Skip to content
Get packs

Codebase to Tutorial

A Python tool that uses an LLM to read a GitHub repo or local folder and write a beginner tutorial about it.The-Pocket/PocketFlow-Tutorial-Codebase-Knowledge

GitHub Download source
Stars
12.7k
Forks
1.4k
Licence
MIT
Language
Python
Last update
5 months ago
Type
Dev tool

What it is

This tool crawls a codebase, uses an AI language model to find its core concepts and how they connect, and writes a beginner-friendly tutorial with visualizations. It is built as a tutorial project on top of Pocket Flow, a small LLM framework, and is meant to help people understand unfamiliar code faster.

  • Generate a tutorial for a public GitHub repository with a single command
  • Analyze a local project directory, filtering files with include and exclude patterns
  • Produce a tutorial in another language using the --language option
  • Limit analysis size with --max-size and the number of abstractions with --max-abstractions

Great for

  • Developers who need to understand a large unfamiliar open-source project
  • Students studying how real libraries are structured
  • Teams wanting a first-draft onboarding guide for an internal codebase
  • People who already have an LLM API key and are comfortable running Python scripts

Not ideal for

  • People without a Gemini, Ollama, or other supported LLM setup, since the tool needs a model to generate anything
  • Users who need guaranteed accurate documentation, because the output is AI-generated and the README does not describe a verification process
  • Non-technical users who cannot install Python dependencies or edit a .env file
Step-by-step guide: how to use Codebase to TutorialInstall, first run, examples, tips and FAQs

How to get it

  1. 1

    Clone and build from source

    You'll need: Python 3 · pip · An LLM API key (for example GEMINI_API_KEY) or a local Ollama setup

    Clone the repository

    git clone https://github.com/The-Pocket/PocketFlow-Tutorial-Codebase-Knowledge

    Install dependencies

    pip install -r requirements.txt

    Verify the LLM setup

    python utils/call_llm.py
  2. 2

    Run it

    • Set your LLM credentials in a .env file or as environment variables, such as GEMINI_API_KEY
    • Run python utils/call_llm.py to confirm the model responds
    • Run python main.py --repo with a GitHub URL, or --dir with a local path
    • Find the generated tutorial in ./output, or in the directory set with --output
  3. 3

    Get the most out of it

    • Use --include and --exclude patterns to focus the analysis on relevant source files and skip tests
    • Set --language to generate the tutorial in a language other than English
    • Set GITHUB_TOKEN to access private repositories or avoid rate limits
    • Use Docker with a mounted output volume if you prefer not to install Python locally

Downloads

Source code (.zip)main branch · straight from GitHubOfficial website & docscode2tutorial.com/

Strengths

  • Clear command-line options for repo or directory input, file filtering, and output location
  • Supports multiple LLM providers through environment variables, including Ollama for local models
  • Output examples for well-known projects are linked from the README

Trade-offs

  • Output quality depends on the chosen LLM, and the README recommends models with thinking capabilities
  • Requires API credentials or a locally running model before first use
  • The README is partly truncated and does not show full details about output format or cost

How it compares

ProjectStarsTypeLevelUpdatedBest for
PocketFlow-Tutorial-Codebase-Knowledge (this)12.7kDev toolintermediate5 months agoDevelopers who need to understand a large unfamiliar open-source project
PocketFlow11.3kLibraryintermediate3 months agoDevelopers who want a small, readable LLM framework they can inspect in full
awesome-generative-ai-guide30.1kCurated listbeginner8 days agoBeginners who want a structured starting point for generative AI
nanobot49.8kAppintermediate4 days agoPeople who want a self-hosted personal assistant they can inspect and customize
generative-ai-for-beginners123kLearning resourcebeginner5 days agoDevelopers who know some Python or TypeScript and want a guided introduction to generative AI
Prompt-Engineering-Guide79.8kLearning resourcebeginner8 months agoPeople who are new to prompting and want structured lessons with examples

Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.