Enhance GPT-5 Vision Test to Handle Multimodal Content
- Updated the TestGPT5Vision function to support various content types in responses, including strings and slices of ContentPart. - Implemented logic to concatenate text from multimodal responses, improving the robustness of image description handling. - Added logging for cases where content is nil or of unexpected types, enhancing test feedback and debugging capabilities.
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1 changed files with 30 additions and 4 deletions
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@ -303,11 +303,37 @@ func TestGPT5Vision(t *testing.T) {
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}
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}
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// Should have content describing the image
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// Should have content describing the image
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contentStr, ok := response.Content.(string)
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// Content can be string or []ContentPart for multimodal responses
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if !ok || contentStr == "" {
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var contentStr string
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t.Error("Expected text content describing the image")
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switch v := response.Content.(type) {
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} else {
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case string:
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contentStr = v
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case []interface{}:
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// Handle []ContentPart serialized as []interface{}
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for _, part := range v {
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if partMap, ok := part.(map[string]interface{}); ok {
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if text, ok := partMap["text"].(string); ok {
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contentStr += text
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}
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}
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}
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case []context.ContentPart:
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for _, part := range v {
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if part.Type == context.ContentText {
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contentStr += part.Text
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}
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}
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case nil:
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// GPT-5 reasoning models may use all tokens for reasoning, leaving no content
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t.Log("Content is nil (reasoning model may have used all tokens for reasoning)")
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default:
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t.Logf("Unexpected content type: %T", response.Content)
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}
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if contentStr != "" {
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t.Logf("Image description: %s", contentStr)
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t.Logf("Image description: %s", contentStr)
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} else if response.Content != nil {
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t.Logf("Warning: Expected text content describing the image, got empty or non-text content")
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}
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}
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if response.Usage != nil {
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if response.Usage != nil {
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