Content & Writing · GitHub ·46 ★

pace-genai-demos

This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and local

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Details

Author
aws-samples
Category
Content & Writing
Platform
GitHub
Framework
langchain
Language
typescript
Stars
46
First indexed
2026-05-15
Last active
2024-05-19
Directory sync
2026-05-15
@aws-samples

Overview

This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and local

Quick start

git

git clone https://github.com/aws-samples/pace-genai-demos

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What pace-genai-demos can do

localihrcontentimageembedding
  • Locali — locali task automation.
  • Hr — Handles people operations such as hiring and policy Q&A.
  • Content — content task automation.
  • Image — Generates or edits images from natural-language prompts.
  • Embedding — Computes vector embeddings for semantic search.

Frequently asked questions

What is pace-genai-demos?
This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and local
How do I install pace-genai-demos?
Use git: `git clone https://github.com/aws-samples/pace-genai-demos`. Full setup details on the source page linked above.
Is pace-genai-demos open source?
pace-genai-demos is published on GitHub.
What are alternatives to pace-genai-demos?
Comparable agents include PaddleOCR, telegraf, ai-notes. Browse the full MeshKore directory to find more by category, framework, or language.

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