Turn Any GitHub Repo Into Interactive Diagrams

.. PLUS: Learn how LLMs work under the hood

Author

Sumanth P
June 02, 2025

In today’s newsletter:

  • Turn any GitHub repository into interactive diagrams

  • Learn how LLMs work under the hood

  • Test and detect security issues in your LLM Apps

Reading time: 3 minutes.

Turn any GitHub repo into an interactive diagrams!

Just replace "hub" with "diagram" in a GitHub URL and instantly visualize the code base with interactive diagrams.

Why GitDiagram is a Game-Changer:

  • Instant visualization : Convert any GitHub repo into a system design or architecture diagram

  • Fully interactive : Navigate directly to source files and folders by clicking on diagram components.

  • Fast + accurate : Built on Claude 3.5 Sonnet for efficient and precise diagram generation.

  • Customizable : Modify diagrams with your own instructions and regenerate instantly.

👉 It’s 100% open source. You can find the repo here → Gitdiagram 

Interactive website to learn how LLMs work.

It combines clear, step-by-step explanations with dynamic 3D visualizations for an intuitive learning experience.

It starts with a brief introduction and walks you through every major component of an LLM, from Embedding, Layer Norm, Self-Attention, MLP, Transformer layers, Softmax, to Output layers.

Test and detect security issues in your LLM Apps!

DeepTeam is an open-source LLM red teaming framework to safety test LLM systems.

It lets you simulate adversarial attacks using state-of-the-art techniques like jailbreaking and prompt injections, so you can fix vulnerabilities such as PII leakage before users’ data get leaked.

What DeepTeam Does:

  • Red-teaming for LLMs: Test against jailbreaks, prompt injections, edge cases

  • Scenario-based tests: Write your own test cases for specific failure types

  • Works anywhere: Local, cloud, APIs, or even full agent pipelines

  • Developer-first: Run from the CLI, inspect outputs, iterate fast

That’s a Wrap

That’s all for today. Thank you for reading today’s edition. See you in the next issue with more AI Engineering insights.

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