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/huggingface.go

@@ -2,6 +2,7 @@ package ai
 
 import (
 	"context"
+
 	"github.com/hupe1980/go-huggingface"
 	"k8s.io/utils/ptr"
 )
@@ -14,6 +15,7 @@ type HuggingfaceClient struct {
 	client      *huggingface.InferenceClient
 	model       string
 	topP        float32
+	topK        int32
 	temperature float32
 	maxTokens   int
 }
@@ -26,6 +28,7 @@ func (c *HuggingfaceClient) Configure(config IAIConfig) error {
 	c.client = client
 	c.model = config.GetModel()
 	c.topP = config.GetTopP()
+	c.topK = config.GetTopK()
 	c.temperature = config.GetTemperature()
 	if config.GetMaxTokens() > 500 {
 		c.maxTokens = 500
@@ -43,6 +46,7 @@ func (c *HuggingfaceClient) GetCompletion(ctx context.Context, prompt string) (s
 		Model: c.model,
 		Parameters: huggingface.ConversationalParameters{
 			TopP:        ptr.To[float64](float64(c.topP)),
+			TopK:        ptr.To[int](int(c.topK)),
 			Temperature: ptr.To[float64](float64(c.temperature)),
 			MaxLength:   &c.maxTokens,
 		},