Added skeleton structure for docs (langchain4j#458)

Hi @LizeRaes,

In reference to
[this](langchain4j#429 (reply in thread)),
I've added the skeleton structure for documentation under the `docs`
directory.

I've also updated the `README.md` under the `docs` directory to help in
setting up and running the docs.

It's straightforward to set up and run the docs locally to get a feel
for its appearance.

I've also attached a few screenshots of the pages to get a quick look at
the appearance.

Please have a look and do let me know what you think. Thanks!


**_Sample Images:_**

- Docs: Home/Landing Page

<img width="1792" alt="1"
src="https://github.com/langchain4j/langchain4j/assets/1876165/c2ff1bf3-a412-4d86-be0d-9937936ec533">

- Docs: Inner Page Sample

<img width="1792" alt="2"
src="https://github.com/langchain4j/langchain4j/assets/1876165/9166df41-f16a-4bff-a3ca-145364be475c">

- Docs: Sample Blog

<img width="1792" alt="3"
src="https://github.com/langchain4j/langchain4j/assets/1876165/44dc1e7c-f669-4806-acfe-8fc2c3d2f59b">

Co-authored-by: Amith Koujalgi <[email protected]>

docs/.gitignore

@@ -0,0 +1,20 @@
+# Dependencies
+/node_modules
+
+# Production
+/build
+
+# Generated files
+.docusaurus
+.cache-loader
+
+# Misc
+.DS_Store
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*

docs/Makefile

@@ -0,0 +1,7 @@
+build:
+	npm ci; \
+	npm run build
+
+dev:
+	npm ci; \
+	npm run start

docs/README.md

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+## LangChain4j Documentation
+
+### Table of Contents
+
+- [Prerequisites](#prerequisites)
+- [Installation](#installation)
+
+This is built using [Docusaurus](https://docusaurus.io/), a modern static docs/website generator.
+
+### Prerequisites
+
+- [Node.JS](https://nodejs.org/en/download) (20+)
+
+### Installation
+
+This command installs all the Node dependencies.
+
+```bash
+npm ci
+```
+
+### Build
+
+This command builds the deployable static artifacts (i.e., html, js, css, etc) under the `build` directory. This static content can then be deployed to `GitHub pages` or `Vercel`, etc.
+
+```
+npm run build
+```
+
+### Local Development
+
+This command starts a local development server and opens up a browser window. Most changes are reflected live without
+having to restart the server.
+
+```
+npm run start
+```

docs/babel.config.js

@@ -0,0 +1,3 @@
+module.exports = {
+  presets: [require.resolve('@docusaurus/core/lib/babel/preset')],
+};

docs/blog/2023-01-01-welcome/index.md

@@ -0,0 +1,9 @@
+---
+slug: welcome
+title: Welcome
+authors: [ lanchain4j ]
+tags: [ Java, AI, LLM, GenAI, GenerativeAI, LangChain4j, LangChain, OpenSource, Developers
+]
+---
+
+Welcome to LangChain4j!

docs/blog/2023-08-29-release-0.22.0.md

@@ -0,0 +1,33 @@
+---
+slug: release-0.22.0
+title: Release 0.22.0
+authors: [ lanchain4j ]
+tags: [ Java, AI, LLM, GenAI, GenerativeAI, LangChain4j, LangChain, OpenSource, Developers
+]
+---
+
+LangChain4j 0.22.0 is out!
+
+- Integration with [Google Vertex AI](https://cloud.google.com/vertex-ai)
+- Offline text classification with embeddings
+- Reworked document splitters
+- In-process embedding models can now embed longer texts
+- In-memory embedding store can now be easily persisted
+- And more: https://github.com/langchain4j/langchain4j/releases/tag/0.22.0
+
+Now any text (e.g. document, message from a user, etc) can be classified completely offline and without any external
+calls.
+
+See example [here](https://github.com/langchain4j/langchain4j-examples/blob/main/other-examples/src/main/java/embedding/classification/EmbeddingModelTextClassifierExample.java).
+
+You only need to specify some examples for each label/category and that's it! BTW, examples can be generated using
+LLMs ;)
+
+Benefits are: faster and cheaper usage of LLMs.
+
+There are lots of use cases:
+
+1. Labeling documents
+2. For chatbots: choosing appropriate (system) prompt depending on the user's message (e.g. is it a complaint? a
+   greeting? regular question? etc)
+3. For chatbots/agents: choosing appropriate tools depending on a user's message (to save on tokens)

docs/blog/authors.yml

@@ -0,0 +1,11 @@
+amith:
+  name: Amith Koujalgi
+  title: Maintainer of Ollama4j
+  url: https://github.com/amithkoujalgi
+  image_url: https://github.com/amithkoujalgi.png
+
+lanchain4j:
+  name: LangChain4j
+  title: Author and Maintainer of LangChain4j
+  url: https://github.com/langchain4j
+  image_url: https://github.com/langchain4j.png

docs/docs/code-examples/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "Code Examples",
+  "position": 6,
+  "link": {
+    "type": "generated-index",
+    "description": "Code Examples"
+  }
+}

docs/docs/code-examples/hello-world.md

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+---
+sidebar_position: 1
+---
+
+# Hello, World!
+
+[HelloWorld.java](https://github.com/langchain4j/langchain4j-examples/blob/main/other-examples/src/main/java/HelloWorldExample.java)
+
+```java
+import dev.langchain4j.model.chat.ChatLanguageModel;
+import dev.langchain4j.model.openai.OpenAiChatModel;
+
+public class HelloWorldExample {
+
+    public static void main(String[] args) {
+
+        // Create an instance of a model
+        ChatLanguageModel model = OpenAiChatModel.withApiKey(ApiKeys.OPENAI_API_KEY);
+
+        // Start interacting
+        String answer = model.generate("Hello world!");
+
+        System.out.println(answer); // Hello! How can I assist you today?
+    }
+}
+```

docs/docs/code-examples/plain-java.md

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+---
+sidebar_position: 2
+---
+
+# Plain Java
+
+[Simple Service](https://github.com/langchain4j/langchain4j-examples/blob/main/other-examples/src/main/java/SimpleServiceExample.java)
+
+```java
+import dev.langchain4j.model.chat.ChatLanguageModel;
+import dev.langchain4j.model.openai.OpenAiChatModel;
+import dev.langchain4j.service.AiServices;
+
+public class SimpleServiceExample {
+
+    interface Assistant {
+
+        String chat(String message);
+    }
+
+    public static void main(String[] args) {
+
+        ChatLanguageModel chatLanguageModel = OpenAiChatModel.withApiKey(ApiKeys.OPENAI_API_KEY);
+
+        Assistant assistant = AiServices.create(Assistant.class, chatLanguageModel);
+
+        String answer = assistant.chat("Hello");
+
+        System.out.println(answer); // Hello! How can I assist you today?
+    }
+}
+```

docs/docs/code-examples/sping-boot.md

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+---
+sidebar_position: 3
+---
+
+# Spring Boot
+
+[CustomerSupportApplicationTest.java](https://github.com/langchain4j/langchain4j-examples/blob/main/spring-boot-example/src/test/java/dev/example/CustomerSupportApplicationTest.java)
+
+```java
+package dev.example;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.test.context.SpringBootTest;
+
+@SpringBootTest
+class CustomerSupportApplicationTest {
+
+    @Autowired
+    CustomerSupportAgent agent;
+
+    @Test
+    void should_provide_booking_details_and_explain_why_cancellation_is_not_possible() {
+
+        // Please define API keys in application.properties before running this test.
+        // Tip: Use gpt-4 for this example, as gpt-3.5-turbo tends to hallucinate often and invent name and surname.
+
+        interact(agent, "Hi, I forgot when my booking is.");
+        interact(agent, "123-457");
+        interact(agent, "I'm sorry I'm so inattentive today. Klaus Heisler.");
+        interact(agent, "My bad, it's 123-456");
+
+        // Here, information about the cancellation policy is automatically retrieved and injected into the prompt.
+        // Although the LLM sometimes attempts to cancel the booking, it fails to do so and will explain
+        // the reason why the booking cannot be cancelled, based on the injected cancellation policy.
+        interact(agent, "My plans have changed, can I cancel my booking?");
+    }
+
+    private static void interact(CustomerSupportAgent agent, String userMessage) {
+        System.out.println("==========================================================================================");
+        System.out.println("[User]: " + userMessage);
+        System.out.println("==========================================================================================");
+        String agentAnswer = agent.chat(userMessage);
+        System.out.println("==========================================================================================");
+        System.out.println("[Agent]: " + agentAnswer);
+        System.out.println("==========================================================================================");
+    }
+}
+```

docs/docs/documentation/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "Documentation",
+  "position": 5,
+  "link": {
+    "type": "generated-index",
+    "description": "Documentation"
+  }
+}

docs/docs/documentation/hello-world.md

@@ -0,0 +1,5 @@
+---
+sidebar_position: 1
+---
+
+# TBD

docs/docs/getting-started/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "Getting Started",
+  "position": 4,
+  "link": {
+    "type": "generated-index",
+    "description": "Getting Started"
+  }
+}

docs/docs/getting-started/hello-world.md

@@ -0,0 +1,48 @@
+---
+sidebar_position: 2
+---
+
+# Write a Hello World program!
+
+:::note
+
+Before you proceed, make sure you have Java 8+ and Maven installed. Verify it by typing in these commands in your terminal:
+
+```shell
+java --version
+mvn --version
+```
+
+:::
+
+Easiest way to get started is with OpenAI integration. So, you'll need to setup an OpenAI account.
+Then, specify your OpenAPI key as the environment variable `OPENAI_API_KEY`.
+
+```shell
+export OPENAI_API_KEY=sk-<the-rest-of-your-key>
+```
+
+Once you've setup OpenAPI key, create this Java class and run it.
+
+```java
+import dev.langchain4j.data.message.AiMessage;
+import dev.langchain4j.model.chat.ChatLanguageModel;
+import dev.langchain4j.model.openai.OpenAiChatModel;
+
+public class HelloWorldExample {
+
+    public static void main(String[] args) {
+
+        // Create an instance of a model
+        ChatLanguageModel model = OpenAiChatModel
+                .withApiKey(System.getenv("OPENAI_API_KEY");
+
+        // Start interacting
+        AiMessage answer = model.sendUserMessage("Hello world!");
+
+        System.out.println(answer.text()); // Hello! How can I assist you today?
+    }
+}
+```
+
+Find more examples [here](/docs/category/code-examples).

docs/docs/getting-started/setup.md

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+---
+sidebar_position: 1
+---
+
+# Setup
+
+### Table of Contents
+
+- [Requirements](#requirements)
+- [Installation](#installation)
+
+#### Requirements
+
+![Java](https://img.shields.io/badge/Java-8_+-blue.svg?style=for-the-badge&labelColor=gray)
+
+Latest version of LangChain4j: ![Maven Central](https://img.shields.io/maven-central/v/dev.langchain4j/langchain4j?style=for-the-badge&labelColor=gray)
+
+To install langchain4j to your project, add the following dependency to your `pom.xml` file.
+
+For Maven project:
+
+```xml
+
+<dependency>
+    <groupId>dev.langchain4j</groupId>
+    <artifactId>langchain4j</artifactId>
+    <version>{your-version}</version> <!-- Specify your version here -->
+</dependency>
+```
+
+For Gradle project:
+
+```groovy
+implementation 'dev.langchain4j:langchain4j:{your-version}'
+```

docs/docs/integrations/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "Integrations",
+  "position": 7,
+  "link": {
+    "type": "generated-index",
+    "description": "Integrations"
+  }
+}

docs/docs/integrations/code-execution-engines.md

@@ -0,0 +1,5 @@
+---
+sidebar_position: 5
+---
+
+# Code Execution Engines

docs/docs/integrations/document-loaders.md

@@ -0,0 +1,5 @@
+---
+sidebar_position: 2
+---
+
+# Document Loaders

docs/docs/integrations/embedding-models.md

@@ -0,0 +1,5 @@
+---
+sidebar_position: 4
+---
+
+# Embedding Models

docs/docs/integrations/embedding-stores.md

@@ -0,0 +1,5 @@
+---
+sidebar_position: 3
+---
+
+# Embedding Stores

docs/docs/integrations/frameworks.md

@@ -0,0 +1,5 @@
+---
+sidebar_position: 6
+---
+
+# Frameworks