feat: implement Top-K sampling for improved user control (#1110)

This commit adds Top-K sampling, a feature that allows users to control
the randomness of the generated text by specifying the number of most
probable next words considered by the model. This enhances user control
and potentially improves the quality of the generated outputs.

Fixes: https://github.com/k8sgpt-ai/k8sgpt/issues/1105

Signed-off-by: VaibhavMalik4187 <vaibhavmalik2018@gmail.com>
Co-authored-by: Alex Jones <alexsimonjones@gmail.com>

pkg/ai/amazonsagemaker.go

@@ -33,6 +33,7 @@ type SageMakerAIClient struct {
 	temperature float32
 	endpoint    string
 	topP        float32
+	topK        int32
 	maxTokens   int
 }
 
@@ -56,6 +57,7 @@ type Message struct {
 type Parameters struct {
 	MaxNewTokens int     `json:"max_new_tokens"`
 	TopP         float64 `json:"top_p"`
+	TopK         float64 `json:"top_k"`
 	Temperature  float64 `json:"temperature"`
 }
 
@@ -74,6 +76,7 @@ func (c *SageMakerAIClient) Configure(config IAIConfig) error {
 	c.temperature = config.GetTemperature()
 	c.maxTokens = config.GetMaxTokens()
 	c.topP = config.GetTopP()
+	c.topK = config.GetTopK()
 	return nil
 }
 
@@ -90,6 +93,7 @@ func (c *SageMakerAIClient) GetCompletion(_ context.Context, prompt string) (str
 		Parameters: Parameters{
 			MaxNewTokens: int(c.maxTokens),
 			TopP:         float64(c.topP),
+			TopK:         float64(c.topK),
 			Temperature:  float64(c.temperature),
 		},
 	}