Fix param name

examples/llm_bash/main.go

@@ -13,7 +13,7 @@ import (
 
 func main() {
 	openai, err := llm.NewOpenAI(os.Getenv("OPENAI_API_KEY"), func(o *llm.OpenAIOptions) {
-		o.Temperatur = 0.01
+		o.Temperature = 0.01
 	})
 	if err != nil {
 		log.Fatal(err)

model/chatmodel/azure_openai.go

@@ -22,7 +22,7 @@ func NewAzureOpenAI(apiKey, baseURL string, optFns ...func(o *AzureOpenAIOptions
 				Verbose: golc.Verbose,
 			},
 			ModelName:        openai.GPT3Dot5Turbo,
-			Temperatur:       1,
+			Temperature:      1,
 			TopP:             1,
 			PresencePenalty:  0,
 			FrequencyPenalty: 0,

model/chatmodel/openai.go

@@ -27,7 +27,7 @@ type OpenAIOptions struct {
 	// Model name to use.
 	ModelName string
 	// Sampling temperature to use.
-	Temperatur float32
+	Temperature float32
 	// The maximum number of tokens to generate in the completion.
 	// -1 returns as many tokens as possible given the prompt and
 	//the models maximal context size.
@@ -87,7 +87,7 @@ func NewOpenAIFromClient(client OpenAIClient, optFns ...func(o *OpenAIOptions))
 			Verbose: golc.Verbose,
 		},
 		ModelName:        openai.GPT3Dot5Turbo,
-		Temperatur:       1,
+		Temperature:      1,
 		TopP:             1,
 		PresencePenalty:  0,
 		FrequencyPenalty: 0,
@@ -152,9 +152,10 @@ func (cm *OpenAI) Generate(ctx context.Context, messages schema.ChatMessages, op
 	}
 
 	res, err := cm.client.CreateChatCompletion(ctx, openai.ChatCompletionRequest{
-		Model:     cm.opts.ModelName,
-		Messages:  openAIMessages,
-		Functions: functions,
+		Model:       cm.opts.ModelName,
+		Temperature: cm.opts.Temperature,
+		Messages:    openAIMessages,
+		Functions:   functions,
 	})
 	if err != nil {
 		return nil, err

model/chatmodel/openai_test.go

@@ -25,7 +25,8 @@ func TestOpenAI_Generate(t *testing.T) {
 
 		// Define the expected arguments and response for the mock client
 		expectedRequest := openai.ChatCompletionRequest{
-			Model: openAI.opts.ModelName,
+			Model:       openAI.opts.ModelName,
+			Temperature: 1,
 			Messages: []openai.ChatCompletionMessage{
 				{Role: "user", Content: "Hello"},
 				{Role: "assistant", Content: "Hi there"},
@@ -63,7 +64,8 @@ func TestOpenAI_Generate(t *testing.T) {
 
 		// Define the expected arguments and error for the mock client
 		expectedRequest := openai.ChatCompletionRequest{
-			Model: openAI.opts.ModelName,
+			Model:       openAI.opts.ModelName,
+			Temperature: 1,
 			Messages: []openai.ChatCompletionMessage{
 				{Role: "user", Content: "Hello"},
 				{Role: "assistant", Content: "Hi there"},

model/chatmodel/palm.go

@@ -26,7 +26,7 @@ type PalmOptions struct {
 	ModelName string `map:"model_name,omitempty"`
 
 	// Temperature is the sampling temperature to use during text generation.
-	Temperatur float32 `map:"temperatur,omitempty"`
+	Temperature float32 `map:"temperature,omitempty"`
 
 	// TopP is the total probability mass of tokens to consider at each step.
 	TopP float32 `map:"top_p,omitempty"`
@@ -51,7 +51,7 @@ func NewPalm(client PalmClient, optFns ...func(o *PalmOptions)) (*Palm, error) {
 			Verbose: golc.Verbose,
 		},
 		ModelName:      "models/chat-bison-001",
-		Temperatur:     0.7,
+		Temperature:    0.7,
 		CandidateCount: 1,
 	}
 
@@ -87,7 +87,7 @@ func (l *Palm) Generate(ctx context.Context, prompt string, optFns ...func(o *sc
 	res, err := l.client.GenerateMessage(ctx, &generativelanguagepb.GenerateMessageRequest{
 		Prompt:         &generativelanguagepb.MessagePrompt{},
 		Model:          l.opts.ModelName,
-		Temperature:    &l.opts.Temperatur,
+		Temperature:    &l.opts.Temperature,
 		TopP:           &l.opts.TopP,
 		TopK:           &l.opts.TopK,
 		CandidateCount: &l.opts.CandidateCount,

model/chatmodel/palm_test.go

@@ -73,15 +73,15 @@ func TestPalm(t *testing.T) {
 	t.Run("InvocationParams", func(t *testing.T) {
 		// Create a Palm instance
 		llm, err := NewPalm(&mockPalmClient{}, func(o *PalmOptions) {
-			o.Temperatur = 0.7
+			o.Temperature = 0.7
 		})
 		assert.NoError(t, err)
 
 		// Call the InvocationParams method
 		params := llm.InvocationParams()
 
 		// Assert the result
-		assert.Equal(t, float32(0.7), params["temperatur"])
+		assert.Equal(t, float32(0.7), params["temperature"])
 	})
 }
 

model/llm/cohere.go

@@ -35,8 +35,8 @@ type CohereOptions struct {
 	// MaxTokens denotes the number of tokens to predict per generation.
 	MaxTokens uint `map:"max_tokens"`
 
-	// Temperatur is a non-negative float that tunes the degree of randomness in generation.
-	Temperatur float64 `map:"temperature"`
+	// Temperature is a non-negative float that tunes the degree of randomness in generation.
+	Temperature float64 `map:"temperature"`
 
 	// K specifies the number of top most likely tokens to consider for generation at each step.
 	K int `map:"k"`
@@ -91,7 +91,7 @@ func NewCohereFromClient(client CohereClient, optFns ...func(o *CohereOptions))
 		Model:            "medium",
 		NumGenerations:   1,
 		MaxTokens:        256,
-		Temperatur:       0.75,
+		Temperature:      0.75,
 		K:                0,
 		P:                1,
 		FrequencyPenalty: 0,
@@ -133,7 +133,7 @@ func (l *Cohere) Generate(ctx context.Context, prompt string, optFns ...func(o *
 		Model:             l.opts.Model,
 		NumGenerations:    l.opts.NumGenerations,
 		MaxTokens:         l.opts.MaxTokens,
-		Temperature:       l.opts.Temperatur,
+		Temperature:       l.opts.Temperature,
 		K:                 l.opts.K,
 		P:                 l.opts.P,
 		PresencePenalty:   l.opts.PresencePenalty,

model/llm/openai.go

@@ -36,7 +36,7 @@ type OpenAIOptions struct {
 	// ModelName is the name of the OpenAI language model to use.
 	ModelName string `map:"model_name,omitempty"`
 	// Temperature is the sampling temperature to use during text generation.
-	Temperatur float32 `map:"temperatur,omitempty"`
+	Temperature float32 `map:"temperature,omitempty"`
 	// MaxTokens is the maximum number of tokens to generate in the completion.
 	MaxTokens int `map:"max_tokens,omitempty"`
 	// TopP is the total probability mass of tokens to consider at each step.
@@ -98,7 +98,7 @@ func NewOpenAIFromClient(client OpenAIClient, optFns ...func(o *OpenAIOptions))
 			Verbose: golc.Verbose,
 		},
 		ModelName:        openai.GPT3TextDavinci002,
-		Temperatur:       0.7,
+		Temperature:      0.7,
 		MaxTokens:        256,
 		TopP:             1,
 		PresencePenalty:  0,
@@ -140,7 +140,7 @@ func (l *OpenAI) Generate(ctx context.Context, prompt string, optFns ...func(o *
 	completionRequest := openai.CompletionRequest{
 		Prompt:           prompt,
 		Model:            l.opts.ModelName,
-		Temperature:      l.opts.Temperatur,
+		Temperature:      l.opts.Temperature,
 		MaxTokens:        l.opts.MaxTokens,
 		TopP:             l.opts.TopP,
 		PresencePenalty:  l.opts.PresencePenalty,

model/llm/palm.go

@@ -26,7 +26,7 @@ type PalmOptions struct {
 	ModelName string `map:"model_name,omitempty"`
 
 	// Temperature is the sampling temperature to use during text generation.
-	Temperatur float32 `map:"temperatur,omitempty"`
+	Temperature float32 `map:"temperature,omitempty"`
 
 	// TopP is the total probability mass of tokens to consider at each step.
 	TopP float32 `map:"top_p,omitempty"`
@@ -54,7 +54,7 @@ func NewPalm(client PalmClient, optFns ...func(o *PalmOptions)) (*Palm, error) {
 			Verbose: golc.Verbose,
 		},
 		ModelName:      "models/text-bison-001",
-		Temperatur:     0.7,
+		Temperature:    0.7,
 		CandidateCount: 1,
 	}
 
@@ -92,7 +92,7 @@ func (l *Palm) Generate(ctx context.Context, prompt string, optFns ...func(o *sc
 			Text: prompt,
 		},
 		Model:           l.opts.ModelName,
-		Temperature:     &l.opts.Temperatur,
+		Temperature:     &l.opts.Temperature,
 		TopP:            &l.opts.TopP,
 		TopK:            &l.opts.TopK,
 		MaxOutputTokens: &l.opts.MaxOutputTokens,

model/llm/palm_test.go

@@ -72,7 +72,7 @@ func TestPalm(t *testing.T) {
 	t.Run("InvocationParams", func(t *testing.T) {
 		// Create a Palm instance
 		llm, err := NewPalm(&mockPalmClient{}, func(o *PalmOptions) {
-			o.Temperatur = 0.7
+			o.Temperature = 0.7
 			o.MaxOutputTokens = 4711
 		})
 		assert.NoError(t, err)
@@ -81,7 +81,7 @@ func TestPalm(t *testing.T) {
 		params := llm.InvocationParams()
 
 		// Assert the result
-		assert.Equal(t, float32(0.7), params["temperatur"])
+		assert.Equal(t, float32(0.7), params["temperature"])
 		assert.Equal(t, int32(4711), params["max_output_tokens"])
 	})
 }

model/llm/vertexai.go

@@ -30,7 +30,7 @@ type VertexAIOptions struct {
 	schema.Tokenizer        `map:"-"`
 
 	// Temperature is the sampling temperature to use during text generation.
-	Temperatur float32 `map:"temperatur"`
+	Temperature float32 `map:"temperature"`
 
 	// MaxOutputTokens determines the maximum amount of text output from one prompt.
 	MaxOutputTokens int `map:"max_output_tokens"`
@@ -56,7 +56,7 @@ func NewVertexAI(client VertexAIClient, endpoint string, optFns ...func(o *Verte
 		CallbackOptions: &schema.CallbackOptions{
 			Verbose: golc.Verbose,
 		},
-		Temperatur:      0.0,
+		Temperature:     0.0,
 		MaxOutputTokens: 128,
 		TopP:            0.95,
 		TopK:            40,
@@ -101,7 +101,7 @@ func (l *VertexAI) Generate(ctx context.Context, prompt string, optFns ...func(o
 	}
 
 	parameters, err := structpb.NewValue(map[string]any{
-		"temperature":       l.opts.Temperatur,
+		"temperature":       l.opts.Temperature,
 		"max_output_tokens": l.opts.MaxOutputTokens,
 		"top_p":             l.opts.TopP,
 		"top_k":             l.opts.TopK,

model/llm/vertexai_test.go

@@ -76,7 +76,7 @@ func TestVertexAI_Generate(t *testing.T) {
 	t.Run("InvocationParams", func(t *testing.T) {
 		// Create a VertexAI instance
 		llm, err := NewVertexAI(&mockVertexAIClient{}, "dummy", func(o *VertexAIOptions) {
-			o.Temperatur = 0.7
+			o.Temperature = 0.7
 			o.MaxOutputTokens = 4711
 		})
 		assert.NoError(t, err)
@@ -85,7 +85,7 @@ func TestVertexAI_Generate(t *testing.T) {
 		params := llm.InvocationParams()
 
 		// Assert the result
-		assert.Equal(t, float32(0.7), params["temperatur"])
+		assert.Equal(t, float32(0.7), params["temperature"])
 		assert.Equal(t, 4711, params["max_output_tokens"])
 	})
 }