Editorial course preview
What the public course preview actually shows
These 4 complementary views highlight concrete, legible examples from the course presentation.
This Jupyter Notebook screenshot demonstrates how to use LangChain's PromptTemplate and LLMChain classes to build a simple generative AI application with Python.
This diagram illustrates the technical workflow of vector embeddings, showing how content and queries are processed by an embedding model and stored in a vector database for retrieval.
This interface demonstrates a functional LLM question-answering application built with Streamlit, showing the file upload process and configuration parameters for document processing.
An architecture diagram illustrating how LangChain integrates various large language models like GPT-4 and data sources such as PDFs and cloud services.
