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https://gitcode.com/JianFeeeee/HomeAgent.git
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背景:此前媒体是靠「生成的描述文本」将就进记忆的——写 marker 进正文、 再由正则反解成 media_refs 与图库里的 type=Media 实体。这条链路有三个 致命缺陷:描述由异步模型生成(未生成前媒体等于不存在)、语义检索实质上 只搜描述文字、图库里的「媒体节点」是描述文本的投影而不是媒体本身。 本提交把这条链路整体拆除,媒体改为按自己的原生向量参与记忆: 一、描述链彻底删除(无残留、无兼容分支) - media.Item 去掉 Description/DescribedBy 与对应列; - 删除 Store.Describe / Store.Search / Store.Pending; - 删除 Agent.mediaDescribeLoop / describePendingMedia 与配置项 core.memory.media.describe_on_ingest; - SDK 侧 MediaAttachment 去掉 Description(见 SDK 仓独立提交)。 二、marker 机制删除,媒体归属改为结构化块边 - 删除 mediaMarkerLine/parseMediaMarkers/mediaEntityName/mediaTriplesFromText/ extractMediaDigests/sentenceWithMediaMarkers/docMediaContext; - memory.Triple 新增 MediaDigests 结构化字段;句子文本保持原样, 不再被 marker 污染; - 块以 sentence --contains--> block / document --contains--> block 结构边 挂到承载节点(新增 documents 表与 document 节点种类); - 模型未给原句时用「主谓宾。」拼一句自然语言作落点,不造 marker 文本。 三、旧数据迁移(幂等) - 新增 GraphDB.MigrateLegacyMediaEntities:把 type=Media 的旧实体按短 digest 还原成原生块、挂回原句子、删除旧实体与描述关系;Agent 启动时执行; - CleanupOrphanedSentences 同时看关系引用与块边,避免把只靠块存活的句子 连同块边一起删掉。 四、向量融合:媒体按图本身被召回 - 新增 vector.FuseVectors(逐维求和 + L2 归一化); - Doc.DenseVec = 文本向量 ⊕ 文档块的媒体向量(同 fingerprint 才融合), 新增 Doc.DenseFP,指纹变化触发重算; - ContextEvent.DenseVec 同理融合事件块;事件新增 DenseFP,Prune 只在 同一统一空间内比稠密余弦; - 跨模态视觉路只召回「仍被某层记忆块持有」的媒体,CAS 全库字节不再 直接充当记忆检索结果。 五、同时纳入本分支既有的嵌入基础改造(此前工作区未提交,缺它 HEAD 不可构建) - internal/tfidf 懒回退包、千问三段式多模态 ONNX 空间的 Go 侧 (qwen/embedder.go、image.go、model_input.go)、CLIP 移除、 sdk.NewStore 分词器签名与调用点、embed 侧车 systemd 单元。 验证:go build ./... 、go vet ./...(含 -tags medialive)均通过; 在 HEAD 的独立 worktree 上重放本次暂存集后 go test -short ./internal/... 全部通过(端口冲突类用例在隔离环境中亦通过)。未提交工作区中与本改造 无关的改动(HarmonyOS、waiter、devicebridge、plan.md 等)。
525 lines
16 KiB
Go
525 lines
16 KiB
Go
package core
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import (
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"fmt"
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"log"
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"runtime/debug"
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"time"
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agentAPI "gitcode.com/JianFeeeee/HomeAgent/internal/agent/api"
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agentIO "gitcode.com/JianFeeeee/HomeAgent/internal/agent/io"
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"gitcode.com/JianFeeeee/HomeAgent/internal/events"
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sdk "gitcode.com/JianFeeeee/HomeAgent/internal/sdk"
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pubsdk "gitcode.com/JianFeeeee/homeagent-sdk/sdk"
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)
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func (a *Agent) eventLoop() {
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defer func() {
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if r := recover(); r != nil {
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log.Printf("[agent] eventLoop panic recovered: %v\n%s", r, debug.Stack())
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time.Sleep(time.Second)
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go a.eventLoop()
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}
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}()
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for {
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select {
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case evt := <-a.io.InputChan():
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a.handleInput(evt)
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case msg := <-a.selfInputCh:
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a.handleSelfInput(msg)
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case <-a.ctx.Done():
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return
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}
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}
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}
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func (a *Agent) interceptLoop() {
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defer func() {
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if r := recover(); r != nil {
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log.Printf("[agent] interceptLoop panic recovered: %v\n%s", r, debug.Stack())
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time.Sleep(time.Second)
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go a.interceptLoop()
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}
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}()
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for {
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select {
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case evt := <-a.io.InputInterruptChan():
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text, _ := evt.Payload["content"].(string)
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if text == "" {
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continue
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}
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log.Printf("[agent] interrupt from %s/%s: %s", evt.Source, evt.OutputChannel, truncateStr(text, 80))
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clone := &agentIO.InputEvent{
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RequestID: evt.RequestID,
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Source: evt.Source,
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Type: evt.Type,
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Payload: map[string]interface{}{},
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OutputChannel: evt.OutputChannel,
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}
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for k, v := range evt.Payload {
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clone.Payload[k] = v
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}
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clone.Payload["interrupt"] = true
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clone.Payload["interrupt_source"] = evt.Source
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clone.Payload["interrupt_channel"] = evt.OutputChannel
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a.llmMu.Lock()
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hasActiveLLM := a.cancelLLM != nil
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if hasActiveLLM {
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a.cancelLLM()
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log.Printf("[agent] LLM request cancelled by interrupt")
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}
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a.llmMu.Unlock()
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if hasActiveLLM {
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if a.currentOutputChannel == "_consolidation_" {
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log.Printf("[agent] consolidation interrupted, re-injecting input for %s/%s", evt.Source, evt.OutputChannel)
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a.io.InjectInputTo(evt.Source, evt.OutputChannel, "text", map[string]interface{}{
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"content": text,
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"interrupt": true,
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"interrupt_source": evt.Source,
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"interrupt_channel": evt.OutputChannel,
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})
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} else {
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select {
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case a.interceptCh <- clone:
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default:
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log.Printf("[agent] intercept channel full, queuing input for %s", evt.Source)
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a.io.InjectInputTo(evt.Source, evt.OutputChannel, "text", map[string]interface{}{
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"content": text,
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"interrupt": true,
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"interrupt_source": evt.Source,
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"interrupt_channel": evt.OutputChannel,
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})
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}
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}
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} else {
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a.io.InjectInputTo(evt.Source, evt.OutputChannel, "text", map[string]interface{}{
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"content": text,
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"interrupt": true,
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"interrupt_source": evt.Source,
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"interrupt_channel": evt.OutputChannel,
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})
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}
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case <-a.ctx.Done():
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return
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}
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}
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}
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// channelConsolidation 标记记忆整理类自输入:无记忆路径处理,
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// 不写入对话上下文、不向任何输出通道 emit 响应。
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const channelConsolidation = "_consolidation_"
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// selfInputMsg 自循环输入消息。channel 决定处理路径:
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// - channelConsolidation:记忆整理,无记忆(不污染上下文/知识库)
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// - 其他值(如 "cli"、"webui"):正常输入路径,写入上下文并 emit 响应
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// (典型场景:子 Agent 完成通知,需让父 Agent 感知并可回复用户)
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type selfInputMsg struct {
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text string
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channel string
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}
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func (a *Agent) handleSelfInput(msg selfInputMsg) {
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if msg.channel == "" {
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msg.channel = channelConsolidation // 兼容空值:默认走整理路径
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}
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a.processInput(&agentIO.InputEvent{
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Source: "system",
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Type: "text",
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Payload: map[string]interface{}{"content": msg.text},
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OutputChannel: msg.channel,
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})
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}
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func (a *Agent) handleInput(evt *agentIO.InputEvent) {
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switch evt.Type {
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case "text", "image", "audio":
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a.processInput(evt)
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case "event":
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log.Printf("[agent] event from %s: %v", evt.Source, evt.Payload)
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case "command":
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cmd, _ := evt.Payload["command"].(string)
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log.Printf("[agent] command from %s: %s", evt.Source, cmd)
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default:
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log.Printf("[agent] unknown event type from %s: %s", evt.Source, evt.Type)
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}
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}
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// inputPayload 是一次输入在「模态」这个维度上的全部内容。
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//
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// 拆出这个结构,是为了让 processInput 只有一条主干:模态不再决定走哪个函数,
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// 只决定这里的字段填不填。此前 text 与 image/audio 各有一个 process 函数,
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// 媒体那条缺了去重、no_memory、通道 Cleaner、中断语义、EventRawInput 五项——
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// 不是因为媒体不需要,而是复制粘贴之后文本那条继续演进、媒体那条没跟上。
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type inputPayload struct {
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// text 是进 LLM 与记忆的文本。纯媒体输入时它是 mediaToBlocks 给的 alt 文案。
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text string
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// blocks 非空表示本轮带多模态内容,随当前轮的 message 一起发给模型。
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blocks []agentAPI.ContentBlock
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// mediaType 供插件在 stage 里判断本轮媒体的模态。
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mediaType string
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// captureTool 是媒体落进 CAS 时记录的来源标签。
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captureTool string
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}
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// resolveInput 把 InputEvent 归一成 inputPayload。
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//
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// 三种来源在这里合流:
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// 1. evt.Type 是 image/audio —— 用户直接发的媒体,payload 里是 data/url;
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// 2. evt.Type 是 text 且 payload 带 media_blocks —— 插件经 IOInjector 的
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// InjectInputMedia / InjectInputMediaSync / InjectInterruptMedia 注入的
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// 媒体,块已经是成品;
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// 3. 纯文本。
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//
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// 第 2 种此前无处可去:注入方把块放进 payload,而文本路径不看这个键,
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// 于是插件注入的媒体到 payload 就断了,且不报错。
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func (a *Agent) resolveInput(evt *agentIO.InputEvent) (inputPayload, bool) {
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switch evt.Type {
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case "image", "audio":
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blocks, alt := a.mediaToBlocks(evt.Payload, evt.Type, evt.Source)
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return inputPayload{
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text: alt,
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blocks: blocks,
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mediaType: evt.Type,
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captureTool: "input_" + evt.Type,
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}, true
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}
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text, _ := evt.Payload["content"].(string)
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blocks, mediaType := injectedBlocks(evt.Payload)
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// 文本与媒体都空才算无效输入:只带图不带字是合法的(插件注入常这样)。
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if text == "" && len(blocks) == 0 {
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return inputPayload{}, false
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}
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return inputPayload{
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text: text,
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blocks: blocks,
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mediaType: mediaType,
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captureTool: "inject_" + evt.Source,
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}, true
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}
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// injectedBlocks 取出 payload 里插件注入的多模态块。
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//
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// 两种静态类型都要认:内核内部注入直接给 []agentAPI.ContentBlock,
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// 而经公共 SDK 的 IOInjector 过来的是 []pubsdk.ContentBlock。两者字段完全一致,
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// 但 Go 不会自动转换,只认一种的后果是另一种被静默丢弃。
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func injectedBlocks(payload map[string]interface{}) ([]agentAPI.ContentBlock, string) {
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var blocks []agentAPI.ContentBlock
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switch v := payload["media_blocks"].(type) {
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case []agentAPI.ContentBlock:
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blocks = v
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case []pubsdk.ContentBlock:
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blocks = make([]agentAPI.ContentBlock, 0, len(v))
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for _, b := range v {
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nb := agentAPI.ContentBlock{Type: b.Type, Text: b.Text}
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if b.ImageURL != nil {
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nb.ImageURL = &agentAPI.ImageURL{URL: b.ImageURL.URL, Detail: b.ImageURL.Detail}
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}
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if b.AudioURL != nil {
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nb.AudioURL = &agentAPI.AudioURL{URL: b.AudioURL.URL}
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}
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blocks = append(blocks, nb)
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}
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}
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if len(blocks) == 0 {
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return nil, ""
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}
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// 模态由块自身判定,注入方不必额外声明。图优先:一次注入里图片是主体。
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mediaType := ""
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for _, b := range blocks {
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if b.ImageURL != nil {
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return blocks, "image"
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}
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if b.AudioURL != nil {
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mediaType = "audio"
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}
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}
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return blocks, mediaType
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}
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func (a *Agent) mediaToBlocks(payload map[string]interface{}, mediaType string, source string) ([]agentAPI.ContentBlock, string) {
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data, _ := payload["data"].(string)
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mime, _ := payload["mime"].(string)
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url, _ := payload["url"].(string)
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alt, _ := payload["alt"].(string)
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if alt == "" {
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if source == "" {
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source = "unknown"
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}
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alt = fmt.Sprintf("[从 %s 收到了 %s]", source, mediaType)
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}
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var blocks []agentAPI.ContentBlock
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desc := ""
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switch mediaType {
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case "image":
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desc = a.inputCfg.Image.DescribePrompt
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if desc == "" {
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desc = fmt.Sprintf("从 %s 收到了一张图片,请使用 describe_image 工具查看详情。", source)
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}
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case "audio":
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desc = a.inputCfg.Audio.DescribePrompt
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if desc == "" {
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desc = fmt.Sprintf("从 %s 收到了一段音频,请使用 transcribe_audio 工具查看内容。", source)
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}
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}
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blocks = append(blocks, agentAPI.ContentBlock{Type: "text", Text: desc})
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if data != "" || url != "" {
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imgURL := url
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if data != "" {
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if mime == "" {
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mime = "image/png"
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}
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imgURL = "data:" + mime + ";base64," + data
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}
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if mediaType == "image" {
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blocks = append(blocks, agentAPI.ContentBlock{
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Type: "image_url",
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ImageURL: &agentAPI.ImageURL{URL: imgURL, Detail: "auto"},
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})
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} else if mediaType == "audio" {
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blocks = append(blocks, agentAPI.ContentBlock{
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Type: "audio_url",
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AudioURL: &agentAPI.AudioURL{URL: imgURL},
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})
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}
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}
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return blocks, alt
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}
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// processInput 是全部模态输入的唯一主干。
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//
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// 文本、用户上传的图/音频、插件注入的多模态块走同一条路径,因此去重、
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// no_memory、通道 Cleaner、中断语义、EventRawInput、媒体入 CAS、媒体记忆绑定
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// 对所有模态一致——不会再出现「文本路径加了功能、媒体路径没跟上」。
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func (a *Agent) processInput(evt *agentIO.InputEvent) {
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start := time.Now()
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in, ok := a.resolveInput(evt)
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if !ok {
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return
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}
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// 去重按文本做:webui/GUI 断线重连会重放未确认消息。
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// 带媒体时跳过——媒体输入的 alt 文案("[从 qq 收到了 image]")对不同图片
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// 是同一句,拿它去重会把连发的两张图误判成重复。
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if len(in.blocks) == 0 && a.isDuplicateInput(evt.Source, in.text) {
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log.Printf("[agent] dropped duplicate input from %s: %s", evt.Source, truncateStr(in.text, 60))
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return
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}
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a.currentOutputChannel = evt.OutputChannel
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if a.currentOutputChannel == "" {
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a.currentOutputChannel = evt.Source
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}
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if evt.OutputChannel == "_consolidation_" {
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a.processConsolidation(evt, in.text)
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return
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}
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// pendingMedia 让 describe_image / transcribe_audio / ocr_image 拿到本轮媒体的
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// 原始 data/url,也是这三个工具是否出现在工具表里的开关。仅对用户直接上传成立
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//(payload 里才有 data/url);插件注入的是成品 block,取不到原始数据。
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if evt.Type == "image" || evt.Type == "audio" {
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a.pendingMedia = evt.Payload
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defer func() { a.pendingMedia = nil }()
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}
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// 媒体先落进 CAS。不存的后果是 ContextEvent.Input 只剩一句 alt 文本,
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// base64 随 message 数组发给模型后就丢了。
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if len(in.blocks) > 0 {
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a.stageMediaDigests(a.captureBlockMedia(in.blocks, in.captureTool)...)
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}
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noMemory := false
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if v, ok := evt.Payload["no_memory"].(bool); ok {
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noMemory = v
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}
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if !noMemory && a.io != nil {
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if chDef, ok := a.io.GetInputChannelDef(evt.Source); ok && chDef.NoMemory {
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noMemory = true
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}
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}
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// 工具提醒/中断(terminal_watch、timer 等)不是用户发言:
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// 以 system 角色注入 LLM,且不写入用户对话履历。
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isInterrupt, _ := evt.Payload["interrupt"].(bool)
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a.mu.Lock()
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a.interruptInput = isInterrupt
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a.mu.Unlock()
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if isInterrupt {
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noMemory = true
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}
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stageCtx := a.stageCtxFromInput(in.text, evt.Source, "")
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stageCtx.Extra["input_source"] = evt.Source
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stageCtx.Extra["output_channel"] = evt.OutputChannel
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if len(in.blocks) > 0 {
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stageCtx.Extra["media_blocks"] = in.blocks
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stageCtx.Extra["media_type"] = in.mediaType
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}
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if noMemory {
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stageCtx.NoMemory = true
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}
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a.injectSourceContext(stageCtx, evt)
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if a.runStage(sdk.StageOnInput, stageCtx) {
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a.emitResponse(evt, *stageCtx.Response)
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return
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}
|
||
|
||
input := stageCtx.RawMessage
|
||
|
||
// 计算层用的清洗文本(不改原文):通道 Cleaner 提取语义内容后用于向量化/提关键词
|
||
cleanInput := input
|
||
if a.io != nil {
|
||
if chDef, ok := a.io.GetInputChannelDef(evt.Source); ok && chDef.Cleaner != nil {
|
||
cleanInput = chDef.Cleaner(input)
|
||
}
|
||
}
|
||
|
||
// upload_* 字段一并转发:webui 的 EventRawInput 订阅方靠它们还原附件卡片。
|
||
// 媒体路径此前把整个 payload 塞进 content(一个 map),订阅方按 string 断言
|
||
// 直接失败 → 用户发的图从不出现在聊天记录里。
|
||
rawPayload := map[string]interface{}{"content": input, "source": evt.Source}
|
||
for _, k := range []string{"upload_url", "upload_type", "upload_size", "upload_name"} {
|
||
if v, ok := evt.Payload[k]; ok {
|
||
rawPayload[k] = v
|
||
}
|
||
}
|
||
a.publishEvent(events.EventRawInput, rawPayload)
|
||
|
||
archived := a.context.Prune(cleanInput, a.maxContextSize-1, a.docStore)
|
||
if archived > 0 {
|
||
log.Printf("[agent] pruned %d low-relevance events to document memory", archived)
|
||
}
|
||
|
||
if !isInterrupt {
|
||
a.context.Append(ContextEvent{
|
||
Timestamp: start,
|
||
Source: evt.Source,
|
||
Input: input,
|
||
})
|
||
}
|
||
|
||
response, toolsUsed, toolResults, err := a.process(input, stageCtx)
|
||
if err != nil {
|
||
log.Printf("[agent] process %s error: %v", evt.Type, err)
|
||
resp := fmt.Sprintf("处理错误: %v", err)
|
||
a.emitResponse(evt, resp)
|
||
a.context.Append(ContextEvent{Timestamp: time.Now(), Source: "agent", Input: input, Response: resp})
|
||
return
|
||
}
|
||
|
||
elapsed := time.Since(start)
|
||
log.Printf("[agent] %s from %s → response (%dms, tools=%v)", evt.Type, evt.Source, elapsed.Milliseconds(), toolsUsed)
|
||
|
||
// 本轮捕获的媒体一起挂到这条事件上:用户上传的、插件注入的,以及模型调
|
||
// multimodal_see_picture / see_video 时经 SetToolBlocks 注入的(后者在
|
||
// process() 里被捕获,纯文本输入也会有)。
|
||
turnEvt := ContextEvent{
|
||
Timestamp: time.Now(),
|
||
Source: "agent",
|
||
Input: cleanInput,
|
||
Response: response,
|
||
ToolsUsed: toolsUsed,
|
||
ToolResults: toolResults,
|
||
}
|
||
a.bindEventMedia(&turnEvt, a.drainMediaDigests())
|
||
a.context.Append(turnEvt)
|
||
|
||
a.emitResponse(evt, response)
|
||
|
||
if !stageCtx.NoMemory {
|
||
a.emitMemoryCandidate(evt.Source, cleanInput, response, toolResults, toolsUsed)
|
||
}
|
||
}
|
||
|
||
func (a *Agent) emitResponse(evt *agentIO.InputEvent, response string) {
|
||
stageCtx := &sdk.StageContext{
|
||
FinalText: response,
|
||
Phase: sdk.StageBeforeOutput,
|
||
}
|
||
a.runStage(sdk.StageBeforeOutput, stageCtx)
|
||
response = stageCtx.FinalText
|
||
|
||
ch := a.currentOutputChannel
|
||
if ch == "" {
|
||
ch = evt.OutputChannel
|
||
}
|
||
if ch == "" {
|
||
ch = evt.Source
|
||
}
|
||
|
||
payload := map[string]interface{}{
|
||
"content": response,
|
||
"request_id": evt.RequestID,
|
||
}
|
||
if stageCtx.ReasoningContent != "" {
|
||
payload["reasoning_content"] = stageCtx.ReasoningContent
|
||
}
|
||
if stageCtx.TokenUsage != nil {
|
||
payload["usage"] = stageCtx.TokenUsage
|
||
}
|
||
if evt.ResponseCh != nil {
|
||
evt.ResponseCh <- &agentIO.OutputEvent{
|
||
RequestID: evt.RequestID,
|
||
Target: evt.Source,
|
||
Type: "text",
|
||
Payload: payload,
|
||
Done: true,
|
||
OutputChannel: ch,
|
||
}
|
||
}
|
||
|
||
out := map[string]interface{}{
|
||
"content": response,
|
||
"channel": ch,
|
||
"source": evt.Source,
|
||
}
|
||
if stageCtx.ReasoningContent != "" {
|
||
out["reasoning_content"] = stageCtx.ReasoningContent
|
||
}
|
||
a.publishEvent(events.EventAgentOutput, out)
|
||
stageCtx.Phase = sdk.StageAfterOutput
|
||
a.runStage(sdk.StageAfterOutput, stageCtx)
|
||
}
|
||
|
||
func (a *Agent) drainInterrupts() []string {
|
||
var out []string
|
||
for {
|
||
select {
|
||
case evt := <-a.interceptCh:
|
||
if evt == nil {
|
||
continue
|
||
}
|
||
text, _ := evt.Payload["content"].(string)
|
||
if text == "" {
|
||
continue
|
||
}
|
||
source := evt.Source
|
||
if source == "" {
|
||
source = "unknown"
|
||
}
|
||
channel := evt.OutputChannel
|
||
if channel == "" {
|
||
channel = source
|
||
}
|
||
out = append(out, fmt.Sprintf("[打断消息][来源:%s][输出通道:%s] %s", source, channel, text))
|
||
default:
|
||
return out
|
||
}
|
||
}
|
||
}
|