Prompt Engineering in Web Development | Using LangChain and Templates with OpenAI
49Continuing our series on building web applications that incorporate AI tooling, @heyAustinGil dives into the concept of prompt engineering. Austin demonstrates how you can use prompt templates to streamline and manage the use of AI prompts in web application development.
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Chapters:
0:00 Introduction
0:34 Modify the UI
4:25 Define Input Component Properties
8:05 Have Attribute Inherit to Text Area
11:28 Add aria-value
13:19 Create global.d.ts
15:50 Create Opponents Bot
16:30 Add in the AI and Context
23:40 Refine the Prompts
24:20 What Are Tokens?
26:30 Temperature Values
27:40 Refine Prompt
29:10 Introducing LangChain
35:00 Animating the Winning Result
40:20 Add RegEx to Format Winning Response
43:40 Insert Query Collector
45:30 Insert Rainbow Class
46:30 Install party-js
47:50 Test App
49:20 Conclusion
Follow along with Austin's GitHub → https://github.com/AustinGil/versus
Check out Qwik.js docs→ https://qwik.builder.io/docs/
See OpenAI Docs → https://platform.openai.com/overview
Learn more about Fetch API → https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API
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#AkamaiDeveloper #openai #qwikjs #nodejs
Product: Akamai Developer, OpenAI, Qwik.js, ChatGPT; @heyAustinGil