provider

type ChatCompletionChoice struct {
	Index        int      `json:"index"`
	Message      Message  `json:"message"`
	Delta        *Message `json:"delta,omitempty"`
	FinishReason *string  `json:"finish_reason"`
	Logprobs     any      `json:"logprobs,omitempty"`
}

type ChatCompletionChunk struct {
	ID                string                 `json:"id"`
	Object            string                 `json:"object"`
	Created           int64                  `json:"created"`
	Model             string                 `json:"model"`
	SystemFingerprint *string                `json:"system_fingerprint,omitempty"`
	Choices           []ChatCompletionChoice `json:"choices"`
	Usage             *Usage                 `json:"usage,omitempty"`
	ProviderMetadata  map[string]any         `json:"provider_metadata,omitempty"` // Provider-specific metadata
}

type ChatCompletionRequest struct {
	Model            string          `json:"model"`
	Messages         []Message       `json:"messages"`
	MaxTokens        *int            `json:"max_tokens,omitempty"`
	Temperature      *float64        `json:"temperature,omitempty"`
	TopP             *float64        `json:"top_p,omitempty"`
	TopK             *int            `json:"top_k,omitempty"` // Anthropic, Gemini, Ollama
	Stream           *bool           `json:"stream,omitempty"`
	Stop             []string        `json:"stop,omitempty"`
	PresencePenalty  *float64        `json:"presence_penalty,omitempty"`
	FrequencyPenalty *float64        `json:"frequency_penalty,omitempty"`
	LogitBias        map[string]int  `json:"logit_bias,omitempty"`
	User             *string         `json:"user,omitempty"`
	Tools            []Tool          `json:"tools,omitempty"`
	ToolChoice       any             `json:"tool_choice,omitempty"`
	Seed             *int            `json:"seed,omitempty"`            // OpenAI, X.AI - for reproducible outputs
	N                *int            `json:"n,omitempty"`               // OpenAI - number of completions
	ResponseFormat   *ResponseFormat `json:"response_format,omitempty"` // OpenAI, Gemini - JSON mode
	Logprobs         *bool           `json:"logprobs,omitempty"`        // OpenAI - return log probabilities
	TopLogprobs      *int            `json:"top_logprobs,omitempty"`    // OpenAI - number of top logprobs
}

type ChatCompletionResponse struct {
	ID                string                 `json:"id"`
	Object            string                 `json:"object"`
	Created           int64                  `json:"created"`
	Model             string                 `json:"model"`
	SystemFingerprint *string                `json:"system_fingerprint,omitempty"`
	Choices           []ChatCompletionChoice `json:"choices"`
	Usage             Usage                  `json:"usage"`
	ProviderMetadata  map[string]any         `json:"provider_metadata,omitempty"` // Provider-specific metadata
}

type ChatCompletionStream interface {
	// Recv receives the next chunk from the stream
	Recv() (*ChatCompletionChunk, error)

	// Close closes the stream
	Close() error
}

type EmbeddingData struct {
	// Object is the object type (always "embedding")
	Object string `json:"object"`

	// Index is the index of this embedding in the input array
	Index int `json:"index"`

	// Embedding is the vector representation as float64 values
	Embedding []float64 `json:"embedding"`
}

type EmbeddingEncodingFormat string

type EmbeddingProvider interface {
	// CreateEmbedding creates embeddings for the given input texts
	CreateEmbedding(ctx context.Context, req *EmbeddingRequest) (*EmbeddingResponse, error)

	// Close closes the provider and cleans up resources
	Close() error

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

type EmbeddingRequest struct {
	// Model is the embedding model to use (e.g., "text-embedding-3-small")
	Model string `json:"model"`

	// Input is the text(s) to embed. Can be a single string or array of strings.
	Input []string `json:"input"`

	// EncodingFormat specifies the format of the returned embeddings (optional)
	// Defaults to "float". Some providers support "base64" for efficiency.
	EncodingFormat EmbeddingEncodingFormat `json:"encoding_format,omitempty"`

	// Dimensions specifies the number of dimensions for the output vectors (optional)
	// Only supported by some models (e.g., text-embedding-3-small/large)
	Dimensions *int `json:"dimensions,omitempty"`

	// User is an optional unique identifier for the end-user
	User *string `json:"user,omitempty"`
}

type EmbeddingResponse struct {
	// Object is the object type (always "list" for embeddings)
	Object string `json:"object"`

	// Data contains the embedding vectors
	Data []EmbeddingData `json:"data"`

	// Model is the model used to generate the embeddings
	Model string `json:"model"`

	// Usage contains token usage information
	Usage EmbeddingUsage `json:"usage"`

	// ProviderMetadata contains provider-specific metadata
	ProviderMetadata map[string]any `json:"provider_metadata,omitempty"`
}

type EmbeddingUsage struct {
	// PromptTokens is the number of tokens in the input
	PromptTokens int `json:"prompt_tokens"`

	// TotalTokens is the total number of tokens used
	TotalTokens int `json:"total_tokens"`
}

type Message struct {
	Role       Role       `json:"role"`
	Content    string     `json:"content"`
	Name       *string    `json:"name,omitempty"`
	ToolCallID *string    `json:"tool_call_id,omitempty"`
	ToolCalls  []ToolCall `json:"tool_calls,omitempty"`
}

type Provider interface {
	// CreateChatCompletion creates a new chat completion
	CreateChatCompletion(ctx context.Context, req *ChatCompletionRequest) (*ChatCompletionResponse, error)

	// CreateChatCompletionStream creates a streaming chat completion
	CreateChatCompletionStream(ctx context.Context, req *ChatCompletionRequest) (ChatCompletionStream, error)

	// Close closes the provider and cleans up resources
	Close() error

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

type ResponseFormat struct {
	Type string `json:"type"` // "text" or "json_object"
}

type Role string

type Tool struct {
	Type     string   `json:"type"`
	Function ToolSpec `json:"function"`
}

type ToolCall struct {
	ID       string       `json:"id"`
	Type     string       `json:"type"`
	Function ToolFunction `json:"function"`
}

type ToolFunction struct {
	Name      string `json:"name"`
	Arguments string `json:"arguments"`
}

type ToolSpec struct {
	Name        string `json:"name"`
	Description string `json:"description"`
	Parameters  any    `json:"parameters"`
}

type Usage struct {
	PromptTokens     int `json:"prompt_tokens"`
	CompletionTokens int `json:"completion_tokens"`
	TotalTokens      int `json:"total_tokens"`
}