refactor: Refactor experimental Pipeline to use inheritancee (#323)

* Remove PipelineBase since it's not modified

* Use inheritance

* Remove unused import

* Don't make resume_state and debug_path attributes

* Add back minimal pipelinebase

* Formatting

Author: sjrl

haystack_experimental/core/__init__.py

@@ -1,7 +1,3 @@
 # SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
 #
 # SPDX-License-Identifier: Apache-2.0
-
-from .pipeline.base import ComponentPriority, PipelineBase
-
-__all__ = ["PipelineBase"]

haystack_experimental/core/errors.py

@@ -2,93 +2,7 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-from typing import Any, Dict, Optional, Type
-
-
-class PipelineError(Exception):
-    pass
-
-
-class PipelineRuntimeError(Exception):
-    def __init__(self, component_name: Optional[str], component_type: Optional[Type], message: str) -> None:
-        self.component_name = component_name
-        self.component_type = component_type
-        super().__init__(message)
-
-    @classmethod
-    def from_exception(cls, component_name: str, component_type: Type, error: Exception) -> "PipelineRuntimeError":
-        """
-        Create a PipelineRuntimeError from an exception.
-        """
-        message = (
-            f"The following component failed to run:\n"
-            f"Component name: '{component_name}'\n"
-            f"Component type: '{component_type.__name__}'\n"
-            f"Error: {str(error)}"
-        )
-        return cls(component_name, component_type, message)
-
-    @classmethod
-    def from_invalid_output(cls, component_name: str, component_type: Type, output: Any) -> "PipelineRuntimeError":
-        """
-        Create a PipelineRuntimeError from an invalid output.
-        """
-        message = (
-            f"The following component returned an invalid output:\n"
-            f"Component name: '{component_name}'\n"
-            f"Component type: '{component_type.__name__}'\n"
-            f"Expected a dictionary, but got {type(output).__name__} instead.\n"
-            f"Check the component's output and ensure it is a valid dictionary."
-        )
-        return cls(component_name, component_type, message)
-
-
-class PipelineComponentsBlockedError(PipelineRuntimeError):
-    def __init__(self) -> None:
-        message = (
-            "Cannot run pipeline - all components are blocked. "
-            "This typically happens when:\n"
-            "1. There is no valid entry point for the pipeline\n"
-            "2. There is a circular dependency preventing the pipeline from running\n"
-            "Check the connections between these components and ensure all required inputs are provided."
-        )
-        super().__init__(None, None, message)
-
-
-class PipelineConnectError(PipelineError):
-    pass
-
-
-class PipelineValidationError(PipelineError):
-    pass
-
-
-class PipelineDrawingError(PipelineError):
-    pass
-
-
-class PipelineMaxComponentRuns(PipelineError):
-    pass
-
-
-class PipelineUnmarshalError(PipelineError):
-    pass
-
-
-class ComponentError(Exception):
-    pass
-
-
-class ComponentDeserializationError(Exception):
-    pass
-
-
-class DeserializationError(Exception):
-    pass
-
-
-class SerializationError(Exception):
-    pass
+from typing import Any, Dict, Optional
 
 
 class PipelineBreakpointException(Exception):

haystack_experimental/core/pipeline/__init__.py

@@ -0,0 +1,7 @@
+# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from .pipeline import Pipeline
+
+__all__ = ["Pipeline"]