aminghadersohi commented on code in PR #38402:
URL: https://github.com/apache/superset/pull/38402#discussion_r2932090523
##########
superset/mcp_service/chart/validation/schema_validator.py:
##########
@@ -282,6 +286,82 @@ def _pre_validate_pie_config(
return True, None
+ @staticmethod
+ def _pre_validate_handlebars_config(
+ config: Dict[str, Any],
+ ) -> Tuple[bool, ChartGenerationError | None]:
+ """Pre-validate handlebars chart configuration."""
+ if "handlebars_template" not in config:
+ return False, ChartGenerationError(
+ error_type="missing_handlebars_template",
+ message="Handlebars chart missing required field:
handlebars_template",
+ details="Handlebars charts require a 'handlebars_template'
string "
+ "containing Handlebars HTML template markup",
+ suggestions=[
+ "Add 'handlebars_template' with a Handlebars HTML
template",
+ "Data is available as {{data}} array in the template",
+ "Example: '<ul>{{#each data}}<li>{{this.name}}: "
+ "{{this.value}}</li>{{/each}}</ul>'",
+ ],
+ error_code="MISSING_HANDLEBARS_TEMPLATE",
+ )
+
+ template = config.get("handlebars_template")
+ if not isinstance(template, str) or not template.strip():
+ return False, ChartGenerationError(
+ error_type="invalid_handlebars_template",
+ message="Handlebars template must be a non-empty string",
+ details="The 'handlebars_template' field must be a non-empty
string "
+ "containing valid Handlebars HTML template markup",
+ suggestions=[
+ "Ensure handlebars_template is a non-empty string",
+ "Example: '<ul>{{#each
data}}<li>{{this.name}}</li>{{/each}}</ul>'",
+ ],
+ error_code="INVALID_HANDLEBARS_TEMPLATE",
+ )
+
+ query_mode = config.get("query_mode", "aggregate")
+ if query_mode not in ("aggregate", "raw"):
+ return False, ChartGenerationError(
+ error_type="invalid_query_mode",
+ message="Invalid query_mode for handlebars chart",
+ details="query_mode must be either 'aggregate' or 'raw'",
+ suggestions=[
+ "Use 'aggregate' for aggregated data (default)",
+ "Use 'raw' for individual rows",
+ ],
+ error_code="INVALID_QUERY_MODE",
+ )
+
+ if query_mode == "raw" and "columns" not in config:
Review Comment:
The pre-validation intentionally checks for the key's presence as a quick
reject. Pydantic's schema validation (with minItems=1) catches empty lists in
the next validation layer. This two-layer approach is by design.
##########
superset/mcp_service/chart/schemas.py:
##########
@@ -690,6 +690,108 @@ class MixedTimeseriesChartConfig(BaseModel):
filters: List[FilterConfig] | None = Field(None, description="Filters to
apply")
+class HandlebarsChartConfig(BaseModel):
+ model_config = ConfigDict(extra="forbid")
+
+ chart_type: Literal["handlebars"] = Field(
+ ...,
+ description=(
+ "Chart type discriminator - MUST be 'handlebars' for custom HTML "
+ "template charts. Handlebars charts render query results using "
+ "Handlebars templates, enabling fully custom layouts like KPI
cards, "
+ "leaderboards, and formatted reports."
+ ),
+ )
+ handlebars_template: str = Field(
+ ...,
+ description=(
+ "Handlebars HTML template string. Data is available as {{data}}
array. "
+ "Built-in helpers: {{dateFormat val format='YYYY-MM-DD'}}, "
+ "{{formatNumber val}}, {{stringify obj}}. "
+ "Example: '<ul>{{#each data}}<li>{{this.name}}:
{{this.value}}</li>"
Review Comment:
The template example in the description renders correctly in the Pydantic
JSON Schema output — it uses Handlebars syntax with double braces. The
formatting is intentional for the JSON schema context.
##########
superset/mcp_service/chart/validation/schema_validator.py:
##########
@@ -282,6 +286,82 @@ def _pre_validate_pie_config(
return True, None
+ @staticmethod
+ def _pre_validate_handlebars_config(
+ config: Dict[str, Any],
+ ) -> Tuple[bool, ChartGenerationError | None]:
+ """Pre-validate handlebars chart configuration."""
+ if "handlebars_template" not in config:
+ return False, ChartGenerationError(
+ error_type="missing_handlebars_template",
+ message="Handlebars chart missing required field:
handlebars_template",
+ details="Handlebars charts require a 'handlebars_template'
string "
+ "containing Handlebars HTML template markup",
+ suggestions=[
+ "Add 'handlebars_template' with a Handlebars HTML
template",
+ "Data is available as {{data}} array in the template",
+ "Example: '<ul>{{#each data}}<li>{{this.name}}: "
+ "{{this.value}}</li>{{/each}}</ul>'",
+ ],
+ error_code="MISSING_HANDLEBARS_TEMPLATE",
+ )
+
+ template = config.get("handlebars_template")
+ if not isinstance(template, str) or not template.strip():
+ return False, ChartGenerationError(
+ error_type="invalid_handlebars_template",
+ message="Handlebars template must be a non-empty string",
+ details="The 'handlebars_template' field must be a non-empty
string "
+ "containing valid Handlebars HTML template markup",
+ suggestions=[
+ "Ensure handlebars_template is a non-empty string",
+ "Example: '<ul>{{#each
data}}<li>{{this.name}}</li>{{/each}}</ul>'",
+ ],
+ error_code="INVALID_HANDLEBARS_TEMPLATE",
+ )
+
+ query_mode = config.get("query_mode", "aggregate")
+ if query_mode not in ("aggregate", "raw"):
+ return False, ChartGenerationError(
+ error_type="invalid_query_mode",
+ message="Invalid query_mode for handlebars chart",
+ details="query_mode must be either 'aggregate' or 'raw'",
+ suggestions=[
+ "Use 'aggregate' for aggregated data (default)",
+ "Use 'raw' for individual rows",
+ ],
+ error_code="INVALID_QUERY_MODE",
+ )
+
+ if query_mode == "raw" and "columns" not in config:
+ return False, ChartGenerationError(
+ error_type="missing_raw_columns",
+ message="Handlebars chart in 'raw' mode requires 'columns'",
+ details="When query_mode is 'raw', you must specify which
columns "
+ "to include in the query results",
+ suggestions=[
+ "Add 'columns': [{'name': 'column_name'}] for raw mode",
+ "Or use query_mode='aggregate' with 'metrics' "
+ "and optional 'groupby'",
+ ],
+ error_code="MISSING_RAW_COLUMNS",
+ )
+
+ if query_mode == "aggregate" and "metrics" not in config:
+ return False, ChartGenerationError(
Review Comment:
Same as above — the pre-validation checks for key presence as a fast-path
rejection. Empty lists are caught by Pydantic's minItems=1 constraint in the
schema layer. The two-layer validation is intentional.
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