From 269c0cf6806f055284219a851c160529351f0e20 Mon Sep 17 00:00:00 2001
From: Pawel Podhajski <106311100+pw-ppodhajski@users.noreply.github.com>
Date: Tue, 19 Nov 2024 13:42:59 +0100
Subject: [PATCH] llm-app: readme shields (#7697)

GitOrigin-RevId: 2b1b2216ace34f7f00b10d3f69c3efc9cfc0342a
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 README.md | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 94efbe6..762cc2d 100644
--- a/README.md
+++ b/README.md
@@ -2,14 +2,10 @@
 
 # LLM App
 
-[![LICENSE](https://img.shields.io/github/license/pathwaycom/llm-app?style=plastic)](https://github.com/pathwaycom/llm-app/blob/main/LICENSE)
-[![Contributors](https://img.shields.io/github/contributors/pathwaycom/llm-app?style=plastic)](https://github.com/pathwaycom/llm-app/graphs/contributors)
-
-<!--- [![Contributors](https://img.shields.io/github/actions/workflow/status/pathwaycom/llm-app/install_package.yml?style=plastic)](https://github.com/pathwaycom/llm-app/actions/workflows/install_package.yml) --->
-![Linux](https://img.shields.io/badge/OS-Linux-green)
-![macOS](https://img.shields.io/badge/OS-macOS-green)
-[![chat on Discord](https://img.shields.io/discord/1042405378304004156?logo=discord)](https://discord.gg/pathway)
-[![follow on Twitter](https://img.shields.io/twitter/follow/pathway_com?style=social&logo=twitter)](https://twitter.com/intent/follow?screen_name=pathway_com)
+![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black)
+![macOS](https://img.shields.io/badge/mac%20os-000000?style=for-the-badge&logo=apple&logoColor=white)
+[![chat on Discord](https://img.shields.io/badge/Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/pathway)
+[![follow on X](  https://img.shields.io/badge/X-000000?style=for-the-badge&logo=x&logoColor=white)](https://x.com/intent/follow?screen_name=pathway_com)
 </div>
 
 Pathway's **LLM (Large Language Model) App Templates** allow you to quickly put in production AI applications which offer **high-accuracy RAG and AI enterprise search at scale** using the most **up-to-date knowledge** available in your data sources. You can test them on your own machine and deploy on-cloud (GCP, AWS, Azure, Render,...) or on-premises.