chore: Add README.md files

README.md

@@ -0,0 +1,50 @@
+kvant AI Model as a Service & LangChain4j
+===============================================
+
+This demos helps you get started with the integration of AI in Java based applications using Quarkus and LangChain4j.
+Java is a widely used language established over the last 2 decades. There are a huge number of applications developed 
+using Java, including many deployed in enterprise environments.  This makes it appropriate to approach AI from 
+the Java world.
+
+# Goals
+You are going to play (and hopefully enjoy) with:
+* How to integrate LLMs (Language Models) in your Java application
+* How to build a chatbot using LangChain4j
+* How to configure and how to pass prompts to the LLM
+* How to build agentic systems
+* How to build simple and advanced RAG (Retrieval-Augmented Generation) patterns
+* How to deal with prompt injection: Guardrails
+* How to look in the room-machine: Observability
+
+# Requirements
+* Acquire kvant AI Model as a Service tokens. You can start with the FREE plans!!!  - https://console.kvant.cloud/en/products/categories/CLOUD_MAAS 
+* Java SDK (version 21.x.x, recommend GraalVM CE) - https://www.graalvm.org/downloads/#
+* Apache Maven JDK (version >= 3.9.x) - https://maven.apache.org/download.cgi
+* Git (version >= 2.34.x) - https://git-scm.com/downloads
+* Docker Desktop - https://www.docker.com/products/docker-desktop/ (version >= 4.35.x)
+* LLM Access tokens - They will be provided during the workshop
+* (Recommended) IntelliJ IDEA - https://www.jetbrains.com/idea/download/ (version >= 2024.2.5)
+
+
+# Run demos
+1) Clone the `ai-lc4j-workshop` repository - https://git.kvant.cloud/phoenix/ai-lc4j-workshop
+2) Move to your `ai-lc4j-workshop` folder
+3) Move to the corresponding `demo-0x` folder
+4) Execute `mvn clean quarkus:dev`
+5) Open your internet browser a point to `http:\\localhost:8080`
+
+**WARNING:** Be sure your Docker environment is running
+
+
+# Credits
+These demos are based on the existing LangChain4j examples and workshops. They have been adapted to use 
+Phoenix Technologies AG's kvant AI cloud platform and LLM's hosted on it.
+
+# Resources
+* Phoenix Technologies AG - https://phoenix-technologies.ch/en
+* Kvant AI Cloud - https://kvant.cloud/en/products/kvant-ai/ai-concierge
+* LangChain - https://www.langchain.com/
+* LangChain4j - https://docs.langchain4j.dev/intro/
+* LangChain4j Tutorials - https://docs.langchain4j.dev/category/tutorials
+* Quarkus LangChain4j - https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html
+* Quarkus - https://quarkus.io/