openinference

const (
	// EnvHideLLMInvocationParameters is the environment variable for TraceConfig.HideLLMInvocationParameters.
	EnvHideLLMInvocationParameters = "OPENINFERENCE_HIDE_LLM_INVOCATION_PARAMETERS"
	// EnvHideInputs is the environment variable for TraceConfig.HideInputs.
	EnvHideInputs = "OPENINFERENCE_HIDE_INPUTS"
	// EnvHideOutputs is the environment variable for TraceConfig.HideOutputs.
	EnvHideOutputs = "OPENINFERENCE_HIDE_OUTPUTS"
	// EnvHideInputMessages is the environment variable for TraceConfig.HideInputMessages.
	EnvHideInputMessages = "OPENINFERENCE_HIDE_INPUT_MESSAGES"
	// EnvHideOutputMessages is the environment variable for TraceConfig.HideOutputMessages.
	EnvHideOutputMessages = "OPENINFERENCE_HIDE_OUTPUT_MESSAGES"
	// EnvHideInputImages is the environment variable for TraceConfig.HideInputImages.
	EnvHideInputImages = "OPENINFERENCE_HIDE_INPUT_IMAGES"
	// EnvHideInputText is the environment variable for TraceConfig.HideInputText.
	EnvHideInputText = "OPENINFERENCE_HIDE_INPUT_TEXT"
	// EnvHideOutputText is the environment variable for TraceConfig.HideOutputText.
	EnvHideOutputText = "OPENINFERENCE_HIDE_OUTPUT_TEXT"
	// EnvHideEmbeddingsText is the environment variable for TraceConfig.HideEmbeddingsText.
	EnvHideEmbeddingsText = "OPENINFERENCE_HIDE_EMBEDDINGS_TEXT"
	// EnvHideEmbeddingsVectors is the environment variable for TraceConfig.HideEmbeddingsVectors.
	EnvHideEmbeddingsVectors = "OPENINFERENCE_HIDE_EMBEDDINGS_VECTORS"
	// EnvBase64ImageMaxLength is the environment variable for TraceConfig.Base64ImageMaxLength.
	EnvBase64ImageMaxLength = "OPENINFERENCE_BASE64_IMAGE_MAX_LENGTH"
	// EnvHidePrompts is the environment variable for TraceConfig.HidePrompts.
	// Hides LLM prompts (completions API).
	// See: https://github.com/Arize-ai/openinference/blob/main/spec/configuration.md
	EnvHidePrompts = "OPENINFERENCE_HIDE_PROMPTS"
	// EnvHideChoices is the environment variable for TraceConfig.HideChoices.
	// Hides LLM choices (completions API outputs).
	// See: https://github.com/Arize-ai/openinference/blob/main/spec/configuration.md
	EnvHideChoices = "OPENINFERENCE_HIDE_CHOICES"
)

const (
	// SpanKind identifies the type of operation (required for all OpenInference spans).
	SpanKind = "openinference.span.kind"

	// SpanKindLLM indicates a Large Language Model operation.
	SpanKindLLM = "LLM"

	// SpanKindEmbedding indicates an Embedding operation.
	SpanKindEmbedding = "EMBEDDING"
)

const (
	// LLMSystem identifies the AI system/product (e.g., "openai").
	LLMSystem = "llm.system"

	// LLMModelName specifies the model name (e.g., "gpt-4", "gpt-3.5-turbo").
	LLMModelName = "llm.model_name"

	// LLMInvocationParameters contains the invocation parameters as JSON string.
	LLMInvocationParameters = "llm.invocation_parameters"
)

const (
	// InputValue contains the input data as a string (typically JSON).
	InputValue = "input.value"

	// InputMimeType specifies the MIME type of the input data.
	InputMimeType = "input.mime_type"

	// OutputValue contains the output data as a string (typically JSON).
	OutputValue = "output.value"

	// OutputMimeType specifies the MIME type of the output data.
	OutputMimeType = "output.mime_type"

	// MimeTypeJSON for JSON content.
	MimeTypeJSON = "application/json"
)

const (
	// LLMPrompts prefix for prompt attributes in completions API.
	// Usage: llm.prompts.{index}.prompt.text
	// Prompts provided to a completions API, indexed starting from 0.
	LLMPrompts = "llm.prompts"

	// LLMChoices prefix for completion choice attributes in completions API.
	// Usage: llm.choices.{index}.completion.text
	// Text choices returned from a completions API, indexed starting from 0.
	LLMChoices = "llm.choices"
)

const (
	// LLMInputMessages prefix for input message attributes.
	// Usage: llm.input_messages.{index}.message.role, llm.input_messages.{index}.message.content.
	LLMInputMessages = "llm.input_messages"

	// LLMOutputMessages prefix for output message attributes.
	// Usage: llm.output_messages.{index}.message.role, llm.output_messages.{index}.message.content.
	LLMOutputMessages = "llm.output_messages"

	// MessageRole suffix for message role (e.g., "user", "assistant", "system").
	MessageRole = "message.role"

	// MessageContent suffix for message content.
	MessageContent = "message.content"
)

const (
	// LLMTokenCountPrompt contains the number of tokens in the prompt.
	LLMTokenCountPrompt = "llm.token_count.prompt" // #nosec G101

	// LLMTokenCountCompletion contains the number of tokens in the completion.
	LLMTokenCountCompletion = "llm.token_count.completion" // #nosec G101

	// LLMTokenCountTotal contains the total number of tokens.
	LLMTokenCountTotal = "llm.token_count.total" // #nosec G101
)

const (
	// LLMTools contains the list of available tools as JSON.
	// Format: llm.tools.{index}.tool.json_schema.
	LLMTools = "llm.tools"

	// MessageToolCalls prefix for tool calls in messages.
	// Format: message.tool_calls.{index}.tool_call.{attribute}.
	MessageToolCalls = "message.tool_calls"

	// ToolCallID suffix for tool call ID.
	ToolCallID = "tool_call.id"

	// ToolCallFunctionName suffix for function name in a tool call.
	ToolCallFunctionName = "tool_call.function.name"

	// ToolCallFunctionArguments suffix for function arguments as JSON string.
	ToolCallFunctionArguments = "tool_call.function.arguments"
)

const (
	// LLMTokenCountPromptCacheHit represents the number of prompt tokens successfully.
	// retrieved from cache (cache hits). This enables tracking of cache efficiency
	// and cost savings from cached prompts.
	LLMTokenCountPromptCacheHit = "llm.token_count.prompt_details.cache_read" // #nosec G101

	// LLMTokenCountPromptAudio represents the number of audio tokens in the prompt.
	// Used for multimodal models that support audio input.
	LLMTokenCountPromptAudio = "llm.token_count.prompt_details.audio" // #nosec G101

	// LLMTokenCountCompletionReasoning represents the number of tokens used for
	// reasoning or chain-of-thought processes in the completion. This helps track
	// the computational cost of complex reasoning tasks.
	LLMTokenCountCompletionReasoning = "llm.token_count.completion_details.reasoning" // #nosec G101

	// LLMTokenCountCompletionAudio represents the number of audio tokens in the.
	// completion. Used for models that generate audio output.
	LLMTokenCountCompletionAudio = "llm.token_count.completion_details.audio" // #nosec G101
)

const (
	// EmbeddingModelName specifies the name of the embedding model.
	// Example: "text-embedding-3-small"
	EmbeddingModelName = "embedding.model_name"

	// EmbeddingInvocationParameters contains the invocation parameters as JSON string.
	// This includes parameters sent to the model excluding input.
	// Example: {"model": "text-embedding-3-small", "encoding_format": "float"}
	EmbeddingInvocationParameters = "embedding.invocation_parameters"

	// EmbeddingEmbeddings is the prefix for embedding data attributes in batch operations.
	// Forms the base for nested attributes like embedding.embeddings.{index}.embedding.text
	// and embedding.embeddings.{index}.embedding.vector.
	EmbeddingEmbeddings = "embedding.embeddings"
)

const (
	// LLMSystemOpenAI for OpenAI systems.
	LLMSystemOpenAI = "openai"
)

const RedactedValue = "__REDACTED__"