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Code AI with Rok

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_{Why am I using AI voiceover?
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📚 Table of contents 📚

Click to expand

• LLM providers
  
  • OpenAI
    
  • Google
    
• Frameworks
  
  • LlamaIndex
    
• Agents
  • LangGraph
    
  • CrewAI
    
  • Fetch.ai
    
• Cloud
  
  • Google Cloud
    
  • Snowflake
    
• Monitoring
  
  • LangSmith
    
• Vector DBs
  
  • Milvus
    
• NLP
  
  • spaCy
    
• My story
  
• Support
  
• Star history
  
• Contributions
  
• License

👾 LLM providers 👾

OpenAI

	Tutorial title	Tutorial description	Tech stack	Links
#1	Response in JSON format	Python and Node.js examples on how to get a JSON response using the OpenAI Chat Completions API		GitHub	YouTube
#2	Personal Math Tutor* *Assistants API v1 beta	Python and Node.js examples on how to build a Personal Math Tutor using the OpenAI Assistants API v1 beta with the Code Interpreter tool		GitHub	YouTube
#3	GUI for the Personal Math Tutor* *Assistants API v1 beta	Next.js GUI for the #2 Personal Math Tutor tutorial		GitHub	YouTube
#4	Customer Support Chatbot* *Assistants API v1 beta	Python and Node.js examples on how to build a Customer Support Chatbot using the OpenAI Assistants API v1 beta with the Knowledge Retrieval tool		GitHub	YouTube
#5	TUI for the Customer Support Chatbot* *Assistants API v1 beta	Python and Node.js TUIs for the #4 Customer Support Chatbot tutorial		GitHub	YouTube
#6	TUI for the Customer Support Chatbot with response streaming* *Assistants API v1 beta	Python and Node.js TUIs for the #4 Customer Support Chatbot tutorial with response streaming		GitHub	YouTube
#7	TUI for assistants: response polling vs. streaming* *Assistants API v2 beta	Python and Node.js TUIs for assistants to show the difference between response polling (manual or with a helper) and streaming (with a helper)		GitHub	YouTube
#8	LLMs explained	Python and Node.js examples on how LLMs work using the OpenAI SDK top_logprobs parameter		GitHub	YouTube

Google

	Tutorial title	Tutorial description	Tech stack	Links
#1	Gemini Pro API starter	Python and Node.js examples on how to use the Gemini Pro API		GitHub	YouTube

🛠️ Frameworks 🛠️

LlamaIndex

	Tutorial title	Tutorial description	Tech stack	Links
#1	Create Llama app with 1 command in 2 minutes	Instructions on how to create a LlamaIndex chat streaming app using Next.js GUI and OpenAI LLM with 1 command in 2 minutes		GitHub	YouTube
#2	GUI for a Travel Recommendation RAG	Streamlit GUI for a Travel Recommendation RAG with response streaming using LlamaIndex and OpenAI LLM		GitHub	YouTube
#3	Eval of the Travel Recommendation RAG	Evaluation of the #2 GUI for a Travel Recommendation RAG tutorial		GitHub	YouTube

🤖 Agents 🤖

LangGraph

	Tutorial title	Tutorial description	Tech stack	Links
#1	TUI for a LangGraph agent with a web connection	Python and Node.js TUIs for a LangGraph ReAct agent using OpenAI LLM and Tavily tool to get a web connection		GitHub	YouTube
#2	TUI for a LangGraph agent with memory	Add memory to the #1 TUI for a LangGraph agent with a web connection tutorial		GitHub	YouTube
#3	TUI for a LangGraph agent with persistent memory using PostgreSQL	Add persistent memory using PostgreSQL to the #1 TUI for a LangGraph agent with a web connection tutorial		GitHub	YouTube
#4	TUI for a LangGraph agent with persistent memory using PostgreSQL with pgvector	Add persistent memory using PostgreSQL with pgvector to the #1 TUI for a LangGraph agent with a web connection tutorial		GitHub	YouTube

CrewAI

	Tutorial title	Tutorial description	Tech stack	Links
#1	Podcast prepper	Python example using CrewAI, Anthropic LLM and Exa tool, designed for podcast hosts, helping them: research a guest prepare detailed insights about the guest suggest relevant questions for an upcoming episode with the guest		GitHub	YouTube
#2	Personalized poem writer	Python example using CrewAI, Mistral LLM and Exa tool, designed for creative writers and lyricists, helping them: research a person prepare detailed insights about the person write a personalized, funny, and light-hearted poem inspired by the person's life story		Coming soon... ✨	Coming soon... ✨

Fetch.ai

	Tutorial title	Tutorial description	Tech stack	Links
#1	uAgents starter	Python examples on how to: build a Fetch.ai agent with a startup task build a Fetch.ai agent with an interval task build a Fetch.ai agent and get its address build a Fetch.ai stateful agent		GitHub	YouTube
#2	uAgents communication	Python examples on how to make Fetch.ai agents communicate with each other locally or remotely using Almanac contracts		GitHub	YouTube

☁️ Cloud ☁️

Google Cloud

	Tutorial title	Tutorial description	Tech stack	Links
#1	Vertex AI Gemini Pro API starter	Python and Node.js examples on how to use the Vertex AI Gemini Pro API		GitHub	YouTube

Snowflake

	Tutorial title	Tutorial description	Tech stack	Links
#1	Snowflake Cortex LLM functions starter	Python example on how to use the Snowflake Cortex LLM functions		GitHub	YouTube

📈 Monitoring 📈

LangSmith

	Tutorial title	Tutorial description	Tech stack	Links
#1	LangSmith observability starter	Add observability using LangSmith to the #3 TUI for a LangGraph agent with persistent memory using PostgreSQL tutorial		GitHub	YouTube

🗃️ Vector DBs 🗃️

Milvus

	Tutorial title	Tutorial description	Tech stack	Links
#1	Milvus Standalone starter	Python and Node.js examples on how to install Milvus Standalone using Docker, connect to a Milvus Standalone server and list all Milvus collections		GitHub	YouTube
#2	Attu starter	Instructions on how to run Attu, a GUI for Milvus Standalone, using Docker		GitHub	YouTube
#3	Text similarity search	Python example on how to do text similarity search with Milvus Standalone		GitHub	YouTube

💬 NLP 💬

spaCy

	Tutorial title	Tutorial description	Tech stack	Links
#1	Add a new entity label to NER	Jupyter Notebook example on how to add a new entity label to spaCy's default NER model		GitHub	YouTube

🌱 My story 🌱

I started this YouTube channel in November 2023. At the time, I was working full-time as a developer and also being very active on Stack Overflow. I didn’t have much free time, but I still wanted to share my knowledge in video format. Using AI voiceover was the only way I could realistically make tutorials without burning out. It saved me from recording myself and needing any special equipment.

Some people mention the voiceover in the comments. I get it. Everyone has different preferences.

But... Making just one 10-minute tutorial takes me 25+ hours!

Here’s what goes into it:

• 🔍 Researching

  • I always try to cover the latest stuff in AI.
  • I spend time reading official docs.
  • I test everything myself before sharing it.

• 💻 Coding

  • I spend hours writing and debugging code.
  • I add comments and docstrings so it’s easier to follow.
  • I organize the GitHub repo by framework to keep it neat.
  • I always include the requirements.txt, pyproject.toml, or package.json file so you know exactly which dependency versions to use.

• ✍️ Scripting

  • I think a lot about what’s important and what’s not.
  • I try to keep things clear and to the point.
  • I always aim to explain even complex concepts in a simple way.
  • I make sure everything is practically explained, no theoretical fluff.

• 🎥 Recording

  • I record everything: the code editor, terminal, Docker Desktop, pgAdmin, and the browser for official docs, installation steps, or GitHub repos.
  • I show the full process, not just the code.
  • I capture how the code behaves in real-time, including command flow and output examples.
  • I walk you through the entire process step by step.

• 🗣️ Voiceover

  • I use AI to generate voiceover.
  • I rework the script and try again in case AI mispronounces something.

• 🎞️ Editing

  • I cut out boring parts, like when my computer lags.
  • I blur secrets when I show the .env file.
  • I make sure the video flows well and stays focused.

• 📤 Uploading

  • I organize my YouTube channel so it’s easy to find videos by framework.
  • I add timestamps so you can jump to the part you need.
  • I write a detailed description of the video, so whether you want to reach out to me, get the links I mention, or support me, you can find everything there.

• 🧾 Writing

  • I write the README.md file with helpful notes, tips, warnings, output examples, screenshots, GIFs, and more.
  • I use grammar checkers to make sure it’s clean.
  • I double-check all the links to make sure nothing’s broken.

• 📣 Sharing

  • I write posts for LinkedIn and X to help people discover the content.
  • I always link back and forth between the YouTube video and GitHub code so everything stays connected.

I do all of this for free! Yes, you’ll see ads when watching my tutorials, but I’m not earning anything from them. My YouTube channel doesn’t meet all the requirements for monetization (yet).

Despite using AI voiceover, I believe my tutorials are valuable. I focus more on delivering quality content than worrying about how natural the voice sounds.

So yeah, that’s why I’m using AI voiceover. Anyway, you're here to learn coding, not to judge my voice’s acting career, right? Because I’m not counting on becoming a voice actor anytime soon. Unless they’re casting for a robot.

☕ Support ☕

If you found my content helpful and want to help keep the tutorials brewing, you can buy me a coffee.

Thanks for the support! ❤️

⭐ Star history ⭐

🤝 Contributions 🤝

Thank you for considering contributing to my repo. While I don't accept direct additions of tutorials, I warmly welcome contributions in the following forms:

• Reporting major issues: Found a bug, or error? Feel free to open an issue on GitHub. Be sure to provide as much detail as possible, including steps to reproduce the issue.
• Fixing minor issues: Found a typo, grammatical error, or other small issue? Feel free to open a pull request to fix them directly.
• Making suggestions: Have an idea how I can enhance my tutorials or topics I should cover? Share your thoughts by creating a new issue outlining your suggestion. I'll carefully consider all reasonable ideas.

To contribute:

1. Fork this repo.
2. Make your desired changes.
3. Create a commit and push the changes.
4. Create a pull request.

I'll review your pull request and get back to you as soon as possible.

📄 License 📄

This project is open source and available under the MIT license.