byteit 1.1.0

AI-powered document intelligence platform - Turn your data into structured data with a single line of code.

ByteIT Python SDK

ByteIT is a Python client for document parsing and structured extraction. Use it to submit files, retrieve parsed content, and extract schema-based data from completed parse jobs.

Installation

pip install byteit

Requires Python 3.8+ and a ByteIT API key.

Quick Start

from byteit import ByteITClient

client = ByteITClient(api_key="your_api_key")
result = client.parse("document.pdf")
print(result.decode("utf-8"))

parse() returns raw bytes. Pass output="result.json" to write the result directly to disk.

Parse Documents

from byteit import ByteITClient, ProcessingOptions

client = ByteITClient(api_key="your_api_key")

result = client.parse(
    "invoice.pdf",
    processing_options=ProcessingOptions(languages=["en"], page_range="1-2"),
)

Public parse submission methods always request JSON output internally. If you need another format, request it when downloading an async result.

Async Workflow

job = client.parse_async("document.pdf")

status = client.get_job_status(job.id)
details = client.get_parse_job_details(job.id)

if status.is_completed:
    result_json = client.get_parse_job_result(job.id)
    result_txt = client.get_parse_job_result(job.id, result_format="txt")

Available parse-job methods:

Method	Purpose
get_parse_jobs()	List parse jobs
get_parse_job_details(job_id)	Get full parse-job details
get_job_status(job_id)	Check lightweight processing status
get_parse_job_result(job_id, result_format=None)	Download parse result

Structured Extraction

Extraction runs on a completed parse job and returns a dictionary matching your schema.

from byteit import ByteITClient, ExtractionSchema
from pydantic import Field


class InvoiceSchema(ExtractionSchema):
    invoice_number: str | None = Field(description="Invoice number")
    total_amount: str | None = Field(description="Total amount")


client = ByteITClient(api_key="your_api_key")
parse_job = client.parse_async("invoice.pdf")

result = client.extract(
    parse_job.id,
    InvoiceSchema,
    extraction_complexity="medium",
)

Async extraction is also available:

extract_job = client.extract_async(parse_job.id, InvoiceSchema)

status = client.get_job_status(extract_job.id)
if status.is_completed:
    extracted = client.get_extract_job_result(extract_job.id)

Available extraction methods:

Method	Purpose
extract(parse_job_id, schema, output=None, extraction_complexity="medium")	Run extraction and wait for the result
extract_async(parse_job_id, schema, extraction_complexity="medium")	Submit extraction without waiting
get_extract_jobs()	List extraction jobs
get_extract_job_details(job_id)	Get full extraction job details
get_extract_job_result(job_id)	Download extraction result

Processing Options

You can pass either a ProcessingOptions instance or a plain dictionary.

result = client.parse(
    "document.pdf",
    processing_options={
        "languages": ["de", "en"],
        "page_range": "1-5",
        "extraction_type": "complex",
    },
)

Error Handling

All SDK exceptions inherit from ByteITError.

from byteit.exceptions import (
    AuthenticationError,
    ByteITError,
    JobProcessingError,
    RateLimitError,
    ValidationError,
)

try:
    result = client.parse("document.pdf")
except AuthenticationError:
    print("Invalid API key")
except ValidationError as exc:
    print("Invalid request:", exc.message)
except RateLimitError:
    print("Rate limit exceeded")
except JobProcessingError as exc:
    print("Processing failed:", exc.message)
except ByteITError as exc:
    print("ByteIT error:", exc.message)

Supported Inputs

Common supported inputs include PDF, Word, PowerPoint, HTML, Markdown, plain text, JSON, XML, and common image formats such as PNG, JPEG, TIFF, and BMP.

Notebook Behavior

When running in Jupyter, parse results are automatically displayed as JSON when possible. Pass output=... if you want to suppress inline display and save the response directly.

Resources

• Studio: studio.byteit.ai
• Pricing: byteit.ai/pricing
• Support: byteit.ai/support
• LinkedIn: ByteIT on LinkedIn

Licensed under Apache 2.0. © 2026 ByteIT GmbH.