openAIKey := "abc"
openai := llm.NewOpenAILLM(openAIKey)

systemPrompt := "You only use Emojis."
textRequest := llm.ChatCompletionRequest{
		SystemPrompt: &systemPrompt,
		Model:        llm.ModelGPT4o,
		Messages: []llm.InputMessage{
			{
				Role: llm.RoleUser,
				MultiContent: []llm.ContentPart{
					{
						Type: llm.ContentTypeText,
						Text: `What is the purpose of life?`
					},
				},
			},
		},
		JSONMode:    false,
		MaxTokens:   1000,
		Temperature: 0,
	}

response, err := openai.CreateChatCompletion(context.Background(), textRequest)
if err != nil {
	panic(err)
}

fmt.Println(response)

// OpenAI model from OpenAI API
openAIKey := ""
openai := llm.NewOpenAILLM(openAIKey)

// Claude model from OpenAI API
anthropicKey := ""
claude := llm.NewAnthropicLLM(anthropicKey)

// Gemini model from Vertex API
geminiKey := ""
gemini, err := llm.NewGeminiLLM(geminiKey)
if err != nil {
    panic(err)
}

// Claude model from Vertex API
// read google credentials from file
credBytes, err := os.ReadFile("google.json")
if err != nil {
    panic(err)
}

claudeVertex := llm.NewVertexLLM(credBytes, "project-id", "location")

openAIKey := ""
openai := llm.NewOpenAILLM(openAIKey)


// read image from test_images/cats.png and convert to base64
imageBytesDogs, _ := os.ReadFile("images/dogs.png")
imageBytesCats, _ := os.ReadFile("images/cats.png")


imageBase64Dogs := base64.StdEncoding.EncodeToString(imageBytesDogs)
imageBase64Cats := base64.StdEncoding.EncodeToString(imageBytesCats)

systemPrompt := "You are a cat and speak in cat language."
imageRequest := llm.ChatCompletionRequest{
	SystemPrompt: &systemPrompt,
	Model:        llm.ModelGPT4o,
	Messages: []llm.InputMessage{
		{
			Role: llm.RoleUser,
			MultiContent: []llm.ContentPart{
				{
					Type: llm.ContentTypeText,
					Text: "Image number 1",
				},
				{
					Type:      llm.ContentTypeImage,
					Data:      imageBase64Cats,
					MediaType: "image/png",
				},
				{
					Type: llm.ContentTypeText,
					Text: "Image number 2",
				},
				{
					Type:      llm.ContentTypeImage,
					Data:      imageBase64Dogs,
					MediaType: "image/png",
				},
				{
					Type: llm.ContentTypeText,
					Text: `Compare the two images`.
				},
			},
		},
	},
	JSONMode:    false,
	MaxTokens:   1000,
	Temperature: 0,
}

response, _ := openai.CreateChatCompletion(context.Background(), imageRequest)
fmt.Println(reponse)

openAIKey := ""
openai := llm.NewOpenAILLM(openAIKey)

toolRequestWithToolResponse := llm.ChatCompletionRequest{
	Model: llm.ModelGPT4o,
	Messages: []llm.InputMessage{
		{
			Role: llm.RoleUser,
			MultiContent: []llm.ContentPart{
				{
					Type: llm.ContentTypeText,
					Text: "What is the weather in Paris, France?",
				},
			},
		},
		{
			Role: llm.RoleAssistant,
			ToolCalls: []llm.ToolCall{{
				ID:   "123",
				Type: "function",
				Function: llm.ToolCallFunction{
					Name:      "get_weather",
					Arguments: "{\"location\": \"Paris, France\"}",
				},
			}},
		},
		{
			Role:         llm.RoleTool,
			MultiContent: nil,
			ToolResults: []llm.ToolResult{
				{
					ToolCallID:   "123",
					FunctionName: "get_weather",
					Result:       "15 degrees",
					IsError:      false,
				},
			},
		},
	},
	Tools: []llm.Tool{
		{
			Type: "function",
			Function: &llm.Function{
				Name:        "get_weather",
				Description: "Get current temperature for a given location.",
				Parameters: map[string]interface{}{
					"type": "object",
					"properties": map[string]interface{}{
						"location": map[string]interface{}{
							"type":        "string",
							"description": "City and country e.g. Bogotá, Colombia",
						},
					},
					"required":             []string{"location"},
					"additionalProperties": false,
				},
			},
		},
	},
	JSONMode:    false,
	MaxTokens:   1000,
	Temperature: 0,
}

response, _ := openai.CreateChatCompletion(context.Background(), toolRequestWithToolResponse)
fmt.Println(response)