package com.xly.config; import com.fasterxml.jackson.databind.ObjectMapper; import com.xly.agent.AgentIdentity; import com.xly.agent.ReActAgent; import com.xly.service.ErpClient; import com.xly.service.FormResolverService; import com.xly.service.OpService; import com.xly.service.SystemPromptService; import com.xly.tool.ErpReadTool; import com.xly.tool.FormCollectTool; import com.xly.tool.InteractionTool; import com.xly.tool.KgQueryTool; import com.xly.tool.ProposeWriteTool; import com.xly.agent.ProjectedChatMemory; import dev.langchain4j.model.chat.StreamingChatModel; import dev.langchain4j.service.AiServices; import org.springframework.beans.factory.annotation.Qualifier; import org.springframework.jdbc.core.JdbcTemplate; import org.springframework.stereotype.Component; /** * 按「每次请求的身份」组装单一 ReAct agent(架构 §5/§7 的 per-call context)。 * *
为什么按请求新建:LangChain4j 流式工具执行发生在模型 HTTP 回调线程,而非控制器工作线程, * ThreadLocal 不可靠。于是把 {@link AgentIdentity}(透传 token + 权限集)直接注入到**每请求新建**的 * 工具实例里(ErpReadTool/ProposeWriteTool/FormCollectTool),从根上保证鉴权与 token 正确。 * *
工具集**固定 6 个**(findForms/readFormData/lookupRecord/collectForm/proposeWrite/askUser), * 不再按意图分范围:n=50 基准显示分范围收不到准确率收益,反而破坏 KV-cache 前缀稳定性。 * 无状态、全局的工具({@link KgQueryTool}、{@link InteractionTool})是单例、跨请求复用。 */ @Component public class AgentFactory { private final StreamingChatModel streamingModel; private final RedisChatMemoryStore memoryStore; private final SystemPromptService systemPromptService; private final ErpClient erp; private final JdbcTemplate jdbc; private final FormResolverService resolver; private final OpService ops; private final ObjectMapper mapper; private final KgQueryTool kgQueryTool; private final InteractionTool interactionTool; public AgentFactory(@Qualifier("agentStreamingModel") StreamingChatModel streamingModel, RedisChatMemoryStore memoryStore, SystemPromptService systemPromptService, ErpClient erp, JdbcTemplate jdbc, FormResolverService resolver, OpService ops, ObjectMapper mapper, KgQueryTool kgQueryTool, InteractionTool interactionTool) { this.streamingModel = streamingModel; this.memoryStore = memoryStore; this.systemPromptService = systemPromptService; this.erp = erp; this.jdbc = jdbc; this.resolver = resolver; this.ops = ops; this.mapper = mapper; this.kgQueryTool = kgQueryTool; this.interactionTool = interactionTool; } /** * 组装 ReAct agent:固定 6 工具 + 唯一 system prompt。{@code maxSequentialToolsInvocations} * 作为循环护栏,杜绝「反复追问同一问题」这类失控 ReAct 循环。 */ public ReActAgent build(AgentIdentity identity) { Object[] tools = new Object[]{kgQueryTool, interactionTool, new ErpReadTool(erp, resolver, identity), new ProposeWriteTool(erp, jdbc, ops, mapper, identity, resolver), new FormCollectTool(jdbc, resolver, identity, mapper)}; return AiServices.builder(ReActAgent.class) .streamingChatModel(streamingModel) .tools(tools) .maxSequentialToolsInvocations(8) // 循环护栏:防止 askUser/工具无限自我循环 // token 预算投影记忆:存储保完整、读取按预算收拢,旧工具结果压一行(见 ProjectedChatMemory) .chatMemoryProvider(memoryId -> new ProjectedChatMemory(memoryId, memoryStore, 6000, 80)) .systemMessageProvider(memoryId -> systemPromptService.prompt()) .build(); } /** 供确定性「新增」路径直接构建 collectForm 表单(不经 LLM 工具选择)。 */ public FormCollectTool formCollectTool(AgentIdentity identity) { return new FormCollectTool(jdbc, resolver, identity, mapper); } /** 供确定性「修改/作废/审核…」路径直接调 proposeWrite(不经 LLM 工具选择)。 */ public ProposeWriteTool proposeWriteTool(AgentIdentity identity) { return new ProposeWriteTool(erp, jdbc, ops, mapper, identity, resolver); } }