ChatGPT and LangChain - The Complete Developer's Masterclass

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Free Download ChatGPT and LangChain - The Complete Developer's Masterclass
Last updated: 12/2024
Created by: Stephen Grider
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English + subtitle | Duration: 137 Lectures ( 12h 11m ) | Size: 3.3 GB

Intensive masterclass on ChatGPT, LangChain, and Python. Make production-ready apps focused on real-world AI integration
What you'll learn
Integrate ChatGPT into production-style apps with LangChain
Use LangChain components to build complex text generation pipelines
Enhance ChatGPT's output by automatically integrating user feedback
Teach ChatGPT new facts through Retrieval Augmented Generation
Extend LangChain to implement server-to-browser text streaming
Use OpenAI Plugins to add new capabilities to ChatGPT, such as database access and code execution
Understand every line of code we write so you can use these exact same techniques on your own projects
Build your own chat-with-a-PDF web application, complete with document upload and authentication
See how users interact with your chat features using observability and tracing
Requirements
Basic programming experience with Python
Description
You've found the most advanced, most complete, and most intensive masterclass online for learning how to integrate LangChain and ChatGPT into production-ready applications!Thousands of engineers have learned how to build amazing applications using ChatGPT, and you can too. This course uses a time-tested, battle-proven method to make sure you understand exactly how ChatGPT works, and is the perfect pathway to help you get a new job as a software engineer working on AI-enabled apps.The difference between this course and all the others: you will go far beyond the basics of simple ChatGPT prompts, and understand how companies are integrating text generation into their apps today.___________ChatGPT is being used across industries to enhance applications with text generation. But with this new feature comes many challenges: Building complex text generation pipelines that incorporate outside informationCreating reusable configuration components that can be reassembled in different waysApplying user feedback (like upvotes/downvotes) to enhance ChatGPT's outputWiring in observability and tracing to see how users are interacting with your AIGenerate text performantly using distributed processingThis course will walk you through production-ready, repeatable techniques for addressing each of these challenges and many more.What will you build?This course focuses on creating a series of different projects of increasing complexity. You'll start from the very basics, understanding how to access ChatGPT 4 programatically. From there, we will quickly increase in complexity, building more complex projects with many more features. By the end, you will make a fully-featured web app that implements a "Chat-with-a-PDF" feature. Note: no previous web development experience is required.Here's a partial list of some of the topics you'll cover:Understand how complex text-generation pipelines workWrite reusable code using chains provided by LangChainConnect chains together in different ways to dramatically change your apps behavior with easeStore, retrieve, and summarize chat messages using conversational memoryImplement semantic search for Retrieval-Augmented Generation using embeddingsGenerate and store embeddings in vector databases like ChromaDB and PineconeUse retrievers to refine, reduce, and rank context documents, teaching ChatGPT new informationCreate agents to automatically accomplish tasks for you using goals you defineWrite tools and plugins to allow ChatGPT to access the outside worldMaintain a consistent focus on performance through distributed processing using Celery and RedisExtend LangChain to implement server-to-browser text streamingImprove ChatGPT's output quality through user-generated feedback mechanismsGet visibility into how users interact with your text generation features by using tracingThere are a ton of courses that show how to use ChatGPT at a very basic level. This is one of the very few courses online that goes far beyond the basics to teach you advanced techniques that top companies are using today. I have a passion for teaching topics the right way - the way that you'll actually use technology in the real world. Sign up today and join me!
Who this course is for
Software engineers looking to add AI into their apps
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[0dayddl]

Chatgpt And Langchain: The Complete Developer'S Masterclass
Last updated 1/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 3.20 GB | Duration: 12h 11m​

Intensive masterclass on ChatGPT, LangChain, and Python. Make production-ready apps focused on real-world AI integration

What you'll learn
Integrate ChatGPT into production-style apps with LangChain
Use LangChain components to build complex text generation pipelines
Enhance ChatGPT's output by automatically integrating user feedback
Teach ChatGPT new facts through Retrieval Augmented Generation
Extend LangChain to implement server-to-browser text streaming
Use OpenAI Plugins to add new capabilities to ChatGPT, such as database access and code execution
Understand every line of code we write so you can use these exact same techniques on your own projects
Build your own chat-with-a-PDF web application, complete with document upload and authentication
See how users interact with your chat features using observability and tracing

Requirements
Basic programming experience with Python

Description
You've found the most advanced, most complete, and most intensive masterclass online for learning how to integrate LangChain and ChatGPT into production-ready applications!Thousands of engineers have learned how to build amazing applications using ChatGPT, and you can too. This course uses a time-tested, battle-proven method to make sure you understand exactly how ChatGPT works, and is the perfect pathway to help you get a new job as a software engineer working on AI-enabled apps.The difference between this course and all the others: you will go far beyond the basics of simple ChatGPT prompts, and understand how companies are integrating text generation into their apps today.___________ChatGPT is being used across industries to enhance applications with text generation. But with this new feature comes many challenges: Building complex text generation pipelines that incorporate outside informationCreating reusable configuration components that can be reassembled in different waysApplying user feedback (like upvotes/downvotes) to enhance ChatGPT's outputWiring in observability and tracing to see how users are interacting with your AIGenerate text performantly using distributed processingThis course will walk you through production-ready, repeatable techniques for addressing each of these challenges and many more.What will you build?This course focuses on creating a series of different projects of increasing complexity. You'll start from the very basics, understanding how to access ChatGPT 4 programatically. From there, we will quickly increase in complexity, building more complex projects with many more features. By the end, you will make a fully-featured web app that implements a "Chat-with-a-PDF" feature. Note: no previous web development experience is required.Here's a partial list of some of the topics you'll cover:Understand how complex text-generation pipelines workWrite reusable code using chains provided by LangChainConnect chains together in different ways to dramatically change your apps behavior with easeStore, retrieve, and summarize chat messages using conversational memoryImplement semantic search for Retrieval-Augmented Generation using embeddingsGenerate and store embeddings in vector databases like ChromaDB and PineconeUse retrievers to refine, reduce, and rank context documents, teaching ChatGPT new informationCreate agents to automatically accomplish tasks for you using goals you defineWrite tools and plugins to allow ChatGPT to access the outside worldMaintain a consistent focus on performance through distributed processing using Celery and RedisExtend LangChain to implement server-to-browser text streamingImprove ChatGPT's output quality through user-generated feedback mechanismsGet visibility into how users interact with your text generation features by using tracingThere are a ton of courses that show how to use ChatGPT at a very basic level. This is one of the very few courses online that goes far beyond the basics to teach you advanced techniques that top companies are using today. I have a passion for teaching topics the right way - the way that you'll actually use technology in the real world. Sign up today and join me!

Who this course is for:
Software engineers looking to add AI into their apps

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[0dayddl]

4.41 GB | 28min 8s | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

FileName :1 How to Get Help.mp4 | Size: (1.1 MB)
FileName :2 What is LangChain.mp4 | Size: (17.99 MB)
FileName :3 How a Typical AI-Enabled App Works.mp4 | Size: (71.82 MB)
FileName :4 Here It Is, This is Why We Use LangChain.mp4 | Size: (32.79 MB)
FileName :2 Project Overview and Setup.mp4 | Size: (7.58 MB)
FileName :4 Using LangChain the Simple Way.mp4 | Size: (9.56 MB)
FileName :5 Introducing Chains.mp4 | Size: (52.32 MB)
FileName :6 Adding a Chain.mp4 | Size: (25.75 MB)
FileName :8 Parsing Command Line Arguments.mp4 | Size: (7.89 MB)
FileName :9 Securing the API Key.mp4 | Size: (15.58 MB)
FileName :10 Connecting Chains Together.mp4 | Size: (9.63 MB)
FileName :11 Chains in Series with SequentialChain.mp4 | Size: (50.15 MB)
FileName :2 App Overview.mp4 | Size: (7.76 MB)
FileName :3 Receiving User Input.mp4 | Size: (4.37 MB)
FileName :4 Chat vs Completion Style Models.mp4 | Size: (30.62 MB)
FileName :5 Representing Messages with ChatPromptTemplates.mp4 | Size: (15.87 MB)
FileName :6 Implementing a Chat Chain.mp4 | Size: (18.71 MB)
FileName :7 Understanding Memory.mp4 | Size: (35.6 MB)
FileName :8 Using ChatBufferMemory to Store Conversations.mp4 | Size: (31.75 MB)
FileName :9 Saving and Extending Conversations.mp4 | Size: (34.75 MB)
FileName :10 Summarizations Conversation Summary Memory.mp4 | Size: (59.61 MB)
FileName :1 Project Overview.mp4 | Size: (12.62 MB)
FileName :4 Project Setup.mp4 | Size: (4.16 MB)
FileName :5 Loading Files with Document Loaders.mp4 | Size: (37.78 MB)
FileName :6 Search Criteria.mp4 | Size: (19.1 MB)
FileName :7 Introducing Embeddings.mp4 | Size: (43.66 MB)
FileName :8 The Entire Embedding Flow.mp4 | Size: (13.88 MB)
FileName :9 Chunking Text.mp4 | Size: (81.25 MB)
FileName :10 Generating Embeddings.mp4 | Size: (22.94 MB)
FileName :1 Introducing ChromaDB.mp4 | Size: (71.94 MB)
FileName :2 Building a Retrieval Chain.mp4 | Size: (67.05 MB)
FileName :3 What is a Retriever.mp4 | Size: (17.9 MB)
FileName :4 Optional Understanding Refine, MapReduce, and MapRerank.mp4 | Size: (315.8 MB)
FileName :5 Removing Duplicate Documents.mp4 | Size: (40.12 MB)
FileName :6 Creating a Custom Retriever.mp4 | Size: (84.83 MB)
FileName :7 Custom Retriever in Action.mp4 | Size: (74 MB)
FileName :9 Visualizing Embeddings.mp4 | Size: (30.35 MB)
FileName :2 App Overview.mp4 | Size: (8.85 MB)
FileName :3 Understanding Tools.mp4 | Size: (36.99 MB)
FileName :4 Understanding ChatGPT Functions.mp4 | Size: (38.08 MB)
FileName :6 Defining a Tool.mp4 | Size: (22.84 MB)
FileName :7 Defining an Agent and AgentExecutor.mp4 | Size: (17.16 MB)
FileName :8 Understanding Agents and AgentExecutors.mp4 | Size: (44.44 MB)
FileName :9 Shortcomings in ChatGPT's Assumptions.mp4 | Size: (29.11 MB)
FileName :10 Recovering from Errors in Tools.mp4 | Size: (21.83 MB)
FileName :11 Adding Table Context.mp4 | Size: (70.1 MB)
FileName :12 Adding a Table Description Tool.mp4 | Size: (34.19 MB)
FileName :13 Being Direct with System Messages.mp4 | Size: (11.55 MB)
FileName :14 Adding Better Descriptions for Tool Arguments.mp4 | Size: (71.77 MB)
FileName :15 Tools with Multiple Arguments.mp4 | Size: (68.36 MB)
FileName :16 Memory vs Agent Scratchpad.mp4 | Size: (64.51 MB)
FileName :17 Preserving Messages with Agent Executor.mp4 | Size: (25.64 MB)
FileName :18 Understanding Callbacks.mp4 | Size: (34.54 MB)
FileName :19 Implementing a Basic Callback Handler.mp4 | Size: (57.87 MB)
FileName :20 More Handler Implementaion.mp4 | Size: (105.53 MB)
FileName :1 App Overview.mp4 | Size: (9.02 MB)
FileName :2 Taking a Look at Mockups.mp4 | Size: (16.31 MB)
FileName :4 Boilerplate Setup.mp4 | Size: (27.4 MB)
FileName :5 How This App is Designed.mp4 | Size: (42.41 MB)
FileName :6 Outlining the First Feature.mp4 | Size: (17.91 MB)
FileName :7 Loading and Splitting From a PDF.mp4 | Size: (24.78 MB)
FileName :10 Testing the PDF Upload.mp4 | Size: (19.21 MB)
FileName :12 Introducing Pinecone.mp4 | Size: (33.85 MB)
FileName :14 Initializing the Pinecone Client.mp4 | Size: (15.71 MB)
FileName :15 Adding Documents to the Vector Store.mp4 | Size: (27.41 MB)
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FileName :4 Building the Retriever.mp4 | Size: (30.77 MB)
FileName :5 Custom History Objects.mp4 | Size: (18.53 MB)
FileName :6 Building a Custom SQL History.mp4 | Size: (29.26 MB)
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FileName :4 Chains Don't Want to Stream.mp4 | Size: (28.03 MB)
FileName :5 Receiving Chunks with a Callback.mp4 | Size: (18.07 MB)
FileName :6 Extending a LLM Chain.mp4 | Size: (40.69 MB)
FileName :7 Adding a Queue for Communication.mp4 | Size: (50.59 MB)
FileName :8 The Chain Really Wants to Wait.mp4 | Size: (11.91 MB)
FileName :9 Solving the Slow Chain.mp4 | Size: (7.06 MB)
FileName :10 It Works!.mp4 | Size: (18.45 MB)
FileName :11 Ending the Loop.mp4 | Size: (19.21 MB)
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FileName :3 Integrating the Streaming Code.mp4 | Size: (57.1 MB)
FileName :4 Testing the Streaming Setup.mp4 | Size: (58.38 MB)
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FileName :7 Collecting User Feedback.mp4 | Size: (19.48 MB)
FileName :8 Redis Connection Setup.mp4 | Size: (30.59 MB)
FileName :9 Storing Votes in Redis.mp4 | Size: (36.81 MB)
FileName :10 Weighted Randomness.mp4 | Size: (31.35 MB)
FileName :11 Extracting Scores.mp4 | Size: (45.64 MB)
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FileName :8 Understanding the Trace.mp4 | Size: (35.72 MB)
FileName :9 Automatic Trace Creation.mp4 | Size: (102.18 MB)
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FileName :+page.ts | Size: (176 B)
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FileName :store.ts | Size: (176 B)
FileName :stream.ts | Size: (176 B)
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]
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