LangChain4j

Use LangChain4j @Tool-annotated POJOs directly with Conductor. The bridge reflects your annotated methods, builds a JSON Schema from the parameter types, and registers each method as a Conductor worker task.

Dependency

implementation 'org.conductoross:conductor-client-ai:<VERSION>'
implementation 'dev.langchain4j:langchain4j:1.0.0'

1.0.0 is the version exercised by this repository's agent examples. Replace <VERSION> with a published SDK version from Maven Central.

Usage

import dev.langchain4j.agent.tool.Tool;
import dev.langchain4j.agent.tool.P;
import org.conductoross.conductor.ai.Agent;
import org.conductoross.conductor.ai.AgentRuntime;
import org.conductoross.conductor.ai.frameworks.LangChain4jAgent;
import org.conductoross.conductor.ai.model.AgentResult;

// Your existing LangChain4j tool POJO — no changes needed
public class CalculatorTools {

    @Tool("Add two integers and return the result")
    public int add(@P("a") int a, @P("b") int b) {
        return a + b;
    }

    @Tool("Look up the current stock price for a ticker symbol")
    public double stockPrice(@P("ticker") String ticker) {
        return fetchPrice(ticker);
    }
}

// Wrap with LangChain4jAgent
Agent agent = LangChain4jAgent.from(
    "calculator_agent",                         // agent name
    "anthropic/claude-sonnet-4-6",                       // model
    "You can perform math and look up prices.", // instructions
    new CalculatorTools()                       // one or more tool POJOs
);

try (AgentRuntime runtime = new AgentRuntime()) {
    AgentResult result = runtime.run(agent, "What is 7 plus 8?");
    System.out.println(result.getOutput());
}

Detection

Check whether an object has LangChain4j @Tool methods:

boolean isTools = LangChain4jAgent.isLangChain4jTools(new CalculatorTools()); // true
boolean isTools = LangChain4jAgent.isLangChain4jTools(new Object());           // false

What gets mapped

LangChain4j annotation	Conductor mapping
@Tool("description")	Tool name = method name; description = annotation value
@Tool(name="x", value="desc")	Tool name = x; description = desc
@P("paramName")	JSON Schema property name
Method return type	Output schema

Using with LangChainBridge

For ChatModel-based agents (not @Tool POJOs):

Fragment — SearchTools is an application class. The local ChatModel supplies provider and model metadata; Conductor performs the LLM call with the credential configured on the server.

import dev.langchain4j.model.chat.ChatModel;
import dev.langchain4j.model.openai.OpenAiChatModel;
import org.conductoross.conductor.ai.frameworks.LangChainBridge;
import org.conductoross.conductor.ai.internal.ToolRegistry;

ChatModel model = OpenAiChatModel.builder()
    .apiKey("server-configured-credential")
    .modelName("gpt-4o-mini")
    .build();

Agent agent = LangChainBridge.agentBuilder("lc_agent", model, "You are helpful.")
    .tools(ToolRegistry.fromInstance(new SearchTools()))
    .build();