chore: tool models should reside in tool module (#187)

Author: mathislucka

src/deepset_mcp/api/pipeline/models.py

@@ -269,26 +269,6 @@ class DeepsetStreamEvent(BaseModel):
     "Error message if type is 'error'"
 
 
-class PipelineValidationResultWithYaml(BaseModel):
-    """Model for pipeline validation result that includes the original YAML."""
-
-    validation_result: PipelineValidationResult
-    "Result of validating the pipeline configuration"
-    yaml_config: str
-    "Original YAML configuration that was validated"
-
-
-class PipelineOperationWithErrors(BaseModel):
-    """Model for pipeline operations that complete with validation errors."""
-
-    message: str
-    "Descriptive message about the pipeline operation"
-    validation_result: PipelineValidationResult
-    "Validation errors encountered during the operation"
-    pipeline: DeepsetPipeline
-    "Pipeline object after the operation completed"
-
-
 class LogLevel(StrEnum):
     """Log level filter options for pipeline logs."""
 

src/deepset_mcp/tools/pipeline.py

@@ -5,16 +5,15 @@
 import asyncio
 
 import yaml
+from pydantic import BaseModel
 
 from deepset_mcp.api.exceptions import BadRequestError, ResourceNotFoundError, UnexpectedAPIError
 from deepset_mcp.api.pipeline.models import (
     DeepsetPipeline,
     DeepsetSearchResponse,
     LogLevel,
     PipelineLog,
-    PipelineOperationWithErrors,
     PipelineValidationResult,
-    PipelineValidationResultWithYaml,
 )
 from deepset_mcp.api.protocols import AsyncClientProtocol
 from deepset_mcp.api.shared_models import PaginatedResponse
@@ -55,6 +54,15 @@ async def get_pipeline(*, client: AsyncClientProtocol, workspace: str, pipeline_
         return f"Failed to fetch pipeline '{pipeline_name}': {e}"
 
 
+class PipelineValidationResultWithYaml(BaseModel):
+    """Model for pipeline validation result that includes the original YAML."""
+
+    validation_result: PipelineValidationResult
+    "Result of validating the pipeline configuration"
+    yaml_config: str
+    "Original YAML configuration that was validated"
+
+
 async def validate_pipeline(
     *, client: AsyncClientProtocol, workspace: str, yaml_configuration: str
 ) -> PipelineValidationResultWithYaml | str:
@@ -82,6 +90,17 @@ async def validate_pipeline(
         return f"Failed to validate pipeline: {e}"
 
 
+class PipelineOperationWithErrors(BaseModel):
+    """Model for pipeline operations that complete with validation errors."""
+
+    message: str
+    "Descriptive message about the pipeline operation"
+    validation_result: PipelineValidationResult
+    "Validation errors encountered during the operation"
+    pipeline: DeepsetPipeline
+    "Pipeline object after the operation completed"
+
+
 async def create_pipeline(
     *,
     client: AsyncClientProtocol,

test/unit/tools/test_pipeline.py

@@ -22,17 +22,17 @@
     ExceptionInfo,
     LogLevel,
     PipelineLog,
-    PipelineOperationWithErrors,
     PipelineServiceLevel,
     PipelineValidationResult,
-    PipelineValidationResultWithYaml,
     ValidationError,
 )
 from deepset_mcp.api.pipeline.protocols import PipelineResourceProtocol
 from deepset_mcp.api.shared_models import DeepsetUser, NoContentResponse, PaginatedResponse
 
 # Adjust the import path below to match your project structure
 from deepset_mcp.tools.pipeline import (
+    PipelineOperationWithErrors,
+    PipelineValidationResultWithYaml,
     create_pipeline,
     deploy_pipeline,
     get_pipeline,