Sapling Python Client

Python SDK wrapper for the Sapling.ai API.

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Overview

Sapling is a toolkit for helping developers build language model-powered applications. The API provides spelling and grammar checking, autocomplete, tone detection, rephrasing, AI detection, zero-shot text classification, structured data extraction, translation, PII detection and redaction, content safety scoring, plain-language simplification, SEO analysis, and more.

Key Features:

• 60% More Corrections: Outperforms competing solutions at similar accuracy levels using state-of-the-art generative AI models.
• Real-Time Performance: Experience the same low-latency corrections as Sapling's native integrations.
• Comprehensive Error Detection: Identifies over 20 error types including prepositions, noun forms, verb tense, with both high-level and fine-grained error information.
• Domain-Specific Models: Get corrections optimized for your content type, from academic writing, to doctors notes, to user-generated reviews.
• Enterprise-Grade Security: Features include no data retention policies, self-hosted/on-premises deployment options, and enterprise-grade security policies and procedures.
• Rich Text Editor Integration: Supports TinyMCE, CKEditor, QuillJS, Trix, ProseMirror, WordPress, Draft.js, Froala, Lexical and more. For web-based editors, consider using our JavaScript SDK for display UI components.

Installation

Install the sapling-py package from PyPI with pip:

python -m pip install sapling-py

Or add it to a uv project:

uv add sapling-py

Documentation

Documentation for the client is available at Read the Docs and documentation for the HTTP API is available at Sapling.ai.

Quickstart

• Register for an account at Sapling.ai.
• After registering and signing in, generate a development API key in your dashboard.
• Install the Python client by following the installation steps above.

from sapling import SaplingClient

API_KEY = '<YOUR_API_KEY>'
client = SaplingClient(api_key=API_KEY)
edits = client.edits('Lets get started!', session_id='test_session')

The result should be an array of edits of this form:

[{
  "id": "aa5ee291-a073-5146-8ebc-c9c899d01278",
  "sentence": "Lets get started!",
  "sentence_start": 0,
  "start": 0,
  "end": 4,
  "replacement": "Let's",
  "error_type": "R:OTHER",
  "general_error_type": "Other",
}]

Get a production key by following this documentation.

Here's some more information on request options and response structure.

Batch requests

The analysis endpoints — classify, extract, safety, langdetect, translate, summarize, quality and aidetect — also accept a list of 1-10 texts in place of a single string. The batch is sent as one request (the same options apply to every item) and returns {'results': [...]} with one single-response-shaped dict per input, in order:

scores = client.quality(['First draft.', 'Second draft.'], sentence_scores=True)
langs = client.langdetect(['Bonjour le monde', 'Hello world'])

License

Copyright 2024--present Sapling Intelligence, Inc.

Licensed under the Apache License, Version 2.0.