testopenai

const (

	// CassetteChatBasic is the canonical OpenAI chat completion request.
	CassetteChatBasic Cassette = iota
	// CassetteChatJSONMode is a chat completion request with JSON response format.
	CassetteChatJSONMode
	// CassetteChatMultimodal is a multimodal chat request with text and image inputs.
	CassetteChatMultimodal
	// CassetteChatMultiturn is a multi-turn conversation with message history.
	CassetteChatMultiturn
	// CassetteChatNoMessages is a request missing the required messages field.
	CassetteChatNoMessages
	// CassetteChatParallelTools is a chat completion with parallel function calling enabled.
	CassetteChatParallelTools
	// CassetteChatStreaming is the canonical OpenAI chat completion request,
	// with streaming enabled.
	CassetteChatStreaming
	// CassetteChatTools is a chat completion request with function tools.
	CassetteChatTools
	// CassetteChatUnknownModel is a request with a non-existent model.
	CassetteChatUnknownModel
	// CassetteChatBadRequest is a request with multiple validation errors.
	CassetteChatBadRequest
	// CassetteChatReasoning tests capture of reasoning_tokens in completion_tokens_details for O1 models.
	CassetteChatReasoning
	// CassetteChatImageToText tests image input processing showing image token
	// count in usage details.
	CassetteChatImageToText
	// CassetteChatTextToImageTool tests image generation through tool calls since
	// chat completions cannot natively output images.
	CassetteChatTextToImageTool
	// CassetteChatAudioToText tests audio input transcription and audio_tokens
	// in prompt_tokens_details.
	CassetteChatAudioToText
	// CassetteChatTextToAudio tests audio output generation where the model
	// produces audio content, showing audio_tokens in completion_tokens_details.
	CassetteChatTextToAudio
	// CassetteChatDetailedUsage tests capture of all token usage detail fields in a single response.
	CassetteChatDetailedUsage
	// CassetteChatStreamingDetailedUsage tests capture of detailed token usage in streaming responses with include_usage.
	CassetteChatStreamingDetailedUsage
	// CassetteChatWebSearch tests OpenAI Web Search tool with a small URL response, including citations.
	CassetteChatWebSearch
	// CassetteChatStreamingWebSearch is CassetteChatWebSearch except with streaming enabled.
	CassetteChatStreamingWebSearch
	// CassetteChatOpenAIAgentsPython is a real request from OpenAI Agents Python library for financial research.
	// See https://github.com/openai/openai-agents-python/tree/main/examples/financial_research_agent
	CassetteChatOpenAIAgentsPython

	// CassetteCompletionBasic tests standard single-prompt code completion
	// requests typical of LoRA-tuned CodeLlama or Starcoder models deployed via
	// vLLM/llama.cpp. Uses fibonacci function as representative coding task for
	// model evaluation.
	// See: https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html
	CassetteCompletionBasic
	// CassetteCompletionToken is CassetteCompletionBasic, but with cl100k_base
	// tokens as input instead of text strings. This simulates LoRA fine-tuning
	// workflows requiring precise tokenization control.
	CassetteCompletionToken
	// CassetteCompletionStreaming is CassetteCompletionBasic, with streaming
	// enabled to test real-time token delivery common in IDE.
	CassetteCompletionStreaming
	// CassetteCompletionStreamingUsage is CassetteCompletionStreaming, but
	// with include_usage enabled to test detailed token usage reporting.
	CassetteCompletionStreamingUsage
	// CassetteCompletionTextBatch tests multiple code completion variants
	// generated simultaneously, common in IDE autocomplete where users select
	// from LoRA model suggestions. Full vs truncated prompts simulate real
	// editing scenarios.
	// See: https://community.openai.com/t/n-argument-vs-batch-input/59121
	CassetteCompletionTextBatch
	// CassetteCompletionTokenBatch is CassetteCompletionTextBatch, but with
	// cl100k_base tokens as input instead of text strings. This simulates LoRA
	// fine-tuning workflows requiring precise tokenization control.
	CassetteCompletionTokenBatch
	// CassetteCompletionSuffix tests the suffix parameter for fill-in-the-middle
	// completion tasks. The model generates code to insert between a prompt (partial
	// function definition) and a suffix (function call). Also tests logprobs for
	// confidence scoring and n for multiple completion variants. Only gpt-3.5-turbo-instruct
	// supports the suffix parameter.
	// See: https://platform.openai.com/docs/guides/completions/inserting-text
	CassetteCompletionSuffix
	// CassetteCompletionBadRequest is a request with multiple validation
	// errors.
	CassetteCompletionBadRequest
	// CassetteCompletionUnknownModel is a request with a non-existent model.
	CassetteCompletionUnknownModel

	// CassetteEmbeddingsBasic is the canonical OpenAI embeddings request with a single string input.
	CassetteEmbeddingsBasic
	// CassetteEmbeddingsBase64 tests base64 encoding format for embedding vectors.
	CassetteEmbeddingsBase64
	// CassetteEmbeddingsTokens tests embeddings with token array input instead of text.
	CassetteEmbeddingsTokens
	// CassetteEmbeddingsLargeText tests embeddings with a longer text input.
	CassetteEmbeddingsLargeText
	// CassetteEmbeddingsUnknownModel tests error handling for non-existent model.
	CassetteEmbeddingsUnknownModel
	// CassetteEmbeddingsDimensions tests embeddings with specified output dimensions.
	CassetteEmbeddingsDimensions
	// CassetteEmbeddingsMixedBatch tests batch with varying text lengths.
	CassetteEmbeddingsMixedBatch
	// CassetteEmbeddingsMaxTokens tests input that approaches token limit.
	CassetteEmbeddingsMaxTokens
	// CassetteEmbeddingsWhitespace tests handling of various whitespace patterns.
	CassetteEmbeddingsWhitespace
	// CassetteEmbeddingsBadRequest tests request with multiple validation errors.
	CassetteEmbeddingsBadRequest

	// CassetteImageGenerationBasic is a basic image generation request with model and prompt.
	CassetteImageGenerationBasic

	// CassetteAzureChatBasic is the same as CassetteChatBasic, except using
	// Azure OpenAI Service authentication and endpoint format.
	CassetteAzureChatBasic
)