feat: 增强智能体模型调用兼容能力
- 增加模型流式开关和 HTTP 传输策略配置 - 使用 AgentScope 执行基础连接、流式与 VLM 双阶段验证 - 固定多模态校验图片并统一验证状态展示
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package tech.easyflow.agent.runtime;
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import com.easyagents.agent.runtime.model.AgentGenerationOptions;
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import com.easyagents.agent.runtime.model.AgentHttpVersionPolicy;
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import com.easyagents.agent.runtime.model.AgentModelSpec;
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import org.junit.Assert;
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import org.junit.Test;
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import tech.easyflow.agent.entity.Agent;
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import tech.easyflow.ai.entity.Model;
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import tech.easyflow.ai.service.ModelService;
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import java.lang.reflect.Field;
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import java.lang.reflect.Method;
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import java.math.BigInteger;
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import java.util.Map;
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/**
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* Agent 模型生成和 HTTP 传输配置编译测试。
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*/
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public class AgentRuntimeCompilerModelConfigTest {
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/**
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* 验证缺少 stream 时默认开启，显式关闭时保持关闭。
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*
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* @throws Exception 反射调用失败时抛出
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*/
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@Test
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public void generationStreamShouldDefaultToTrueAndAllowFalse() throws Exception {
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AgentRuntimeCompiler compiler = new AgentRuntimeCompiler();
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AgentGenerationOptions defaultOptions = invokeGenerationOptions(compiler, Map.of());
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AgentGenerationOptions disabledOptions = invokeGenerationOptions(compiler, Map.of("stream", false));
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Assert.assertTrue(defaultOptions.getStream());
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Assert.assertFalse(disabledOptions.getStream());
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}
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/**
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* 验证模型 options 中的 HTTP 策略会编译到中立模型声明。
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*
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* @throws Exception 反射调用失败时抛出
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*/
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@Test
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public void modelHttpPolicyShouldCompileFromOptions() throws Exception {
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Model model = model(Map.of("agentHttpVersionPolicy", "HTTP_1_1"));
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AgentRuntimeCompiler compiler = compiler(model);
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AgentModelSpec spec = invokeModelSpec(compiler);
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Assert.assertEquals(AgentHttpVersionPolicy.HTTP_1_1, spec.getHttpVersionPolicy());
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}
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/**
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* 验证未知 HTTP 策略安全回退到 AUTO。
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*
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* @throws Exception 反射调用失败时抛出
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*/
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@Test
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public void unknownModelHttpPolicyShouldFallbackToAuto() throws Exception {
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Model model = model(Map.of("agentHttpVersionPolicy", "HTTP_3"));
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AgentRuntimeCompiler compiler = compiler(model);
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AgentModelSpec spec = invokeModelSpec(compiler);
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Assert.assertEquals(AgentHttpVersionPolicy.AUTO, spec.getHttpVersionPolicy());
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}
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/**
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* 创建已注入模型服务的编译器。
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*
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* @param model 模型
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* @return 编译器
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* @throws Exception 注入失败时抛出
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*/
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private AgentRuntimeCompiler compiler(Model model) throws Exception {
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AgentRuntimeCompiler compiler = new AgentRuntimeCompiler();
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ModelService modelService = (ModelService) java.lang.reflect.Proxy.newProxyInstance(
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ModelService.class.getClassLoader(),
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new Class<?>[]{ModelService.class},
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(proxy, method, args) -> "getModelInstance".equals(method.getName()) ? model : null);
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Field field = AgentRuntimeCompiler.class.getDeclaredField("modelService");
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field.setAccessible(true);
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field.set(compiler, modelService);
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return compiler;
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}
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/**
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* 创建测试模型。
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*
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* @param options 模型扩展配置
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* @return 测试模型
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*/
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private Model model(Map<String, Object> options) {
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Model model = new Model();
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model.setId(BigInteger.TEN);
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model.setModelName("test-model");
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model.setOptions(options);
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return model;
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}
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/**
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* 调用私有生成参数编译方法。
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*
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* @param compiler 编译器
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* @param config 生成配置
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* @return 生成参数
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* @throws Exception 反射调用失败时抛出
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*/
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private AgentGenerationOptions invokeGenerationOptions(AgentRuntimeCompiler compiler,
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Map<String, Object> config) throws Exception {
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Method method = AgentRuntimeCompiler.class.getDeclaredMethod("buildGenerationOptions", Map.class);
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method.setAccessible(true);
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return (AgentGenerationOptions) method.invoke(compiler, config);
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}
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/**
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* 调用私有模型声明编译方法。
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*
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* @param compiler 编译器
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* @return 模型声明
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* @throws Exception 反射调用失败时抛出
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*/
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private AgentModelSpec invokeModelSpec(AgentRuntimeCompiler compiler) throws Exception {
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Agent agent = new Agent();
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agent.setModelId(BigInteger.TEN);
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Method method = AgentRuntimeCompiler.class.getDeclaredMethod("buildModelSpec", Agent.class);
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method.setAccessible(true);
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return (AgentModelSpec) method.invoke(compiler, agent);
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}
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}
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package tech.easyflow.agent.runtime;
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import com.easyagents.agent.runtime.agentscope.AgentScopeMessageAdapter;
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import com.easyagents.agent.runtime.model.AgentGenerationOptions;
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import com.easyagents.agent.runtime.model.AgentModelFactory;
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import com.easyagents.agent.runtime.model.AgentModelSpec;
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import io.agentscope.core.message.Base64Source;
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import io.agentscope.core.message.ImageBlock;
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import io.agentscope.core.message.Msg;
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import io.agentscope.core.message.TextBlock;
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import io.agentscope.core.model.ChatResponse;
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import io.agentscope.core.model.GenerateOptions;
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import io.agentscope.core.model.ToolSchema;
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import org.junit.Assert;
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import org.junit.Test;
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import reactor.core.publisher.Flux;
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import tech.easyflow.ai.entity.Model;
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import tech.easyflow.ai.entity.ModelProvider;
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import tech.easyflow.ai.service.support.VlmVerificationImage;
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import tech.easyflow.ai.service.verification.ChatModelVerificationResult;
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import tech.easyflow.ai.service.verification.ModelVerificationStatus;
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import tech.easyflow.common.web.exceptions.BusinessException;
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import java.math.BigInteger;
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import java.time.Duration;
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import java.util.ArrayList;
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import java.util.Base64;
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import java.util.List;
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/**
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* AgentScope 双阶段模型连通性验证测试。
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*/
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public class AgentScopeChatModelConnectivityVerifierTest {
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/**
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* 验证非流式与流式阶段按顺序执行并返回通过状态。
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*/
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@Test
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public void shouldPassWhenBothPhasesReturnText() {
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RecordingModelFactory factory = new RecordingModelFactory(
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Flux.just(response("你好")),
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Flux.just(response("你"), response("好")));
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AgentScopeChatModelConnectivityVerifier verifier = verifier(factory);
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ChatModelVerificationResult result = verifier.verify(model(false));
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Assert.assertEquals(ModelVerificationStatus.PASSED, result.getStatus());
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Assert.assertEquals("HTTP_1_1", result.getEffectiveHttpVersion());
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Assert.assertEquals(List.of(false, true), factory.getFactoryStreams());
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Assert.assertEquals(List.of(false, true), factory.getRequestStreams());
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Assert.assertEquals(List.of(false, false), factory.getEnableThinkingValues());
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Assert.assertEquals(List.of(false, false), factory.getChatTemplateThinkingValues());
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}
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/**
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* 验证基础连接通过而流式阶段失败时返回部分通过结果。
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*/
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@Test
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public void shouldReturnPartialWhenStreamingPhaseFails() {
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RecordingModelFactory factory = new RecordingModelFactory(
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Flux.just(response("你好")),
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Flux.error(new IllegalStateException("stream failed")));
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ChatModelVerificationResult result = verifier(factory).verify(model(false));
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Assert.assertEquals(ModelVerificationStatus.PARTIAL, result.getStatus());
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Assert.assertEquals(ModelVerificationStatus.PASSED, result.getNonStreaming());
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Assert.assertEquals(ModelVerificationStatus.FAILED, result.getStreaming());
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Assert.assertTrue(result.getMessage().contains("流式响应不可用"));
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}
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/**
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* 验证基础连接失败时立即终止且返回业务失败。
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*/
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@Test
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public void shouldStopWhenNonStreamingPhaseFails() {
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RecordingModelFactory factory = new RecordingModelFactory(
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Flux.error(new IllegalStateException("connection failed")));
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try {
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verifier(factory).verify(model(false));
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Assert.fail("Expected base connectivity verification failure");
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} catch (BusinessException exception) {
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Assert.assertTrue(exception.getMessage().contains("基础连接验证失败"));
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Assert.assertFalse(exception.getMessage().contains("connection failed"));
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}
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Assert.assertEquals(List.of(false), factory.getFactoryStreams());
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}
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/**
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* 验证流式阶段超时被归类为部分可用且不暴露底层异常。
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*/
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@Test
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public void shouldReturnPartialWhenStreamingPhaseTimesOut() {
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RecordingModelFactory factory = new RecordingModelFactory(
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Flux.just(response("你好")),
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Flux.never());
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AgentScopeChatModelConnectivityVerifier verifier = new AgentScopeChatModelConnectivityVerifier(
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factory,
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new AgentScopeMessageAdapter(),
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Duration.ofMillis(20));
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ChatModelVerificationResult result = verifier.verify(model(false));
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Assert.assertEquals(ModelVerificationStatus.PARTIAL, result.getStatus());
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Assert.assertEquals("连接成功，流式响应不可用，可关闭智能体的模型流式响应。",
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result.getMessage());
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}
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/**
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* 验证 VLM 使用 Base64 图片，并能聚合流式文本增量。
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*/
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@Test
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public void shouldVerifyVlmImageAndAggregateStreamingChunks() {
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RecordingModelFactory factory = new RecordingModelFactory(
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Flux.just(response("图片中的内容是“" + VlmVerificationImage.VERIFICATION_CODE + "”。")),
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Flux.just(response("识别结果：58"), response("39")));
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ChatModelVerificationResult result = verifier(factory).verify(model(true));
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Assert.assertEquals(ModelVerificationStatus.PASSED, result.getStatus());
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Msg message = factory.getMessages().get(0);
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ImageBlock image = message.getContent().stream()
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.filter(ImageBlock.class::isInstance)
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.map(ImageBlock.class::cast)
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.findFirst()
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.orElseThrow();
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Assert.assertTrue(image.getSource() instanceof Base64Source);
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byte[] imageBytes = Base64.getDecoder().decode(((Base64Source) image.getSource()).getData());
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Assert.assertEquals((byte) 0x89, imageBytes[0]);
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Assert.assertEquals((byte) 0x50, imageBytes[1]);
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}
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/**
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* 创建待验证模型。
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*
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* @param supportImage 是否支持图片
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* @return 测试模型
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*/
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private Model model(boolean supportImage) {
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Model model = new Model();
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model.setId(BigInteger.TEN);
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model.setModelName("test-model");
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model.setEndpoint("http://model.example.com");
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model.setRequestPath("/v1/chat/completions");
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model.setApiKey("test-key");
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model.setSupportImage(supportImage);
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ModelProvider provider = new ModelProvider();
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provider.setProviderType("gpustack");
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model.setModelProvider(provider);
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return model;
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}
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/**
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* 创建使用测试工厂的验证器。
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*
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* @param factory 记录型模型工厂
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* @return 验证器
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*/
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private AgentScopeChatModelConnectivityVerifier verifier(RecordingModelFactory factory) {
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return new AgentScopeChatModelConnectivityVerifier(
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factory,
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new AgentScopeMessageAdapter(),
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Duration.ofSeconds(2));
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}
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/**
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* 创建单个文本响应片段。
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*
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* @param text 文本内容
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* @return AgentScope 响应
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*/
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private ChatResponse response(String text) {
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return ChatResponse.builder()
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.content(List.of(TextBlock.builder().text(text).build()))
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.build();
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}
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/**
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* 按阶段返回预设响应并记录调用参数的模型工厂。
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*/
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private static final class RecordingModelFactory
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implements AgentModelFactory<io.agentscope.core.model.Model> {
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/** 每个阶段的预设响应。 */
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private final List<Flux<ChatResponse>> phaseResponses;
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/** 模型工厂收到的流式参数。 */
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private final List<Boolean> factoryStreams = new ArrayList<>();
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/** 模型请求收到的流式参数。 */
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private final List<Boolean> requestStreams = new ArrayList<>();
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/** 模型请求收到的消息。 */
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private final List<Msg> messages = new ArrayList<>();
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/** OpenAI-compatible 请求中的思考开关。 */
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private final List<Object> enableThinkingValues = new ArrayList<>();
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/** GPUStack 模板参数中的思考开关。 */
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private final List<Object> chatTemplateThinkingValues = new ArrayList<>();
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/**
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* 创建记录型模型工厂。
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*
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* @param phaseResponses 每个阶段的预设响应
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*/
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@SafeVarargs
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private RecordingModelFactory(Flux<ChatResponse>... phaseResponses) {
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this.phaseResponses = List.of(phaseResponses);
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}
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/**
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* 创建当前验证阶段的测试模型。
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*
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* @param modelSpec 模型声明
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* @param generationOptions 生成参数
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* @return 测试模型
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*/
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@Override
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public io.agentscope.core.model.Model create(
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AgentModelSpec modelSpec,
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AgentGenerationOptions generationOptions) {
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int phaseIndex = factoryStreams.size();
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factoryStreams.add(Boolean.TRUE.equals(generationOptions.getStream()));
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enableThinkingValues.add(
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generationOptions.getAdditionalBodyParams().get("enable_thinking"));
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Object templateOptions = generationOptions.getAdditionalBodyParams()
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.get("chat_template_kwargs");
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chatTemplateThinkingValues.add(templateOptions instanceof java.util.Map<?, ?> map
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? map.get("enable_thinking")
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: null);
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Flux<ChatResponse> responses = phaseResponses.get(phaseIndex);
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return new io.agentscope.core.model.Model() {
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/**
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* 返回预设响应并记录真实请求参数。
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*
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* @param inputMessages 模型消息
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* @param tools 工具声明
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* @param options 生成参数
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* @return 预设响应
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*/
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@Override
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public Flux<ChatResponse> stream(
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List<Msg> inputMessages,
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List<ToolSchema> tools,
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GenerateOptions options) {
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requestStreams.add(Boolean.TRUE.equals(options.getStream()));
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messages.add(inputMessages.get(0));
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return responses;
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}
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/**
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* 返回测试模型名称。
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*
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* @return 测试模型名称
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*/
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@Override
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public String getModelName() {
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return modelSpec.getModelName();
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}
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};
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}
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/**
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* 获取工厂流式参数记录。
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*
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* @return 流式参数列表
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*/
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private List<Boolean> getFactoryStreams() {
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return factoryStreams;
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}
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/**
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* 获取请求流式参数记录。
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*
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* @return 流式参数列表
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*/
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private List<Boolean> getRequestStreams() {
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return requestStreams;
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}
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/**
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* 获取请求消息记录。
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*
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* @return 消息列表
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*/
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private List<Msg> getMessages() {
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return messages;
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}
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/**
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* 获取 OpenAI-compatible 请求中的思考开关。
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*
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* @return 各阶段思考开关
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*/
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private List<Object> getEnableThinkingValues() {
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return enableThinkingValues;
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}
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/**
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* 获取 GPUStack 模板参数中的思考开关。
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*
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* @return 各阶段模板思考开关
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*/
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private List<Object> getChatTemplateThinkingValues() {
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return chatTemplateThinkingValues;
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}
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}
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}
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