Refactor(go-models)/llm token usage for longcat (#17480)

### Summary Add token usage reporting for the LongCat (Meituan) model provider. Related to #17284. Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-07-29 12:09:31 +08:00 · 2026-07-28 21:08:51 +08:00
parent 996c5156e5
commit b02df503ac
2 changed files with 218 additions and 39 deletions
--- a/internal/entity/models/longcat.go
+++ b/internal/entity/models/longcat.go
@@ -51,6 +51,31 @@ func (l *LongCatModel) Name() string {
 	return "longcat"
 }

+// LongCatChatResponse mirrors the OpenAI-compatible response returned by
+// LongCat's POST /openai/v1/chat/completions endpoint. Usage is always
+// present on a successful response.
+type LongCatChatResponse struct {
+	ID      string `json:"id"`
+	Object  string `json:"object"`
+	Created int64  `json:"created"`
+	Model   string `json:"model"`
+	Choices []struct {
+		Index        int    `json:"index"`
+		FinishReason string `json:"finish_reason"`
+		Message      struct {
+			Role             string           `json:"role"`
+			Content          string           `json:"content"`
+			ReasoningContent string           `json:"reasoning_content"`
+			ToolCalls        []map[string]any `json:"tool_calls"`
+		} `json:"message"`
+	} `json:"choices"`
+	Usage struct {
+		PromptTokens     int `json:"prompt_tokens"`
+		CompletionTokens int `json:"completion_tokens"`
+		TotalTokens      int `json:"total_tokens"`
+	} `json:"usage"`
+}
+
 // ChatWithMessages sends multiple messages with roles and returns the response.
 func (l *LongCatModel) ChatWithMessages(ctx context.Context, modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig, modelUsage *common.ModelUsage) (*ChatResponse, error) {
 	if err := l.baseModel.APIConfigCheck(apiConfig); err != nil {
@@ -102,47 +127,48 @@ func (l *LongCatModel) ChatWithMessages(ctx context.Context, modelName string, m
 		return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
 	}

-	var result map[string]interface{}
-	if err = json.Unmarshal(body, &result); err != nil {
-		return nil, fmt.Errorf("failed to parse response: %w", err)
-	}
+	return parseChatCompletionResponse(body, chatModelConfig, modelUsage, func(body []byte, chatConfig *ChatConfig) (chatResponseParts, error) {
+		var result LongCatChatResponse
+		if err := json.Unmarshal(body, &result); err != nil {
+			return chatResponseParts{}, fmt.Errorf("failed to parse response: %w", err)
+		}
+		if len(result.Choices) == 0 {
+			return chatResponseParts{}, fmt.Errorf("no choices in response")
+		}

-	choices, ok := result["choices"].([]interface{})
-	if !ok || len(choices) == 0 {
-		return nil, fmt.Errorf("no choices in response")
-	}
+		choice := &result.Choices[0]
+		content := choice.Message.Content
+		// LongCat-Flash-Thinking may emit all output as reasoning_content
+		// with content left null/empty. That is a valid response — only
+		// reject when there is neither content, reasoning, nor tool calls.
+		if content == "" && choice.Message.ReasoningContent == "" && len(choice.Message.ToolCalls) == 0 {
+			return chatResponseParts{}, fmt.Errorf("invalid content format")
+		}

-	firstChoice, ok := choices[0].(map[string]interface{})
-	if !ok {
-		return nil, fmt.Errorf("invalid choice format")
-	}
+		// LongCat 2.0 returns the chain-of-thought in a
+		// `reasoning_content` field on the message (OpenAI o-series shape,
+		// also used by kimi-k2.6 and DeepSeek-R1). The field is typically
+		// prefixed with a leading newline — trim it so callers see clean
+		// reasoning. Absent or empty means no reasoning was emitted.
+		reasonContent := choice.Message.ReasoningContent
+		if reasonContent != "" && reasonContent[0] == '\n' {
+			reasonContent = reasonContent[1:]
+		}

-	messageMap, ok := firstChoice["message"].(map[string]interface{})
-	if !ok {
-		return nil, fmt.Errorf("invalid message format")
-	}
+		usage := &TokenUsage{
+			PromptTokens:     result.Usage.PromptTokens,
+			CompletionTokens: result.Usage.CompletionTokens,
+			TotalTokens:      result.Usage.TotalTokens,
+		}

-	content, ok := messageMap["content"].(string)
-	toolCalls := extractToolCalls(messageMap)
-	if !ok && len(toolCalls) == 0 {
-		return nil, fmt.Errorf("invalid content format")
-	}
-
-	// LongCat-Flash-Thinking returns the chain-of-thought in a
-	// `reasoning_content` field on the message (OpenAI o-series shape,
-	// also used by kimi-k2.6 and DeepSeek-R1). Pass it through when
-	// present so callers can surface reasoning to the UI. Absent or
-	// non-string means no reasoning was emitted — leave it empty.
-	reasonContent := ""
-	if r, ok := messageMap["reasoning_content"].(string); ok {
-		reasonContent = r
-	}
-
-	return &ChatResponse{
-		Answer:        &content,
-		ReasonContent: &reasonContent,
-		ToolCalls:     toolCalls,
-	}, nil
+		return chatResponseParts{
+			RequestID:     result.ID,
+			Content:       &content,
+			ReasonContent: &reasonContent,
+			ToolCalls:     choice.Message.ToolCalls,
+			Usage:         usage,
+		}, nil
+	})
 }

 // ChatStreamlyWithSender sends messages and streams the response via the
@@ -167,13 +193,14 @@ func (l *LongCatModel) ChatStreamlyWithSender(ctx context.Context, modelName str
 	url := fmt.Sprintf("%s/%s", baseURL, l.baseModel.URLSuffix.Chat)
 	reqBody := buildRequestBody(chatModelConfig, modelName, messages, true)
 	delete(reqBody, "stop")
+	reqBody["stream_options"] = map[string]any{"include_usage": true}

 	if chatModelConfig != nil {
 		if chatModelConfig.Stream != nil && !*chatModelConfig.Stream {
 			return fmt.Errorf("stream must be true in ChatStreamlyWithSender")
 		}
-
-		// Only documented fields are forwarded; see ChatWithMessages.
+		chatModelConfig.ToolCallsResult = nil
+		chatModelConfig.UsageResult = nil
 	}

 	jsonData, err := json.Marshal(reqBody)
@@ -208,6 +235,14 @@ func (l *LongCatModel) ChatStreamlyWithSender(ctx context.Context, modelName str
 			return fmt.Errorf("longcat: upstream stream error: %v", apiErr)
 		}

+		tokenUsage, found, usageErr := decodeOpenAICompatibleStreamUsage(event)
+		if usageErr != nil {
+			return usageErr
+		}
+		if found {
+			applyStreamUsage(chatModelConfig, modelUsage, tokenUsage)
+		}
+
 		choices, ok := event["choices"].([]interface{})
 		if !ok || len(choices) == 0 {
 			return nil
--- a/internal/entity/models/longcat_test.go
+++ b/internal/entity/models/longcat_test.go
@@ -176,6 +176,150 @@ func TestLongCatChatExtractsReasoningContent(t *testing.T) {
 	}
 }

+// TestLongCatChatParsesUsage verifies that the typed LongCat response
+// parser extracts the OpenAI-compatible usage block into ChatResponse.Usage.
+// LongCat always returns usage on success, so the field must be populated.
+func TestLongCatChatParsesUsage(t *testing.T) {
+	ctx := t.Context()
+	srv := newLongCatServer(t, "/openai/v1/chat/completions", func(t *testing.T, _ *http.Request, body map[string]interface{}, w http.ResponseWriter) {
+		_ = json.NewEncoder(w).Encode(map[string]interface{}{
+			"id":      "chatcmpl-abc123",
+			"object":  "chat.completion",
+			"created": 1700000000,
+			"model":   "LongCat-2.0",
+			"choices": []map[string]interface{}{{
+				"index": 0,
+				"message": map[string]interface{}{
+					"role":    "assistant",
+					"content": "Hello!",
+				},
+				"finish_reason": "stop",
+			}},
+			"usage": map[string]interface{}{
+				"prompt_tokens":     20,
+				"completion_tokens": 15,
+				"total_tokens":      35,
+			},
+		})
+	})
+	defer srv.Close()
+
+	m := newLongCatForTest(srv.URL)
+	apiKey := "test-key"
+	resp, err := m.ChatWithMessages(ctx, "LongCat-2.0",
+		[]Message{{Role: "user", Content: "ping"}},
+		&APIConfig{ApiKey: &apiKey}, nil, nil)
+	if err != nil {
+		t.Fatalf("Chat: %v", err)
+	}
+	if resp.Usage == nil {
+		t.Fatal("Usage must be non-nil")
+	}
+	if resp.Usage.PromptTokens != 20 {
+		t.Errorf("PromptTokens=%d, want 20", resp.Usage.PromptTokens)
+	}
+	if resp.Usage.CompletionTokens != 15 {
+		t.Errorf("CompletionTokens=%d, want 15", resp.Usage.CompletionTokens)
+	}
+	if resp.Usage.TotalTokens != 35 {
+		t.Errorf("TotalTokens=%d, want 35", resp.Usage.TotalTokens)
+	}
+}
+
+// TestLongCatChatAcceptsReasoningOnlyResponse verifies that a response with
+// null content but non-empty reasoning_content is accepted. LongCat's
+// thinking model can emit all output as reasoning_content, leaving content
+// null — that is a valid response, not an error.
+func TestLongCatChatAcceptsReasoningOnlyResponse(t *testing.T) {
+	ctx := t.Context()
+	srv := newLongCatServer(t, "/openai/v1/chat/completions", func(t *testing.T, _ *http.Request, _ map[string]interface{}, w http.ResponseWriter) {
+		_ = json.NewEncoder(w).Encode(map[string]interface{}{
+			"id":     "cmpl_reasoning_only",
+			"object": "chat.completion",
+			"model":  "LongCat-2.0",
+			"choices": []map[string]interface{}{{
+				"index": 0,
+				"message": map[string]interface{}{
+					"role":              "assistant",
+					"content":           nil,
+					"reasoning_content": "\nThe answer is 4.",
+				},
+				"finish_reason": "stop",
+			}},
+			"usage": map[string]interface{}{
+				"prompt_tokens":     5,
+				"completion_tokens": 10,
+				"total_tokens":      15,
+			},
+		})
+	})
+	defer srv.Close()
+
+	m := newLongCatForTest(srv.URL)
+	apiKey := "test-key"
+	resp, err := m.ChatWithMessages(ctx, "LongCat-2.0",
+		[]Message{{Role: "user", Content: "what is 2+2"}},
+		&APIConfig{ApiKey: &apiKey}, nil, nil)
+	if err != nil {
+		t.Fatalf("Chat: %v (should not error on reasoning-only response)", err)
+	}
+	if resp.Answer == nil {
+		t.Error("Answer must be non-nil")
+	} else if *resp.Answer != "" {
+		t.Errorf("Answer=%q, want empty string", *resp.Answer)
+	}
+	if resp.ReasonContent == nil {
+		t.Error("ReasonContent must be non-nil")
+	} else if *resp.ReasonContent != "The answer is 4." {
+		t.Errorf("ReasonContent=%q, want 'The answer is 4.'", *resp.ReasonContent)
+	}
+	if resp.Usage == nil {
+		t.Error("Usage must be non-nil")
+	} else if resp.Usage.TotalTokens != 15 {
+		t.Errorf("Usage=%#v, want total=15", resp.Usage)
+	}
+}
+
+// TestLongCatStreamRequestsIncludeUsage verifies that the streaming driver
+// asks LongCat for aggregate token usage via stream_options.include_usage,
+// and that the usage event populates chatConfig.UsageResult.
+func TestLongCatStreamRequestsIncludeUsage(t *testing.T) {
+	ctx := t.Context()
+	srv := newLongCatServer(t, "/openai/v1/chat/completions", func(t *testing.T, _ *http.Request, body map[string]interface{}, w http.ResponseWriter) {
+		streamOpts, ok := body["stream_options"].(map[string]interface{})
+		if !ok {
+			t.Errorf("stream_options missing: %v", body)
+			return
+		}
+		if inc, _ := streamOpts["include_usage"].(bool); !inc {
+			t.Errorf("stream_options.include_usage=%v, want true", streamOpts["include_usage"])
+		}
+		w.Header().Set("Content-Type", "text/event-stream")
+		_, _ = io.WriteString(w,
+			`data: {"choices":[{"index":0,"delta":{"content":"hi"}}]}`+"\n"+
+				`data: {"choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":10,"completion_tokens":2,"total_tokens":12}}`+"\n"+
+				`data: [DONE]`+"\n")
+	})
+	defer srv.Close()
+
+	m := newLongCatForTest(srv.URL)
+	apiKey := "test-key"
+	chatConfig := &ChatConfig{}
+	err := m.ChatStreamlyWithSender(ctx, "LongCat-2.0",
+		[]Message{{Role: "user", Content: "x"}},
+		&APIConfig{ApiKey: &apiKey}, chatConfig, nil,
+		func(*string, *string) error { return nil })
+	if err != nil {
+		t.Fatalf("stream: %v", err)
+	}
+	if chatConfig.UsageResult == nil {
+		t.Fatal("UsageResult must be non-nil after stream with usage event")
+	}
+	if chatConfig.UsageResult.PromptTokens != 10 || chatConfig.UsageResult.CompletionTokens != 2 || chatConfig.UsageResult.TotalTokens != 12 {
+		t.Errorf("UsageResult=%#v, want prompt=10 completion=2 total=12", chatConfig.UsageResult)
+	}
+}
+
 // TestLongCatChatDropsUndocumentedFields guards against re-introducing
 // stop / reasoning_effort / response_format / tools etc. The LongCat
 // docs only list model, messages, stream, max_tokens, temperature,