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📝 Add docstrings to fix/channel-test-responses-fallback

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Docstrings generation was requested by @FlowerRealm.

* https://github.com/QuantumNous/new-api/pull/2501#issuecomment-3686382220

The following files were modified:

* `controller/channel-test.go`
* `relay/helper/valid_request.go`
* `service/error.go`
This commit is contained in:
coderabbitai[bot]
2025-12-23 11:56:30 +00:00
committed by GitHub
parent 42109c5840
commit 40a3e19a78
3 changed files with 54 additions and 8 deletions
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40
controller/channel-test.go
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@@ -40,6 +40,13 @@ type testResult struct {
newAPIError *types.NewAPIError
}
// testChannel executes a test request against the given channel using the provided testModel and optional endpointType,
// and returns a testResult containing the test context and any encountered error information.
// It selects or derives a model when testModel is empty, auto-detects the request endpoint (chat, responses, embeddings, images, rerank) when endpointType is not specified,
// converts and relays the request to the upstream adapter, and parses the upstream response to collect usage and pricing information.
// On upstream responses that indicate the chat/completions `messages` parameter is unsupported and endpointType was not specified, it will retry the test using the Responses API.
// The function records consumption logs and returns a testResult with a populated context on success, or with localErr/newAPIError set on failure;
// for channel types that are not supported for testing it returns a localErr explaining that the channel test is not supported.
func testChannel(channel *model.Channel, testModel string, endpointType string) testResult {
tik := time.Now()
var unsupportedTestChannelTypes = []int{
@@ -75,6 +82,8 @@ func testChannel(channel *model.Channel, testModel string, endpointType string)
}
}
originTestModel := testModel
requestPath := "/v1/chat/completions"
// 如果指定了端点类型，使用指定的端点类型
@@ -84,6 +93,10 @@ 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 common.IsOpenAIResponseOnlyModel(testModel) {
requestPath = "/v1/responses"
}
// 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
@@ -319,6 +332,13 @@ func testChannel(channel *model.Channel, testModel string, endpointType string)
httpResp = resp.(*http.Response)
if httpResp.StatusCode != http.StatusOK {
err := service.RelayErrorHandler(c.Request.Context(), httpResp, true)
// 自动检测模式下，如果上游不支持 chat.completions 的 messages 参数，尝试切换到 Responses API 再测一次。
if endpointType == "" && requestPath == "/v1/chat/completions" && err != nil {
lowerErr := strings.ToLower(err.Error())
if strings.Contains(lowerErr, "unsupported parameter") && strings.Contains(lowerErr, "messages") {
return testChannel(channel, originTestModel, string(constant.EndpointTypeOpenAIResponse))
}
}
return testResult{
context: c,
localErr: err,
@@ -389,6 +409,7 @@ func testChannel(channel *model.Channel, testModel string, endpointType string)
}
}
// for embedding models, and otherwise a chat/completion request with model-specific token limit heuristics.
func buildTestRequest(model string, endpointType string) dto.Request {
// 根据端点类型构建不同的测试请求
if endpointType != "" {
@@ -417,9 +438,12 @@ func buildTestRequest(model string, endpointType string) dto.Request {
}
case constant.EndpointTypeOpenAIResponse:
// 返回 OpenAIResponsesRequest
maxOutputTokens := uint(10)
return &dto.OpenAIResponsesRequest{
Model: model,
Input: json.RawMessage("\"hi\""),
Model: model,
Input: json.RawMessage(`[{"role":"user","content":"hi"}]`),
MaxOutputTokens: maxOutputTokens,
Stream: true,
}
case constant.EndpointTypeAnthropic, constant.EndpointTypeGemini, constant.EndpointTypeOpenAI:
// 返回 GeneralOpenAIRequest
@@ -442,6 +466,16 @@ func buildTestRequest(model string, endpointType string) dto.Request {
}
// 自动检测逻辑（保持原有行为）
if common.IsOpenAIResponseOnlyModel(model) {
maxOutputTokens := uint(10)
return &dto.OpenAIResponsesRequest{
Model: model,
Input: json.RawMessage(`[{"role":"user","content":"hi"}]`),
MaxOutputTokens: maxOutputTokens,
Stream: true,
}
}
// 先判断是否为 Embedding 模型
if strings.Contains(strings.ToLower(model), "embedding") ||
strings.HasPrefix(model, "m3e") ||
@@ -640,4 +674,4 @@ func AutomaticallyTestChannels() {
}
}
})
}
}