TEXT in SQLite."}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_stderr_attempt_1.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_f7b65c68a1da564a/cli/sql_stderr_attempt_2.txt ADDED
File without changes