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superset2/superset/mcp_service/common/error_schemas.py

111 lines
4.1 KiB
Python

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Enhanced error schemas for MCP chart generation with contextual information
"""
from typing import Any, Dict, List
from pydantic import BaseModel, Field
class ColumnSuggestion(BaseModel):
"""Suggested column with context"""
name: str = Field(..., description="Column name")
type: str = Field(..., description="Column data type")
similarity_score: float = Field(..., description="Similarity score (0-1)")
description: str | None = Field(None, description="Column description")
class ValidationError(BaseModel):
"""Individual validation error with context"""
field: str = Field(..., description="Field that failed validation")
provided_value: Any = Field(..., description="Value that was provided")
error_type: str = Field(..., description="Type of validation error")
message: str = Field(..., description="Human-readable error message")
suggestions: List[ColumnSuggestion] = Field(
default_factory=list, description="Suggested alternatives"
)
class DatasetContext(BaseModel):
"""Dataset information for error context"""
model_config = {"populate_by_name": True}
id: int = Field(..., description="Dataset ID")
table_name: str = Field(..., description="Table name")
schema_name: str | None = Field(
None,
alias="schema",
serialization_alias="schema",
description="Schema name",
)
database_name: str = Field(..., description="Database name")
available_columns: List[Dict[str, Any]] = Field(
default_factory=list, description="Available columns with metadata"
)
available_metrics: List[Dict[str, Any]] = Field(
default_factory=list, description="Available metrics with metadata"
)
class ChartGenerationError(BaseModel):
"""Enhanced error response for chart generation failures"""
error_type: str = Field(
..., description="Type of error (validation, execution, etc.)"
)
message: str = Field(..., description="High-level error message")
details: str = Field(..., description="Detailed error explanation")
validation_errors: List[ValidationError] = Field(
default_factory=list, description="Specific field validation errors"
)
dataset_context: DatasetContext | None = Field(
None, description="Dataset information for context"
)
query_info: Dict[str, Any] | None = Field(
None, description="Query execution details"
)
suggestions: List[str] = Field(
default_factory=list, description="Actionable suggestions to fix the error"
)
help_url: str | None = Field(
None, description="URL to documentation for this error type"
)
error_code: str | None = Field(
None, description="Unique error code for support reference"
)
class ChartGenerationResponse(BaseModel):
"""Enhanced chart generation response with detailed error handling"""
success: bool = Field(..., description="Whether chart generation succeeded")
chart: Dict[str, Any] | None = Field(
None, description="Chart information if successful"
)
error: ChartGenerationError | None = Field(
None, description="Error details if failed"
)
performance: Dict[str, Any] | None = Field(None, description="Performance metadata")
schema_version: str = Field(default="2.0", description="Response schema version")
api_version: str = Field(default="v1", description="API version")