import logging
from pathlib import Path

from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
from docling.backend.msword_backend import MsWordDocumentBackend
from docling.datamodel.base_models import InputFormat
from docling.datamodel.document import DocumentConversionInput
from docling.document_converter import DocumentConverter, FormatOption, PdfFormatOption
from docling.pipeline.simple_model_pipeline import SimpleModelPipeline
from docling.pipeline.standard_pdf_model_pipeline import StandardPdfModelPipeline

_log = logging.getLogger(__name__)

USE_EXPERIMENTAL = False

input_paths = [
    Path("tests/data/wiki_duck.html"),
    Path("tests/data/word_sample.docx"),
    Path("tests/data/lorem_ipsum.docx"),
    Path("tests/data/powerpoint_sample.pptx"),
    Path("tests/data/2206.01062.pdf"),
]
input = DocumentConversionInput.from_paths(input_paths)

# for defaults use:
doc_converter = DocumentConverter()

# to customize use:
# doc_converter = DocumentConverter(  # all of the below is optional, has internal defaults.
#     formats=[
#         InputFormat.PDF,
#         InputFormat.DOCX,
#     ],  # whitelist formats, other files are ignored.
#     format_options={
#         InputFormat.PDF: PdfFormatOption(backend=DoclingParseDocumentBackend),
#         InputFormat.DOCX: FormatOption(
#             pipeline_cls=StandardPdfModelPipeline, backend=MsWordDocumentBackend
#         ),
#         # InputFormat.IMAGE: PdfFormatOption(),
#     },
# )

conv_results = doc_converter.convert(input)

for res in conv_results:
    out_path = Path("./scratch") / f"{res.input.file.name}.experimental.md"
    print(
        f"Document {res.input.file.name} converted with status {res.status}."
        f"\nSaved markdown output to: {str(out_path)}"
    )
    # print(res.experimental.export_to_markdown())
    # Export Docling document format to markdown (experimental):
    with out_path.open("w") as fp:
        fp.write(res.experimental.export_to_markdown())