Merge pull request #133 from ollama4j/docs-updates

Update index.js

.github/workflows/build-on-pr-create.yml

@@ -1,34 +0,0 @@
-# This workflow will build a package using Maven and then publish it to GitHub packages when a release is created
-# For more information see: https://github.com/actions/setup-java/blob/main/docs/advanced-usage.md#apache-maven-with-a-settings-path
-
-name: Build on PR Create
-
-on:
-  pull_request:
-    types: [ opened, reopened ]
-    branches: [ "main" ]
-
-
-jobs:
-  build:
-
-    runs-on: ubuntu-latest
-    permissions:
-      contents: read
-      packages: write
-
-    steps:
-      - uses: actions/checkout@v3
-      - name: Set up JDK 11
-        uses: actions/setup-java@v3
-        with:
-          java-version: '11'
-          distribution: 'adopt-hotspot'
-          server-id: github # Value of the distributionManagement/repository/id field of the pom.xml
-          settings-path: ${{ github.workspace }} # location for the settings.xml file
-
-      - name: Build with Maven
-        run: mvn --file pom.xml -U clean package
-
-      - name: Run Tests
-        run: mvn --file pom.xml -U clean test -Punit-tests

.github/workflows/build-on-pull-request.yml

@@ -0,0 +1,46 @@
+name: Run Tests
+
+on:
+  pull_request:
+    #    types: [opened, reopened, synchronize, edited]
+    branches: [ "main" ]
+    paths:
+      - 'src/**'           # Run if changes occur in the 'src' folder
+      - 'pom.xml'          # Run if changes occur in the 'pom.xml' file
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  run-tests:
+
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up JDK 11
+        uses: actions/setup-java@v3
+        with:
+          java-version: '11'
+          distribution: 'adopt-hotspot'
+          server-id: github # Value of the distributionManagement/repository/id field of the pom.xml
+          settings-path: ${{ github.workspace }} # location for the settings.xml file
+
+      - name: Build with Maven
+        run: mvn --file pom.xml -U clean package
+
+      - name: Run unit tests
+        run: mvn --file pom.xml -U clean test -Punit-tests
+
+      - name: Run integration tests
+        run: mvn --file pom.xml -U clean verify -Pintegration-tests
+
+      - name: Use Node.js
+        uses: actions/setup-node@v3
+        with:
+          node-version: '20.x'
+      - run: cd docs && npm ci
+      - run: cd docs && npm run build

.github/workflows/label-issue-stale.yml

@@ -0,0 +1,24 @@
+name: Mark stale issues
+
+on:
+  workflow_dispatch: # for manual run
+  schedule:
+    - cron: '0 0 * * *'  # Runs every day at midnight
+
+permissions:
+  contents: write # only for delete-branch option
+  issues: write
+
+jobs:
+  stale:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Mark stale issues
+        uses: actions/stale@v8
+        with:
+          repo-token: ${{ github.token }}
+          days-before-stale: 15
+          stale-issue-message: 'This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs.'
+          days-before-close: 7
+          stale-issue-label: 'stale'
+          exempt-issue-labels: 'pinned,security'

.github/workflows/publish-docs.yml

@@ -1,5 +1,5 @@
 # Simple workflow for deploying static content to GitHub Pages
-name: Deploy Docs to GH Pages
+name: Publish Docs to GH Pages
 
 on:
   release:
@@ -63,12 +63,12 @@ jobs:
           working-directory: "."
 
       - name: Setup Pages
-        uses: actions/configure-pages@v3
+        uses: actions/configure-pages@v5
       - name: Upload artifact
-        uses: actions/upload-pages-artifact@v2
+        uses: actions/upload-pages-artifact@v3
         with:
           # Upload entire repository
           path: './docs/build/.'
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v2
+        uses: actions/deploy-pages@v4

.github/workflows/run-tests.yml

@@ -0,0 +1,35 @@
+name: Run Unit and Integration Tests
+
+on:
+#  push:
+#    branches:
+#      - main
+  workflow_dispatch:
+    inputs:
+      branch:
+        description: 'Branch name to run the tests on'
+        required: true
+        default: 'main'
+
+jobs:
+  run-tests:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          ref: ${{ github.event.inputs.branch }}
+
+      - name: Set up JDK 17
+        uses: actions/setup-java@v3
+        with:
+          java-version: '17'
+          distribution: 'temurin'
+          server-id: github
+          settings-path: ${{ github.workspace }}
+
+      - name: Run unit tests
+        run: mvn clean test -Punit-tests
+
+      - name: Run integration tests
+        run: mvn clean verify -Pintegration-tests

.pre-commit-config.yaml

@@ -0,0 +1,38 @@
+repos:
+
+  # pre-commit hooks
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: "v5.0.0"
+    hooks:
+      - id: no-commit-to-branch
+        args: ['--branch', 'main']
+      - id: check-merge-conflict
+      - id: check-added-large-files
+      - id: check-yaml
+      - id: check-xml
+      - id: check-json
+      - id: pretty-format-json
+        args: ['--no-sort-keys', '--autofix', '--indent=4']
+      - id: end-of-file-fixer
+        exclude: \.json$
+        files: \.java$|\.xml$
+      - id: trailing-whitespace
+      - id: mixed-line-ending
+
+  # for commit message formatting
+  - repo: https://github.com/commitizen-tools/commitizen
+    rev: v4.4.1
+    hooks:
+      - id: commitizen
+        stages: [commit-msg]
+
+#  # for java code quality
+#  - repo: https://github.com/gherynos/pre-commit-java
+#    rev: v0.6.10
+#    hooks:
+#      - id: pmd
+#        exclude: /test/
+#      - id: cpd
+#        exclude: /test/
+#      - id: checkstyle
+#        exclude: /test/

Makefile

@@ -1,11 +1,25 @@
+dev:
+	@echo "Setting up dev environment..."
+	@command -v pre-commit >/dev/null 2>&1 || { echo "Error: pre-commit is not installed. Please install it first."; exit 1; }
+	@command -v docker >/dev/null 2>&1 || { echo "Error: docker is not installed. Please install it first."; exit 1; }
+	pre-commit install
+	pre-commit autoupdate
+	pre-commit install --install-hooks
+
 build:
+	mvn -B clean install -Dgpg.skip=true
+
+full-build:
 	mvn -B clean install
 
 unit-tests:
 	mvn clean test -Punit-tests
 
 integration-tests:
-	mvn clean verify -Pintegration-tests
+	export USE_EXTERNAL_OLLAMA_HOST=false && mvn clean verify -Pintegration-tests
+
+integration-tests-remote:
+	export USE_EXTERNAL_OLLAMA_HOST=true && export OLLAMA_HOST=http://192.168.29.223:11434 && mvn clean verify -Pintegration-tests -Dgpg.skip=true
 
 doxygen:
 	doxygen Doxyfile
@@ -15,10 +29,10 @@ list-releases:
       --compressed \
       --silent | jq -r '.components[].version'
 
-build-docs:
+docs-build:
 	npm i --prefix docs && npm run build --prefix docs
 
-start-docs:
+docs-serve:
 	npm i --prefix docs && npm run start --prefix docs
 
 start-cpu:

README.md

@@ -31,8 +31,11 @@ Find more details on the [website](https://ollama4j.github.io/ollama4j/).
 
 ![GitHub last commit](https://img.shields.io/github/last-commit/ollama4j/ollama4j?color=green)
 [![codecov](https://codecov.io/gh/ollama4j/ollama4j/graph/badge.svg?token=U0TE7BGP8L)](https://codecov.io/gh/ollama4j/ollama4j)
+
+[![Run Unit and Integration Tests](https://github.com/ollama4j/ollama4j/actions/workflows/run-tests.yml/badge.svg)](https://github.com/ollama4j/ollama4j/actions/workflows/run-tests.yml)
 ![Build Status](https://github.com/ollama4j/ollama4j/actions/workflows/maven-publish.yml/badge.svg)
 
+
 </div>
 
 [//]: # (![Hits]&#40;https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2Follama4j%2Follama4j&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=hits&edge_flat=false&#41;)
@@ -45,6 +48,7 @@ Find more details on the [website](https://ollama4j.github.io/ollama4j/).
 - [Requirements](#requirements)
 - [Installation](#installation)
 - [API Spec](https://ollama4j.github.io/ollama4j/category/apis---model-management)
+- [Examples](#examples)
 - [Javadoc](https://ollama4j.github.io/ollama4j/apidocs/)
 - [Development](#development)
 - [Contributions](#get-involved)
@@ -73,61 +77,6 @@ Find more details on the [website](https://ollama4j.github.io/ollama4j/).
   <img src="https://img.shields.io/badge/v0.3.0-green.svg?style=for-the-badge&labelColor=gray&label=Ollama&color=blue" alt=""/>
 </a>
 
-<table>
-<tr>
-<td> 
-
-<a href="https://ollama.ai/" target="_blank">Local Installation</a>
-
-</td> 
-
-<td> 
-
-<a href="https://hub.docker.com/r/ollama/ollama" target="_blank">Docker Installation</a>
-
-</td>
-</tr>
-<tr>
-<td>
-
-<a href="https://ollama.com/download/Ollama-darwin.zip" target="_blank">Download for macOS</a>
-
-<a href="https://ollama.com/download/OllamaSetup.exe" target="_blank">Download for Windows</a>
-
-Install on Linux
-
-```shell 
-curl -fsSL https://ollama.com/install.sh | sh
-```
-
-</td>
-<td>
-
-
-
-CPU only
-
-```shell
-docker run -d -p 11434:11434 \
-  -v ollama:/root/.ollama \
-  --name ollama \
-  ollama/ollama
-```
-
-NVIDIA GPU
-
-```shell
-docker run -d -p 11434:11434 \
-  --gpus=all \
-  -v ollama:/root/.ollama \
-  --name ollama \
-  ollama/ollama
-```
-
-</td>
-</tr>
-</table>
-
 ## Installation
 
 > [!NOTE]
@@ -153,7 +102,7 @@ In your Maven project, add this dependency:
 <dependency>
     <groupId>io.github.ollama4j</groupId>
     <artifactId>ollama4j</artifactId>
-    <version>1.0.89</version>
+    <version>1.0.100</version>
 </dependency>
 ```
 
@@ -209,7 +158,7 @@ In your Maven project, add this dependency:
 <dependency>
     <groupId>io.github.ollama4j</groupId>
     <artifactId>ollama4j</artifactId>
-    <version>1.0.89</version>
+    <version>1.0.100</version>
 </dependency>
 ```
 
@@ -219,7 +168,7 @@ In your Maven project, add this dependency:
 
 ```groovy
 dependencies {
-    implementation 'io.github.ollama4j:ollama4j:1.0.79'
+    implementation 'io.github.ollama4j:ollama4j:1.0.100'
 }
 ```
 
@@ -242,47 +191,80 @@ dependencies {
 > [!TIP]
 > Find the full API specifications on the [website](https://ollama4j.github.io/ollama4j/).
 
-#### Development
+### Development
 
-Build:
+Make sure you have `pre-commit` installed.
+
+With `brew`:
+
+```shell
+brew install pre-commit
+```
+
+With `pip`:
+
+```shell
+pip install pre-commit
+```
+
+#### Setup dev environment
+
+> **Note**
+> If you're on Windows, install [Chocolatey Package Manager for Windows](https://chocolatey.org/install) and then install `make` by running `choco install make`. Just a little tip - run the command with administrator privileges if installation faiils.
+
+```shell
+make dev
+```
+
+#### Build
 
 ```shell
 make build
 ```
 
-Run unit tests:
+#### Run unit tests
 
 ```shell
 make unit-tests
 ```
 
-Run integration tests:
+#### Run integration tests
+
+Make sure you have Docker running as this uses [testcontainers](https://testcontainers.com/) to run the integration
+tests on Ollama Docker container.
 
 ```shell
 make integration-tests
 ```
 
-#### Releases
+### Releases
 
 Newer artifacts are published via GitHub Actions CI workflow when a new release is created from `main` branch.
 
+## Examples
+
+The `ollama4j-examples` repository contains examples for using the Ollama4j library. You can explore
+it [here](https://github.com/ollama4j/ollama4j-examples).
+
 ## ⭐ Give us a Star!
 
 If you like or are using this project to build your own, please give us a star. It's a free way to show your support.
 
 ## Who's using Ollama4j?
 
-| # | Project Name      | Description                                                                                                   | Link                                                                                                                                           |
-|---|-------------------|---------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|
-| 1 | Datafaker         | A library to generate fake data                                                                               | [GitHub](https://github.com/datafaker-net/datafaker-experimental/tree/main/ollama-api)                                                         |
-| 2 | Vaadin Web UI     | UI-Tester for interactions with Ollama via ollama4j                                                           | [GitHub](https://github.com/TEAMPB/ollama4j-vaadin-ui)                                                                                         |
-| 3 | ollama-translator | A Minecraft 1.20.6 Spigot plugin that translates all messages into a specific target language via Ollama      | [GitHub](https://github.com/liebki/ollama-translator)                                                                                          |
-| 4 | AI Player         | A Minecraft mod that adds an intelligent "second player" to the game                                          | [GitHub](https://github.com/shasankp000/AI-Player), <br/> [Reddit Thread](https://www.reddit.com/r/fabricmc/comments/1e65x5s/comment/ldr2vcf/) |
-| 5 | Ollama4j Web UI   | A web UI for Ollama written in Java using Spring Boot, Vaadin, and Ollama4j                                   | [GitHub](https://github.com/ollama4j/ollama4j-web-ui)                                                                                          |
-| 6 | JnsCLI            | A command-line tool for Jenkins that manages jobs, builds, and configurations, with AI-powered error analysis | [GitHub](https://github.com/mirum8/jnscli)                                                                                                     |
-| 7 | Katie Backend     | An open-source AI-based question-answering platform for accessing private domain knowledge                    | [GitHub](https://github.com/wyona/katie-backend)                                                                                               |
-| 8 | TeleLlama3 Bot    | A question-answering Telegram bot                                                                             | [Repo](https://git.hiast.edu.sy/mohamadbashar.disoki/telellama3-bot)                                                                           |
-| 9 | moqui-wechat      | A moqui-wechat component                                                                                      | [GitHub](https://github.com/heguangyong/moqui-wechat)                                                                                          |
+| #  | Project Name      | Description                                                                                                                                                        | Link                                                                                                                                                                                          |
+|----|-------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 1  | Datafaker         | A library to generate fake data                                                                                                                                    | [GitHub](https://github.com/datafaker-net/datafaker-experimental/tree/main/ollama-api)                                                                                                        |
+| 2  | Vaadin Web UI     | UI-Tester for interactions with Ollama via ollama4j                                                                                                                | [GitHub](https://github.com/TEAMPB/ollama4j-vaadin-ui)                                                                                                                                        |
+| 3  | ollama-translator | A Minecraft 1.20.6 Spigot plugin that translates all messages into a specific target language via Ollama                                                           | [GitHub](https://github.com/liebki/ollama-translator)                                                                                                                                         |
+| 4  | AI Player         | A Minecraft mod that adds an intelligent "second player" to the game                                                                                               | [Website](https://modrinth.com/mod/ai-player), [GitHub](https://github.com/shasankp000/AI-Player), <br/> [Reddit Thread](https://www.reddit.com/r/fabricmc/comments/1e65x5s/comment/ldr2vcf/) |
+| 5  | Ollama4j Web UI   | A web UI for Ollama written in Java using Spring Boot, Vaadin, and Ollama4j                                                                                        | [GitHub](https://github.com/ollama4j/ollama4j-web-ui)                                                                                                                                         |
+| 6  | JnsCLI            | A command-line tool for Jenkins that manages jobs, builds, and configurations, with AI-powered error analysis                                                      | [GitHub](https://github.com/mirum8/jnscli)                                                                                                                                                    |
+| 7  | Katie Backend     | An open-source AI-based question-answering platform for accessing private domain knowledge                                                                         | [GitHub](https://github.com/wyona/katie-backend)                                                                                                                                              |
+| 8  | TeleLlama3 Bot    | A question-answering Telegram bot                                                                                                                                  | [Repo](https://git.hiast.edu.sy/mohamadbashar.disoki/telellama3-bot)                                                                                                                          |
+| 9  | moqui-wechat      | A moqui-wechat component                                                                                                                                           | [GitHub](https://github.com/heguangyong/moqui-wechat)                                                                                                                                         |
+| 10 | B4X               | A set of simple and powerful RAD tool for Desktop and Server development                                                                                           | [Website](https://www.b4x.com/android/forum/threads/ollama4j-library-pnd_ollama4j-your-local-offline-llm-like-chatgpt.165003/)                                                                |
+| 11 | Research Article  | Article: `Large language model based mutations in genetic improvement` - published on National Library of Medicine (National Center for Biotechnology Information) | [Website](https://pmc.ncbi.nlm.nih.gov/articles/PMC11750896/)                                                                                                                                 |
 
 ## Traction
 
@@ -349,7 +331,7 @@ project.
   </a>
 </p>
 
-### Appreciate my work?
+### Appreciate the work?
 
 <p align="center">
   <a href="https://www.buymeacoffee.com/amithkoujalgi" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>

docs/blog/2023-12-01-welcome/index.md

@@ -1,9 +0,0 @@
----
-slug: welcome
-title: Welcome
-authors: [ amith ]
-tags: [ Java, AI, LLM, GenAI, GenerativeAI, Ollama, Ollama4J, OpenSource, Developers
-]
----
-
-Welcome Java Developers!

docs/blog/2023-12-22-release-post.md

@@ -1,6 +1,6 @@
 ---
 slug: release-post
-title: Release
+title: First Release 🚀
 authors: [ amith ]
 tags: [ Java, AI, LLM, GenAI, GenerativeAI, Ollama, Ollama4j, OpenSource, Developers
 ]

docs/blog/2025-03-08-blog/index.md

@@ -0,0 +1,709 @@
+---
+slug: talk-to-your-data-on-couchbase-via-ollama4j
+title: "Talk to Your Data Using Natural Language: A Guide to Interacting with Couchbase via Ollama4j"
+authors: [ amith ]
+tags: [ Java, AI, LLM, GenAI, GenerativeAI, Generative AI Tools, Ollama, Ollama4J, OpenSource, Developers,
+]
+---
+
+Sometime back, I created a small wrapper called Ollama4j to interact with the Ollama server over the REST API in Java as
+a side project and made the [repository](https://github.com/ollama4j/ollama4j) public on GitHub. Over time, the project
+gained traction, with many fellow Java
+developers contributing, and it now boasts over _300 stars_! 😍
+
+We’ve consistently introduced new features, and when we added the tool-calling capability, the library became incredibly
+powerful, opening up so many possibilities. With this addition, we could automate numerous tasks using natural language!
+I wanted to share how to make the most of this functionality.
+
+In this article, we’ll explore how to use Ollama4j, a Java SDK for interacting with Ollama-hosted models, to leverage
+tool-calling models like Mistral for querying a Couchbase database. The goal is to create a system where you can query
+your database using natural, conversational language — just like interacting with a virtual assistant. We’ll walk you
+through the code, explain the key components, and show you how to set up your environment to ensure everything runs
+smoothly.
+
+### Overview of the Technologies Involved
+
+Before diving into the implementation, let’s understand the core technologies we’re using:
+
+- **Ollama4j**: A Java SDK that interacts with hosted AI models through a convenient API. Ollama allows you to interact
+  with
+  pre-trained models (like Mistral) and access additional tools that can be applied to real-world tasks.
+- **Mistral**: A powerful, language-based model that can be used for a variety of tasks, including answering questions,
+  text
+  generation, and data retrieval from external sources. While I’ve used Mistral in this instance, you can easily replace
+  it with [any other model](https://ollama.com/search?c=tools) that supports tool-calling capabilities.
+- **Couchbase**: A NoSQL database that provides a flexible and scalable data model. In this example, we’ll query a
+  Couchbase
+  database to retrieve airline information.
+
+The magic happens when we combine these technologies to allow the model to query the database in a more intuitive and
+human-like way, acting as an interface between the user’s natural language and Couchbase’s structured data.
+
+
+> Oh, by the way, you can either set up
+> a [Couchbase server](https://www.couchbase.com/downloads/?family=couchbase-server) on your own or, if you prefer a
+> more
+> effortless approach like
+> I
+> do, give [Couchbase Capella](https://www.couchbase.com/products/capella/) a spin. It’s a fully managed
+> Database-as-a-Service (DBaaS) with a free tier 🎉 that’s so
+> easy
+> to set up, you’ll be querying your data in no time. It’s perfect for developers who want to dive in without any
+> hassle —
+> it’s like having your own cloud database, minus the headache!
+
+
+In the following section, we will walk you through the simple steps to create your free Couchbase Capella database
+cluster. If you’d prefer to set up your own Couchbase server elsewhere, feel free to skip this section and go directly
+to the [Code Environment Setup](#setting-up-the-environment-for-code) section.
+
+Sign up for a free database cluster on Couchbase Capella
+Head over to https://cloud.couchbase.com/sign-in and sign up for an account.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*vsJC0ugfoh9vpYNapt4-5A.png'} />
+
+Once you’re in, you will be able to create a new database cluster. Click on the _**Operational**_ tab and click on the
+**_Create Cluster_** button.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*ZNicgmYNkclgaBIxwRN7Ug.png'} />
+
+Select the default project named **_My First Project_** and click on the **_Continue_** button.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*vfc2cF7IgkjLtNXvls8giQ.png'} />
+
+You’ll now see the available cluster options. Go ahead and select the **_Free_** option! 😍
+Next, choose your preferred cloud provider (you can select any provider or stick with the default AWS provider).
+Pick a region (or leave it set to the default).
+Finally, click on the Create Cluster button to proceed.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*rdWpeSrUaBKC6Y5q8Kd6EA.png'} />
+
+Give it a couple of minutes, and let the magic happen as your cluster gets deployed.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*no3uHx8cIzVBn7qccYEZ3A.png'} />
+
+Once your cluster is deployed, you’ll see the status of your cluster as **_Healthy_**.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*Jyu9uiSDSE0o-EQRb53CJA.png'} />
+
+Click on the listed cluster to open its details. Here, you can view the version of the deployed Couchbase server, the
+enabled services, as well as the cloud provider and region.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*Sv-7wQuAoD0l0bjbI5I7Aw.png'} />
+
+Click on **_Explore Data_** button. Notice that a default bucket called **_travel-sample_** with some sample data has
+been created
+for you.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*z85GsgMBvdR2mrvKUrIjJg.png'} />
+
+Browse through the collection to explore the pre-created buckets, scopes and collections available to you.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*Qr84bs1dvn6m9ZjkNxXvUg.png'} />
+
+Open up a sample document from the **_travel-sample_** (bucket) > **_inventory_** (scope) > **_airline_** (collection)
+to see the contents
+of the document.
+
+The document shown in the image below is about an airline named **_Astraeus_**, whose call sign (a unique name or code
+used to
+identify an airline or aircraft in communication) is **_FLYSTAR_**.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*AmvixYfdNNKC6nXNNXbe4Q.png'} />
+
+Navigate to the **_Connect_** tab, and you will see a **_Public Connection String_** that allows you to access the
+Capella cluster
+endpoint from your client application, which looks like the following URL:
+
+```
+couchbases://cb.uniqueclusteridentifer.cloud.couchbase.com
+```
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*jwnVdj5ZOQMHoggj9JZeJQ.png'} />
+
+To access this cluster endpoint, you need to allow the IP addresses that are permitted to connect. Click on the
+**_Settings_**
+tab, which will take you to the **_Cluster Settings_** view. Then, click on **_Allowed IP Addresses_** in the left pane
+under
+**_Networking_**, where you can add allowed IP addresses. Then, click on the **_Add Allowed IP_** button.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*tS83AJaNzlBa4Q3aadxohw.png'} />
+
+You can either click on the **_Add Current IP Address_** button to limit access to your cluster to your IP address
+alone, or
+if you’d like to allow access from anywhere, click on the **_Allow Access from Anywhere_** button.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*XBgqQoXQQJyYg51Ztugw6w.png'} />
+
+Confirm that you want to allow the IP addresses.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*WjfYQQaiT2WqwNnWvUCyww.png'} />
+
+The IP addresses have now been added to the allow list, and the networking is set up.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*5BHIp2rqUf7E_GNX8TENoA.png'} />
+
+Now that you’ve allowed IP addresses, it’s time to create credentials for accessing the cluster using a username and
+password. Click on the **_Cluster Access_** tab in the left pane, then click on the **_Create Cluster Access_** button.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*Q5l_EE3gGtxiANdkKilVTQ.png'} />
+
+Enter a username of your choice in the **_Cluster Access Name_** text field, and then enter a password of your choice in
+the
+**_Password_** text field.
+
+Next, select the bucket, scope, and the read/write permissions you want these credentials to have access to. In this
+example, I’ve granted access to all buckets and scopes with both read and write permissions.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*j2DRB1oDWE78SKpcsIb2SA.png'} />
+
+Alright, your cluster access is now set up.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*8TY-5DPDfQlwz0-2IYR8Sg.png'} />
+
+One last step: you just need to select the **_Cluster Access Credentials_** that you want to allow to connect to your
+Capella
+cluster. Head over to the **_Connect_** tab, then click on the **_SDKs_** tab in the left pane. Under Choose the
+**_Cluster Access Credentials you want to use to connect to your Capella cluster_**, select the cluster credentials you
+just created.
+
+<img src={'https://miro.medium.com/v2/resize:fit:1400/format:webp/1*sIlH51v2HllTzBDV8K-9Aw.png'} />
+
+Awesome! Your cluster access is all set up, and you’re ready to connect to your Capella cluster using a Couchbase
+client. That’s it — you’re all set and good to go!
+
+### Setting Up the Environment For Code
+
+Before you begin, ensure you have the following components setup.
+
+**Java**: Make sure you have Java 11+ installed on your system. Set it up
+from [here](https://www.oracle.com/in/java/technologies/downloads/). Verify it by running the following
+command in your terminal.
+
+```shell
+java --version
+```
+
+**Maven**: Make sure you have the Maven build system set up. Set it up from [here](https://maven.apache.org/download.cgi).
+Verify it by running the following command
+in your terminal.
+
+```
+mvn --version
+```
+
+**Ollama Server**: Make sure you have installed the latest version of [Ollama server](https://ollama.com/) and it is up
+and running. Verify it by
+running the following command in your terminal.
+
+```shell
+ollama --version
+```
+
+**Model**: You’ll need [tool-calling model](https://ollama.com/search?c=tools) (such as Mistral) downloaded and ready to
+serve from your Ollama server.
+
+To download/pull the model into your Ollama server, run the following command in your terminal.
+
+```shell
+ollama pull mistral
+
+```
+
+You can list the models available on your model server by running the following command in your terminal.
+
+```shell
+ollama list
+```
+
+Once you have these, you can start setting up the application.
+
+Setup `pom.xml` for your Maven project.
+
+```xml
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <modelVersion>4.0.0</modelVersion>
+
+    <groupId>io.github.ollama4j.couchbase</groupId>
+    <artifactId>ollama4j-couchbase</artifactId>
+    <version>0.0.1</version>
+    <name>Ollama4j Couchbase</name>
+    <description>Talk to your data in Couchbase over Ollama4j</description>
+    <packaging>jar</packaging>
+
+    <properties>
+        <maven.compiler.release>11</maven.compiler.release>
+        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+        <lombok.version>1.18.30</lombok.version>
+    </properties>
+
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-source-plugin</artifactId>
+                <version>3.3.1</version>
+                <executions>
+                    <execution>
+                        <id>attach-sources</id>
+                        <goals>
+                            <goal>jar-no-fork</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-javadoc-plugin</artifactId>
+                <version>3.11.2</version>
+                <configuration>
+                    <!-- to disable the "missing" warnings. Remove the doclint to enable warnings-->
+                    <doclint>all,-missing</doclint>
+                </configuration>
+                <executions>
+                    <execution>
+                        <id>attach-javadocs</id>
+                        <goals>
+                            <goal>jar</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+        </plugins>
+
+        <pluginManagement>
+            <plugins>
+                <plugin>
+                    <artifactId>maven-compiler-plugin</artifactId>
+                    <version>3.14.0</version>
+                </plugin>
+            </plugins>
+        </pluginManagement>
+    </build>
+
+    <dependencies>
+        <dependency>
+            <groupId>io.github.ollama4j</groupId>
+            <artifactId>ollama4j</artifactId>
+            <version>ollama4j-revision</version>
+        </dependency>
+
+        <!-- SLF4J API -->
+        <dependency>
+            <groupId>org.slf4j</groupId>
+            <artifactId>slf4j-api</artifactId>
+            <version>2.0.0</version>
+        </dependency>
+
+        <!-- Logback Classic (SLF4J binding) -->
+        <dependency>
+            <groupId>ch.qos.logback</groupId>
+            <artifactId>logback-classic</artifactId>
+            <version>1.4.12</version>
+        </dependency>
+
+        <dependency>
+            <groupId>com.couchbase.client</groupId>
+            <artifactId>java-client</artifactId>
+            <version>3.7.8</version>
+        </dependency>
+
+        <dependency>
+            <groupId>org.projectlombok</groupId>
+            <artifactId>lombok</artifactId>
+            <version>1.18.30</version>
+            <scope>provided</scope>
+        </dependency>
+    </dependencies>
+</project>
+```
+
+### Code Walkthrough
+
+Here’s the main part of the implementation in the Java code.
+
+```java
+package io.github.ollama4j.examples;
+
+
+import com.couchbase.client.java.Bucket;
+import com.couchbase.client.java.Cluster;
+import com.couchbase.client.java.ClusterOptions;
+import com.couchbase.client.java.Scope;
+import com.couchbase.client.java.json.JsonObject;
+import com.couchbase.client.java.query.QueryResult;
+import io.github.ollama4j.OllamaAPI;
+import io.github.ollama4j.exceptions.OllamaBaseException;
+import io.github.ollama4j.exceptions.ToolInvocationException;
+import io.github.ollama4j.tools.OllamaToolsResult;
+import io.github.ollama4j.tools.ToolFunction;
+import io.github.ollama4j.tools.Tools;
+import io.github.ollama4j.utils.OptionsBuilder;
+import io.github.ollama4j.utils.Utilities;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.io.IOException;
+import java.time.Duration;
+import java.util.Arrays;
+import java.util.Map;
+
+
+public class CouchbaseToolCallingExample {
+
+    public static void main(String[] args) throws IOException, ToolInvocationException, OllamaBaseException, InterruptedException {
+        String connectionString = Utilities.getFromEnvVar("CB_CLUSTER_URL");
+        String username = Utilities.getFromEnvVar("CB_CLUSTER_USERNAME");
+        String password = Utilities.getFromEnvVar("CB_CLUSTER_PASSWORD");
+        String bucketName = "travel-sample";
+
+        Cluster cluster = Cluster.connect(
+                connectionString,
+                ClusterOptions.clusterOptions(username, password).environment(env -> {
+                    env.applyProfile("wan-development");
+                })
+        );
+
+        String host = Utilities.getFromConfig("host");
+        String modelName = Utilities.getFromConfig("tools_model_mistral");
+
+        OllamaAPI ollamaAPI = new OllamaAPI(host);
+        ollamaAPI.setVerbose(false);
+        ollamaAPI.setRequestTimeoutSeconds(60);
+
+        Tools.ToolSpecification callSignFinderToolSpec = getCallSignFinderToolSpec(cluster, bucketName);
+        Tools.ToolSpecification callSignUpdaterToolSpec = getCallSignUpdaterToolSpec(cluster, bucketName);
+
+        ollamaAPI.registerTool(callSignFinderToolSpec);
+        ollamaAPI.registerTool(callSignUpdaterToolSpec);
+
+        String prompt1 = "What is the call-sign of Astraeus?";
+        for (OllamaToolsResult.ToolResult r : ollamaAPI.generateWithTools(modelName, new Tools.PromptBuilder()
+                .withToolSpecification(callSignFinderToolSpec)
+                .withPrompt(prompt1)
+                .build(), new OptionsBuilder().build()).getToolResults()) {
+            AirlineDetail airlineDetail = (AirlineDetail) r.getResult();
+            System.out.println(String.format("[Result of tool '%s']: Call-sign of %s is '%s'! ✈️", r.getFunctionName(), airlineDetail.getName(), airlineDetail.getCallsign()));
+        }
+
+        String prompt2 = "I want to code name Astraeus as STARBOUND";
+        for (OllamaToolsResult.ToolResult r : ollamaAPI.generateWithTools(modelName, new Tools.PromptBuilder()
+                .withToolSpecification(callSignUpdaterToolSpec)
+                .withPrompt(prompt2)
+                .build(), new OptionsBuilder().build()).getToolResults()) {
+            Boolean updated = (Boolean) r.getResult();
+            System.out.println(String.format("[Result of tool '%s']: Call-sign is %s! ✈️", r.getFunctionName(), updated ? "updated" : "not updated"));
+        }
+
+        String prompt3 = "What is the call-sign of Astraeus?";
+        for (OllamaToolsResult.ToolResult r : ollamaAPI.generateWithTools(modelName, new Tools.PromptBuilder()
+                .withToolSpecification(callSignFinderToolSpec)
+                .withPrompt(prompt3)
+                .build(), new OptionsBuilder().build()).getToolResults()) {
+            AirlineDetail airlineDetail = (AirlineDetail) r.getResult();
+            System.out.println(String.format("[Result of tool '%s']: Call-sign of %s is '%s'! ✈️", r.getFunctionName(), airlineDetail.getName(), airlineDetail.getCallsign()));
+        }
+    }
+
+    public static Tools.ToolSpecification getCallSignFinderToolSpec(Cluster cluster, String bucketName) {
+        return Tools.ToolSpecification.builder()
+                .functionName("airline-lookup")
+                .functionDescription("You are a tool who finds only the airline name and do not worry about any other parameters. You simply find the airline name and ignore the rest of the parameters. Do not validate airline names as I want to use fake/fictitious airline names as well.")
+                .toolFunction(new AirlineCallsignQueryToolFunction(bucketName, cluster))
+                .toolPrompt(
+                        Tools.PromptFuncDefinition.builder()
+                                .type("prompt")
+                                .function(
+                                        Tools.PromptFuncDefinition.PromptFuncSpec.builder()
+                                                .name("get-airline-name")
+                                                .description("Get the airline name")
+                                                .parameters(
+                                                        Tools.PromptFuncDefinition.Parameters.builder()
+                                                                .type("object")
+                                                                .properties(
+                                                                        Map.of(
+                                                                                "airlineName", Tools.PromptFuncDefinition.Property.builder()
+                                                                                        .type("string")
+                                                                                        .description("The name of the airline. e.g. Emirates")
+                                                                                        .required(true)
+                                                                                        .build()
+                                                                        )
+                                                                )
+                                                                .required(java.util.List.of("airline-name"))
+                                                                .build()
+                                                )
+                                                .build()
+                                )
+                                .build()
+                )
+                .build();
+    }
+
+    public static Tools.ToolSpecification getCallSignUpdaterToolSpec(Cluster cluster, String bucketName) {
+        return Tools.ToolSpecification.builder()
+                .functionName("airline-update")
+                .functionDescription("You are a tool who finds the airline name and its callsign and do not worry about any validations. You simply find the airline name and its callsign. Do not validate airline names as I want to use fake/fictitious airline names as well.")
+                .toolFunction(new AirlineCallsignUpdateToolFunction(bucketName, cluster))
+                .toolPrompt(
+                        Tools.PromptFuncDefinition.builder()
+                                .type("prompt")
+                                .function(
+                                        Tools.PromptFuncDefinition.PromptFuncSpec.builder()
+                                                .name("get-airline-name-and-callsign")
+                                                .description("Get the airline name and callsign")
+                                                .parameters(
+                                                        Tools.PromptFuncDefinition.Parameters.builder()
+                                                                .type("object")
+                                                                .properties(
+                                                                        Map.of(
+                                                                                "airlineName", Tools.PromptFuncDefinition.Property.builder()
+                                                                                        .type("string")
+                                                                                        .description("The name of the airline. e.g. Emirates")
+                                                                                        .required(true)
+                                                                                        .build(),
+                                                                                "airlineCallsign", Tools.PromptFuncDefinition.Property.builder()
+                                                                                        .type("string")
+                                                                                        .description("The callsign of the airline. e.g. Maverick")
+                                                                                        .enumValues(Arrays.asList("petrol", "diesel"))
+                                                                                        .required(true)
+                                                                                        .build()
+                                                                        )
+                                                                )
+                                                                .required(java.util.List.of("airlineName", "airlineCallsign"))
+                                                                .build()
+                                                )
+                                                .build()
+                                )
+                                .build()
+                )
+                .build();
+    }
+}
+
+class AirlineCallsignQueryToolFunction implements ToolFunction {
+    private final String bucketName;
+    private final Cluster cluster;
+
+    public AirlineCallsignQueryToolFunction(String bucketName, Cluster cluster) {
+        this.bucketName = bucketName;
+        this.cluster = cluster;
+    }
+
+    @Override
+    public AirlineDetail apply(Map<String, Object> arguments) {
+        String airlineName = arguments.get("airlineName").toString();
+
+        Bucket bucket = cluster.bucket(bucketName);
+        bucket.waitUntilReady(Duration.ofSeconds(10));
+
+        Scope inventoryScope = bucket.scope("inventory");
+        QueryResult result = inventoryScope.query(String.format("SELECT * FROM airline WHERE name = '%s';", airlineName));
+
+        JsonObject row = (JsonObject) result.rowsAsObject().get(0).get("airline");
+        return new AirlineDetail(row.getString("callsign"), row.getString("name"), row.getString("country"));
+    }
+}
+
+class AirlineCallsignUpdateToolFunction implements ToolFunction {
+    private final String bucketName;
+    private final Cluster cluster;
+
+    public AirlineCallsignUpdateToolFunction(String bucketName, Cluster cluster) {
+        this.bucketName = bucketName;
+        this.cluster = cluster;
+    }
+
+
+    @Override
+    public Boolean apply(Map<String, Object> arguments) {
+        String airlineName = arguments.get("airlineName").toString();
+        String airlineNewCallsign = arguments.get("airlineCallsign").toString();
+
+        Bucket bucket = cluster.bucket(bucketName);
+        bucket.waitUntilReady(Duration.ofSeconds(10));
+
+        Scope inventoryScope = bucket.scope("inventory");
+        String query = String.format("SELECT * FROM airline WHERE name = '%s';", airlineName);
+
+        QueryResult result;
+        try {
+            result = inventoryScope.query(query);
+        } catch (Exception e) {
+            throw new RuntimeException("Error executing query", e);
+        }
+
+        if (result.rowsAsObject().isEmpty()) {
+            throw new RuntimeException("Airline not found with name: " + airlineName);
+        }
+
+        JsonObject row = (JsonObject) result.rowsAsObject().get(0).get("airline");
+
+        if (row == null) {
+            throw new RuntimeException("Airline data is missing or corrupted.");
+        }
+
+        String currentCallsign = row.getString("callsign");
+
+        if (!airlineNewCallsign.equals(currentCallsign)) {
+            JsonObject updateQuery = JsonObject.create()
+                    .put("callsign", airlineNewCallsign);
+
+            inventoryScope.query(String.format(
+                    "UPDATE airline SET callsign = '%s' WHERE name = '%s';",
+                    airlineNewCallsign, airlineName
+            ));
+            return true;
+        }
+        return false;
+    }
+}
+
+@SuppressWarnings("ALL")
+@Data
+@AllArgsConstructor
+@NoArgsConstructor
+class AirlineDetail {
+    private String callsign;
+    private String name;
+    private String country;
+}
+```
+
+### Key Concepts
+
+#### 1. Ollama API Client Setup
+
+```javascript
+OllamaAPI ollamaAPI = new OllamaAPI(host);
+
+ollamaAPI.setRequestTimeoutSeconds(60);
+```
+
+Here, we initialize the Ollama API client and configure it with the host of the Ollama server, where the model is hosted
+and can handle API requests. Additionally, we set the request timeout to 60 seconds to ensure that even if the model
+takes longer to respond, the request will still be processed.
+
+#### 2. Tool Specification
+
+The ToolSpecification class defines how the model will interact with the Couchbase database. We define a function that
+queries the database for airline details based on the airline name.
+
+```javascript
+Tools.ToolSpecification callSignFinderToolSpec = getCallSignFinderToolSpec(cluster, bucketName);
+
+ollamaAPI.registerTool(callSignFinderToolSpec);
+```
+
+This step registers custom tools with Ollama that allows the tool-calling model to invoke database queries.
+
+#### 3. Query Execution
+
+The tool will execute a Couchbase N1QL query to retrieve the airline details:
+
+```javascript
+QueryResult result = inventoryScope.query(String.format("SELECT * FROM airline WHERE name = '%s';", airlineName));
+```
+
+The result is processed and returned as an AirlineDetail object.
+
+#### 4. Set up your prompt (question)
+
+```javascript
+String prompt = "What is the call-sign of Astraeus?";
+```
+
+#### 5. Generating Results with Tools
+
+```javascript
+for (OllamaToolsResult.ToolResult r : ollamaAPI.generateWithTools(modelName, new Tools.PromptBuilder()
+        .withToolSpecification(callSignFinderToolSpec)
+        .withPrompt(prompt)
+        .build(), new OptionsBuilder().build()).getToolResults()) {
+    AirlineDetail airlineDetail = (AirlineDetail) r.getResult();
+    System.out.printf("[Result of tool '%s']: Call-sign of %s is '%s'! ✈️", r.getFunctionName(), airlineDetail.getName(), airlineDetail.getCallsign());
+}
+```
+
+This invokes the tool-calling model (Mistral in this case) with the provided prompt and uses the registered tool to
+query the database. The result is returned and printed to the console.
+
+So, we ask the following question to the model.
+
+> **What is the call-sign of Astraeus?**
+
+And, here’s what the model responds:
+
+> **Call-sign of Astraeus is ‘FLYSTAR’! ✈️**
+
+Isn’t that amazing? Now, let’s enhance it further by adding a function that allows us to update an airline’s call sign
+using natural language.
+
+Let’s define another `ToolSpecificationclass` that defines how the model will interact with the Couchbase database to
+update the database. We define a function that queries the database for airline details based on the airline name and
+then update the airline’s callsign.
+
+```javascript
+Tools.ToolSpecification callSignUpdaterToolSpec = getCallSignUpdaterToolSpec(cluster, bucketName);
+
+ollamaAPI.registerTool(callSignUpdaterToolSpec);
+```
+
+The tool will execute a Couchbase N1QL query to update the airline’s callsign.
+
+```javascript
+inventoryScope.query(String.format(
+        "UPDATE airline SET callsign = '%s' WHERE name = '%s';",
+        airlineNewCallsign, airlineName
+));
+```
+
+Setup the prompt to instruct the model to update the airline’s callsign.
+
+```javascript
+String prompt = "I want to code name Astraeus as STARBOUND";
+```
+
+And then we invoke the model with the new prompt.
+
+```javascript
+String prompt = "I want to code name Astraeus as STARBOUND";
+for (OllamaToolsResult.ToolResult r : ollamaAPI.generateWithTools(modelName, new Tools.PromptBuilder()
+        .withToolSpecification(callSignUpdaterToolSpec)
+        .withPrompt(prompt)
+        .build(), new OptionsBuilder().build()).getToolResults()) {
+    Boolean updated = (Boolean) r.getResult();
+    System.out.println(String.format("[Result of tool '%s']: Call-sign is %s! ✈️", r.getFunctionName(), updated ? "updated" : "not updated"));
+}
+```
+
+This invokes the tool-calling model (Mistral in this case) with the new prompt and uses the registered tool to update
+the database.
+
+So, we ask the following question to the model.
+
+> **I want to code name Astraeus as STARBOUND.**
+
+And, here’s what the model responds:
+
+> **Call-sign is updated! ✈️**
+
+How amazing is that? The possibilities for interacting with your data using natural language are endless. You could
+integrate features like checking flight availability, booking tickets, retrieving ticket details, and so much more!
+
+Feel free to extend this example further by adding more sophisticated capabilities! 🚀
+
+### Conclusion
+
+With the code above, you can use Ollama’s hosted models (like Mistral) to query a Couchbase database using natural
+language prompts. This makes it possible to interact with databases in a more intuitive and human-like way.
+
+By leveraging Ollama4j, you can connect AI models to real-world applications and build powerful tools that can automate
+complex tasks or simply make querying your data more conversational.
+
+You can find the full code and more such examples from
+the [ollama4j-examples](https://github.com/ollama4j/ollama4j-examples) GitHub repository.
+
+Credit to Couchbase, Ollama, and all the model teams for providing us with such amazing software!

docs/docs/apis-extras/bearer-auth.md

@@ -0,0 +1,26 @@
+---
+sidebar_position: 2
+---
+
+# Set Bearer Authentication
+
+This API lets you set the bearer authentication for the Ollama client. This would help in scenarios where
+Ollama server would be setup behind a gateway/reverse proxy with bearer auth.
+
+After configuring bearer authentication, all subsequent requests will include the Bearer Auth header.
+
+```java
+import io.github.ollama4j.OllamaAPI;
+
+public class Main {
+
+    public static void main(String[] args) {
+
+        String host = "http://localhost:11434/";
+
+        OllamaAPI ollamaAPI = new OllamaAPI(host);
+
+        ollamaAPI.setBearerAuth("YOUR-TOKEN");
+    }
+}
+```

docs/docs/apis-generate/chat-with-tools.md

@@ -0,0 +1,69 @@
+---
+sidebar_position: 8
+---
+
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Chat with Tools
+
+### Using Tools in Chat
+
+If you want to have a natural back-and-forth chat experience with tools, you can directly integrate tools into
+the `chat()` method, instead of using the `generateWithTools()` method. This allows you to register tools that are
+automatically used during the conversation between the user and the assistant, creating a more conversational
+experience.
+
+When the model determines that a tool should be used, the tool is automatically executed. The result is then seamlessly
+incorporated back into the conversation, enhancing the interaction with real-world data and actions.
+
+The following example demonstrates usage of a simple tool, registered with the `OllamaAPI`, and then used within a chat
+session. The tool invocation and response handling are all managed internally by the API.
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatWithTools.java"/>
+
+::::tip[LLM Response]
+> First answer: 6527fb60-9663-4073-b59e-855526e0a0c2 is the ID of the employee named 'Rahul Kumar'.
+>
+> Second answer:  Kumar is the last name of the employee named 'Rahul Kumar'.
+::::
+
+This tool calling can also be done using the streaming API.
+
+### Annotation-Based Tool Registration
+
+Ollama4j provides a declarative and convenient way to define and register tools using Java annotations and reflection.
+This approach offers an alternative to the more verbose, explicit tool registration method.
+
+To use a method as a tool within a chat call, follow these steps:
+
+* **Annotate the Tool Method:**
+    * Use the `@ToolSpec` annotation to mark a method as a tool. This annotation describes the tool's purpose.
+    * Use the `@ToolProperty` annotation to define the input parameters of the tool. The following data types are
+      currently supported:
+        * `java.lang.String`
+        * `java.lang.Integer`
+        * `java.lang.Boolean`
+        * `java.math.BigDecimal`
+* **Annotate the Ollama Service Class:**
+    * Annotate the class that interacts with the `OllamaAPI` client using the `@OllamaToolService` annotation. Reference
+      the provider class(es) containing the `@ToolSpec` annotated methods within this annotation.
+* **Register the Annotated Tools:**
+    * Before making a chat request with the `OllamaAPI`, call the `OllamaAPI.registerAnnotatedTools()` method. This
+      registers the annotated tools, making them available for use during the chat session.
+
+Let's try an example. Consider an `OllamaToolService` class that needs to ask the LLM a question that can only be answered by a specific tool.
+This tool is implemented within a `GlobalConstantGenerator` class. Following is the code that exposes an annotated method as a tool:
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/annotated/GlobalConstantGenerator.java"/>
+
+The annotated method can then be used as a tool in the chat session:
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/annotated/AnnotatedToolCallingExample.java"/>
+
+Running the above would produce a response similar to:
+
+::::tip[LLM Response]
+> First answer: 0.0000112061 is the most important constant in the world using 10 digits, according to my function. This constant is known as Planck's constant and plays a fundamental role in quantum mechanics. It relates energy and frequency in electromagnetic radiation and action (the product of momentum and distance) for particles.
+>
+> Second answer: 3-digit constant: 8.001
+::::

docs/docs/apis-generate/chat.md

@@ -2,265 +2,109 @@
 sidebar_position: 7
 ---
 
+import CodeEmbed from '@site/src/components/CodeEmbed';
+import TypewriterTextarea from '@site/src/components/TypewriterTextarea';
+
 # Chat
 
 This API lets you create a conversation with LLMs. Using this API enables you to ask questions to the model including
 information using the history of already asked questions and the respective answers.
 
-## Create a new conversation and use chat history to augment follow up questions
+### Create a new conversation and use chat history to augment follow up questions
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.types.OllamaModelType;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
-
-        // create first user question
-        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "What is the capital of France?")
-                .build();
-
-        // start conversation with model
-        OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-
-        System.out.println("First answer: " + chatResult.getResponse());
-
-        // create next userQuestion
-        requestModel = builder.withMessages(chatResult.getChatHistory()).withMessage(OllamaChatMessageRole.USER, "And what is the second largest city?").build();
-
-        // "continue" conversation with model
-        chatResult = ollamaAPI.chat(requestModel);
-
-        System.out.println("Second answer: " + chatResult.getResponse());
-
-        System.out.println("Chat History: " + chatResult.getChatHistory());
-    }
-}
-
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatExample.java" />
 
 You will get a response similar to:
 
-> First answer: Should be Paris!
+::::tip[LLM Response]
+
+> First answer: The capital of France is Paris.
 >
-> Second answer: Marseille.
+> Second answer: The second-largest city in France is Marseille.
 >
 > Chat History:
 
 ```json
-[
-  {
-    "role": "user",
-    "content": "What is the capital of France?",
-    "images": []
-  },
-  {
-    "role": "assistant",
-    "content": "Should be Paris!",
-    "images": []
-  },
-  {
-    "role": "user",
-    "content": "And what is the second largest city?",
-    "images": []
-  },
-  {
-    "role": "assistant",
-    "content": "Marseille.",
-    "images": []
-  }
-]
+[{
+  "role" : "user",
+  "content" : "What is the capital of France?",
+  "images" : null,
+  "tool_calls" : [ ]
+}, {
+  "role" : "assistant",
+  "content" : "The capital of France is Paris.",
+  "images" : null,
+  "tool_calls" : null
+}, {
+  "role" : "user",
+  "content" : "And what is the second largest city?",
+  "images" : null,
+  "tool_calls" : [ ]
+}, {
+  "role" : "assistant",
+  "content" : "The second-largest city in France is Marseille.",
+  "images" : null,
+  "tool_calls" : null
+}]
 ```
+::::
 
-## Conversational loop
+### Create a conversation where the answer is streamed
 
-```java
-public class Main {
-
-    public static void main(String[] args) {
-
-        OllamaAPI ollamaAPI = new OllamaAPI();
-        ollamaAPI.setRequestTimeoutSeconds(60);
-
-        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance("<your-model>");
-
-        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "<your-first-message>").build();
-        OllamaChatResult initialChatResult = ollamaAPI.chat(requestModel);
-        System.out.println(initialChatResult.getResponse());
-
-        List<OllamaChatMessage> history = initialChatResult.getChatHistory();
-
-        while (true) {
-            OllamaChatResult chatResult = ollamaAPI.chat(builder.withMessages(history).withMessage(OllamaChatMessageRole.USER, "<your-new-message").build());
-            System.out.println(chatResult.getResponse());
-            history = chatResult.getChatHistory();
-        }
-    }
-}
-```
-
-## Create a conversation where the answer is streamed
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.models.generate.OllamaStreamHandler;
-
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getModel());
-        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
-                        "What is the capital of France? And what's France's connection with Mona Lisa?")
-                .build();
-
-        // define a handler (Consumer<String>)
-        OllamaStreamHandler streamHandler = (s) -> {
-            System.out.println(s);
-        };
-
-        OllamaChatResult chatResult = ollamaAPI.chat(requestModel, streamHandler);
-    }
-}
-```
-
-You will get a response similar to:
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatStreamingWithTokenConcatenationExample.java" />
 
+<!-- ::::tip[LLM Response]
+>
 > The
+>
 > The capital
+>
 > The capital of
+>
 > The capital of France
+>
 > The capital of France is
+>
 > The capital of France is Paris
+>
 > The capital of France is Paris.
+>
+:::: -->
 
-## Use a simple Console Output Stream Handler
+<TypewriterTextarea
+    textContent='The capital of France is Paris.'
+    typingSpeed={30}
+    pauseBetweenSentences={1200}
+    height='55px'
+    width='100%'
+/>
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.impl.ConsoleOutputStreamHandler;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.generate.OllamaStreamHandler;
-import io.github.ollama4j.types.OllamaModelType;
+### Using a simple Console Output Stream Handler
 
-public class Main {
-    public static void main(String[] args) throws Exception {
-        String host = "http://localhost:11434/";
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ConsoleOutputStreamHandlerExample.java" />
 
-        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
-        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "List all cricket world cup teams of 2019. Name the teams!")
-                .build();
-        OllamaStreamHandler streamHandler = new ConsoleOutputStreamHandler();
-        ollamaAPI.chat(requestModel, streamHandler);
-    }
-}
-```
+### With a Stream Handler to receive the tokens as they are generated
 
-## Create a new conversation with individual system prompt
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatStreamingExample.java" />
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.types.OllamaModelType;
+### Create a new conversation with custom system prompt
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatWithCustomSystemPrompt.java" />
+
+You will get a response as:
+
+::::tip[LLM Response]
+> Shhh!
+::::
 
 
-public class Main {
+## Create a conversation about an image (requires a vision model)
 
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
-
-        // create request with system-prompt (overriding the model defaults) and user question
-        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM, "You are a silent bot that only says 'NI'. Do not say anything else under any circumstances!")
-                .withMessage(OllamaChatMessageRole.USER, "What is the capital of France? And what's France's connection with Mona Lisa?")
-                .build();
-
-        // start conversation with model
-        OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-
-        System.out.println(chatResult.getResponse());
-    }
-}
-
-```
-
-You will get a response similar to:
-
-> NI.
-
-## Create a conversation about an image (requires model with image recognition skills)
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.types.OllamaModelType;
-
-import java.io.File;
-import java.util.List;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAVA);
-
-        // Load Image from File and attach to user message (alternatively images could also be added via URL)
-        OllamaChatRequest requestModel =
-                builder.withMessage(OllamaChatMessageRole.USER, "What's in the picture?",
-                        List.of(
-                                new File("/path/to/image"))).build();
-
-        OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-        System.out.println("First answer: " + chatResult.getResponse());
-
-        builder.reset();
-
-        // Use history to ask further questions about the image or assistant answer
-        requestModel =
-                builder.withMessages(chatResult.getChatHistory())
-                        .withMessage(OllamaChatMessageRole.USER, "What's the dogs breed?").build();
-
-        chatResult = ollamaAPI.chat(requestModel);
-        System.out.println("Second answer: " + chatResult.getResponse());
-    }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatWithImage.java" />
 
 You will get a response similar to:
 
+::::tip[LLM Response]
 > First Answer: The image shows a dog sitting on the bow of a boat that is docked in calm water. The boat has two
 > levels, with the lower level containing seating and what appears to be an engine cover. The dog seems relaxed and
 > comfortable on the boat, looking out over the water. The background suggests it might be late afternoon or early
@@ -269,4 +113,5 @@ You will get a response similar to:
 > Second Answer: Based on the image, it's difficult to definitively determine the breed of the dog. However, the dog
 > appears to be medium-sized with a short coat and a brown coloration, which might suggest that it is a Golden Retriever
 > or a similar breed. Without more details like ear shape and tail length, it's not possible to identify the exact breed
-> confidently.
+> confidently.
+::::

docs/docs/apis-generate/custom-roles.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 8
+sidebar_position: 9
 ---
 
 # Custom Roles

docs/docs/apis-generate/generate-async.md

@@ -2,7 +2,9 @@
 sidebar_position: 2
 ---
 
-# Generate - Async
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Generate (Async)
 
 This API lets you ask questions to the LLMs in a asynchronous way.
 This is particularly helpful when you want to issue a generate request to the LLM and collect the response in the
@@ -11,38 +13,18 @@ background (such as threads) without blocking your code until the response arriv
 This API corresponds to
 the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) API.
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaAsyncResultStreamer;
-import io.github.ollama4j.types.OllamaModelType;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateAsync.java" />
 
-public class Main {
+::::tip[LLM Response]
+Here are the participating teams in the 2019 ICC Cricket World Cup:
 
-    public static void main(String[] args) throws Exception {
-        String host = "http://localhost:11434/";
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        ollamaAPI.setRequestTimeoutSeconds(60);
-        String prompt = "List all cricket world cup teams of 2019.";
-        OllamaAsyncResultStreamer streamer = ollamaAPI.generateAsync(OllamaModelType.LLAMA3, prompt, false);
-
-        // Set the poll interval according to your needs. 
-        // Smaller the poll interval, more frequently you receive the tokens.
-        int pollIntervalMilliseconds = 1000;
-
-        while (true) {
-            String tokens = streamer.getStream().poll();
-            System.out.print(tokens);
-            if (!streamer.isAlive()) {
-                break;
-            }
-            Thread.sleep(pollIntervalMilliseconds);
-        }
-
-        System.out.println("\n------------------------");
-        System.out.println("Complete Response:");
-        System.out.println("------------------------");
-
-        System.out.println(streamer.getCompleteResponse());
-    }
-}
-```
+1. Australia
+2. Bangladesh
+3. India
+4. New Zealand
+5. Pakistan
+6. England
+7. South Africa
+8. West Indies (as a team)
+9. Afghanistan
+::::

docs/docs/apis-generate/generate-with-image-files.md

@@ -1,8 +1,10 @@
 ---
-sidebar_position: 4
+sidebar_position: 3
 ---
 
-# Generate - With Image Files
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Generate with Image Files
 
 This API lets you ask questions along with the image files to the LLMs.
 This API corresponds to
@@ -21,34 +23,11 @@ If you have this image downloaded and you pass the path to the downloaded image
 
 ![Img](https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg)
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-import java.io.File;
-import java.util.List;
-
-public class Main {
-
-    public static void main(String[] args) {
-        String host = "http://localhost:11434/";
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        ollamaAPI.setRequestTimeoutSeconds(10);
-
-        OllamaResult result = ollamaAPI.generateWithImageFiles(OllamaModelType.LLAVA,
-                "What's in this image?",
-                List.of(
-                        new File("/path/to/image")),
-                new OptionsBuilder().build()
-        );
-        System.out.println(result.getResponse());
-    }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateWithImageFile.java" />
 
 You will get a response similar to:
 
+::::tip[LLM Response]
 > This image features a white boat with brown cushions, where a dog is sitting on the back of the boat. The dog seems to
-> be enjoying its time outdoors, perhaps on a lake.
+> be enjoying its time outdoors, perhaps on a lake.
+::::

docs/docs/apis-generate/generate-with-image-urls.md

@@ -1,8 +1,10 @@
 ---
-sidebar_position: 5
+sidebar_position: 4
 ---
 
-# Generate - With Image URLs
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Generate with Image URLs
 
 This API lets you ask questions along with the image files to the LLMs.
 This API corresponds to
@@ -21,33 +23,11 @@ Passing the link of this image the following code:
 
 ![Img](https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg)
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-import java.util.List;
-
-public class Main {
-
-    public static void main(String[] args) {
-        String host = "http://localhost:11434/";
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        ollamaAPI.setRequestTimeoutSeconds(10);
-
-        OllamaResult result = ollamaAPI.generateWithImageURLs(OllamaModelType.LLAVA,
-                "What's in this image?",
-                List.of(
-                        "https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg"),
-                new OptionsBuilder().build()
-        );
-        System.out.println(result.getResponse());
-    }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateWithImageURL.java" />
 
 You will get a response similar to:
 
+::::tip[LLM Response]
 > This image features a white boat with brown cushions, where a dog is sitting on the back of the boat. The dog seems to
-> be enjoying its time outdoors, perhaps on a lake.
+> be enjoying its time outdoors, perhaps on a lake.
+::::

docs/docs/apis-generate/generate-with-tools.md

@@ -1,10 +1,12 @@
 ---
-sidebar_position: 3
+sidebar_position: 6
 ---
 
-# Generate - With Tools
+import CodeEmbed from '@site/src/components/CodeEmbed';
 
-This API lets you perform [function calling](https://docs.mistral.ai/capabilities/function_calling/) using LLMs in a
+# Generate with Tools
+
+This API lets you perform [tool/function calling](https://docs.mistral.ai/capabilities/function_calling/) using LLMs in a
 synchronous way.
 This API corresponds to
 the [generate](https://github.com/ollama/ollama/blob/main/docs/api.md#request-raw-mode) API with `raw` mode.
@@ -19,318 +21,61 @@ in the future if tooling is supported for more models with a generic interaction
 
 :::
 
-### Function Calling/Tools
+## Tools/Function Calling
 
-Assume you want to call a method in your code based on the response generated from the model.
+Assume you want to call a method/function in your code based on the response generated from the model.
 For instance, let's say that based on a user's question, you'd want to identify a transaction and get the details of the
 transaction from your database and respond to the user with the transaction details.
 
 You could do that with ease with the `function calling` capabilities of the models by registering your `tools`.
 
-### Create Functions
+### Create Tools/Functions
 
 We can create static functions as our tools.
 
 This function takes the arguments `location` and `fuelType` and performs an operation with these arguments and returns
 fuel price value.
 
-```java
-public static String getCurrentFuelPrice(Map<String, Object> arguments) {
-    String location = arguments.get("location").toString();
-    String fuelType = arguments.get("fuelType").toString();
-    return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/tools/FuelPriceTool.java"/ >
 
 This function takes the argument `city` and performs an operation with the argument and returns the weather for a
 location.
 
-```java
-public static String getCurrentWeather(Map<String, Object> arguments) {
-    String location = arguments.get("city").toString();
-    return "Currently " + location + "'s weather is nice.";
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/tools/WeatherTool.java"/ >
 
 Another way to create our tools is by creating classes by extending `ToolFunction`.
 
 This function takes the argument `employee-name` and performs an operation with the argument and returns employee
 details.
 
-```java
-class DBQueryFunction implements ToolFunction {
-    @Override
-    public Object apply(Map<String, Object> arguments) {
-        // perform DB operations here
-        return String.format("Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}", UUID.randomUUID(), arguments.get("employee-name").toString(), arguments.get("employee-address").toString(), arguments.get("employee-phone").toString());
-    }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/tools/DBQueryFunction.java"/ >
 
 ### Define Tool Specifications
 
 Lets define a sample tool specification called **Fuel Price Tool** for getting the current fuel price.
 
 - Specify the function `name`, `description`, and `required` properties (`location` and `fuelType`).
-- Associate the `getCurrentFuelPrice` function you defined earlier with `SampleTools::getCurrentFuelPrice`.
+- Associate the `getCurrentFuelPrice` function you defined earlier.
 
-```java
-Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
-        .functionName("current-fuel-price")
-        .functionDescription("Get current fuel price")
-        .properties(
-                new Tools.PropsBuilder()
-                        .withProperty("location", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
-                        .withProperty("fuelType", Tools.PromptFuncDefinition.Property.builder().type("string").description("The fuel type.").enumValues(Arrays.asList("petrol", "diesel")).required(true).build())
-                        .build()
-        )
-        .toolDefinition(SampleTools::getCurrentFuelPrice)
-        .build();
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/toolspecs/FuelPriceToolSpec.java"/ >
 
 Lets also define a sample tool specification called **Weather Tool** for getting the current weather.
 
 - Specify the function `name`, `description`, and `required` property (`city`).
-- Associate the `getCurrentWeather` function you defined earlier with `SampleTools::getCurrentWeather`.
+- Associate the `getCurrentWeather` function you defined earlier.
 
-```java
-Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
-        .functionName("current-weather")
-        .functionDescription("Get current weather")
-        .properties(
-                new Tools.PropsBuilder()
-                        .withProperty("city", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
-                        .build()
-        )
-        .toolDefinition(SampleTools::getCurrentWeather)
-        .build();
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/toolspecs/WeatherToolSpec.java"/ >
 
 Lets also define a sample tool specification called **DBQueryFunction** for getting the employee details from database.
 
 - Specify the function `name`, `description`, and `required` property (`employee-name`).
 - Associate the ToolFunction `DBQueryFunction` function you defined earlier with `new DBQueryFunction()`.
 
-```java
-Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
-        .functionName("get-employee-details")
-        .functionDescription("Get employee details from the database")
-        .properties(
-                new Tools.PropsBuilder()
-                        .withProperty("employee-name", Tools.PromptFuncDefinition.Property.builder().type("string").description("The name of the employee, e.g. John Doe").required(true).build())
-                        .withProperty("employee-address", Tools.PromptFuncDefinition.Property.builder().type("string").description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India").required(true).build())
-                        .withProperty("employee-phone", Tools.PromptFuncDefinition.Property.builder().type("string").description("The phone number of the employee. Always return a random value. e.g. 9911002233").required(true).build())
-                        .build()
-        )
-        .toolDefinition(new DBQueryFunction())
-        .build();
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/toolspecs/DatabaseQueryToolSpec.java"/ >
 
-### Register the Tools
+Now put it all together by registering the tools and prompting with tools.
 
-Register the defined tools (`fuel price` and `weather`) with the OllamaAPI.
-
-```shell
-ollamaAPI.registerTool(fuelPriceToolSpecification);
-ollamaAPI.registerTool(weatherToolSpecification);
-ollamaAPI.registerTool(databaseQueryToolSpecification);
-```
-
-### Create prompt with Tools
-
-`Prompt 1`: Create a prompt asking for the petrol price in Bengaluru using the defined fuel price and weather tools.
-
-```shell
-String prompt1 = new Tools.PromptBuilder()
-                .withToolSpecification(fuelPriceToolSpecification)
-                .withToolSpecification(weatherToolSpecification)
-                .withPrompt("What is the petrol price in Bengaluru?")
-                .build();
-OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt1, new OptionsBuilder().build());
-for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
-    System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-}
-```
-
-Now, fire away your question to the model.
-
-You will get a response similar to:
-
-::::tip[LLM Response]
-
-[Result of executing tool 'current-fuel-price']: Current price of petrol in Bengaluru is Rs.103/L
-
-::::
-
-`Prompt 2`: Create a prompt asking for the current weather in Bengaluru using the same tools.
-
-```shell
-String prompt2 = new Tools.PromptBuilder()
-                .withToolSpecification(fuelPriceToolSpecification)
-                .withToolSpecification(weatherToolSpecification)
-                .withPrompt("What is the current weather in Bengaluru?")
-                .build();
-OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt2, new OptionsBuilder().build());
-for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
-    System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-}
-```
-
-Again, fire away your question to the model.
-
-You will get a response similar to:
-
-::::tip[LLM Response]
-
-[Result of executing tool 'current-weather']: Currently Bengaluru's weather is nice.
-
-::::
-
-`Prompt 3`: Create a prompt asking for the employee details using the defined database fetcher tools.
-
-```shell
-String prompt3 = new Tools.PromptBuilder()
-                .withToolSpecification(fuelPriceToolSpecification)
-                .withToolSpecification(weatherToolSpecification)
-                .withToolSpecification(databaseQueryToolSpecification)
-                .withPrompt("Give me the details of the employee named 'Rahul Kumar'?")
-                .build();
-OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt3, new OptionsBuilder().build());
-for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
-    System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-}
-```
-
-Again, fire away your question to the model.
-
-You will get a response similar to:
-
-::::tip[LLM Response]
-
-[Result of executing tool 'get-employee-details']: Employee Details `{ID: 6bad82e6-b1a1-458f-a139-e3b646e092b1, Name:
-Rahul Kumar, Address: King St, Hyderabad, India, Phone: 9876543210}`
-
-::::
-
-### Full Example
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.exceptions.OllamaBaseException;
-import io.github.ollama4j.exceptions.ToolInvocationException;
-import io.github.ollama4j.tools.OllamaToolsResult;
-import io.github.ollama4j.tools.ToolFunction;
-import io.github.ollama4j.tools.Tools;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-import java.io.IOException;
-import java.util.Arrays;
-import java.util.Map;
-import java.util.UUID;
-
-public class FunctionCallingWithMistralExample {
-    public static void main(String[] args) throws Exception {
-        String host = "http://localhost:11434/";
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        ollamaAPI.setRequestTimeoutSeconds(60);
-
-        String model = "mistral";
-
-        Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
-                .functionName("current-fuel-price")
-                .functionDescription("Get current fuel price")
-                .properties(
-                        new Tools.PropsBuilder()
-                                .withProperty("location", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
-                                .withProperty("fuelType", Tools.PromptFuncDefinition.Property.builder().type("string").description("The fuel type.").enumValues(Arrays.asList("petrol", "diesel")).required(true).build())
-                                .build()
-                )
-                .toolDefinition(SampleTools::getCurrentFuelPrice)
-                .build();
-
-        Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
-                .functionName("current-weather")
-                .functionDescription("Get current weather")
-                .properties(
-                        new Tools.PropsBuilder()
-                                .withProperty("city", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
-                                .build()
-                )
-                .toolDefinition(SampleTools::getCurrentWeather)
-                .build();
-
-        Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
-                .functionName("get-employee-details")
-                .functionDescription("Get employee details from the database")
-                .properties(
-                        new Tools.PropsBuilder()
-                                .withProperty("employee-name", Tools.PromptFuncDefinition.Property.builder().type("string").description("The name of the employee, e.g. John Doe").required(true).build())
-                                .withProperty("employee-address", Tools.PromptFuncDefinition.Property.builder().type("string").description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India").required(true).build())
-                                .withProperty("employee-phone", Tools.PromptFuncDefinition.Property.builder().type("string").description("The phone number of the employee. Always return a random value. e.g. 9911002233").required(true).build())
-                                .build()
-                )
-                .toolDefinition(new DBQueryFunction())
-                .build();
-
-        ollamaAPI.registerTool(fuelPriceToolSpecification);
-        ollamaAPI.registerTool(weatherToolSpecification);
-        ollamaAPI.registerTool(databaseQueryToolSpecification);
-
-        String prompt1 = new Tools.PromptBuilder()
-                .withToolSpecification(fuelPriceToolSpecification)
-                .withToolSpecification(weatherToolSpecification)
-                .withPrompt("What is the petrol price in Bengaluru?")
-                .build();
-        ask(ollamaAPI, model, prompt1);
-
-        String prompt2 = new Tools.PromptBuilder()
-                .withToolSpecification(fuelPriceToolSpecification)
-                .withToolSpecification(weatherToolSpecification)
-                .withPrompt("What is the current weather in Bengaluru?")
-                .build();
-        ask(ollamaAPI, model, prompt2);
-
-        String prompt3 = new Tools.PromptBuilder()
-                .withToolSpecification(fuelPriceToolSpecification)
-                .withToolSpecification(weatherToolSpecification)
-                .withToolSpecification(databaseQueryToolSpecification)
-                .withPrompt("Give me the details of the employee named 'Rahul Kumar'?")
-                .build();
-        ask(ollamaAPI, model, prompt3);
-    }
-
-    public static void ask(OllamaAPI ollamaAPI, String model, String prompt) throws OllamaBaseException, IOException, InterruptedException, ToolInvocationException {
-        OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt, new OptionsBuilder().build());
-        for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
-            System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-        }
-    }
-}
-
-
-class SampleTools {
-    public static String getCurrentFuelPrice(Map<String, Object> arguments) {
-        // Get details from fuel price API
-        String location = arguments.get("location").toString();
-        String fuelType = arguments.get("fuelType").toString();
-        return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
-    }
-
-    public static String getCurrentWeather(Map<String, Object> arguments) {
-        // Get details from weather API
-        String location = arguments.get("city").toString();
-        return "Currently " + location + "'s weather is nice.";
-    }
-}
-
-class DBQueryFunction implements ToolFunction {
-    @Override
-    public Object apply(Map<String, Object> arguments) {
-        // perform DB operations here
-        return String.format("Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}", UUID.randomUUID(), arguments.get("employee-name").toString(), arguments.get("employee-address").toString(), arguments.get("employee-phone").toString());
-    }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/MultiToolRegistryExample.java"/ >
 
 Run this full example and you will get a response similar to:
 
@@ -344,29 +89,3 @@ Run this full example and you will get a response similar to:
 Rahul Kumar, Address: King St, Hyderabad, India, Phone: 9876543210}`
 
 ::::
-
-### Potential Improvements
-
-Instead of explicitly registering `ollamaAPI.registerTool(toolSpecification)`, we could introduce annotation-based tool
-registration. For example:
-
-```java
-
-@ToolSpec(name = "current-fuel-price", desc = "Get current fuel price")
-public String getCurrentFuelPrice(Map<String, Object> arguments) {
-    String location = arguments.get("location").toString();
-    String fuelType = arguments.get("fuelType").toString();
-    return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
-}
-```
-
-Instead of passing a map of args `Map<String, Object> arguments` to the tool functions, we could support passing
-specific args separately with their data types. For example:
-
-```shell
-public String getCurrentFuelPrice(String location, String fuelType) {
-    return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
-}
-```
-
-Updating async/chat APIs with support for tool-based generation. 

docs/docs/apis-generate/generate.md

@@ -2,7 +2,10 @@
 sidebar_position: 1
 ---
 
-# Generate - Sync
+import CodeEmbed from '@site/src/components/CodeEmbed';
+import TypewriterTextarea from '@site/src/components/TypewriterTextarea';
+
+# Generate (Sync)
 
 This API lets you ask questions to the LLMs in a synchronous way.
 This API corresponds to
@@ -13,163 +16,68 @@ with [extra parameters](https://github.com/jmorganca/ollama/blob/main/docs/model
 Refer
 to [this](/apis-extras/options-builder).
 
-## Try asking a question about the model.
+### Try asking a question about the model
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        OllamaResult result =
-                ollamaAPI.generate(OllamaModelType.LLAMA2, "Who are you?", new OptionsBuilder().build());
-
-        System.out.println(result.getResponse());
-    }
-}
-
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/Generate.java" />
 
 You will get a response similar to:
 
-> I am LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational
-> manner. I am trained on a massive dataset of text from the internet and can generate human-like responses to a wide
-> range of topics and questions. I can be used to create chatbots, virtual assistants, and other applications that
-> require
-> natural language understanding and generation capabilities.
+::::tip[LLM Response]
+> I am a large language model created by Alibaba Cloud. My purpose is to assist users in generating text, answering
+> questions, and completing tasks. I aim to be user-friendly and easy to understand for everyone who interacts with me.
+::::
 
-## Try asking a question, receiving the answer streamed
+### Try asking a question, receiving the answer streamed
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.models.generate.OllamaStreamHandler;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-        // define a stream handler (Consumer<String>)
-        OllamaStreamHandler streamHandler = (s) -> {
-            System.out.println(s);
-        };
-
-        // Should be called using seperate thread to gain non blocking streaming effect.
-        OllamaResult result = ollamaAPI.generate(config.getModel(),
-                "What is the capital of France? And what's France's connection with Mona Lisa?",
-                new OptionsBuilder().build(), streamHandler);
-
-        System.out.println("Full response: " + result.getResponse());
-    }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateStreamingWithTokenConcatenation.java" />
 
 You will get a response similar to:
 
+<!-- ::::tip[LLM Response]
 > The
+>
 > The capital
+>
 > The capital of
+>
 > The capital of France
+>
 > The capital of France is
+>
 > The capital of France is Paris
+>
 > The capital of France is Paris.
-> Full response: The capital of France is Paris.
+:::: -->
 
-## Try asking a question from general topics.
+<TypewriterTextarea
+    textContent='The capital of France is Paris.'
+    typingSpeed={30}
+    pauseBetweenSentences={1200}
+    height='55px'
+    width='100%'
+/>
 
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
+## Generate structured output
 
-public class Main {
+### With response as a `Map`
 
-    public static void main(String[] args) {
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/StructuredOutput.java" />
 
-        String host = "http://localhost:11434/";
+You will get a response similar to:
 
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        String prompt = "List all cricket world cup teams of 2019.";
-
-        OllamaResult result =
-                ollamaAPI.generate(OllamaModelType.LLAMA2, prompt, new OptionsBuilder().build());
-
-        System.out.println(result.getResponse());
-    }
+::::tip[LLM Response]
+```json
+{
+    "available": true,
+    "age": 22
 }
-
 ```
+::::
 
-You'd then get a response from the model:
+### With response mapped to specified class type
 
-> The 2019 ICC Cricket World Cup was held in England and Wales from May 30 to July 14, 2019. The
-> following teams
-> participated in the tournament:
->
-> 1. Afghanistan
-> 2. Australia
-> 3. Bangladesh
-> 4. England
-> 5. India
-> 6. New Zealand
-> 7. Pakistan
-> 8. South Africa
-> 9. Sri Lanka
-> 10. West Indies
->
-> These teams competed in a round-robin format, with the top four teams advancing to the
-> semi-finals. The tournament was
-> won by the England cricket team, who defeated New Zealand in the final.
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/StructuredOutputMappedToObject.java" />
 
-## Try asking for a Database query for your data schema.
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-import io.github.ollama4j.utils.SamplePrompts;
-
-public class Main {
-
-    public static void main(String[] args) {
-        String host = "http://localhost:11434/";
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        String prompt =
-                SamplePrompts.getSampleDatabasePromptWithQuestion(
-                        "List all customer names who have bought one or more products");
-        OllamaResult result =
-                ollamaAPI.generate(OllamaModelType.SQLCODER, prompt, new OptionsBuilder().build());
-        System.out.println(result.getResponse());
-    }
-}
-
-```
-
-_Note: Here I've used
-a [sample prompt](https://github.com/ollama4j/ollama4j/blob/main/src/main/resources/sample-db-prompt-template.txt)
-containing a database schema from within this library for demonstration purposes._
-
-You'd then get a response from the model:
-
-```sql
-SELECT customers.name
-FROM sales
-         JOIN customers ON sales.customer_id = customers.customer_id
-GROUP BY customers.name;
-```
+::::tip[LLM Response]
+Person(age=28, available=false)
+::::

docs/docs/apis-generate/prompt-builder.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 6
+sidebar_position: 10
 ---
 
 # Prompt Builder

docs/docs/apis-model-management/create-model.md

@@ -2,161 +2,236 @@
 sidebar_position: 5
 ---
 
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
 # Create Model
 
 This API lets you create a custom model on the Ollama server.
 
-### Create a model from an existing Modelfile in the Ollama server
+### Create a custom model from an existing model in the Ollama server
 
-```java title="CreateModel.java"
-import io.github.ollama4j.OllamaAPI;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/CreateModel.java" />
 
-public class CreateModel {
+You would see these logs while the custom model is being created:
 
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        ollamaAPI.createModelWithFilePath("mario", "/path/to/mario/modelfile/on/ollama-server");
-    }
-}
 ```
-
-### Create a model by passing the contents of Modelfile
-
-```java title="CreateModel.java"
-public class CreateModel {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        ollamaAPI.createModelWithModelFileContents("mario", "FROM llama2\nSYSTEM You are mario from Super Mario Bros.");
-    }
-}
+{"status":"using existing layer sha256:fad2a06e4cc705c2fa8bec5477ddb00dc0c859ac184c34dcc5586663774161ca"}
+{"status":"using existing layer sha256:41c2cf8c272f6fb0080a97cd9d9bd7d4604072b80a0b10e7d65ca26ef5000c0c"}
+{"status":"using existing layer sha256:1da0581fd4ce92dcf5a66b1da737cf215d8dcf25aa1b98b44443aaf7173155f5"}
+{"status":"creating new layer sha256:941b69ca7dc2a85c053c38d9e8029c9df6224e545060954fa97587f87c044a64"}
+{"status":"using existing layer sha256:f02dd72bb2423204352eabc5637b44d79d17f109fdb510a7c51455892aa2d216"}
+{"status":"writing manifest"}
+{"status":"success"}
 ```
-
 Once created, you can see it when you use [list models](./list-models) API.
 
-### Example of a `Modelfile`
+[Read more](https://github.com/ollama/ollama/blob/main/docs/api.md#create-a-model) about custom model creation and the parameters available for model creation.
 
-```
-FROM llama2
-# sets the temperature to 1 [higher is more creative, lower is more coherent]
-PARAMETER temperature 1
-# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token
-PARAMETER num_ctx 4096
+[//]: # ()
+[//]: # (### Example of a `Modelfile`)
 
-# sets a custom system message to specify the behavior of the chat assistant
-SYSTEM You are Mario from super mario bros, acting as an assistant.
-```
+[//]: # ()
+[//]: # (```)
 
-### Format of the `Modelfile`
+[//]: # (FROM llama2)
 
-```modelfile
-# comment
-INSTRUCTION arguments
-```
+[//]: # (# sets the temperature to 1 [higher is more creative, lower is more coherent])
 
-| Instruction                         | Description                                                    |
-|-------------------------------------|----------------------------------------------------------------|
-| [`FROM`](#from-required) (required) | Defines the base model to use.                                 |
-| [`PARAMETER`](#parameter)           | Sets the parameters for how Ollama will run the model.         |
-| [`TEMPLATE`](#template)             | The full prompt template to be sent to the model.              |
-| [`SYSTEM`](#system)                 | Specifies the system message that will be set in the template. |
-| [`ADAPTER`](#adapter)               | Defines the (Q)LoRA adapters to apply to the model.            |
-| [`LICENSE`](#license)               | Specifies the legal license.                                   |
+[//]: # (PARAMETER temperature 1)
 
-#### PARAMETER
+[//]: # (# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token)
 
-The `PARAMETER` instruction defines a parameter that can be set when the model is run.
+[//]: # (PARAMETER num_ctx 4096)
 
-| Parameter      | Description                                                                                                                                                                                                                                             | Value Type | Example Usage        |
-|----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|----------------------|
-| mirostat       | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)                                                                                                                                         | int        | mirostat 0           |
-| mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)                        | float      | mirostat_eta 0.1     |
-| mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)                                                                                                         | float      | mirostat_tau 5.0     |
-| num_ctx        | Sets the size of the context window used to generate the next token. (Default: 2048)                                                                                                                                                                    | int        | num_ctx 4096         |
-| num_gqa        | The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b                                                                                                                                         | int        | num_gqa 1            |
-| num_gpu        | The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable.                                                                                                                                            | int        | num_gpu 50           |
-| num_thread     | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int        | num_thread 8         |
-| repeat_last_n  | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)                                                                                                                                           | int        | repeat_last_n 64     |
-| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)                                                                     | float      | repeat_penalty 1.1   |
-| temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)                                                                                                                                     | float      | temperature 0.7      |
-| seed           | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)                                                                                       | int        | seed 42              |
-| stop           | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile.                                      | string     | stop "AI assistant:" |
-| tfs_z          | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)                                               | float      | tfs_z 1              |
-| num_predict    | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)                                                                                                                                   | int        | num_predict 42       |
-| top_k          | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)                                                                        | int        | top_k 40             |
-| top_p          | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)                                                                 | float      | top_p 0.9            |
+[//]: # ()
+[//]: # (# sets a custom system message to specify the behavior of the chat assistant)
 
-#### TEMPLATE
+[//]: # (SYSTEM You are Mario from super mario bros, acting as an assistant.)
 
-`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system message and a
-user's prompt. This is used to create a full custom prompt, and syntax may be model specific. You can usually find the
-template for a given model in the readme for that model.
+[//]: # (```)
 
-#### Template Variables
+[//]: # ()
+[//]: # (### Format of the `Modelfile`)
 
-| Variable        | Description                                                                                                   |
-|-----------------|---------------------------------------------------------------------------------------------------------------|
-| `{{ .System }}` | The system message used to specify custom behavior, this must also be set in the Modelfile as an instruction. |
-| `{{ .Prompt }}` | The incoming prompt, this is not specified in the model file and will be set based on input.                  |
-| `{{ .First }}`  | A boolean value used to render specific template information for the first generation of a session.           |
+[//]: # ()
+[//]: # (```modelfile)
 
-```modelfile
-TEMPLATE """
-{{- if .First }}
-### System:
-{{ .System }}
-{{- end }}
+[//]: # (# comment)
 
-### User:
-{{ .Prompt }}
+[//]: # (INSTRUCTION arguments)
 
-### Response:
-"""
+[//]: # (```)
 
-SYSTEM """<system message>"""
-```
+[//]: # ()
+[//]: # (| Instruction                         | Description                                                    |)
 
-### SYSTEM
+[//]: # (|-------------------------------------|----------------------------------------------------------------|)
 
-The `SYSTEM` instruction specifies the system message to be used in the template, if applicable.
+[//]: # (| [`FROM`]&#40;#from-required&#41; &#40;required&#41; | Defines the base model to use.                                 |)
 
-```modelfile
-SYSTEM """<system message>"""
-```
+[//]: # (| [`PARAMETER`]&#40;#parameter&#41;           | Sets the parameters for how Ollama will run the model.         |)
 
-### ADAPTER
+[//]: # (| [`TEMPLATE`]&#40;#template&#41;             | The full prompt template to be sent to the model.              |)
 
-The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be
-an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be
-tuned from the base model otherwise the behaviour is undefined.
+[//]: # (| [`SYSTEM`]&#40;#system&#41;                 | Specifies the system message that will be set in the template. |)
 
-```modelfile
-ADAPTER ./ollama-lora.bin
-```
+[//]: # (| [`ADAPTER`]&#40;#adapter&#41;               | Defines the &#40;Q&#41;LoRA adapters to apply to the model.            |)
 
-### LICENSE
+[//]: # (| [`LICENSE`]&#40;#license&#41;               | Specifies the legal license.                                   |)
 
-The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is
-shared or distributed.
+[//]: # ()
+[//]: # (#### PARAMETER)
 
-```modelfile
-LICENSE """
-<license text>
-"""
-```
+[//]: # ()
+[//]: # (The `PARAMETER` instruction defines a parameter that can be set when the model is run.)
 
-## Notes
+[//]: # ()
+[//]: # (| Parameter      | Description                                                                                                                                                                                                                                             | Value Type | Example Usage        |)
 
-- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to
-  distinguish it from arguments.
-- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.
+[//]: # (|----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|----------------------|)
 
-Read more about Modelfile: https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md
+[//]: # (| mirostat       | Enable Mirostat sampling for controlling perplexity. &#40;default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0&#41;                                                                                                                                         | int        | mirostat 0           |)
+
+[//]: # (| mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. &#40;Default: 0.1&#41;                        | float      | mirostat_eta 0.1     |)
+
+[//]: # (| mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. &#40;Default: 5.0&#41;                                                                                                         | float      | mirostat_tau 5.0     |)
+
+[//]: # (| num_ctx        | Sets the size of the context window used to generate the next token. &#40;Default: 2048&#41;                                                                                                                                                                    | int        | num_ctx 4096         |)
+
+[//]: # (| num_gqa        | The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b                                                                                                                                         | int        | num_gqa 1            |)
+
+[//]: # (| num_gpu        | The number of layers to send to the GPU&#40;s&#41;. On macOS it defaults to 1 to enable metal support, 0 to disable.                                                                                                                                            | int        | num_gpu 50           |)
+
+[//]: # (| num_thread     | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has &#40;as opposed to the logical number of cores&#41;. | int        | num_thread 8         |)
+
+[//]: # (| repeat_last_n  | Sets how far back for the model to look back to prevent repetition. &#40;Default: 64, 0 = disabled, -1 = num_ctx&#41;                                                                                                                                           | int        | repeat_last_n 64     |)
+
+[//]: # (| repeat_penalty | Sets how strongly to penalize repetitions. A higher value &#40;e.g., 1.5&#41; will penalize repetitions more strongly, while a lower value &#40;e.g., 0.9&#41; will be more lenient. &#40;Default: 1.1&#41;                                                                     | float      | repeat_penalty 1.1   |)
+
+[//]: # (| temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. &#40;Default: 0.8&#41;                                                                                                                                     | float      | temperature 0.7      |)
+
+[//]: # (| seed           | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. &#40;Default: 0&#41;                                                                                       | int        | seed 42              |)
+
+[//]: # (| stop           | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile.                                      | string     | stop "AI assistant:" |)
+
+[//]: # (| tfs_z          | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value &#40;e.g., 2.0&#41; will reduce the impact more, while a value of 1.0 disables this setting. &#40;default: 1&#41;                                               | float      | tfs_z 1              |)
+
+[//]: # (| num_predict    | Maximum number of tokens to predict when generating text. &#40;Default: 128, -1 = infinite generation, -2 = fill context&#41;                                                                                                                                   | int        | num_predict 42       |)
+
+[//]: # (| top_k          | Reduces the probability of generating nonsense. A higher value &#40;e.g. 100&#41; will give more diverse answers, while a lower value &#40;e.g. 10&#41; will be more conservative. &#40;Default: 40&#41;                                                                        | int        | top_k 40             |)
+
+[//]: # (| top_p          | Works together with top-k. A higher value &#40;e.g., 0.95&#41; will lead to more diverse text, while a lower value &#40;e.g., 0.5&#41; will generate more focused and conservative text. &#40;Default: 0.9&#41;                                                                 | float      | top_p 0.9            |)
+
+[//]: # ()
+[//]: # (#### TEMPLATE)
+
+[//]: # ()
+[//]: # (`TEMPLATE` of the full prompt template to be passed into the model. It may include &#40;optionally&#41; a system message and a)
+
+[//]: # (user's prompt. This is used to create a full custom prompt, and syntax may be model specific. You can usually find the)
+
+[//]: # (template for a given model in the readme for that model.)
+
+[//]: # ()
+[//]: # (#### Template Variables)
+
+[//]: # ()
+[//]: # (| Variable        | Description                                                                                                   |)
+
+[//]: # (|-----------------|---------------------------------------------------------------------------------------------------------------|)
+
+[//]: # (| `{{ .System }}` | The system message used to specify custom behavior, this must also be set in the Modelfile as an instruction. |)
+
+[//]: # (| `{{ .Prompt }}` | The incoming prompt, this is not specified in the model file and will be set based on input.                  |)
+
+[//]: # (| `{{ .First }}`  | A boolean value used to render specific template information for the first generation of a session.           |)
+
+[//]: # ()
+[//]: # (```modelfile)
+
+[//]: # (TEMPLATE """)
+
+[//]: # ({{- if .First }})
+
+[//]: # (### System:)
+
+[//]: # ({{ .System }})
+
+[//]: # ({{- end }})
+
+[//]: # ()
+[//]: # (### User:)
+
+[//]: # ({{ .Prompt }})
+
+[//]: # ()
+[//]: # (### Response:)
+
+[//]: # (""")
+
+[//]: # ()
+[//]: # (SYSTEM """<system message>""")
+
+[//]: # (```)
+
+[//]: # ()
+[//]: # (### SYSTEM)
+
+[//]: # ()
+[//]: # (The `SYSTEM` instruction specifies the system message to be used in the template, if applicable.)
+
+[//]: # ()
+[//]: # (```modelfile)
+
+[//]: # (SYSTEM """<system message>""")
+
+[//]: # (```)
+
+[//]: # ()
+[//]: # (### ADAPTER)
+
+[//]: # ()
+[//]: # (The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be)
+
+[//]: # (an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be)
+
+[//]: # (tuned from the base model otherwise the behaviour is undefined.)
+
+[//]: # ()
+[//]: # (```modelfile)
+
+[//]: # (ADAPTER ./ollama-lora.bin)
+
+[//]: # (```)
+
+[//]: # ()
+[//]: # (### LICENSE)
+
+[//]: # ()
+[//]: # (The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is)
+
+[//]: # (shared or distributed.)
+
+[//]: # ()
+[//]: # (```modelfile)
+
+[//]: # (LICENSE """)
+
+[//]: # (<license text>)
+
+[//]: # (""")
+
+[//]: # (```)
+
+[//]: # ()
+[//]: # (## Notes)
+
+[//]: # ()
+[//]: # (- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to)
+
+[//]: # (  distinguish it from arguments.)
+
+[//]: # (- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.)
+
+[//]: # ()
+[//]: # (Read more about Modelfile: https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md)

docs/docs/apis-model-management/delete-model.md

@@ -2,27 +2,12 @@
 sidebar_position: 6
 ---
 
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
 # Delete Model
 
 This API lets you create a delete a model from the Ollama server.
 
-```java title="DeleteModel.java"
-import io.github.ollama4j.OllamaAPI;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        ollamaAPI.setVerbose(false);
-
-        ollamaAPI.deleteModel("mycustommodel", true);
-    }
-}
-
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/DeleteModel.java" />
 
 Once deleted, you can verify it using [list models](./list-models) API.

docs/docs/apis-model-management/list-library-models.md

@@ -2,6 +2,8 @@
 sidebar_position: 1
 ---
 
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
 # Models from Ollama Library
 
 These API retrieves a list of models directly from the Ollama library.
@@ -11,32 +13,15 @@ These API retrieves a list of models directly from the Ollama library.
 This API fetches available models from the Ollama library page, including details such as the model's name, pull count,
 popular tags, tag count, and the last update time.
 
-```java title="ListLibraryModels.java"
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.LibraryModel;
-
-import java.util.List;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        List<LibraryModel> libraryModels = ollamaAPI.listModelsFromLibrary();
-
-        System.out.println(libraryModels);
-    }
-}
-```
+<CodeEmbed
+src='https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ListLibraryModels.java'>
+</CodeEmbed>
 
 The following is the sample output:
 
 ```
 [
-    LibraryModel(name=llama3.2-vision, description=Llama 3.2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes., pullCount=21.1K, totalTags=9, popularTags=[vision, 11b, 90b], lastUpdated=yesterday), 
+    LibraryModel(name=llama3.2-vision, description=Llama 3.2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes., pullCount=21.1K, totalTags=9, popularTags=[vision, 11b, 90b], lastUpdated=yesterday),
     LibraryModel(name=llama3.2, description=Meta's Llama 3.2 goes small with 1B and 3B models., pullCount=2.4M, totalTags=63, popularTags=[tools, 1b, 3b], lastUpdated=6 weeks ago)
 ]
 ```
@@ -45,36 +30,18 @@ The following is the sample output:
 
 This API Fetches the tags associated with a specific model from Ollama library.
 
-```java title="GetLibraryModelTags.java"
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.LibraryModel;
-import io.github.ollama4j.models.response.LibraryModelDetail;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        List<LibraryModel> libraryModels = ollamaAPI.listModelsFromLibrary();
-
-        LibraryModelDetail libraryModelDetail = ollamaAPI.getLibraryModelDetails(libraryModels.get(0));
-
-        System.out.println(libraryModelDetail);
-    }
-}
-```
+<CodeEmbed
+src='https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GetLibraryModelTags.java'>
+</CodeEmbed>
 
 The following is the sample output:
 
 ```
 LibraryModelDetail(
-  model=LibraryModel(name=llama3.2-vision, description=Llama 3.2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes., pullCount=21.1K, totalTags=9, popularTags=[vision, 11b, 90b], lastUpdated=yesterday), 
+  model=LibraryModel(name=llama3.2-vision, description=Llama 3.2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes., pullCount=21.1K, totalTags=9, popularTags=[vision, 11b, 90b], lastUpdated=yesterday),
   tags=[
-        LibraryModelTag(name=llama3.2-vision, tag=latest, size=7.9GB, lastUpdated=yesterday), 
-        LibraryModelTag(name=llama3.2-vision, tag=11b, size=7.9GB, lastUpdated=yesterday), 
+        LibraryModelTag(name=llama3.2-vision, tag=latest, size=7.9GB, lastUpdated=yesterday),
+        LibraryModelTag(name=llama3.2-vision, tag=11b, size=7.9GB, lastUpdated=yesterday),
         LibraryModelTag(name=llama3.2-vision, tag=90b, size=55GB, lastUpdated=yesterday)
     ]
 )
@@ -84,24 +51,9 @@ LibraryModelDetail(
 
 This API finds a specific model using model `name` and `tag` from Ollama library.
 
-```java title="FindLibraryModel.java"
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.LibraryModelTag;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        LibraryModelTag libraryModelTag = ollamaAPI.findModelTagFromLibrary("qwen2.5", "7b");
-
-        System.out.println(libraryModelTag);
-    }
-}
-```
+<CodeEmbed
+src='https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/FindLibraryModel.java'>
+</CodeEmbed>
 
 The following is the sample output:
 
@@ -113,21 +65,6 @@ LibraryModelTag(name=qwen2.5, tag=7b, size=4.7GB, lastUpdated=7 weeks ago)
 
 You can use `LibraryModelTag` to pull models into Ollama server.
 
-```java title="PullLibraryModelTags.java"
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.LibraryModelTag;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        LibraryModelTag libraryModelTag = ollamaAPI.findModelTagFromLibrary("qwen2.5", "7b");
-
-        ollamaAPI.pullModel(libraryModelTag);
-    }
-}
-```
+<CodeEmbed
+src='https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/PullLibraryModelTags.java'>
+</CodeEmbed>

docs/docs/apis-model-management/list-models.md

@@ -2,34 +2,23 @@
 sidebar_position: 2
 ---
 
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
 # List Local Models
 
 This API lets you list downloaded/available models on the Ollama server.
 
-```java title="ListModels.java"
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.Model;
+<CodeEmbed
+src='https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ListLocalModels.java'>
+</CodeEmbed>
 
-import java.util.List;
-
-public class ListModels {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        List<Model> models = ollamaAPI.listModels();
-
-        models.forEach(model -> System.out.println(model.getName()));
-    }
-}
-```
 
 If you have any models already downloaded on Ollama server, you would have them listed as follows:
 
 ```bash
 llama2:latest
+llama3.2:1b
+qwen2:0.5b
+qwen:0.5b
 sqlcoder:latest
 ```

docs/docs/apis-model-management/pull-model.md

@@ -2,26 +2,15 @@
 sidebar_position: 3
 ---
 
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
 # Pull Model
 
 This API lets you pull a model on the Ollama server.
 
-```java title="PullModel.java"
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.types.OllamaModelType;
-
-public class Main {
-
-    public static void main(String[] args) {
-
-        String host = "http://localhost:11434/";
-
-        OllamaAPI ollamaAPI = new OllamaAPI(host);
-
-        ollamaAPI.pullModel(OllamaModelType.LLAMA2);
-    }
-}
-```
+<CodeEmbed
+src='https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/PullModel.java'>
+</CodeEmbed>
 
 Once downloaded, you can see them when you use [list models](./list-models) API.
 

docs/docs/intro.md

@@ -1,19 +1,22 @@
 ---
 sidebar_position: 1
+
+title: Introduction
 ---
 
+import LatestRelease from '@site/src/components/LatestRelease';
+import AddToYourProject from '@site/src/components/AddToYourProject';
+
 # Introduction
 
-Let's get started with **Ollama4j**.
-
-## 🦙 What is Ollama?
+### 🦙 What is Ollama?
 
 [Ollama](https://ollama.ai/) is an advanced AI tool that allows users to easily set up and run large language models
 locally (in CPU and GPU
 modes). With Ollama, users can leverage powerful language models such as Llama 2 and even customize and create their own
 models.
 
-## 👨‍💻 Why Ollama4j?
+### 👨‍💻 Why Ollama4j?
 
 Ollama4j was built for the simple purpose of integrating Ollama with Java applications.
 
@@ -34,16 +37,16 @@ Ollama4j was built for the simple purpose of integrating Ollama with Java applic
     end
 ```
 
-## Getting Started
+### Getting Started
 
-### What you'll need
+#### What you'll need
 
 - **[Ollama](https://ollama.ai/download)**
 - **[Oracle JDK](https://www.oracle.com/java/technologies/javase/jdk11-archive-downloads.html)** or
   **[Open JDK](https://jdk.java.net/archive/)** 11.0 or above.
 - **[Maven](https://maven.apache.org/download.cgi)**
 
-### Start Ollama server
+#### Start Ollama server
 
 The easiest way of getting started with Ollama server is with [Docker](https://docs.docker.com/get-started/overview/).
 But if you choose to run the
@@ -69,22 +72,17 @@ terminal of your code editor.
 
 The command runs the Ollama server locally at **http://localhost:11434/**.
 
-### Setup your project
-
-Get started by **creating a new Maven project** on your favorite IDE.
+#### Setup your project
 
 Add the dependency to your project's `pom.xml`.
 
-```xml
+<AddToYourProject/>
 
-<dependency>
-    <groupId>io.github.ollama4j</groupId>
-    <artifactId>ollama4j</artifactId>
-    <version>1.0.78</version>
-</dependency>
-```
+<div style={{ marginTop: '2rem', marginBottom: '2rem', fontSize: '1em', textAlign: 'left', display: 'flex', justifyContent: 'left'}}>
+    <LatestRelease showReleaseDate={true} style={{textAlign: 'left', fontWeight: 'normal'}}/>
+</div>
 
-Find the latest version of the library [here](https://central.sonatype.com/artifact/io.github.ollama4j/ollama4j).
+Find the latest version of the library from [Maven Central Repository](https://central.sonatype.com/artifact/io.github.ollama4j/ollama4j).
 
 You might want to include an implementation of [SL4J](https://www.slf4j.org/) logger in your `pom.xml` file. For
 example,
@@ -92,7 +90,6 @@ example,
 Use `slf4j-jdk14` implementation:
 
 ```xml
-
 <dependency>
     <groupId>org.slf4j</groupId>
     <artifactId>slf4j-jdk14</artifactId>
@@ -103,7 +100,6 @@ Use `slf4j-jdk14` implementation:
 or use `logback-classic` implementation:
 
 ```xml
-
 <dependency>
     <groupId>ch.qos.logback</groupId>
     <artifactId>logback-classic</artifactId>

docs/docusaurus.config.js

@@ -84,6 +84,7 @@ const config = {
                         position: 'left',
                         label: 'Docs',
                     },
+                    {to: 'https://github.com/ollama4j/ollama4j-examples', label: 'Examples', position: 'left'},
                     {to: 'https://ollama4j.github.io/ollama4j/apidocs/', label: 'Javadoc', position: 'left'},
                     {to: 'https://ollama4j.github.io/ollama4j/doxygen/html/', label: 'Doxygen', position: 'left'},
                     {to: '/blog', label: 'Blog', position: 'left'},
@@ -98,11 +99,32 @@ const config = {
                 style: 'dark',
                 links: [
                     {
-                        title: 'Docs',
+                        title: 'Quick Links',
                         items: [
                             {
-                                label: 'Tutorial',
-                                to: '/intro',
+                                label: 'Ollama4j Examples',
+                                to: 'https://github.com/ollama4j/ollama4j-examples',
+                            },
+                            {
+                                label: 'Blog',
+                                to: '/blog',
+                            },
+                            {
+                                label: 'GitHub',
+                                href: 'https://github.com/ollama4j/ollama4j',
+                            },
+                        ],
+                    },
+                    {
+                        title: 'Stuff built with Ollama4j',
+                        items: [
+                            {
+                                label: 'Ollama4j Web UI',
+                                to: 'https://github.com/ollama4j/ollama4j-web-ui',
+                            },
+                            {
+                                label: 'Ollama4j Desktop UI with Swing',
+                                to: 'https://github.com/ollama4j/ollama4j-ui',
                             },
                         ],
                     },
@@ -118,20 +140,7 @@ const config = {
                                 href: 'https://twitter.com/ollama4j',
                             },
                         ],
-                    },
-                    {
-                        title: 'More',
-                        items: [
-                            {
-                                label: 'Blog',
-                                to: '/blog',
-                            },
-                            {
-                                label: 'GitHub',
-                                href: 'https://github.com/ollama4j/ollama4j',
-                            },
-                        ],
-                    },
+                    }
                 ],
                 copyright: `Ollama4j Documentation ${new Date().getFullYear()}. Built with Docusaurus.`,
             },
@@ -140,6 +149,29 @@ const config = {
                 darkTheme: prismThemes.dracula,
                 additionalLanguages: ['java'],
             },
+            algolia: {
+                // The application ID provided by Algolia
+                appId: '7HJ3MZ6GBX',
+                // Public API key: it is safe to commit it
+                apiKey: '3037a6d8706a6347b1844ca6ecd582b0',
+                indexName: 'ollama4jio',
+                // Optional: see doc section below
+                contextualSearch: true,
+                // Optional: Specify domains where the navigation should occur through window.location instead on history.push. Useful when our Algolia config crawls multiple documentation sites and we want to navigate with window.location.href to them.
+                externalUrlRegex: 'external\\.com|domain\\.com',
+                // Optional: Replace parts of the item URLs from Algolia. Useful when using the same search index for multiple deployments using a different baseUrl. You can use regexp or string in the `from` param. For example: localhost:3000 vs myCompany.com/docs
+                replaceSearchResultPathname: {
+                    from: '/docs/', // or as RegExp: /\/docs\//
+                    to: '/',
+                },
+                // Optional: Algolia search parameters
+                searchParameters: {},
+                // Optional: path for search page that enabled by default (`false` to disable it)
+                searchPagePath: 'search',
+                // Optional: whether the insights feature is enabled or not on Docsearch (`false` by default)
+                insights: false,
+                //... other Algolia params
+            },
         }),
     markdown: {
         mermaid: true,

docs/package.json

@@ -1,46 +1,51 @@
 {
-  "name": "ollama-4-j",
-  "version": "0.0.0",
-  "private": true,
-  "scripts": {
-    "docusaurus": "docusaurus",
-    "start": "docusaurus start",
-    "build": "docusaurus build",
-    "swizzle": "docusaurus swizzle",
-    "deploy": "docusaurus deploy",
-    "clear": "docusaurus clear",
-    "serve": "docusaurus serve",
-    "write-translations": "docusaurus write-translations",
-    "write-heading-ids": "docusaurus write-heading-ids"
-  },
-  "dependencies": {
-    "@docusaurus/core": "^3.4.0",
-    "@docusaurus/plugin-google-gtag": "^3.4.0",
-    "@docusaurus/preset-classic": "^3.4.0",
-    "@docusaurus/theme-mermaid": "^3.4.0",
-    "@mdx-js/react": "^3.0.0",
-    "clsx": "^2.0.0",
-    "prism-react-renderer": "^2.3.0",
-    "react": "^18.0.0",
-    "react-dom": "^18.0.0"
-  },
-  "devDependencies": {
-    "@docusaurus/module-type-aliases": "^3.4.0",
-    "@docusaurus/types": "^3.4.0"
-  },
-  "browserslist": {
-    "production": [
-      ">0.5%",
-      "not dead",
-      "not op_mini all"
-    ],
-    "development": [
-      "last 3 chrome version",
-      "last 3 firefox version",
-      "last 5 safari version"
-    ]
-  },
-  "engines": {
-    "node": ">=18.0"
-  }
+    "name": "ollama-4-j",
+    "version": "0.0.0",
+    "private": true,
+    "scripts": {
+        "docusaurus": "docusaurus",
+        "start": "docusaurus start",
+        "build": "docusaurus build",
+        "swizzle": "docusaurus swizzle",
+        "deploy": "docusaurus deploy",
+        "clear": "docusaurus clear",
+        "serve": "docusaurus serve",
+        "write-translations": "docusaurus write-translations",
+        "write-heading-ids": "docusaurus write-heading-ids"
+    },
+    "dependencies": {
+        "@docsearch/js": "^3.9.0",
+        "@docusaurus/core": "^3.4.0",
+        "@docusaurus/plugin-google-gtag": "^3.4.0",
+        "@docusaurus/preset-classic": "^3.4.0",
+        "@docusaurus/theme-mermaid": "^3.4.0",
+        "@iconify/react": "^5.2.1",
+        "@mdx-js/react": "^3.0.0",
+        "clsx": "^2.0.0",
+        "font-awesome": "^4.7.0",
+        "prism-react-renderer": "^2.3.0",
+        "react": "^18.0.0",
+        "react-dom": "^18.0.0",
+        "react-icons": "^5.5.0",
+        "react-image-gallery": "^1.4.0"
+    },
+    "devDependencies": {
+        "@docusaurus/module-type-aliases": "^3.4.0",
+        "@docusaurus/types": "^3.4.0"
+    },
+    "browserslist": {
+        "production": [
+            ">0.5%",
+            "not dead",
+            "not op_mini all"
+        ],
+        "development": [
+            "last 3 chrome version",
+            "last 3 firefox version",
+            "last 5 safari version"
+        ]
+    },
+    "engines": {
+        "node": ">=18.0"
+    }
 }

docs/src/components/AddToYourProject/index.js

@@ -0,0 +1,65 @@
+import React, { useState, useEffect } from 'react';
+import CodeBlock from '@theme/CodeBlock';
+
+const AddToYourProject = () => {
+    const [releaseInfo, setReleaseInfo] = useState(null);
+    const [loading, setLoading] = useState(true);
+    const [error, setError] = useState(null);
+
+    useEffect(() => {
+        const fetchLatestRelease = async () => {
+            setLoading(true);
+            setError(null);
+            try {
+                const response = await fetch('https://api.github.com/repos/ollama4j/ollama4j/releases/latest');
+                if (!response.ok) {
+                    throw new Error(`HTTP error! status: ${response.status}`);
+                }
+                const data = await response.json();
+                setReleaseInfo(data);
+            } catch (err) {
+                console.error('Failed to fetch release info:', err);
+                setError(err);
+            } finally {
+                setLoading(false);
+            }
+        };
+
+        fetchLatestRelease();
+    }, []);
+
+    return (
+        <div style={{ width: '100%' }}>
+            {loading ? (
+                <div>Loading latest release info...</div>
+            ) : error ? (
+                <div>Error: {error.message}</div>
+            ) : releaseInfo ? (
+                <>
+                    <h4>Using Maven <code>pom.xml</code></h4>
+                    <CodeBlock className="language-xml">
+                        {`<dependency>
+    <groupId>io.github.ollama4j</groupId>
+    <artifactId>ollama4j</artifactId>
+    <version>${releaseInfo.name}</version>
+</dependency>`}
+                    </CodeBlock>
+                    <h4>Using Groovy-based <code>build.gradle</code></h4>
+                    <CodeBlock className="language-groovy">
+                        {`dependencies {
+    implementation 'io.github.ollama4j:ollama4j:${releaseInfo.name}'
+}`}
+                    </CodeBlock>
+                    <h4>For Kotlin-based <code>build.gradle.kts</code></h4>
+                    <CodeBlock className="language-kotlin">
+                        {`dependencies {
+    implementation("io.github.ollama4j:ollama4j:${releaseInfo.name}")
+}`}
+                    </CodeBlock>
+                </>
+            ) : null}
+        </div>
+    );
+};
+
+export default AddToYourProject;

docs/src/components/CodeEmbed/index.js

@@ -0,0 +1,170 @@
+// import React, { useState, useEffect } from 'react';
+// import CodeBlock from '@theme/CodeBlock';
+// import Icon from '@site/src/components/Icon';
+
+
+// const CodeEmbed = ({ src }) => {
+//     const [code, setCode] = useState('');
+//     const [loading, setLoading] = useState(true);
+//     const [error, setError] = useState(null);
+
+//     useEffect(() => {
+//         let isMounted = true;
+
+//         const fetchCodeFromUrl = async (url) => {
+//             if (!isMounted) return;
+
+//             setLoading(true);
+//             setError(null);
+
+//             try {
+//                 const response = await fetch(url);
+//                 if (!response.ok) {
+//                     throw new Error(`HTTP error! status: ${response.status}`);
+//                 }
+//                 const data = await response.text();
+//                 if (isMounted) {
+//                     setCode(data);
+//                 }
+//             } catch (err) {
+//                 console.error('Failed to fetch code:', err);
+//                 if (isMounted) {
+//                     setError(err);
+//                     setCode(`// Failed to load code from ${url}\n// ${err.message}`);
+//                 }
+//             } finally {
+//                 if (isMounted) {
+//                     setLoading(false);
+//                 }
+//             }
+//         };
+
+//         if (src) {
+//             fetchCodeFromUrl(src);
+//         }
+
+//         return () => {
+//             isMounted = false;
+//         };
+//     }, [src]);
+
+//     const githubUrl = src ? src.replace('https://raw.githubusercontent.com', 'https://github.com').replace('/refs/heads/', '/blob/') : null;
+//     const fileName = src ? src.substring(src.lastIndexOf('/') + 1) : null;
+
+//     return (
+//         loading ? (
+//             <div>Loading code...</div>
+//         ) : error ? (
+//             <div>Error: {error.message}</div>
+//         ) : (
+//             <div style={{ backgroundColor: 'transparent', padding: '0px', borderRadius: '5px' }}>
+//                 <div style={{ textAlign: 'right' }}>
+//                     {githubUrl && (
+//                         <a href={githubUrl} target="_blank" rel="noopener noreferrer" style={{ paddingRight: '15px', color: 'gray', fontSize: '0.8em', fontStyle: 'italic', display: 'inline-flex', alignItems: 'center' }}>
+//                             View on GitHub
+//                             <Icon icon="mdi:github" height="48" />
+//                         </a>
+//                     )}
+//                 </div>
+//                 <CodeBlock title={fileName} className="language-java">{code}</CodeBlock>
+//             </div>
+//         )
+//     );
+// };
+
+// export default CodeEmbed;
+import React, { useState, useEffect } from 'react';
+import CodeBlock from '@theme/CodeBlock';
+import Icon from '@site/src/components/Icon';
+
+
+const CodeEmbed = ({ src }) => {
+    const [code, setCode] = useState('');
+    const [loading, setLoading] = useState(true);
+    const [error, setError] = useState(null);
+
+    useEffect(() => {
+        let isMounted = true;
+
+        const fetchCodeFromUrl = async (url) => {
+            if (!isMounted) return;
+
+            setLoading(true);
+            setError(null);
+
+            try {
+                const response = await fetch(url);
+                if (!response.ok) {
+                    throw new Error(`HTTP error! status: ${response.status}`);
+                }
+                const data = await response.text();
+                if (isMounted) {
+                    setCode(data);
+                }
+            } catch (err) {
+                console.error('Failed to fetch code:', err);
+                if (isMounted) {
+                    setError(err);
+                    setCode(`// Failed to load code from ${url}\n// ${err.message}`);
+                }
+            } finally {
+                if (isMounted) {
+                    setLoading(false);
+                }
+            }
+        };
+
+        if (src) {
+            fetchCodeFromUrl(src);
+        }
+
+        return () => {
+            isMounted = false;
+        };
+    }, [src]);
+
+    const githubUrl = src ? src.replace('https://raw.githubusercontent.com', 'https://github.com').replace('/refs/heads/', '/blob/') : null;
+    const fileName = src ? src.substring(src.lastIndexOf('/') + 1) : null;
+
+    const title = (
+        <div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center' }}>
+            <a
+                href={githubUrl}
+                target="_blank"
+                rel="noopener noreferrer"
+                style={{
+                    color: 'gray',
+                    textDecoration: 'none',
+                }}
+                onMouseOver={e => {
+                    e.target.style.textDecoration = 'underline';
+                }}
+                onMouseOut={e => {
+                    e.target.style.textDecoration = 'none';
+                }}
+            >
+                <span>{fileName}</span>
+            </a>
+            {githubUrl && (
+                <a href={githubUrl} target="_blank" rel="noopener noreferrer" style={{ color: 'gray', fontSize: '0.9em', fontStyle: 'italic', display: 'inline-flex', alignItems: 'center' }}>
+                    View on GitHub
+                    <Icon icon="mdi:github" height="1em" />
+                </a>
+            )}
+        </div>
+    );
+
+    return (
+        loading ? (
+            <div>Loading code...</div>
+        ) : error ? (
+            <div>Error: {error.message}</div>
+        ) : (
+            <div style={{ backgroundColor: 'transparent', padding: '0px', borderRadius: '5px' }}>
+                <CodeBlock title={title} className="language-java">{code}</CodeBlock>
+            </div>
+        )
+    );
+};
+
+export default CodeEmbed;

docs/src/components/HomepageFeatures/index.js

@@ -1,39 +1,107 @@
 import clsx from 'clsx';
 import Heading from '@theme/Heading';
 import styles from './styles.module.css';
+import Ollama4jUIImageCarousel from '@site/src/components/Ollama4jUIImageCarousel';
 
 const FeatureList = [
-  {
-    title: 'Easy LLM Integration',
-    Svg: require('@site/static/img/undraw_docusaurus_mountain.svg').default,
-    description: (
-      <>
-        Easy integration with Ollama, enabling the execution of large language models locally.
-
-      </>
-    ),
-  },
   {
     title: 'Developer-Friendly',
     Svg: require('@site/static/img/undraw_docusaurus_tree.svg').default,
     description: (
       <>
-        Clean and simple <code>APIs</code>, focused on seamless interaction with Ollama.
+        Provides clean and simple <code>APIs</code> for interacting with Ollama, including model management, chat functionalities, and authentication capability when Ollama is deployed behind proxy server.
       </>
     ),
   },
   {
-    title: 'Powered by Java',
+    title: 'Chat with Images',
+    Svg: require('@site/static/img/undraw_docusaurus_mountain.svg').default,
+    description: (
+      <>
+        Supports interactions with vision/image models, allowing you to build applications that can understand and respond to visual content.  Upload images directly into your chat sessions and receive intelligent, context-aware replies.
+      </>
+    ),
+  },
+  {
+    title: 'Tools Support',
     Svg: require('@site/static/img/undraw_docusaurus_react.svg').default,
     description: (
       <>
-        Empowers Java developers to harness the full capabilities of Ollama.
+        Supports tool/function calling with tool calling models such as mistral, llama3.x, qwen, etc. Empower your models to interact with external services and data sources, enabling more complex and dynamic AI workflows.
       </>
     ),
   },
 ];
+const UsageList = [
+  {
+    title: 'Datafaker',
+    Svg: require('@site/static/img/datafaker.svg').default,
+    link: 'https://www.datafaker.net/',
+    description: (
+      <>
+        A powerful fake data generation library designed for JVM programs, offering over 200 data providers to easily create realistic and diverse datasets within minutes.
+      </>
+    ),
+    imageSize: '20%',
+  },
+  {
+    title: 'Katie',
+    Svg: require('@site/static/img/katie_logo_v3.svg').default,
+    link: 'https://katie.qa/home',
+    description: (
+      <>
+        An Open Source AI-based question-answering platform that helps companies and organizations make their private domain knowledge accessible and useful to their employees and customers.
+      </>
+    ),
+    imageSize: '30%',
+  },
+  {
+    title: 'AI Player',
+    Svg: require('@site/static/img/ai-player.svg').default,
+    link: 'https://modrinth.com/mod/ai-player',
+    description: (
+      <>
+        A minecraft mod which aims to add a "second player" into the game which will actually be intelligent.
+      </>
+    ),
+    imageSize: '15%',
+  },
+  {
+    title: 'Ollama Translator Plugin',
+    Svg: require('@site/static/img/minecraft-spigot.svg').default,
+    link: 'https://github.com/liebki/ollama-translator',
+    description: (
+      <>
+        A minecraft 1.21 spigot plugin allows to easily break language barriers by using ollama on the server to translate all messages into a specfic target language.
+      </>
+    ),
+    imageSize: '20%',
+  },
+  {
+    title: 'JnsCLI',
+    Svg: require('@site/static/img/jnscli.svg').default,
+    link: 'https://github.com/mirum8/jnscli',
+    description: (
+      <>
+        JnsCLI is a command-line tool for Jenkins, allowing you to manage jobs, builds, and configurations directly from the terminal. It also features AI-powered error analysis for quick troubleshooting.
+      </>
+    ),
+    imageSize: '20%',
+  },
+  {
+    title: 'Featured in a Research Article on AI-Assisted Code Optimization',
+    Svg: require('@site/static/img/pmc-logo.svg').default,
+    link: 'https://pmc.ncbi.nlm.nih.gov/articles/PMC11750896/',
+    description: (
+      <>
+        Ollama4j was used in a research article – “Large Language Model Based Mutations in Genetic Improvement” (PubMed Central).
+      </>
+    ),
+    imageSize: '50%',
+  },
+];
 
-function Feature({Svg, title, description}) {
+function Feature({ Svg, title, description }) {
   return (
     <div className={clsx('col col--4')}>
       <div className="text--center">
@@ -47,16 +115,58 @@ function Feature({Svg, title, description}) {
   );
 }
 
-export default function HomepageFeatures() {
+function Usage({ Svg, title, description, link, imageSize }) {
   return (
-    <section className={styles.features}>
-      <div className="container">
-        <div className="row">
-          {FeatureList.map((props, idx) => (
-            <Feature key={idx} {...props} />
-          ))}
-        </div>
+    <div className={clsx('col col--4')}>
+      <div className="text--center">
+        <Svg className={styles.featureSvg} role="img" style={{ width: imageSize }} />
       </div>
-    </section>
+      <div className="text--center padding-horiz--md">
+        <Heading as="h3" style={{ color: 'red' }}>
+          {link ? (
+            <a href={link} target="_blank" rel="noopener noreferrer" style={{ color: '#11bc11' }}>
+              {title}
+            </a>
+          ) : (
+            <span style={{ color: 'red' }}>{title}</span>
+          )}
+        </Heading>
+        <p>{description}</p>
+      </div>
+    </div>
+  );
+}
+
+export default function HomepageFeatures() {
+  return (
+    <>
+      <section className={styles.features}>
+        <div className="container">
+          <div className="row">
+            {FeatureList.map((props, idx) => (
+              <Feature key={idx} {...props} />
+            ))}
+          </div>
+        </div>
+      </section>
+      <hr />
+      <section className={styles.features}>
+        <div className="container">
+          <div style={{ fontSize: '20px', fontWeight: 'bold', display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
+            Check out who's using Ollama4j
+          </div>
+          <div className="row">
+            {UsageList.map((props, idx) => (
+              <Usage key={idx} {...props} />
+            ))}
+          </div>
+        </div>
+      </section>
+      <section className={styles.features}>
+        <div className="container">
+          <Ollama4jUIImageCarousel></Ollama4jUIImageCarousel>
+        </div>
+      </section>
+    </>
   );
 }

docs/src/components/Icon/index.js

@@ -0,0 +1,9 @@
+// @site/src/components/Icon.js
+import React from 'react';
+import { Icon as IconifyIcon } from '@iconify/react';
+
+const IIcon = ({ icon, color, width = '24', height = '24' }) => (
+  <IconifyIcon icon={icon} color={color} width={width} height={height} />
+);
+
+export default IIcon;

docs/src/components/LatestRelease/index.js

@@ -0,0 +1,52 @@
+import React, { useState, useEffect } from 'react';
+
+const LatestRelease = ({ showReleaseDate }) => {
+    const [releaseInfo, setReleaseInfo] = useState(null);
+    const [loading, setLoading] = useState(true);
+    const [error, setError] = useState(null);
+
+    useEffect(() => {
+        const fetchLatestRelease = async () => {
+            setLoading(true);
+            setError(null);
+            try {
+                const response = await fetch('https://api.github.com/repos/ollama4j/ollama4j/releases/latest');
+                if (!response.ok) {
+                    throw new Error(`HTTP error! status: ${response.status}`);
+                }
+                const data = await response.json();
+                setReleaseInfo(data);
+            } catch (err) {
+                console.error('Failed to fetch release info:', err);
+                setError(err);
+            } finally {
+                setLoading(false);
+            }
+        };
+
+        fetchLatestRelease();
+    }, []);
+
+    return (
+        <div style={{ display: 'flex', justifyContent: 'center' }}>
+            {loading ? (
+                <div>Loading latest release info...</div>
+            ) : error ? (
+                <div>Error: {error.message}</div>
+            ) : releaseInfo ? (
+                <div>
+                    {/* <h4 style={{ display: 'flex', justifyContent: 'center'}}>Latest Release</h4> */}
+                    <div>
+                        <span style={{ fontWeight: 'bold'}}>Latest Version</span>: <a href={releaseInfo.html_url} target='_blank' rel="noopener noreferrer"><span style={{color: 'white', fontWeight: 'bold', backgroundColor:'#11bc11', borderRadius: '15px', padding: '5px'}}>{releaseInfo.name}</span></a>
+                        {showReleaseDate && ` released on ${new Date(releaseInfo.published_at).toLocaleDateString(undefined, { year: 'numeric', month: 'long', day: 'numeric' })}`}
+                    </div>
+                    {/* <pre style={{ whiteSpace: 'pre-wrap' }}>
+                        {JSON.stringify(releaseInfo, null, 2)}
+                    </pre> */}
+                </div>
+            ) : null}
+        </div>
+    );
+};
+
+export default LatestRelease;

docs/src/components/Ollama4jUIImageCarousel/index.js

@@ -0,0 +1,54 @@
+import React from 'react';
+import "react-image-gallery/styles/css/image-gallery.css";
+import ImageGallery from "react-image-gallery";
+
+const images = [
+    {
+        original: require('@site/static/img/ollama4j-ui/1.png').default,
+        thumbnail: require('@site/static/img/ollama4j-ui/1.png').default,
+    },
+    {
+        original: require('@site/static/img/ollama4j-ui/2.png').default,
+        thumbnail: require('@site/static/img/ollama4j-ui/2.png').default,
+    },
+    {
+        original: require('@site/static/img/ollama4j-ui/3.png').default,
+        thumbnail: require('@site/static/img/ollama4j-ui/3.png').default,
+    },
+    {
+        original: require('@site/static/img/ollama4j-ui/4.png').default,
+        thumbnail: require('@site/static/img/ollama4j-ui/4.png').default,
+    },
+];
+
+class Ollama4jUIImageCarousel extends React.Component {
+    renderItem = (item) => {
+        return (
+            <div className="image-gallery-image" style={{ textAlign: 'center' }}>
+                <img
+                    src={item.original}
+                    alt=""
+                    style={{ maxHeight: '500px', width: 'auto', maxWidth: '100%' }}
+                />
+            </div>
+        );
+    };
+
+    render() {
+        return (
+            <div style={{ margin: '0 auto', maxWidth: '800px' }}>
+                <div style={{ display: 'flex', flexDirection: 'column', justifyContent: 'center', alignItems: 'center', textAlign: 'center' }}>
+                    <h2>Explore the stuff we have built with Ollama4j</h2>
+                    <h4>
+                        <a href="https://github.com/ollama4j/ollama4j-ui" target='_blank' rel="noopener noreferrer">
+                            Ollama4j UI - Desktop UI built in Java with Swing
+                        </a>
+                    </h4>
+                </div>
+                <ImageGallery items={images} renderItem={this.renderItem} />
+            </div>
+        );
+    }
+}
+
+export default Ollama4jUIImageCarousel;

docs/src/components/TypewriterTextarea/index.js

@@ -0,0 +1,66 @@
+import React, { useEffect, useState, useRef } from 'react';
+
+const TypewriterTextarea = ({ textContent, typingSpeed = 50, pauseBetweenSentences = 1000, height = '200px', width = '100%' }) => {
+  const [text, setText] = useState('');
+  const [sentenceIndex, setSentenceIndex] = useState(0);
+  const [charIndex, setCharIndex] = useState(0);
+  const sentences = textContent ? textContent.split('\n') : [];
+  const isTyping = useRef(false);
+
+  useEffect(() => {
+    if (!textContent) return;
+
+    if (!isTyping.current) {
+      isTyping.current = true;
+    }
+
+    if (sentenceIndex >= sentences.length) {
+      // Reset to start from the beginning
+      setSentenceIndex(0);
+      setCharIndex(0);
+      setText('');
+      return;
+    }
+
+    const currentSentence = sentences[sentenceIndex];
+
+    if (charIndex < currentSentence.length) {
+      const timeout = setTimeout(() => {
+        setText((prevText) => prevText + currentSentence[charIndex]);
+        setCharIndex((prevCharIndex) => prevCharIndex + 1);
+      }, typingSpeed);
+
+      return () => clearTimeout(timeout);
+    } else {
+      // Wait a bit, then go to the next sentence
+      const timeout = setTimeout(() => {
+        setSentenceIndex((prev) => prev + 1);
+        setCharIndex(0);
+      }, pauseBetweenSentences);
+
+      return () => clearTimeout(timeout);
+    }
+  }, [charIndex, sentenceIndex, sentences, typingSpeed, pauseBetweenSentences, textContent]);
+
+  return (
+    <textarea
+      value={text}
+      readOnly
+      rows={10}
+      cols={5}
+      style={{
+        width: typeof width === 'number' ? `${width}px` : width,
+        height: height,
+        padding: '1rem',
+        fontFamily: 'monospace',
+        fontSize: '1rem',
+        backgroundColor: '#f4f4f4',
+        border: '1px solid #ccc',
+        resize: 'none',
+        whiteSpace: 'pre-wrap',
+      }}
+    />
+  );
+};
+
+export default TypewriterTextarea;

docs/src/css/custom.css

@@ -4,6 +4,8 @@
  * work well for content-centric websites.
  */
 
+ @import 'font-awesome/css/font-awesome.min.css';
+
 /* You can override the default Infima variables here. */
 :root {
     --ifm-color-primary: #2e8555;

docs/src/pages/index.js

@@ -7,39 +7,59 @@ import BuyMeACoffee from '@site/src/components/BuyMeACoffee';
 import Heading from '@theme/Heading';
 import styles from './index.module.css';
 import BrowserOnly from '@docusaurus/BrowserOnly';
+import LatestRelease from '@site/src/components/LatestRelease';
+import TypewriterTextarea from '@site/src/components/TypewriterTextarea';
 
 function HomepageHeader() {
   const {siteConfig} = useDocusaurusContext();
-  return (<header className={clsx('hero hero--primary', styles.heroBanner)}>
-    <div className="container">
-      <Heading as="h1" className="hero__title">
-        {siteConfig.title}
-      </Heading>
-      <img src="img/logo.svg" alt="Ollama4j Logo" className={styles.logo}
-           style={{maxWidth: '20vh'}}/>
-      <p className="hero__subtitle">{siteConfig.tagline}</p>
-      <div className={styles.buttons}>
-        <Link
-            className="button button--secondary button--lg"
-            to="/intro">
-          Getting Started
-        </Link>
+  return (
+    <header className={clsx('hero hero--primary', styles.heroBanner)}>
+      <div className="container">
+        <Heading as="h1" className="hero__title">
+          {siteConfig.title}
+        </Heading>
+        <img
+          src="img/logo.svg"
+          alt="Ollama4j Logo"
+          className={styles.logo}
+          style={{ maxWidth: '20vh' }}
+        />
+        <p className="hero__subtitle">{siteConfig.tagline}</p>
+        <div style={{ marginTop: '2rem' }}>
+          <TypewriterTextarea
+            textContent='Hello there! I’m a handy little Java library that helps you talk to an Ollama server — nice and easy.'
+            typingSpeed={30}
+            pauseBetweenSentences={1200}
+            height='130px'
+            width='100%'
+          />
+        </div>
+        <div className={styles.buttons} >
+          <Link className="button button--secondary button--lg" to="/intro" style={{ marginTop:'2rem' }}>
+            Get Started
+          </Link>
+        </div>
+        <div style={{ marginTop: '3rem' }}>
+          <LatestRelease showReleaseDate={false} />
+        </div>
       </div>
-    </div>
-  </header>);
+    </header>
+  );
 }
 
 export default function Home() {
   const {siteConfig} = useDocusaurusContext();
-  return (<Layout
-      title={`Hello from ${siteConfig.title}`}
+  return (
+    <Layout
+      title={`${siteConfig.title}`}
       description="Description will go into a meta tag in <head />">
-    <HomepageHeader/>
-    <main>
-      <HomepageFeatures/>
-      <BrowserOnly>
-        {() => <BuyMeACoffee />}
-      </BrowserOnly>
-    </main>
-  </Layout>);
+      <HomepageHeader />
+      <main>
+        <HomepageFeatures />
+        <BrowserOnly>
+          {() => <BuyMeACoffee />}
+        </BrowserOnly>
+      </main>
+    </Layout>
+  );
 }

docs/static/img/ai-player.svg

@@ -0,0 +1,7 @@
+<svg width="96" height="96" viewBox="0 0 96 96" xmlns="http://www.w3.org/2000/svg">
+  <rect width="96" height="96" rx="16" fill="#3F0F8D"/>
+  <path d="M26 24H70V32H26V24Z" fill="white"/>
+  <path d="M36 44H44V52H36V44Z" fill="white"/>
+  <path d="M52 44H60V52H52V44Z" fill="white"/>
+  <path d="M36 60H60V68H36V60Z" fill="white"/>
+</svg>

docs/static/img/datafaker.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path fill="gray" d="M12 8a3 3 0 0 0 3-3 3 3 0 0 0-3-3 3 3 0 0 0-3 3 3 3 0 0 0 3 3m0 3.54C9.64 9.35 6.5 8 3 8v11c3.5 0 6.64 1.35 9 3.54 2.36-2.19 5.5-3.54 9-3.54V8c-3.5 0-6.64 1.35-9 3.54z"></path></svg>

docs/static/img/katie_logo_v3.svg

@@ -0,0 +1,13 @@
+<svg width="539" height="122" viewBox="0 0 539 122" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M233.794 106.267L194.606 73.1369L230.215 42.896C233.395 40.1969 233.755 35.4621 231.017 32.3237C228.282 29.1851 223.482 28.8263 220.301 31.533L177.914 67.5271V10.039C177.914 5.89749 174.511 2.54163 170.316 2.54163C166.119 2.54163 162.717 5.89749 162.717 10.039V111.961C162.717 116.103 166.119 119.458 170.316 119.458C174.511 119.458 177.914 116.103 177.914 111.961V78.7709L223.905 117.655C225.339 118.865 227.096 119.458 228.847 119.458C230.988 119.458 233.116 118.571 234.62 116.84C237.35 113.694 236.981 108.961 233.794 106.267Z" fill="#414041"/>
+<path d="M323.056 30.4831C318.932 30.4831 315.592 33.8533 315.592 38.0129V42.0425C307.753 33.3984 296.966 27.9584 285.263 27.9584C262.554 27.9584 244.075 49.0502 244.075 74.9781C244.075 100.907 262.554 122 285.263 122C298.217 122 308.397 116.775 315.592 108.901V112.96C315.592 117.12 318.932 120.49 323.056 120.49C327.178 120.49 330.519 117.12 330.519 112.96V38.0129C330.519 33.8533 327.178 30.4831 323.056 30.4831ZM285.263 106.941C271.027 106.941 259.002 92.3023 259.002 74.9781C259.002 57.6537 271.027 43.018 285.263 43.018C298.803 43.018 313.299 55.8594 313.299 74.9781C313.299 95.962 299.197 106.941 285.263 106.941Z" fill="#414041"/>
+<path d="M411.244 105.137C409.576 101.309 405.12 99.5521 401.277 101.222C400.739 101.454 400.076 101.763 399.304 102.121C395.776 103.764 385.034 108.765 380.927 106.146C378.976 104.904 377.859 100.863 377.859 95.0546V43.0501H394.522C398.705 43.0501 402.096 39.6633 402.096 35.4831C402.096 31.3029 398.705 27.9159 394.522 27.9159H377.859V7.56714C377.859 3.38695 374.47 0 370.285 0C366.102 0 362.711 3.38695 362.711 7.56714V27.9159H350.805C346.621 27.9159 343.231 31.3029 343.231 35.4831C343.231 39.6633 346.621 43.0501 350.805 43.0501H362.711V95.0546C362.711 106.629 366.102 114.654 372.785 118.909C376.316 121.155 380.207 122 384.1 122C392.482 122 400.877 118.088 405.707 115.839C406.339 115.544 406.885 115.288 407.327 115.095C411.161 113.428 412.917 108.969 411.244 105.137Z" fill="#414041"/>
+<path d="M502.288 122C487.874 122 460.527 111.883 460.187 73.5909C460.052 58.2558 464.703 45.0328 473.288 36.3573C480.37 29.1992 489.739 25.4166 500.381 25.4166C526.708 25.4166 537.58 47.0116 538.976 67.2225C539.168 69.9859 538.2 72.7323 536.321 74.7481C534.467 76.7394 531.854 77.8793 529.147 77.8793H475.52C477.843 105.988 499.689 106.84 502.288 106.84C516.078 106.84 523.655 98.4106 523.729 98.327C526.452 95.1443 531.226 94.7713 534.398 97.4901C537.577 100.209 537.951 104.994 535.234 108.177C534.754 108.742 523.197 122 502.288 122ZM476.301 62.7194H523.227C519.981 43.6041 507.776 40.5766 500.381 40.5766C493.774 40.5766 488.273 42.7479 484.036 47.0289C480.257 50.851 477.621 56.2473 476.301 62.7194Z" fill="#414041"/>
+<path d="M434.759 33.0416C430.546 33.0416 427.132 36.4385 427.132 40.6307V111.869C427.132 116.061 430.546 119.458 434.759 119.458C438.973 119.458 442.387 116.061 442.387 111.869V40.6307C442.387 36.4385 438.973 33.0416 434.759 33.0416Z" fill="#414041"/>
+<path d="M434.759 22.875C440.376 22.875 444.929 18.3232 444.929 12.7083C444.929 7.09347 440.376 2.54163 434.759 2.54163C429.142 2.54163 424.59 7.09347 424.59 12.7083C424.59 18.3232 429.142 22.875 434.759 22.875Z" fill="#414041"/>
+<path d="M111.868 0H10.1698C4.55318 0 0 4.55177 0 10.1667V111.833C0 117.448 4.55318 122 10.1698 122H111.868C117.485 122 122.038 117.448 122.038 111.833V10.1667C122.038 4.55177 117.485 0 111.868 0Z" fill="#FF89BB"/>
+<path d="M119.138 3H3.10229V119H119.138V3Z" fill="#FF89BB"/>
+<path d="M37.0639 65.2438C41.7531 65.2438 45.5543 60.8104 45.5543 55.3414C45.5543 49.8724 41.7531 45.439 37.0639 45.439C32.3748 45.439 28.5735 49.8724 28.5735 55.3414C28.5735 60.8104 32.3748 65.2438 37.0639 65.2438Z" fill="#414041"/>
+<path d="M82.3464 56.756C87.0355 56.756 90.8368 52.3226 90.8368 46.8536C90.8368 41.3846 87.0355 36.9512 82.3464 36.9512C77.6573 36.9512 73.856 41.3846 73.856 46.8536C73.856 52.3226 77.6573 56.756 82.3464 56.756Z" fill="#414041"/>
+<path d="M59.8714 99.1951C42.5471 99.1951 30.8795 89.4538 30.3195 88.985C28.2142 87.1935 27.9803 84.0583 29.7949 81.9799C31.6096 79.9085 34.771 79.6705 36.8763 81.448C37.0748 81.616 49.2599 91.5603 65.9462 88.747C83.0366 85.8638 93.003 73.0154 93.1022 72.8894C94.768 70.699 97.9153 70.2511 100.134 71.8887C102.353 73.5262 102.821 76.6194 101.169 78.8168C100.673 79.4746 88.8208 94.9683 67.6333 98.5373C64.9468 98.9992 62.3453 99.1951 59.8714 99.1951Z" fill="#414041"/>
+</svg>

docs/static/img/minecraft-spigot.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" shape-rendering="geometricPrecision" text-rendering="geometricPrecision" image-rendering="optimizeQuality" fill-rule="evenodd" clip-rule="evenodd" viewBox="0 0 512 448.012"><path fill="#424C57" fill-rule="nonzero" d="M386.912 404.082c-31.653 27.804-68.134 42.5-104.037 43.83-37.327 1.383-73.956-11.673-103.851-39.445l-15.148-14.072-54.139-44.075h-48.07c-25.406 0-43.633-20.936-46.214-46.212L.195 154.71c-2.581-25.279 20.879-48.258 46.214-46.215l189.276 15.258c25.335 2.042 46.214 20.793 46.214 46.215v134.14c0 25.418-20.805 46.212-46.214 46.212h-59.323l4.221 47.53 4.398 2.497c33.226 18.862 65.806 26.928 96.721 22.849 28.258-3.73 55.317-17.66 80.412-42.828l-15.449-13.603 64.278-14.309-7.532 67.307-16.499-15.681z"/><path fill="#337EC6" d="M276.315 73.91l113.118-9.119-30.176-17.127c-33.228-18.859-65.809-26.927-96.721-22.848-28.26 3.73-55.319 17.66-80.414 42.827l15.449 13.604-64.277 14.309 7.533-67.307 16.498 15.682C188.979 16.128 225.46 1.43 261.363.099c37.327-1.382 73.956 11.673 103.851 39.446l26.942 25.027 73.434-5.92c25.335-2.042 48.796 20.936 46.215 46.216l-15.258 149.397c-2.581 25.277-20.808 46.212-46.215 46.212h-50.099l-71.815 58.466 5.19-58.466h-57.293c-25.411 0-46.216-20.793-46.216-46.212V120.126c0-25.422 20.881-44.173 46.216-46.216z"/><path fill="#fff" d="M84.246 173.714h43.841v-12.353h19.585v12.353h44.001v20.281h-9.033c-1.629 12.811-5.21 23.368-11.297 34.746-5.149 9.611-11.796 18.87-19.516 27.744 12.32 14.735 27.616 27.554 45.826 39.24l-10.073 15.701c-19.119-12.267-35.356-25.774-48.699-41.332-11.936 11.547-25.496 22.303-39.7 32.127l-10.588-15.325c14.055-9.725 27.407-20.347 38.896-31.672-10.588-15.493-18.697-32.88-24.308-52.875l17.968-5.038c4.601 16.401 11.052 30.837 19.344 43.759 5.657-6.848 10.548-13.876 14.412-21.092 4.74-8.866 7.286-16.196 8.89-25.983H84.246v-20.281zM398.456 215.314h-55.931l-7.357 25.09h-27.814c11.988-31.729 25.831-69.829 37.825-101.573 4.318-11.466 9.234-30.467 24.943-30.467 16.284 0 21.691 17.409 26.222 29.436l38.4 103.122h-28.708l-7.58-25.608zm-6-24.398l-21.893-57.703-21.971 57.703h43.864z"/></svg>

pom.xml

@@ -13,8 +13,8 @@
     <packaging>jar</packaging>
 
     <properties>
-        <maven.compiler.source>11</maven.compiler.source>
-        <maven.compiler.target>11</maven.compiler.target>
+        <maven.compiler.release>11</maven.compiler.release>
+        <project.build.outputTimestamp>${git.commit.time}</project.build.outputTimestamp><!-- populated via git-commit-id-plugin -->
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
         <maven-surefire-plugin.version>3.0.0-M5</maven-surefire-plugin.version>
         <maven-failsafe-plugin.version>3.0.0-M5</maven-failsafe-plugin.version>
@@ -49,7 +49,7 @@
             <plugin>
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-source-plugin</artifactId>
-                <version>3.3.0</version>
+                <version>3.3.1</version>
                 <executions>
                     <execution>
                         <id>attach-sources</id>
@@ -62,7 +62,7 @@
             <plugin>
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-javadoc-plugin</artifactId>
-                <version>3.5.0</version>
+                <version>3.11.2</version>
                 <configuration>
                     <!-- to disable the "missing" warnings. Remove the doclint to enable warnings-->
                     <doclint>all,-missing</doclint>
@@ -70,9 +70,13 @@
                 <executions>
                     <execution>
                         <id>attach-javadocs</id>
+                        <phase>package</phase>
                         <goals>
                             <goal>jar</goal>
                         </goals>
+                        <configuration>
+                            <outputDirectory>${project.build.directory}</outputDirectory>
+                        </configuration>
                     </execution>
                 </executions>
             </plugin>
@@ -114,7 +118,6 @@
                 </executions>
             </plugin>
 
-
             <plugin>
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-gpg-plugin</artifactId>
@@ -130,7 +133,36 @@
                 </executions>
             </plugin>
 
+            <plugin>
+                <groupId>io.github.git-commit-id</groupId>
+                <artifactId>git-commit-id-maven-plugin</artifactId>
+                <version>9.0.1</version>
+                <executions>
+                    <execution>
+                        <goals>
+                            <goal>revision</goal>
+                        </goals>
+                    </execution>
+                </executions>
+                <configuration>
+                    <dateFormat>yyyy-MM-dd'T'HH:mm:ss'Z'</dateFormat>
+		    <dateFormatTimeZone>Etc/UTC</dateFormatTimeZone>
+                </configuration>
+            </plugin>
         </plugins>
+
+        <pluginManagement>
+            <plugins>
+                <plugin>
+                    <artifactId>maven-compiler-plugin</artifactId>
+                    <version>3.14.0</version>
+                </plugin>
+                <plugin>
+                    <artifactId>maven-jar-plugin</artifactId>
+                    <version>3.4.2</version>
+                </plugin>
+            </plugins>
+        </pluginManagement>
     </build>
 
     <dependencies>
@@ -184,6 +216,13 @@
             <version>20240205</version>
             <scope>test</scope>
         </dependency>
+
+        <dependency>
+            <groupId>org.testcontainers</groupId>
+            <artifactId>ollama</artifactId>
+            <version>1.20.2</version>
+            <scope>test</scope>
+        </dependency>
     </dependencies>
 
     <distributionManagement>
@@ -225,6 +264,7 @@
                 <test.env>unit</test.env>
                 <skipUnitTests>false</skipUnitTests>
                 <skipIntegrationTests>true</skipIntegrationTests>
+                <skipGpgPluginDuringTests>true</skipGpgPluginDuringTests>
             </properties>
             <activation>
                 <activeByDefault>false</activeByDefault>
@@ -250,6 +290,23 @@
                             </execution>
                         </executions>
                     </plugin>
+                    <plugin>
+                        <groupId>org.apache.maven.plugins</groupId>
+                        <artifactId>maven-gpg-plugin</artifactId>
+                        <version>1.5</version>
+                        <executions>
+                            <execution>
+                                <id>sign-artifacts</id>
+                                <phase>verify</phase>
+                                <goals>
+                                    <goal>sign</goal>
+                                </goals>
+                                <configuration>
+                                    <skip>${skipGpgPluginDuringTests}</skip>
+                                </configuration>
+                            </execution>
+                        </executions>
+                    </plugin>
                 </plugins>
             </build>
         </profile>
@@ -259,7 +316,29 @@
                 <test.env>integration</test.env>
                 <skipUnitTests>true</skipUnitTests>
                 <skipIntegrationTests>false</skipIntegrationTests>
+                <skipGpgPluginDuringTests>true</skipGpgPluginDuringTests>
             </properties>
+            <build>
+                <plugins>
+                    <plugin>
+                        <groupId>org.apache.maven.plugins</groupId>
+                        <artifactId>maven-gpg-plugin</artifactId>
+                        <version>1.5</version>
+                        <executions>
+                            <execution>
+                                <id>sign-artifacts</id>
+                                <phase>verify</phase>
+                                <goals>
+                                    <goal>sign</goal>
+                                </goals>
+                                <configuration>
+                                    <skip>${skipGpgPluginDuringTests}</skip>
+                                </configuration>
+                            </execution>
+                        </executions>
+                    </plugin>
+                </plugins>
+            </build>
         </profile>
         <profile>
             <id>ci-cd</id>
@@ -303,7 +382,6 @@
                             <autoReleaseAfterClose>true</autoReleaseAfterClose>
                         </configuration>
                     </plugin>
-
                     <plugin>
                         <groupId>org.jacoco</groupId>
                         <artifactId>jacoco-maven-plugin</artifactId>
@@ -328,4 +406,4 @@
         </profile>
     </profiles>
 
-</project>
+</project>

src/main/java/io/github/ollama4j/exceptions/ToolInvocationException.java

@@ -2,6 +2,10 @@ package io.github.ollama4j.exceptions;
 
 public class ToolInvocationException extends Exception {
 
+    public ToolInvocationException(String s) {
+        super(s);
+    }
+
     public ToolInvocationException(String s, Exception e) {
         super(s, e);
     }

src/main/java/io/github/ollama4j/models/chat/OllamaChatMessage.java

@@ -2,6 +2,7 @@ package io.github.ollama4j.models.chat;
 
 import static io.github.ollama4j.utils.Utils.getObjectMapper;
 
+import com.fasterxml.jackson.annotation.JsonProperty;
 import com.fasterxml.jackson.core.JsonProcessingException;
 import com.fasterxml.jackson.databind.annotation.JsonSerialize;
 
@@ -32,6 +33,8 @@ public class OllamaChatMessage {
     @NonNull
     private String content;
 
+    private @JsonProperty("tool_calls") List<OllamaChatToolCalls> toolCalls;
+
     @JsonSerialize(using = FileToBase64Serializer.class)
     private List<byte[]> images;
 

src/main/java/io/github/ollama4j/models/chat/OllamaChatMessageRole.java

@@ -28,9 +28,9 @@ public class OllamaChatMessageRole {
     }
 
     public static OllamaChatMessageRole newCustomRole(String roleName) {
-        OllamaChatMessageRole customRole = new OllamaChatMessageRole(roleName);
-        roles.add(customRole);
-        return customRole;
+//        OllamaChatMessageRole customRole = new OllamaChatMessageRole(roleName);
+//        roles.add(customRole);
+        return new OllamaChatMessageRole(roleName);
     }
 
     public static List<OllamaChatMessageRole> getRoles() {

src/main/java/io/github/ollama4j/models/chat/OllamaChatRequest.java

@@ -3,6 +3,7 @@ package io.github.ollama4j.models.chat;
 import java.util.List;
 
 import io.github.ollama4j.models.request.OllamaCommonRequest;
+import io.github.ollama4j.tools.Tools;
 import io.github.ollama4j.utils.OllamaRequestBody;
 
 import lombok.Getter;
@@ -21,6 +22,8 @@ public class OllamaChatRequest extends OllamaCommonRequest implements OllamaRequ
 
   private List<OllamaChatMessage> messages;
 
+  private List<Tools.PromptFuncDefinition> tools;
+
   public OllamaChatRequest() {}
 
   public OllamaChatRequest(String model, List<OllamaChatMessage> messages) {

src/main/java/io/github/ollama4j/models/chat/OllamaChatRequestBuilder.java

@@ -10,6 +10,7 @@ import java.io.IOException;
 import java.net.URISyntaxException;
 import java.nio.file.Files;
 import java.util.ArrayList;
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -38,7 +39,11 @@ public class OllamaChatRequestBuilder {
         request = new OllamaChatRequest(request.getModel(), new ArrayList<>());
     }
 
-    public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content, List<File> images) {
+    public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content){
+        return withMessage(role,content, Collections.emptyList());
+    }
+
+    public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content, List<OllamaChatToolCalls> toolCalls,List<File> images) {
         List<OllamaChatMessage> messages = this.request.getMessages();
 
         List<byte[]> binaryImages = images.stream().map(file -> {
@@ -50,11 +55,11 @@ public class OllamaChatRequestBuilder {
             }
         }).collect(Collectors.toList());
 
-        messages.add(new OllamaChatMessage(role, content, binaryImages));
+        messages.add(new OllamaChatMessage(role, content,toolCalls, binaryImages));
         return this;
     }
 
-    public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content, String... imageUrls) {
+    public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content,List<OllamaChatToolCalls> toolCalls, String... imageUrls) {
         List<OllamaChatMessage> messages = this.request.getMessages();
         List<byte[]> binaryImages = null;
         if (imageUrls.length > 0) {
@@ -70,7 +75,7 @@ public class OllamaChatRequestBuilder {
             }
         }
 
-        messages.add(new OllamaChatMessage(role, content, binaryImages));
+        messages.add(new OllamaChatMessage(role, content,toolCalls, binaryImages));
         return this;
     }
 

src/main/java/io/github/ollama4j/models/chat/OllamaChatResult.java

@@ -2,28 +2,53 @@ package io.github.ollama4j.models.chat;
 
 import java.util.List;
 
-import io.github.ollama4j.models.response.OllamaResult;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import lombok.Getter;
+
+import static io.github.ollama4j.utils.Utils.getObjectMapper;
 
 /**
  * Specific chat-API result that contains the chat history sent to the model and appends the answer as {@link OllamaChatResult} given by the
  * {@link OllamaChatMessageRole#ASSISTANT} role.
  */
-public class OllamaChatResult extends OllamaResult {
+@Getter
+public class OllamaChatResult {
 
-    private List<OllamaChatMessage> chatHistory;
+    private final List<OllamaChatMessage> chatHistory;
 
-    public OllamaChatResult(String response, long responseTime, int httpStatusCode, List<OllamaChatMessage> chatHistory) {
-        super(response, responseTime, httpStatusCode);
+    private final OllamaChatResponseModel responseModel;
+
+    public OllamaChatResult(OllamaChatResponseModel responseModel, List<OllamaChatMessage> chatHistory) {
         this.chatHistory = chatHistory;
-        appendAnswerToChatHistory(response);
+        this.responseModel = responseModel;
+        appendAnswerToChatHistory(responseModel);
     }
 
-    public List<OllamaChatMessage> getChatHistory() {
-        return chatHistory;
+    private void appendAnswerToChatHistory(OllamaChatResponseModel response) {
+        this.chatHistory.add(response.getMessage());
     }
 
-    private void appendAnswerToChatHistory(String answer) {
-        OllamaChatMessage assistantMessage = new OllamaChatMessage(OllamaChatMessageRole.ASSISTANT, answer);
-        this.chatHistory.add(assistantMessage);
+    @Override
+    public String toString() {
+        try {
+            return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
+        } catch (JsonProcessingException e) {
+            throw new RuntimeException(e);
+        }
+    }
+
+    @Deprecated
+    public String getResponse(){
+        return responseModel != null ? responseModel.getMessage().getContent() : "";
+    }
+
+    @Deprecated
+    public int getHttpStatusCode(){
+        return 200;
+    }
+
+    @Deprecated
+    public long getResponseTime(){
+        return responseModel != null ? responseModel.getTotalDuration() : 0L;
     }
 }

src/main/java/io/github/ollama4j/models/chat/OllamaChatStreamObserver.java

@@ -1,31 +1,19 @@
 package io.github.ollama4j.models.chat;
 
 import io.github.ollama4j.models.generate.OllamaStreamHandler;
+import io.github.ollama4j.models.generate.OllamaTokenHandler;
+import lombok.RequiredArgsConstructor;
 
-import java.util.ArrayList;
-import java.util.List;
-
-public class OllamaChatStreamObserver {
-
-    private OllamaStreamHandler streamHandler;
-
-    private List<OllamaChatResponseModel> responseParts = new ArrayList<>();
-
+@RequiredArgsConstructor
+public class OllamaChatStreamObserver implements OllamaTokenHandler {
+    private final OllamaStreamHandler streamHandler;
     private String message = "";
 
-    public OllamaChatStreamObserver(OllamaStreamHandler streamHandler) {
-        this.streamHandler = streamHandler;
+    @Override
+    public void accept(OllamaChatResponseModel token) {
+        if (streamHandler != null) {
+            message += token.getMessage().getContent();
+            streamHandler.accept(message);
+        }
     }
-
-    public void notify(OllamaChatResponseModel currentResponsePart) {
-        responseParts.add(currentResponsePart);
-        handleCurrentResponsePart(currentResponsePart);
-    }
-
-    protected void handleCurrentResponsePart(OllamaChatResponseModel currentResponsePart) {
-        message = message + currentResponsePart.getMessage().getContent();
-        streamHandler.accept(message);
-    }
-
-
 }

src/main/java/io/github/ollama4j/models/chat/OllamaChatToolCalls.java

@@ -0,0 +1,16 @@
+package io.github.ollama4j.models.chat;
+
+import io.github.ollama4j.tools.OllamaToolCallsFunction;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class OllamaChatToolCalls {
+
+    private OllamaToolCallsFunction function;
+
+
+}

src/main/java/io/github/ollama4j/models/embeddings/OllamaEmbedRequestBuilder.java

@@ -5,7 +5,7 @@ import io.github.ollama4j.utils.Options;
 import java.util.List;
 
 /**
- * Builderclass to easily create Requests for Embedding models using ollama.
+ * Builder class to easily create Requests for Embedding models using ollama.
  */
 public class OllamaEmbedRequestBuilder {
 

src/main/java/io/github/ollama4j/models/generate/OllamaTokenHandler.java

@@ -0,0 +1,8 @@
+package io.github.ollama4j.models.generate;
+
+import io.github.ollama4j.models.chat.OllamaChatResponseModel;
+
+import java.util.function.Consumer;
+
+public interface OllamaTokenHandler extends Consumer<OllamaChatResponseModel> {
+}

src/main/java/io/github/ollama4j/models/request/Auth.java

@@ -0,0 +1,10 @@
+package io.github.ollama4j.models.request;
+
+public abstract class Auth {
+  /**
+   * Get authentication header value.
+   *
+   * @return authentication header value
+   */
+  public abstract String getAuthHeaderValue();
+}

src/main/java/io/github/ollama4j/models/request/BasicAuth.java

@@ -1,13 +1,24 @@
 package io.github.ollama4j.models.request;
 
+import java.util.Base64;
+
 import lombok.AllArgsConstructor;
 import lombok.Data;
 import lombok.NoArgsConstructor;
 
 @Data
-@NoArgsConstructor
 @AllArgsConstructor
-public class BasicAuth {
+public class BasicAuth extends Auth {
   private String username;
   private String password;
+
+  /**
+   * Get basic authentication header value.
+   *
+   * @return basic authentication header value (encoded credentials)
+   */
+  public String getAuthHeaderValue() {
+      final String credentialsToEncode = this.getUsername() + ":" + this.getPassword();
+      return "Basic " + Base64.getEncoder().encodeToString(credentialsToEncode.getBytes());
+  }
 }

src/main/java/io/github/ollama4j/models/request/BearerAuth.java

@@ -0,0 +1,19 @@
+package io.github.ollama4j.models.request;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+
+@Data
+@AllArgsConstructor
+public class BearerAuth extends Auth {
+  private String bearerToken;
+
+  /**
+   * Get authentication header value.
+   *
+   * @return authentication header value with bearer token
+   */
+  public String getAuthHeaderValue() {
+      return "Bearer "+ bearerToken;
+  }
+}

src/main/java/io/github/ollama4j/models/request/CustomModelRequest.java

@@ -0,0 +1,45 @@
+package io.github.ollama4j.models.request;
+
+import static io.github.ollama4j.utils.Utils.getObjectMapper;
+
+import com.fasterxml.jackson.core.JsonProcessingException;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.Data;
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+
+import java.util.List;
+import java.util.Map;
+
+
+@Data
+@AllArgsConstructor
+@Builder
+public class CustomModelRequest {
+    private String model;
+    private String from;
+    private Map<String, String> files;
+    private Map<String, String> adapters;
+    private String template;
+    private Object license; // Using Object to handle both String and List<String>
+    private String system;
+    private Map<String, Object> parameters;
+    private List<Object> messages;
+    private Boolean stream;
+    private Boolean quantize;
+
+    public CustomModelRequest() {
+        this.stream = true;
+        this.quantize = false;
+    }
+
+    @Override
+    public String toString() {
+        try {
+            return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
+        } catch (JsonProcessingException e) {
+            throw new RuntimeException(e);
+        }
+    }
+}

src/main/java/io/github/ollama4j/models/request/OllamaChatEndpointCaller.java

@@ -3,17 +3,23 @@ package io.github.ollama4j.models.request;
 import com.fasterxml.jackson.core.JsonProcessingException;
 import com.fasterxml.jackson.core.type.TypeReference;
 import io.github.ollama4j.exceptions.OllamaBaseException;
-import io.github.ollama4j.models.chat.OllamaChatMessage;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.models.chat.OllamaChatResponseModel;
-import io.github.ollama4j.models.chat.OllamaChatStreamObserver;
-import io.github.ollama4j.models.generate.OllamaStreamHandler;
-import io.github.ollama4j.utils.OllamaRequestBody;
+import io.github.ollama4j.models.chat.*;
+import io.github.ollama4j.models.generate.OllamaTokenHandler;
+import io.github.ollama4j.models.response.OllamaErrorResponse;
 import io.github.ollama4j.utils.Utils;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
+import java.io.BufferedReader;
 import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.net.URI;
+import java.net.http.HttpClient;
+import java.net.http.HttpRequest;
+import java.net.http.HttpResponse;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
 
 /**
  * Specialization class for requests
@@ -22,10 +28,10 @@ public class OllamaChatEndpointCaller extends OllamaEndpointCaller {
 
     private static final Logger LOG = LoggerFactory.getLogger(OllamaChatEndpointCaller.class);
 
-    private OllamaChatStreamObserver streamObserver;
+    private OllamaTokenHandler tokenHandler;
 
-    public OllamaChatEndpointCaller(String host, BasicAuth basicAuth, long requestTimeoutSeconds, boolean verbose) {
-        super(host, basicAuth, requestTimeoutSeconds, verbose);
+    public OllamaChatEndpointCaller(String host, Auth auth, long requestTimeoutSeconds, boolean verbose) {
+        super(host, auth, requestTimeoutSeconds, verbose);
     }
 
     @Override
@@ -53,8 +59,8 @@ public class OllamaChatEndpointCaller extends OllamaEndpointCaller {
             OllamaChatMessage message = ollamaResponseModel.getMessage();
             if(message != null) {
                 responseBuffer.append(message.getContent());
-                if (streamObserver != null) {
-                    streamObserver.notify(ollamaResponseModel);
+                if (tokenHandler != null) {
+                    tokenHandler.accept(ollamaResponseModel);
                 }
             }
             return ollamaResponseModel.isDone();
@@ -64,9 +70,75 @@ public class OllamaChatEndpointCaller extends OllamaEndpointCaller {
         }
     }
 
-    public OllamaResult call(OllamaRequestBody body, OllamaStreamHandler streamHandler)
+    public OllamaChatResult call(OllamaChatRequest body, OllamaTokenHandler tokenHandler)
             throws OllamaBaseException, IOException, InterruptedException {
-        streamObserver = new OllamaChatStreamObserver(streamHandler);
-        return super.callSync(body);
+        this.tokenHandler = tokenHandler;
+        return callSync(body);
+    }
+
+    public OllamaChatResult callSync(OllamaChatRequest body) throws OllamaBaseException, IOException, InterruptedException {
+        // Create Request
+        HttpClient httpClient = HttpClient.newHttpClient();
+        URI uri = URI.create(getHost() + getEndpointSuffix());
+        HttpRequest.Builder requestBuilder =
+                getRequestBuilderDefault(uri)
+                        .POST(
+                                body.getBodyPublisher());
+        HttpRequest request = requestBuilder.build();
+        if (isVerbose()) LOG.info("Asking model: " + body);
+        HttpResponse<InputStream> response =
+                httpClient.send(request, HttpResponse.BodyHandlers.ofInputStream());
+
+        int statusCode = response.statusCode();
+        InputStream responseBodyStream = response.body();
+        StringBuilder responseBuffer = new StringBuilder();
+        OllamaChatResponseModel ollamaChatResponseModel = null;
+        List<OllamaChatToolCalls> wantedToolsForStream = null;
+        try (BufferedReader reader =
+                     new BufferedReader(new InputStreamReader(responseBodyStream, StandardCharsets.UTF_8))) {
+
+            String line;
+            while ((line = reader.readLine()) != null) {
+                if (statusCode == 404) {
+                    LOG.warn("Status code: 404 (Not Found)");
+                    OllamaErrorResponse ollamaResponseModel =
+                            Utils.getObjectMapper().readValue(line, OllamaErrorResponse.class);
+                    responseBuffer.append(ollamaResponseModel.getError());
+                } else if (statusCode == 401) {
+                    LOG.warn("Status code: 401 (Unauthorized)");
+                    OllamaErrorResponse ollamaResponseModel =
+                            Utils.getObjectMapper()
+                                    .readValue("{\"error\":\"Unauthorized\"}", OllamaErrorResponse.class);
+                    responseBuffer.append(ollamaResponseModel.getError());
+                } else if (statusCode == 400) {
+                    LOG.warn("Status code: 400 (Bad Request)");
+                    OllamaErrorResponse ollamaResponseModel = Utils.getObjectMapper().readValue(line,
+                            OllamaErrorResponse.class);
+                    responseBuffer.append(ollamaResponseModel.getError());
+                } else {
+                    boolean finished = parseResponseAndAddToBuffer(line, responseBuffer);
+                        ollamaChatResponseModel = Utils.getObjectMapper().readValue(line, OllamaChatResponseModel.class);
+                    if(body.stream && ollamaChatResponseModel.getMessage().getToolCalls() != null){
+                        wantedToolsForStream = ollamaChatResponseModel.getMessage().getToolCalls();
+                    }
+                    if (finished && body.stream) {
+                        ollamaChatResponseModel.getMessage().setContent(responseBuffer.toString());
+                        break;
+                    }
+                }
+            }
+        }
+        if (statusCode != 200) {
+            LOG.error("Status code " + statusCode);
+            throw new OllamaBaseException(responseBuffer.toString());
+        } else {
+            if(wantedToolsForStream != null) {
+                ollamaChatResponseModel.getMessage().setToolCalls(wantedToolsForStream);
+            }
+            OllamaChatResult ollamaResult =
+                    new OllamaChatResult(ollamaChatResponseModel,body.getMessages());
+            if (isVerbose()) LOG.info("Model response: " + ollamaResult);
+            return ollamaResult;
+        }
     }
 }

src/main/java/io/github/ollama4j/models/request/OllamaEndpointCaller.java

@@ -1,41 +1,31 @@
 package io.github.ollama4j.models.request;
 
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.exceptions.OllamaBaseException;
-import io.github.ollama4j.models.response.OllamaErrorResponse;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.utils.OllamaRequestBody;
-import io.github.ollama4j.utils.Utils;
+import java.net.URI;
+import java.net.http.HttpRequest;
+import java.time.Duration;
+
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import java.io.BufferedReader;
-import java.io.IOException;
-import java.io.InputStream;
-import java.io.InputStreamReader;
-import java.net.URI;
-import java.net.http.HttpClient;
-import java.net.http.HttpRequest;
-import java.net.http.HttpResponse;
-import java.nio.charset.StandardCharsets;
-import java.time.Duration;
-import java.util.Base64;
+import io.github.ollama4j.OllamaAPI;
+import lombok.Getter;
 
 /**
  * Abstract helperclass to call the ollama api server.
  */
+@Getter
 public abstract class OllamaEndpointCaller {
 
     private static final Logger LOG = LoggerFactory.getLogger(OllamaAPI.class);
 
-    private String host;
-    private BasicAuth basicAuth;
-    private long requestTimeoutSeconds;
-    private boolean verbose;
+    private final String host;
+    private final Auth auth;
+    private final long requestTimeoutSeconds;
+    private final boolean verbose;
 
-    public OllamaEndpointCaller(String host, BasicAuth basicAuth, long requestTimeoutSeconds, boolean verbose) {
+    public OllamaEndpointCaller(String host, Auth auth, long requestTimeoutSeconds, boolean verbose) {
         this.host = host;
-        this.basicAuth = basicAuth;
+        this.auth = auth;
         this.requestTimeoutSeconds = requestTimeoutSeconds;
         this.verbose = verbose;
     }
@@ -45,107 +35,30 @@ public abstract class OllamaEndpointCaller {
     protected abstract boolean parseResponseAndAddToBuffer(String line, StringBuilder responseBuffer);
 
 
-    /**
-     * Calls the api server on the given host and endpoint suffix asynchronously, aka waiting for the response.
-     *
-     * @param body POST body payload
-     * @return result answer given by the assistant
-     * @throws OllamaBaseException  any response code than 200 has been returned
-     * @throws IOException          in case the responseStream can not be read
-     * @throws InterruptedException in case the server is not reachable or network issues happen
-     */
-    public OllamaResult callSync(OllamaRequestBody body) throws OllamaBaseException, IOException, InterruptedException {
-        // Create Request
-        long startTime = System.currentTimeMillis();
-        HttpClient httpClient = HttpClient.newHttpClient();
-        URI uri = URI.create(this.host + getEndpointSuffix());
-        HttpRequest.Builder requestBuilder =
-                getRequestBuilderDefault(uri)
-                        .POST(
-                                body.getBodyPublisher());
-        HttpRequest request = requestBuilder.build();
-        if (this.verbose) LOG.info("Asking model: " + body.toString());
-        HttpResponse<InputStream> response =
-                httpClient.send(request, HttpResponse.BodyHandlers.ofInputStream());
-
-        int statusCode = response.statusCode();
-        InputStream responseBodyStream = response.body();
-        StringBuilder responseBuffer = new StringBuilder();
-        try (BufferedReader reader =
-                     new BufferedReader(new InputStreamReader(responseBodyStream, StandardCharsets.UTF_8))) {
-            String line;
-            while ((line = reader.readLine()) != null) {
-                if (statusCode == 404) {
-                    LOG.warn("Status code: 404 (Not Found)");
-                    OllamaErrorResponse ollamaResponseModel =
-                            Utils.getObjectMapper().readValue(line, OllamaErrorResponse.class);
-                    responseBuffer.append(ollamaResponseModel.getError());
-                } else if (statusCode == 401) {
-                    LOG.warn("Status code: 401 (Unauthorized)");
-                    OllamaErrorResponse ollamaResponseModel =
-                            Utils.getObjectMapper()
-                                    .readValue("{\"error\":\"Unauthorized\"}", OllamaErrorResponse.class);
-                    responseBuffer.append(ollamaResponseModel.getError());
-                } else if (statusCode == 400) {
-                    LOG.warn("Status code: 400 (Bad Request)");
-                    OllamaErrorResponse ollamaResponseModel = Utils.getObjectMapper().readValue(line,
-                            OllamaErrorResponse.class);
-                    responseBuffer.append(ollamaResponseModel.getError());
-                } else {
-                    boolean finished = parseResponseAndAddToBuffer(line, responseBuffer);
-                    if (finished) {
-                        break;
-                    }
-                }
-            }
-        }
-
-        if (statusCode != 200) {
-            LOG.error("Status code " + statusCode);
-            throw new OllamaBaseException(responseBuffer.toString());
-        } else {
-            long endTime = System.currentTimeMillis();
-            OllamaResult ollamaResult =
-                    new OllamaResult(responseBuffer.toString().trim(), endTime - startTime, statusCode);
-            if (verbose) LOG.info("Model response: " + ollamaResult);
-            return ollamaResult;
-        }
-    }
-
     /**
      * Get default request builder.
      *
      * @param uri URI to get a HttpRequest.Builder
      * @return HttpRequest.Builder
      */
-    private HttpRequest.Builder getRequestBuilderDefault(URI uri) {
+    protected HttpRequest.Builder getRequestBuilderDefault(URI uri) {
         HttpRequest.Builder requestBuilder =
                 HttpRequest.newBuilder(uri)
                         .header("Content-Type", "application/json")
                         .timeout(Duration.ofSeconds(this.requestTimeoutSeconds));
-        if (isBasicAuthCredentialsSet()) {
-            requestBuilder.header("Authorization", getBasicAuthHeaderValue());
+        if (isAuthCredentialsSet()) {
+            requestBuilder.header("Authorization", this.auth.getAuthHeaderValue());
         }
         return requestBuilder;
     }
 
     /**
-     * Get basic authentication header value.
+     * Check if Auth credentials set.
      *
-     * @return basic authentication header value (encoded credentials)
+     * @return true when Auth credentials set
      */
-    private String getBasicAuthHeaderValue() {
-        String credentialsToEncode = this.basicAuth.getUsername() + ":" + this.basicAuth.getPassword();
-        return "Basic " + Base64.getEncoder().encodeToString(credentialsToEncode.getBytes());
-    }
-
-    /**
-     * Check if Basic Auth credentials set.
-     *
-     * @return true when Basic Auth credentials set
-     */
-    private boolean isBasicAuthCredentialsSet() {
-        return this.basicAuth != null;
+    protected boolean isAuthCredentialsSet() {
+        return this.auth != null;
     }
 
 }

src/main/java/io/github/ollama4j/models/request/OllamaGenerateEndpointCaller.java

@@ -2,6 +2,7 @@ package io.github.ollama4j.models.request;
 
 import com.fasterxml.jackson.core.JsonProcessingException;
 import io.github.ollama4j.exceptions.OllamaBaseException;
+import io.github.ollama4j.models.response.OllamaErrorResponse;
 import io.github.ollama4j.models.response.OllamaResult;
 import io.github.ollama4j.models.generate.OllamaGenerateResponseModel;
 import io.github.ollama4j.models.generate.OllamaGenerateStreamObserver;
@@ -11,7 +12,15 @@ import io.github.ollama4j.utils.Utils;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
+import java.io.BufferedReader;
 import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.net.URI;
+import java.net.http.HttpClient;
+import java.net.http.HttpRequest;
+import java.net.http.HttpResponse;
+import java.nio.charset.StandardCharsets;
 
 public class OllamaGenerateEndpointCaller extends OllamaEndpointCaller {
 
@@ -19,7 +28,7 @@ public class OllamaGenerateEndpointCaller extends OllamaEndpointCaller {
 
     private OllamaGenerateStreamObserver streamObserver;
 
-    public OllamaGenerateEndpointCaller(String host, BasicAuth basicAuth, long requestTimeoutSeconds, boolean verbose) {
+    public OllamaGenerateEndpointCaller(String host, Auth basicAuth, long requestTimeoutSeconds, boolean verbose) {
         super(host, basicAuth, requestTimeoutSeconds, verbose);
     }
 
@@ -46,6 +55,73 @@ public class OllamaGenerateEndpointCaller extends OllamaEndpointCaller {
     public OllamaResult call(OllamaRequestBody body, OllamaStreamHandler streamHandler)
             throws OllamaBaseException, IOException, InterruptedException {
         streamObserver = new OllamaGenerateStreamObserver(streamHandler);
-        return super.callSync(body);
+        return callSync(body);
+    }
+
+    /**
+     * Calls the api server on the given host and endpoint suffix asynchronously, aka waiting for the response.
+     *
+     * @param body POST body payload
+     * @return result answer given by the assistant
+     * @throws OllamaBaseException  any response code than 200 has been returned
+     * @throws IOException          in case the responseStream can not be read
+     * @throws InterruptedException in case the server is not reachable or network issues happen
+     */
+    public OllamaResult callSync(OllamaRequestBody body) throws OllamaBaseException, IOException, InterruptedException {
+        // Create Request
+        long startTime = System.currentTimeMillis();
+        HttpClient httpClient = HttpClient.newHttpClient();
+        URI uri = URI.create(getHost() + getEndpointSuffix());
+        HttpRequest.Builder requestBuilder =
+                getRequestBuilderDefault(uri)
+                        .POST(
+                                body.getBodyPublisher());
+        HttpRequest request = requestBuilder.build();
+        if (isVerbose()) LOG.info("Asking model: " + body.toString());
+        HttpResponse<InputStream> response =
+                httpClient.send(request, HttpResponse.BodyHandlers.ofInputStream());
+
+        int statusCode = response.statusCode();
+        InputStream responseBodyStream = response.body();
+        StringBuilder responseBuffer = new StringBuilder();
+        try (BufferedReader reader =
+                     new BufferedReader(new InputStreamReader(responseBodyStream, StandardCharsets.UTF_8))) {
+            String line;
+            while ((line = reader.readLine()) != null) {
+                if (statusCode == 404) {
+                    LOG.warn("Status code: 404 (Not Found)");
+                    OllamaErrorResponse ollamaResponseModel =
+                            Utils.getObjectMapper().readValue(line, OllamaErrorResponse.class);
+                    responseBuffer.append(ollamaResponseModel.getError());
+                } else if (statusCode == 401) {
+                    LOG.warn("Status code: 401 (Unauthorized)");
+                    OllamaErrorResponse ollamaResponseModel =
+                            Utils.getObjectMapper()
+                                    .readValue("{\"error\":\"Unauthorized\"}", OllamaErrorResponse.class);
+                    responseBuffer.append(ollamaResponseModel.getError());
+                } else if (statusCode == 400) {
+                    LOG.warn("Status code: 400 (Bad Request)");
+                    OllamaErrorResponse ollamaResponseModel = Utils.getObjectMapper().readValue(line,
+                            OllamaErrorResponse.class);
+                    responseBuffer.append(ollamaResponseModel.getError());
+                } else {
+                    boolean finished = parseResponseAndAddToBuffer(line, responseBuffer);
+                    if (finished) {
+                        break;
+                    }
+                }
+            }
+        }
+
+        if (statusCode != 200) {
+            LOG.error("Status code " + statusCode);
+            throw new OllamaBaseException(responseBuffer.toString());
+        } else {
+            long endTime = System.currentTimeMillis();
+            OllamaResult ollamaResult =
+                    new OllamaResult(responseBuffer.toString().trim(), endTime - startTime, statusCode);
+            if (isVerbose()) LOG.info("Model response: " + ollamaResult);
+            return ollamaResult;
+        }
     }
 }

src/main/java/io/github/ollama4j/models/response/Model.java

@@ -2,12 +2,14 @@ package io.github.ollama4j.models.response;
 
 import java.time.OffsetDateTime;
 
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.fasterxml.jackson.core.JsonProcessingException;
 import io.github.ollama4j.utils.Utils;
 import lombok.Data;
 
 @Data
+@JsonIgnoreProperties(ignoreUnknown = true)
 public class Model {
 
   private String name;

src/main/java/io/github/ollama4j/models/response/OllamaResult.java

@@ -1,19 +1,26 @@
 package io.github.ollama4j.models.response;
 
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.core.type.TypeReference;
+
+import lombok.Data;
+import lombok.Getter;
+
 import static io.github.ollama4j.utils.Utils.getObjectMapper;
 
-import com.fasterxml.jackson.core.JsonProcessingException;
-import lombok.Data;
-import lombok.Getter;
+import java.util.HashMap;
+import java.util.Map;
 
 /** The type Ollama result. */
 @Getter
 @SuppressWarnings("unused")
 @Data
+@JsonIgnoreProperties(ignoreUnknown = true)
 public class OllamaResult {
   /**
    * -- GETTER --
-   *  Get the completion/response text
+   * Get the completion/response text
    *
    * @return String completion/response text
    */
@@ -21,7 +28,7 @@ public class OllamaResult {
 
   /**
    * -- GETTER --
-   *  Get the response status code.
+   * Get the response status code.
    *
    * @return int - response status code
    */
@@ -29,7 +36,7 @@ public class OllamaResult {
 
   /**
    * -- GETTER --
-   *  Get the response time in milliseconds.
+   * Get the response time in milliseconds.
    *
    * @return long - response time in milliseconds
    */
@@ -44,9 +51,68 @@ public class OllamaResult {
   @Override
   public String toString() {
     try {
-      return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
+      Map<String, Object> responseMap = new HashMap<>();
+      responseMap.put("response", this.response);
+      responseMap.put("httpStatusCode", this.httpStatusCode);
+      responseMap.put("responseTime", this.responseTime);
+      return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(responseMap);
     } catch (JsonProcessingException e) {
       throw new RuntimeException(e);
     }
   }
+
+  /**
+   * Get the structured response if the response is a JSON object.
+   *
+   * @return Map - structured response
+   * @throws IllegalArgumentException if the response is not a valid JSON object
+   */
+  public Map<String, Object> getStructuredResponse() {
+    String responseStr = this.getResponse();
+    if (responseStr == null || responseStr.trim().isEmpty()) {
+      throw new IllegalArgumentException("Response is empty or null");
+    }
+
+    try {
+      // Check if the response is a valid JSON
+      if ((!responseStr.trim().startsWith("{") && !responseStr.trim().startsWith("[")) ||
+          (!responseStr.trim().endsWith("}") && !responseStr.trim().endsWith("]"))) {
+        throw new IllegalArgumentException("Response is not a valid JSON object");
+      }
+
+      Map<String, Object> response = getObjectMapper().readValue(responseStr,
+          new TypeReference<Map<String, Object>>() {
+          });
+      return response;
+    } catch (JsonProcessingException e) {
+      throw new IllegalArgumentException("Failed to parse response as JSON: " + e.getMessage(), e);
+    }
+  }
+
+  /**
+   * Get the structured response mapped to a specific class type.
+   *
+   * @param <T> The type of class to map the response to
+   * @param clazz The class to map the response to
+   * @return An instance of the specified class with the response data
+   * @throws IllegalArgumentException if the response is not a valid JSON or is empty
+   * @throws RuntimeException if there is an error mapping the response
+   */
+  public <T> T as(Class<T> clazz) {
+    String responseStr = this.getResponse();
+    if (responseStr == null || responseStr.trim().isEmpty()) {
+      throw new IllegalArgumentException("Response is empty or null");
+    }
+
+    try {
+      // Check if the response is a valid JSON
+      if ((!responseStr.trim().startsWith("{") && !responseStr.trim().startsWith("[")) ||
+          (!responseStr.trim().endsWith("}") && !responseStr.trim().endsWith("]"))) {
+        throw new IllegalArgumentException("Response is not a valid JSON object");
+      }
+      return getObjectMapper().readValue(responseStr, clazz);
+    } catch (JsonProcessingException e) {
+      throw new IllegalArgumentException("Failed to parse response as JSON: " + e.getMessage(), e);
+    }
+  }
 }

src/main/java/io/github/ollama4j/models/response/OllamaStructuredResult.java

@@ -0,0 +1,77 @@
+package io.github.ollama4j.models.response;
+
+import static io.github.ollama4j.utils.Utils.getObjectMapper;
+
+import java.util.Map;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.core.type.TypeReference;
+
+import lombok.Data;
+import lombok.Getter;
+import lombok.NoArgsConstructor;
+
+@Getter
+@SuppressWarnings("unused")
+@Data
+@NoArgsConstructor
+@JsonIgnoreProperties(ignoreUnknown = true)
+public class OllamaStructuredResult {
+  private String response;
+
+  private int httpStatusCode;
+
+  private long responseTime = 0;
+
+  private String model;
+
+  public OllamaStructuredResult(String response, long responseTime, int httpStatusCode) {
+    this.response = response;
+    this.responseTime = responseTime;
+    this.httpStatusCode = httpStatusCode;
+  }
+
+  @Override
+  public String toString() {
+    try {
+      return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
+    } catch (JsonProcessingException e) {
+      throw new RuntimeException(e);
+    }
+  }
+
+  /**
+   * Get the structured response if the response is a JSON object.
+   *
+   * @return Map - structured response
+   */
+  public Map<String, Object> getStructuredResponse() {
+    try {
+      Map<String, Object> response = getObjectMapper().readValue(this.getResponse(),
+          new TypeReference<Map<String, Object>>() {
+          });
+      return response;
+    } catch (JsonProcessingException e) {
+      throw new RuntimeException(e);
+    }
+  }
+
+  /**
+   * Get the structured response mapped to a specific class type.
+   *
+   * @param <T> The type of class to map the response to
+   * @param clazz The class to map the response to
+   * @return An instance of the specified class with the response data
+   * @throws RuntimeException if there is an error mapping the response
+   */
+  public <T> T getStructuredResponse(Class<T> clazz) {
+    try {
+      return getObjectMapper().readValue(this.getResponse(), clazz);
+    } catch (JsonProcessingException e) {
+      throw new RuntimeException(e);
+    }
+  }
+}

src/main/java/io/github/ollama4j/models/response/OllamaVersion.java

@@ -0,0 +1,10 @@
+package io.github.ollama4j.models.response;
+
+import lombok.Data;
+
+import java.util.List;
+
+@Data
+public class OllamaVersion {
+    private String version;
+}

src/main/java/io/github/ollama4j/tools/OllamaToolCallsFunction.java

@@ -0,0 +1,18 @@
+package io.github.ollama4j.tools;
+
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.util.Map;
+
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+@JsonIgnoreProperties(ignoreUnknown = true)
+public class OllamaToolCallsFunction
+{
+    private String name;
+    private Map<String,Object> arguments;
+}

src/main/java/io/github/ollama4j/tools/OllamaToolsResult.java

@@ -18,6 +18,9 @@ public class OllamaToolsResult {
 
     public List<ToolResult> getToolResults() {
         List<ToolResult> results = new ArrayList<>();
+        if (this.toolResults == null) {
+            return results;
+        }
         for (Map.Entry<ToolFunctionCallSpec, Object> r : this.toolResults.entrySet()) {
             results.add(new ToolResult(r.getKey().getName(), r.getKey().getArguments(), r.getValue()));
         }

src/main/java/io/github/ollama4j/tools/ReflectionalToolFunction.java

@@ -0,0 +1,54 @@
+package io.github.ollama4j.tools;
+
+import lombok.AllArgsConstructor;
+import lombok.Getter;
+import lombok.Setter;
+
+import java.lang.reflect.Method;
+import java.math.BigDecimal;
+import java.util.LinkedHashMap;
+import java.util.Map;
+
+/**
+ * Specification of a {@link ToolFunction} that provides the implementation via java reflection calling.
+ */
+@Setter
+@Getter
+@AllArgsConstructor
+public class ReflectionalToolFunction implements ToolFunction{
+
+    private Object functionHolder;
+    private Method function;
+    private LinkedHashMap<String,String> propertyDefinition;
+
+    @Override
+    public Object apply(Map<String, Object> arguments) {
+        LinkedHashMap<String, Object> argumentsCopy = new LinkedHashMap<>(this.propertyDefinition);
+        for (Map.Entry<String,String> param : this.propertyDefinition.entrySet()){
+            argumentsCopy.replace(param.getKey(),typeCast(arguments.get(param.getKey()),param.getValue()));
+        }
+        try {
+            return function.invoke(functionHolder, argumentsCopy.values().toArray());
+        } catch (Exception e) {
+            throw new RuntimeException("Failed to invoke tool: " + function.getName(), e);
+        }
+    }
+
+    private Object typeCast(Object inputValue, String className) {
+        if(className == null || inputValue == null) {
+            return null;
+        }
+        String inputValueString = inputValue.toString();
+        switch (className) {
+            case "java.lang.Integer":
+                return Integer.parseInt(inputValueString);
+            case "java.lang.Boolean":
+                return Boolean.valueOf(inputValueString);
+            case "java.math.BigDecimal":
+                return new BigDecimal(inputValueString);
+            default:
+                return inputValueString;
+        }
+    }
+
+}

src/main/java/io/github/ollama4j/tools/ToolRegistry.java

@@ -1,16 +1,22 @@
 package io.github.ollama4j.tools;
 
+import java.util.Collection;
 import java.util.HashMap;
 import java.util.Map;
 
 public class ToolRegistry {
-    private final Map<String, ToolFunction> functionMap = new HashMap<>();
+    private final Map<String, Tools.ToolSpecification> tools = new HashMap<>();
 
-    public ToolFunction getFunction(String name) {
-        return functionMap.get(name);
+    public ToolFunction getToolFunction(String name) {
+        final Tools.ToolSpecification toolSpecification = tools.get(name);
+        return toolSpecification !=null ? toolSpecification.getToolFunction() : null ;
     }
 
-    public void addFunction(String name, ToolFunction function) {
-        functionMap.put(name, function);
+    public void addTool (String name, Tools.ToolSpecification specification) {
+        tools.put(name, specification);
+    }
+
+    public Collection<Tools.ToolSpecification> getRegisteredSpecs(){
+        return tools.values();
     }
 }

src/main/java/io/github/ollama4j/tools/Tools.java

@@ -6,8 +6,10 @@ import com.fasterxml.jackson.annotation.JsonInclude;
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.fasterxml.jackson.core.JsonProcessingException;
 import io.github.ollama4j.utils.Utils;
+import lombok.AllArgsConstructor;
 import lombok.Builder;
 import lombok.Data;
+import lombok.NoArgsConstructor;
 
 import java.util.ArrayList;
 import java.util.HashMap;
@@ -20,17 +22,23 @@ public class Tools {
     public static class ToolSpecification {
         private String functionName;
         private String functionDescription;
-        private Map<String, PromptFuncDefinition.Property> properties;
-        private ToolFunction toolDefinition;
+        private PromptFuncDefinition toolPrompt;
+        private ToolFunction toolFunction;
     }
 
     @Data
     @JsonIgnoreProperties(ignoreUnknown = true)
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
     public static class PromptFuncDefinition {
         private String type;
         private PromptFuncSpec function;
 
         @Data
+        @Builder
+        @NoArgsConstructor
+        @AllArgsConstructor
         public static class PromptFuncSpec {
             private String name;
             private String description;
@@ -38,6 +46,9 @@ public class Tools {
         }
 
         @Data
+        @Builder
+        @NoArgsConstructor
+        @AllArgsConstructor
         public static class Parameters {
             private String type;
             private Map<String, Property> properties;
@@ -46,6 +57,8 @@ public class Tools {
 
         @Data
         @Builder
+        @NoArgsConstructor
+        @AllArgsConstructor
         public static class Property {
             private String type;
             private String description;
@@ -94,10 +107,10 @@ public class Tools {
 
             PromptFuncDefinition.Parameters parameters = new PromptFuncDefinition.Parameters();
             parameters.setType("object");
-            parameters.setProperties(spec.getProperties());
+            parameters.setProperties(spec.getToolPrompt().getFunction().parameters.getProperties());
 
             List<String> requiredValues = new ArrayList<>();
-            for (Map.Entry<String, PromptFuncDefinition.Property> p : spec.getProperties().entrySet()) {
+            for (Map.Entry<String, PromptFuncDefinition.Property> p : spec.getToolPrompt().getFunction().getParameters().getProperties().entrySet()) {
                 if (p.getValue().isRequired()) {
                     requiredValues.add(p.getKey());
                 }

src/main/java/io/github/ollama4j/tools/annotations/OllamaToolService.java

@@ -0,0 +1,23 @@
+package io.github.ollama4j.tools.annotations;
+
+import io.github.ollama4j.OllamaAPI;
+
+import java.lang.annotation.ElementType;
+import java.lang.annotation.Retention;
+import java.lang.annotation.RetentionPolicy;
+import java.lang.annotation.Target;
+
+/**
+ * Annotates a class that calls {@link io.github.ollama4j.OllamaAPI} such that the Method
+ * {@link OllamaAPI#registerAnnotatedTools()} can be used to auto-register all provided classes (resp. all
+ * contained Methods of the provider classes annotated with {@link ToolSpec}).
+ */
+@Target(ElementType.TYPE)
+@Retention(RetentionPolicy.RUNTIME)
+public @interface OllamaToolService {
+
+    /**
+     * @return Classes with no-arg constructor that will be used for tool-registration.
+     */
+    Class<?>[] providers();
+}

src/main/java/io/github/ollama4j/tools/annotations/ToolProperty.java

@@ -0,0 +1,32 @@
+package io.github.ollama4j.tools.annotations;
+
+import java.lang.annotation.ElementType;
+import java.lang.annotation.Retention;
+import java.lang.annotation.RetentionPolicy;
+import java.lang.annotation.Target;
+
+/**
+ * Annotates a Method Parameter in a {@link ToolSpec} annotated Method. A parameter annotated with this annotation will
+ * be part of the tool description that is sent to the llm for tool-calling.
+ */
+@Retention(RetentionPolicy.RUNTIME)
+@Target(ElementType.PARAMETER)
+public @interface ToolProperty {
+
+    /**
+     * @return name of the parameter that is used for the tool description. Has to be set as depending on the caller,
+     * method name backtracking is not possible with reflection.
+     */
+    String name();
+
+    /**
+     * @return a detailed description of the parameter. This is used by the llm called to specify, which property has
+     * to be set by the llm and how this should be filled.
+     */
+    String desc();
+
+    /**
+     * @return tells the llm that it has to set a value for this property.
+     */
+    boolean required() default true;
+}

src/main/java/io/github/ollama4j/tools/annotations/ToolSpec.java

@@ -0,0 +1,28 @@
+package io.github.ollama4j.tools.annotations;
+
+import io.github.ollama4j.OllamaAPI;
+
+import java.lang.annotation.ElementType;
+import java.lang.annotation.Retention;
+import java.lang.annotation.RetentionPolicy;
+import java.lang.annotation.Target;
+
+/**
+ * Annotates Methods of classes that should be registered as tools by {@link OllamaAPI#registerAnnotatedTools()}
+ * automatically.
+ */
+@Target(ElementType.METHOD)
+@Retention(RetentionPolicy.RUNTIME)
+public @interface ToolSpec {
+
+    /**
+     * @return tool-name that the method should be used as. Defaults to the methods name.
+     */
+    String name() default "";
+
+    /**
+     * @return a detailed description of the method that can be interpreted by the llm, whether it should call the tool
+     * or not.
+     */
+    String desc();
+}

src/main/java/io/github/ollama4j/types/OllamaModelType.java

@@ -15,6 +15,7 @@ public class OllamaModelType {
     public static final String LLAMA3_1 = "llama3.1";
     public static final String MISTRAL = "mistral";
     public static final String MIXTRAL = "mixtral";
+    public static final String DEEPSEEK_R1 = "deepseek-r1";
     public static final String LLAVA = "llava";
     public static final String LLAVA_PHI3 = "llava-phi3";
     public static final String NEURAL_CHAT = "neural-chat";

src/test/java/io/github/ollama4j/integrationtests/OllamaAPIIntegrationTest.java

@@ -0,0 +1,681 @@
+package io.github.ollama4j.integrationtests;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import io.github.ollama4j.OllamaAPI;
+import io.github.ollama4j.exceptions.OllamaBaseException;
+import io.github.ollama4j.exceptions.ToolInvocationException;
+import io.github.ollama4j.models.chat.*;
+import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
+import io.github.ollama4j.models.response.LibraryModel;
+import io.github.ollama4j.models.response.Model;
+import io.github.ollama4j.models.response.ModelDetail;
+import io.github.ollama4j.models.response.OllamaResult;
+import io.github.ollama4j.samples.AnnotatedTool;
+import io.github.ollama4j.tools.OllamaToolCallsFunction;
+import io.github.ollama4j.tools.ToolFunction;
+import io.github.ollama4j.tools.Tools;
+import io.github.ollama4j.tools.annotations.OllamaToolService;
+import io.github.ollama4j.utils.OptionsBuilder;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.MethodOrderer.OrderAnnotation;
+import org.junit.jupiter.api.Order;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.TestMethodOrder;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.testcontainers.ollama.OllamaContainer;
+
+import java.io.File;
+import java.io.IOException;
+import java.net.ConnectException;
+import java.net.URISyntaxException;
+import java.util.*;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+@OllamaToolService(providers = {AnnotatedTool.class})
+@TestMethodOrder(OrderAnnotation.class)
+
+@SuppressWarnings({"HttpUrlsUsage", "SpellCheckingInspection"})
+public class OllamaAPIIntegrationTest {
+    private static final Logger LOG = LoggerFactory.getLogger(OllamaAPIIntegrationTest.class);
+
+    private static OllamaContainer ollama;
+    private static OllamaAPI api;
+
+    private static final String EMBEDDING_MODEL_MINILM = "all-minilm";
+    private static final String CHAT_MODEL_QWEN_SMALL = "qwen2.5:0.5b";
+    private static final String CHAT_MODEL_INSTRUCT = "qwen2.5:0.5b-instruct";
+    private static final String CHAT_MODEL_SYSTEM_PROMPT = "llama3.2:1b";
+    private static final String CHAT_MODEL_LLAMA3 = "llama3";
+    private static final String IMAGE_MODEL_LLAVA = "llava";
+
+    @BeforeAll
+    public static void setUp() {
+        try {
+            boolean useExternalOllamaHost = Boolean.parseBoolean(System.getenv("USE_EXTERNAL_OLLAMA_HOST"));
+            String ollamaHost = System.getenv("OLLAMA_HOST");
+            if (useExternalOllamaHost) {
+                LOG.info("Using external Ollama host...");
+                api = new OllamaAPI(ollamaHost);
+            } else {
+                throw new RuntimeException(
+                        "USE_EXTERNAL_OLLAMA_HOST is not set so, we will be using Testcontainers Ollama host for the tests now. If you would like to use an external host, please set the env var to USE_EXTERNAL_OLLAMA_HOST=true and set the env var OLLAMA_HOST=http://localhost:11435 or a different host/port.");
+            }
+        } catch (Exception e) {
+            String ollamaVersion = "0.6.1";
+            int internalPort = 11434;
+            int mappedPort = 11435;
+            ollama = new OllamaContainer("ollama/ollama:" + ollamaVersion);
+            ollama.addExposedPort(internalPort);
+            List<String> portBindings = new ArrayList<>();
+            portBindings.add(mappedPort + ":" + internalPort);
+            ollama.setPortBindings(portBindings);
+            ollama.start();
+            LOG.info("Using Testcontainer Ollama host...");
+            api = new OllamaAPI("http://" + ollama.getHost() + ":" + ollama.getMappedPort(internalPort));
+        }
+        api.setRequestTimeoutSeconds(120);
+        api.setVerbose(true);
+        api.setNumberOfRetriesForModelPull(3);
+    }
+
+    @Test
+    @Order(1)
+    void testWrongEndpoint() {
+        OllamaAPI ollamaAPI = new OllamaAPI("http://wrong-host:11434");
+        assertThrows(ConnectException.class, ollamaAPI::listModels);
+    }
+
+    @Test
+    @Order(1)
+    public void testVersionAPI() throws URISyntaxException, IOException, OllamaBaseException, InterruptedException {
+        // String expectedVersion = ollama.getDockerImageName().split(":")[1];
+        String actualVersion = api.getVersion();
+        assertNotNull(actualVersion);
+        // assertEquals(expectedVersion, actualVersion, "Version should match the Docker
+        // image version");
+    }
+
+    @Test
+    @Order(2)
+    public void testListModelsAPI()
+            throws URISyntaxException, IOException, OllamaBaseException, InterruptedException {
+        api.pullModel(EMBEDDING_MODEL_MINILM);
+        // Fetch the list of models
+        List<Model> models = api.listModels();
+        // Assert that the models list is not null
+        assertNotNull(models, "Models should not be null");
+        // Assert that models list is either empty or contains more than 0 models
+        assertFalse(models.isEmpty(), "Models list should not be empty");
+    }
+
+    @Test
+    @Order(2)
+    void testListModelsFromLibrary()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
+        List<LibraryModel> models = api.listModelsFromLibrary();
+        assertNotNull(models);
+        assertFalse(models.isEmpty());
+    }
+
+    @Test
+    @Order(3)
+    public void testPullModelAPI()
+            throws URISyntaxException, IOException, OllamaBaseException, InterruptedException {
+        api.pullModel(EMBEDDING_MODEL_MINILM);
+        List<Model> models = api.listModels();
+        assertNotNull(models, "Models should not be null");
+        assertFalse(models.isEmpty(), "Models list should contain elements");
+    }
+
+    @Test
+    @Order(4)
+    void testListModelDetails() throws IOException, OllamaBaseException, URISyntaxException, InterruptedException {
+        api.pullModel(EMBEDDING_MODEL_MINILM);
+        ModelDetail modelDetails = api.getModelDetails(EMBEDDING_MODEL_MINILM);
+        assertNotNull(modelDetails);
+        assertTrue(modelDetails.getModelFile().contains(EMBEDDING_MODEL_MINILM));
+    }
+
+    @Test
+    @Order(5)
+    public void testEmbeddings() throws Exception {
+        api.pullModel(EMBEDDING_MODEL_MINILM);
+        OllamaEmbedResponseModel embeddings = api.embed(EMBEDDING_MODEL_MINILM,
+                Arrays.asList("Why is the sky blue?", "Why is the grass green?"));
+        assertNotNull(embeddings, "Embeddings should not be null");
+        assertFalse(embeddings.getEmbeddings().isEmpty(), "Embeddings should not be empty");
+    }
+
+    @Test
+    @Order(6)
+    void testAskModelWithStructuredOutput()
+            throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
+        api.pullModel(CHAT_MODEL_LLAMA3);
+
+        int timeHour = 6;
+        boolean isNightTime = false;
+
+        String prompt = "The Sun is shining, and its " + timeHour + ". Its daytime.";
+
+        Map<String, Object> format = new HashMap<>();
+        format.put("type", "object");
+        format.put("properties", new HashMap<String, Object>() {
+            {
+                put("timeHour", new HashMap<String, Object>() {
+                    {
+                        put("type", "integer");
+                    }
+                });
+                put("isNightTime", new HashMap<String, Object>() {
+                    {
+                        put("type", "boolean");
+                    }
+                });
+            }
+        });
+        format.put("required", Arrays.asList("timeHour", "isNightTime"));
+
+        OllamaResult result = api.generate(CHAT_MODEL_LLAMA3, prompt, format);
+
+        assertNotNull(result);
+        assertNotNull(result.getResponse());
+        assertFalse(result.getResponse().isEmpty());
+
+        assertEquals(timeHour,
+                result.getStructuredResponse().get("timeHour"));
+        assertEquals(isNightTime,
+                result.getStructuredResponse().get("isNightTime"));
+
+        TimeOfDay timeOfDay = result.as(TimeOfDay.class);
+
+        assertEquals(timeHour, timeOfDay.getTimeHour());
+        assertEquals(isNightTime, timeOfDay.isNightTime());
+    }
+
+    @Test
+    @Order(6)
+    void testAskModelWithDefaultOptions()
+            throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
+        api.pullModel(CHAT_MODEL_QWEN_SMALL);
+        OllamaResult result = api.generate(CHAT_MODEL_QWEN_SMALL,
+                "What is the capital of France? And what's France's connection with Mona Lisa?", false,
+                new OptionsBuilder().build());
+        assertNotNull(result);
+        assertNotNull(result.getResponse());
+        assertFalse(result.getResponse().isEmpty());
+    }
+
+    @Test
+    @Order(7)
+    void testAskModelWithDefaultOptionsStreamed()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
+        api.pullModel(CHAT_MODEL_QWEN_SMALL);
+        StringBuffer sb = new StringBuffer();
+        OllamaResult result = api.generate(CHAT_MODEL_QWEN_SMALL,
+                "What is the capital of France? And what's France's connection with Mona Lisa?", false,
+                new OptionsBuilder().build(), (s) -> {
+                    LOG.info(s);
+                    String substring = s.substring(sb.toString().length(), s.length());
+                    LOG.info(substring);
+                    sb.append(substring);
+                });
+
+        assertNotNull(result);
+        assertNotNull(result.getResponse());
+        assertFalse(result.getResponse().isEmpty());
+        assertEquals(sb.toString().trim(), result.getResponse().trim());
+    }
+
+    @Test
+    @Order(8)
+    void testAskModelWithOptions()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_INSTRUCT);
+
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_INSTRUCT);
+        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM,
+                        "You are a helpful assistant who can generate random person's first and last names in the format [First name, Last name].")
+                .build();
+        requestModel = builder.withMessages(requestModel.getMessages())
+                .withMessage(OllamaChatMessageRole.USER, "Give me a cool name")
+                .withOptions(new OptionsBuilder().setTemperature(0.5f).build()).build();
+        OllamaChatResult chatResult = api.chat(requestModel);
+
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertFalse(chatResult.getResponseModel().getMessage().getContent().isEmpty());
+    }
+
+    @Test
+    @Order(9)
+    void testChatWithSystemPrompt()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM,
+                        "You are a silent bot that only says 'Shush'. Do not say anything else under any circumstances!")
+                .withMessage(OllamaChatMessageRole.USER, "What's something that's brown and sticky?")
+                .withOptions(new OptionsBuilder().setTemperature(0.8f).build()).build();
+
+        OllamaChatResult chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertNotNull(chatResult.getResponseModel().getMessage());
+        assertFalse(chatResult.getResponseModel().getMessage().getContent().isBlank());
+        assertTrue(chatResult.getResponseModel().getMessage().getContent().contains("Shush"));
+        assertEquals(3, chatResult.getChatHistory().size());
+    }
+
+    @Test
+    @Order(10)
+    public void testChat() throws Exception {
+        api.pullModel(CHAT_MODEL_LLAMA3);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_LLAMA3);
+
+        // Create the initial user question
+        OllamaChatRequest requestModel = builder
+                .withMessage(OllamaChatMessageRole.USER, "What is 1+1? Answer only in numbers.")
+                .build();
+
+        // Start conversation with model
+        OllamaChatResult chatResult = api.chat(requestModel);
+
+        assertTrue(chatResult.getChatHistory().stream().anyMatch(chat -> chat.getContent().contains("2")),
+                "Expected chat history to contain '2'");
+
+        // Create the next user question: second largest city
+        requestModel = builder.withMessages(chatResult.getChatHistory())
+                .withMessage(OllamaChatMessageRole.USER, "And what is its squared value?").build();
+
+        // Continue conversation with model
+        chatResult = api.chat(requestModel);
+
+        assertTrue(chatResult.getChatHistory().stream().anyMatch(chat -> chat.getContent().contains("4")),
+                "Expected chat history to contain '4'");
+
+        // Create the next user question: the third question
+        requestModel = builder.withMessages(chatResult.getChatHistory())
+                .withMessage(OllamaChatMessageRole.USER,
+                        "What is the largest value between 2, 4 and 6?")
+                .build();
+
+        // Continue conversation with the model for the third question
+        chatResult = api.chat(requestModel);
+
+        // verify the result
+        assertNotNull(chatResult, "Chat result should not be null");
+        assertTrue(chatResult.getChatHistory().size() > 2,
+                "Chat history should contain more than two messages");
+        assertTrue(chatResult.getChatHistory().get(chatResult.getChatHistory().size() - 1).getContent()
+                        .contains("6"),
+                "Response should contain '6'");
+    }
+
+    @Test
+    @Order(10)
+    void testChatWithImageFromURL()
+            throws OllamaBaseException, IOException, InterruptedException, URISyntaxException, ToolInvocationException {
+        api.pullModel(IMAGE_MODEL_LLAVA);
+
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(IMAGE_MODEL_LLAVA);
+        OllamaChatRequest requestModel = builder
+                .withMessage(OllamaChatMessageRole.USER, "What's in the picture?",
+                        Collections.emptyList(),
+                        "https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg")
+                .build();
+        api.registerAnnotatedTools(new OllamaAPIIntegrationTest());
+
+        OllamaChatResult chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+    }
+
+    @Test
+    @Order(10)
+    void testChatWithImageFromFileWithHistoryRecognition()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(IMAGE_MODEL_LLAVA);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(IMAGE_MODEL_LLAVA);
+        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
+                        "What's in the picture?",
+                        Collections.emptyList(), List.of(getImageFileFromClasspath("emoji-smile.jpeg")))
+                .build();
+
+        OllamaChatResult chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        builder.reset();
+
+        requestModel = builder.withMessages(chatResult.getChatHistory())
+                .withMessage(OllamaChatMessageRole.USER, "What's the color?").build();
+
+        chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+    }
+
+    @Test
+    @Order(11)
+    void testChatWithExplicitToolDefinition()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_SYSTEM_PROMPT);
+
+        final Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
+                .functionName("get-employee-details")
+                .functionDescription("Get employee details from the database")
+                .toolPrompt(Tools.PromptFuncDefinition.builder().type("function")
+                        .function(Tools.PromptFuncDefinition.PromptFuncSpec.builder()
+                                .name("get-employee-details")
+                                .description("Get employee details from the database")
+                                .parameters(Tools.PromptFuncDefinition.Parameters
+                                        .builder().type("object")
+                                        .properties(new Tools.PropsBuilder()
+                                                .withProperty("employee-name",
+                                                        Tools.PromptFuncDefinition.Property
+                                                                .builder()
+                                                                .type("string")
+                                                                .description("The name of the employee, e.g. John Doe")
+                                                                .required(true)
+                                                                .build())
+                                                .withProperty("employee-address",
+                                                        Tools.PromptFuncDefinition.Property
+                                                                .builder()
+                                                                .type("string")
+                                                                .description(
+                                                                        "The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India")
+                                                                .required(true)
+                                                                .build())
+                                                .withProperty("employee-phone",
+                                                        Tools.PromptFuncDefinition.Property
+                                                                .builder()
+                                                                .type("string")
+                                                                .description(
+                                                                        "The phone number of the employee. Always return a random value. e.g. 9911002233")
+                                                                .required(true)
+                                                                .build())
+                                                .build())
+                                        .required(List.of("employee-name"))
+                                        .build())
+                                .build())
+                        .build())
+                .toolFunction(arguments -> {
+                    // perform DB operations here
+                    return String.format(
+                            "Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}",
+                            UUID.randomUUID(), arguments.get("employee-name"),
+                            arguments.get("employee-address"),
+                            arguments.get("employee-phone"));
+                }).build();
+
+        api.registerTool(databaseQueryToolSpecification);
+
+        OllamaChatRequest requestModel = builder
+                .withMessage(OllamaChatMessageRole.USER,
+                        "Give me the ID of the employee named 'Rahul Kumar'?")
+                .build();
+
+        OllamaChatResult chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertNotNull(chatResult.getResponseModel().getMessage());
+        assertEquals(OllamaChatMessageRole.ASSISTANT.getRoleName(),
+                chatResult.getResponseModel().getMessage().getRole().getRoleName());
+        List<OllamaChatToolCalls> toolCalls = chatResult.getChatHistory().get(1).getToolCalls();
+        assertEquals(1, toolCalls.size());
+        OllamaToolCallsFunction function = toolCalls.get(0).getFunction();
+        assertEquals("get-employee-details", function.getName());
+        assert !function.getArguments().isEmpty();
+        Object employeeName = function.getArguments().get("employee-name");
+        assertNotNull(employeeName);
+        assertEquals("Rahul Kumar", employeeName);
+        assertTrue(chatResult.getChatHistory().size() > 2);
+        List<OllamaChatToolCalls> finalToolCalls = chatResult.getResponseModel().getMessage().getToolCalls();
+        assertNull(finalToolCalls);
+    }
+
+    @Test
+    @Order(12)
+    void testChatWithAnnotatedToolsAndSingleParam()
+            throws OllamaBaseException, IOException, InterruptedException, URISyntaxException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_SYSTEM_PROMPT);
+
+        api.registerAnnotatedTools();
+
+        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
+                "Compute the most important constant in the world using 5 digits").build();
+
+        OllamaChatResult chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertNotNull(chatResult.getResponseModel().getMessage());
+        assertEquals(OllamaChatMessageRole.ASSISTANT.getRoleName(),
+                chatResult.getResponseModel().getMessage().getRole().getRoleName());
+        List<OllamaChatToolCalls> toolCalls = chatResult.getChatHistory().get(1).getToolCalls();
+        assertEquals(1, toolCalls.size());
+        OllamaToolCallsFunction function = toolCalls.get(0).getFunction();
+        assertEquals("computeImportantConstant", function.getName());
+        assertEquals(1, function.getArguments().size());
+        Object noOfDigits = function.getArguments().get("noOfDigits");
+        assertNotNull(noOfDigits);
+        assertEquals("5", noOfDigits.toString());
+        assertTrue(chatResult.getChatHistory().size() > 2);
+        List<OllamaChatToolCalls> finalToolCalls = chatResult.getResponseModel().getMessage().getToolCalls();
+        assertNull(finalToolCalls);
+    }
+
+    @Test
+    @Order(13)
+    void testChatWithAnnotatedToolsAndMultipleParams()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_SYSTEM_PROMPT);
+
+        api.registerAnnotatedTools(new AnnotatedTool());
+
+        OllamaChatRequest requestModel = builder
+                .withMessage(OllamaChatMessageRole.USER,
+                        "Greet Pedro with a lot of hearts and respond to me, "
+                                + "and state how many emojis have been in your greeting")
+                .build();
+
+        OllamaChatResult chatResult = api.chat(requestModel);
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertNotNull(chatResult.getResponseModel().getMessage());
+        assertEquals(OllamaChatMessageRole.ASSISTANT.getRoleName(),
+                chatResult.getResponseModel().getMessage().getRole().getRoleName());
+        List<OllamaChatToolCalls> toolCalls = chatResult.getChatHistory().get(1).getToolCalls();
+        assertEquals(1, toolCalls.size());
+        OllamaToolCallsFunction function = toolCalls.get(0).getFunction();
+        assertEquals("sayHello", function.getName());
+        assertEquals(2, function.getArguments().size());
+        Object name = function.getArguments().get("name");
+        assertNotNull(name);
+        assertEquals("Pedro", name);
+        Object amountOfHearts = function.getArguments().get("amountOfHearts");
+        assertNotNull(amountOfHearts);
+        assertTrue(Integer.parseInt(amountOfHearts.toString()) > 1);
+        assertTrue(chatResult.getChatHistory().size() > 2);
+        List<OllamaChatToolCalls> finalToolCalls = chatResult.getResponseModel().getMessage().getToolCalls();
+        assertNull(finalToolCalls);
+    }
+
+    @Test
+    @Order(14)
+    void testChatWithToolsAndStream()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_SYSTEM_PROMPT);
+        final Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
+                .functionName("get-employee-details")
+                .functionDescription("Get employee details from the database")
+                .toolPrompt(Tools.PromptFuncDefinition.builder().type("function")
+                        .function(Tools.PromptFuncDefinition.PromptFuncSpec.builder()
+                                .name("get-employee-details")
+                                .description("Get employee details from the database")
+                                .parameters(Tools.PromptFuncDefinition.Parameters
+                                        .builder().type("object")
+                                        .properties(new Tools.PropsBuilder()
+                                                .withProperty("employee-name",
+                                                        Tools.PromptFuncDefinition.Property
+                                                                .builder()
+                                                                .type("string")
+                                                                .description("The name of the employee, e.g. John Doe")
+                                                                .required(true)
+                                                                .build())
+                                                .withProperty("employee-address",
+                                                        Tools.PromptFuncDefinition.Property
+                                                                .builder()
+                                                                .type("string")
+                                                                .description(
+                                                                        "The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India")
+                                                                .required(true)
+                                                                .build())
+                                                .withProperty("employee-phone",
+                                                        Tools.PromptFuncDefinition.Property
+                                                                .builder()
+                                                                .type("string")
+                                                                .description(
+                                                                        "The phone number of the employee. Always return a random value. e.g. 9911002233")
+                                                                .required(true)
+                                                                .build())
+                                                .build())
+                                        .required(List.of("employee-name"))
+                                        .build())
+                                .build())
+                        .build())
+                .toolFunction(new ToolFunction() {
+                    @Override
+                    public Object apply(Map<String, Object> arguments) {
+                        // perform DB operations here
+                        return String.format(
+                                "Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}",
+                                UUID.randomUUID(), arguments.get("employee-name"),
+                                arguments.get("employee-address"),
+                                arguments.get("employee-phone"));
+                    }
+                }).build();
+
+        api.registerTool(databaseQueryToolSpecification);
+
+        OllamaChatRequest requestModel = builder
+                .withMessage(OllamaChatMessageRole.USER,
+                        "Give me the ID of the employee named 'Rahul Kumar'?")
+                .build();
+
+        StringBuffer sb = new StringBuffer();
+
+        OllamaChatResult chatResult = api.chat(requestModel, (s) -> {
+            LOG.info(s);
+            String substring = s.substring(sb.toString().length());
+            LOG.info(substring);
+            sb.append(substring);
+        });
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertNotNull(chatResult.getResponseModel().getMessage());
+        assertNotNull(chatResult.getResponseModel().getMessage().getContent());
+        assertEquals(sb.toString().trim(), chatResult.getResponseModel().getMessage().getContent().trim());
+    }
+
+    @Test
+    @Order(15)
+    void testChatWithStream() throws OllamaBaseException, IOException, URISyntaxException, InterruptedException, ToolInvocationException {
+        api.pullModel(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(CHAT_MODEL_SYSTEM_PROMPT);
+        OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
+                        "What is the capital of France? And what's France's connection with Mona Lisa?")
+                .build();
+
+        StringBuffer sb = new StringBuffer();
+
+        OllamaChatResult chatResult = api.chat(requestModel, (s) -> {
+            LOG.info(s);
+            String substring = s.substring(sb.toString().length(), s.length());
+            LOG.info(substring);
+            sb.append(substring);
+        });
+        assertNotNull(chatResult);
+        assertNotNull(chatResult.getResponseModel());
+        assertNotNull(chatResult.getResponseModel().getMessage());
+        assertNotNull(chatResult.getResponseModel().getMessage().getContent());
+        assertEquals(sb.toString().trim(), chatResult.getResponseModel().getMessage().getContent().trim());
+    }
+
+    @Test
+    @Order(17)
+    void    testAskModelWithOptionsAndImageURLs()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
+        api.pullModel(IMAGE_MODEL_LLAVA);
+
+        OllamaResult result = api.generateWithImageURLs(IMAGE_MODEL_LLAVA, "What is in this image?",
+                List.of("https://upload.wikimedia.org/wikipedia/commons/thumb/a/aa/Noto_Emoji_v2.034_1f642.svg/360px-Noto_Emoji_v2.034_1f642.svg.png"),
+                new OptionsBuilder().build());
+        assertNotNull(result);
+        assertNotNull(result.getResponse());
+        assertFalse(result.getResponse().isEmpty());
+    }
+
+    @Test
+    @Order(18)
+    void testAskModelWithOptionsAndImageFiles()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
+        api.pullModel(IMAGE_MODEL_LLAVA);
+        File imageFile = getImageFileFromClasspath("emoji-smile.jpeg");
+        try {
+            OllamaResult result = api.generateWithImageFiles(IMAGE_MODEL_LLAVA, "What is in this image?",
+                    List.of(imageFile),
+                    new OptionsBuilder().build());
+            assertNotNull(result);
+            assertNotNull(result.getResponse());
+            assertFalse(result.getResponse().isEmpty());
+        } catch (IOException | OllamaBaseException | InterruptedException e) {
+            fail(e);
+        }
+    }
+
+    @Test
+    @Order(20)
+    void testAskModelWithOptionsAndImageFilesStreamed()
+            throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
+        api.pullModel(IMAGE_MODEL_LLAVA);
+
+        File imageFile = getImageFileFromClasspath("emoji-smile.jpeg");
+
+        StringBuffer sb = new StringBuffer();
+
+        OllamaResult result = api.generateWithImageFiles(IMAGE_MODEL_LLAVA, "What is in this image?",
+                List.of(imageFile),
+                new OptionsBuilder().build(), (s) -> {
+                    LOG.info(s);
+                    String substring = s.substring(sb.toString().length(), s.length());
+                    LOG.info(substring);
+                    sb.append(substring);
+                });
+        assertNotNull(result);
+        assertNotNull(result.getResponse());
+        assertFalse(result.getResponse().isEmpty());
+        assertEquals(sb.toString().trim(), result.getResponse().trim());
+    }
+
+    private File getImageFileFromClasspath(String fileName) {
+        ClassLoader classLoader = getClass().getClassLoader();
+        return new File(Objects.requireNonNull(classLoader.getResource(fileName)).getFile());
+    }
+}
+
+@Data
+@AllArgsConstructor
+@NoArgsConstructor
+class TimeOfDay {
+    @JsonProperty("timeHour")
+    private int timeHour;
+    @JsonProperty("isNightTime")
+    private boolean nightTime;
+}

src/test/java/io/github/ollama4j/integrationtests/TestRealAPIs.java

@@ -1,407 +0,0 @@
-package io.github.ollama4j.integrationtests;
-
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.exceptions.OllamaBaseException;
-import io.github.ollama4j.models.response.ModelDetail;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.models.embeddings.OllamaEmbeddingsRequestBuilder;
-import io.github.ollama4j.models.embeddings.OllamaEmbeddingsRequestModel;
-import io.github.ollama4j.utils.OptionsBuilder;
-import lombok.Data;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.Order;
-import org.junit.jupiter.api.Test;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-
-import java.io.File;
-import java.io.IOException;
-import java.io.InputStream;
-import java.net.ConnectException;
-import java.net.URISyntaxException;
-import java.net.http.HttpConnectTimeoutException;
-import java.util.List;
-import java.util.Objects;
-import java.util.Properties;
-
-import static org.junit.jupiter.api.Assertions.*;
-
-class TestRealAPIs {
-
-    private static final Logger LOG = LoggerFactory.getLogger(TestRealAPIs.class);
-
-    OllamaAPI ollamaAPI;
-    Config config;
-
-    private File getImageFileFromClasspath(String fileName) {
-        ClassLoader classLoader = getClass().getClassLoader();
-        return new File(Objects.requireNonNull(classLoader.getResource(fileName)).getFile());
-    }
-
-    @BeforeEach
-    void setUp() {
-        config = new Config();
-        ollamaAPI = new OllamaAPI(config.getOllamaURL());
-        ollamaAPI.setRequestTimeoutSeconds(config.getRequestTimeoutSeconds());
-    }
-
-    @Test
-    @Order(1)
-    void testWrongEndpoint() {
-        OllamaAPI ollamaAPI = new OllamaAPI("http://wrong-host:11434");
-        assertThrows(ConnectException.class, ollamaAPI::listModels);
-    }
-
-    @Test
-    @Order(1)
-    void testEndpointReachability() {
-        try {
-            assertNotNull(ollamaAPI.listModels());
-        } catch (HttpConnectTimeoutException e) {
-            fail(e.getMessage());
-        } catch (Exception e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(2)
-    void testListModels() {
-        testEndpointReachability();
-        try {
-            assertNotNull(ollamaAPI.listModels());
-            ollamaAPI.listModels().forEach(System.out::println);
-        } catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(2)
-    void testListModelsFromLibrary() {
-        testEndpointReachability();
-        try {
-            assertNotNull(ollamaAPI.listModelsFromLibrary());
-            ollamaAPI.listModelsFromLibrary().forEach(System.out::println);
-        } catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(2)
-    void testPullModel() {
-        testEndpointReachability();
-        try {
-            ollamaAPI.pullModel(config.getModel());
-            boolean found =
-                    ollamaAPI.listModels().stream()
-                            .anyMatch(model -> model.getModel().equalsIgnoreCase(config.getModel()));
-            assertTrue(found);
-        } catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testListDtails() {
-        testEndpointReachability();
-        try {
-            ModelDetail modelDetails = ollamaAPI.getModelDetails(config.getModel());
-            assertNotNull(modelDetails);
-            System.out.println(modelDetails);
-        } catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testAskModelWithDefaultOptions() {
-        testEndpointReachability();
-        try {
-            OllamaResult result =
-                    ollamaAPI.generate(
-                            config.getModel(),
-                            "What is the capital of France? And what's France's connection with Mona Lisa?",
-                            false,
-                            new OptionsBuilder().build());
-            assertNotNull(result);
-            assertNotNull(result.getResponse());
-            assertFalse(result.getResponse().isEmpty());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testAskModelWithDefaultOptionsStreamed() {
-        testEndpointReachability();
-        try {
-            StringBuffer sb = new StringBuffer("");
-            OllamaResult result = ollamaAPI.generate(config.getModel(),
-                    "What is the capital of France? And what's France's connection with Mona Lisa?",
-                    false,
-                    new OptionsBuilder().build(), (s) -> {
-                        LOG.info(s);
-                        String substring = s.substring(sb.toString().length(), s.length());
-                        LOG.info(substring);
-                        sb.append(substring);
-                    });
-
-            assertNotNull(result);
-            assertNotNull(result.getResponse());
-            assertFalse(result.getResponse().isEmpty());
-            assertEquals(sb.toString().trim(), result.getResponse().trim());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testAskModelWithOptions() {
-        testEndpointReachability();
-        try {
-            OllamaResult result =
-                    ollamaAPI.generate(
-                            config.getModel(),
-                            "What is the capital of France? And what's France's connection with Mona Lisa?",
-                            true,
-                            new OptionsBuilder().setTemperature(0.9f).build());
-            assertNotNull(result);
-            assertNotNull(result.getResponse());
-            assertFalse(result.getResponse().isEmpty());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testChat() {
-        testEndpointReachability();
-        try {
-            OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getModel());
-            OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "What is the capital of France?")
-                    .withMessage(OllamaChatMessageRole.ASSISTANT, "Should be Paris!")
-                    .withMessage(OllamaChatMessageRole.USER, "And what is the second larges city?")
-                    .build();
-
-            OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-            assertNotNull(chatResult);
-            assertFalse(chatResult.getResponse().isBlank());
-            assertEquals(4, chatResult.getChatHistory().size());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testChatWithSystemPrompt() {
-        testEndpointReachability();
-        try {
-            OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getModel());
-            OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM,
-                            "You are a silent bot that only says 'NI'. Do not say anything else under any circumstances!")
-                    .withMessage(OllamaChatMessageRole.USER,
-                            "What is the capital of France? And what's France's connection with Mona Lisa?")
-                    .build();
-
-            OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-            assertNotNull(chatResult);
-            assertFalse(chatResult.getResponse().isBlank());
-            assertTrue(chatResult.getResponse().startsWith("NI"));
-            assertEquals(3, chatResult.getChatHistory().size());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testChatWithStream() {
-        testEndpointReachability();
-        try {
-            OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getModel());
-            OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
-                            "What is the capital of France? And what's France's connection with Mona Lisa?")
-                    .build();
-
-            StringBuffer sb = new StringBuffer("");
-
-            OllamaChatResult chatResult = ollamaAPI.chat(requestModel, (s) -> {
-                LOG.info(s);
-                String substring = s.substring(sb.toString().length(), s.length());
-                LOG.info(substring);
-                sb.append(substring);
-            });
-            assertNotNull(chatResult);
-            assertEquals(sb.toString().trim(), chatResult.getResponse().trim());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testChatWithImageFromFileWithHistoryRecognition() {
-        testEndpointReachability();
-        try {
-            OllamaChatRequestBuilder builder =
-                    OllamaChatRequestBuilder.getInstance(config.getImageModel());
-            OllamaChatRequest requestModel =
-                    builder.withMessage(OllamaChatMessageRole.USER, "What's in the picture?",
-                            List.of(getImageFileFromClasspath("dog-on-a-boat.jpg"))).build();
-
-            OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-            assertNotNull(chatResult);
-            assertNotNull(chatResult.getResponse());
-
-            builder.reset();
-
-            requestModel =
-                    builder.withMessages(chatResult.getChatHistory())
-                            .withMessage(OllamaChatMessageRole.USER, "What's the dogs breed?").build();
-
-            chatResult = ollamaAPI.chat(requestModel);
-            assertNotNull(chatResult);
-            assertNotNull(chatResult.getResponse());
-
-
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testChatWithImageFromURL() {
-        testEndpointReachability();
-        try {
-            OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getImageModel());
-            OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "What's in the picture?",
-                            "https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg")
-                    .build();
-
-            OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-            assertNotNull(chatResult);
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testAskModelWithOptionsAndImageFiles() {
-        testEndpointReachability();
-        File imageFile = getImageFileFromClasspath("dog-on-a-boat.jpg");
-        try {
-            OllamaResult result =
-                    ollamaAPI.generateWithImageFiles(
-                            config.getImageModel(),
-                            "What is in this image?",
-                            List.of(imageFile),
-                            new OptionsBuilder().build());
-            assertNotNull(result);
-            assertNotNull(result.getResponse());
-            assertFalse(result.getResponse().isEmpty());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testAskModelWithOptionsAndImageFilesStreamed() {
-        testEndpointReachability();
-        File imageFile = getImageFileFromClasspath("dog-on-a-boat.jpg");
-        try {
-            StringBuffer sb = new StringBuffer("");
-
-            OllamaResult result = ollamaAPI.generateWithImageFiles(config.getImageModel(),
-                    "What is in this image?", List.of(imageFile), new OptionsBuilder().build(), (s) -> {
-                        LOG.info(s);
-                        String substring = s.substring(sb.toString().length(), s.length());
-                        LOG.info(substring);
-                        sb.append(substring);
-                    });
-            assertNotNull(result);
-            assertNotNull(result.getResponse());
-            assertFalse(result.getResponse().isEmpty());
-            assertEquals(sb.toString().trim(), result.getResponse().trim());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    void testAskModelWithOptionsAndImageURLs() {
-        testEndpointReachability();
-        try {
-            OllamaResult result =
-                    ollamaAPI.generateWithImageURLs(
-                            config.getImageModel(),
-                            "What is in this image?",
-                            List.of(
-                                    "https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg"),
-                            new OptionsBuilder().build());
-            assertNotNull(result);
-            assertNotNull(result.getResponse());
-            assertFalse(result.getResponse().isEmpty());
-        } catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
-            fail(e);
-        }
-    }
-
-    @Test
-    @Order(3)
-    public void testEmbedding() {
-        testEndpointReachability();
-        try {
-            OllamaEmbeddingsRequestModel request = OllamaEmbeddingsRequestBuilder
-                    .getInstance(config.getModel(), "What is the capital of France?").build();
-
-            List<Double> embeddings = ollamaAPI.generateEmbeddings(request);
-
-            assertNotNull(embeddings);
-            assertFalse(embeddings.isEmpty());
-        } catch (IOException | OllamaBaseException | InterruptedException e) {
-            fail(e);
-        }
-    }
-}
-
-@Data
-class Config {
-    private String ollamaURL;
-    private String model;
-    private String imageModel;
-    private int requestTimeoutSeconds;
-
-    public Config() {
-        Properties properties = new Properties();
-        try (InputStream input =
-                     getClass().getClassLoader().getResourceAsStream("test-config.properties")) {
-            if (input == null) {
-                throw new RuntimeException("Sorry, unable to find test-config.properties");
-            }
-            properties.load(input);
-            this.ollamaURL = properties.getProperty("ollama.url");
-            this.model = properties.getProperty("ollama.model");
-            this.imageModel = properties.getProperty("ollama.model.image");
-            this.requestTimeoutSeconds =
-                    Integer.parseInt(properties.getProperty("ollama.request-timeout-seconds"));
-        } catch (IOException e) {
-            throw new RuntimeException("Error loading properties", e);
-        }
-    }
-}

src/test/java/io/github/ollama4j/samples/AnnotatedTool.java

@@ -0,0 +1,21 @@
+package io.github.ollama4j.samples;
+
+import io.github.ollama4j.tools.annotations.ToolProperty;
+import io.github.ollama4j.tools.annotations.ToolSpec;
+
+import java.math.BigDecimal;
+
+public class AnnotatedTool {
+
+    @ToolSpec(desc = "Computes the most important constant all around the globe!")
+    public String computeImportantConstant(@ToolProperty(name = "noOfDigits",desc = "Number of digits that shall be returned") Integer noOfDigits ){
+        return BigDecimal.valueOf((long)(Math.random()*1000000L),noOfDigits).toString();
+    }
+
+    @ToolSpec(desc = "Says hello to a friend!")
+    public String sayHello(@ToolProperty(name = "name",desc = "Name of the friend") String name, Integer someRandomProperty, @ToolProperty(name="amountOfHearts",desc = "amount of heart emojis that should be used",  required = false) Integer amountOfHearts) {
+        String hearts = amountOfHearts!=null ? "♡".repeat(amountOfHearts) : "";
+        return "Hello " + name +" ("+someRandomProperty+") " + hearts;
+    }
+
+}

src/test/java/io/github/ollama4j/unittests/TestMockedAPIs.java

@@ -6,6 +6,7 @@ import io.github.ollama4j.exceptions.RoleNotFoundException;
 import io.github.ollama4j.models.chat.OllamaChatMessageRole;
 import io.github.ollama4j.models.embeddings.OllamaEmbedRequestModel;
 import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
+import io.github.ollama4j.models.request.CustomModelRequest;
 import io.github.ollama4j.models.response.ModelDetail;
 import io.github.ollama4j.models.response.OllamaAsyncResultStreamer;
 import io.github.ollama4j.models.response.OllamaResult;
@@ -52,12 +53,11 @@ class TestMockedAPIs {
     @Test
     void testCreateModel() {
         OllamaAPI ollamaAPI = Mockito.mock(OllamaAPI.class);
-        String model = OllamaModelType.LLAMA2;
-        String modelFilePath = "FROM llama2\nSYSTEM You are mario from Super Mario Bros.";
+        CustomModelRequest customModelRequest = CustomModelRequest.builder().model("mario").from("llama3.2:latest").system("You are Mario from Super Mario Bros.").build();
         try {
-            doNothing().when(ollamaAPI).createModelWithModelFileContents(model, modelFilePath);
-            ollamaAPI.createModelWithModelFileContents(model, modelFilePath);
-            verify(ollamaAPI, times(1)).createModelWithModelFileContents(model, modelFilePath);
+            doNothing().when(ollamaAPI).createModel(customModelRequest);
+            ollamaAPI.createModel(customModelRequest);
+            verify(ollamaAPI, times(1)).createModel(customModelRequest);
         } catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
             throw new RuntimeException(e);
         }

src/test/java/io/github/ollama4j/unittests/jackson/TestChatRequestSerialization.java

@@ -4,6 +4,7 @@ import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.junit.jupiter.api.Assertions.assertThrowsExactly;
 
 import java.io.File;
+import java.util.Collections;
 import java.util.List;
 
 import io.github.ollama4j.models.chat.OllamaChatRequest;
@@ -42,7 +43,7 @@ public class TestChatRequestSerialization extends AbstractSerializationTest<Olla
 
     @Test
     public void testRequestWithMessageAndImage() {
-        OllamaChatRequest req = builder.withMessage(OllamaChatMessageRole.USER, "Some prompt",
+        OllamaChatRequest req = builder.withMessage(OllamaChatMessageRole.USER, "Some prompt", Collections.emptyList(),
                 List.of(new File("src/test/resources/dog-on-a-boat.jpg"))).build();
         String jsonRequest = serialize(req);
         assertEqualsAfterUnmarshalling(deserialize(jsonRequest, OllamaChatRequest.class), req);

src/test/resources/test-config.properties

@@ -1,4 +1,4 @@
 ollama.url=http://localhost:11434
-ollama.model=qwen:0.5b
-ollama.model.image=llava
+ollama.model=llama3.2:1b
+ollama.model.image=llava:latest
 ollama.request-timeout-seconds=120