feat(ai-core): real vision image analysis

- llm: Adapter.Vision sends multimodal chat requests (text + image_url,
  data URLs supported) and logs the call as purpose 'vision'
- gateway /images/analyze now accepts image_url or image_base64 and
  returns real analysis instead of a placeholder message
- main wires the default LLM adapter as the vision analyzer
- httptest coverage for the vision request/response shape

backend/cmd/cyrene/main.go

@@ -315,6 +315,7 @@ func main() {
 		gwDeps.ChatStore = chatStore
 	}
 	gwDeps.VoiceSvc = voiceSvc
+	gwDeps.Vision = visionAdapter{llmSelector.DefaultAdapter()}
 
 	wsHub := ws.NewHub(orch)
 	gwDeps.WSHub = wsHub
@@ -462,6 +463,17 @@ func (a *perfAdapter) History() []map[string]any {
 	return result
 }
 
+// visionAdapter adapts the LLM adapter to api.VisionAnalyzer.
+type visionAdapter struct{ llm *llm.Adapter }
+
+func (v visionAdapter) AnalyzeImage(ctx context.Context, prompt, imageRef string) (string, error) {
+	resp, err := v.llm.Vision(ctx, prompt, imageRef)
+	if err != nil {
+		return "", err
+	}
+	return resp.Content, nil
+}
+
 // automationSourceAdapter adapts api.AutomationStore to engine.RuleSource.
 type automationSourceAdapter struct{ s *api.AutomationStore }
 

backend/services/ai-core/llm/llm.go

@@ -76,6 +76,42 @@ type CallRecord struct {
 	Error          string
 }
 
+// Vision sends a prompt plus an image (URL or data URL) to a multimodal model
+// and returns the analysis text.
+func (a *Adapter) Vision(ctx context.Context, prompt, imageRef string) (*model.LLMResponse, error) {
+	start := time.Now()
+	body := map[string]any{
+		"model": a.cfg.Model,
+		"messages": []map[string]any{
+			{
+				"role": "user",
+				"content": []map[string]any{
+					{"type": "text", "text": prompt},
+					{"type": "image_url", "image_url": map[string]string{"url": imageRef}},
+				},
+			},
+		},
+	}
+
+	resp := &model.LLMResponse{Model: a.cfg.Model}
+	err := a.doRequest(ctx, "POST", "/chat/completions", body, func(data map[string]any) error {
+		if choices, ok := data["choices"].([]any); ok && len(choices) > 0 {
+			choice := choices[0].(map[string]any)
+			if msg, ok := choice["message"].(map[string]any); ok {
+				if content, ok := msg["content"].(string); ok { resp.Content = content }
+			}
+			if reason, ok := choice["finish_reason"].(string); ok { resp.FinishReason = reason }
+		}
+		if usage, ok := data["usage"].(map[string]any); ok {
+			if total, ok := usage["total_tokens"].(float64); ok { resp.TokensUsed = int(total) }
+		}
+		return nil
+	})
+
+	a.recordCall(start, "vision", resp.TokensUsed, 0, err)
+	return resp, err
+}
+
 // ModelName returns the configured model name.
 func (a *Adapter) ModelName() string { return a.cfg.Model }
 

backend/services/ai-core/llm/llm_test.go

@@ -0,0 +1,37 @@
+package llm
+
+import (
+	"context"
+	"io"
+	"net/http"
+	"net/http/httptest"
+	"strings"
+	"testing"
+)
+
+func TestVision(t *testing.T) {
+	srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		body, _ := io.ReadAll(r.Body)
+		s := string(body)
+		if !strings.Contains(s, `"type":"image_url"`) || !strings.Contains(s, "data:image/jpeg;base64,AAAA") {
+			t.Errorf("unexpected vision request body: %s", s)
+		}
+		w.Write([]byte(`{"choices":[{"message":{"content":"图片里是一只猫"},"finish_reason":"stop"}],"usage":{"total_tokens":42}}`))
+	}))
+	defer srv.Close()
+
+	cfg := DefaultConfig()
+	cfg.BaseURL = srv.URL
+	a := NewAdapter(cfg)
+
+	resp, err := a.Vision(context.Background(), "这是什么？", "data:image/jpeg;base64,AAAA")
+	if err != nil {
+		t.Fatalf("Vision: %v", err)
+	}
+	if resp.Content != "图片里是一只猫" {
+		t.Errorf("content = %q", resp.Content)
+	}
+	if resp.TokensUsed != 42 {
+		t.Errorf("tokens = %d", resp.TokensUsed)
+	}
+}

backend/services/gateway/api/handlers_more.go

@@ -260,16 +260,35 @@ func (r *Router) sessionExportHandler(w http.ResponseWriter, req *http.Request)
 
 func (r *Router) imageAnalyzeHandler(w http.ResponseWriter, req *http.Request) {
 	if req.Method != "POST" { writeJSON(w, 405, M{"error": "POST required"}); return }
+	if r.deps.Vision == nil { writeJSON(w, 503, M{"error": "vision not available"}); return }
 	var body struct {
-		ImageURL string `json:"image_url"`
+		ImageURL    string `json:"image_url"`
-		Prompt   string `json:"prompt"`
+		ImageBase64 string `json:"image_base64"` // raw base64 or data URL
+		Prompt      string `json:"prompt"`
 	}
 	json.NewDecoder(req.Body).Decode(&body)
-	// Stub: requires multimodal LLM (GPT-4o / Qwen-VL)
+
-	writeJSON(w, 200, M{
+	imageRef := body.ImageURL
-		"analysis": "图片分析需要多模态大模型。当前为预留接口。请配置支持 vision 的 LLM provider。",
+	if imageRef == "" && body.ImageBase64 != "" {
-		"image_url": body.ImageURL, "prompt": body.Prompt,
+		imageRef = body.ImageBase64
-	})
+		if !strings.HasPrefix(imageRef, "data:") {
+			imageRef = "data:image/jpeg;base64," + imageRef
+		}
+	}
+	if imageRef == "" {
+		writeJSON(w, 400, M{"error": "missing image_url or image_base64"})
+		return
+	}
+	if body.Prompt == "" {
+		body.Prompt = "描述这张图片的内容。"
+	}
+
+	analysis, err := r.deps.Vision.AnalyzeImage(req.Context(), body.Prompt, imageRef)
+	if err != nil {
+		writeJSON(w, 500, M{"error": err.Error()})
+		return
+	}
+	writeJSON(w, 200, M{"analysis": analysis, "prompt": body.Prompt})
 }
 
 func (r *Router) hostExecHandler(w http.ResponseWriter, req *http.Request) {

backend/services/gateway/api/router.go

@@ -91,6 +91,11 @@ type AutomationEngine interface {
 	Trigger(ctx context.Context, id string) error
 }
 
+// VisionAnalyzer analyzes images with a multimodal model.
+type VisionAnalyzer interface {
+	AnalyzeImage(ctx context.Context, prompt, imageRef string) (string, error)
+}
+
 // ChatStorer persists chat sessions and messages.
 type ChatStorer interface {
 	CreateSession(ctx context.Context, id, userID, title string) (*store.Session, error)
@@ -117,6 +122,7 @@ type Dependencies struct {
 	Automation   *AutomationStore
 	AutomationEng AutomationEngine
 	Reminders    *ReminderStore
+	Vision       VisionAnalyzer
 	PluginList   []map[string]string
 }