byteit 0.1.2

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

ByteIT Python SDK

ByteIT's Python library for extracting structured data from documents. It is designed for backend services and ETL pipelines that require reliable, consistent document parsing at scale through a simple API.

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Installation

Install from PyPI:

pip install byteit

Python 3.8 or newer is required.

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Quick Start

from byteit import ByteITClient

client = ByteITClient(api_key="your_api_key")

result = client.parse("document.pdf")
print(result.decode())

The returned value is raw bytes containing the parsed document content.

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Supported Input File Types

ByteIT supports the following file types as input:

• PDF (.pdf)
• Word (.docx)
• PowerPoint (.pptx)
• HTML (.html)
• Markdown (.md)
• Plain text (.txt)
• JSON (.json)
• XML (.xml)

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Basic Usage

Parse a Local File

result = client.parse("invoice.pdf")

By default, the output format is Markdown (md).

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Output Formats

You can choose the output format depending on your pipeline needs:

txt = client.parse("doc.pdf", output_format="txt")
json = client.parse("doc.pdf", output_format="json")
md = client.parse("doc.pdf", output_format="md")
html = client.parse("doc.pdf", output_format="html")

Supported output formats:

• Plain text (txt)
• JSON (json)
• Markdown (md) (default)
• HTML (html)

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Save Output to File

client.parse(
    "doc.pdf",
    output_format="md",
    output="result.md"
)

When output is provided, the parsed result is written directly to disk.

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Notebook Integration

When used in Jupyter notebooks, ByteIT automatically displays results in a readable format:

• JSON: Interactive, expandable/collapsible tree view
• Markdown: Rendered with formatting (headers, lists, etc.)
• HTML: Rendered as HTML
• Text: Code block with syntax highlighting

# In a Jupyter notebook - automatically displays formatted result
result = client.parse("document.pdf", result_format="json")

To disable auto-display, save to a file instead:

# Saves to file, no auto-display
result = client.parse("doc.pdf", result_format="json", output="output.json")

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Typical Use Cases

• Extracting structured data from documents in ETL pipelines
• Preprocessing documents before indexing or downstream processing
• Automating ingestion of invoices, contracts, or reports
• Interactive document exploration in Jupyter notebooks

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API Reference

ByteITClient

ByteITClient(api_key: str)

Creates a new ByteIT client.

Parameters

• api_key (str): Your ByteIT API key

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parse(...)

parse(
    input,
    output_format: str = "md",
    output = None
)

Parse a document and return the extracted content.

Parameters

• input (str | Path): Path to a local document
• output_format (str): Output format (txt, json, md, html)
• output (str | Path | None): Optional path to save the result

Returns

• bytes: Parsed document content

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Error Handling

The SDK exposes specific exceptions for common error cases:

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

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

All exceptions inherit from ByteITError.

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Configuration

Environment Variable

You can provide the API key via environment variable:

export BYTEIT_API_KEY="your_api_key"

import os
from byteit import ByteITClient

client = ByteITClient(api_key=os.getenv("BYTEIT_API_KEY"))

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Requirements

• Python 3.8+
• requests

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About ByteIT

ByteIT provides document parsing and data extraction APIs designed for backend systems and automation workflows.

Website: https://byteit.ai

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License

This project is licensed under the terms specified in the LICENSE file.

© 2026 ByteIT GmbH

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