Error in Azure Cognitive Search Service when storing document page associated to each chunk extracted from PDF in a custom WebApiSkill

I have the following custom WebApiSkill:

@app.route(route="CustomSplitSkill", auth_level=func.AuthLevel.FUNCTION)

def CustomSplit&PageSkill(req: func.HttpRequest) -> func.HttpResponse:

    logging.info('Python HTTP trigger function processed a request.')

    try:

        req_body = req.get_json()

    except ValueError:

        return func.HttpResponse("Invalid input", status_code=400)

    try:

        # 'values' expected top-level key in the request body

        response_body = {"values": []}

        for value in req_body.get('values', []):

            recordId = value.get('recordId')

            text = value.get('data', {}).get('text', '')

            # Remove sequences of dots, numbers following them, and

            # any additional punctuation or newline characters, replacing them with a single space

            cleaned_text = re.sub(r"[',.\n]+|\d+", ' ', text)

            # Replace multiple spaces with a single space and trim leading/trailing spaces

            cleaned_text = re.sub(r'\s{2,}', ' ', cleaned_text).strip()

            # Pattern to match sequences of ". " occurring more than twice

            cleaned_text = re.sub(r"(\. ){3,}", "", cleaned_text)

            chunks, page_numbers = split_text_into_chunks_with_overlap(cleaned_text, chunk_size=256, overlap_size=20)

            

            # response object for specific pdf

            response_record = {

                "recordId": recordId,

                "data": {

                    "textItems": chunks,  # chunks is a str list

                    "numberItems": page_numbers # page_numbers is an int list

                }

            }

            response_body['values'].append(response_record)

        return func.HttpResponse(json.dumps(response_body), mimetype="application/json")

    except ValueError:

        return func.HttpResponse("Function app crashed", status_code=400)

The inputs and outputs of this skill in the skillset are defined like this:

inputs=[

    InputFieldMappingEntry(name="text", source="/document/content")

],

outputs=[

    OutputFieldMappingEntry(name="textItems", target_name="pages"),

    OutputFieldMappingEntry(name="numberItems", target_name="numbers")

],

And the SearchIndexerIndexProjectionSelector is configured in the following way:

index_projections = SearchIndexerIndexProjections(  

        selectors=[  

            SearchIndexerIndexProjectionSelector(  

                target_index_name=index_name,  

                parent_key_field_name="parent_id",  

                source_context="/document/pages/*",  

                mappings=[  

                    InputFieldMappingEntry(name="chunk", source="/document/pages/*"),  

                    InputFieldMappingEntry(name="vector", source="/document/pages/*/vector"),  

                    InputFieldMappingEntry(name="title", source="/document/metadata_storage_name"),

                    InputFieldMappingEntry(name="page_number", source="/document/numbers/*"), 

                ],  

            ),  

        ],  

        parameters=SearchIndexerIndexProjectionsParameters(  

            projection_mode=IndexProjectionMode.SKIP_INDEXING_PARENT_DOCUMENTS  

        ),  

    )

My search fields look like this:

fields = [  

        SearchField(

            name="parent_id",

            type=SearchFieldDataType.String,

            sortable=True,

            filterable=True,

            facetable=True

        ),  

        SearchField(

            name="title",

            type=SearchFieldDataType.String

        ),  

        SearchField(

            name="chunk_id",

            type=SearchFieldDataType.String,

            key=True,

            sortable=True,

            filterable=True,

            facetable=True,

            analyzer_name="keyword"

        ),  

        SearchField(

            name="chunk",

            type=SearchFieldDataType.String,

            sortable=False,

            filterable=False,

            facetable=False

        ),  

        SearchField(

            name="vector",

            type=SearchFieldDataType.Collection(SearchFieldDataType.Single),

            vector_search_dimensions=1536,

            vector_search_profile_name="myHnswProfile"

        ),

        SearchField(

            name="page_number",

            type=SearchFieldDataType.Int32,

            sortable=True,

            filterable=True,

            facetable=True

        ), 

    ] 

I get the following error:

The data field 'page_number' in the document with key 'xyz' has an invalid value of type 'Edm.String' ('String maps to Edm.String'). The expected type was 'Edm.Int32'.

When changing the value to String the index creation passes, with the following result under page_numbers:

"page_number": "[1,2,3,4,5,6,7,...]"

But I want to get a single value under each chunk