package org.ruoyi.chat.service.chat.impl;
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import cn.hutool.json.JSONUtil;
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import io.modelcontextprotocol.client.McpClient;
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import io.modelcontextprotocol.client.transport.WebFluxSseClientTransport;
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import io.modelcontextprotocol.spec.McpSchema;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.ruoyi.chat.listener.SSEEventSourceListener;
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import org.ruoyi.chat.service.chat.IChatService;
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import org.ruoyi.common.chat.entity.chat.*;
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import org.ruoyi.common.chat.entity.chat.tool.ToolCallFunction;
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import org.ruoyi.common.chat.entity.chat.tool.Tools;
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import org.ruoyi.common.chat.entity.chat.tool.ToolsFunction;
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import org.ruoyi.common.chat.openai.OpenAiStreamClient;
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import org.ruoyi.common.chat.request.ChatRequest;
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import org.ruoyi.common.core.exception.ServiceException;
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import org.springframework.stereotype.Service;
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import org.springframework.web.reactive.function.client.WebClient;
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import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Map;
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@Service
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@Slf4j
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@RequiredArgsConstructor
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public class OpenAIServiceImpl implements IChatService {
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private final OpenAiStreamClient openAiStreamClient;
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@Override
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public SseEmitter chat(ChatRequest chatRequest,SseEmitter emitter) {
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String toolString = mcpChat(chatRequest);
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Message userMessage = Message.builder().content("工具返回信息："+toolString).role(Message.Role.ASSISTANT).build();
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List<Message> messages = chatRequest.getMessages();
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messages.add(userMessage);
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SSEEventSourceListener openAIEventSourceListener = new SSEEventSourceListener(emitter);
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ChatCompletion completion = ChatCompletion
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.builder()
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.messages(messages)
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.model(chatRequest.getModel())
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.stream(true)
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.build();
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openAiStreamClient.streamChatCompletion(completion, openAIEventSourceListener);
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return emitter;
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}
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public String mcpChat(ChatRequest chatRequest) {
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WebFluxSseClientTransport webFluxSseClientTransport = new WebFluxSseClientTransport(WebClient.builder().baseUrl("http://localhost:8080"));
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ChatCompletion completion = ChatCompletion
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.builder()
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.messages(chatRequest.getMessages())
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.model(chatRequest.getModel())
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.stream(false)
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.build();
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List<Tools> tools = new ArrayList<>();
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McpSchema.Content content = null;
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try (var client = McpClient.sync(webFluxSseClientTransport).build()) {
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client.initialize();
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McpSchema.ListToolsResult toolsList = client.listTools();
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for (McpSchema.Tool mcpTool : toolsList.tools()) {
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McpSchema.JsonSchema jsonSchema = mcpTool.inputSchema();
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Parameters parameters = Parameters.builder()
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.type(jsonSchema.type())
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.properties(jsonSchema.properties())
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.required(jsonSchema.required()).build();
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Tools tool = Tools.builder()
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.type(Tools.Type.FUNCTION.getName())
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.function(ToolsFunction.builder().name(mcpTool.name()).description(mcpTool.description()).parameters(parameters).build())
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.build();
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tools.add(tool);
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}
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completion.setTools(tools);
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ChatCompletionResponse chatCompletionResponse = openAiStreamClient.chatCompletion(completion);
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String arguments = chatCompletionResponse.getChoices().get(0).getMessage().getToolCalls().get(0).getFunction().getArguments();
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String name = chatCompletionResponse.getChoices().get(0).getMessage().getToolCalls().get(0).getFunction().getName();
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Map<String, Object> map = JSONUtil.toBean(arguments, Map.class);
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McpSchema.CallToolResult sumResult = client.callTool(new McpSchema.CallToolRequest(name, map));
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content= sumResult.content().get(0);
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} catch (Exception e) {
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throw new ServiceException("请求失败"+e);
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}
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return content.toString();
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}
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}
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