
Learn how LangChain abstracts LLMs, set up an OpenAI account and API key, and install LangChain and OpenAI to use OpenAI models with LangChain in a Python REPL.
Explore calling prompts with large language models using OpenAI in LangChain, including setting up the OpenAI model, adjusting temperature, and generating single or multiple prompts with llm.generate.
Learn prompt templating with placeholders using from_template, and chain prompts with a large language model via LangChain to handle multiple variables.
Learn to build a LangChain sequential chain by connecting two LLMChain instances with PromptTemplate, using SimpleSequentialChain to pass first output to the second, to generate a company name and catchphrase.
Learn how LangChain action agents chain tools like Wikipedia and LLM math to answer questions by stepwise observations, while plan-and-execute agents lock in a full sequence upfront.
Explore how to use human input as a tool in LangChain, guiding an LLM-driven agent to request and incorporate personal information when needed.
Learn how plan and execute agents in LangChain plan steps and execute tasks with SerpAPI and Wikipedia. See how planner and executor models drive multi-step queries from plan to execution.
Learn how LangChain memory and ConversationChain retain chat context for chatbots. Build a terminal-based AI chatbot using the predict method and memory-driven history.
Store and retrieve chat history with LangChain using ChatMessageHistory and ConversationBufferMemory to preserve context across conversations.
Apply LangChain and large language models to your own documents by loading a text file, chunking, embedding, storing in Chroma, and using a retrieval QA chain to answer questions.
Ready for an electrifying plunge into the universe of language technology? Prepare to enter the thrilling realm of LangChain with "LangChain 101 for Beginners (OpenAI / ChatGPT / LLMOps)", where you'll be taught how to harness the power of LangChain and Large Language Models (LLMs) to build your very own Python applications.
Our aim for this course is simple - to equip you with everything you need to embark on your LangChain adventure. You'll be walked through using different LLMs from industry giants OpenAI and HuggingFace, understand the magic of calling prompts, creating templates, and chaining these prompts together to create a robust, interactive system.
But that's not all! We’ll dive into the heart of conversational chatbots and explore how memory works within LangChain. We'll wrap things up with a detailed tutorial on how you can apply these impressive LLMs to your own documents.
This course isn’t just informative—it’s also seriously fun. Through the use of memes, real-world analogies, and an engaging, down-to-earth approach, we've designed this course to be an enjoyable journey into the world of LangChain.
Say goodbye to those long, never-ending courses that are all fluff and no substance. This course is compact, to-the-point, and perfect for Python developers looking for a fast-track introduction to LangChain and LLMs. We know your time is precious, so we've packed all the essential information into one power-packed hour.
"LangChain 101 for Beginners" is your golden ticket to understanding and implementing LangChain. By the end of this course, you'll not only have a comprehensive understanding of LangChain, but also be ready to dive headfirst into your next project with a newfound arsenal of skills and knowledge.
Don't wait—let's start scripting the future, together. Let’s dive into the incredible world of LangChain and Large Language Models, and have some fun along the way!