llmjuice

Documentation

Index

• Constants
• type Choice
• type GrokPrompter
  • func NewGrokPrompter(apiKey, url, model string) *GrokPrompter
  • func (p *GrokPrompter) Prompt(ctx context.Context, opts PrompterOpts) (string, error)
• type JSONSchemaFormat
• type Message
• type MessageRole
• type PromptRequest
• type PromptResponse
• type PrompterOpts
• type ResponseFormat

Constants

const (
	GrokChatCompletionsURL = "https://api.x.ai/v1/chat/completions"
	Grok2LatestModel       = "grok-2-latest"
)

Types

type Choice

type Choice struct {
	Message struct {
		Content string `json:"content"`
	} `json:"message"`
}

Choice represents a choice in the response.

type GrokPrompter

type GrokPrompter struct {
	APIKey string
	URL    string
	Model  string
}

GrokPrompter is a prompter for the Grok LLM.

func NewGrokPrompter

func NewGrokPrompter(apiKey, url, model string) *GrokPrompter

NewGrokPrompter returns a new GrokPrompter instance.

func (*GrokPrompter) Prompt

func (p *GrokPrompter) Prompt(ctx context.Context, opts PrompterOpts) (string, error)

Prompt sends a prompt to the LLM and retrieves the response.

Use contextual messages to provide context to the LLM.

Additional options are not utilized by this implementation.

type JSONSchemaFormat

type JSONSchemaFormat struct {
	Name   string                 `json:"name"`
	Schema map[string]interface{} `json:"schema"`
	Strict bool                   `json:"strict"`
}

JSONSchemaFormat represents the JSON schema format customization of the response.

type Message

type Message struct {
	Role    string `json:"role"`
	Content string `json:"content"`
}

Message represents a message in the conversation.

For contextual messages, see:

• https://docs.x.ai/docs/guides/chat#conversations

type MessageRole

type MessageRole = string

MessageRole represents the role of a message.

const (
	// MessageRoleSystem is the role for the system message.
	MessageRoleSystem MessageRole = "system"

	// MessageRoleUser is the role for the user message.
	MessageRoleUser MessageRole = "user"

	// MessageRoleAssistant is the role for the assistant message.
	MessageRoleAssistant MessageRole = "assistant"
)

type PromptRequest

type PromptRequest struct {
	Model          string          `json:"model"`
	Messages       []Message       `json:"messages"`
	Stream         bool            `json:"stream,omitempty"`
	Temperature    float64         `json:"temperature,omitempty"`
	ResponseFormat *ResponseFormat `json:"response_format,omitempty"`
}

PromptRequest represents the payload for the LLM API request.

type PromptResponse

type PromptResponse struct {
	Choices []struct {
		Index   int `json:"index"`
		Message struct {
			Role    string `json:"role"`
			Content string `json:"content"`
			Refusal string `json:"refusal,omitempty"`
		} `json:"message"`
		FinishReason string `json:"finish_reason"`
	} `json:"choices"`
}

PromptResponse represents the response from the Grok LLM API.

type PrompterOpts

type PrompterOpts struct {
	SystemPrompt   string                 // The system prompt for the LLM.
	UserPrompt     string                 // The user prompt for the LLM.
	Context        []Message              // The context for the LLM.
	Temperature    float64                // The temperature for the LLM.
	ResponseFormat *ResponseFormat        // The response format for the LLM.
	AdditionalOpts map[string]interface{} // Additional options for the LLM to be implemented by prompters, optionally.
}

PrompterOpts represents the options for the Prompter.

type ResponseFormat

type ResponseFormat struct {
	Type       string            `json:"type"`
	JSONSchema *JSONSchemaFormat `json:"json_schema,omitempty"`
}

ResponseFormat represents the response format customization.