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[improvement](chat) remove Python service and rewrite it using a Java project (#428)

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This commit is contained in:
lexluo09
2023-11-27 17:40:10 +08:00
committed by GitHub
parent c36082476f
commit 41e585324d
23 changed files with 16 additions and 613 deletions
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13
chat/core/pom.xml
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@@ -116,19 +116,6 @@
<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>

84
chat/core/src/main/java/com/tencent/supersonic/chat/llm/EmbedLLMInterpreter.java
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@@ -1,84 +0,0 @@
package com.tencent.supersonic.chat.llm;
import com.tencent.supersonic.chat.config.OptimizationConfig;
import com.tencent.supersonic.chat.llm.prompt.FunctionCallPromptGenerator;
import com.tencent.supersonic.chat.llm.prompt.OutputFormat;
import com.tencent.supersonic.chat.llm.prompt.SqlExampleLoader;
import com.tencent.supersonic.chat.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 EmbedLLMInterpreter implements LLMInterpreter {
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);
}
}

43
chat/core/src/main/java/com/tencent/supersonic/chat/llm/listener/EmbeddingInitListener.java
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@@ -1,43 +0,0 @@
package com.tencent.supersonic.chat.llm.listener;
import com.tencent.supersonic.chat.config.OptimizationConfig;
import com.tencent.supersonic.chat.llm.EmbedLLMInterpreter;
import com.tencent.supersonic.chat.llm.LLMInterpreter;
import com.tencent.supersonic.chat.llm.prompt.SqlExample;
import com.tencent.supersonic.chat.llm.prompt.SqlExampleLoader;
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 LLMInterpreter llmInterpreter = ComponentFactory.getLLMInterpreter();
@Autowired
private SqlExampleLoader sqlExampleLoader;
@Autowired
private OptimizationConfig optimizationConfig;
@Override
public void run(String... args) {
initSqlExamples();
}
public void initSqlExamples() {
try {
if (llmInterpreter instanceof EmbedLLMInterpreter) {
List<SqlExample> sqlExamples = sqlExampleLoader.getSqlExamples();
String collectionName = optimizationConfig.getText2sqlCollectionName();
sqlExampleLoader.addEmbeddingStore(sqlExamples, collectionName);
}
} catch (Exception e) {
log.error("initSqlExamples error", e);
}
}
}

43
chat/core/src/main/java/com/tencent/supersonic/chat/llm/prompt/FunctionCallPromptGenerator.java
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@@ -1,43 +0,0 @@
package com.tencent.supersonic.chat.llm.prompt;
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);
}
}

43
chat/core/src/main/java/com/tencent/supersonic/chat/llm/prompt/InputFormat.java
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@@ -1,43 +0,0 @@
package com.tencent.supersonic.chat.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;
}
}

54
chat/core/src/main/java/com/tencent/supersonic/chat/llm/prompt/OutputFormat.java
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@@ -1,54 +0,0 @@
package com.tencent.supersonic.chat.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;
}
}
}

32
chat/core/src/main/java/com/tencent/supersonic/chat/llm/prompt/SqlExample.java
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@@ -1,32 +0,0 @@
package com.tencent.supersonic.chat.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;
}

50
chat/core/src/main/java/com/tencent/supersonic/chat/llm/prompt/SqlExampleLoader.java
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@@ -1,50 +0,0 @@
package com.tencent.supersonic.chat.llm.prompt;
import com.fasterxml.jackson.core.type.TypeReference;
import com.tencent.supersonic.chat.llm.vectordb.EmbeddingStoreOperator;
import com.tencent.supersonic.common.util.JsonUtil;
import dev.langchain4j.data.segment.TextSegment;
import java.io.IOException;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
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";
@Autowired
private EmbeddingStoreOperator embeddingStoreOperator;
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) {
embeddingStoreOperator.addAll(sqlExamples, collectionName);
}
public List<Map<String, String>> retrieverSqlExamples(String queryText, String collectionName, int maxResults) {
List<TextSegment> textSegments = embeddingStoreOperator.retriever(queryText, collectionName, maxResults);
List<Map<String, String>> result = new ArrayList<>();
for (TextSegment textSegment : textSegments) {
if (Objects.nonNull(textSegment.metadata())) {
result.add(textSegment.metadata().asMap());
}
}
return result;
}
}

66
chat/core/src/main/java/com/tencent/supersonic/chat/llm/prompt/SqlPromptGenerator.java
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@@ -1,66 +0,0 @@
package com.tencent.supersonic.chat.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;
}
}

20
chat/core/src/main/java/com/tencent/supersonic/chat/llm/vectordb/EmbeddingStoreFactory.java
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@@ -1,20 +0,0 @@
package com.tencent.supersonic.chat.llm.vectordb;
import dev.langchain4j.store.embedding.EmbeddingStore;
import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import lombok.extern.slf4j.Slf4j;
@Slf4j
public class EmbeddingStoreFactory {
private static Map<String, EmbeddingStore> collectionNameToStore = new ConcurrentHashMap<>();
public static EmbeddingStore create(String collectionName) {
return collectionNameToStore.computeIfAbsent(collectionName, k -> new InMemoryEmbeddingStore());
}
}

55
chat/core/src/main/java/com/tencent/supersonic/chat/llm/vectordb/EmbeddingStoreOperator.java
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@@ -1,55 +0,0 @@
package com.tencent.supersonic.chat.llm.vectordb;
import com.tencent.supersonic.chat.llm.prompt.SqlExample;
import com.tencent.supersonic.common.util.JsonUtil;
import dev.langchain4j.data.document.Metadata;
import dev.langchain4j.data.embedding.Embedding;
import dev.langchain4j.data.segment.TextSegment;
import dev.langchain4j.model.embedding.EmbeddingModel;
import dev.langchain4j.retriever.EmbeddingStoreRetriever;
import dev.langchain4j.store.embedding.EmbeddingStore;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
@Service
@Slf4j
public class EmbeddingStoreOperator {
@Autowired
private EmbeddingModel embeddingModel;
public List<TextSegment> retriever(String text, String collectionName, int maxResults) {
EmbeddingStore embeddingStore = EmbeddingStoreFactory.create(collectionName);
EmbeddingStoreRetriever retriever = EmbeddingStoreRetriever.from(embeddingStore, embeddingModel, maxResults);
return retriever.findRelevant(text);
}
public List<String> addAll(List<SqlExample> sqlExamples, String collectionName) {
List<Embedding> embeddings = new ArrayList<>();
List<TextSegment> textSegments = new ArrayList<>();
for (SqlExample sqlExample : sqlExamples) {
String question = sqlExample.getQuestion();
Embedding embedding = embeddingModel.embed(question).content();
embeddings.add(embedding);
Map<String, String> metaDataMap = JsonUtil.toMap(JsonUtil.toString(sqlExample), String.class,
String.class);
TextSegment textSegment = TextSegment.from(question, new Metadata(metaDataMap));
textSegments.add(textSegment);
}
return addAllInternal(embeddings, textSegments, collectionName);
}
private List<String> addAllInternal(List<Embedding> embeddings, List<TextSegment> textSegments,
String collectionName) {
EmbeddingStore embeddingStore = EmbeddingStoreFactory.create(collectionName);
return embeddingStore.addAll(embeddings, textSegments);
}
}

6
chat/core/src/main/java/com/tencent/supersonic/chat/llm/HttpLLMInterpreter.java → chat/core/src/main/java/com/tencent/supersonic/chat/parser/HttpLLMInterpreter.java
View File

@@ -1,4 +1,4 @@
package com.tencent.supersonic.chat.llm;
package com.tencent.supersonic.chat.parser;
import com.alibaba.fastjson.JSON;
import com.tencent.supersonic.chat.config.LLMParserConfig;
@@ -9,6 +9,8 @@ import com.tencent.supersonic.chat.query.llm.s2sql.LLMReq;
import com.tencent.supersonic.chat.query.llm.s2sql.LLMResp;
import com.tencent.supersonic.common.util.ContextUtils;
import com.tencent.supersonic.common.util.JsonUtil;
import java.net.URI;
import java.net.URL;
import lombok.extern.slf4j.Slf4j;
import org.springframework.http.HttpEntity;
import org.springframework.http.HttpHeaders;
@@ -17,8 +19,6 @@ import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.web.client.RestTemplate;
import org.springframework.web.util.UriComponentsBuilder;
import java.net.URI;
import java.net.URL;
@Slf4j
public class HttpLLMInterpreter implements LLMInterpreter {

2
chat/core/src/main/java/com/tencent/supersonic/chat/llm/LLMInterpreter.java → chat/core/src/main/java/com/tencent/supersonic/chat/parser/LLMInterpreter.java
View File

@@ -1,4 +1,4 @@
package com.tencent.supersonic.chat.llm;
package com.tencent.supersonic.chat.parser;
import com.tencent.supersonic.chat.parser.plugin.function.FunctionReq;
import com.tencent.supersonic.chat.parser.plugin.function.FunctionResp;

2
chat/core/src/main/java/com/tencent/supersonic/chat/parser/llm/s2sql/LLMRequestService.java
View File

@@ -12,7 +12,7 @@ import com.tencent.supersonic.chat.api.pojo.SemanticSchema;
import com.tencent.supersonic.chat.api.pojo.request.QueryReq;
import com.tencent.supersonic.chat.config.LLMParserConfig;
import com.tencent.supersonic.chat.config.OptimizationConfig;
import com.tencent.supersonic.chat.llm.LLMInterpreter;
import com.tencent.supersonic.chat.parser.LLMInterpreter;
import com.tencent.supersonic.chat.parser.SatisfactionChecker;
import com.tencent.supersonic.chat.query.llm.s2sql.LLMReq;
import com.tencent.supersonic.chat.query.llm.s2sql.LLMReq.ElementValue;

4
chat/core/src/main/java/com/tencent/supersonic/chat/parser/plugin/embedding/EmbeddingBasedParser.java
View File

@@ -2,8 +2,8 @@ package com.tencent.supersonic.chat.parser.plugin.embedding;
import com.google.common.collect.Lists;
import com.tencent.supersonic.chat.api.pojo.QueryContext;
import com.tencent.supersonic.chat.llm.HttpLLMInterpreter;
import com.tencent.supersonic.chat.llm.LLMInterpreter;
import com.tencent.supersonic.chat.parser.HttpLLMInterpreter;
import com.tencent.supersonic.chat.parser.LLMInterpreter;
import com.tencent.supersonic.chat.parser.ParseMode;
import com.tencent.supersonic.chat.parser.plugin.PluginParser;
import com.tencent.supersonic.chat.plugin.Plugin;

4
chat/core/src/main/java/com/tencent/supersonic/chat/parser/plugin/function/FunctionBasedParser.java
View File

@@ -1,8 +1,8 @@
package com.tencent.supersonic.chat.parser.plugin.function;
import com.tencent.supersonic.chat.api.pojo.QueryContext;
import com.tencent.supersonic.chat.llm.HttpLLMInterpreter;
import com.tencent.supersonic.chat.llm.LLMInterpreter;
import com.tencent.supersonic.chat.parser.HttpLLMInterpreter;
import com.tencent.supersonic.chat.parser.LLMInterpreter;
import com.tencent.supersonic.chat.parser.ParseMode;
import com.tencent.supersonic.chat.parser.plugin.PluginParser;
import com.tencent.supersonic.chat.plugin.Plugin;

2
chat/core/src/main/java/com/tencent/supersonic/chat/utils/ComponentFactory.java
View File

@@ -4,7 +4,7 @@ import com.tencent.supersonic.chat.api.component.SchemaMapper;
import com.tencent.supersonic.chat.api.component.SemanticCorrector;
import com.tencent.supersonic.chat.api.component.SemanticInterpreter;
import com.tencent.supersonic.chat.api.component.SemanticParser;
import com.tencent.supersonic.chat.llm.LLMInterpreter;
import com.tencent.supersonic.chat.parser.LLMInterpreter;
import com.tencent.supersonic.chat.parser.llm.s2sql.ModelResolver;
import com.tencent.supersonic.chat.postprocessor.PostProcessor;
import com.tencent.supersonic.chat.responder.execute.ExecuteResponder;

4
launchers/chat/src/main/resources/META-INF/spring.factories
View File

@@ -19,8 +19,8 @@ com.tencent.supersonic.chat.api.component.SemanticCorrector=\
com.tencent.supersonic.chat.corrector.GroupByCorrector, \
com.tencent.supersonic.chat.corrector.HavingCorrector
com.tencent.supersonic.chat.llm.LLMInterpreter=\
com.tencent.supersonic.chat.llm.HttpLLMInterpreter
com.tencent.supersonic.chat.parser.LLMInterpreter=\
com.tencent.supersonic.chat.parser.HttpLLMInterpreter
com.tencent.supersonic.chat.api.component.SemanticInterpreter=\
com.tencent.supersonic.knowledge.semantic.RemoteSemanticInterpreter

10
launchers/standalone/pom.xml
View File

@@ -96,16 +96,6 @@
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</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>
<profiles>

15
launchers/standalone/src/main/java/com/tencent/supersonic/config/LangChain4jConfig.java
View File

@@ -1,15 +0,0 @@
package com.tencent.supersonic.config;
import dev.langchain4j.model.embedding.AllMiniLmL6V2EmbeddingModel;
import dev.langchain4j.model.embedding.EmbeddingModel;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
@Configuration
public class LangChain4jConfig {
@Bean
EmbeddingModel embeddingModel() {
return new AllMiniLmL6V2EmbeddingModel();
}
}

8
launchers/standalone/src/main/resources/META-INF/spring.factories
View File

@@ -21,8 +21,8 @@ com.tencent.supersonic.chat.api.component.SemanticCorrector=\
com.tencent.supersonic.chat.corrector.HavingCorrector, \
com.tencent.supersonic.chat.corrector.FromCorrector
com.tencent.supersonic.chat.llm.LLMInterpreter=\
com.tencent.supersonic.chat.llm.HttpLLMInterpreter
com.tencent.supersonic.chat.parser.LLMInterpreter=\
com.tencent.supersonic.chat.parser.HttpLLMInterpreter
com.tencent.supersonic.chat.api.component.SemanticInterpreter=\
com.tencent.supersonic.knowledge.semantic.LocalSemanticInterpreter
@@ -49,6 +49,4 @@ com.tencent.supersonic.chat.responder.parse.ParseResponder=\
com.tencent.supersonic.chat.responder.execute.ExecuteResponder=\
com.tencent.supersonic.chat.responder.execute.EntityInfoExecuteResponder, \
com.tencent.supersonic.chat.responder.execute.SimilarMetricExecuteResponder
org.springframework.boot.autoconfigure.EnableAutoConfiguration=dev.langchain4j.LangChain4jAutoConfiguration
com.tencent.supersonic.chat.responder.execute.SimilarMetricExecuteResponder

17
launchers/standalone/src/main/resources/application-local.yaml
View File

@@ -39,19 +39,4 @@ llm:
embedding:
url: http://127.0.0.1:9092
functionCall:
url: http://127.0.0.1:9092
langchain4j:
chat-model:
provider: open_ai
openai:
api-key: api_key
model-name: gpt-3.5-turbo
temperature: 0.0
timeout: PT60S
logging:
level:
dev.langchain4j: DEBUG
dev.ai4j.openai4j: DEBUG
url: http://127.0.0.1:9092

52
pom.xml
View File

@@ -71,7 +71,6 @@
<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>
@@ -95,57 +94,6 @@
<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>