-
Урок 1.
00:01:15
How to Get Help
-
Урок 2.
00:03:58
What is LangChain?
-
Урок 3.
00:10:00
How a Typical AI-Enabled App Works
-
Урок 4.
00:05:29
Here It Is, This is Why We Use LangChain
-
Урок 5.
00:03:21
Project Overview and Setup
-
Урок 6.
00:02:56
Using LangChain the Simple Way
-
Урок 7.
00:10:09
Introducing Chains
-
Урок 8.
00:04:11
Adding a Chain
-
Урок 9.
00:02:30
Parsing Command Line Arguments
-
Урок 10.
00:04:45
Securing the API Key
-
Урок 11.
00:02:57
Connecting Chains Together
-
Урок 12.
00:07:01
Chains in Series with SequentialChain
-
Урок 13.
00:02:12
App Overview
-
Урок 14.
00:02:00
Receiving User Input
-
Урок 15.
00:10:10
Chat vs Completion Style Models
-
Урок 16.
00:06:02
Representing Messages with ChatPromptTemplates
-
Урок 17.
00:04:38
Implementing a Chat Chain
-
Урок 18.
00:09:26
Understanding Memory
-
Урок 19.
00:07:28
Using ChatBufferMemory to Store Conversations
-
Урок 20.
00:04:44
Saving and Extending Conversations
-
Урок 21.
00:09:43
Summarizations Conversation Summary Memory
-
Урок 22.
00:03:29
Project Overview
-
Урок 23.
00:01:54
Project Setup
-
Урок 24.
00:06:15
Loading Files with Document Loaders
-
Урок 25.
00:04:37
Search Criteria
-
Урок 26.
00:10:32
Introducing Embeddings
-
Урок 27.
00:02:10
The Entire Embedding Flow
-
Урок 28.
00:07:16
Chunking Text
-
Урок 29.
00:04:22
Generating Embeddings
-
Урок 30.
00:10:02
Introducing ChromaDB
-
Урок 31.
00:10:33
Building a Retrieval Chain
-
Урок 32.
00:05:21
What is a Retriever?
-
Урок 33.
00:28:09
[Optional] Understanding Refine, MapReduce, and MapRerank
-
Урок 34.
00:07:54
Removing Duplicate Documents
-
Урок 35.
00:11:13
Creating a Custom Retriever
-
Урок 36.
00:06:02
Custom Retriever in Action
-
Урок 37.
00:04:35
Visualizing Embeddings
-
Урок 38.
00:04:14
App Overview
-
Урок 39.
00:08:13
Understanding Tools
-
Урок 40.
00:10:55
Understanding ChatGPT Functions
-
Урок 41.
00:06:36
Defining a Tool
-
Урок 42.
00:05:52
Defining an Agent and AgentExecutor
-
Урок 43.
00:09:14
Understanding Agents and AgentExecutors
-
Урок 44.
00:04:45
Shortcomings in ChatGPT's Assumptions
-
Урок 45.
00:04:28
Recovering from Errors in Tools
-
Урок 46.
00:09:29
Adding Table Context
-
Урок 47.
00:05:21
Adding a Table Description Tool
-
Урок 48.
00:02:52
Being Direct with System Messages
-
Урок 49.
00:06:59
Adding Better Descriptions for Tool Arguments
-
Урок 50.
00:07:13
Tools with Multiple Arguments
-
Урок 51.
00:09:25
Memory vs Agent Scratchpad
-
Урок 52.
00:02:38
Preserving Messages with Agent Executor
-
Урок 53.
00:04:47
Understanding Callbacks
-
Урок 54.
00:05:04
Implementing a Basic Callback Handler
-
Урок 55.
00:11:23
More Handler Implementaion
-
Урок 56.
00:02:27
App Overview
-
Урок 57.
00:03:24
Taking a Look at Mockups
-
Урок 58.
00:04:44
Boilerplate Setup
-
Урок 59.
00:06:10
How This App is Designed
-
Урок 60.
00:04:29
Outlining the First Feature
-
Урок 61.
00:03:41
Loading and Splitting From a PDF
-
Урок 62.
00:02:17
Testing the PDF Upload
-
Урок 63.
00:06:31
Introducing Pinecone
-
Урок 64.
00:05:54
Initializing the Pinecone Client
-
Урок 65.
00:03:52
Adding Documents to the Vector Store
-
Урок 66.
00:06:11
Why is Processing Taking Forever?
-
Урок 67.
00:07:45
Introducing Background Jobs
-
Урок 68.
00:01:56
Redis Setup
-
Урок 69.
00:04:09
Adding in the Worker
-
Урок 70.
00:04:04
Queuing Up Jobs
-
Урок 71.
00:07:08
Updating Document Metadata
-
Урок 72.
00:07:59
Understanding the Apps Requirements
-
Урок 73.
00:12:09
Persistent Message Storage
-
Урок 74.
00:10:36
Introducing the Conversational Retrieval Chain
-
Урок 75.
00:04:57
Building the Retriever
-
Урок 76.
00:04:44
Custom History Objects
-
Урок 77.
00:08:53
Building a Custom SQL History
-
Урок 78.
00:04:59
Testing the Chain
-
Урок 79.
00:03:58
Streaming Text Generation
-
Урок 80.
00:05:12
Creating a Working Playground
-
Урок 81.
00:09:11
Experimenting with a Streaming Language Model
-
Урок 82.
00:06:53
Chains Don't Want to Stream
-
Урок 83.
00:04:34
Receiving Chunks with a Callback
-
Урок 84.
00:08:50
Extending a LLM Chain
-
Урок 85.
00:07:28
Adding a Queue for Communication
-
Урок 86.
00:04:14
The Chain Really Wants to Wait
-
Урок 87.
00:02:45
Solving the Slow Chain
-
Урок 88.
00:02:41
It Works!
-
Урок 89.
00:04:59
Ending the Loop
-
Урок 90.
00:03:37
Isolating the Queue and Handler
-
Урок 91.
00:04:47
Using a Mixin Approach
-
Урок 92.
00:06:59
Integrating the Streaming Code
-
Урок 93.
00:07:07
Testing the Streaming Setup
-
Урок 94.
00:04:38
Here's the Issue
-
Урок 95.
00:07:50
Isolating the Handler
-
Урок 96.
00:10:34
Streaming Complete!
-
Урок 97.
00:04:17
Random Component Parts
-
Урок 98.
00:05:19
Component Part Flow
-
Урок 99.
00:06:14
Partial KWArg Application
-
Урок 100.
00:04:35
Building Component Maps
-
Урок 101.
00:08:02
Randomly Picking a Component
-
Урок 102.
00:10:09
Generalizing Component Picking
-
Урок 103.
00:05:16
Collecting User Feedback
-
Урок 104.
00:06:52
Redis Connection Setup
-
Урок 105.
00:07:35
Storing Votes in Redis
-
Урок 106.
00:03:03
Weighted Randomness
-
Урок 107.
00:06:31
Extracting Scores
-
Урок 108.
00:07:33
Calculating the Average Score
-
Урок 109.
00:04:38
Selecting Components By Score
-
Урок 110.
00:02:45
Adding Score Observability
-
Урок 111.
00:03:50
Building the Score Aggregate
-
Урок 112.
00:02:37
Adding Another Form of Memory
-
Урок 113.
00:06:10
Window Memory Implementation
-
Урок 114.
00:04:32
Text Generation Tracing
-
Урок 115.
00:03:28
Langfuse Signup
-
Урок 116.
00:06:50
Adding in Tracing
-
Урок 117.
00:05:27
Understanding the Trace
-
Урок 118.
00:10:32
Automatic Trace Creation