Get chunked elements

import json, base64, zlib
from typing import List, Dict, Any

# Extract the contents of an orig_elements field.
def extract_orig_elements(orig_elements):
    decoded_orig_elements = base64.b64decode(orig_elements)
    decompressed_orig_elements = zlib.decompress(decoded_orig_elements)
    return decompressed_orig_elements.decode('utf-8')

def get_chunked_elements(input_json_file_path: str) -> List[Dict[str, Any]]:
    # Create a dictionary that will hold only
    # a transposed version of the returned elements. 
    # For instance, we just want to capture each element's ID,
    # the chunk's text, and the chunk's associated elements in context.
    orig_elements_dict: List[Dict[str, Any]] = []

    with open(input_json_file_path, 'r') as file:
        file_elements = json.load(file)

    for element in file_elements:
        # For each chunk that has an "orig_elements" field...
        if "orig_elements" in element["metadata"]:
            # ...get the chunk's associated elements in context...
            orig_elements = extract_orig_elements(element["metadata"]["orig_elements"])
            # ...and then transpose it and other associated fields into a separate dictionary.
            orig_elements_dict.append({
                "element_id": element["element_id"],
                "text": element["text"],
                "orig_elements": json.loads(orig_elements)
            })
    
    return orig_elements_dict

if __name__ == "__main__":
    # Source file: https://www.fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf
    input_filepath = "local-ingest-output-json/Portable-Document-Format-Specifications.json"
    output_filepath = "local-ingest-output-orig/Portable-Document-Format-Specifications-Orig-Elements-Only.json"

    orig_elements_dict = get_chunked_elements(input_json_file_path = input_filepath)

    # Convert the elements into a JSON object.
    orig_elements_json = json.dumps(orig_elements_dict, indent=2)

    # Write the JSON to a file.
    with open(output_filepath, "w") as file:
        file.write(orig_elements_json)

from unstructured_client import UnstructuredClient
from unstructured_client.models import operations, shared
from unstructured.staging.base import elements_from_dicts, elements_to_json

import os, base64, zlib
from typing import List, Dict, Any

# Extract the contents of an orig_elements field.
def extract_orig_elements(orig_elements):
    decoded_orig_elements = base64.b64decode(orig_elements)
    decompressed_orig_elements = zlib.decompress(decoded_orig_elements)
    return decompressed_orig_elements.decode('utf-8')

# Source file: https://www.fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf
input_filepath = "local-ingest-input-pdf/Portable-Document-Format-Specifications.pdf"
output_filepath = "local-ingest-output-json/Portable-Document-Format-Specifications.json"

client = UnstructuredClient(
    api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
    server_url=os.getenv("UNSTRUCTURED_API_URL"),
)

with open(input_filepath, "rb") as f:
    files = shared.Files(
        content=f.read(),
        file_name=input_filepath
    )

# Chunk the document with a basic chunking strategy.
# Create chunks that are at least around 200 characters (soft limit)
# but never more than 300 characters (hard maximum).
req = operations.PartitionRequest(
    shared.PartitionParameters(
        files=files,
        strategy=shared.Strategy.HI_RES,
        split_pdf_page=True,
        split_pdf_allow_failed=True,
        split_pdf_concurrency_level=15,
        chunking_strategy="basic",
        new_after_n_chars=200,
        max_characters=300
    )
)

try:
    res = client.general.partition(request=req)

    # Create a dictionary that will hold only
    # a transposed version of the returned elements. 
    # For instance, we just want to capture each element's ID,
    # the chunk's text, and the chunk's associated elements in context.
    orig_elements_dict: List[Dict[str, Any]] = []

    for element in res.elements:
        # For each chunk that has an "orig_elements" field...
        if "orig_elements" in element["metadata"]:
            # ...get the chunk's associated elements in context...
            orig_elements = extract_orig_elements(element["metadata"]["orig_elements"])
            # ...and then transpose it and other associated fields into a separate dictionary.
            orig_elements_dict.append({
                "element_id": element["element_id"],
                "text": element["text"],
                "orig_elements": json.loads(orig_elements)
            })
    
    # Convert the elements into a JSON object.
    orig_elements_json = json.dumps(orig_elements_dict, indent=2)

    # Write the JSON to a file.
    with open(output_filepath, "w") as file:
        file.write(orig_elements_json)
except Exception as e:
    print(e)