IndyDevDan | Llama-3 70b OMNI-complete: AUTO Improving AUTOcomplete Prompt for EVERYTHING (Groq) @indydevdan | Uploaded May 2024 | Updated October 2024, 2 hours ago.
Unlock the Power of LLM Autocompletes: All you need is this PROMPT & LLAMA 3.
Writing autocomplete code is a challenge. Then you have to write it again and again as the business logic changes. 🔥 In this video, I'll show you how to harness the power of LLM Llama 3-70b with Groq to create an OmniComplete – a self-improving, domain-agnostic autocomplete that works across ALL your tools and applications! 🤯
Imagine this: Your users start typing, and your OmniComplete instantly suggests relevant completions based on ALL previous user inputs AND your unique domain knowledge. 🤯 No more rigid dropdowns or limited suggestions – this is next-level LLM autocomplete!
Here's what you'll discover:
- The HUGE difference between traditional autocompletes and LLM-powered autocompletes – and why LLMs are GAME-CHANGING!
- How LLM AutoCompletes self-improve with every use – watch your autocomplete get smarter over time!
- Actionable insights from your users – uncover what your audience REALLY cares about, directly from their autocomplete interactions!
- A simple yet POWERFUL prompt-centered architecture – easily reuse your OmniComplete across different domains with minor prompt tweaks!
The complete codebase – get up and running with your OWN OmniComplete today!
Plus, we'll dive deep into:
- Prompt engineering for autocompletion – craft prompts that deliver spot-on suggestions.
- One-shot prompts – get accurate completions with just a single example.
- Building a prompt-centered architecture – design a system that revolves around your prompts for maximum flexibility and reusability.
- Prompt testing and validation – ensure your OmniComplete is always delivering high-quality results.
Ready to supercharge your user experience with AI-powered autocomplete? 🚀 Hit that like button, subscribe, and let's build the future of autocomplete together!
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What do you predict OpenAI will release today (May 12th, 2024) ? My Prediction ⬇️⬇️⬇️
Prediction #1: OpenAI will announce an on device compatible, GPT4 level model.
Prediction #2: OpenAI will announce apple as a partner and discuss plans to deploy ‘GPT4-mini’ on the iPhone.
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🔗 Resources
Codebase: github.com/disler/omni-complete
Learn about BAPs (Big Ass Prompts): youtu.be/JBgUmTUQx0I
Master Prompt Testing: youtu.be/sb9wSWeOPI4
Build better prompts: youtube.com/watch?v=wDxZhkQj27Y
Unocsss: https://unocss.dev/
📖 Chapters
00:00 Increase your earnings potential
00:38 Omnicomplete - the autocomplete for everything
01:16 LLM Autocompletes can self improve
02:00 Reveal Actionable Information from your users
03:20 Client - Server - Prompt Architecture
05:30 LLM Autocomplete DEMO
06:45 Autocomplete PROMPT
08:45 Auto Improve LLM / Self Improve LLM
10:25 Break down codebase
12:28 Direct prompt testing integration
14:10 Domain Knowledge Example
16:00 Interesting Use Case For LLMs in 2024, 2025
#promptengineering #llama3 #autocomplete
Unlock the Power of LLM Autocompletes: All you need is this PROMPT & LLAMA 3.
Writing autocomplete code is a challenge. Then you have to write it again and again as the business logic changes. 🔥 In this video, I'll show you how to harness the power of LLM Llama 3-70b with Groq to create an OmniComplete – a self-improving, domain-agnostic autocomplete that works across ALL your tools and applications! 🤯
Imagine this: Your users start typing, and your OmniComplete instantly suggests relevant completions based on ALL previous user inputs AND your unique domain knowledge. 🤯 No more rigid dropdowns or limited suggestions – this is next-level LLM autocomplete!
Here's what you'll discover:
- The HUGE difference between traditional autocompletes and LLM-powered autocompletes – and why LLMs are GAME-CHANGING!
- How LLM AutoCompletes self-improve with every use – watch your autocomplete get smarter over time!
- Actionable insights from your users – uncover what your audience REALLY cares about, directly from their autocomplete interactions!
- A simple yet POWERFUL prompt-centered architecture – easily reuse your OmniComplete across different domains with minor prompt tweaks!
The complete codebase – get up and running with your OWN OmniComplete today!
Plus, we'll dive deep into:
- Prompt engineering for autocompletion – craft prompts that deliver spot-on suggestions.
- One-shot prompts – get accurate completions with just a single example.
- Building a prompt-centered architecture – design a system that revolves around your prompts for maximum flexibility and reusability.
- Prompt testing and validation – ensure your OmniComplete is always delivering high-quality results.
Ready to supercharge your user experience with AI-powered autocomplete? 🚀 Hit that like button, subscribe, and let's build the future of autocomplete together!
---
What do you predict OpenAI will release today (May 12th, 2024) ? My Prediction ⬇️⬇️⬇️
Prediction #1: OpenAI will announce an on device compatible, GPT4 level model.
Prediction #2: OpenAI will announce apple as a partner and discuss plans to deploy ‘GPT4-mini’ on the iPhone.
---
🔗 Resources
Codebase: github.com/disler/omni-complete
Learn about BAPs (Big Ass Prompts): youtu.be/JBgUmTUQx0I
Master Prompt Testing: youtu.be/sb9wSWeOPI4
Build better prompts: youtube.com/watch?v=wDxZhkQj27Y
Unocsss: https://unocss.dev/
📖 Chapters
00:00 Increase your earnings potential
00:38 Omnicomplete - the autocomplete for everything
01:16 LLM Autocompletes can self improve
02:00 Reveal Actionable Information from your users
03:20 Client - Server - Prompt Architecture
05:30 LLM Autocomplete DEMO
06:45 Autocomplete PROMPT
08:45 Auto Improve LLM / Self Improve LLM
10:25 Break down codebase
12:28 Direct prompt testing integration
14:10 Domain Knowledge Example
16:00 Interesting Use Case For LLMs in 2024, 2025
#promptengineering #llama3 #autocomplete
