package gemini

import (
	"encoding/json"
	"errors"
	"fmt"
	"io"
	"net/http"
	"strings"
	"time"

	"github.com/gin-gonic/gin"
	"github.com/songquanpeng/one-api/common/config"
	"github.com/songquanpeng/one-api/common/helper"
	channelhelper "github.com/songquanpeng/one-api/relay/adaptor"
	"github.com/songquanpeng/one-api/relay/adaptor/openai"
	"github.com/songquanpeng/one-api/relay/meta"
	"github.com/songquanpeng/one-api/relay/model"
	"github.com/songquanpeng/one-api/relay/relaymode"
)

type Adaptor struct {
}

func (a *Adaptor) Init(meta *meta.Meta) {
}

func (a *Adaptor) GetRequestURL(meta *meta.Meta) (string, error) {
	defaultVersion := config.GeminiVersion
	modelLower := strings.ToLower(meta.ActualModelName)
	if strings.Contains(modelLower, "gemini-1.5") ||
		strings.Contains(modelLower, "gemini-2.") ||
		strings.Contains(modelLower, "gemini-3.") {
		defaultVersion = "v1beta"
	}

	version := helper.AssignOrDefault(meta.Config.APIVersion, defaultVersion)

	modelName := meta.ActualModelName

	switch meta.Mode {
	case relaymode.ImagesGenerations:
		return fmt.Sprintf("%s/v1beta/models/%s:predict", meta.BaseURL, modelName), nil
	case relaymode.Embeddings:
		return fmt.Sprintf("%s/%s/models/%s:batchEmbedContents", meta.BaseURL, version, modelName), nil
	}

	action := "generateContent"
	if meta.IsStream {
		action = "streamGenerateContent?alt=sse"
	}
	return fmt.Sprintf("%s/%s/models/%s:%s", meta.BaseURL, version, modelName, action), nil
}

func (a *Adaptor) SetupRequestHeader(c *gin.Context, req *http.Request, meta *meta.Meta) error {
	channelhelper.SetupCommonRequestHeader(c, req, meta)
	req.Header.Set("x-goog-api-key", meta.APIKey)
	return nil
}

func (a *Adaptor) ConvertRequest(c *gin.Context, relayMode int, request *model.GeneralOpenAIRequest) (any, error) {
	if request == nil {
		return nil, errors.New("request is nil")
	}
	switch relayMode {
	case relaymode.Embeddings:
		geminiEmbeddingRequest := ConvertEmbeddingRequest(*request)
		return geminiEmbeddingRequest, nil
	default:
		geminiRequest := ConvertRequest(*request)
		return geminiRequest, nil
	}
}

func (a *Adaptor) ConvertImageRequest(request *model.ImageRequest) (any, error) {
	if request == nil {
		return nil, errors.New("request is nil")
	}
	n := request.N
	if n <= 0 {
		n = 1
	}
	return ImagenRequest{
		Instances: []ImagenInstance{{Prompt: request.Prompt}},
		Parameters: ImagenParameters{
			SampleCount: n,
			AspectRatio: sizeToAspectRatio(request.Size),
		},
	}, nil
}

// sizeToAspectRatio converts OpenAI size strings to Imagen aspect ratios.
func sizeToAspectRatio(size string) string {
	switch size {
	case "1792x1024":
		return "16:9"
	case "1024x1792":
		return "9:16"
	case "1024x1024", "":
		return "1:1"
	default:
		return "1:1"
	}
}

func (a *Adaptor) DoRequest(c *gin.Context, meta *meta.Meta, requestBody io.Reader) (*http.Response, error) {
	return channelhelper.DoRequestHelper(a, c, meta, requestBody)
}

func (a *Adaptor) DoResponse(c *gin.Context, resp *http.Response, meta *meta.Meta) (usage *model.Usage, err *model.ErrorWithStatusCode) {
	if meta.IsStream {
		err, usage = StreamHandler(c, resp)
		if usage != nil {
			usage.PromptTokens = meta.PromptTokens
		}
	} else {
		switch meta.Mode {
		case relaymode.Embeddings:
			err, usage = EmbeddingHandler(c, resp)
		case relaymode.ImagesGenerations:
			err = ImagenHandler(c, resp)
		default:
			err, usage = Handler(c, resp, meta.PromptTokens, meta.ActualModelName)
		}
	}
	return
}

// ImagenHandler converts a Google Imagen predict response to OpenAI image response format.
func ImagenHandler(c *gin.Context, resp *http.Response) *model.ErrorWithStatusCode {
	responseBody, readErr := io.ReadAll(resp.Body)
	resp.Body.Close()
	if readErr != nil {
		return openai.ErrorWrapper(readErr, "read_response_body_failed", http.StatusInternalServerError)
	}

	var imagenResp ImagenResponse
	if err := json.Unmarshal(responseBody, &imagenResp); err != nil {
		return openai.ErrorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError)
	}

	if imagenResp.Error != nil {
		return openai.ErrorWrapper(
			fmt.Errorf("%s", imagenResp.Error.Message),
			"imagen_error",
			http.StatusInternalServerError,
		)
	}

	// Convert to OpenAI image response format
	data := make([]openai.ImageData, 0, len(imagenResp.Predictions))
	for _, p := range imagenResp.Predictions {
		data = append(data, openai.ImageData{B64Json: p.BytesBase64Encoded})
	}
	openaiResp := openai.ImageResponse{
		Created: time.Now().Unix(),
		Data:    data,
	}

	jsonBytes, err := json.Marshal(openaiResp)
	if err != nil {
		return openai.ErrorWrapper(err, "marshal_response_failed", http.StatusInternalServerError)
	}

	c.Writer.Header().Set("Content-Type", "application/json")
	c.Writer.WriteHeader(http.StatusOK)
	c.Writer.Write(jsonBytes)
	return nil
}

func (a *Adaptor) GetModelList() []string {
	return ModelList
}

func (a *Adaptor) GetChannelName() string {
	return "google gemini"
}