LangChain for Beginners (OpenAI / LLMOps)

Learn how to build LLM-powered Python applications with LangChain and OpenAI, with core concepts like chains, agents, and memory.

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67 minutes


Calling Prompts with LLMs

Learn how to interact with language models by sending prompts and interpreting responses.

4 min

Storing and Retrieving Chat History

Learn techniques to save and retrieve past interactions, improving your chatbot's performance and user experience.

7 min

Memory and Chat Bots

Learn about the importance of memory for chatbots and how to implement it for more contextual conversations through a terminal-based chat bot.

7 min

Human as a Tool

Learn how to integrate human inputs and decisions into the LLM thought process, leveraging human strengths.

3 min

Prompt Templating and Chaining

Learn to structure and sequence your prompts for more complex and controlled model responses.

6 min

Using Different Large Language Models

Learn to explore, compare, and select among different Language Learning Models (LLMs) for various tasks from HuggingFace.

5 min

Simple Sequential Chains

Learn how to chain together multiple LLM chains, taking the output of one chain as the input of the next via simple sequential chains.

6 min

Getting Started with LangChain

Learn about LangChain, LLMs, getting your OpenAI access token and setting up your coding environment.

4 min

Plan and Execute Agents

Learn about another type of LangChain agent, the plan and execute agent and how it plans its steps first and then executes each one.

9 min

Action Agents and Tools

Learn how to create dynamic AI agents that can perform actions, react, and interact with real-world information.

7 min

Document Loading and Q&A Retrieval

Learn how to load and process documents with DocumentLoaders for deeper information extraction and interaction, as well as using Retrieval chains.

13 min