agentscope-java
agentscope-ai/agentscope-javaExpert Java developer skill for AgentScope Java framework - a reactive, message-driven multi-agent system built on Project Reactor. Use when working with reactive programming, LLM integration, agent orchestration, multi-agent systems, or when the user mentions AgentScope, ReActAgent, Mono/Flux, Project Reactor, or Java agent development. Specializes in non-blocking code, tool integration, hooks, pipelines, and production-ready agent applications.
SKILL.md
name: agentscope-java description: Expert Java developer skill for AgentScope Java framework - a reactive, message-driven multi-agent system built on Project Reactor. Use when working with reactive programming, LLM integration, agent orchestration, multi-agent systems, or when the user mentions AgentScope, ReActAgent, Mono/Flux, Project Reactor, or Java agent development. Specializes in non-blocking code, tool integration, hooks, pipelines, and production-ready agent applications. license: Apache-2.0 compatibility: Designed for Claude Code and Cursor. Requires Java 17+, Maven/Gradle, and familiarity with reactive programming concepts. metadata: framework: AgentScope Java language: Java 17+ paradigm: Reactive Programming core-library: Project Reactor version: "1.0"
When the user asks you to write AgentScope Java code, follow these instructions carefully.
CRITICAL RULES - NEVER VIOLATE THESE
🚫 ABSOLUTELY FORBIDDEN:
- NEVER use
.block()in example code - This is the #1 mistake. Only use.block()inmain()methods or test code when explicitly creating a runnable example. - NEVER use
Thread.sleep()- UseMono.delay()instead. - NEVER use
ThreadLocal- Use Reactor Context withMono.deferContextual(). - NEVER hardcode API keys - Always use
System.getenv(). - NEVER ignore errors silently - Always log errors and provide fallback values.
- NEVER use wrong import paths - All models are in
io.agentscope.core.model.*, NOTio.agentscope.model.*.
✅ ALWAYS DO:
- Use
MonoandFluxfor all asynchronous operations. - Chain operations with
.map(),.flatMap(),.then(). - Use Builder pattern for creating agents, models, and messages.
- Include error handling with
.onErrorResume()or.onErrorReturn(). - Add logging with SLF4J for important operations.
- Use correct imports:
import io.agentscope.core.model.DashScopeChatModel; - Use correct APIs (many methods don't exist or have changed):
toolkit.registerTool()NOTregisterObject()toolkit.getToolNames()NOTgetTools()event.getToolUse().getName()NOTgetToolName()result.getOutput()NOTgetContent()(ToolResultBlock)event.getToolResult()NOTgetResult()(PostActingEvent)toolUse.getInput()NOTgetArguments()(ToolUseBlock)- Model builder: NO
temperature()method, usedefaultOptions(GenerateOptions.builder()...) - Hook events: NO
getMessages(),getResponse(),getIterationCount(),getThinkingBlock()methods - ToolResultBlock: NO
getToolUseName()method, useevent.getToolUse().getName()instead - ToolResultBlock.getOutput() returns
List<ContentBlock>NOTString, need to convert - @ToolParam format: MUST use
@ToolParam(name = "x", description = "y")NOT@ToolParam(name="x")
WHEN GENERATING CODE
FIRST: Identify the context
- Is this a
main()method or test code? →.block()is allowed (but add a warning comment) - Is this agent logic, service method, or library code? →
.block()is FORBIDDEN
For every code example you provide:
- Check: Does it use
.block()? → If yes in non-main/non-test code, REWRITE IT. - Check: Are all operations non-blocking? → If no, FIX IT.
- Check: Does it have error handling? → If no, ADD IT.
- Check: Are API keys from environment? → If no, CHANGE IT.
- Check: Are imports correct? → If using
io.agentscope.model.*, FIX TOio.agentscope.core.model.*.
Default code structure for agent logic:
// ✅ CORRECT - Non-blocking, reactive (use this pattern by default)
return model.generate(messages, null, null)
.map(response -> processResponse(response))
.onErrorResume(e -> {
log.error("Operation failed", e);
return Mono.just(fallbackValue);
});
// ❌ WRONG - Never generate this in agent logic
String result = model.generate(messages, null, null).block(); // DON'T DO THIS
Only for main() methods (add warning comment):
public static void main(String[] args) {
// ⚠️ .block() is ONLY allowed here because this is a main() method
Msg response = agent.call(userMsg).block();
System.out.println(response.getTextContent());
}
PROJECT SETUP
When creating a new AgentScope project, use the correct Maven dependencies:
Maven Configuration (pom.xml)
For production use (recommended):
<properties>
<java.version>17</java.version>
</properties>
<dependencies>
<!-- Use the latest stable release from Maven Central -->
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope</artifactId>
<version>1.0.6</version>
</dependency>
</dependencies>
For local development (if working with source code):
<properties>
<agentscope.version>1.0.6</agentscope.version>
<java.version>17</java.version>
</properties>
<dependencies>
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope-core</artifactId>
<version>${agentscope.version}</version>
</dependency>
</dependencies>
⚠️ IMPORTANT: Version Selection
- Use
agentscope:1.0.6for production (stable, from Maven Central) - Use
agentscope-core:1.0.6only if you're developing AgentScope itself - NEVER use version
0.1.0-SNAPSHOT- this version doesn't exist
⚠️ CRITICAL: Common Dependency Mistakes
❌ WRONG - These artifacts don't exist:
<!-- DON'T use these - they don't exist -->
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope-model-dashscope</artifactId> <!-- ❌ WRONG -->
</dependency>
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope-model-openai</artifactId> <!-- ❌ WRONG -->
</dependency>
❌ WRONG - These versions don't exist:
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope-core</artifactId>
<version>0.1.0-SNAPSHOT</version> <!-- ❌ WRONG - doesn't exist -->
</dependency>
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope</artifactId>
<version>0.1.0</version> <!-- ❌ WRONG - doesn't exist -->
</dependency>
✅ CORRECT - Use the stable release:
<!-- For production: use the stable release from Maven Central -->
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope</artifactId>
<version>1.0.6</version> <!-- ✅ CORRECT -->
</dependency>
Available Model Classes (all in agentscope-core)
// DashScope (Alibaba Cloud)
import io.agentscope.core.model.DashScopeChatModel;
// OpenAI
import io.agentscope.core.model.OpenAIChatModel;
// Gemini (Google)
import io.agentscope.core.model.GeminiChatModel;
// Anthropic (Claude)
import io.agentscope.core.model.AnthropicChatModel;
// Ollama (Local models)
import io.agentscope.core.model.OllamaChatModel;
Optional Extensions
<!-- Long-term memory with Mem0 -->
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope-extensions-mem0</artifactId>
<version>${agentscope.version}</version>
</dependency>
<!-- RAG with Dify -->
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope-extensions-rag-dify</artifactId>
<version>${agentscope.version}</version>
</dependency>
PROJECT OVERVIEW & ARCHITECTURE
AgentScope Java is a reactive, message-driven multi-agent framework built on Project Reactor and Java 17+.
Core Abstractions
Agent: The fundamental unit of execution. Most agents extendAgentBase.Msg: The message object exchanged between agents.Memory: Stores conversation history (InMemoryMemory,LongTermMemory).Toolkit&AgentTool: Defines capabilities the agent can use.Model: Interfaces with LLMs (OpenAI, DashScope, Gemini, Anthropic, etc.).Hook: Intercepts and modifies agent execution at various lifecycle points.Pipeline: Orchestrates multiple agents in sequential or parallel patterns.
Reactive Nature
Almost all operations (agent calls, model inference, tool execution) return Mono<T> or Flux<T>.
Key Design Principles
- Non-blocking: All I/O operations are asynchronous
- Message-driven: Agents communicate via immutable
Msgobjects - Composable: Agents and pipelines can be nested and combined
- Extensible: Hooks and custom tools allow deep customization
CODING STANDARDS & BEST PRACTICES
2.1 Java Version & Style
Target Java 17 (LTS) for maximum compatibility:
- Use Java 17 features (Records, Switch expressions, Pattern Matching for instanceof,
var, Sealed classes) - AVOID Java 21+ preview features (pattern matching in switch, record patterns)
- Follow standard Java conventions (PascalCase for classes, camelCase for methods/variables)
- Use Lombok where appropriate (
@Data,@Builderfor DTOs/Messages) - Prefer immutability for data classes
- Use meaningful names that reflect domain concepts
⚠️ CRITICAL: Avoid Preview Features
// ❌ WRONG - Requires Java 21 with --enable-preview
return switch (event) {
case PreReasoningEvent e -> Mono.just(e); // Pattern matching in switch
default -> Mono.just(event);
};
// ✅ CORRECT - Java 17 compatible
if (event instanceof PreReasoningEvent e) { // Pattern matching for instanceof (Java 17)
return Mono.just(event);
} else {
return Mono.just(event);
}
2.2 Reactive Programming (Critical)
⚠️ NEVER BLOCK IN AGENT LOGIC
Blocking operations will break the reactive chain and cause performance issues.
Rules:
- ❌ Never use
.block()in agent logic (only inmainmethods or tests) - ✅ Use
Monofor single results (e.g.,agent.call()) - ✅ Use
Fluxfor streaming responses (e.g.,model.stream()) - ✅ Chain operations using
.map(),.flatMap(),.then() - ✅ Use
Mono.defer()for lazy evaluation - ✅ Use
Mono.deferContextual()for reactive context access
Example:
// ❌ WRONG - Blocking
public Mono<String> processData(String input) {
String result = externalService.call(input).block(); // DON'T DO THIS
return Mono.just(result);
}
// ✅ CORRECT - Non-blocking
public Mono<String> processData(String input) {
return externalService.call(input)
.map(this::transform)
.flatMap(this::validate);
}
2.3 Message Handling (Msg)
Create messages using the Builder pattern:
Msg userMsg = Msg.builder()
.role(MsgRole.USER)
.content(TextBlock.builder().text("Hello").build())
.name("user")
.build();
Content Blocks:
TextBlock: For text contentThinkingBlock: For Chain of Thought (CoT) reasoningToolUseBlock: For tool callsToolResultBlock: For tool outputs
Helper Methods:
// Prefer safe helper methods
String text = msg.getTextContent(); // Safe, returns null if not found
// Avoid direct access
String text = msg.getContent().get(0).getText(); // May throw NPE
2.4 Implementing Agents
Extend AgentBase and implement doCall(List<Msg> msgs):
public class MyAgent extends AgentBase {
private final Model model;
private final Memory memory;
public MyAgent(String name, Model model) {
super(name, "A custom agent", true, List.of());
this.model = model;
this.memory = new InMemoryMemory();
}
@Override
protected Mono<Msg> doCall(List<Msg> msgs) {
// 1. Process inputs
if (msgs != null) {
msgs.forEach(memory::addMessage);
}
// 2. Call model or logic
return model.generate(memory.getMessages(), null, null)
.map(response -> Msg.builder()
.name(getName())
.role(MsgRole.ASSISTANT)
.content(TextBlock.builder().text(response.getText()).build())
.build());
}
}
2.5 Tool Definition
Use @Tool annotation for function-based tools. Tools can return:
String(synchronous)Mono<String>(asynchronous)Mono<ToolResultBlock>(for complex results)
⚠️ CRITICAL: @ToolParam Format
- ✅ CORRECT:
@ToolParam(name = "city", description = "City name") - ❌ WRONG:
@ToolParam(name="city", description="...")(no spaces around=) - ❌ WRONG:
@ToolParam("city")(missing name= and description=)
Synchronous Tool Example:
public class WeatherTools {
@Tool(description = "Get current weather for a city. Returns temperature and conditions.")
public String getWeather(
@ToolParam(name = "city", description = "City name, e.g., 'San Francisco'")
String city) {
// Implementation
return "Sunny, 25°C";
}
}
Asynchronous Tool Example:
public class AsyncTools {
private final WebClient webClient;
@Tool(description = "Fetch data from trusted API endpoint")
public Mono<String> fetchData(
@ToolParam(name = "url", description = "API endpoint URL (must start with https://api.myservice.com)")
String url) {
// SECURITY: Validate URL to prevent SSRF
if (!url.startsWith("https://api.myservice.com")) {
return Mono.just("Error: URL not allowed. Must start with https://api.myservice.com");
}
return webClient.get()
.uri(url)
.retrieve()
.bodyToMono(String.class)
.timeout(Duration.ofSeconds(10))
.onErrorResume(e -> Mono.just("Error: " + e.getMessage()));
}
}
Register with Toolkit:
Toolkit toolkit = new Toolkit();
toolkit.registerTool(new WeatherTools());
toolkit.registerTool(new AsyncTools());
HOOK SYSTEM
Hooks allow you to intercept and modify agent execution at various lifecycle points.
Hook Interface
public interface Hook {
<T extends HookEvent> Mono<T> onEvent(T event);
default int priority() { return 100; } // Lower = higher priority
}
Common Hook Events
PreReasoningEvent: Before LLM reasoning (modifiable)PostReasoningEvent: After LLM reasoning (modifiable)ReasoningChunkEvent: Streaming reasoning chunks (notification)PreActingEvent: Before tool execution (modifiable)PostActingEvent: After tool execution (modifiable)ActingChunkEvent: Streaming tool execution (notification)
Hook Example
Java 17+ compatible (recommended):
Hook loggingHook = new Hook() {
@Override
public <T extends HookEvent> Mono<T> onEvent(T event) {
// Use if-instanceof instead of switch patterns (Java 17 compatible)
if (event instanceof PreReasoningEvent e) {
log.info("Reasoning with model: {}", e.getModelName());
return Mono.just(event);
} else if (event instanceof PreActingEvent e) {
log.info("Calling tool: {}", e.getToolUse().getName());
return Mono.just(event);
} else if (event instanceof PostActingEvent e) {
log.info("Tool {} completed", e.getToolUse().getName());
return Mono.just(event);
} else {
return Mono.just(event);
}
}
@Override
public int priority() {
return 500; // Low priority (logging)
}
};
ReActAgent agent = ReActAgent.builder()
.name("Assistant")
.model(model)
.hook(loggingHook)
.build();
Alternative: Traditional if-else (Java 17):
Hook loggingHook = new Hook() {
@Override
public <T extends HookEvent> Mono<T> onEvent(T event) {
if (event instanceof PreReasoningEvent) {
PreReasoningEvent e = (PreReasoningEvent) event;
log.info("Reasoning with model: {}", e.getModelName());
} else if (event instanceof PreActingEvent) {
PreActingEvent e = (PreActingEvent) event;
log.info("Calling tool: {}", e.getToolUse().getName());
} else if (event instanceof PostActingEvent) {
PostActingEvent e = (PostActingEvent) event;
log.info("Tool {} completed", e.getToolUse().getName());
}
return Mono.just(event);
}
@Override
public int priority() {
return 500;
}
};
Priority Guidelines:
- 0-50: Critical system hooks (auth, security)
- 51-100: High priority hooks (validation, preprocessing)
- 101-500: Normal priority hooks (business logic)
- 501-1000: Low priority hooks (logging, metrics)
PIPELINE PATTERNS
Pipelines orchestrate multiple agents in structured workflows.
Sequential Pipeline
Executes agents in sequence (output of one becomes input of next):
SequentialPipeline pipeline = SequentialPipeline.builder()
.addAgent(researchAgent)
.addAgent(summaryAgent)
.addAgent(reviewAgent)
.build();
Msg result = pipeline.execute(userInput).block();
Fanout Pipeline
Executes agents in parallel and aggregates results:
FanoutPipeline pipeline = FanoutPipeline.builder()
.addAgent(agent1)
.addAgent(agent2)
.addAgent(agent3)
.build();
Msg result = pipeline.execute(userInput).block();
When to Use:
- Sequential: When each agent depends on the previous agent's output
- Fanout: When agents can work independently and results need aggregation
MEMORY MANAGEMENT
In-Memory (Short-term)
Memory memory = new InMemoryMemory();
Long-Term Memory
// Configure long-term memory
LongTermMemory longTermMemory = Mem0LongTermMemory.builder()
.apiKey(System.getenv("MEM0_API_KEY"))
.userId("user_123")
.build();
// Use with agent
ReActAgent agent = ReActAgent.builder()
.name("Assistant")
.model(model)
.longTermMemory(longTermMemory)
.longTermMemoryMode(LongTermMemoryMode.BOTH) // STATIC_CONTROL, AGENTIC, or BOTH
.build();
Memory Modes:
STATIC_CONTROL: Framework automatically manages memory (via hooks)AGENTIC: Agent decides when to use memory (via tools)BOTH: Combines both approaches
MCP (MODEL CONTEXT PROTOCOL) INTEGRATION
AgentScope supports MCP for integrating external tools and resources.
// Create MCP client
// SECURITY: In production, use a specific version or a local binary to prevent supply chain attacks
McpClientWrapper mcpClient = McpClientBuilder.stdio()
.command("npx")
.args("-y", "@modelcontextprotocol/[email protected]", "/path/to/files") // Always pin versions
.build();
// Register with toolkit
Toolkit toolkit = new Toolkit();
toolkit.registration()
.mcpClient(mcpClient)
.enableTools(List.of("read_file", "write_file"))
.apply();
// Use with agent
ReActAgent agent = ReActAgent.builder()
.name("Assistant")
.model(model)
.toolkit(toolkit)
.build();
TESTING
Unit Testing with StepVerifier
@Test
void testAgentCall() {
Msg input = Msg.builder()
.role(MsgRole.USER)
.content(TextBlock.builder().text("Hello").build())
.build();
StepVerifier.create(agent.call(input))
.assertNext(response -> {
assertEquals(MsgRole.ASSISTANT, response.getRole());
assertNotNull(response.getTextContent());
})
.verifyComplete();
}
Mocking External Dependencies
@Test
void testWithMockModel() {
Model mockModel = mock(Model.class);
when(mockModel.generate(any(), any(), any()))
.thenReturn(Mono.just(ChatResponse.builder()
.text("Mocked response")
.build()));
ReActAgent agent = ReActAgent.builder()
.name("TestAgent")
.model(mockModel)
.build();
// Test agent behavior
}
Testing Best Practices:
- Always test reactive chains with
StepVerifier - Mock external dependencies (models, APIs)
- Test error cases and edge conditions
- Verify that hooks are called correctly
- Test timeout and cancellation scenarios
CODE STYLE GUIDE
Logging
private static final Logger log = LoggerFactory.getLogger(MyClass.class);
// Use parameterized logging
log.info("Processing message from user: {}", userId);
log.error("Failed to call model: {}", modelName, exception);
Error Handling
// Prefer specific error messages
return Mono.error(new IllegalArgumentException(
"Invalid model name: " + modelName + ". Expected one of: " + VALID_MODELS));
// Use onErrorResume for graceful degradation
return model.generate(msgs, null, null)
.onErrorResume(e -> {
log.error("Model call failed, using fallback", e);
return Mono.just(fallbackResponse);
});
Null Safety
// Use Optional for nullable returns
public Optional<AgentTool> findTool(String name) {
return Optional.ofNullable(tools.get(name));
}
// Use Objects.requireNonNull for validation
public MyAgent(Model model) {
this.model = Objects.requireNonNull(model, "Model cannot be null");
}
Comments
// Use Javadoc for public APIs
/**
* Creates a new agent with the specified configuration.
*
* @param name The agent name (must be unique)
* @param model The LLM model to use
* @return Configured agent instance
* @throws IllegalArgumentException if name is null or empty
*/
public static ReActAgent create(String name, Model model) {
// Implementation
}
// Use inline comments sparingly, only for complex logic
// Calculate exponential backoff: 2^attempt * baseDelay
Duration delay = Duration.ofMillis((long) Math.pow(2, attempt) * baseDelayMs);
KEY LIBRARIES
- Reactor Core:
Mono,Fluxfor reactive programming - Jackson: JSON serialization/deserialization
- SLF4J: Logging (
private static final Logger log = LoggerFactory.getLogger(MyClass.class);) - OkHttp: HTTP client for model APIs
- MCP SDK: Model Context Protocol integration
- JUnit 5: Testing framework
- Mockito: Mocking framework
- Lombok: Boilerplate reduction
PROHIBITED PRACTICES
❌ NEVER Do These
-
Block in reactive chains
// ❌ WRONG return someMonoOperation().block(); -
Use Thread.sleep() or blocking I/O
// ❌ WRONG Thread.sleep(1000); // ✅ CORRECT return Mono.delay(Duration.ofSeconds(1)); -
Mutate shared state without synchronization
// ❌ WRONG private List<Msg> messages = new ArrayList<>(); public void addMessage(Msg msg) { messages.add(msg); // Not thread-safe } -
Ignore errors silently
// ❌ WRONG .onErrorResume(e -> Mono.empty()) // ✅ CORRECT .onErrorResume(e -> { log.error("Operation failed", e); return Mono.just(fallbackValue); }) -
Use ThreadLocal in reactive code
// ❌ WRONG ThreadLocal<String> context = new ThreadLocal<>(); // ✅ CORRECT return Mono.deferContextual(ctx -> { String value = ctx.get("key"); // Use value }); -
Create agents without proper resource management
// ❌ WRONG - No cleanup public void processRequests() { for (int i = 0; i < 1000; i++) { ReActAgent agent = createAgent(); agent.call(msg).block(); } } -
Hardcode API keys or secrets
// ❌ WRONG String apiKey = "sk-1234567890"; // ✅ CORRECT String apiKey = System.getenv("OPENAI_API_KEY"); -
Use Java preview features (requires --enable-preview)
// ❌ WRONG - Requires Java 21 with --enable-preview return switch (event) { case PreReasoningEvent e -> handleReasoning(e); case PostActingEvent e -> handleActing(e); default -> Mono.just(event); }; // ✅ CORRECT - Java 17 compatible if (event instanceof PreReasoningEvent e) { return handleReasoning(e); } else if (event instanceof PostActingEvent e) { return handleActing(e); } else { return Mono.just(event); }
COMMON PITFALLS & SOLUTIONS
❌ Blocking Operations
// WRONG
Msg response = agent.call(msg).block(); // Don't block in agent logic
// CORRECT
return agent.call(msg)
.flatMap(response -> processResponse(response));
❌ Null Handling
// WRONG
String text = msg.getContent().get(0).getText(); // May throw NPE
// CORRECT
String text = msg.getTextContent(); // Safe helper method
// OR
String text = msg.getContentBlocks(TextBlock.class).stream()
.findFirst()
.map(TextBlock::getText)
.orElse("");
❌ Thread Context
// WRONG
ThreadLocal<String> context = new ThreadLocal<>(); // May not work in reactive streams
// CORRECT
return Mono.deferContextual(ctx -> {
String value = ctx.get("key");
// Use value
});
❌ Error Swallowing
// WRONG
.onErrorResume(e -> Mono.empty()) // Silent failure
// CORRECT
.onErrorResume(e -> {
log.error("Failed to process: {}", input, e);
return Mono.just(createErrorResponse(e));
})
COMPLETE EXAMPLE
package com.example.agentscope;
import io.agentscope.core.ReActAgent;
import io.agentscope.core.hook.Hook;
import io.agentscope.core.hook.HookEvent;
import io.agentscope.core.hook.ReasoningChunkEvent;
import io.agentscope.core.memory.InMemoryMemory;
import io.agentscope.core.message.Msg;
import io.agentscope.core.message.MsgRole;
import io.agentscope.core.message.TextBlock;
import io.agentscope.core.model.Model;
import io.agentscope.core.tool.Tool;
import io.agentscope.core.tool.ToolParam;
import io.agentscope.core.tool.Toolkit;
import io.agentscope.core.model.DashScopeChatModel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import reactor.core.publisher.Mono;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
/**
* Complete example demonstrating AgentScope best practices.
*/
public class CompleteExample {
private static final Logger log = LoggerFactory.getLogger(CompleteExample.class);
public static void main(String[] args) {
// 1. Create model (no .temperature() method, use defaultOptions)
Model model = DashScopeChatModel.builder()
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.modelName("qwen-plus")
.stream(true)
.build();
// 2. Create toolkit with tools
Toolkit toolkit = new Toolkit();
toolkit.registerTool(new WeatherTools());
toolkit.registerTool(new TimeTools());
// 3. Create hook for streaming output
Hook streamingHook = new Hook() {
@Override
public <T extends HookEvent> Mono<T> onEvent(T event) {
if (event instanceof ReasoningChunkEvent e) {
String text = e.getIncrementalChunk().getTextContent();
if (text != null) {
System.out.print(text);
}
}
return Mono.just(event);
}
@Override
public int priority() {
return 500; // Low priority
}
};
// 4. Build agent
ReActAgent agent = ReActAgent.builder()
.name("Assistant")
.sysPrompt("You are a helpful assistant. Use tools when appropriate.")
.model(model)
.toolkit(toolkit)
.memory(new InMemoryMemory())
.hook(streamingHook)
.maxIters(10)
.build();
// 5. Use agent
Msg userMsg = Msg.builder()
.role(MsgRole.USER)
.content(TextBlock.builder()
.text("What's the weather in San Francisco and what time is it?")
.build())
.build();
try {
System.out.println("User: " + userMsg.getTextContent());
System.out.print("Assistant: ");
// ⚠️ IMPORTANT: .block() is ONLY allowed in main() methods for demo purposes
// NEVER use .block() in agent logic, service methods, or library code
Msg response = agent.call(userMsg).block();
System.out.println("\n\n--- Response Details ---");
System.out.println("Role: " + response.getRole());
System.out.println("Content: " + response.getTextContent());
} catch (Exception e) {
log.error("Error during agent execution", e);
System.err.println("Error: " + e.getMessage());
}
}
/**
* Example tool class for weather information.
*/
public static class WeatherTools {
@Tool(description = "Get current weather for a city. Returns temperature and conditions.")
public String getWeather(
@ToolParam(name = "city", description = "City name, e.g., 'San Francisco'")
String city) {
log.info("Getting weather for city: {}", city);
// Simulate API call
return String.format("Weather in %s: Sunny, 22°C, Light breeze", city);
}
}
/**
* Example tool class for time information.
*/
public static class TimeTools {
private static final DateTimeFormatter FORMATTER =
DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
@Tool(description = "Get current date and time")
public String getCurrentTime() {
LocalDateTime now = LocalDateTime.now();
String formatted = now.format(FORMATTER);
log.info("Returning current time: {}", formatted);
return "Current time: " + formatted;
}
}
}
QUICK REFERENCE
Agent Creation
ReActAgent agent = ReActAgent.builder()
.name("AgentName")
.sysPrompt("System prompt")
.model(model)
.toolkit(toolkit)
.memory(memory)
.hooks(hooks)
.maxIters(10)
.build();
Message Creation
Msg msg = Msg.builder()
.role(MsgRole.USER)
.content(TextBlock.builder().text("Hello").build())
.build();
Tool Registration
Toolkit toolkit = new Toolkit();
toolkit.registerTool(new MyTools());
Hook Creation
Hook hook = new Hook() {
public <T extends HookEvent> Mono<T> onEvent(T event) {
// Handle event
return Mono.just(event);
}
};
Pipeline Creation
SequentialPipeline pipeline = SequentialPipeline.builder()
.addAgent(agent1)
.addAgent(agent2)
.build();
README
Build Production-Ready AI Agents in Java
📖 Documentation | 中文 | Discord
AgentScope Java is an agent-oriented programming framework for building LLM-powered applications. It provides everything you need to create intelligent agents: ReAct reasoning, tool calling, memory management, multi-agent collaboration, and more.
Highlights
🎯 Smart Agents, Full Control
AgentScope adopts the ReAct (Reasoning-Acting) paradigm, enabling agents to autonomously plan and execute complex tasks. Unlike rigid workflow-based approaches, ReAct agents dynamically decide which tools to use and when, adapting to changing requirements in real-time.
However, autonomy without control is a liability in production. AgentScope provides comprehensive runtime intervention mechanisms:
- Safe Interruption - Pause agent execution at any point while preserving full context and tool state, enabling seamless resumption without data loss
- Graceful Cancellation - Terminate long-running or unresponsive tool calls without corrupting agent state, allowing immediate recovery and redirection
- Human-in-the-Loop - Inject corrections, additional context, or guidance at any reasoning step through the Hook system, maintaining human oversight over critical decisions
🛠️ Built-in Tools
AgentScope includes production-ready tools that address common challenges in agent development:
-
PlanNotebook - A structured task management system that decomposes complex objectives into ordered, trackable steps. Agents can create, modify, pause, and resume multiple concurrent plans, ensuring systematic execution of multi-step workflows.
-
Structured Output - A self-correcting output parser that guarantees type-safe responses. When LLM output deviates from the expected format, the system automatically detects errors and guides the model to produce valid output, mapping results directly to Java POJOs without manual parsing.
-
Long-term Memory - Persistent memory storage with semantic search capabilities across sessions. Supports automatic management, agent-controlled recording, or hybrid modes. Enables multi-tenant isolation for enterprise deployments where agents serve multiple users independently.
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RAG (Retrieval-Augmented Generation) - Seamless integration with enterprise knowledge bases. Supports both self-hosted embedding-based retrieval and managed services like Alibaba Cloud Bailian, grounding agent responses in authoritative data sources.
🔌 Seamless Integration
AgentScope is designed to integrate with existing enterprise infrastructure without requiring extensive modifications:
-
MCP Protocol - Integrate with any MCP-compatible server to instantly extend agent capabilities. Connect to the growing ecosystem of MCP tools and services—from file systems and databases to web browsers and code interpreters—without writing custom integration code.
-
A2A Protocol - Enable distributed multi-agent collaboration through standard service discovery. Register agent capabilities to Nacos or similar registries, allowing agents to discover and invoke each other as naturally as calling microservices.
🚀 Production Grade
Built for enterprise deployment requirements:
-
High Performance - Reactive architecture based on Project Reactor ensures non-blocking execution. GraalVM native image compilation achieves 200ms cold start times, making AgentScope suitable for serverless and auto-scaling environments.
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Security Sandbox - AgentScope Runtime provides isolated execution environments for untrusted tool code. Includes pre-built sandboxes for GUI automation, file system operations, and mobile device interaction, preventing unauthorized access to system resources.
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Observability - Native integration with OpenTelemetry for distributed tracing across the entire agent execution pipeline. AgentScope Studio provides visual debugging, real-time monitoring, and comprehensive logging for development and production environments.
Quick Start
Requirements: JDK 17+
<dependency>
<groupId>io.agentscope</groupId>
<artifactId>agentscope</artifactId>
<version>1.0.6</version>
</dependency>
ReActAgent agent = ReActAgent.builder()
.name("Assistant")
.sysPrompt("You are a helpful AI assistant.")
.model(DashScopeChatModel.builder()
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.modelName("qwen-max")
.build())
.build();
Msg response = agent.call(Msg.builder()
.textContent("Hello!")
.build()).block();
System.out.println(response.getTextContent());
For more examples, see the documentation.
Contributing
We welcome contributions! Please see CONTRIBUTING.md for guidelines.
Community
| Discord | DingTalk | |
|---|---|---|
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License
Apache License 2.0 - see LICENSE for details.
Publications
If you find AgentScope helpful, please cite our papers:
- AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
- AgentScope: A Flexible yet Robust Multi-Agent Platform


