批次A admin 端点(原本 404 变 200 真实数据):
- GET /admin/llm:读 s.cfg.LLM 组 openai+anthropic 两 provider(enabled=当前 Provider、multimodal=配 VisionModel),APIKey 不进 wire 零泄露。
- GET /admin/automations:*automations.Service.List()(reminders+event rules+cron schedules,cron 加只读登记)。
- GET /admin/users:cfg.AdminUser + *auth.APIKey.List()(密钥掩码);无用户存储,恒先返回当前 admin 账号。
- GET /admin/backthink:*backthink.Backthink.List(ctx,50)。均只读、owner/admin RBAC、{data} 信封。
批次B 视觉真推理 + 语音:
- rest.go chatRequest 加 Image?;流式 publishChatStream 带 image;userChatMessages 构造 ImageMessage(model.go:71)。
- loop/vision.go:ImageResolver 可注入(MVP 先看图再对话);run.go Run 开头 resolveImages,无 resolver 透传直交主模型。
- vision/resolver.go:MessageResolver 调 vision.Router.Route——KindMain 保留图片交主模型多模态、KindVisionTool/OCRTool 经 dispatcher.Invoke 折叠成 [图片内容] 文本、KindUnsupported 记日志保留原图不崩。
- gateway/voice.go:VoiceService 接口 + SetVoice 注入点 + handleVoiceInput(未注入回 error 不崩)+ runVoiceTurn 异步 STT→loop chat→TTS→定向 voice_output 帧。
- ws_hub/ws_route:voice_input 接 handleVoiceInput;前端 ws.ts decodeBase64/playVoiceAudio/case voice_output。
第3步 wire.go 收口(唯一碰 wire.go 的一步):
- Deps 补传 Automations:a.automation / Backthink:a.backthink / Users:auth.NewAPIKey(a.cfg.Auth)(*auth.APIKey 原生满足 UserStore,避免 admin 重复的复合类型)。
- gw.SetVoice(a.voice);loop.Options.Vision = vision.NewMessageResolver(router, info, dispatcher.Invoke)(router=NewRouter(WithVisionTool/WithOCRTool)、info=cfg.LLM.VisionModel)。
实机验证:四 admin 端点 200 真实数据(llm 双 provider 脱敏、users=admin,yeij0942,owner);WS 握手正常。go build/vet/test 全绿 + 前端 tsc。wire.go 557 行。
124 lines
4.5 KiB
Go
124 lines
4.5 KiB
Go
package vision
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import (
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"context"
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"fmt"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/model"
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)
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// ModelInfoProvider supplies the main model's vision capability so the resolver
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// can route an image the way the vision Router decides (design/06 §0). It is
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// called per image; the same provider is shared across a single resolution.
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type ModelInfoProvider func() ModelInfo
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// ToolInvoker invokes a registered tool (the vision or OCR tool) by name with
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// the given arguments. It is satisfied by *tool.Dispatcher.Invoke.
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type ToolInvoker func(ctx context.Context, name string, args map[string]any) (any, error)
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// MessageResolver is the loop's concrete ImageResolver. For each image part in a
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// user message it asks the vision Router how to route it: when the main model
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// supports vision and is confident, the image part is kept so the main model sees
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// the image; otherwise the vision/OCR tool is invoked and its text result replaces
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// the image part, so a text-only main model can reason over the image ("先看图再
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// 对话"). It is safe for concurrent use.
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type MessageResolver struct {
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router *Router
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info ModelInfoProvider
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invoke ToolInvoker
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}
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// NewMessageResolver builds a MessageResolver. router decides the layer; info
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// reports the main model's vision capability; invoke runs a registered vision/OCR
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// tool. A nil invoke leaves any tool route failed (the image is then kept), so a
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// resolver without tools degrades to the main-model path.
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func NewMessageResolver(router *Router, info ModelInfoProvider, invoke ToolInvoker) *MessageResolver {
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return &MessageResolver{
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router: router,
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info: info,
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invoke: invoke,
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}
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}
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// Resolve rewrites msg so every image part is either kept (main model sees it) or
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// replaced by a text description produced by the vision/OCR tool. Text parts are
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// preserved in order. It errors only when an image cannot be routed or a tool
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// invocation fails; the caller (loop) then keeps the original message.
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func (r *MessageResolver) Resolve(ctx context.Context, msg model.Message) (model.Message, error) {
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if r.router == nil {
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return msg, nil
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}
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out := make([]model.Content, 0, len(msg.Content))
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for _, part := range msg.Content {
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if part.Type != model.ContentTypeImage {
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out = append(out, part)
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continue
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}
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replacement, err := r.resolveImage(ctx, part.ImageURL)
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if err != nil {
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return model.Message{}, err
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}
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out = append(out, replacement)
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}
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return model.Message{Role: msg.Role, Content: out}, nil
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}
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// resolveImage picks a route and either keeps the image (KindMain) or folds it
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// into a text description via the vision/OCR tool.
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func (r *MessageResolver) resolveImage(ctx context.Context, imageURL string) (model.Content, error) {
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target := ModelInfo{}
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if r.info != nil {
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target = r.info()
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}
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decision := r.router.Route(target, RouteRequest{})
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switch decision.Kind {
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case KindMain:
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// A vision-capable main model sees the image directly.
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return model.Content{Type: model.ContentTypeImage, ImageURL: imageURL}, nil
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case KindVisionTool:
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return r.invokeTool(ctx, decision.Tool, map[string]any{
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"image": imageURL,
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"prompt": "Describe this image in detail.",
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}, "description")
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case KindOCRTool:
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return r.invokeTool(ctx, decision.Tool, map[string]any{
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"image": imageURL,
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}, "text")
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default:
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return model.Content{}, fmt.Errorf("image route: %w: %s", ErrUnsupportedSource, decision.Reason)
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}
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}
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// invokeTool runs a registered vision/OCR tool and turns its text result into a
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// text content part. field is the result map key ("description" or "text").
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func (r *MessageResolver) invokeTool(ctx context.Context, toolName string, args map[string]any, field string) (model.Content, error) {
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if r.invoke == nil {
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return model.Content{}, fmt.Errorf("%s: %w", toolName, ErrNotConfigured)
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}
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result, err := r.invoke(ctx, toolName, args)
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if err != nil {
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return model.Content{}, fmt.Errorf("image tool %s: %w", toolName, err)
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}
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return model.Content{Type: model.ContentTypeText, Text: descriptionFragment(fieldText(result, field))}, nil
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}
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// fieldText extracts a string field from a tool result map, tolerating the
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// map[string]any shape returned by the vision/OCR tools.
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func fieldText(result any, field string) string {
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m, ok := result.(map[string]any)
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if !ok {
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return ""
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}
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s, _ := m[field].(string)
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return s
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}
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// descriptionFragment labels a tool-produced description so the model can tell it
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// refers to the picture the user attached.
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func descriptionFragment(desc string) string {
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if desc == "" {
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return "[图片内容] 无法识别该图片"
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}
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return "[图片内容] " + desc
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}
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