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fix(relay): apply model-specific OpenAI chat capabilities #7211
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Calcium-Ion
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QuantumNous:main
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pdmaker:fix/gpt5plus-max-completion-tokens
Sep 6, 2026
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,39 @@ | ||
| package controller | ||
|
|
||
| import ( | ||
| "testing" | ||
|
|
||
| "github.com/QuantumNous/new-api/model" | ||
| "github.com/QuantumNous/new-api/relaykit/dto" | ||
| "github.com/stretchr/testify/require" | ||
| ) | ||
|
|
||
| func TestBuildTestRequestUsesMaxCompletionTokensForGPT5Plus(t *testing.T) { | ||
| tests := []struct { | ||
| model string | ||
| wantMaxCompletion bool | ||
| wantMaxTokensPresent bool | ||
| }{ | ||
| {model: "o3-mini", wantMaxCompletion: true}, | ||
| {model: "gpt-5.6-luna", wantMaxCompletion: true}, | ||
| {model: "gpt-6-astra", wantMaxCompletion: true}, | ||
| {model: "gpt-4.1-nano", wantMaxTokensPresent: true}, | ||
| {model: "gpt-4o", wantMaxTokensPresent: true}, | ||
| } | ||
|
|
||
| for _, tt := range tests { | ||
| t.Run(tt.model, func(t *testing.T) { | ||
| req, ok := buildTestRequest(tt.model, "", &model.Channel{}, false).(*dto.GeneralOpenAIRequest) | ||
| require.True(t, ok) | ||
| if tt.wantMaxCompletion { | ||
| require.NotNil(t, req.MaxCompletionTokens) | ||
| require.Equal(t, uint(16), *req.MaxCompletionTokens) | ||
| require.Nil(t, req.MaxTokens) | ||
| } | ||
| if tt.wantMaxTokensPresent { | ||
| require.NotNil(t, req.MaxTokens) | ||
| require.Nil(t, req.MaxCompletionTokens) | ||
| } | ||
| }) | ||
| } | ||
| } |
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🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
Apply the GPT-5 token rule to the explicit OpenAI path.
buildTestRequestreturns from theconstant.EndpointTypeOpenAIbranch before this condition runs. A GPT-5 request with that endpoint still setsMaxTokens, notMaxCompletionTokens, and can fail the GPT-5 request contract. Apply the same model check in the explicit branch or share token-field selection between both paths. Add a regression case for the explicit endpoint.🤖 Prompt for AI Agents