DocLens AI

DocLens AI is a production-grade documentation analysis platform that evaluates technical documentation for readability, structure, completeness, and writing style. It provides a CLI tool, a REST API, and Dockerized deployment, backed by automated testing and CI.

This project is designed to demonstrate real-world software engineering practices, not a demo or toy project.

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Key Features

• Analyze documentation from a public URL
• Readability scoring using linguistic metrics
• Structural analysis (headings, lists, flow)
• Completeness checks (examples, instructions)
• Writing style assessment
• Command Line Interface (CLI)
• FastAPI-based REST API
• Docker & Docker Compose support
• End-to-end validation script
• CI pipeline with automated tests

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Tech Stack

• Python 3.10
• FastAPI
• Pydantic
• Requests, BeautifulSoup
• textstat, nltk
• Pytest
• Docker, Docker Compose
• GitHub Actions CI

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Project Structure

document_analyzer/
├── docker/                 # Docker & Compose files
├── scripts/                # Validation scripts
├── src/doclens/             # Application source
│   ├── api/                # FastAPI layer
│   ├── cli/                # CLI interface
│   ├── core/               # Core analysis logic
│   ├── services/           # Independent analyzers
│   ├── utils/              # Utility helpers
│   ├── config/             # Logging & config
│   └── premium/            # Premium feature placeholders
├── tests/                  # Unit tests
├── reports/                # Output reports
├── Makefile
├── requirements.txt
├── requirements-dev.txt
├── ARCHITECTURE.md
└── README.md

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Installation (Local)

Using Conda (recommended)

conda create -n doclens python=3.10
conda activate doclens
pip install -r requirements.txt
pip install -r requirements-dev.txt

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CLI Usage

Run the documentation analyzer from the command line:

make cli

Or directly:

PYTHONPATH=src python -m doclens.cli.analyze \
"https://example.com/docs" \
-o reports/report.json

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API Usage

Start the API server

make api

API runs at:

http://127.0.0.1:8000

Health Check

GET /health

Response:

{
  "status": "ok"
}

Analyze Documentation

POST /analyze

Request body:

{
  "url": "https://example.com/docs"
}

Response (example):

{
  "url": "...",
  "readability": {...},
  "structure_and_flow": {...},
  "completeness_and_examples": {...},
  "style_guidelines": {...}
}

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Docker Usage

Build and run with Docker Compose

docker compose -f docker/docker-compose.yml up --build

API will be available at:

http://localhost:8000

Health check is automatically configured.

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Testing

Run unit tests:

make test

Run full end-to-end validation (CLI + API):

make validate

This script verifies:

• Dependencies
• Unit tests
• CLI execution
• API startup
• Health endpoint
• JSON output validation

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CI Pipeline

GitHub Actions CI automatically:

• Installs dependencies
• Runs unit tests
• Validates the project structure

CI configuration lives in:

.github/workflows/ci.yml

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Architecture

A detailed system design is documented in:

ARCHITECTURE.md

It covers:

• Layered architecture
• Data flow
• Service boundaries
• Extensibility design
• Premium feature placeholders

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Premium Features (Planned)

Premium capabilities are intentionally stubbed and clearly marked:

• AI-powered revision suggestions
• Automatic doc rewriting
• Export to multiple formats
• Team analytics dashboards

These are placeholders only and do not contain business logic.

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Versioning

Current release:

v1.0.0

Tagged and published.

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License

MIT License. See LICENSE for details.