cneicy/new-api-custom
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feat: sync deployed v1.0.0-rc.38-custom.67

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cneicy committed 2026-10-06 00:07:10 +08:00
1 parent d2e03ab7e8
commit ffc8cf56db
154 files changed
+39540 -20509
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controller/detection.go
+12 -13
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@@ -16,6 +16,7 @@ import (
"github.com/QuantumNous/new-api/common"
"github.com/QuantumNous/new-api/middleware"
"github.com/QuantumNous/new-api/model"
benchmark "github.com/QuantumNous/new-api/pkg/model_benchmark"
fingerprint "github.com/QuantumNous/new-api/pkg/model_fingerprint"
"github.com/QuantumNous/new-api/relay"
relaycommon "github.com/QuantumNous/new-api/relay/common"
@@ -41,7 +42,7 @@ func detectionInput(c *gin.Context) (detectionRequest, *model.User, service.Dete
if err := c.ShouldBindJSON(&input); err != nil {
return input, nil, service.DetectionPrice{}, 0, errors.New("invalid detection request")
}
if input.Kind != "pelican" && input.Kind != "fingerprint" {
if input.Kind != "benchmark" && input.Kind != "fingerprint" {
return input, nil, service.DetectionPrice{}, 0, errors.New("invalid detection type")
}
user, err := model.GetUserById(c.GetInt("id"), false)
@@ -62,9 +63,9 @@ func EstimateDetection(c *gin.Context) {
return
}
encoded, _ := common.Marshal(price)
calls := 1
calls := benchmark.ProbeCount
if input.Kind == "fingerprint" {
calls = 3
calls = fingerprint.ProbeCount
}
c.JSON(200, gin.H{"success": true, "data": gin.H{"reserved": reserve, "ratio": price.Snapshot.GroupRatio, "calls": calls, "price_version": model.DetectionSecretHash(string(encoded))}})
}
@@ -267,7 +268,7 @@ func detectionProxyRequest(data []byte) (*dto.OpenAIResponsesRequest, error) {
return nil, errors.New("input too large")
}
// Service-selected bounds cannot be overridden by the bearer.
fields = map[string]any{"model": fingerprint.Model, "input": fields["input"], "instructions": instructions, "stream": true, "max_output_tokens": 16384, "reasoning": map[string]string{"effort": "high"}, "store": false, "tools": []any{}}
fields = map[string]any{"model": fingerprint.Model, "input": fields["input"], "instructions": instructions, "stream": true, "max_output_tokens": 16384, "reasoning": map[string]string{"effort": "medium"}, "store": false, "tools": []any{}}
encoded, _ := common.Marshal(fields)
var request dto.OpenAIResponsesRequest
err = common.Unmarshal(encoded, &request)
@@ -342,14 +343,6 @@ func DetectionProxy(c *gin.Context) {
}
}
}
if success {
if html := detectionHTML(raw, contentType); html != "" {
if saveErr := model.DB.Model(&model.DetectionRun{}).Where("id = ?", run.ID).Update("html", html).Error; saveErr != nil {
call.Error = "artwork_save_failed"
success = false
}
}
}
if err = model.FinishDetectionCall(call); err != nil {
success = false
}
@@ -481,7 +474,13 @@ func boundDetectionBody(body common.ReplayableBody, request *dto.OpenAIResponses
prepared["instructions"] = instructions
prepared["max_output_tokens"] = *request.MaxOutputTokens
if *request.MaxOutputTokens == 16384 {
prepared["reasoning"] = map[string]string{"effort": "high"}
prepared["reasoning"] = map[string]string{"effort": "medium"}
}
if *request.MaxOutputTokens == fingerprint.OutputTokens || *request.MaxOutputTokens == benchmark.OutputTokens {
prepared["reasoning"] = map[string]string{"effort": "low"}
delete(prepared, "instructions")
delete(prepared, "temperature")
delete(prepared, "top_p")
}
prepared["tools"] = []any{}
prepared["tool_choice"] = "none"