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