[PLT-1207] Added prompt classification for python object support

[Gabefire]

Description

Please include a summary of the changes and the related issue. Please also include relevant motivation and context.

• Gives the ability to import annotations for prompt response projects
• Made custom prompt classification annotation class for better validation (only one is allowed per label)
• Did some testing and classification annotation class will work for a response (only classification). I had a response custom class but I think that is to complicated and reuses a bunch of code
• Since we are deprecating the data type. I only allowed global keys to be passed in as a dict for data. I don't see the point of adding since we are deprecating.
• Switch the default inference data type to GenericDataRowData to deserialize a label. This improves testing

Type of change

Please delete options that are not relevant.

• [x] New feature (non-breaking change which adds functionality)

All Submissions

• [x] Have you followed the guidelines in our Contributing document?
• [x] Have you provided a description?
• [x] Are your changes properly formatted?

New Feature Submissions

• [x] Does your submission pass tests?
• [x] Have you added thorough tests for your new feature?
• [x] Have you commented your code, particularly in hard-to-understand areas?
• [x] Have you added a Docstring?

[Gabefire]

prompt_annotation = lb_types.PromptClassificationAnnotation(
    name="test",
    value=lb_types.PromptText(answer="the answer to the text questions right here"),

)

response_annotation = lb_types.ClassificationAnnotation(
    name="response_radio",
    value=lb_types.Radio(answer = 
                         lb_types.ClassificationAnswer(
                             name="1"
                         ))
)

label = []
label.append(
    lb_types.Label(
        data={"global_key": "clxxmppe00p36073qc3qqfvkq"},
        annotations=[
            prompt_annotation,
            response_annotation
        ],
    ))