fix: test using the correct path for rerank (#2736)

* fix: test using the correct path for rerank.

* fix: The `input` parameter for testing responses uses an array to accommodate certain channels, such as Codex, which are incompatible with single strings.

controller/channel-test.go

@@ -84,6 +84,11 @@ func testChannel(channel *model.Channel, testModel string, endpointType string)
 		}
 	} else {
 		// 如果没有指定端点类型，使用原有的自动检测逻辑
+
+		if strings.Contains(strings.ToLower(testModel), "rerank") {
+			requestPath = "/v1/rerank"
+		}
+
 		// 先判断是否为 Embedding 模型
 		if strings.Contains(strings.ToLower(testModel), "embedding") ||
 			strings.HasPrefix(testModel, "m3e") || // m3e 系列模型
@@ -456,7 +461,7 @@ func buildTestRequest(model string, endpointType string, channel *model.Channel)
 			// 返回 OpenAIResponsesRequest
 			return &dto.OpenAIResponsesRequest{
 				Model: model,
-				Input: json.RawMessage("\"hi\""),
+				Input: json.RawMessage(`[{"role":"user","content":"hi"}]`),
 			}
 		case constant.EndpointTypeAnthropic, constant.EndpointTypeGemini, constant.EndpointTypeOpenAI:
 			// 返回 GeneralOpenAIRequest
@@ -479,6 +484,15 @@ func buildTestRequest(model string, endpointType string, channel *model.Channel)
 	}
 
 	// 自动检测逻辑（保持原有行为）
+	if strings.Contains(strings.ToLower(model), "rerank") {
+		return &dto.RerankRequest{
+			Model:     model,
+			Query:     "What is Deep Learning?",
+			Documents: []any{"Deep Learning is a subset of machine learning.", "Machine learning is a field of artificial intelligence."},
+			TopN:      2,
+		}
+	}
+
 	// 先判断是否为 Embedding 模型
 	if strings.Contains(strings.ToLower(model), "embedding") ||
 		strings.HasPrefix(model, "m3e") ||
@@ -494,7 +508,7 @@ func buildTestRequest(model string, endpointType string, channel *model.Channel)
 	if strings.Contains(strings.ToLower(model), "codex") {
 		return &dto.OpenAIResponsesRequest{
 			Model: model,
-			Input: json.RawMessage("\"hi\""),
+			Input: json.RawMessage(`[{"role":"user","content":"hi"}]`),
 		}
 	}