[improvement](python) LLM related services support Java service invocation (#484)

chat/core/pom.xml

@@ -104,6 +104,19 @@
             <version>${mockito-inline.version}</version>
             <scope>test</scope>
         </dependency>
+        <!--langchain4j-->
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-open-ai</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-chroma</artifactId>
+        </dependency>
 
     </dependencies>
 

chat/core/src/main/java/com/tencent/supersonic/chat/mapper/EmbeddingMatchStrategy.java

@@ -4,10 +4,11 @@ import com.google.common.collect.Lists;
 import com.tencent.supersonic.chat.api.pojo.QueryContext;
 import com.tencent.supersonic.chat.config.OptimizationConfig;
 import com.tencent.supersonic.common.pojo.Constants;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
+import com.tencent.supersonic.common.util.ComponentFactory;
 import com.tencent.supersonic.common.util.embedding.Retrieval;
 import com.tencent.supersonic.common.util.embedding.RetrieveQuery;
 import com.tencent.supersonic.common.util.embedding.RetrieveQueryResult;
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
 import com.tencent.supersonic.knowledge.dictionary.EmbeddingResult;
 import com.tencent.supersonic.semantic.model.domain.listener.MetaEmbeddingListener;
 import java.util.Comparator;
@@ -32,8 +33,8 @@ public class EmbeddingMatchStrategy extends BaseMatchStrategy<EmbeddingResult> {
 
     @Autowired
     private OptimizationConfig optimizationConfig;
-    @Autowired
+
-    private EmbeddingUtils embeddingUtils;
+    private S2EmbeddingStore s2EmbeddingStore = ComponentFactory.getS2EmbeddingStore();
 
     @Override
     public boolean needDelete(EmbeddingResult oneRoundResult, EmbeddingResult existResult) {
@@ -83,7 +84,7 @@ public class EmbeddingMatchStrategy extends BaseMatchStrategy<EmbeddingResult> {
                 .queryEmbeddings(null)
                 .build();
         // step2. retrieveQuery by detectSegment
-        List<RetrieveQueryResult> retrieveQueryResults = embeddingUtils.retrieveQuery(
+        List<RetrieveQueryResult> retrieveQueryResults = s2EmbeddingStore.retrieveQuery(
                 MetaEmbeddingListener.COLLECTION_NAME, retrieveQuery, embeddingNumber);
 
         if (CollectionUtils.isEmpty(retrieveQueryResults)) {
@@ -97,7 +98,7 @@ public class EmbeddingMatchStrategy extends BaseMatchStrategy<EmbeddingResult> {
                         retrievals.removeIf(retrieval -> retrieval.getDistance() > distance.doubleValue());
                         if (CollectionUtils.isNotEmpty(detectModelIds)) {
                             retrievals.removeIf(retrieval -> {
-                                String modelIdStr = retrieval.getMetadata().get("modelId");
+                                String modelIdStr = retrieval.getMetadata().get("modelId").toString();
                                 if (StringUtils.isBlank(modelIdStr)) {
                                     return true;
                                 }

chat/core/src/main/java/com/tencent/supersonic/chat/parser/EmbedLLMProxy.java

@@ -0,0 +1,84 @@
+package com.tencent.supersonic.chat.parser;
+
+import com.tencent.supersonic.chat.config.OptimizationConfig;
+import com.tencent.supersonic.chat.parser.plugin.function.FunctionCallPromptGenerator;
+import com.tencent.supersonic.chat.parser.sql.llm.prompt.OutputFormat;
+import com.tencent.supersonic.chat.parser.sql.llm.prompt.SqlExampleLoader;
+import com.tencent.supersonic.chat.parser.sql.llm.prompt.SqlPromptGenerator;
+import com.tencent.supersonic.chat.parser.plugin.function.FunctionReq;
+import com.tencent.supersonic.chat.parser.plugin.function.FunctionResp;
+import com.tencent.supersonic.chat.query.llm.s2sql.LLMReq;
+import com.tencent.supersonic.chat.query.llm.s2sql.LLMReq.ElementValue;
+import com.tencent.supersonic.chat.query.llm.s2sql.LLMResp;
+import com.tencent.supersonic.common.util.ContextUtils;
+import com.tencent.supersonic.common.util.JsonUtil;
+import dev.langchain4j.data.message.AiMessage;
+import dev.langchain4j.model.chat.ChatLanguageModel;
+import dev.langchain4j.model.input.Prompt;
+import dev.langchain4j.model.input.PromptTemplate;
+import dev.langchain4j.model.output.Response;
+import lombok.extern.slf4j.Slf4j;
+
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+@Slf4j
+public class EmbedLLMProxy implements LLMProxy {
+
+    public LLMResp query2sql(LLMReq llmReq, String modelClusterKey) {
+
+        ChatLanguageModel chatLanguageModel = ContextUtils.getBean(ChatLanguageModel.class);
+
+        SqlExampleLoader sqlExampleLoader = ContextUtils.getBean(SqlExampleLoader.class);
+
+        OptimizationConfig config = ContextUtils.getBean(OptimizationConfig.class);
+
+        List<Map<String, String>> sqlExamples = sqlExampleLoader.retrieverSqlExamples(llmReq.getQueryText(),
+                config.getText2sqlCollectionName(), config.getText2sqlFewShotsNum());
+
+        String queryText = llmReq.getQueryText();
+        String modelName = llmReq.getSchema().getModelName();
+        List<String> fieldNameList = llmReq.getSchema().getFieldNameList();
+        List<ElementValue> linking = llmReq.getLinking();
+
+        SqlPromptGenerator sqlPromptGenerator = ContextUtils.getBean(SqlPromptGenerator.class);
+        String linkingPromptStr = sqlPromptGenerator.generateSchemaLinkingPrompt(queryText, modelName, fieldNameList,
+                linking, sqlExamples);
+
+        Prompt linkingPrompt = PromptTemplate.from(JsonUtil.toString(linkingPromptStr)).apply(new HashMap<>());
+        Response<AiMessage> linkingResult = chatLanguageModel.generate(linkingPrompt.toSystemMessage());
+
+        String schemaLinkStr = OutputFormat.schemaLinkParse(linkingResult.content().text());
+
+        String generateSqlPrompt = sqlPromptGenerator.generateSqlPrompt(queryText, modelName, schemaLinkStr,
+                llmReq.getCurrentDate(), sqlExamples);
+
+        Prompt sqlPrompt = PromptTemplate.from(JsonUtil.toString(generateSqlPrompt)).apply(new HashMap<>());
+        Response<AiMessage> sqlResult = chatLanguageModel.generate(sqlPrompt.toSystemMessage());
+
+        LLMResp result = new LLMResp();
+        result.setQuery(queryText);
+        result.setSchemaLinkingOutput(linkingPromptStr);
+        result.setSchemaLinkStr(schemaLinkStr);
+        result.setModelName(modelName);
+        result.setSqlOutput(sqlResult.content().text());
+        return result;
+    }
+
+    @Override
+    public FunctionResp requestFunction(FunctionReq functionReq) {
+
+        FunctionCallPromptGenerator promptGenerator = ContextUtils.getBean(FunctionCallPromptGenerator.class);
+
+        String functionCallPrompt = promptGenerator.generateFunctionCallPrompt(functionReq.getQueryText(),
+                functionReq.getPluginConfigs());
+
+        ChatLanguageModel chatLanguageModel = ContextUtils.getBean(ChatLanguageModel.class);
+
+        String functionSelect = chatLanguageModel.generate(functionCallPrompt);
+
+        return OutputFormat.functionCallParse(functionSelect);
+    }
+
+}

chat/core/src/main/java/com/tencent/supersonic/chat/parser/plugin/function/FunctionCallPromptGenerator.java

@@ -0,0 +1,44 @@
+package com.tencent.supersonic.chat.parser.plugin.function;
+
+import com.tencent.supersonic.chat.parser.sql.llm.prompt.InputFormat;
+import com.tencent.supersonic.chat.plugin.PluginParseConfig;
+import java.util.List;
+import java.util.stream.Collectors;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+@Component
+@Slf4j
+public class FunctionCallPromptGenerator {
+
+    public String generateFunctionCallPrompt(String queryText, List<PluginParseConfig> toolConfigList) {
+        List<String> toolExplainList = toolConfigList.stream()
+                .map(this::constructPluginPrompt)
+                .collect(Collectors.toList());
+        String functionList = String.join(InputFormat.SEPERATOR, toolExplainList);
+        return constructTaskPrompt(queryText, functionList);
+    }
+
+    public String constructPluginPrompt(PluginParseConfig parseConfig) {
+        String toolName = parseConfig.getName();
+        String toolDescription = parseConfig.getDescription();
+        List<String> toolExamples = parseConfig.getExamples();
+
+        StringBuilder prompt = new StringBuilder();
+        prompt.append("【工具名称】\n").append(toolName).append("\n");
+        prompt.append("【工具描述】\n").append(toolDescription).append("\n");
+        prompt.append("【工具适用问题示例】\n");
+        for (String example : toolExamples) {
+            prompt.append(example).append("\n");
+        }
+        return prompt.toString();
+    }
+
+    public String constructTaskPrompt(String queryText, String functionList) {
+        String instruction = String.format("问题为:%s\n请根据问题和工具的描述，选择对应的工具，完成任务。"
+                + "请注意，只能选择1个工具。请一步一步地分析选择工具的原因(每个工具的【工具适用问题示例】是选择的重要参考依据)，"
+                + "并给出最终选择，输出格式为json,key为’分析过程‘, ’选择工具‘", queryText);
+
+        return String.format("工具选择如下:\n\n%s\n\n【任务说明】\n%s", functionList, instruction);
+    }
+}

chat/core/src/main/java/com/tencent/supersonic/chat/parser/sql/llm/prompt/InputFormat.java

@@ -0,0 +1,42 @@
+package com.tencent.supersonic.chat.parser.sql.llm.prompt;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import lombok.extern.slf4j.Slf4j;
+
+@Slf4j
+public class InputFormat {
+
+    public static final String SEPERATOR = "\n\n";
+
+    public static String format(String template, List<String> templateKey,
+            List<Map<String, String>> toFormatList) {
+        List<String> result = new ArrayList<>();
+
+        for (Map<String, String> formatItem : toFormatList) {
+            Map<String, String> retrievalMeta = subDict(formatItem, templateKey);
+            result.add(format(template, retrievalMeta));
+        }
+
+        return String.join(SEPERATOR, result);
+    }
+
+    public static String format(String input, Map<String, String> replacements) {
+        for (Map.Entry<String, String> entry : replacements.entrySet()) {
+            input = input.replace(entry.getKey(), entry.getValue());
+        }
+        return input;
+    }
+
+    private static Map<String, String> subDict(Map<String, String> dict, List<String> keys) {
+        Map<String, String> subDict = new HashMap<>();
+        for (String key : keys) {
+            if (dict.containsKey(key)) {
+                subDict.put(key, dict.get(key));
+            }
+        }
+        return subDict;
+    }
+}

chat/core/src/main/java/com/tencent/supersonic/chat/parser/sql/llm/prompt/OutputFormat.java

@@ -0,0 +1,53 @@
+package com.tencent.supersonic.chat.parser.sql.llm.prompt;
+
+import com.tencent.supersonic.chat.parser.plugin.function.FunctionResp;
+import com.tencent.supersonic.common.util.JsonUtil;
+import java.util.Map;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+import lombok.extern.slf4j.Slf4j;
+
+/***
+ * output format
+ */
+@Slf4j
+public class OutputFormat {
+
+    public static final String PATTERN = "\\{[^{}]+\\}";
+
+    public static String schemaLinkParse(String schemaLinkOutput) {
+        try {
+            schemaLinkOutput = schemaLinkOutput.trim();
+            String pattern = "Schema_links:(.*)";
+            Pattern regexPattern = Pattern.compile(pattern, Pattern.DOTALL);
+            Matcher matcher = regexPattern.matcher(schemaLinkOutput);
+            if (matcher.find()) {
+                schemaLinkOutput = matcher.group(1).trim();
+            } else {
+                schemaLinkOutput = null;
+            }
+        } catch (Exception e) {
+            log.error("", e);
+            schemaLinkOutput = null;
+        }
+        return schemaLinkOutput;
+    }
+
+    public static FunctionResp functionCallParse(String llmOutput) {
+        try {
+            String[] findResult = llmOutput.split(PATTERN);
+            String result = findResult[0].trim();
+
+            Map<String, String> resultDict = JsonUtil.toMap(result, String.class, String.class);
+            log.info("result:{},resultDict:{}", result, resultDict);
+
+            String selection = resultDict.get("选择工具");
+            FunctionResp resp = new FunctionResp();
+            resp.setToolSelection(selection);
+            return resp;
+        } catch (Exception e) {
+            log.error("", e);
+            return null;
+        }
+    }
+}

chat/core/src/main/java/com/tencent/supersonic/chat/parser/sql/llm/prompt/SqlExample.java

@@ -0,0 +1,32 @@
+package com.tencent.supersonic.chat.parser.sql.llm.prompt;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import lombok.Data;
+
+@Data
+public class SqlExample {
+
+    @JsonProperty("currentDate")
+    private String currentDate;
+
+    @JsonProperty("tableName")
+    private String tableName;
+
+    @JsonProperty("fieldsList")
+    private String fieldsList;
+
+    @JsonProperty("question")
+    private String question;
+
+    @JsonProperty("priorSchemaLinks")
+    private String priorSchemaLinks;
+
+    @JsonProperty("analysis")
+    private String analysis;
+
+    @JsonProperty("schemaLinks")
+    private String schemaLinks;
+
+    @JsonProperty("sql")
+    private String sql;
+}

chat/core/src/main/java/com/tencent/supersonic/chat/parser/sql/llm/prompt/SqlExampleLoader.java

@@ -0,0 +1,76 @@
+package com.tencent.supersonic.chat.parser.sql.llm.prompt;
+
+
+import com.fasterxml.jackson.core.type.TypeReference;
+import com.tencent.supersonic.common.util.ComponentFactory;
+import com.tencent.supersonic.common.util.JsonUtil;
+import com.tencent.supersonic.common.util.embedding.EmbeddingQuery;
+import com.tencent.supersonic.common.util.embedding.Retrieval;
+import com.tencent.supersonic.common.util.embedding.RetrieveQuery;
+import com.tencent.supersonic.common.util.embedding.RetrieveQueryResult;
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
+import java.io.IOException;
+import java.io.InputStream;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+import java.util.stream.Collectors;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.collections4.CollectionUtils;
+import org.springframework.core.io.ClassPathResource;
+import org.springframework.stereotype.Component;
+
+@Slf4j
+@Component
+public class SqlExampleLoader {
+
+    private static final String EXAMPLE_JSON_FILE = "example.json";
+
+    private S2EmbeddingStore s2EmbeddingStore = ComponentFactory.getS2EmbeddingStore();
+    private TypeReference<List<SqlExample>> valueTypeRef = new TypeReference<List<SqlExample>>() {
+    };
+
+    public List<SqlExample> getSqlExamples() throws IOException {
+        ClassPathResource resource = new ClassPathResource(EXAMPLE_JSON_FILE);
+        InputStream inputStream = resource.getInputStream();
+        return JsonUtil.INSTANCE.getObjectMapper().readValue(inputStream, valueTypeRef);
+    }
+
+    public void addEmbeddingStore(List<SqlExample> sqlExamples, String collectionName) {
+        List<EmbeddingQuery> queries = new ArrayList<>();
+        for (int i = 0; i < sqlExamples.size(); i++) {
+            SqlExample sqlExample = sqlExamples.get(i);
+            String question = sqlExample.getQuestion();
+            Map<String, Object> metaDataMap = JsonUtil.toMap(JsonUtil.toString(sqlExample), String.class, Object.class);
+            EmbeddingQuery embeddingQuery = new EmbeddingQuery();
+            embeddingQuery.setQueryId(String.valueOf(i));
+            embeddingQuery.setQuery(question);
+            embeddingQuery.setMetadata(metaDataMap);
+            queries.add(embeddingQuery);
+        }
+        s2EmbeddingStore.addQuery(collectionName, queries);
+    }
+
+    public List<Map<String, String>> retrieverSqlExamples(String queryText, String collectionName, int maxResults) {
+
+        RetrieveQuery retrieveQuery = RetrieveQuery.builder().queryTextsList(Collections.singletonList(queryText))
+                .queryEmbeddings(null).build();
+
+        List<RetrieveQueryResult> resultList = s2EmbeddingStore.retrieveQuery(collectionName, retrieveQuery,
+                maxResults);
+        List<Map<String, String>> result = new ArrayList<>();
+        if (CollectionUtils.isEmpty(resultList)) {
+            return result;
+        }
+        for (Retrieval retrieval : resultList.get(0).getRetrieval()) {
+            if (Objects.nonNull(retrieval.getMetadata()) && !retrieval.getMetadata().isEmpty()) {
+                Map<String, String> convertedMap = retrieval.getMetadata().entrySet().stream()
+                        .collect(Collectors.toMap(Map.Entry::getKey, entry -> String.valueOf(entry.getValue())));
+                result.add(convertedMap);
+            }
+        }
+        return result;
+    }
+}

chat/core/src/main/java/com/tencent/supersonic/chat/parser/sql/llm/prompt/SqlPromptGenerator.java

@@ -0,0 +1,65 @@
+package com.tencent.supersonic.chat.parser.sql.llm.prompt;
+
+import com.tencent.supersonic.chat.query.llm.s2sql.LLMReq.ElementValue;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+@Component
+@Slf4j
+public class SqlPromptGenerator {
+
+    public String generateSchemaLinkingPrompt(String question, String modelName, List<String> fieldsList,
+            List<ElementValue> priorSchemaLinks, List<Map<String, String>> exampleList) {
+
+        String exampleTemplate = "Table {tableName}, columns = {fieldsList}, prior_schema_links = {priorSchemaLinks}\n"
+                + "问题:{question}\n分析:{analysis} 所以Schema_links是:\nSchema_links:{schemaLinks}";
+
+        List<String> exampleKeys = Arrays.asList("tableName", "fieldsList", "priorSchemaLinks", "question", "analysis",
+                "schemaLinks");
+
+        String schemaLinkingPrompt = InputFormat.format(exampleTemplate, exampleKeys, exampleList);
+
+        String newCaseTemplate = "Table {tableName}, columns = {fieldsList}, prior_schema_links = {priorSchemaLinks}\n"
+                + "问题:{question}\n分析: 让我们一步一步地思考。";
+
+        String newCasePrompt = newCaseTemplate.replace("{tableName}", modelName)
+                .replace("{fieldsList}", fieldsList.toString())
+                .replace("{priorSchemaLinks}", getPriorSchemaLinks(priorSchemaLinks))
+                .replace("{question}", question);
+
+        String instruction = "# 根据数据库的表结构,参考先验信息,找出为每个问题生成SQL查询语句的schema_links";
+        return instruction + InputFormat.SEPERATOR + schemaLinkingPrompt + InputFormat.SEPERATOR + newCasePrompt;
+    }
+
+    private String getPriorSchemaLinks(List<ElementValue> priorSchemaLinks) {
+        return priorSchemaLinks.stream()
+                .map(elementValue -> "'" + elementValue.getFieldName() + "'->" + elementValue.getFieldValue())
+                .collect(Collectors.joining(",", "[", "]"));
+    }
+
+    public String generateSqlPrompt(String question, String modelName, String schemaLinkStr, String dataDate,
+            List<Map<String, String>> exampleList) {
+
+        List<String> exampleKeys = Arrays.asList("question", "currentDate", "tableName", "schemaLinks", "sql");
+        String exampleTemplate = "问题:{question}\nCurrent_date:{currentDate}\nTable {tableName}\n"
+                + "Schema_links:{schemaLinks}\nSQL:{sql}";
+
+        String sqlExamplePrompt = InputFormat.format(exampleTemplate, exampleKeys, exampleList);
+
+        String newCaseTemplate = "问题:{question}\nCurrent_date:{currentDate}\nTable {tableName}\n"
+                + "Schema_links:{schemaLinks}\nSQL:";
+
+        String newCasePrompt = newCaseTemplate.replace("{question}", question)
+                .replace("{currentDate}", dataDate)
+                .replace("{tableName}", modelName)
+                .replace("{schemaLinks}", schemaLinkStr);
+
+        String instruction = "# 根据schema_links为每个问题生成SQL查询语句";
+        return instruction + InputFormat.SEPERATOR + sqlExamplePrompt + InputFormat.SEPERATOR + newCasePrompt;
+    }
+
+}

chat/core/src/main/java/com/tencent/supersonic/chat/plugin/PluginManager.java

@@ -19,12 +19,13 @@ import com.tencent.supersonic.chat.query.plugin.WebBase;
 import com.tencent.supersonic.chat.service.AgentService;
 import com.tencent.supersonic.chat.service.PluginService;
 import com.tencent.supersonic.common.config.EmbeddingConfig;
+import com.tencent.supersonic.common.util.ComponentFactory;
 import com.tencent.supersonic.common.util.ContextUtils;
 import com.tencent.supersonic.common.util.embedding.EmbeddingQuery;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
 import com.tencent.supersonic.common.util.embedding.Retrieval;
 import com.tencent.supersonic.common.util.embedding.RetrieveQuery;
 import com.tencent.supersonic.common.util.embedding.RetrieveQueryResult;
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
 import java.util.ArrayList;
 import java.util.Collection;
 import java.util.Collections;
@@ -39,7 +40,6 @@ import org.apache.commons.collections.CollectionUtils;
 import org.apache.commons.lang3.tuple.Pair;
 import org.springframework.context.event.EventListener;
 import org.springframework.stereotype.Component;
-import org.springframework.web.client.RestTemplate;
 
 @Slf4j
 @Component
@@ -47,14 +47,10 @@ public class PluginManager {
 
     private EmbeddingConfig embeddingConfig;
 
-    private RestTemplate restTemplate;
+    private S2EmbeddingStore s2EmbeddingStore = ComponentFactory.getS2EmbeddingStore();
 
-    private EmbeddingUtils embeddingUtils;
+    public PluginManager(EmbeddingConfig embeddingConfig) {
-
-    public PluginManager(EmbeddingConfig embeddingConfig, RestTemplate restTemplate, EmbeddingUtils embeddingUtils) {
         this.embeddingConfig = embeddingConfig;
-        this.restTemplate = restTemplate;
-        this.embeddingUtils = embeddingUtils;
     }
 
     public static List<Plugin> getPluginAgentCanSupport(Integer agentId) {
@@ -133,7 +129,7 @@ public class PluginManager {
             embeddingQuery.setQueryId(id);
             queries.add(embeddingQuery);
         }
-        embeddingUtils.deleteQuery(presetCollection, queries);
+        s2EmbeddingStore.deleteQuery(presetCollection, queries);
     }
 
     public void requestEmbeddingPluginAdd(List<EmbeddingQuery> queries) {
@@ -141,7 +137,7 @@ public class PluginManager {
             return;
         }
         String presetCollection = embeddingConfig.getPresetCollection();
-        embeddingUtils.addQuery(presetCollection, queries);
+        s2EmbeddingStore.addQuery(presetCollection, queries);
     }
 
     public void requestEmbeddingPluginAddALL(List<Plugin> plugins) {
@@ -150,13 +146,12 @@ public class PluginManager {
 
     public RetrieveQueryResult recognize(String embeddingText) {
 
-        EmbeddingUtils embeddingUtils = ContextUtils.getBean(EmbeddingUtils.class);
 
         RetrieveQuery retrieveQuery = RetrieveQuery.builder()
                 .queryTextsList(Collections.singletonList(embeddingText))
                 .build();
 
-        List<RetrieveQueryResult> resultList = embeddingUtils.retrieveQuery(embeddingConfig.getPresetCollection(),
+        List<RetrieveQueryResult> resultList = s2EmbeddingStore.retrieveQuery(embeddingConfig.getPresetCollection(),
                 retrieveQuery, embeddingConfig.getNResult());
 
 

chat/core/src/main/java/com/tencent/supersonic/chat/query/SimilarMetricQueryResponder.java

@@ -7,13 +7,12 @@ import com.tencent.supersonic.chat.api.pojo.SemanticParseInfo;
 import com.tencent.supersonic.chat.api.pojo.request.ExecuteQueryReq;
 import com.tencent.supersonic.chat.api.pojo.response.QueryResult;
 import com.tencent.supersonic.common.pojo.QueryType;
-import com.tencent.supersonic.common.util.ContextUtils;
+import com.tencent.supersonic.common.util.ComponentFactory;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
 import com.tencent.supersonic.common.util.embedding.Retrieval;
 import com.tencent.supersonic.common.util.embedding.RetrieveQuery;
 import com.tencent.supersonic.common.util.embedding.RetrieveQueryResult;
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
 import com.tencent.supersonic.semantic.model.domain.listener.MetaEmbeddingListener;
-import org.springframework.util.CollectionUtils;
 import java.util.Collections;
 import java.util.Comparator;
 import java.util.HashMap;
@@ -21,6 +20,7 @@ import java.util.List;
 import java.util.Map;
 import java.util.Set;
 import java.util.stream.Collectors;
+import org.springframework.util.CollectionUtils;
 
 /**
  * SimilarMetricQueryResponder fills recommended metrics based on embedding similarity.
@@ -29,6 +29,8 @@ public class SimilarMetricQueryResponder implements QueryResponder {
 
     private static final int METRIC_RECOMMEND_SIZE = 5;
 
+    private S2EmbeddingStore s2EmbeddingStore = ComponentFactory.getS2EmbeddingStore();
+
     @Override
     public void fillInfo(QueryResult queryResult, SemanticParseInfo semanticParseInfo, ExecuteQueryReq queryReq) {
         fillSimilarMetric(queryResult.getChatContext());
@@ -46,8 +48,7 @@ public class SimilarMetricQueryResponder implements QueryResponder {
         filterCondition.put("type", SchemaElementType.METRIC.name());
         RetrieveQuery retrieveQuery = RetrieveQuery.builder().queryTextsList(metricNames)
                 .filterCondition(filterCondition).queryEmbeddings(null).build();
-        EmbeddingUtils embeddingUtils = ContextUtils.getBean(EmbeddingUtils.class);
+        List<RetrieveQueryResult> retrieveQueryResults = s2EmbeddingStore.retrieveQuery(
-        List<RetrieveQueryResult> retrieveQueryResults = embeddingUtils.retrieveQuery(
                 MetaEmbeddingListener.COLLECTION_NAME, retrieveQuery, METRIC_RECOMMEND_SIZE + 1);
         if (CollectionUtils.isEmpty(retrieveQueryResults)) {
             return;
@@ -66,7 +67,8 @@ public class SimilarMetricQueryResponder implements QueryResponder {
                 SchemaElement schemaElement = JSONObject.parseObject(JSONObject.toJSONString(retrieval.getMetadata()),
                         SchemaElement.class);
                 if (retrieval.getMetadata().containsKey("modelId")) {
-                    schemaElement.setModel(Long.parseLong(retrieval.getMetadata().get("modelId")));
+                    String modelId = retrieval.getMetadata().get("modelId").toString();
+                    schemaElement.setModel(Long.parseLong(modelId));
                 }
                 schemaElement.setOrder(++metricOrder);
                 parseInfo.getMetrics().add(schemaElement);

chat/core/src/main/java/com/tencent/supersonic/chat/query/llm/analytics/MetricAnalyzeQuery.java

@@ -1,6 +1,5 @@
 package com.tencent.supersonic.chat.query.llm.analytics;
 
-import com.alibaba.fastjson.JSONObject;
 import com.google.common.collect.Lists;
 import com.tencent.supersonic.auth.api.authentication.pojo.User;
 import com.tencent.supersonic.chat.api.component.SemanticInterpreter;
@@ -14,13 +13,11 @@ import com.tencent.supersonic.chat.query.QueryManager;
 import com.tencent.supersonic.chat.query.llm.LLMSemanticQuery;
 import com.tencent.supersonic.chat.utils.ComponentFactory;
 import com.tencent.supersonic.chat.utils.QueryReqBuilder;
-import com.tencent.supersonic.common.config.EmbeddingConfig;
 import com.tencent.supersonic.common.pojo.Aggregator;
 import com.tencent.supersonic.common.pojo.QueryColumn;
 import com.tencent.supersonic.common.pojo.QueryType;
 import com.tencent.supersonic.common.pojo.enums.AggOperatorEnum;
 import com.tencent.supersonic.common.util.ContextUtils;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
 import com.tencent.supersonic.semantic.api.model.response.QueryResultWithSchemaResp;
 import com.tencent.supersonic.semantic.api.query.request.QueryStructReq;
 import java.util.HashMap;
@@ -31,8 +28,6 @@ import java.util.stream.Collectors;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.calcite.sql.parser.SqlParseException;
 import org.apache.commons.lang3.StringUtils;
-import org.springframework.http.HttpMethod;
-import org.springframework.http.ResponseEntity;
 import org.springframework.stereotype.Component;
 import org.springframework.util.CollectionUtils;
 
@@ -43,7 +38,6 @@ public class MetricAnalyzeQuery extends LLMSemanticQuery {
 
     public static final String QUERY_MODE = "METRIC_INTERPRET";
 
-
     public MetricAnalyzeQuery() {
         QueryManager.register(this);
     }
@@ -151,23 +145,7 @@ public class MetricAnalyzeQuery extends LLMSemanticQuery {
     }
 
     public String fetchInterpret(String queryText, String dataText) {
-        LLMAnswerReq lLmAnswerReq = new LLMAnswerReq();
+        return "";
-        lLmAnswerReq.setQueryText(queryText);
-        lLmAnswerReq.setPluginOutput(dataText);
-        EmbeddingUtils embeddingUtils = ContextUtils.getBean(EmbeddingUtils.class);
-        EmbeddingConfig embeddingConfig = ContextUtils.getBean(EmbeddingConfig.class);
-        String metricAnalyzeQueryCollection = embeddingConfig.getMetricAnalyzeQueryCollection();
-
-        String url = String.format("%s/retrieve_query?collection_name=%s", embeddingConfig.getUrl(),
-                metricAnalyzeQueryCollection);
-
-        ResponseEntity<String> responseEntity = embeddingUtils.doRequest(url, JSONObject.toJSONString(lLmAnswerReq),
-                HttpMethod.POST);
-        LLMAnswerResp lLmAnswerResp = JSONObject.parseObject(responseEntity.getBody(), LLMAnswerResp.class);
-        if (lLmAnswerResp != null) {
-            return lLmAnswerResp.getAssistantMessage();
-        }
-        return null;
     }
 
 }

chat/core/src/main/java/com/tencent/supersonic/chat/utils/ComponentFactory.java

@@ -8,11 +8,11 @@ import com.tencent.supersonic.chat.parser.LLMProxy;
 import com.tencent.supersonic.chat.parser.sql.llm.ModelResolver;
 import com.tencent.supersonic.chat.processor.ParseResultProcessor;
 import com.tencent.supersonic.chat.query.QueryResponder;
-import org.apache.commons.collections.CollectionUtils;
-import org.springframework.core.io.support.SpringFactoriesLoader;
 import java.util.ArrayList;
 import java.util.List;
 import java.util.Objects;
+import org.apache.commons.collections.CollectionUtils;
+import org.springframework.core.io.support.SpringFactoriesLoader;
 
 public class ComponentFactory {
 

chat/core/src/main/java/com/tencent/supersonic/chat/utils/SolvedQueryManager.java

@@ -4,11 +4,12 @@ import com.google.common.collect.Lists;
 import com.tencent.supersonic.chat.api.pojo.request.SolvedQueryReq;
 import com.tencent.supersonic.chat.api.pojo.response.SolvedQueryRecallResp;
 import com.tencent.supersonic.common.config.EmbeddingConfig;
+import com.tencent.supersonic.common.util.ComponentFactory;
 import com.tencent.supersonic.common.util.embedding.EmbeddingQuery;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
 import com.tencent.supersonic.common.util.embedding.Retrieval;
 import com.tencent.supersonic.common.util.embedding.RetrieveQuery;
 import com.tencent.supersonic.common.util.embedding.RetrieveQueryResult;
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
 import java.net.URI;
 import java.util.HashMap;
 import java.util.HashSet;
@@ -36,11 +37,11 @@ public class SolvedQueryManager {
 
     private EmbeddingConfig embeddingConfig;
 
-    private EmbeddingUtils embeddingUtils;
+    private S2EmbeddingStore s2EmbeddingStore = ComponentFactory.getS2EmbeddingStore();
 
-    public SolvedQueryManager(EmbeddingConfig embeddingConfig, EmbeddingUtils embeddingUtils) {
+
+    public SolvedQueryManager(EmbeddingConfig embeddingConfig) {
         this.embeddingConfig = embeddingConfig;
-        this.embeddingUtils = embeddingUtils;
     }
 
     public void saveSolvedQuery(SolvedQueryReq solvedQueryReq) {
@@ -54,12 +55,12 @@ public class SolvedQueryManager {
             embeddingQuery.setQueryId(uniqueId);
             embeddingQuery.setQuery(queryText);
 
-            Map<String, String> metaData = new HashMap<>();
+            Map<String, Object> metaData = new HashMap<>();
-            metaData.put("modelId", String.valueOf(solvedQueryReq.getModelId()));
+            metaData.put("modelId", (solvedQueryReq.getModelId()));
-            metaData.put("agentId", String.valueOf(solvedQueryReq.getAgentId()));
+            metaData.put("agentId", solvedQueryReq.getAgentId());
             embeddingQuery.setMetadata(metaData);
             String solvedQueryCollection = embeddingConfig.getSolvedQueryCollection();
-            embeddingUtils.addQuery(solvedQueryCollection, Lists.newArrayList(embeddingQuery));
+            s2EmbeddingStore.addQuery(solvedQueryCollection, Lists.newArrayList(embeddingQuery));
         } catch (Exception e) {
             log.warn("save history question to embedding failed, queryText:{}", queryText, e);
         }
@@ -80,7 +81,7 @@ public class SolvedQueryManager {
                     .queryTextsList(Lists.newArrayList(queryText))
                     .filterCondition(filterCondition)
                     .build();
-            List<RetrieveQueryResult> resultList = embeddingUtils.retrieveQuery(solvedQueryCollection, retrieveQuery,
+            List<RetrieveQueryResult> resultList = s2EmbeddingStore.retrieveQuery(solvedQueryCollection, retrieveQuery,
                     solvedQueryResultNum);
 
             log.info("[embedding] recognize result body:{}", resultList);

common/pom.xml

@@ -161,6 +161,20 @@
             <artifactId>spring-boot-starter-web</artifactId>
         </dependency>
 
+        <!--langchain4j-->
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-open-ai</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-chroma</artifactId>
+        </dependency>
+
     </dependencies>
 
 </project>

common/src/main/java/com/tencent/supersonic/common/config/EmbeddingConfig.java

@@ -29,6 +29,7 @@ public class EmbeddingConfig {
     @Value("${embedding.metric.analyzeQuery.collection:solved_query_collection}")
     private String metricAnalyzeQueryCollection;
 
-
+    @Value("${embedding.metric.analyzeQuery.nResult:5}")
+    private int metricAnalyzeQueryResultNum;
 
 }

common/src/main/java/com/tencent/supersonic/common/util/ComponentFactory.java

@@ -0,0 +1,23 @@
+package com.tencent.supersonic.common.util;
+
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
+import java.util.Objects;
+import org.springframework.core.io.support.SpringFactoriesLoader;
+
+public class ComponentFactory {
+
+    private static S2EmbeddingStore s2EmbeddingStore;
+
+    public static S2EmbeddingStore getS2EmbeddingStore() {
+        if (Objects.isNull(s2EmbeddingStore)) {
+            s2EmbeddingStore = init(S2EmbeddingStore.class);
+        }
+        return s2EmbeddingStore;
+    }
+
+    private static <T> T init(Class<T> factoryType) {
+        return SpringFactoriesLoader.loadFactories(factoryType,
+                Thread.currentThread().getContextClassLoader()).get(0);
+    }
+
+}

common/src/main/java/com/tencent/supersonic/common/util/embedding/EmbeddingQuery.java

@@ -13,7 +13,7 @@ public class EmbeddingQuery {
 
     private String query;
 
-    private Map<String, String> metadata;
+    private Map<String, Object> metadata;
 
     private List<Double> queryEmbedding;
 

common/src/main/java/com/tencent/supersonic/common/util/embedding/InMemoryS2EmbeddingStore.java

@@ -0,0 +1,83 @@
+package com.tencent.supersonic.common.util.embedding;
+
+import com.tencent.supersonic.common.util.ContextUtils;
+import dev.langchain4j.data.embedding.Embedding;
+import dev.langchain4j.model.embedding.EmbeddingModel;
+import dev.langchain4j.store.embedding.EmbeddingMatch;
+import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+import java.util.concurrent.ConcurrentHashMap;
+import lombok.extern.slf4j.Slf4j;
+
+@Slf4j
+public class InMemoryS2EmbeddingStore implements S2EmbeddingStore {
+
+    private static Map<String, InMemoryEmbeddingStore<EmbeddingQuery>> collectionNameToStore =
+            new ConcurrentHashMap<>();
+
+    @Override
+    public void addCollection(String collectionName) {
+        collectionNameToStore.computeIfAbsent(collectionName, k -> new InMemoryEmbeddingStore());
+    }
+
+    @Override
+    public void addQuery(String collectionName, List<EmbeddingQuery> queries) {
+        InMemoryEmbeddingStore<EmbeddingQuery> embeddingStore = getEmbeddingStore(collectionName);
+        EmbeddingModel embeddingModel = ContextUtils.getBean(EmbeddingModel.class);
+        for (EmbeddingQuery query : queries) {
+            String question = query.getQuery();
+            Embedding embedding = embeddingModel.embed(question).content();
+            embeddingStore.add(query.getQueryId(), embedding, query);
+        }
+    }
+
+    private InMemoryEmbeddingStore<EmbeddingQuery> getEmbeddingStore(String collectionName) {
+        InMemoryEmbeddingStore<EmbeddingQuery> embeddingStore = collectionNameToStore.get(collectionName);
+        if (Objects.isNull(embeddingStore)) {
+            synchronized (InMemoryS2EmbeddingStore.class) {
+                addCollection(collectionName);
+                embeddingStore = collectionNameToStore.get(collectionName);
+            }
+
+        }
+        return embeddingStore;
+    }
+
+    @Override
+    public void deleteQuery(String collectionName, List<EmbeddingQuery> queries) {
+        //not support in InMemoryEmbeddingStore
+    }
+
+    @Override
+    public List<RetrieveQueryResult> retrieveQuery(String collectionName, RetrieveQuery retrieveQuery, int num) {
+        InMemoryEmbeddingStore<EmbeddingQuery> embeddingStore = getEmbeddingStore(collectionName);
+        EmbeddingModel embeddingModel = ContextUtils.getBean(EmbeddingModel.class);
+
+        List<RetrieveQueryResult> results = new ArrayList<>();
+
+        List<String> queryTextsList = retrieveQuery.getQueryTextsList();
+        for (String queryText : queryTextsList) {
+            Embedding embeddedText = embeddingModel.embed(queryText).content();
+            List<EmbeddingMatch<EmbeddingQuery>> relevant = embeddingStore.findRelevant(embeddedText, num);
+
+            RetrieveQueryResult retrieveQueryResult = new RetrieveQueryResult();
+            retrieveQueryResult.setQuery(queryText);
+            List<Retrieval> retrievals = new ArrayList<>();
+            for (EmbeddingMatch<EmbeddingQuery> embeddingMatch : relevant) {
+                Retrieval retrieval = new Retrieval();
+                retrieval.setDistance(embeddingMatch.score());
+                retrieval.setId(embeddingMatch.embeddingId());
+                retrieval.setQuery(embeddingMatch.embedded().getQuery());
+                retrieval.setMetadata(embeddingMatch.embedded().getMetadata());
+                retrievals.add(retrieval);
+            }
+            retrieveQueryResult.setRetrieval(retrievals);
+            results.add(retrieveQueryResult);
+        }
+
+        return results;
+    }
+}

common/src/main/java/com/tencent/supersonic/common/util/embedding/PythonS2EmbeddingStore.java

@@ -4,6 +4,10 @@ import com.alibaba.fastjson.JSONObject;
 import com.alibaba.fastjson.serializer.SerializerFeature;
 import com.google.common.collect.Lists;
 import com.tencent.supersonic.common.config.EmbeddingConfig;
+import java.net.URI;
+import java.util.List;
+import java.util.Optional;
+import java.util.stream.Collectors;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.core.ParameterizedTypeReference;
@@ -12,18 +16,12 @@ import org.springframework.http.HttpHeaders;
 import org.springframework.http.HttpMethod;
 import org.springframework.http.MediaType;
 import org.springframework.http.ResponseEntity;
-import org.springframework.stereotype.Component;
 import org.springframework.util.CollectionUtils;
 import org.springframework.web.client.RestTemplate;
 import org.springframework.web.util.UriComponentsBuilder;
-import java.net.URI;
-import java.util.List;
-import java.util.Optional;
-import java.util.stream.Collectors;
 
 @Slf4j
-@Component
+public class PythonS2EmbeddingStore implements S2EmbeddingStore {
-public class EmbeddingUtils {
 
     @Autowired
     private EmbeddingConfig embeddingConfig;
@@ -103,6 +101,5 @@ public class EmbeddingUtils {
         }
         return ResponseEntity.of(Optional.empty());
     }
-
 }
 

common/src/main/java/com/tencent/supersonic/common/util/embedding/Retrieval.java

@@ -15,7 +15,7 @@ public class Retrieval {
 
     protected String query;
 
-    protected Map<String, String> metadata;
+    protected Map<String, Object> metadata;
 
     public static Long getLongId(String id) {
         if (StringUtils.isBlank(id)) {

common/src/main/java/com/tencent/supersonic/common/util/embedding/S2EmbeddingStore.java

@@ -0,0 +1,19 @@
+package com.tencent.supersonic.common.util.embedding;
+
+import java.util.List;
+
+/**
+ * Supersonic EmbeddingStore
+ * Added the functionality of adding and querying collection names.
+ */
+public interface S2EmbeddingStore {
+
+    void addCollection(String collectionName);
+
+    void addQuery(String collectionName, List<EmbeddingQuery> queries);
+
+    void deleteQuery(String collectionName, List<EmbeddingQuery> queries);
+
+    List<RetrieveQueryResult> retrieveQuery(String collectionName, RetrieveQuery retrieveQuery, int num);
+
+}

launchers/common/pom.xml

@@ -43,6 +43,16 @@
             <groupId>org.projectlombok</groupId>
             <artifactId>lombok</artifactId>
         </dependency>
+        <!--langchain4j-->
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-spring-boot-starter</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
+        </dependency>
     </dependencies>
 
 </project>

launchers/common/src/main/java/dev/langchain4j/ModelProvider.java

@@ -0,0 +1,8 @@
+package dev.langchain4j;
+
+enum ModelProvider {
+    OPEN_AI,
+    HUGGING_FACE,
+    LOCAL_AI,
+    IN_MEMORY
+}

launchers/common/src/main/java/dev/langchain4j/S2LangChain4jAutoConfiguration.java

@@ -0,0 +1,283 @@
+package dev.langchain4j;
+
+import static dev.langchain4j.ModelProvider.OPEN_AI;
+import static dev.langchain4j.exception.IllegalConfigurationException.illegalConfiguration;
+import static dev.langchain4j.internal.Utils.isNullOrBlank;
+
+import dev.langchain4j.model.chat.ChatLanguageModel;
+import dev.langchain4j.model.embedding.AllMiniLmL6V2EmbeddingModel;
+import dev.langchain4j.model.embedding.EmbeddingModel;
+import dev.langchain4j.model.huggingface.HuggingFaceChatModel;
+import dev.langchain4j.model.huggingface.HuggingFaceEmbeddingModel;
+import dev.langchain4j.model.huggingface.HuggingFaceLanguageModel;
+import dev.langchain4j.model.language.LanguageModel;
+import dev.langchain4j.model.localai.LocalAiChatModel;
+import dev.langchain4j.model.localai.LocalAiEmbeddingModel;
+import dev.langchain4j.model.localai.LocalAiLanguageModel;
+import dev.langchain4j.model.moderation.ModerationModel;
+import dev.langchain4j.model.openai.OpenAiChatModel;
+import dev.langchain4j.model.openai.OpenAiEmbeddingModel;
+import dev.langchain4j.model.openai.OpenAiLanguageModel;
+import dev.langchain4j.model.openai.OpenAiModerationModel;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
+import org.springframework.boot.context.properties.EnableConfigurationProperties;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.context.annotation.Lazy;
+import org.springframework.context.annotation.Primary;
+
+@Configuration
+@EnableConfigurationProperties(LangChain4jProperties.class)
+public class S2LangChain4jAutoConfiguration {
+
+    @Autowired
+    private LangChain4jProperties properties;
+
+    @Bean
+    @Lazy
+    @ConditionalOnMissingBean
+    ChatLanguageModel chatLanguageModel(LangChain4jProperties properties) {
+        if (properties.getChatModel() == null) {
+            throw illegalConfiguration("\n\nPlease define 'langchain4j.chat-model' properties, for example:\n"
+                    + "langchain4j.chat-model.provider = openai\n"
+                    + "langchain4j.chat-model.openai.api-key = sk-...\n");
+        }
+
+        switch (properties.getChatModel().getProvider()) {
+
+            case OPEN_AI:
+                OpenAi openAi = properties.getChatModel().getOpenAi();
+                if (openAi == null || isNullOrBlank(openAi.getApiKey())) {
+                    throw illegalConfiguration("\n\nPlease define 'langchain4j.chat-model.openai.api-key' property");
+                }
+                return OpenAiChatModel.builder()
+                        .baseUrl(openAi.getBaseUrl())
+                        .apiKey(openAi.getApiKey())
+                        .modelName(openAi.getModelName())
+                        .temperature(openAi.getTemperature())
+                        .topP(openAi.getTopP())
+                        .maxTokens(openAi.getMaxTokens())
+                        .presencePenalty(openAi.getPresencePenalty())
+                        .frequencyPenalty(openAi.getFrequencyPenalty())
+                        .timeout(openAi.getTimeout())
+                        .maxRetries(openAi.getMaxRetries())
+                        .logRequests(openAi.getLogRequests())
+                        .logResponses(openAi.getLogResponses())
+                        .build();
+
+            case HUGGING_FACE:
+                HuggingFace huggingFace = properties.getChatModel().getHuggingFace();
+                if (huggingFace == null || isNullOrBlank(huggingFace.getAccessToken())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.chat-model.huggingface.access-token' property");
+                }
+                return HuggingFaceChatModel.builder()
+                        .accessToken(huggingFace.getAccessToken())
+                        .modelId(huggingFace.getModelId())
+                        .timeout(huggingFace.getTimeout())
+                        .temperature(huggingFace.getTemperature())
+                        .maxNewTokens(huggingFace.getMaxNewTokens())
+                        .returnFullText(huggingFace.getReturnFullText())
+                        .waitForModel(huggingFace.getWaitForModel())
+                        .build();
+
+            case LOCAL_AI:
+                LocalAi localAi = properties.getChatModel().getLocalAi();
+                if (localAi == null || isNullOrBlank(localAi.getBaseUrl())) {
+                    throw illegalConfiguration("\n\nPlease define 'langchain4j.chat-model.localai.base-url' property");
+                }
+                if (isNullOrBlank(localAi.getModelName())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.chat-model.localai.model-name' property");
+                }
+                return LocalAiChatModel.builder()
+                        .baseUrl(localAi.getBaseUrl())
+                        .modelName(localAi.getModelName())
+                        .temperature(localAi.getTemperature())
+                        .topP(localAi.getTopP())
+                        .maxTokens(localAi.getMaxTokens())
+                        .timeout(localAi.getTimeout())
+                        .maxRetries(localAi.getMaxRetries())
+                        .logRequests(localAi.getLogRequests())
+                        .logResponses(localAi.getLogResponses())
+                        .build();
+
+            default:
+                throw illegalConfiguration("Unsupported chat model provider: %s",
+                        properties.getChatModel().getProvider());
+        }
+    }
+
+    @Bean
+    @Lazy
+    @ConditionalOnMissingBean
+    LanguageModel languageModel(LangChain4jProperties properties) {
+        if (properties.getLanguageModel() == null) {
+            throw illegalConfiguration("\n\nPlease define 'langchain4j.language-model' properties, for example:\n"
+                    + "langchain4j.language-model.provider = openai\n"
+                    + "langchain4j.language-model.openai.api-key = sk-...\n");
+        }
+
+        switch (properties.getLanguageModel().getProvider()) {
+
+            case OPEN_AI:
+                OpenAi openAi = properties.getLanguageModel().getOpenAi();
+                if (openAi == null || isNullOrBlank(openAi.getApiKey())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.language-model.openai.api-key' property");
+                }
+                return OpenAiLanguageModel.builder()
+                        .apiKey(openAi.getApiKey())
+                        .modelName(openAi.getModelName())
+                        .temperature(openAi.getTemperature())
+                        .timeout(openAi.getTimeout())
+                        .maxRetries(openAi.getMaxRetries())
+                        .logRequests(openAi.getLogRequests())
+                        .logResponses(openAi.getLogResponses())
+                        .build();
+
+            case HUGGING_FACE:
+                HuggingFace huggingFace = properties.getLanguageModel().getHuggingFace();
+                if (huggingFace == null || isNullOrBlank(huggingFace.getAccessToken())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.language-model.huggingface.access-token' property");
+                }
+                return HuggingFaceLanguageModel.builder()
+                        .accessToken(huggingFace.getAccessToken())
+                        .modelId(huggingFace.getModelId())
+                        .timeout(huggingFace.getTimeout())
+                        .temperature(huggingFace.getTemperature())
+                        .maxNewTokens(huggingFace.getMaxNewTokens())
+                        .returnFullText(huggingFace.getReturnFullText())
+                        .waitForModel(huggingFace.getWaitForModel())
+                        .build();
+
+            case LOCAL_AI:
+                LocalAi localAi = properties.getLanguageModel().getLocalAi();
+                if (localAi == null || isNullOrBlank(localAi.getBaseUrl())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.language-model.localai.base-url' property");
+                }
+                if (isNullOrBlank(localAi.getModelName())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.language-model.localai.model-name' property");
+                }
+                return LocalAiLanguageModel.builder()
+                        .baseUrl(localAi.getBaseUrl())
+                        .modelName(localAi.getModelName())
+                        .temperature(localAi.getTemperature())
+                        .topP(localAi.getTopP())
+                        .maxTokens(localAi.getMaxTokens())
+                        .timeout(localAi.getTimeout())
+                        .maxRetries(localAi.getMaxRetries())
+                        .logRequests(localAi.getLogRequests())
+                        .logResponses(localAi.getLogResponses())
+                        .build();
+
+            default:
+                throw illegalConfiguration("Unsupported language model provider: %s",
+                        properties.getLanguageModel().getProvider());
+        }
+    }
+
+    @Bean
+    @Lazy
+    @ConditionalOnMissingBean
+    @Primary
+    EmbeddingModel embeddingModel(LangChain4jProperties properties) {
+        if (properties.getEmbeddingModel() == null || properties.getEmbeddingModel().getProvider() == null) {
+            throw illegalConfiguration("\n\nPlease define 'langchain4j.embedding-model' properties, for example:\n"
+                    + "langchain4j.embedding-model.provider = openai\n"
+                    + "langchain4j.embedding-model.openai.api-key = sk-...\n");
+        }
+
+        switch (properties.getEmbeddingModel().getProvider()) {
+
+            case OPEN_AI:
+                OpenAi openAi = properties.getEmbeddingModel().getOpenAi();
+                if (openAi == null || isNullOrBlank(openAi.getApiKey())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.embedding-model.openai.api-key' property");
+                }
+                return OpenAiEmbeddingModel.builder()
+                        .apiKey(openAi.getApiKey())
+                        .modelName(openAi.getModelName())
+                        .timeout(openAi.getTimeout())
+                        .maxRetries(openAi.getMaxRetries())
+                        .logRequests(openAi.getLogRequests())
+                        .logResponses(openAi.getLogResponses())
+                        .build();
+
+            case HUGGING_FACE:
+                HuggingFace huggingFace = properties.getEmbeddingModel().getHuggingFace();
+                if (huggingFace == null || isNullOrBlank(huggingFace.getAccessToken())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.embedding-model.huggingface.access-token' property");
+                }
+                return HuggingFaceEmbeddingModel.builder()
+                        .accessToken(huggingFace.getAccessToken())
+                        .modelId(huggingFace.getModelId())
+                        .waitForModel(huggingFace.getWaitForModel())
+                        .timeout(huggingFace.getTimeout())
+                        .build();
+
+            case LOCAL_AI:
+                LocalAi localAi = properties.getEmbeddingModel().getLocalAi();
+                if (localAi == null || isNullOrBlank(localAi.getBaseUrl())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.embedding-model.localai.base-url' property");
+                }
+                if (isNullOrBlank(localAi.getModelName())) {
+                    throw illegalConfiguration(
+                            "\n\nPlease define 'langchain4j.embedding-model.localai.model-name' property");
+                }
+                return LocalAiEmbeddingModel.builder()
+                        .baseUrl(localAi.getBaseUrl())
+                        .modelName(localAi.getModelName())
+                        .timeout(localAi.getTimeout())
+                        .maxRetries(localAi.getMaxRetries())
+                        .logRequests(localAi.getLogRequests())
+                        .logResponses(localAi.getLogResponses())
+                        .build();
+            case IN_MEMORY:
+                return new AllMiniLmL6V2EmbeddingModel();
+            default:
+                throw illegalConfiguration("Unsupported embedding model provider: %s",
+                        properties.getEmbeddingModel().getProvider());
+
+
+        }
+    }
+
+    @Bean
+    @Lazy
+    @ConditionalOnMissingBean
+    ModerationModel moderationModel(LangChain4jProperties properties) {
+        if (properties.getModerationModel() == null) {
+            throw illegalConfiguration("\n\nPlease define 'langchain4j.moderation-model' properties, for example:\n"
+                    + "langchain4j.moderation-model.provider = openai\n"
+                    + "langchain4j.moderation-model.openai.api-key = sk-...\n");
+        }
+
+        if (properties.getModerationModel().getProvider() != OPEN_AI) {
+            throw illegalConfiguration("Unsupported moderation model provider: %s",
+                    properties.getModerationModel().getProvider());
+        }
+
+        OpenAi openAi = properties.getModerationModel().getOpenAi();
+        if (openAi == null || isNullOrBlank(openAi.getApiKey())) {
+            throw illegalConfiguration("\n\nPlease define 'langchain4j.moderation-model.openai.api-key' property");
+        }
+
+        return OpenAiModerationModel.builder()
+                .apiKey(openAi.getApiKey())
+                .modelName(openAi.getModelName())
+                .timeout(openAi.getTimeout())
+                .maxRetries(openAi.getMaxRetries())
+                .logRequests(openAi.getLogRequests())
+                .logResponses(openAi.getLogResponses())
+                .build();
+    }
+
+}

launchers/standalone/src/main/java/com/tencent/supersonic/EmbeddingInitListener.java

@@ -0,0 +1,43 @@
+package com.tencent.supersonic;
+
+import com.tencent.supersonic.chat.config.OptimizationConfig;
+import com.tencent.supersonic.chat.parser.sql.llm.prompt.SqlExample;
+import com.tencent.supersonic.chat.parser.sql.llm.prompt.SqlExampleLoader;
+import com.tencent.supersonic.chat.parser.EmbedLLMProxy;
+import com.tencent.supersonic.chat.parser.LLMProxy;
+import com.tencent.supersonic.chat.utils.ComponentFactory;
+import java.util.List;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.CommandLineRunner;
+import org.springframework.core.annotation.Order;
+import org.springframework.stereotype.Component;
+
+@Slf4j
+@Component
+@Order(4)
+public class EmbeddingInitListener implements CommandLineRunner {
+
+    protected LLMProxy llmProxy = ComponentFactory.getLLMProxy();
+    @Autowired
+    private SqlExampleLoader sqlExampleLoader;
+    @Autowired
+    private OptimizationConfig optimizationConfig;
+
+    @Override
+    public void run(String... args) {
+        initSqlExamples();
+    }
+
+    public void initSqlExamples() {
+        try {
+            if (llmProxy instanceof EmbedLLMProxy) {
+                List<SqlExample> sqlExamples = sqlExampleLoader.getSqlExamples();
+                String collectionName = optimizationConfig.getText2sqlCollectionName();
+                sqlExampleLoader.addEmbeddingStore(sqlExamples, collectionName);
+            }
+        } catch (Exception e) {
+            log.error("initSqlExamples error", e);
+        }
+    }
+}

launchers/standalone/src/main/java/com/tencent/supersonic/StandaloneLauncher.java

@@ -1,9 +1,11 @@
 package com.tencent.supersonic;
 
+import dev.langchain4j.S2LangChain4jAutoConfiguration;
 import org.springframework.boot.SpringApplication;
 import org.springframework.boot.autoconfigure.SpringBootApplication;
 import org.springframework.boot.autoconfigure.data.mongo.MongoDataAutoConfiguration;
 import org.springframework.boot.autoconfigure.mongo.MongoAutoConfiguration;
+import org.springframework.context.annotation.Import;
 import org.springframework.scheduling.annotation.EnableAsync;
 import org.springframework.scheduling.annotation.EnableScheduling;
 
@@ -11,6 +13,7 @@ import org.springframework.scheduling.annotation.EnableScheduling;
         exclude = {MongoAutoConfiguration.class, MongoDataAutoConfiguration.class})
 @EnableScheduling
 @EnableAsync
+@Import(S2LangChain4jAutoConfiguration.class)
 public class StandaloneLauncher {
 
     public static void main(String[] args) {

launchers/standalone/src/main/resources/META-INF/spring.factories

@@ -31,7 +31,7 @@ com.tencent.supersonic.chat.processor.ParseResultProcessor=\
     com.tencent.supersonic.chat.processor.RespBuildProcessor
 
 com.tencent.supersonic.chat.parser.LLMProxy=\
-  com.tencent.supersonic.chat.parser.PythonLLMProxy
+  com.tencent.supersonic.chat.parser.EmbedLLMProxy
 
 com.tencent.supersonic.chat.api.component.SemanticInterpreter=\
     com.tencent.supersonic.knowledge.semantic.LocalSemanticInterpreter
@@ -47,3 +47,6 @@ com.tencent.supersonic.auth.api.authentication.adaptor.UserAdaptor=\
 
 com.tencent.supersonic.chat.query.QueryResponder=\
     com.tencent.supersonic.chat.query.SimilarMetricQueryResponder
+
+com.tencent.supersonic.common.util.embedding.S2EmbeddingStore=\
+    com.tencent.supersonic.common.util.embedding.InMemoryS2EmbeddingStore

launchers/standalone/src/main/resources/application-local.yaml

@@ -36,8 +36,40 @@ mybatis:
 
 llm:
   parser:
-    url:  http://127.0.0.1:9092
+    url:
 embedding:
   url: http://127.0.0.1:9092
 functionCall:
   url: http://127.0.0.1:9092
+
+#langchain4j config
+langchain4j:
+  #1.chat-model
+  chat-model:
+    provider: open_ai
+    openai:
+      api-key: api_key
+      model-name: gpt-3.5-turbo
+      temperature: 0.0
+      timeout: PT60S
+  #2.embedding-model
+  embedding-model:
+    provider: in_memory
+#  embedding-model:
+#    hugging-face:
+#      access-token: hg_access_token
+#      model-id: sentence-transformers/all-MiniLM-L6-v2
+#      timeout: 1h
+
+#  embedding-model:
+#    provider: open_ai
+#    openai:
+#      api-key: api_key
+#      modelName: all-minilm-l6-v2.onnx
+
+
+#langchain4j log
+logging:
+  level:
+    dev.langchain4j: DEBUG
+    dev.ai4j.openai4j: DEBUG

launchers/standalone/src/test/java/com/tencent/supersonic/integration/MetricInterpretTest.java

@@ -1,16 +1,13 @@
 package com.tencent.supersonic.integration;
 
-import com.alibaba.fastjson.JSONObject;
 import com.tencent.supersonic.StandaloneLauncher;
 import com.tencent.supersonic.chat.query.llm.analytics.LLMAnswerResp;
 import com.tencent.supersonic.chat.service.AgentService;
 import com.tencent.supersonic.common.config.EmbeddingConfig;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
 import org.junit.Test;
 import org.junit.runner.RunWith;
 import org.springframework.boot.test.context.SpringBootTest;
 import org.springframework.boot.test.mock.mockito.MockBean;
-import org.springframework.http.ResponseEntity;
 import org.springframework.test.context.ActiveProfiles;
 import org.springframework.test.context.junit4.SpringRunner;
 
@@ -21,13 +18,9 @@ public class MetricInterpretTest {
 
     @MockBean
     private AgentService agentService;
-
     @MockBean
     private EmbeddingConfig embeddingConfig;
 
-    @MockBean
-    private EmbeddingUtils embeddingUtils;
-
     @Test
     public void testMetricInterpret() throws Exception {
         MockConfiguration.mockAgent(agentService);
@@ -36,7 +29,6 @@ public class MetricInterpretTest {
         LLMAnswerResp lLmAnswerResp = new LLMAnswerResp();
         lLmAnswerResp.setAssistantMessage("alice最近在超音数的访问情况有增多");
 
-        MockConfiguration.embeddingUtils(embeddingUtils, ResponseEntity.ok(JSONObject.toJSONString(lLmAnswerResp)));
     }
 
 }

launchers/standalone/src/test/java/com/tencent/supersonic/integration/MockConfiguration.java

@@ -1,20 +1,17 @@
 package com.tencent.supersonic.integration;
 
 
-import static org.mockito.ArgumentMatchers.anyObject;
 import static org.mockito.Mockito.when;
 
 import com.google.common.collect.Lists;
 import com.tencent.supersonic.chat.plugin.PluginManager;
 import com.tencent.supersonic.chat.service.AgentService;
 import com.tencent.supersonic.common.config.EmbeddingConfig;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
 import com.tencent.supersonic.common.util.embedding.Retrieval;
 import com.tencent.supersonic.common.util.embedding.RetrieveQueryResult;
 import com.tencent.supersonic.util.DataUtils;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.context.annotation.Configuration;
-import org.springframework.http.ResponseEntity;
 
 @Configuration
 @Slf4j
@@ -38,7 +35,4 @@ public class MockConfiguration {
         when(agentService.getAgent(1)).thenReturn(DataUtils.getAgent());
     }
 
-    public static void embeddingUtils(EmbeddingUtils embeddingUtils, ResponseEntity<String> responseEntity) {
-        when(embeddingUtils.doRequest(anyObject(), anyObject(), anyObject())).thenReturn(responseEntity);
-    }
 }

pom.xml

@@ -71,6 +71,7 @@
         <spotless.python.black.version>22.3.0</spotless.python.black.version>
         <easyexcel.version>2.2.6</easyexcel.version>
         <poi.version>3.17</poi.version>
+        <langchain4j.version>0.24.0</langchain4j.version>
     </properties>
 
     <dependencyManagement>
@@ -94,6 +95,57 @@
                 <artifactId>guava</artifactId>
                 <version>${guava.version}</version>
             </dependency>
+            <!--langchain4j-->
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-parent</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-core</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-spring-boot-starter</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-open-ai</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-hugging-face</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-chroma</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-embeddings</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-hugging-face</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
         </dependencies>
     </dependencyManagement>
 

semantic/model/src/main/java/com/tencent/supersonic/semantic/model/domain/listener/MetaEmbeddingListener.java

@@ -4,13 +4,13 @@ import com.alibaba.fastjson.JSONObject;
 import com.tencent.supersonic.common.pojo.DataEvent;
 import com.tencent.supersonic.common.pojo.enums.DictWordType;
 import com.tencent.supersonic.common.pojo.enums.EventType;
+import com.tencent.supersonic.common.util.ComponentFactory;
 import com.tencent.supersonic.common.util.embedding.EmbeddingQuery;
-import com.tencent.supersonic.common.util.embedding.EmbeddingUtils;
+import com.tencent.supersonic.common.util.embedding.S2EmbeddingStore;
 import java.util.List;
 import java.util.Map;
 import java.util.stream.Collectors;
 import lombok.extern.slf4j.Slf4j;
-import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.beans.factory.annotation.Value;
 import org.springframework.context.ApplicationListener;
 import org.springframework.scheduling.annotation.Async;
@@ -23,8 +23,7 @@ public class MetaEmbeddingListener implements ApplicationListener<DataEvent> {
 
     public static final String COLLECTION_NAME = "meta_collection";
 
-    @Autowired
+    private S2EmbeddingStore s2EmbeddingStore = ComponentFactory.getS2EmbeddingStore();
-    private EmbeddingUtils embeddingUtils;
 
     @Value("${embedding.operation.sleep.time:3000}")
     private Integer embeddingOperationSleepTime;
@@ -55,14 +54,14 @@ public class MetaEmbeddingListener implements ApplicationListener<DataEvent> {
         } catch (InterruptedException e) {
             log.error("", e);
         }
-        embeddingUtils.addCollection(COLLECTION_NAME);
+        s2EmbeddingStore.addCollection(COLLECTION_NAME);
         if (event.getEventType().equals(EventType.ADD)) {
-            embeddingUtils.addQuery(COLLECTION_NAME, embeddingQueries);
+            s2EmbeddingStore.addQuery(COLLECTION_NAME, embeddingQueries);
         } else if (event.getEventType().equals(EventType.DELETE)) {
-            embeddingUtils.deleteQuery(COLLECTION_NAME, embeddingQueries);
+            s2EmbeddingStore.deleteQuery(COLLECTION_NAME, embeddingQueries);
         } else if (event.getEventType().equals(EventType.UPDATE)) {
-            embeddingUtils.deleteQuery(COLLECTION_NAME, embeddingQueries);
+            s2EmbeddingStore.deleteQuery(COLLECTION_NAME, embeddingQueries);
-            embeddingUtils.addQuery(COLLECTION_NAME, embeddingQueries);
+            s2EmbeddingStore.addQuery(COLLECTION_NAME, embeddingQueries);
         }
     }