Installation

Requirements

Java 21 or later
Gradle or Maven build tool
A LangChain4j-supported LLM provider (OpenAI, Anthropic, Ollama, etc.)

Add the Dependency

Recommended: Use the agentensemble-bom

agentensemble-bom is a Bill of Materials that aligns every AgentEnsemble module to the same version. Import it once and add only the modules you need — no individual version numbers required.

Gradle (Kotlin DSL):

repositories {
    mavenCentral()
}

dependencies {
    // Import the BOM -- aligns all AgentEnsemble module versions
    implementation(platform("net.agentensemble:agentensemble-bom:2.1.0"))

    // Core framework -- always required
    implementation("net.agentensemble:agentensemble-core")

    // Optional: task-scoped cross-execution memory (MemoryStore SPI)
    implementation("net.agentensemble:agentensemble-memory")

    // Optional: human-in-the-loop review gates (ReviewHandler SPI, ConsoleReviewHandler)
    implementation("net.agentensemble:agentensemble-review")

    // Optional: built-in tools -- add only the ones you need
    implementation("net.agentensemble:agentensemble-tools-web-search")
    implementation("net.agentensemble:agentensemble-tools-web-scraper")
    implementation("net.agentensemble:agentensemble-tools-calculator")
    implementation("net.agentensemble:agentensemble-tools-datetime")
    // Other tools: agentensemble-tools-json-parser, agentensemble-tools-file-read,
    // agentensemble-tools-file-write, agentensemble-tools-process, agentensemble-tools-http

    // Optional: live execution dashboard -- embedded WebSocket server that streams
    // real-time task/tool events to a browser and supports browser-based review gates.
    // agentensemble-review is included transitively; declare it above only if you
    // reference review types directly in your own code.
    implementation("net.agentensemble:agentensemble-web")

    // Optional: Micrometer metrics integration
    implementation("net.agentensemble:agentensemble-metrics-micrometer")

    // Add the LangChain4j integration for your LLM provider:
    implementation("dev.langchain4j:langchain4j-open-ai:1.11.0")
}

Gradle (Groovy DSL):

repositories {
    mavenCentral()
}

dependencies {
    implementation platform('net.agentensemble:agentensemble-bom:2.1.0')
    implementation 'net.agentensemble:agentensemble-core'
    implementation 'net.agentensemble:agentensemble-memory'
    implementation 'net.agentensemble:agentensemble-review'
    implementation 'dev.langchain4j:langchain4j-open-ai:1.11.0'
}

Maven:

<dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>net.agentensemble</groupId>
            <artifactId>agentensemble-bom</artifactId>
            <version>2.1.0</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
    </dependencies>
</dependencyManagement>
<dependencies>
    <dependency>
        <groupId>net.agentensemble</groupId>
        <artifactId>agentensemble-core</artifactId>
        <!-- version from BOM -->
    </dependency>
    <dependency>
        <groupId>net.agentensemble</groupId>
        <artifactId>agentensemble-memory</artifactId>
        <!-- version from BOM -->
    </dependency>
    <dependency>
        <groupId>net.agentensemble</groupId>
        <artifactId>agentensemble-review</artifactId>
        <!-- version from BOM -->
    </dependency>
    <dependency>
        <groupId>dev.langchain4j</groupId>
        <artifactId>langchain4j-open-ai</artifactId>
        <version>1.11.0</version>
    </dependency>
</dependencies>

Minimal: Core Only

If you need only the framework core (no memory, no review, no built-in tools):

dependencies {
    implementation("net.agentensemble:agentensemble-core:2.0.0")
    implementation("dev.langchain4j:langchain4j-open-ai:1.11.0")
}

Tools-Only BOM

If you want to align just the built-in tool versions without importing the full BOM:

dependencies {
    implementation(platform("net.agentensemble:agentensemble-tools-bom:2.0.0"))
    implementation("net.agentensemble:agentensemble-core:2.0.0")

    // No version needed for tools -- resolved from tools BOM
    implementation("net.agentensemble:agentensemble-tools-calculator")
    implementation("net.agentensemble:agentensemble-tools-web-search")
}

Available Modules

Module	Description
`agentensemble-core`	Framework core — required
`agentensemble-tools-calculator`	Arithmetic expression evaluator
`agentensemble-tools-datetime`	Date/time operations
`agentensemble-tools-json-parser`	JSON path extraction
`agentensemble-tools-file-read`	Sandboxed file reading
`agentensemble-tools-file-write`	Sandboxed file writing
`agentensemble-tools-web-search`	Web search (Tavily/SerpAPI)
`agentensemble-tools-web-scraper`	Web page text extraction
`agentensemble-tools-process`	Subprocess execution (cross-language)
`agentensemble-tools-http`	HTTP endpoint wrapping
`agentensemble-tools-bom`	Version alignment BOM
`agentensemble-memory`	Memory subsystem: task-scoped cross-execution memory with MemoryStore SPI; also includes legacy short-term, long-term, and entity memory
`agentensemble-review`	Human-in-the-loop review gates: ReviewHandler SPI, ConsoleReviewHandler, and HumanInputTool
`agentensemble-web`	Live execution dashboard: embedded WebSocket server that streams real-time task/tool/delegation events to a browser and supports browser-based review gates
`agentensemble-metrics-micrometer`	Micrometer metrics integration
`agentensemble-bom`	Top-level BOM — aligns all module versions in one import

Supported LLM Providers

AgentEnsemble uses the LangChain4j ChatModel interface and works with any provider that implements it:

Provider	LangChain4j Artifact
OpenAI (GPT-4o, GPT-4o-mini, etc.)	`langchain4j-open-ai`
Anthropic (Claude 3.5, Claude 3 Haiku, etc.)	`langchain4j-anthropic`
Ollama (local models)	`langchain4j-ollama`
Azure OpenAI	`langchain4j-azure-open-ai`
Amazon Bedrock	`langchain4j-bedrock`
Google Vertex AI	`langchain4j-vertex-ai-gemini`
Mistral AI	`langchain4j-mistral-ai`

For a full list, see the LangChain4j documentation.

Logging

AgentEnsemble uses SLF4J for logging. Add your preferred implementation:

// Logback (recommended)
implementation("ch.qos.logback:logback-classic:1.5.32")

See the Logging guide for configuration details.

Execution Graph Visualizer: agentensemble-viz

agentensemble-viz is a standalone developer tool for visualizing task dependency graphs and execution timelines. It reads JSON files exported by agentensemble-devtools and renders them in a local web UI.

Homebrew (macOS and Linux):

brew install agentensemble/tap/agentensemble-viz
agentensemble-viz ./traces/

This installs a self-contained native binary (no Node.js required). The formula is updated automatically on every AgentEnsemble release.

npx (no installation required):

npx @agentensemble/viz ./traces/

Global npm install:

npm install -g @agentensemble/viz
agentensemble-viz ./traces/

See the Visualization Guide for the complete workflow including how to export DAGs and execution traces from your Java application.

Next Steps

Quickstart — Build your first ensemble
Core Concepts — Understand the key abstractions
Built-in Tools — Ready-to-use tool reference
Remote Tools — Cross-language tools with Python, Node.js, etc.