mirror of
https://github.com/tencentmusic/supersonic.git
synced 2025-12-10 02:46:56 +00:00
(improvement)(chat|common|headless|webapp) 结果分析,改写伪流式输出,加快响应速度 (#2395)
This commit is contained in:
@@ -18,4 +18,5 @@ public class ChatExecuteReq {
|
||||
private int parseId;
|
||||
private String queryText;
|
||||
private boolean saveAnswer;
|
||||
private boolean streamingResult;
|
||||
}
|
||||
|
||||
@@ -32,6 +32,7 @@ import dev.langchain4j.model.input.PromptTemplate;
|
||||
import dev.langchain4j.model.output.Response;
|
||||
import dev.langchain4j.provider.ModelProvider;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
|
||||
@@ -171,10 +172,6 @@ public class NL2SQLParser implements ChatQueryParser {
|
||||
return;
|
||||
}
|
||||
|
||||
// derive mapping result of current question and parsing result of last question.
|
||||
ChatLayerService chatLayerService = ContextUtils.getBean(ChatLayerService.class);
|
||||
MapResp currentMapResult = chatLayerService.map(queryNLReq);
|
||||
|
||||
List<QueryResp> historyQueries =
|
||||
getHistoryQueries(parseContext.getRequest().getChatId(), 1);
|
||||
if (historyQueries.isEmpty()) {
|
||||
@@ -182,12 +179,18 @@ public class NL2SQLParser implements ChatQueryParser {
|
||||
}
|
||||
QueryResp lastQuery = historyQueries.get(0);
|
||||
SemanticParseInfo lastParseInfo = lastQuery.getParseInfos().get(0);
|
||||
Long dataId = lastParseInfo.getDataSetId();
|
||||
String histSQL = lastParseInfo.getSqlInfo().getCorrectedS2SQL();
|
||||
if (StringUtils.isBlank(histSQL)) // 优化性能,如果问答不是chat bi 则无需重写,因为数据都不全
|
||||
return;
|
||||
|
||||
// derive mapping result of current question and parsing result of last question.
|
||||
ChatLayerService chatLayerService = ContextUtils.getBean(ChatLayerService.class);
|
||||
MapResp currentMapResult = chatLayerService.map(queryNLReq); // 优化性能 ,只有满足条件才mapping
|
||||
|
||||
Long dataId = lastParseInfo.getDataSetId();
|
||||
String curtMapStr =
|
||||
generateSchemaPrompt(currentMapResult.getMapInfo().getMatchedElements(dataId));
|
||||
String histMapStr = generateSchemaPrompt(lastParseInfo.getElementMatches());
|
||||
String histSQL = lastParseInfo.getSqlInfo().getCorrectedS2SQL();
|
||||
|
||||
Map<String, Object> variables = new HashMap<>();
|
||||
variables.put("current_question", currentMapResult.getQueryText());
|
||||
|
||||
@@ -1,13 +1,20 @@
|
||||
package com.tencent.supersonic.chat.server.processor.execute;
|
||||
|
||||
import com.alibaba.fastjson.JSON;
|
||||
import com.alibaba.fastjson.JSONObject;
|
||||
import com.tencent.supersonic.chat.api.pojo.response.QueryResult;
|
||||
import com.tencent.supersonic.chat.server.agent.Agent;
|
||||
import com.tencent.supersonic.chat.server.persistence.dataobject.ChatQueryDO;
|
||||
import com.tencent.supersonic.chat.server.persistence.repository.ChatQueryRepository;
|
||||
import com.tencent.supersonic.chat.server.pojo.ExecuteContext;
|
||||
import com.tencent.supersonic.common.pojo.ChatApp;
|
||||
import com.tencent.supersonic.common.pojo.enums.AppModule;
|
||||
import com.tencent.supersonic.common.util.ChatAppManager;
|
||||
import com.tencent.supersonic.common.util.ContextUtils;
|
||||
import dev.langchain4j.data.message.AiMessage;
|
||||
import dev.langchain4j.model.StreamingResponseHandler;
|
||||
import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatLanguageModel;
|
||||
import dev.langchain4j.model.input.Prompt;
|
||||
import dev.langchain4j.model.input.PromptTemplate;
|
||||
import dev.langchain4j.model.output.Response;
|
||||
@@ -24,9 +31,11 @@ import java.util.Objects;
|
||||
* DataInterpretProcessor interprets query result to make it more readable to the users.
|
||||
*/
|
||||
public class DataInterpretProcessor implements ExecuteResultProcessor {
|
||||
|
||||
public static String tip = "AI 回答中...\r\n";
|
||||
private static final Logger keyPipelineLog = LoggerFactory.getLogger("keyPipeline");
|
||||
|
||||
private static Map<Long, StringBuffer> resultCache = new HashMap<>();
|
||||
|
||||
public static final String APP_KEY = "DATA_INTERPRETER";
|
||||
private static final String INSTRUCTION = ""
|
||||
+ "#Role: You are a data expert who communicates with business users everyday."
|
||||
@@ -41,6 +50,16 @@ public class DataInterpretProcessor implements ExecuteResultProcessor {
|
||||
.appModule(AppModule.CHAT).description("通过大模型对结果数据做提炼总结").enable(false).build());
|
||||
}
|
||||
|
||||
public static String getTextSummary(Long queryId) {
|
||||
if (resultCache.get(queryId) != null) {
|
||||
return resultCache.get(queryId).toString();
|
||||
}
|
||||
return "";
|
||||
}
|
||||
|
||||
public static Map<Long, StringBuffer> getResultCache() {
|
||||
return resultCache;
|
||||
}
|
||||
|
||||
@Override
|
||||
public boolean accept(ExecuteContext executeContext) {
|
||||
@@ -71,14 +90,49 @@ public class DataInterpretProcessor implements ExecuteResultProcessor {
|
||||
variable.put("data", queryResult.getTextResult());
|
||||
|
||||
Prompt prompt = PromptTemplate.from(chatApp.getPrompt()).apply(variable);
|
||||
ChatLanguageModel chatLanguageModel =
|
||||
ModelProvider.getChatModel(chatApp.getChatModelConfig());
|
||||
Response<AiMessage> response = chatLanguageModel.generate(prompt.toUserMessage());
|
||||
String anwser = response.content().text();
|
||||
keyPipelineLog.info("DataInterpretProcessor modelReq:\n{} \nmodelResp:\n{}", prompt.text(),
|
||||
anwser);
|
||||
if (StringUtils.isNotBlank(anwser)) {
|
||||
queryResult.setTextSummary(anwser);
|
||||
if (executeContext.getRequest().isStreamingResult()) {
|
||||
StreamingChatLanguageModel chatLanguageModel =
|
||||
ModelProvider.getChatStreamingModel(chatApp.getChatModelConfig());
|
||||
final Long queryId = executeContext.getRequest().getQueryId();
|
||||
resultCache.put(queryId, new StringBuffer(tip));
|
||||
chatLanguageModel.generate(prompt.toUserMessage(),
|
||||
new StreamingResponseHandler<AiMessage>() {
|
||||
@Override
|
||||
public void onNext(String token) {
|
||||
resultCache.get(queryId).append(token);
|
||||
}
|
||||
|
||||
@Override
|
||||
public void onComplete(Response<AiMessage> response) {
|
||||
ChatQueryRepository chatQueryRepository =
|
||||
ContextUtils.getBean(ChatQueryRepository.class);
|
||||
ChatQueryDO chatQueryDO = chatQueryRepository.getChatQueryDO(queryId);
|
||||
JSONObject queryResult = JSON.parseObject(chatQueryDO.getQueryResult());
|
||||
queryResult.put("textSummary",
|
||||
resultCache.get(queryId).toString().substring(tip.length()));
|
||||
chatQueryDO.setQueryResult(queryResult.toJSONString());
|
||||
chatQueryRepository.updateChatQuery(chatQueryDO);
|
||||
resultCache.remove(queryId);
|
||||
}
|
||||
|
||||
@Override
|
||||
public void onError(Throwable error) {
|
||||
error.printStackTrace();
|
||||
resultCache.remove(queryId);
|
||||
}
|
||||
});
|
||||
} else {
|
||||
ChatLanguageModel chatLanguageModel =
|
||||
ModelProvider.getChatModel(chatApp.getChatModelConfig());
|
||||
Response<AiMessage> response = chatLanguageModel.generate(prompt.toUserMessage());
|
||||
String anwser = response.content().text();
|
||||
keyPipelineLog.info("DataInterpretProcessor modelReq:\n{} \nmodelResp:\n{}",
|
||||
prompt.text(), anwser);
|
||||
if (StringUtils.isNotBlank(anwser)) {
|
||||
queryResult.setTextSummary(anwser);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
@@ -5,6 +5,7 @@ import com.tencent.supersonic.chat.api.pojo.request.ChatExecuteReq;
|
||||
import com.tencent.supersonic.chat.api.pojo.request.ChatParseReq;
|
||||
import com.tencent.supersonic.chat.api.pojo.request.ChatQueryDataReq;
|
||||
import com.tencent.supersonic.chat.api.pojo.response.ChatParseResp;
|
||||
import com.tencent.supersonic.chat.api.pojo.response.QueryResult;
|
||||
import com.tencent.supersonic.chat.server.service.ChatQueryService;
|
||||
import com.tencent.supersonic.common.pojo.User;
|
||||
import com.tencent.supersonic.common.pojo.exception.InvalidArgumentException;
|
||||
@@ -50,6 +51,14 @@ public class ChatQueryController {
|
||||
return chatQueryService.execute(chatExecuteReq);
|
||||
}
|
||||
|
||||
@PostMapping("getExecuteSummary")
|
||||
public Object getExecuteSummary(@RequestBody ChatExecuteReq chatExecuteReq,
|
||||
HttpServletRequest request, HttpServletResponse response) {
|
||||
chatExecuteReq.setUser(UserHolder.findUser(request, response));
|
||||
QueryResult res = chatQueryService.getTextSummary(chatExecuteReq);
|
||||
return res;
|
||||
}
|
||||
|
||||
@PostMapping("/")
|
||||
public Object query(@RequestBody ChatParseReq chatParseReq, HttpServletRequest request,
|
||||
HttpServletResponse response) throws Exception {
|
||||
|
||||
@@ -35,6 +35,8 @@ public interface ChatManageService {
|
||||
|
||||
QueryResp getChatQuery(Long queryId);
|
||||
|
||||
ChatQueryDO getChatQueryDO(Long queryId);
|
||||
|
||||
List<QueryResp> getChatQueries(Integer chatId);
|
||||
|
||||
ShowCaseResp queryShowCase(PageQueryInfoReq pageQueryInfoReq, int agentId);
|
||||
|
||||
@@ -19,6 +19,8 @@ public interface ChatQueryService {
|
||||
|
||||
QueryResult execute(ChatExecuteReq chatExecuteReq) throws Exception;
|
||||
|
||||
QueryResult getTextSummary(ChatExecuteReq chatExecuteReq);
|
||||
|
||||
QueryResult parseAndExecute(ChatParseReq chatParseReq);
|
||||
|
||||
Object queryData(ChatQueryDataReq chatQueryDataReq, User user) throws Exception;
|
||||
|
||||
@@ -123,6 +123,11 @@ public class ChatManageServiceImpl implements ChatManageService {
|
||||
return chatQueryRepository.getChatQuery(queryId);
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatQueryDO getChatQueryDO(Long queryId) {
|
||||
return chatQueryRepository.getChatQueryDO(queryId);
|
||||
}
|
||||
|
||||
@Override
|
||||
public List<QueryResp> getChatQueries(Integer chatId) {
|
||||
List<QueryResp> queries = chatQueryRepository.getChatQueries(chatId);
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
package com.tencent.supersonic.chat.server.service.impl;
|
||||
|
||||
import com.alibaba.fastjson.JSONObject;
|
||||
import com.alibaba.fastjson2.JSON;
|
||||
import com.google.common.collect.Lists;
|
||||
import com.tencent.supersonic.chat.api.pojo.request.ChatExecuteReq;
|
||||
import com.tencent.supersonic.chat.api.pojo.request.ChatParseReq;
|
||||
@@ -9,8 +11,10 @@ import com.tencent.supersonic.chat.api.pojo.response.QueryResult;
|
||||
import com.tencent.supersonic.chat.server.agent.Agent;
|
||||
import com.tencent.supersonic.chat.server.executor.ChatQueryExecutor;
|
||||
import com.tencent.supersonic.chat.server.parser.ChatQueryParser;
|
||||
import com.tencent.supersonic.chat.server.persistence.dataobject.ChatQueryDO;
|
||||
import com.tencent.supersonic.chat.server.pojo.ExecuteContext;
|
||||
import com.tencent.supersonic.chat.server.pojo.ParseContext;
|
||||
import com.tencent.supersonic.chat.server.processor.execute.DataInterpretProcessor;
|
||||
import com.tencent.supersonic.chat.server.processor.execute.ExecuteResultProcessor;
|
||||
import com.tencent.supersonic.chat.server.processor.parse.ParseResultProcessor;
|
||||
import com.tencent.supersonic.chat.server.service.AgentService;
|
||||
@@ -143,6 +147,21 @@ public class ChatQueryServiceImpl implements ChatQueryService {
|
||||
return queryResult;
|
||||
}
|
||||
|
||||
@Override
|
||||
public QueryResult getTextSummary(ChatExecuteReq chatExecuteReq) {
|
||||
String text = DataInterpretProcessor.getTextSummary(chatExecuteReq.getQueryId());
|
||||
if (StringUtils.isNotBlank(text)) {
|
||||
QueryResult res = new QueryResult();
|
||||
res.setTextSummary(text);
|
||||
res.setQueryId(chatExecuteReq.getQueryId());
|
||||
return res;
|
||||
} else {
|
||||
ChatQueryDO chatQueryDo = chatManageService.getChatQueryDO(chatExecuteReq.getQueryId());
|
||||
QueryResult res = JSON.parseObject(chatQueryDo.getQueryResult(), QueryResult.class);
|
||||
return res;
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public QueryResult parseAndExecute(ChatParseReq chatParseReq) {
|
||||
ChatParseResp parseResp = parse(chatParseReq);
|
||||
|
||||
@@ -108,6 +108,7 @@ public class PluginServiceImpl implements PluginService {
|
||||
if (StringUtils.isNotBlank(pluginQueryReq.getCreatedBy())) {
|
||||
queryWrapper.lambda().eq(PluginDO::getCreatedBy, pluginQueryReq.getCreatedBy());
|
||||
}
|
||||
queryWrapper.orderByAsc("name");
|
||||
List<PluginDO> pluginDOS = pluginRepository.query(queryWrapper);
|
||||
if (StringUtils.isNotBlank(pluginQueryReq.getPattern())) {
|
||||
pluginDOS = pluginDOS.stream()
|
||||
|
||||
@@ -16,6 +16,7 @@ import org.springframework.util.CollectionUtils;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.concurrent.atomic.AtomicReference;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
@Service
|
||||
public class SystemConfigServiceImpl extends ServiceImpl<SystemConfigMapper, SystemConfigDO>
|
||||
@@ -38,8 +39,8 @@ public class SystemConfigServiceImpl extends ServiceImpl<SystemConfigMapper, Sys
|
||||
return systemConfigDb;
|
||||
}
|
||||
|
||||
private SystemConfig getSystemConfigFromDB() {
|
||||
List<SystemConfigDO> list = list();
|
||||
private SystemConfig getSystemConfigFromDB() { // 加上id ,如果有多条记录,会出错
|
||||
List<SystemConfigDO> list = this.lambdaQuery().eq(SystemConfigDO::getId, 1).list();
|
||||
if (CollectionUtils.isEmpty(list)) {
|
||||
SystemConfig systemConfig = new SystemConfig();
|
||||
systemConfig.setId(1);
|
||||
|
||||
@@ -7,6 +7,7 @@ import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.dify.DifyAiChatModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiEmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import org.springframework.beans.factory.InitializingBean;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
@@ -25,6 +26,11 @@ public class DifyModelFactory implements ModelFactory, InitializingBean {
|
||||
.modelName(modelConfig.getModelName()).timeOut(modelConfig.getTimeOut()).build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public OpenAiStreamingChatModel createChatStreamingModel(ChatModelConfig modelConfig) {
|
||||
throw new RuntimeException("待开发");
|
||||
}
|
||||
|
||||
@Override
|
||||
public EmbeddingModel createEmbeddingModel(EmbeddingModelConfig embeddingModelConfig) {
|
||||
return OpenAiEmbeddingModel.builder().baseUrl(embeddingModelConfig.getBaseUrl())
|
||||
|
||||
@@ -5,6 +5,7 @@ import com.tencent.supersonic.common.pojo.EmbeddingModelConfig;
|
||||
import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.embedding.S2OnnxEmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
import org.springframework.beans.factory.InitializingBean;
|
||||
import org.springframework.stereotype.Service;
|
||||
@@ -35,6 +36,11 @@ public class InMemoryModelFactory implements ModelFactory, InitializingBean {
|
||||
return EmbeddingModelConstant.BGE_SMALL_ZH_MODEL;
|
||||
}
|
||||
|
||||
@Override
|
||||
public OpenAiStreamingChatModel createChatStreamingModel(ChatModelConfig modelConfig) {
|
||||
throw new RuntimeException("待开发");
|
||||
}
|
||||
|
||||
@Override
|
||||
public void afterPropertiesSet() {
|
||||
ModelProvider.add(PROVIDER, this);
|
||||
|
||||
@@ -6,6 +6,7 @@ import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.localai.LocalAiChatModel;
|
||||
import dev.langchain4j.model.localai.LocalAiEmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import org.springframework.beans.factory.InitializingBean;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
@@ -27,6 +28,11 @@ public class LocalAiModelFactory implements ModelFactory, InitializingBean {
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public OpenAiStreamingChatModel createChatStreamingModel(ChatModelConfig modelConfig) {
|
||||
throw new RuntimeException("待开发");
|
||||
}
|
||||
|
||||
@Override
|
||||
public EmbeddingModel createEmbeddingModel(EmbeddingModelConfig embeddingModel) {
|
||||
return LocalAiEmbeddingModel.builder().baseUrl(embeddingModel.getBaseUrl())
|
||||
|
||||
@@ -4,9 +4,12 @@ import com.tencent.supersonic.common.pojo.ChatModelConfig;
|
||||
import com.tencent.supersonic.common.pojo.EmbeddingModelConfig;
|
||||
import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
|
||||
public interface ModelFactory {
|
||||
ChatLanguageModel createChatModel(ChatModelConfig modelConfig);
|
||||
|
||||
OpenAiStreamingChatModel createChatStreamingModel(ChatModelConfig modelConfig);
|
||||
|
||||
EmbeddingModel createEmbeddingModel(EmbeddingModelConfig embeddingModel);
|
||||
}
|
||||
|
||||
@@ -5,7 +5,9 @@ import com.tencent.supersonic.common.pojo.ChatModelConfig;
|
||||
import com.tencent.supersonic.common.pojo.EmbeddingModelConfig;
|
||||
import com.tencent.supersonic.common.util.ContextUtils;
|
||||
import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatLanguageModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
|
||||
import java.util.HashMap;
|
||||
@@ -41,6 +43,20 @@ public class ModelProvider {
|
||||
"Unsupported ChatLanguageModel provider: " + modelConfig.getProvider());
|
||||
}
|
||||
|
||||
public static StreamingChatLanguageModel getChatStreamingModel(ChatModelConfig modelConfig) {
|
||||
if (modelConfig == null || StringUtils.isBlank(modelConfig.getProvider())
|
||||
|| StringUtils.isBlank(modelConfig.getBaseUrl())) {
|
||||
modelConfig = DEMO_CHAT_MODEL;
|
||||
}
|
||||
ModelFactory modelFactory = factories.get(modelConfig.getProvider().toUpperCase());
|
||||
if (modelFactory != null) {
|
||||
return modelFactory.createChatStreamingModel(modelConfig);
|
||||
}
|
||||
|
||||
throw new RuntimeException(
|
||||
"Unsupported ChatLanguageModel provider: " + modelConfig.getProvider());
|
||||
}
|
||||
|
||||
public static EmbeddingModel getEmbeddingModel() {
|
||||
return getEmbeddingModel(null);
|
||||
}
|
||||
|
||||
@@ -6,6 +6,7 @@ import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.ollama.OllamaChatModel;
|
||||
import dev.langchain4j.model.ollama.OllamaEmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import org.springframework.beans.factory.InitializingBean;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
@@ -28,6 +29,11 @@ public class OllamaModelFactory implements ModelFactory, InitializingBean {
|
||||
.logResponses(modelConfig.getLogResponses()).build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public OpenAiStreamingChatModel createChatStreamingModel(ChatModelConfig modelConfig) {
|
||||
throw new RuntimeException("待开发");
|
||||
}
|
||||
|
||||
@Override
|
||||
public EmbeddingModel createEmbeddingModel(EmbeddingModelConfig embeddingModelConfig) {
|
||||
return OllamaEmbeddingModel.builder().baseUrl(embeddingModelConfig.getBaseUrl())
|
||||
|
||||
@@ -6,6 +6,7 @@ import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiEmbeddingModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import org.springframework.beans.factory.InitializingBean;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
@@ -37,6 +38,16 @@ public class OpenAiModelFactory implements ModelFactory, InitializingBean {
|
||||
return openAiChatModelBuilder.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public OpenAiStreamingChatModel createChatStreamingModel(ChatModelConfig modelConfig) {
|
||||
return OpenAiStreamingChatModel.builder().baseUrl(modelConfig.getBaseUrl())
|
||||
.modelName(modelConfig.getModelName()).apiKey(modelConfig.keyDecrypt())
|
||||
.temperature(modelConfig.getTemperature()).topP(modelConfig.getTopP())
|
||||
.timeout(Duration.ofSeconds(modelConfig.getTimeOut()))
|
||||
.logRequests(modelConfig.getLogRequests())
|
||||
.logResponses(modelConfig.getLogResponses()).build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public EmbeddingModel createEmbeddingModel(EmbeddingModelConfig embeddingModel) {
|
||||
return OpenAiEmbeddingModel.builder().baseUrl(embeddingModel.getBaseUrl())
|
||||
|
||||
@@ -117,9 +117,17 @@ public class MultiCustomDictionary extends DynamicCustomDictionary {
|
||||
dictWord.setAlias(word.toLowerCase());
|
||||
String[] split = nature.split(DictWordType.NATURE_SPILT);
|
||||
if (split.length >= 2) {
|
||||
Long dimId = Long.parseLong(
|
||||
nature.split(DictWordType.NATURE_SPILT)[split.length - 1]);
|
||||
KnowledgeBaseService.addDimValueAlias(dimId, Arrays.asList(dictWord));
|
||||
try {
|
||||
Long dimId = Long.parseLong(
|
||||
nature.split(DictWordType.NATURE_SPILT)[split.length - 1]);
|
||||
KnowledgeBaseService.addDimValueAlias(dimId,
|
||||
Arrays.asList(dictWord));
|
||||
} catch (NumberFormatException e) {
|
||||
logger.warning(path + " : 非标准文件,不存入KnowledgeBaseService");
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -10,7 +10,14 @@ import {
|
||||
SimilarQuestionType,
|
||||
} from '../../common/type';
|
||||
import { createContext, useEffect, useRef, useState } from 'react';
|
||||
import { chatExecute, chatParse, queryData, deleteQuery, switchEntity } from '../../service';
|
||||
import {
|
||||
chatExecute,
|
||||
chatParse,
|
||||
queryData,
|
||||
deleteQuery,
|
||||
switchEntity,
|
||||
getExecuteSummary,
|
||||
} from '../../service';
|
||||
import { PARSE_ERROR_TIP, PREFIX_CLS, SEARCH_EXCEPTION_TIP } from '../../common/constants';
|
||||
import { message, Spin } from 'antd';
|
||||
import IconFont from '../IconFont';
|
||||
@@ -169,7 +176,7 @@ const ChatItem: React.FC<Props> = ({
|
||||
setExecuteLoading(true);
|
||||
}
|
||||
try {
|
||||
const res: any = await chatExecute(msg, conversationId!, parseInfoValue, agentId);
|
||||
const res: any = await chatExecute(msg, conversationId!, parseInfoValue, agentId, true);
|
||||
const valid = updateData(res);
|
||||
onMsgDataLoaded?.(
|
||||
{
|
||||
@@ -180,6 +187,20 @@ const ChatItem: React.FC<Props> = ({
|
||||
valid,
|
||||
isRefresh
|
||||
);
|
||||
const queryId = parseInfoValue.queryId; // 伪流式 大模型输出
|
||||
if (queryId != undefined && res.data.queryState != 'INVALID') {
|
||||
const getSummary = async (data: any, queryId: number) => {
|
||||
const res2: any = await getExecuteSummary(queryId);
|
||||
if (res2.data.queryMode == null) {
|
||||
res2.data = { ...data, textSummary: res2.data.textSummary };
|
||||
setData(res2.data);
|
||||
setTimeout(() => getSummary(data, queryId), 500);
|
||||
} else {
|
||||
setData(res2.data);
|
||||
}
|
||||
};
|
||||
setTimeout(() => getSummary(res.data, queryId), 500);
|
||||
}
|
||||
} catch (e) {
|
||||
const tip = SEARCH_EXCEPTION_TIP;
|
||||
setExecuteTip(SEARCH_EXCEPTION_TIP);
|
||||
@@ -423,6 +444,10 @@ const ChatItem: React.FC<Props> = ({
|
||||
return result;
|
||||
}, {});
|
||||
});
|
||||
if (exportData.length === 0) {
|
||||
message.error('该条消息暂不支持该操作');
|
||||
return;
|
||||
}
|
||||
exportCsvFile(exportData);
|
||||
}
|
||||
};
|
||||
|
||||
@@ -79,7 +79,8 @@ export function chatExecute(
|
||||
queryText: string,
|
||||
chatId: number,
|
||||
parseInfo: ChatContextType,
|
||||
agentId?: number
|
||||
agentId?: number,
|
||||
streamingResult?:boolean
|
||||
) {
|
||||
return axios.post<MsgDataType>(`${prefix}/chat/query/execute`, {
|
||||
queryText,
|
||||
@@ -87,6 +88,15 @@ export function chatExecute(
|
||||
chatId: chatId || DEFAULT_CHAT_ID,
|
||||
queryId: parseInfo.queryId,
|
||||
parseId: parseInfo.id,
|
||||
streamingResult:streamingResult
|
||||
});
|
||||
}
|
||||
|
||||
export function getExecuteSummary(
|
||||
queryId: number
|
||||
) {
|
||||
return axios.post<MsgDataType>(`${prefix}/chat/query/getExecuteSummary`, {
|
||||
queryId: queryId,
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user