ModelConfig.java
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package com.xly.config;
import com.fasterxml.jackson.databind.DeserializationFeature;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.SerializationFeature;
import com.fasterxml.jackson.datatype.jsr310.JavaTimeModule;
import com.xly.agent.*;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.ollama.OllamaChatModel;
import dev.langchain4j.model.ollama.OllamaStreamingChatModel;
import dev.langchain4j.service.AiServices;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import java.time.Duration;
/**
* 模型与 Agent 统一装配（langchain4j 1.14.0 新 API：ChatModel / StreamingChatModel）
* 约定：
* - 路由/SQL/参数提取类任务 → 低温（确定性）
* - 闲聊类任务 → 高温（多样性）
*/
@Configuration
public class ModelConfig {
@Value("${langchain4j.ollama.base-url}")
private String baseUrl;
@Value("${langchain4j.ollama.chat-model-name}")
private String chatModelName;
@Value("${langchain4j.ollama.sql-model-name}")
private String sqlModelName;
// ========================================================
// 一、私有 builder 工厂：消除重复配置
// ========================================================
/** 非流式 Ollama 模型的公共构造 */
private OllamaChatModel.OllamaChatModelBuilder chatBuilder(String modelName,
double temperature,
double topP,
long timeoutSeconds,
int maxRetries) {
return OllamaChatModel.builder()
.baseUrl(baseUrl)
.modelName(modelName)
.temperature(temperature)
.topP(topP)
.timeout(Duration.ofSeconds(timeoutSeconds))
.maxRetries(maxRetries);
}
/** 流式 Ollama 模型的公共构造 */
private OllamaStreamingChatModel.OllamaStreamingChatModelBuilder streamingBuilder(String modelName,
double temperature,
double topP,
int numPredict,
long timeoutSeconds) {
return OllamaStreamingChatModel.builder()
.baseUrl(baseUrl)
.modelName(modelName)
.temperature(temperature)
.topP(topP)
.numPredict(numPredict)
.timeout(Duration.ofSeconds(timeoutSeconds));
}
// ========================================================
// 二、模型 Bean
// ========================================================
/** 主对话模型：路由/场景/方法选择等确定性任务共用 */
@Bean
@Primary
public OllamaChatModel chatLanguageModel() {
return chatBuilder(chatModelName, 0.1, 0.95, 120, 2)
.logRequests(true)
.logResponses(true)
.build();
}
/** 自由闲聊（非流式） */
@Bean("chatiModel")
public OllamaChatModel chatiModel() {
return chatBuilder(chatModelName, 0.7, 0.9, 60, 2).build();
}
/** 自由闲聊（流式） */
@Bean("chatiStreamingModel")
public OllamaStreamingChatModel chatiStreamingModel() {
return streamingBuilder(chatModelName, 0.7, 0.9, 512, 60).build();
}
/** SQL 专用（非流式，零温 + 大输出） */
@Bean("sqlChatModel")
public OllamaChatModel sqlChatModel() {
return chatBuilder(sqlModelName, 0.0, 0.95, 120, 3)
.numPredict(4096)
.build();
}
/** 主流式对话 */
@Bean("streamingChatModel")
@Primary
public OllamaStreamingChatModel streamingChatModel() {
return streamingBuilder(chatModelName, 0.3, 0.9, 1024, 60).build();
}
/** SQL 流式 */
@Bean("streamingSqlModel")
public OllamaStreamingChatModel streamingSqlModel() {
return streamingBuilder(sqlModelName, 0.2, 0.95, 2048, 120).build();
}
// ========================================================
// 三、JSON
// ========================================================
@Bean
@Primary
public ObjectMapper objectMapper() {
ObjectMapper mapper = new ObjectMapper();
mapper.registerModule(new JavaTimeModule());
mapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS);
mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
return mapper;
}
// ========================================================
// 四、Agent Bean
// ========================================================
/** 动态 SQL Agent */
@Bean
public DynamicTableNl2SqlAiAgent dynamicTableNl2SqlAiAgent(
@Qualifier("sqlChatModel") OllamaChatModel sqlModel) {
return AiServices.builder(DynamicTableNl2SqlAiAgent.class)
.chatModel(sqlModel)
.chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(10))
.build();
}
/**
* 闲聊 Agent：会话隔离由 @MemoryId + OperableChatMemoryProvider 完成，
* 全局共用一个实例即可
*/
@Bean
public ChatiAgent chatiAgent(
@Qualifier("chatiModel") OllamaChatModel chatiModel,
@Qualifier("chatiStreamingModel") OllamaStreamingChatModel chatiStreamingModel,
OperableChatMemoryProvider operableChatMemoryProvider) {
return AiServices.builder(ChatiAgent.class)
.chatModel(chatiModel)
.streamingChatModel(chatiStreamingModel)
.chatMemoryProvider(operableChatMemoryProvider)
.maxSequentialToolsInvocations(1)
.build();
}
/** 场景选择 Agent（一级路由） */
@Bean
public SceneSelectorAiAgent sceneSelectorAiAgent(
@Qualifier("chatLanguageModel") OllamaChatModel chatLanguageModel) {
return AiServices.builder(SceneSelectorAiAgent.class)
.chatModel(chatLanguageModel)
.chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(10))
.maxSequentialToolsInvocations(1)
.build();
}
/**
* 方法选择 Agent（二级路由）：从场景内方法树中路由出 sMethodNo。
* 分类任务，用极短记忆窗口避免被上文惯性带偏。
*/
@Bean
public SecMethodAiAgent secMethodAiAgent(
@Qualifier("chatLanguageModel") OllamaChatModel chatLanguageModel) {
return AiServices.builder(SecMethodAiAgent.class)
.chatModel(chatLanguageModel)
.chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(2))
.maxSequentialToolsInvocations(1)
.build();
}
/**
* 方法选择 Agent（二级路由）：从数据中获取到对应的 添加的部件名称，删除的部件名称
* 分类任务，用极短记忆窗口避免被上文惯性带偏。
*/
@Bean
public DynamicPartAiAgent dynamicPartAiAgent(
@Qualifier("chatLanguageModel") OllamaChatModel chatLanguageModel) {
return AiServices.builder(DynamicPartAiAgent.class)
.chatModel(chatLanguageModel)
.chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(2))
.maxSequentialToolsInvocations(1)
.build();
}
}