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(improvement)(headless) Add support for the Ollama provider in the frontend and optimize the code (#1270)

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This commit is contained in:
lexluo09
2024-06-28 17:29:58 +08:00
committed by GitHub
parent 7564256b0a
commit 528491717b
15 changed files with 165 additions and 62 deletions
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4
chat/server/src/main/java/com/tencent/supersonic/chat/server/executor/PlainTextExecutor.java
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@@ -7,7 +7,6 @@ import com.tencent.supersonic.chat.server.persistence.repository.ChatQueryReposi
import com.tencent.supersonic.chat.server.pojo.ChatExecuteContext;
import com.tencent.supersonic.chat.server.service.AgentService;
import com.tencent.supersonic.common.util.ContextUtils;
import com.tencent.supersonic.common.util.S2ChatModelProvider;
import com.tencent.supersonic.headless.api.pojo.response.ParseResp;
import com.tencent.supersonic.headless.api.pojo.response.QueryResult;
import com.tencent.supersonic.headless.api.pojo.response.QueryState;
@@ -16,6 +15,7 @@ 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 dev.langchain4j.model.provider.ChatLanguageModelProvider;
import java.util.Collections;
import java.util.List;
@@ -46,7 +46,7 @@ public class PlainTextExecutor implements ChatExecutor {
AgentService agentService = ContextUtils.getBean(AgentService.class);
Agent chatAgent = agentService.getAgent(chatExecuteContext.getAgentId());
ChatLanguageModel chatLanguageModel = S2ChatModelProvider.provide(chatAgent.getLlmConfig());
ChatLanguageModel chatLanguageModel = ChatLanguageModelProvider.provide(chatAgent.getLlmConfig());
Response<AiMessage> response = chatLanguageModel.generate(prompt.toUserMessage());
QueryResult result = new QueryResult();

4
chat/server/src/main/java/com/tencent/supersonic/chat/server/memory/MemoryReviewTask.java
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@@ -4,10 +4,10 @@ import com.tencent.supersonic.chat.api.pojo.enums.MemoryReviewResult;
import com.tencent.supersonic.chat.server.agent.Agent;
import com.tencent.supersonic.chat.server.service.AgentService;
import com.tencent.supersonic.chat.server.service.MemoryService;
import com.tencent.supersonic.common.util.S2ChatModelProvider;
import dev.langchain4j.model.chat.ChatLanguageModel;
import dev.langchain4j.model.input.Prompt;
import dev.langchain4j.model.input.PromptTemplate;
import dev.langchain4j.model.provider.ChatLanguageModelProvider;
import lombok.extern.slf4j.Slf4j;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
@@ -54,7 +54,7 @@ public class MemoryReviewTask {
Prompt prompt = PromptTemplate.from(promptStr).apply(Collections.EMPTY_MAP);
keyPipelineLog.info("MemoryReviewTask reqPrompt:{}", promptStr);
ChatLanguageModel chatLanguageModel = S2ChatModelProvider.provide(chatAgent.getLlmConfig());
ChatLanguageModel chatLanguageModel = ChatLanguageModelProvider.provide(chatAgent.getLlmConfig());
String response = chatLanguageModel.generate(prompt.toUserMessage()).content().text();
keyPipelineLog.info("MemoryReviewTask modelResp:{}", response);

4
chat/server/src/main/java/com/tencent/supersonic/chat/server/parser/NL2SQLParser.java
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@@ -8,7 +8,6 @@ import com.tencent.supersonic.chat.server.pojo.ChatParseContext;
import com.tencent.supersonic.chat.server.util.QueryReqConverter;
import com.tencent.supersonic.common.config.LLMConfig;
import com.tencent.supersonic.common.util.ContextUtils;
import com.tencent.supersonic.common.util.S2ChatModelProvider;
import com.tencent.supersonic.headless.api.pojo.SchemaElement;
import com.tencent.supersonic.headless.api.pojo.SchemaElementMatch;
import com.tencent.supersonic.headless.api.pojo.SchemaElementType;
@@ -24,6 +23,7 @@ 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 dev.langchain4j.model.provider.ChatLanguageModelProvider;
import lombok.Builder;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
@@ -180,7 +180,7 @@ public class NL2SQLParser implements ChatParser {
Prompt prompt = PromptTemplate.from(promptStr).apply(Collections.EMPTY_MAP);
keyPipelineLog.info("NL2SQLParser reqPrompt:{}", promptStr);
ChatLanguageModel chatLanguageModel = S2ChatModelProvider.provide(context.getLlmConfig());
ChatLanguageModel chatLanguageModel = ChatLanguageModelProvider.provide(context.getLlmConfig());
Response<AiMessage> response = chatLanguageModel.generate(prompt.toUserMessage());
String result = response.content().text();

4
chat/server/src/main/java/com/tencent/supersonic/chat/server/util/LLMConnHelper.java
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@@ -2,8 +2,8 @@ package com.tencent.supersonic.chat.server.util;
import com.tencent.supersonic.common.config.LLMConfig;
import com.tencent.supersonic.common.pojo.exception.InvalidArgumentException;
import com.tencent.supersonic.common.util.S2ChatModelProvider;
import dev.langchain4j.model.chat.ChatLanguageModel;
import dev.langchain4j.model.provider.ChatLanguageModelProvider;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
@@ -14,7 +14,7 @@ public class LLMConnHelper {
if (llmConfig == null || StringUtils.isBlank(llmConfig.getBaseUrl())) {
return false;
}
ChatLanguageModel chatLanguageModel = S2ChatModelProvider.provide(llmConfig);
ChatLanguageModel chatLanguageModel = ChatLanguageModelProvider.provide(llmConfig);
String response = chatLanguageModel.generate("Hi there");
return StringUtils.isNotEmpty(response) ? true : false;
} catch (Exception e) {