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[Test Case Failure]: tests/unit/pipelines/Pipeline_unit_test.py::test_serialization #956

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github-actions bot opened this issue Dec 18, 2024 · 21 comments
Open

[Test Case Failure]: tests/unit/pipelines/Pipeline_unit_test.py::test_serialization #956

github-actions bot opened this issue Dec 18, 2024 · 21 comments
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pytest-failure swarmauri

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Test Case:

tests/unit/pipelines/Pipeline_unit_test.py::test_serialization

Failure Details:

tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>

Suggested Fix (via Agent):

Unable to retrieve suggestions from LLM at this time.

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This issue is auto-labeled for the swarmauri package.
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New failure detected:

Test Case:

tests/unit/pipelines/Pipeline_unit_test.py::test_serialization

Failure Details:

tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>

Suggested Fix (via Agent):

The error message indicates that Pydantic is unable to serialize an unknown type, specifically a function. This suggests that one of the attributes of the Pipeline object is a function, which cannot be serialized to JSON.

Looking at the code, the issue is likely due to the parameters attribute of the Pipeline object, which is a list of Parameter objects. One of the Parameter objects might have a function as its value, which is causing the serialization error.

To fix this issue, you need to ensure that all attributes of the Pipeline object can be serialized to JSON. You can do this by checking the parameters attribute and making sure that all values are serializable.

Here's an example of how you can modify the test_serialization test case to check for non-serializable values:

def test_serialization(self):
    pipeline = Pipeline()
    for param in pipeline.parameters:
        if callable(param.value):
            raise ValueError(f"Parameter {param.name} has a non-serializable value: {param.value}")
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id

This code checks if any of the Parameter objects in the parameters list have a value that is a function (i.e., callable). If it finds one, it raises a ValueError with a message indicating which parameter has a non-serializable value.

Alternatively, you can modify the Parameter class to ensure that its values are always serializable. For example, you can add a validate method to the Parameter class that checks if the value is serializable:

class Parameter:
    def __init__(self, name, value):
        self.name = name
        self.value = value
        self.validate()

    def validate(self):
        if callable(self.value):
            raise ValueError(f"Value {self.value} is not serializable")

This way, when you create a Parameter object, it will automatically check if its value is serializable and raise an error if it's not.

By making these changes, you should be able to identify and fix the issue causing the PydanticSerializationError.

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New failure detected:

Test Case:

tests/unit/pipelines/Pipeline_unit_test.py::test_serialization

Failure Details:

tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>

Suggested Fix (via Agent):

The error message indicates that there's an issue with serializing an unknown type, specifically a function, when calling model_dump_json() on the pipeline object. This suggests that one of the attributes of the pipeline object is a function, which cannot be serialized to JSON.

Looking at the code, the Pipeline class is not provided, but based on the error message, it's likely that one of the attributes of the Pipeline class is a function.

To fix this issue, you need to identify the attribute that is a function and exclude it from serialization or modify it to be serializable.

Here are a few possible solutions:

  1. Exclude the function attribute from serialization by using the exclude parameter of the model_dump_json method. For example: 
    

    2. 



pipeline.model_dump_json(exclude={'function_attribute'})


   Replace `'function_attribute'` with the actual name of the attribute that is a function.

2. Modify the function attribute to be serializable. If the function attribute is a method of the `Pipeline` class, you could convert it to a property or a static method, which can be serialized.

3. If the function attribute is not necessary for serialization, you could remove it from the `Pipeline` class.

Without the actual code of the `Pipeline` class, it's difficult to provide a more specific solution. However, by identifying and addressing the function attribute that's causing the serialization issue, you should be able to resolve the error. 

Here's a code snippet that demonstrates how to exclude an attribute from serialization:
```python
from pydantic import BaseModel

class Pipeline(BaseModel):
    id: int
    function_attribute: callable  # This is the function attribute that's causing the issue

pipeline = Pipeline(id=1, function_attribute=lambda x: x)

# Exclude the function attribute from serialization
serialized_pipeline = pipeline.model_dump_json(exclude={'function_attribute'})

print(serialized_pipeline)  # This should print the serialized pipeline without the function attribute





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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that the test case 'tests/unit/pipelines/Pipeline_unit_test.py::test_serialization' is failing due to an issue with serializing an unknown type, specifically a function. This suggests that the Pipeline model contains a field that is a function, which cannot be serialized to JSON.


To fix this issue, you need to modify the Pipeline model to exclude the function field from serialization or provide a custom serialization method for that field.


Here's an example of how you can modify the Pipeline model to exclude the function field from serialization:


from pydantic import BaseModel, Field

class Pipeline(BaseModel):
    #... other fields...
    func_field: callable = Field(exclude=True)  # exclude the function field from serialization
    #... other fields...


Alternatively, you can provide a custom serialization method for the function field using the json_encoder parameter of the model_dump_json method:


from pydantic import BaseModel
import json

class Pipeline(BaseModel):
    #... other fields...
    func_field: callable
    #... other fields...

    class Config:
        json_encoders = {
            callable: lambda f: f.__name__  # serialize the function field as its name
        }


By making these changes, you should be able to fix the serialization issue and get the test case to pass.


Here is the debugged code:


from pydantic import BaseModel, Field
import json

class Pipeline(BaseModel):
    #... other fields...
    func_field: callable = Field(exclude=True)  # exclude the function field from serialization
    #... other fields...

    class Config:
        json_encoders = {
            callable: lambda f: f.__name__  # serialize the function field as its name
        }




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize a function type. This suggests that there is a function or method within the Pipeline object that is not being properly handled during serialization.


Looking at the stack trace, the issue arises from the model_dump_json method of the Pipeline object. This method is likely trying to serialize the entire object, including any methods or functions it contains.


To fix this issue, you need to ensure that any functions or methods within the Pipeline object are excluded from serialization. You can do this by using the exclude parameter of the model_dump_json method to specify which attributes should be excluded.


Here's an example of how you might modify the test_serialization test case to exclude functions from serialization:


def test_serialization(self):
    pipeline = Pipeline()
    exclude = {"__call__"}  # Add any other function names that should be excluded
    assert pipeline.id == Pipeline.model_validate_json(
        pipeline.model_dump_json(exclude=exclude)
    ).id


Alternatively, you can modify the Pipeline model to exclude functions from serialization by default. You can do this by adding an exclude parameter to the model's model_dump_json method:


class Pipeline(BaseModel):
    #...

    def model_dump_json(self, **kwargs):
        exclude = kwargs.get("exclude", set())
        exclude.update({"__call__"})  # Add any other function names that should be excluded
        return super().model_dump_json(exclude=exclude, **kwargs)


By excluding functions from serialization, you should be able to resolve the PydanticSerializationError and get your test case passing.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize a function type. This is likely because the Pipeline model has an attribute that is a function, which cannot be serialized to JSON.


To fix this issue, you need to exclude the function attribute from the serialization process. You can do this by adding the exclude parameter to the model_dump_json method and specifying the name of the function attribute.


Here's an example of how you can modify the test_serialization test case to exclude the function attribute:


def test_serialization(self):
    pipeline = Pipeline()
    # Exclude the function attribute from serialization
    exclude_attributes = {"function_attribute_name"}  # Replace with the actual attribute name
    serialized_pipeline = pipeline.model_dump_json(exclude=exclude_attributes)
    deserialized_pipeline = Pipeline.model_validate_json(serialized_pipeline)
    assert pipeline.id == deserialized_pipeline.id



Alternatively, you can also use the exclude parameter on the Pipeline model itself to exclude the function attribute from serialization. This can be done by adding the exclude parameter to the Pipeline model definition:


class Pipeline(BaseModel):
    #... other attributes...
    function_attribute_name: Callable = Field(exclude=True)  # Replace with the actual attribute name



By excluding the function attribute from serialization, you should be able to fix the PydanticSerializationError and make the test_serialization test case pass.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


Unable to retrieve suggestions from LLM at this time.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error is due to an attempt to serialize an unknown type, specifically a function, in the model_dump_json method. This suggests that one of the attributes of the Pipeline object is a function, which cannot be serialized to JSON.


To fix this issue, you need to exclude the function attribute from serialization. You can do this by adding the exclude parameter to the model_dump_json method and specifying the name of the function attribute.


Here is an example of how you can modify the test_serialization test case to exclude the function attribute:


def test_serialization(self):
    pipeline = Pipeline()
    # Exclude the function attribute from serialization
    exclude_attributes = ["function_attribute_name"]
    serialized_pipeline = pipeline.model_dump_json(exclude=exclude_attributes)
    deserialized_pipeline = Pipeline.model_validate_json(serialized_pipeline)
    assert pipeline.id == deserialized_pipeline.id


Replace "function_attribute_name" with the actual name of the function attribute that is causing the serialization error.


Alternatively, you can also use the exclude parameter on the Pipeline model itself to exclude the function attribute from serialization. This can be done by adding the following code to the Pipeline model:


class Pipeline(BaseModel):
    #... other attributes...
    function_attribute_name: Callable = Field(exclude=True)
    #... other attributes...


This will exclude the function_attribute_name attribute from serialization for all instances of the Pipeline model.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that the test case 'tests/unit/pipelines/Pipeline_unit_test.py::test_serialization' is failing due to an issue with serializing an unknown type, specifically a function.


Looking at the stack trace, it seems like the issue is occurring when trying to serialize the pipeline object to JSON using model_dump_json() method. This method is unable to serialize a function, which is likely a part of the pipeline object.


To fix this issue, you need to modify the Pipeline class to properly handle the serialization of functions. One way to do this is to use a custom JSON encoder that can handle functions.


Here's an example of how you can modify the Pipeline class to use a custom JSON encoder:


import json
from pydantic import BaseModel

class Pipeline(BaseModel):
    #... other fields...

    def model_dump_json(self):
        return json.dumps(self, default=self._encode_function)

    @staticmethod
    def _encode_function(obj):
        if callable(obj):
            return obj.__name__
        return obj


In this example, the model_dump_json method uses a custom JSON encoder _encode_function to serialize functions. This encoder checks if an object is callable (i.e., a function) and returns its name as a string. Otherwise, it returns the object as is.


By using this custom encoder, you should be able to serialize the pipeline object without encountering the PydanticSerializationError.


Alternatively, you can also modify the Pipeline class to exclude functions from serialization by using the exclude parameter of the model_dump_json method. For example:


class Pipeline(BaseModel):
    #... other fields...

    def model_dump_json(self):
        return self.dict(exclude={'function_field'})


In this example, the model_dump_json method excludes the function_field from serialization, assuming that this field contains the function that's causing the serialization error.


By excluding the function field from serialization, you should be able to avoid the PydanticSerializationError and successfully serialize the pipeline object.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


Unable to retrieve suggestions from LLM at this time.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw0] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


Unable to retrieve suggestions from LLM at this time.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


Unable to retrieve suggestions from LLM at this time.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw0] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize an unknown type, specifically a function. This error occurs when trying to serialize an object that contains a function as one of its attributes.


To fix this issue, you need to identify the attribute in the Pipeline object that is a function and exclude it from serialization. You can do this by adding the exclude parameter to the model_dump_json method and specifying the attribute name.


Here's an example of how you can modify the test_serialization test case to exclude the function attribute:


def test_serialization(self):
    pipeline = Pipeline()
    # Exclude the function attribute from serialization
    exclude = {"function_attribute_name"}
    serialized_pipeline = pipeline.model_dump_json(exclude=exclude)
    deserialized_pipeline = Pipeline.model_validate_json(serialized_pipeline)
    assert pipeline.id == deserialized_pipeline.id



Replace "function_attribute_name" with the actual name of the attribute that is a function.


Alternatively, you can also use the exclude parameter on the Pipeline model itself to exclude the function attribute from serialization. You can do this by adding the exclude parameter to the Pipeline model definition:


class Pipeline(BaseModel):
    #...
    class Config:
        exclude = {"function_attribute_name"}



This will exclude the function attribute from serialization for all instances of the Pipeline model.


By excluding the function attribute from serialization, you should be able to fix the error and successfully serialize and deserialize the Pipeline object.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw3] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


Unable to retrieve suggestions from LLM at this time.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize a function type, which suggests that there's a function being passed as an argument to the Pipeline model or one of its fields.


Looking at the stacktrace, the error occurs when calling pipeline.model_dump_json(), which implies that the pipeline object contains a field that is a function.


To fix this issue, you need to identify the field in the Pipeline model that is causing the error and modify it to be serializable. Here are a few possible solutions:


    

  1. Exclude the function field from serialization: If the function field is not necessary for serialization, you can exclude it by using the exclude parameter on the model_dump_json method. For example:

    

    2. 



pipeline.model_dump_json(exclude={"function_field"})


    Replace `"function_field"` with the actual name of the field that is causing the error.

2.  **Use a custom JSON encoder**: If you need to serialize the function field, you can create a custom JSON encoder that knows how to handle function types. Here's an example:
    ```python
import json

class FunctionEncoder(json.JSONEncoder):
    def default(self, obj):
        if callable(obj):
            return obj.__name__
        return super().default(obj)

pipeline.model_dump_json(encoder=FunctionEncoder)



This will serialize the function field as a string containing the function's name.



    

  1. Modify the Pipeline model to use a serializable field: If the function field is not necessary, you can modify the Pipeline model to use a serializable field instead. For example, you could replace the function field with a string field that contains the function's name or a dictionary field that contains the function's configuration.
    2. 



By applying one of these solutions, you should be able to fix the error and make your test pass.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize a function object. This is because Pydantic's model_dump_json method does not know how to serialize function objects.


The issue is likely caused by the fact that the Pipeline model has a field that is a function, which is not serializable by Pydantic.


To fix this issue, you need to modify the Pipeline model to exclude the function field or make it serializable.


Here are a few possible solutions:


    

  1. Exclude the function field: If the function field is not essential for the pipeline's functionality, you can exclude it from the Pipeline model by using the exclude parameter in the __init__ method.
    2. 



class Pipeline(BaseModel):
    #...

    def __init__(self, **data):
        super().__init__(**data, exclude={"function_field"})


    

  1. Make the function field serializable: If the function field is essential, you can make it serializable by using a custom serialization method. You can create a custom json_encoder for the Pipeline model that knows how to serialize function objects.
    2. 



class PipelineEncoder(json.JSONEncoder):
    def default(self, obj):
        if callable(obj):
            return str(obj)
        return super().default(obj)

class Pipeline(BaseModel):
    #...

    def __init__(self, **data):
        super().__init__(**data, json_encoder=PipelineEncoder)


    

  1. Use a different serialization method: If you don't need to serialize the pipeline to JSON, you can use a different serialization method, such as model_dump_yaml or model_dump_dict.
    2. 



assert pipeline.id == Pipeline.model_dump_yaml(pipeline).id


Choose the solution that best fits your use case.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw0] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize an unknown type, which is a function. This is likely because the Pipeline model has a field that is a function, but Pydantic does not know how to serialize functions.


To fix this issue, you need to remove the function field from the Pipeline model or modify it to a type that can be serialized by Pydantic.


Here are a few options:


    

  1. 

    Remove the function field: If the function field is not necessary for the model, you can simply remove it. This will allow Pydantic to serialize the model correctly.
    

    2. 

  2. 

    Modify the function field: If the function field is necessary, you can modify it to a type that can be serialized by Pydantic. For example, you can use a string to represent the function, or a dictionary to represent the function's arguments and return type.
    

    3. 

  3. 

    Use a custom serializer: If you need to serialize functions and Pydantic does not support it, you can create a custom serializer for the function field. This will allow you to control how the function is serialized and deserialized.
    

    4. 



Here is an example of how you can modify the Pipeline model to remove the function field:


from pydantic import BaseModel
from swarmauri_core.prompts.IPromptMatrix import IPromptMatrix

class Pipeline(BaseModel, IPromptMatrix):
    id: str
    # Remove the function field
    # def process_tasks(self):
    #     pass


If you need to keep the function field, you can modify it to a type that can be serialized by Pydantic. For example:


from pydantic import BaseModel
from swarmauri_core.prompts.IPromptMatrix import IPromptMatrix

class Pipeline(BaseModel, IPromptMatrix):
    id: str
    process_tasks: str  # Modify the function field to a string


Note that this is just one possible solution, and you may need to modify the model further to meet your specific requirements.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


Based on the stacktrace, the error occurs when trying to serialize a function using the model_dump_json method of the Pipeline model. The pydantic library is unable to serialize the function because it's an unknown type.


The issue is likely due to the Pipeline model having a field that is a function, which is not serializable by pydantic. To fix this, you need to modify the Pipeline model to remove the function field or make it serializable.


Here are a few possible solutions:


    

  1. Remove the function field from the Pipeline model:
    2. 



If the function field is not necessary for the Pipeline model, you can simply remove it. This will prevent pydantic from trying to serialize it.


    

  1. Make the function field serializable:
    2. 



If the function field is necessary, you can make it serializable by using a custom serialization method. For example, you can use a lambda function to serialize the function:


from pydantic import BaseModel, Json

class Pipeline(BaseModel):
    #...

    def model_dump_json(self):
        data = super().model_dump_json()
        data["function"] = lambda: "serialized_function"
        return data


    

  1. Use a different serialization method:
    2. 



If the above solutions do not work, you can try using a different serialization method, such as json.dumps or pickle.dumps. However, be aware that these methods may not be as safe as pydantic's serialization method.


To identify the cause of the failure, you can try the following:


    

  • Check the Pipeline model to see if it has any fields that are functions.
    • 

  • Check the model_dump_json method to see if it's trying to serialize any functions.
    • 

  • Try to reproduce the error by running the test case in a local environment.
    • 



By following these steps, you should be able to identify the cause of the failure and apply a fix to resolve the issue.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw0] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize an unknown type, which is a function in this case. This is because Pydantic's JSON serialization does not support serializing functions.


The issue is likely caused by the fact that the Pipeline model has a field that is a function, which is not serializable by Pydantic. To fix this, you can modify the Pipeline model to remove the field that is a function, or use a different serialization method that supports serializing functions.


Here are a few possible solutions:


    

  1. Remove the field that is a function:
    2. 



If the field that is a function is not necessary for the model, you can simply remove it. This will prevent Pydantic from trying to serialize it.


    

  1. Use a different serialization method:
    2. 



If the field that is a function is necessary for the model, you can use a different serialization method that supports serializing functions. For example, you can use the json module's dumps function with the default parameter set to a function that serializes functions.


    

  1. Modify the Pipeline model to use a different data type:
    2. 



If the field that is a function needs to be serialized, you can modify the Pipeline model to use a different data type that is serializable by Pydantic. For example, you can use a string or an integer instead of a function.


Here is an example of how you can modify the Pipeline model to remove the field that is a function:


from pydantic import BaseModel

class Pipeline(BaseModel):
    # Remove the field that is a function
    #...

    class Config:
        json_encoders = {
            # Add a custom encoder for the function field
            #...
        }


Alternatively, you can use a different serialization method, such as the json module's dumps function:


import json

class Pipeline(BaseModel):
    #...

    def model_dump_json(self):
        return json.dumps(self, default=lambda o: o.__dict__, sort_keys=True, indent=4)


Note that this will serialize the entire object, including the function field, as a dictionary. You may need to modify the Pipeline model to use a different data type or remove the field that is a function.


I hope this helps you identify the cause of the failure and suggest a fix! Let me know if you have any further questions.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize an object of type function. This is because Pydantic does not know how to serialize functions.


In your code, the test_serialization test case is asserting that the id attribute of a pipeline object is equal to the id attribute of the deserialized pipeline object returned by Pipeline.model_validate_json(pipeline.model_dump_json()).id. However, the id attribute of the pipeline object is a function, which cannot be serialized by Pydantic.


To fix this issue, you need to modify the test_serialization test case to exclude the id attribute when serializing and deserializing the pipeline object. You can do this by using the exclude parameter of the model_dump_json method.


Here's an example of how you can modify the test_serialization test case:


def test_serialization():
    pipeline = Pipeline()
    #...
    assert pipeline.id == Pipeline.model_validate_json(
        pipeline.model_dump_json(exclude=["id"])
    ).id


By excluding the id attribute when serializing and deserializing the pipeline object, you should be able to fix the issue.


Alternatively, if you need to serialize the id attribute, you can modify the Pipeline model to exclude the id attribute when serializing. You can do this by adding an exclude parameter to the model_dump_json method:


class Pipeline(BaseModel):
    #...
    class Config:
        exclude = {"id"}


This will exclude the id attribute when serializing the pipeline object.


It's worth noting that this is a common issue when working with Pydantic models that contain functions or other unserializable objects as attributes. In general, it's a good practice to exclude any attributes that cannot be serialized when using Pydantic.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw1] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize an object of type function. This is because Pydantic's to_json method does not know how to serialize functions.


In the stacktrace, the error occurs in the model_dump_json method of the Pipeline model. This method is used to serialize the model's data into a JSON string.


The issue is likely due to the presence of a function in the model's data. In the Pipeline model, there is a field called model which is a function. When Pydantic tries to serialize this field, it fails because functions cannot be serialized.


To fix this issue, you need to remove the function from the model's data or modify it to be serializable. Here are a few possible solutions:


    

  1. Remove the function from the model's data:
    2. 



If the function is not essential to the model's behavior, you can remove it from the data. This will prevent Pydantic from trying to serialize it.


    

  1. Modify the function to be serializable:
    2. 



If the function is essential to the model's behavior, you can modify it to be serializable. One way to do this is to use a lambda function or a function that returns a serializable object.


    

  1. Use a custom serialization method:
    2. 



If the function is complex and cannot be modified to be serializable, you can use a custom serialization method. You can create a custom to_json method that knows how to serialize functions.


Here's an example of how you can modify the model_dump_json method to serialize functions:


from pydantic import BaseModel
from pydantic_core import PydanticSerializationError

class Pipeline(BaseModel):
    #...

    def model_dump_json(self):
        try:
            return super().model_dump_json()
        except PydanticSerializationError as e:
            if isinstance(e, PydanticSerializationError) and e.type == 'function':
                # Serialize the function as a string
                return {'model': str(self.model)}
            raise e


In this example, the model_dump_json method catches the PydanticSerializationError exception and checks if the error is due to an unknown type. If it is, it serializes the function as a string using the str function.




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New failure detected:


Test Case:


tests/unit/pipelines/Pipeline_unit_test.py::test_serialization


Failure Details:


[gw0] linux -- Python 3.12.8 /home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/bin/python
tests/unit/pipelines/Pipeline_unit_test.py:41: in test_serialization
    assert pipeline.id == Pipeline.model_validate_json(pipeline.model_dump_json()).id
/home/runner/.cache/pypoetry/virtualenvs/swarmauri-dnwSkKe9-py3.12/lib/python3.12/site-packages/pydantic/main.py:477: in model_dump_json
    return self.__pydantic_serializer__.to_json(
E   pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'function'>




Suggested Fix (via Agent):


The error message indicates that Pydantic is unable to serialize an unknown type, which is a function. This is because Pydantic's model_dump_json method is trying to serialize a function object, which is not a valid JSON type.


The cause of this failure is likely due to the fact that the Pipeline model in your project contains a field that is a function, which is not a valid JSON type.


To fix this issue, you need to remove the function field from the Pipeline model or modify it to be a valid JSON type.


Here are the steps to fix the issue:


    

  1. Identify the field in the Pipeline model that is causing the issue.
    2. 

  2. Remove or modify the field to be a valid JSON type.
    3. 

  3. Update the Pipeline model to reflect the changes.
    4. 



Here is an example of how you can modify the Pipeline model to remove the function field:


from pydantic import BaseModel

class Pipeline(BaseModel):
    # Remove the function field
    # def some_function(self):
    #     pass

    # Add the function field as a string
    some_function: str = Field(default="some_function")


Alternatively, you can modify the Pipeline model to use a different data type for the field that is causing the issue.


After making the changes to the Pipeline model, you should be able to run the test without any issues.


If you are still experiencing issues, you can try to debug the code by adding print statements or using a debugger to identify the specific line of code that is causing the issue.


Here is an example of how you can use a debugger to identify the issue:


import pdb

def some_function():
    pdb.set_trace()
    # Add a breakpoint here to debug the code


When you run the test, the debugger will pause at the breakpoint, and you can inspect the variables and the code to identify the issue.


I hope this helps you to identify and fix the issue with your test case!




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