Mô tả

Welcome to the LangChain Udemy course: Unlock the Power of Language Models with Python!

Ready to develop cutting-edge applications powered by language models? LangChain is the framework you need. With LangChain, create data-aware and agentic applications that connect language models with other data sources and enable interaction with the environment.

Why Choose LangChain?

LangChain offers numerous benefits for your language model development needs:

Components: LangChain provides modular and user-friendly abstractions for working with language models, along with a wide range of implementations.

Off-the-shelf chains: Start building applications quickly with pre-built chains designed for specific tasks. Modify existing chains or create new ones for more complex or customized use-cases.

LangChain Course Modules:

LangChain offers standard interfaces and external integrations for various modules:

  1. Model I/O: Easily interface with language models.

  2. Data connection: Connect with application-specific data sources.

  3. Chains: Construct sequences of calls to accomplish specific tasks.

  4. Agents: Enable chains to choose tools based on high-level directives.

  5. Memory: Persist application state between runs of a chain.

With LangChain you'll be able to quickly build real world applications that directly sync up with Large Language Models, such as OpenAI's GPT-4 API!

Revolutionize your applications with the power of language models. Enroll in our LangChain Udemy course now and unlock limitless possibilities!

Bạn sẽ học được gì

Learn to use LangChain for Model Inputs and Outputs to easily switch out LLMs.

Discover how to perform data connections with Vector Databases such as ChromaDB with your LLMs and Langchain.

Understand how to utilize LangChain memory to keep track of User and AI conversations.

Use LangChain to build out custom agents to accomplish tasks with LLMs.

Yêu cầu

  • Python Programming Experience Required, recommended you also have familiarity with OpenAI

Nội dung khoá học

6 sections

Introduction

2 lectures
Introduction and Course Notebooks Download
00:43
Course Introduction and Overview
11:15

Models - Input and Outputs

14 lectures
Introduction to Models - Inputs and Outputs
04:27
OPTIONAL - OPENAI ACCOUNT SETUP
16:56
Using LLMs with LangChain
16:29
Chat Models with LangChain
16:26
Prompt Templates
17:50
Prompt and Models - Exercise
02:20
Prompt and Models - Exercise Solution
06:37
Few Shot Prompt Template
10:28
Parsing Output - Part One
14:30
Parsing Output - Part Two
12:05
Parsing Output - Part Three
08:10
Serialization -Saving and Loading Prompts
02:30
Models - Inputs and Outputs - Project Exercise
05:12
Models - Inputs and Outputs - Project Exercise Solution
19:46

Data Connections

13 lectures
Introduction to Data Connections
00:50
Document Loaders - Part One
13:24
Document Loaders - Integrations
08:57
Document Loading Exercise
03:32
Document Loading Exercise - Solution
07:15
Document Transformers
11:04
Text Embedding
07:36
Vector Store
20:27
Vector Store - Retrievers
02:37
MultiQuery Retrieval
13:36
Context Compression
10:36
Data Connections Exercise
01:35
Data Connections Exercise - Solutions
05:32

Chains

11 lectures
Introduction to LangChain Chains
01:42
LLMChain Object
05:32
SimpleSequentialChain
10:21
SequentialChain
12:15
LLMRouterChain
23:11
TransformChain
08:46
OpenAI Function Calling with LangChain
10:04
MathChain
04:30
Additional Chains - QA Documents
09:21
Chains - Exercise
02:09
Chains - Exercise Solution
07:21

Memory

5 lectures
Introduction to Memory
01:48
ChatMessageHistory Object
03:05
ConversationBufferMemory
07:58
ConversationBufferWindowMemory
04:11
ConversationSummaryMemory
03:39

Agents

5 lectures
Introduction to Agents
05:08
Agent Basics
11:49
Agent Tools
15:59
Custom Tools
13:42
Conversation Agents
04:06

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