LLM, Agent, RAG, Evals, etc..
This lesson teaches you to build interactive chatbots using LangChain's LangGraph and React. It covers setting up a LangGraph project, integrating the `useStream` hook for real-time conversation management, and building a user interface with features like message editing and branch switching for enhanced user experience.
This lesson explores two key approaches to AI-powered deep research: flexible, agent-based methods and structured, workflow-based systems. It highlights the trade-offs between these approaches, showcasing LangChain's open-source tools and their role in building efficient and cost-effective deep research workflows.
This lesson teaches you to build a sophisticated AI-powered email assistant using Langchain and LangGraph. The system leverages LLMs, prompt engineering, and a human-in-the-loop design for efficient email management and meeting scheduling, all while incorporating a robust reflection mechanism for continuous improvement.
This lesson explores how scaling large language models (LLMs) dramatically improves reasoning abilities, particularly through "next word prediction." It introduces a new paradigm using Chain-of-Thought prompting and reinforcement learning to train LLMs for complex tasks like coding and structured output generation, showcasing impressive results and practical applications.
This lesson teaches you to build powerful AI agents using LangChain and LangGraph, leveraging LLMs and tools for complex tasks. The framework offers persistence, streaming, and debugging advantages, but requires understanding its functional API and workflow, including state management and control flow using decorators like `@entrypoint` and `@task`.
This lesson demonstrates building a document extraction system using Langchain and LangSmith to extract key data from 10-K reports, evaluating its accuracy and efficiency with various LLMs. The process involves data loading, prompt engineering, model selection, and performance analysis using LangSmith's evaluation tools, highlighting the trade-offs between accuracy, speed, and cost.
