Responsive LLM Applications with Server-Sent Events

Name: Responsive LLM Applications with Server-Sent Events
Price: 9 USD
Availability: InStock

1h 18m 18s

English

Paid

November 23, 2024

Large Language Models (LLM) are transforming entire industries, but integrating them into user interfaces with real-time data streaming comes with unique challenges. In this course, you will learn to seamlessly embed LLM APIs into applications and create AI interfaces for streaming text and chats using TypeScript, React, and Python. We will develop a fully functional AI application step by step with high-quality code and flexible implementation.

As part of the course, you will create an LLM application that includes:

autocompletion scenario (translation from English to emoji),
chat,
retrieval augmented generation scenario,
AI agent usage scenarios (code execution, data analysis agent).

This application can become a starting point for most projects, saving a lot of time, and its flexibility allows for the addition of new tools as needed.

By the end of the course, you will have mastered the end-to-end implementation of a flexible and high-quality LLM application. You will also gain the knowledge and skills necessary to create complex solutions based on LLM.

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#	Title	Duration
1	Introduction to AI Product Development	03:48
2	Picking the stack - Navigating JavaScript and Python	06:10
3	Designing a Hybrid Web Application Architecture with JavaScript and Python	05:08
4	Streaming events with Server-Sent Events and WebSockets	06:31
5	Discovering the OpenAI Completion API	06:30
6	Handling Server-Sent Events with JavaScript	06:14
7	Building the useCompletion hook	07:01
8	Rendering Completion Output	01:26
9	Mocking Streams	03:29
10	Testing the useCompletion hook	03:11
11	Creating a FastAPI server	01:55
12	Exploring asynchronous programming in Python	03:42
13	Integrating Langchain with FastAPI for Asynchronous Streaming	04:34
14	Testing with PyTest and LangChain	01:02
15	Building the useChat hook	05:12
16	Building the User Interface	01:53
17	Discovering Retrieval Augmented Generation	03:19
18	Building a Semantic Search Engine with Chroma	03:37
19	Adding Retrieval-Augmented Generation to the chat	02:14
20	Final words	01:22