--- title: LangChain & OpenAI description: Today I learned about LangChain slug: openai-langchain tags: [AI,ML,LLM,ChatGPT] image: https://davidawindham.com/wp-content/themes/daw/img/opengraph_image.jpg hide_table_of_contents: false --- Today I learned how the integrate LangChain into the OpenAI API. Since it was quite a bit to wrap my head around, I also had to do the deep dive on some of the fundamentals of machine learning and vector databases. I published a simple demo and started making notes about the process. I've started making notes and related resources @ [/docs/sass/openai](/docs/saas/openai) ₁. I also put up a simple demo @ [https://jenks.davidawindham.com](https://jenks.davidawindham.com) ₂ that uses a doctoral dissertation from a friend who teaches computer science locally. It's powered by the OpenAI API, LangChain, and a Pinecone vector database. I'm about halfway done with a course ChatGPT Prompt Engineering for Developers₃, and I spent a couple hours on the phone talking with a fellow who has a very deep understanding of machine learning and artificial intelligence. It was mostly me asking him to explain some of these to me: - why did my vector database use a cosine metric and what does trigonometry have to do with machine learning? - what are vector dimensions and how to they related to machine learning - how are artificial neural networks built - how are linear regressions used in machine learning - how are weights and dimensions added to models. It's all quite a bit to take in. My brain was lit 🔥 on LangChain, so I spent a good hour just decompressing. I still feel a bit like I did when I first started learning programming in that I have such a naive knowledge of the fundamentals. In the last couple of weeks, I've spent a good bit of time just getting reacquainted with Python development environments like Jupyter, Colab, Tensorflow, and PyTorch. I don't think I'll ever be building neural networks, but I would at least like to know how it's done so that the training, chaining, prompting, transformers, and pipelines will become easier for me to use. Although I can see some really practical applications, I think my first custom project will likely be an absurd AI chatbot built on top of my personal chats, emails, calendar, this knowledge-base, and my website₄. My wife and I were discussing AI a couple days ago and our biggest takeaway is that when systematic knowledge like that of a Jeopardy contestant becomes less impressive, the more that our personal human qualities like emotion and artistic creativity become important. --- 1. Docs / SAAS / OpenAI - [/docs/saas/openai](/docs/saas/openai) 2. TedBot - [https://jenks.davidawindham.com](https://jenks.davidawindham.com) 3. ChatGPT Prompt Engineering for Developers - 4. A Second Brain -