Newline - Responsive LLM Applications with Server - Sent Events

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Free Download Newline - Responsive LLM Applications with Server-Sent Events
Released 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 20 Lessons ( 1h 18m ) | Size: 372 MB
Dive into Retrieval Augmented Generation and Autonomous Agents with LangChain, Chroma and FastAPI

Large Language Models are reshaping industries, yet integrating them into real-time streaming UIs presents unique challenges. In this course we will learn how to seamlessly integrate LLM APIs into applications and build AI-powered streaming text and chat UIs with TypeScript, React, and Python. Step-by-step, we will build a full-stack AI application with quality code and very flexible implementation.
The LLM application in this course includes
Completion Use-Case (english to emojis)
Chat
Retrieval Augmented Generation use-case
AI Agent Use-Cases (code execution, data-Analyste agent)
This app can be used as a starting point in most projects, saving a huge amount of time, and its flexibilty allows new tools to be added as needed.
At the end of this course, you will have mastered end-to-end implementation of a flexible and high-quality LLM application. This course will also equip you with the knowledge and skills necessary to create sophisticated LLM solutions of your own.
What you will learn
How to design systems for AI applications
How to stream the answer of a Large Language Model
Differences between Server-Sent Events and WebSockets
Importance of real-time for GenAI UI
How asynchronous programming in Python works
How to integrate LangChain with FastAPI
What problems Retrieval Augmented Generation can solve
How to create an AI agent
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[0dayddl]

478.16 MB | 00:07:00 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

1 Introduction to AI Product Development (7.26 MB)
10 Testing the useCompletion hook (7.22 MB)
11 Creating a FastAPI server (4.03 MB)
12 Exploring asynchronous programming in Python (6.43 MB)
13 Integrating Langchain with FastAPI for Asynchronous Streaming (8.28 MB)
14 Testing with PyTest and LangChain (1.72 MB)
15 Building the useChat hook (13.76 MB)
16 Building the User Interface (5.96 MB)
17 Discovering Retrieval Augmented Generation (6.59 MB)
18 Building a Semantic Search Engine with Chroma (9.75 MB)
19 Adding Retrieval-Augmented Generation to the chat (5.04 MB)
2 Picking the stack - Navigating JavaScript and Python (14.25 MB)
20 Final words (4.16 MB)
3 Designing a Hybrid Web Application Architecture with JavaScript and Python (10.05 MB)
4 Streaming events with Server-Sent Events and WebSockets (14.13 MB)
5 Discovering the OpenAI Completion API (12.71 MB)
6 Handling Server-Sent Events with JavaScript (14.2 MB)
7 Building the useCompletion hook (14.47 MB)
8 Rendering Completion Output (3.11 MB)
9 Mocking Streams (7.94 MB)
utils (169 B)
setup (362 B)
vite-env d (38 B)
vite config (544 B)
utils (169 B)
setup (362 B)
vite-env d (38 B)
vite config (544 B)
utils (169 B)
setup (362 B)
vite-env d (38 B)
vite config (544 B)
utils (169 B)
setup (362 B)
vite-env d (38 B)
vite config (544 B)
utils (169 B)
setup (362 B)
vite-env d (38 B)
vite config (544 B)

]
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[0dayddl]

478.16 MB | 7min 0s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

FileName :1 Introduction to AI Product Development.mp4 | Size: (7.26 MB)
FileName :10 Testing the useCompletion hook.mp4 | Size: (7.22 MB)
FileName :11 Creating a FastAPI server.mp4 | Size: (4.03 MB)
FileName :12 Exploring asynchronous programming in Python.mp4 | Size: (6.43 MB)
FileName :13 Integrating Langchain with FastAPI for Asynchronous Streaming.mp4 | Size: (8.28 MB)
FileName :14 Testing with PyTest and LangChain.mp4 | Size: (1.72 MB)
FileName :15 Building the useChat hook.mp4 | Size: (13.76 MB)
FileName :16 Building the User Interface.mp4 | Size: (5.96 MB)
FileName :17 Discovering Retrieval Augmented Generation.mp4 | Size: (6.59 MB)
FileName :18 Building a Semantic Search Engine with Chroma.mp4 | Size: (9.75 MB)
FileName :19 Adding Retrieval-Augmented Generation to the chat.mp4 | Size: (5.04 MB)
FileName :2 Picking the stack - Navigating JavaScript and Python.mp4 | Size: (14.25 MB)
FileName :20 Final words.mp4 | Size: (4.16 MB)
FileName :3 Designing a Hybrid Web Application Architecture with JavaScript and Python.mp4 | Size: (10.05 MB)
FileName :4 Streaming events with Server-Sent Events and WebSockets.mp4 | Size: (14.13 MB)
FileName :5 Discovering the OpenAI Completion API.mp4 | Size: (12.71 MB)
FileName :6 Handling Server-Sent Events with JavaScript.mp4 | Size: (14.2 MB)
FileName :7 Building the useCompletion hook.mp4 | Size: (14.47 MB)
FileName :8 Rendering Completion Output.mp4 | Size: (3.11 MB)
FileName :9 Mocking Streams.mp4 | Size: (7.94 MB)
FileName :utils.ts | Size: (169 B)
FileName :setup.ts | Size: (362 B)
FileName :vite-env d.ts | Size: (38 B)
FileName :vite config.ts | Size: (544 B)
FileName :utils.ts | Size: (169 B)
FileName :setup.ts | Size: (362 B)
FileName :vite-env d.ts | Size: (38 B)
FileName :vite config.ts | Size: (544 B)
FileName :utils.ts | Size: (169 B)
FileName :setup.ts | Size: (362 B)
FileName :vite-env d.ts | Size: (38 B)
FileName :vite config.ts | Size: (544 B)
FileName :utils.ts | Size: (169 B)
FileName :setup.ts | Size: (362 B)
FileName :vite-env d.ts | Size: (38 B)
FileName :vite config.ts | Size: (544 B)
FileName :utils.ts | Size: (169 B)
FileName :setup.ts | Size: (362 B)
FileName :vite-env d.ts | Size: (38 B)
FileName :vite config.ts | Size: (544 B)

]
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