Merge pull request #21 from BillFarber/main

Various documentation updates

Author: BillFarber

docs/embedding.md

@@ -29,6 +29,13 @@ langchain4j to generate an embedding for the chunk of text and add it to each ch
 
 ## Adding embedding to documents
 
+To use this example, you'll need to be in this example directory. If you are not already in this example directory, run
+this command:
+
+```
+cd embedding-langchain-java
+```
+
 To try the embedding example, run the following Gradle task:
 
     ../gradlew addEmbeddings

docs/rag-examples/rag-java.md

@@ -20,7 +20,13 @@ directory demonstrate three different kinds of retrievers that you can consider
 The only system requirement for running these examples is Java 8 or higher. You can run the examples via an IDE such as
 Visual Code or IntelliJ. You can also use [Gradle](https://gradle.org/) to run the examples, but you do not
 need Gradle installed - this repository uses the [Gradle wrapper](https://docs.gradle.org/current/userguide/gradle_wrapper.html)
-to download an appropriate version of Gradle.
+to download an appropriate version of Gradle. To start using these examples, you'll need to be in this example
+directory. If you are not already in this example directory, run this command:
+
+```
+cd rag-langchain-java
+```
+
 
 ## RAG with a simple word query
 

docs/rag-examples/rag-javascript.md

@@ -37,6 +37,7 @@ AZURE_OPENAI_API_INSTANCE_NAME=<The host name of your Azure OpenAI endpoint>
 Once Node and npm are installed, and your environment is configured, you can run the examples via an IDE such as Visual
 Code or IntelliJ. To try these examples, you should first use npm to install the required Node modules:
 ```
+cd rag-langchain-js
 npm install
 ```
 

docs/splitting.md

@@ -41,6 +41,13 @@ and leaving the original text documents untouched.
 You also need Java 8 in order to run these examples, which is the same version of Java needed by the aforementioned
 setup instructions.
 
+Finally, to start using these examples, you'll need to be in this example  directory. If you are not already in this
+example directory, run this command:
+
+```
+cd splitting-langchain-java
+```
+
 ## Splitting chunks to separate documents
 
 In this approach, the [langchain4j document splitter API](https://docs.langchain4j.dev/tutorials/rag#document-splitter)

setup/docker-compose-12.yml

@@ -1,4 +1,3 @@
-version: '3.8'
 name: marklogic-12-ai-examples
 
 services:

setup/docker-compose.yml

@@ -1,4 +1,3 @@
-version: '3.8'
 name: marklogic-ai-examples
 
 services: