Skip to main content

Documentor

An enterprise-grade AI documentation suite. It ingests a codebase, parses it semantically, generates accurate documentation using LLMs, and serves it via CLI, Web UI, and CI/CD pipelines.

Installation

Recommended Method (pipx)

Because Documentor is a standalone CLI tool, the best way to install it on modern Linux/macOS systems (which enforce PEP 668) is using pipx. This installs Documentor in an isolated environment while exposing the CLI globally.

# If you don't have pipx installed: python3 -m pip install --user pipx
pipx install documentor-ai

Alternative Methods

If you are inside an active virtual environment (like .venv/), you can use standard pip:

pip install documentor-ai

(Note: If you attempt this globally on newer Linux distributions without pipx, you will get an externally-managed-environment error. You can bypass this by appending --break-system-packages, though pipx is heavily preferred).

Upgrading an Existing Installation

To get the latest version (including new features like Interactive Chat), run the upgrade command corresponding to how you installed it:

# If you used pipx
pipx upgrade documentor-ai

# If you used standard pip
pip install --upgrade documentor-ai

BYO-LLM (Bring Your Own LLM)

Documentor uses LiteLLM under the hood, allowing you to use your preferred model (OpenAI, Anthropic, Gemini, DeepSeek, local models via Ollama, etc.).

Run the interactive setup command to configure your API keys:

documentor configure

(Alternatively, you can just export your keys directly in your terminal, e.g. export OPENAI_API_KEY="sk-...")

Usage

1. Command Line Interface (CLI)

To generate documentation for a repository, run:

documentor generate /path/to/your/repo --model gemini/gemini-3.6-flash

Note on Parsing: Documentor automatically ignores node_modules, dist, .env files, logs, and all .git ignored files by default. If you want to force Documentor to ignore specific files or folders, just create a .docignore file in the root of your project!

More Examples: Generate for the current directory (.) using Google's fast Gemini Flash model:

documentor generate . --model gemini/gemini-3.6-flash

Single/Multiple Specific Files: If you only want to generate or regenerate documentation for specific files (for instance, if you only updated a few files in a large project), you can specify them using the --file or -f flag. This will skip ARCHITECTURE.md and QUICKSTART.md and only document the targeted files:

documentor generate . -f src/main.py -f src/utils.py

Generate using Anthropic's Claude:

documentor generate . --model claude-3-5-sonnet-20240620

2. Chat with your Codebase (RAG)

Once the repository is indexed, you can ask questions about your codebase.

Interactive Chat Mode (Recommended): If you run chat without providing a specific question, it will drop you into an interactive terminal where you can chat continuously!

documentor chat --path . --model gemini/gemini-3.6-flash

Single Question Mode: If you just want a quick answer, you can provide the question directly:

documentor chat "How does the authentication system work?" --path . --model gemini/gemini-3.6-flash

3. Web UI (Playground)

Prefer a visual interface? Spin up the beautifully designed, glassmorphic Web UI:

documentor serve --port 8000

Then open http://localhost:8000 in your browser.

3. GitHub Action (CI/CD)

Documentor comes packaged as a lightning-fast Docker Action. You can automate documentation generation on your Pull Requests by creating .github/workflows/documentor.yml in your target repository:

name: Generate AI Docs
on:
  pull_request:
    branches: [ main ]
jobs:
  docs:
    runs-on: ubuntu-latest
    permissions:
      contents: write
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0
      - uses: nirajmatere/documentor@main
        with:
          model: 'gemini/gemini-3.6-flash'
        env:
          GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
      - run: |
          git config --global user.name 'github-actions[bot]'
          git config --global user.email 'github-actions[bot]@users.noreply.github.com'
          git add docs/ ARCHITECTURE.md QUICKSTART.md
          git commit -m "docs: Auto-update AI documentation" || echo "No changes to commit"
          git push

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

documentor_ai-0.1.10.tar.gz (20.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

documentor_ai-0.1.10-py3-none-any.whl (21.7 kB view details)

Uploaded Python 3

File details

Details for the file documentor_ai-0.1.10.tar.gz.

File metadata

  • Download URL: documentor_ai-0.1.10.tar.gz
  • Upload date:
  • Size: 20.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for documentor_ai-0.1.10.tar.gz
Algorithm Hash digest
SHA256 0f3bce61426441d26cd7298e373efe86adf18a7397a9b65a559ad42d826054b9
MD5 a992201c2e723b41b86f058a3059cd73
BLAKE2b-256 b9e9d362e377e04e4b0aa7b066f1ea13003ec1ce8d1ea04cb8ad975ebecafd50

See more details on using hashes here.

File details

Details for the file documentor_ai-0.1.10-py3-none-any.whl.

File metadata

  • Download URL: documentor_ai-0.1.10-py3-none-any.whl
  • Upload date:
  • Size: 21.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for documentor_ai-0.1.10-py3-none-any.whl
Algorithm Hash digest
SHA256 e3bbc46d97346ba44cb5116e93cd39fef1476e76356e5d79dd903862139e14e6
MD5 532488fe7fea8c81de9cc190b1ec2b32
BLAKE2b-256 228dc294be95012c6bb3c9d223ca5f74223288fb7f40124d250df21716e8fa89

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page