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Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "m6",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m6_428eecb4b7dfac52",
+    "api_calls": 0,
+    "input_tokens": 14998,
+    "cached_input_tokens": 12032,
+    "output_tokens": 317,
+    "total_tokens": 15315,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11285.45,
+    "sql_execution_elapsed_ms_total": 7.44,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:01:03.332814+00:00",
+  "ended_at": "2026-05-19T16:01:06.266232+00:00",
+  "elapsed_ms": 2933.39,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 10653,
+    "bytes_utf8": 10653,
+    "lines": 315,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:01:07.268512+00:00",
+  "ended_at": "2026-05-19T16:01:15.620615+00:00",
+  "elapsed_ms": 8352.06,
+  "prompt_metrics": {
+    "chars": 10653,
+    "bytes_utf8": 10653,
+    "lines": 315,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 783,
+    "bytes_utf8": 783,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 428,
+      "bytes_utf8": 428,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14998,
+      "cached_input_tokens": 12032,
+      "output_tokens": 317,
+      "reasoning_output_tokens": 206
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,315 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m6
+- dataset_name: Online Shoppers Purchasing Intention Dataset
+- table_name: m6
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 17 feature columns and target `VisitorType`.
+- task_type: classification
+- target_column: VisitorType
+- main_row_count: 12330
+- important_fields:
+- Administrative: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Administrative.
+- Administrative_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Administrative Duration.
+- Informational: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Informational.
+- Informational_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Informational Duration.
+- ProductRelated: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated.
+- ProductRelated_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated Duration.
+- BounceRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for BounceRates.
+- ExitRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ExitRates.
+- PageValues: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for PageValues.
+- SpecialDay: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for SpecialDay.
+- Month: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Month.
+- OperatingSystems: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for OperatingSystems.
+- Browser: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Browser.
+- Region: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Region.
+- TrafficType: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for TrafficType.
+- VisitorType: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for VisitorType.
+- Weekend: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Weekend.
+- Revenue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Revenue.
+- useful_field_combinations: [['Administrative', 'Informational', 'VisitorType'], ['Administrative', 'Administrative', 'VisitorType'], ['Administrative', 'Administrative_Duration', 'VisitorType']]
+- fields_requiring_caution: ['VisitorType', 'Administrative_Duration', 'Informational_Duration', 'ProductRelated']
+- source_url: https://archive.ics.uci.edu/dataset/468/online+shoppers+purchasing+intention+dataset
+
+SQLite schema snapshot:
+{
+  "table_name": "m6",
+  "quoted_table_name": "\"m6\"",
+  "row_count": 12330,
+  "columns": [
+    {
+      "name": "Administrative",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Administrative_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "BounceRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ExitRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PageValues",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "SpecialDay",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "OperatingSystems",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Browser",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Region",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "TrafficType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "VisitorType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Weekend",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Revenue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "1",
+      "Browser": "1",
+      "Region": "1",
+      "TrafficType": "1",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "64",
+      "BounceRates": "0",
+      "ExitRates": "0.1",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "2",
+      "Browser": "2",
+      "Region": "1",
+      "TrafficType": "2",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "4",
+      "Browser": "1",
+      "Region": "9",
+      "TrafficType": "3",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "2.666666667",
+      "BounceRates": "0.05",
+      "ExitRates": "0.14",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "2",
+      "Region": "2",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "10",
+      "ProductRelated_Duration": "627.5",
+      "BounceRates": "0.02",
+      "ExitRates": "0.05",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "3",
+      "Region": "1",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "TRUE",
+      "Revenue": "FALSE"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m6",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=SpecialDay, condition_col=OperatingSystems.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "SpecialDay",
+    "condition_col": "OperatingSystems",
+    "condition_value": "2",
+    "positive_value": "2",
+    "negative_value": "1",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,315 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m6
+- dataset_name: Online Shoppers Purchasing Intention Dataset
+- table_name: m6
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 17 feature columns and target `VisitorType`.
+- task_type: classification
+- target_column: VisitorType
+- main_row_count: 12330
+- important_fields:
+- Administrative: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Administrative.
+- Administrative_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Administrative Duration.
+- Informational: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Informational.
+- Informational_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Informational Duration.
+- ProductRelated: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated.
+- ProductRelated_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated Duration.
+- BounceRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for BounceRates.
+- ExitRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ExitRates.
+- PageValues: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for PageValues.
+- SpecialDay: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for SpecialDay.
+- Month: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Month.
+- OperatingSystems: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for OperatingSystems.
+- Browser: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Browser.
+- Region: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Region.
+- TrafficType: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for TrafficType.
+- VisitorType: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for VisitorType.
+- Weekend: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Weekend.
+- Revenue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Revenue.
+- useful_field_combinations: [['Administrative', 'Informational', 'VisitorType'], ['Administrative', 'Administrative', 'VisitorType'], ['Administrative', 'Administrative_Duration', 'VisitorType']]
+- fields_requiring_caution: ['VisitorType', 'Administrative_Duration', 'Informational_Duration', 'ProductRelated']
+- source_url: https://archive.ics.uci.edu/dataset/468/online+shoppers+purchasing+intention+dataset
+
+SQLite schema snapshot:
+{
+  "table_name": "m6",
+  "quoted_table_name": "\"m6\"",
+  "row_count": 12330,
+  "columns": [
+    {
+      "name": "Administrative",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Administrative_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "BounceRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ExitRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PageValues",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "SpecialDay",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "OperatingSystems",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Browser",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Region",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "TrafficType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "VisitorType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Weekend",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Revenue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "1",
+      "Browser": "1",
+      "Region": "1",
+      "TrafficType": "1",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "64",
+      "BounceRates": "0",
+      "ExitRates": "0.1",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "2",
+      "Browser": "2",
+      "Region": "1",
+      "TrafficType": "2",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "4",
+      "Browser": "1",
+      "Region": "9",
+      "TrafficType": "3",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "2.666666667",
+      "BounceRates": "0.05",
+      "ExitRates": "0.14",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "2",
+      "Region": "2",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "10",
+      "ProductRelated_Duration": "627.5",
+      "BounceRates": "0.02",
+      "ExitRates": "0.05",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "3",
+      "Region": "1",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "TRUE",
+      "Revenue": "FALSE"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m6",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=SpecialDay, condition_col=OperatingSystems.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "SpecialDay",
+    "condition_col": "OperatingSystems",
+    "condition_value": "2",
+    "positive_value": "2",
+    "negative_value": "1",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-207b-7553-a6b5-ab866391bd50"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-207b-7553-a6b5-ab866391bd50"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-2fc8-7bb2-a0bb-e48b0dd859c9"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"SpecialDay\\\",\\n       AVG(CASE WHEN \\\"OperatingSystems\\\" = '2' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m6\\\"\\nGROUP BY \\\"SpecialDay\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with group_col=\\\"SpecialDay\\\" and condition_col=\\\"OperatingSystems\\\", using condition_value '2' as a text literal to match the SQLite schema.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14998,"cached_input_tokens":12032,"output_tokens":317,"reasoning_output_tokens":206}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_428eecb4b7dfac52/cli/sql_response_attempt_2.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"SpecialDay\",\n       AVG(CASE WHEN \"OperatingSystems\" = '2' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m6\"\nGROUP BY \"SpecialDay\"\nORDER BY condition_rate DESC;","notes":"Applied the Grouped Condition Rate template with group_col=\"SpecialDay\" and condition_col=\"OperatingSystems\", using condition_value '2' as a text literal to match the SQLite schema."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10601, "bytes_utf8": 10601, "lines": 312, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 2034, "bytes_utf8": 2034, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14973, "cached_input_tokens": 13696, "output_tokens": 2725, "reasoning_output_tokens": 2070}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m6",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m6_5720fd15188f337f",
+    "api_calls": 0,
+    "input_tokens": 14973,
+    "cached_input_tokens": 13696,
+    "output_tokens": 2725,
+    "total_tokens": 17698,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 47305.14,
+    "sql_execution_elapsed_ms_total": 56.77,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:53:36.094953+00:00",
+  "ended_at": "2026-05-19T15:54:23.400126+00:00",
+  "elapsed_ms": 47305.14,
+  "prompt_metrics": {
+    "chars": 10601,
+    "bytes_utf8": 10601,
+    "lines": 312,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2658,
+    "bytes_utf8": 2658,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 2034,
+      "bytes_utf8": 2034,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14973,
+      "cached_input_tokens": 13696,
+      "output_tokens": 2725,
+      "reasoning_output_tokens": 2070
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,312 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m6
+- dataset_name: Online Shoppers Purchasing Intention Dataset
+- table_name: m6
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 17 feature columns and target `VisitorType`.
+- task_type: classification
+- target_column: VisitorType
+- main_row_count: 12330
+- important_fields:
+- Administrative: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Administrative.
+- Administrative_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Administrative Duration.
+- Informational: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Informational.
+- Informational_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Informational Duration.
+- ProductRelated: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated.
+- ProductRelated_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated Duration.
+- BounceRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for BounceRates.
+- ExitRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ExitRates.
+- PageValues: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for PageValues.
+- SpecialDay: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for SpecialDay.
+- Month: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Month.
+- OperatingSystems: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for OperatingSystems.
+- Browser: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Browser.
+- Region: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Region.
+- TrafficType: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for TrafficType.
+- VisitorType: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for VisitorType.
+- Weekend: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Weekend.
+- Revenue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Revenue.
+- useful_field_combinations: [['Administrative', 'Informational', 'VisitorType'], ['Administrative', 'Administrative', 'VisitorType'], ['Administrative', 'Administrative_Duration', 'VisitorType']]
+- fields_requiring_caution: ['VisitorType', 'Administrative_Duration', 'Informational_Duration', 'ProductRelated']
+- source_url: https://archive.ics.uci.edu/dataset/468/online+shoppers+purchasing+intention+dataset
+
+SQLite schema snapshot:
+{
+  "table_name": "m6",
+  "quoted_table_name": "\"m6\"",
+  "row_count": 12330,
+  "columns": [
+    {
+      "name": "Administrative",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Administrative_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "BounceRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ExitRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PageValues",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "SpecialDay",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "OperatingSystems",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Browser",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Region",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "TrafficType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "VisitorType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Weekend",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Revenue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "1",
+      "Browser": "1",
+      "Region": "1",
+      "TrafficType": "1",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "64",
+      "BounceRates": "0",
+      "ExitRates": "0.1",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "2",
+      "Browser": "2",
+      "Region": "1",
+      "TrafficType": "2",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "4",
+      "Browser": "1",
+      "Region": "9",
+      "TrafficType": "3",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "2.666666667",
+      "BounceRates": "0.05",
+      "ExitRates": "0.14",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "2",
+      "Region": "2",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "10",
+      "ProductRelated_Duration": "627.5",
+      "BounceRates": "0.02",
+      "ExitRates": "0.05",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "3",
+      "Region": "1",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "TRUE",
+      "Revenue": "FALSE"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m6",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Administrative, measure_col=ProductRelated.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Administrative",
+    "measure_col": "ProductRelated",
+    "top_k": 13,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 38.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f1-4d83-79e1-91f0-fcd7b97cbe0a"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n  SELECT\\n    \\\"Administrative\\\",\\n    CAST(\\\"ProductRelated\\\" AS REAL) AS \\\"ProductRelated\\\"\\n  FROM \\\"m6\\\"\\n  WHERE \\\"Administrative\\\" IS NOT NULL\\n    AND TRIM(\\\"Administrative\\\") <> ''\\n    AND \\\"ProductRelated\\\" IS NOT NULL\\n    AND TRIM(\\\"ProductRelated\\\") <> ''\\n),\\n\\\"ordered\\\" AS (\\n  SELECT\\n    \\\"Administrative\\\",\\n    \\\"ProductRelated\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Administrative\\\"\\n      ORDER BY \\\"ProductRelated\\\"\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Administrative\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"base\\\"\\n),\\n\\\"params\\\" AS (\\n  SELECT DISTINCT\\n    \\\"Administrative\\\",\\n    \\\"cnt\\\",\\n    1.0 + 0.95 * (\\\"cnt\\\" - 1) AS \\\"pos\\\",\\n    CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER) AS \\\"lo_rn\\\",\\n    CASE\\n      WHEN (1.0 + 0.95 * (\\\"cnt\\\" - 1)) = CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER) THEN CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER)\\n      ELSE CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER) + 1\\n    END AS \\\"hi_rn\\\"\\n  FROM \\\"ordered\\\"\\n)\\nSELECT\\n  p.\\\"Administrative\\\",\\n  CASE\\n    WHEN p.\\\"lo_rn\\\" = p.\\\"hi_rn\\\" THEN MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lo_rn\\\" THEN o.\\\"ProductRelated\\\" END)\\n    ELSE MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lo_rn\\\" THEN o.\\\"ProductRelated\\\" END) * (p.\\\"hi_rn\\\" - p.\\\"pos\\\")\\n       + MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"hi_rn\\\" THEN o.\\\"ProductRelated\\\" END) * (p.\\\"pos\\\" - p.\\\"lo_rn\\\")\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"params\\\" AS p\\nJOIN \\\"ordered\\\" AS o\\n  ON o.\\\"Administrative\\\" = p.\\\"Administrative\\\"\\nWHERE p.\\\"cnt\\\" >= 5\\nGROUP BY\\n  p.\\\"Administrative\\\",\\n  p.\\\"pos\\\",\\n  p.\\\"lo_rn\\\",\\n  p.\\\"hi_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this emulates the 95th percentile per \\\"Administrative\\\" group with window functions and linear interpolation over CAST(\\\"ProductRelated\\\" AS REAL). It also applies the provided minimum group size of 5; no \\\"VisitorType\\\" filter was added because no target value was bound.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14973,"cached_input_tokens":13696,"output_tokens":2725,"reasoning_output_tokens":2070}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_5720fd15188f337f/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n  SELECT\n    \"Administrative\",\n    CAST(\"ProductRelated\" AS REAL) AS \"ProductRelated\"\n  FROM \"m6\"\n  WHERE \"Administrative\" IS NOT NULL\n    AND TRIM(\"Administrative\") <> ''\n    AND \"ProductRelated\" IS NOT NULL\n    AND TRIM(\"ProductRelated\") <> ''\n),\n\"ordered\" AS (\n  SELECT\n    \"Administrative\",\n    \"ProductRelated\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Administrative\"\n      ORDER BY \"ProductRelated\"\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Administrative\"\n    ) AS \"cnt\"\n  FROM \"base\"\n),\n\"params\" AS (\n  SELECT DISTINCT\n    \"Administrative\",\n    \"cnt\",\n    1.0 + 0.95 * (\"cnt\" - 1) AS \"pos\",\n    CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER) AS \"lo_rn\",\n    CASE\n      WHEN (1.0 + 0.95 * (\"cnt\" - 1)) = CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER) THEN CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER)\n      ELSE CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER) + 1\n    END AS \"hi_rn\"\n  FROM \"ordered\"\n)\nSELECT\n  p.\"Administrative\",\n  CASE\n    WHEN p.\"lo_rn\" = p.\"hi_rn\" THEN MAX(CASE WHEN o.\"rn\" = p.\"lo_rn\" THEN o.\"ProductRelated\" END)\n    ELSE MAX(CASE WHEN o.\"rn\" = p.\"lo_rn\" THEN o.\"ProductRelated\" END) * (p.\"hi_rn\" - p.\"pos\")\n       + MAX(CASE WHEN o.\"rn\" = p.\"hi_rn\" THEN o.\"ProductRelated\" END) * (p.\"pos\" - p.\"lo_rn\")\n  END AS \"percentile_measure\"\nFROM \"params\" AS p\nJOIN \"ordered\" AS o\n  ON o.\"Administrative\" = p.\"Administrative\"\nWHERE p.\"cnt\" >= 5\nGROUP BY\n  p.\"Administrative\",\n  p.\"pos\",\n  p.\"lo_rn\",\n  p.\"hi_rn\"\nORDER BY \"percentile_measure\" DESC;","notes":"SQLite does not support PERCENTILE_CONT, so this emulates the 95th percentile per \"Administrative\" group with window functions and linear interpolation over CAST(\"ProductRelated\" AS REAL). It also applies the provided minimum group size of 5; no \"VisitorType\" filter was added because no target value was bound."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_69c46a3db8a520c7/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:04:41.908125+00:00",
+  "ended_at": "2026-05-19T16:04:45.005265+00:00",
+  "elapsed_ms": 3097.1,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 10398,
+    "bytes_utf8": 10398,
+    "lines": 310,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}