feat: 新增统一模型网关与模型管理工作区
- 新增 OpenAI 兼容统一模型调用链路、模型发布配置与批量发布能力 - 重构模型管理页面入口与统一网关工作区，更新服务商 logo 资源与模型 ID 文案 - 收口全新库初始化脚本，仅保留服务商种子并整理统一网关 migration
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package tech.easyflow.ai.invoke.mapper;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import org.junit.Assert;
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import org.junit.Test;
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import tech.easyflow.ai.invoke.exception.ModelInvokeException;
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import tech.easyflow.ai.invoke.model.UnifiedChatRequest;
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import tech.easyflow.ai.invoke.model.UnifiedChatResponse;
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import tech.easyflow.ai.invoke.model.UnifiedChoice;
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import tech.easyflow.ai.invoke.model.UnifiedContentPart;
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import tech.easyflow.ai.invoke.model.UnifiedImageUrl;
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import tech.easyflow.ai.invoke.model.UnifiedMessage;
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import tech.easyflow.ai.invoke.model.UnifiedResponseFormat;
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import tech.easyflow.ai.invoke.model.UnifiedTool;
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import tech.easyflow.ai.invoke.model.UnifiedToolCall;
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import tech.easyflow.ai.invoke.model.UnifiedToolCallFunction;
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import tech.easyflow.ai.invoke.model.UnifiedToolFunction;
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import tech.easyflow.ai.invoke.model.UnifiedUsage;
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import tech.easyflow.ai.invoke.protocol.openai.OpenAiChatCompletionRequest;
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import tech.easyflow.ai.invoke.protocol.openai.OpenAiChatCompletionResponse;
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import java.util.Collections;
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import java.util.List;
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public class OpenAiProtocolMapperTest {
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private final OpenAiProtocolMapper mapper = new OpenAiProtocolMapper(new ObjectMapper());
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@Test
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public void shouldParseTextAndImageRequest() {
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String rawBody = """
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{
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"model": "gpt-4-1-prod",
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"messages": [
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "帮我看下这张图"
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},
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{
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"type": "image_url",
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"image_url": {
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"url": "data:image/png;base64,AAAA",
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"detail": "high"
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}
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}
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]
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}
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],
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"stream": false,
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"temperature": 0.2,
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"top_p": 0.8,
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"max_tokens": 512,
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"seed": 7,
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"tools": [
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{
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"type": "function",
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"function": {
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"name": "query_weather",
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"description": "query weather",
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"parameters": {
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"type": "object"
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}
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}
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}
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],
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"tool_choice": "auto",
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"response_format": {
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"type": "json_schema",
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"json_schema": {
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"name": "weather_schema"
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}
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}
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}
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""";
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OpenAiChatCompletionRequest request = mapper.readRequest(rawBody);
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UnifiedChatRequest unifiedRequest = mapper.toUnifiedRequest(request);
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Assert.assertEquals("gpt-4-1-prod", unifiedRequest.getModel());
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Assert.assertEquals(Long.valueOf(7), unifiedRequest.getSeed());
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Assert.assertEquals(Integer.valueOf(512), unifiedRequest.getMaxTokens());
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Assert.assertNotNull(unifiedRequest.getTools());
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Assert.assertEquals(1, unifiedRequest.getTools().size());
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Assert.assertEquals("query_weather", unifiedRequest.getTools().get(0).getFunction().getName());
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Assert.assertEquals("json_schema", unifiedRequest.getResponseFormat().getType());
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Assert.assertEquals("weather_schema", unifiedRequest.getResponseFormat().getJsonSchema().get("name").asText());
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UnifiedMessage message = unifiedRequest.getMessages().get(0);
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Assert.assertEquals("user", message.getRole());
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Assert.assertNotNull(message.getContentParts());
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Assert.assertEquals(2, message.getContentParts().size());
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UnifiedContentPart imagePart = message.getContentParts().get(1);
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Assert.assertEquals("image_url", imagePart.getType());
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Assert.assertEquals("data:image/png;base64,AAAA", imagePart.getImageUrl().getUrl());
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Assert.assertEquals("high", imagePart.getImageUrl().getDetail());
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}
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@Test
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public void shouldRejectUnsupportedRootField() {
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String rawBody = """
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{
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"model": "gpt-4-1-prod",
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"messages": [
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{
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"role": "user",
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"content": "hello"
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}
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],
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"n": 2
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}
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""";
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ModelInvokeException exception = Assert.assertThrows(
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ModelInvokeException.class,
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() -> mapper.readRequest(rawBody)
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);
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Assert.assertEquals(400, exception.getStatus());
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Assert.assertEquals("unsupported_field", exception.getCode());
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}
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@Test
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public void shouldAllowMissingOptionalFields() {
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String rawBody = """
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{
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"model": "deepseek-chat",
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"messages": [
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{
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"role": "user",
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"content": "你好，介绍一下你自己。"
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}
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]
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}
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""";
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OpenAiChatCompletionRequest request = mapper.readRequest(rawBody);
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UnifiedChatRequest unifiedRequest = mapper.toUnifiedRequest(request);
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Assert.assertEquals("deepseek-chat", unifiedRequest.getModel());
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Assert.assertNotNull(unifiedRequest.getMessages());
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Assert.assertEquals(1, unifiedRequest.getMessages().size());
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Assert.assertNull(unifiedRequest.getTools());
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Assert.assertNull(unifiedRequest.getToolChoice());
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Assert.assertNull(unifiedRequest.getResponseFormat());
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}
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@Test
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public void shouldMapToolCallsAndUsageInResponse() {
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UnifiedChatResponse response = new UnifiedChatResponse();
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response.setId("chatcmpl-1");
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response.setObject("chat.completion");
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response.setCreated(123L);
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response.setModel("gpt-4-1-prod");
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UnifiedToolCallFunction toolCallFunction = new UnifiedToolCallFunction();
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toolCallFunction.setName("query_weather");
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toolCallFunction.setArguments("{\"city\":\"shanghai\"}");
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UnifiedToolCall toolCall = new UnifiedToolCall();
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toolCall.setId("call_1");
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toolCall.setType("function");
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toolCall.setFunction(toolCallFunction);
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UnifiedMessage message = new UnifiedMessage();
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message.setRole("assistant");
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message.setContent(null);
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message.setToolCalls(Collections.singletonList(toolCall));
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UnifiedChoice choice = new UnifiedChoice();
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choice.setIndex(0);
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choice.setMessage(message);
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choice.setFinishReason("tool_calls");
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UnifiedUsage usage = new UnifiedUsage();
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usage.setPromptTokens(12);
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usage.setCompletionTokens(34);
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usage.setTotalTokens(46);
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response.setChoices(List.of(choice));
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response.setUsage(usage);
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OpenAiChatCompletionResponse openAiResponse = mapper.toOpenAiResponse(response);
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Assert.assertEquals("chatcmpl-1", openAiResponse.getId());
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Assert.assertEquals("tool_calls", openAiResponse.getChoices().get(0).getFinishReason());
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Assert.assertEquals("query_weather", openAiResponse.getChoices().get(0).getMessage().getToolCalls().get(0).getFunction().getName());
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Assert.assertEquals(Integer.valueOf(46), openAiResponse.getUsage().getTotalTokens());
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}
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}
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