embeddings

type Config struct {
	APIKey     string
	BaseURL    string
	Model      string
	Dimensions int
	Timeout    time.Duration
}

type EmbedRequest struct {
	Model     string   `json:"model"`
	Input     []string `json:"input"`
	Dimension int      `json:"dimensions,omitempty"`
}

type EmbedResponse struct {
	Object string `json:"object"`
	Data   []struct {
		Object    string    `json:"object"`
		Embedding []float32 `json:"embedding"`
		Index     int       `json:"index"`
	} `json:"data"`
	Model string `json:"model"`
	Usage struct {
		PromptTokens     int `json:"prompt_tokens"`
		CompletionTokens int `json:"completion_tokens"`
		TotalTokens      int `json:"total_tokens"`
	} `json:"usage"`
}

type EmbedResult struct {
	Embeddings []Embedding
	Usage      Usage
}

type Embedding struct {
	Vector  []float32
	Model   string
	Tokens  int
	Created time.Time
}

type OllamaConfig struct {
	Config
	KeepAlive string // How long to keep model loaded (e.g., "5m", "0")
}

type OllamaEmbedRequest struct {
	Model     string `json:"model"`
	Prompt    string `json:"prompt"`
	KeepAlive string `json:"keep_alive,omitempty"`
}

type OllamaEmbedResponse struct {
	Embedding []float32 `json:"embedding"`
}

type OllamaProvider struct {
	// contains filtered or unexported fields
}

type OpenAIProvider struct {
	// contains filtered or unexported fields
}

type Option func(*Config)

type Provider interface {
	// Embed generates embeddings for the given texts.
	Embed(ctx context.Context, texts []string) (*EmbedResult, error)

	// EmbedSingle generates an embedding for a single text.
	EmbedSingle(ctx context.Context, text string) (*Embedding, error)

	// Name returns the provider name.
	Name() string

	// Model returns the default model name.
	Model() string

	// Dimensions returns the embedding dimensions.
	Dimensions() int
}

type Registry struct {
	// contains filtered or unexported fields
}

type Usage struct {
	PromptTokens     int
	CompletionTokens int
	TotalTokens      int
}