Fix product data eval export format
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@@ -346,6 +346,10 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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'type': 'string',
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'description': 'Target label used for included candidates unless review_decisions provides a target.',
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},
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'default_complex': {
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'type': 'boolean',
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'description': 'Default complex dimension for included candidates unless review_decisions provides complex.',
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},
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'review_decisions': {
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'type': 'array',
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'description': 'Optional include/exclude/uncertain decisions keyed by semantic_session_id or req_id.',
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@@ -357,6 +361,7 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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'matched_turn_index': {'type': 'integer'},
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'decision': {'type': 'string', 'enum': ['include', 'exclude', 'uncertain']},
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'target': {'type': 'string'},
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'complex': {'type': 'boolean'},
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'notes': {'type': 'string'},
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},
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},
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@@ -428,7 +433,8 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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name='data_agent_normalize_dataset_draft',
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description=(
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'Parse dataset draft text written with 用户/小爱/target blocks and build canonical '
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'data-agent records with generated record IDs, timestamps, source metadata, context, and labels. '
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'data-agent records with generated record IDs, timestamps, source metadata, context, labels, '
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'and dimensions.complex. '
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'Generated data requires a confirmed_plan_id from data_agent_confirm_generation_plan. '
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'Use draft_path instead of draft_text when the draft is large or contains many quoted targets.'
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),
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@@ -437,7 +443,7 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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'properties': {
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'draft_text': {
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'type': 'string',
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'description': 'Dataset draft text in dataset draft text v1 format. Provide exactly one of draft_text or draft_path.',
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'description': 'Dataset draft text in dataset draft text v1 format. Each case should include complex: true/false. Provide exactly one of draft_text or draft_path.',
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},
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'draft_path': {
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'type': 'string',
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@@ -476,7 +482,7 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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name='data_agent_validate_dataset_records',
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description=(
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'Validate canonical data-agent records for required fields, labels, source metadata, '
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'prev_session structure, timestamp order, and 5-minute prompt stitching constraints.'
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'prev_session structure, dimensions.complex, timestamp order, and 5-minute prompt stitching constraints.'
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),
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parameters={
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'type': 'object',
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@@ -501,7 +507,8 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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description=(
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'Validate canonical data-agent records and write them to a workspace file. '
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'Defaults to compact JSONL, one canonical record per line, and also writes records.csv '
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'in the same output directory for human sharing.'
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'in the same output directory for human sharing. The table function column combines '
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'complex=true/false and label.target.'
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),
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parameters={
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'type': 'object',
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@@ -551,7 +558,8 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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name='data_agent_export_training_jsonl',
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description=(
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'Convert canonical data-agent records into training JSONL. Each line has system, instruction, '
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'and output. The instruction contains 知识注入, 系统状态, 对话历史, 当前query, and function sections.'
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'and output. Output combines dimensions.complex and label.target as two lines. '
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'The instruction contains 知识注入, 系统状态, 对话历史, 当前query, and function sections.'
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),
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parameters={
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'type': 'object',
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@@ -600,7 +608,8 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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name='data_agent_export_planning_eval_csv',
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description=(
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'Convert canonical data-agent records into evaluation CSV with columns: request_id, newPrompt, '
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'query, 类别真实标签, code标签, complex. newPrompt uses the same prompt body as training instruction.'
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'query, 类别真实标签, code标签, complex. The complex column is read from dimensions.complex. '
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'newPrompt wraps the prompt body with <|im_start|>system/user/assistant chat-template tags.'
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),
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parameters={
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'type': 'object',
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@@ -635,9 +644,13 @@ def build_data_agent_tools(handlers: Mapping[str, ToolHandler]) -> list[AgentToo
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'items': {'type': 'string'},
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'description': 'Context fields to inject. Defaults to ["location", "rag"].',
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},
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'system_prompt': {
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'type': 'string',
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'description': 'System prompt wrapped into newPrompt chat template. Defaults to 你是小爱同学,中文智能语音助手。',
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},
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'complex_default': {
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'type': 'boolean',
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'description': 'Default complex column value. Defaults to false.',
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'description': 'Fallback complex value only for legacy records missing dimensions.complex. Defaults to false.',
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},
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'require_validation_ok': {'type': 'boolean'},
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'overwrite': {'type': 'boolean'},
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