InceptBench

License

Educational content evaluation framework using LLM-based analysis.

Website • Benchmarks • API Endpoint • API Docs • GitHub

Overview

InceptBench evaluates educational content across multiple quality dimensions:

Automated Classification - Determines content type (question, quiz, reading, etc.)
Hierarchical Evaluation - Decomposes complex content and evaluates bottom-up
Comprehensive Metrics - 8-11 metrics per content type with scores and reasoning
Curriculum-Aware - Integrates curriculum standards via vector store search

Installation

pip install inceptbench

System Dependencies

InceptBench requires system-level Cairo libraries for inline SVG image analysis. Without these, SVG images in educational content will not be analyzed.

macOS:

brew install cairo pango gdk-pixbuf libffi

Ubuntu/Debian:

sudo apt-get install -y libcairo2 libpango-1.0-0 libpangocairo-1.0-0 libgdk-pixbuf2.0-0 libffi-dev

Windows: Follow the GTK3 installer for Windows or install via MSYS2:

pacman -S mingw-w64-x86_64-cairo mingw-w64-x86_64-pango mingw-w64-x86_64-gdk-pixbuf2

CLI Usage

# Create sample input file
inceptbench example

# Evaluate from JSON file
inceptbench evaluate content.json

# Evaluate raw content
inceptbench evaluate --raw "What is 2+2? A) 3 B) 4 C) 5 D) 6"

# Save results to file
inceptbench evaluate content.json -o results.json

# Check version
inceptbench --version

REST API

The production API is available at https://api.inceptbench.com

# Health check
curl https://api.inceptbench.com/health

# Interactive docs
# Visit: https://api.inceptbench.com/docs

# Evaluate content
curl -X POST https://api.inceptbench.com/evaluate \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-api-key" \
  -d '{"generated_content": [{"content": "What is 2+2? A) 3 B) 4 C) 5 D) 6"}]}'

Programmatic Usage (Python)

import asyncio
from inceptbench import EvaluationService

async def main():
    service = EvaluationService()
    result = await service.evaluate(
        content="What is 2+2? A) 3 B) 4 C) 5 D) 6",
        curriculum="common_core"
    )
    print(f"Score: {result.overall.score:.2f}")

asyncio.run(main())

Input Format

{
  "generated_content": [
    {
      "id": "q1",
      "curriculum": "common_core",
      "request": {
        "grade": "7",
        "subject": "mathematics",
        "type": "mcq",
        "difficulty": "medium",
        "locale": "en-US",
        "skills": {
          "lesson_title": "Congruent and Similar Triangles",
          "substandard_id": "CCSS.MATH.CONTENT.7.G.A.1+3"
        },
        "instruction": "A real-world problem involving congruent and similar triangles"
      },
      "content": "Triangle ABC is similar to triangle DEF. If AB = 6 cm and DE = 9 cm, what is the ratio of their corresponding sides?"
    }
  ]
}

Content Item Fields

Field	Required	Default	Description
`content`	Yes	-	Content to evaluate (string or JSON)
`id`	No	Auto-generated	Unique identifier
`curriculum`	No	`common_core`	Curriculum for alignment
`request`	No	`null`	Generation metadata (see below)

Request Metadata Fields (all optional)

Field	Description
`grade`	Grade level (e.g., "7", "K", "12")
`subject`	Subject area (e.g., "mathematics", "english")
`type`	Content type (e.g., "mcq", "fill-in", "article")
`difficulty`	Difficulty level (e.g., "easy", "medium", "hard")
`locale`	Locale/language code (e.g., "en-US", "es-MX")
`skills`	Skills info (JSON object or string)
`instruction`	Generation instruction/prompt

Images

Images are automatically detected from content. Include as:

Direct URLs: https://example.com/image.png
Markdown: ![alt](https://example.com/image.png)
HTML: <img src="https://example.com/image.png">
Inline SVG: <svg>...</svg> (requires Cairo system libraries, see System Dependencies)

Content Types

The evaluator automatically classifies content into:

Type	Description
`question`	Single educational question
`quiz`	Multiple questions together
`fiction_reading`	Fictional narrative passages
`nonfiction_reading`	Informational passages
`other`	General educational content

Documentation

For complete documentation, input format details, and developer guides:

View Full Documentation on GitHub

License

Proprietary - Copyright Trilogy Education Services

Release files for inceptbench 2.7.8

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for inceptbench 2.7.8
File	Size	Uploaded
inceptbench-2.7.8.tar.gz	9.8 MB	Jul 20, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for inceptbench 2.7.8
File	Interpreter	ABI	Platform	Reset
inceptbench-2.7.8-py3-none-any.whl 10.0 MB Jul 20, 2026	Python 3	none	any	Details

Total release size: 19.8 MB

Release files / inceptbench-2.7.8.tar.gz

Download URL	inceptbench-2.7.8.tar.gz
Size	9.8 MB
Tags	Source
SHA-256 checksum How to use checksums	`0be7cb5ed2756e95e9d120d6aa07ef76b6da2ca719276dc701570c034386f8e3`
BLAKE2b-256 checksum How to use checksums	`5629419857df93e8bc763aad25605150fb3604051fb7526ac9546aa83b11a3dd`
Upload date	Jul 20, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/2.2.1 CPython/3.13.0 Darwin/25.1.0`

Release files / inceptbench-2.7.8-py3-none-any.whl

Download URL	inceptbench-2.7.8-py3-none-any.whl
Size	10.0 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`9dea71da4b93e10a99aaf368121fd6b149e592d83069177718055cdd9f1c1d7d`
BLAKE2b-256 checksum How to use checksums	`10b59141730f7238a8ff2111f64562a786d8448eb6015337b4f2337aaa38ea5a`
Upload date	Jul 20, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/2.2.1 CPython/3.13.0 Darwin/25.1.0`