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refactor: backend/service split, channel-based llm flow (#1963)
Refactor: channel based llm flow and services split --------- Signed-off-by: Dave Lee <dave@gray101.com>
This commit is contained in:
Dave
GitHub
parent
1981154f49
commit
eed5706994
52 changed files with 3064 additions and 2279 deletions
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@ -1,50 +1,18 @@
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package openai
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import (
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"bufio"
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"encoding/base64"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"os"
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"path/filepath"
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"strconv"
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"strings"
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"time"
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"github.com/go-skynet/LocalAI/core/config"
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"github.com/go-skynet/LocalAI/core/schema"
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"github.com/google/uuid"
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fiberContext "github.com/go-skynet/LocalAI/core/http/ctx"
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"github.com/go-skynet/LocalAI/core/backend"
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model "github.com/go-skynet/LocalAI/pkg/model"
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"github.com/gofiber/fiber/v2"
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"github.com/rs/zerolog/log"
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)
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func downloadFile(url string) (string, error) {
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// Get the data
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resp, err := http.Get(url)
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if err != nil {
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return "", err
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}
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defer resp.Body.Close()
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// Create the file
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out, err := os.CreateTemp("", "image")
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if err != nil {
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return "", err
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}
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defer out.Close()
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// Write the body to file
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_, err = io.Copy(out, resp.Body)
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return out.Name(), err
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}
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//
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// https://platform.openai.com/docs/api-reference/images/create
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/*
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*
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@ -59,186 +27,36 @@ func downloadFile(url string) (string, error) {
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*
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*/
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// ImageEndpoint is the OpenAI Image generation API endpoint https://platform.openai.com/docs/api-reference/images/create
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// @Summary Creates an image given a prompt.
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// @Param request body schema.OpenAIRequest true "query params"
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// @Success 200 {object} schema.OpenAIResponse "Response"
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// @Router /v1/images/generations [post]
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func ImageEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
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func ImageEndpoint(fce *fiberContext.FiberContextExtractor, igbs *backend.ImageGenerationBackendService) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
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m, input, err := readRequest(c, ml, appConfig, false)
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// TODO: Somewhat a hack. Is there a better place to assign this?
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if igbs.BaseUrlForGeneratedImages == "" {
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igbs.BaseUrlForGeneratedImages = c.BaseURL() + "/generated-images/"
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}
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_, request, err := fce.OpenAIRequestFromContext(c, false)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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if m == "" {
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m = model.StableDiffusionBackend
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}
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log.Debug().Msgf("Loading model: %+v", m)
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responseChannel := igbs.GenerateImage(request)
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rawResponse := <-responseChannel
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config, input, err := mergeRequestWithConfig(m, input, cl, ml, appConfig.Debug, 0, 0, false)
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if rawResponse.Error != nil {
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return rawResponse.Error
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}
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jsonResult, err := json.Marshal(rawResponse.Value)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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return err
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}
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src := ""
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if input.File != "" {
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fileData := []byte{}
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// check if input.File is an URL, if so download it and save it
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// to a temporary file
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if strings.HasPrefix(input.File, "http://") || strings.HasPrefix(input.File, "https://") {
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out, err := downloadFile(input.File)
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if err != nil {
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return fmt.Errorf("failed downloading file:%w", err)
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}
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defer os.RemoveAll(out)
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fileData, err = os.ReadFile(out)
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if err != nil {
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return fmt.Errorf("failed reading file:%w", err)
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}
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} else {
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// base 64 decode the file and write it somewhere
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// that we will cleanup
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fileData, err = base64.StdEncoding.DecodeString(input.File)
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if err != nil {
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return err
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}
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}
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// Create a temporary file
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outputFile, err := os.CreateTemp(appConfig.ImageDir, "b64")
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if err != nil {
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return err
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}
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// write the base64 result
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writer := bufio.NewWriter(outputFile)
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_, err = writer.Write(fileData)
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if err != nil {
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outputFile.Close()
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return err
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}
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outputFile.Close()
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src = outputFile.Name()
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defer os.RemoveAll(src)
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}
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log.Debug().Msgf("Parameter Config: %+v", config)
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switch config.Backend {
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case "stablediffusion":
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config.Backend = model.StableDiffusionBackend
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case "tinydream":
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config.Backend = model.TinyDreamBackend
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case "":
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config.Backend = model.StableDiffusionBackend
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}
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sizeParts := strings.Split(input.Size, "x")
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if len(sizeParts) != 2 {
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return fmt.Errorf("invalid value for 'size'")
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}
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width, err := strconv.Atoi(sizeParts[0])
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if err != nil {
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return fmt.Errorf("invalid value for 'size'")
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}
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height, err := strconv.Atoi(sizeParts[1])
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if err != nil {
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return fmt.Errorf("invalid value for 'size'")
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}
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b64JSON := false
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if input.ResponseFormat.Type == "b64_json" {
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b64JSON = true
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}
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// src and clip_skip
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var result []schema.Item
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for _, i := range config.PromptStrings {
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n := input.N
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if input.N == 0 {
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n = 1
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}
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for j := 0; j < n; j++ {
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prompts := strings.Split(i, "|")
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positive_prompt := prompts[0]
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negative_prompt := ""
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if len(prompts) > 1 {
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negative_prompt = prompts[1]
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}
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mode := 0
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step := config.Step
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if step == 0 {
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step = 15
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}
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if input.Mode != 0 {
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mode = input.Mode
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}
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if input.Step != 0 {
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step = input.Step
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}
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tempDir := ""
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if !b64JSON {
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tempDir = appConfig.ImageDir
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}
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// Create a temporary file
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outputFile, err := os.CreateTemp(tempDir, "b64")
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if err != nil {
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return err
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}
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outputFile.Close()
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output := outputFile.Name() + ".png"
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// Rename the temporary file
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err = os.Rename(outputFile.Name(), output)
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if err != nil {
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return err
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}
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baseURL := c.BaseURL()
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fn, err := backend.ImageGeneration(height, width, mode, step, *config.Seed, positive_prompt, negative_prompt, src, output, ml, *config, appConfig)
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if err != nil {
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return err
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}
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if err := fn(); err != nil {
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return err
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}
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item := &schema.Item{}
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if b64JSON {
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defer os.RemoveAll(output)
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data, err := os.ReadFile(output)
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if err != nil {
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return err
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}
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item.B64JSON = base64.StdEncoding.EncodeToString(data)
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} else {
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base := filepath.Base(output)
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item.URL = baseURL + "/generated-images/" + base
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}
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result = append(result, *item)
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}
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}
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id := uuid.New().String()
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created := int(time.Now().Unix())
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resp := &schema.OpenAIResponse{
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ID: id,
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Created: created,
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Data: result,
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}
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jsonResult, _ := json.Marshal(resp)
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log.Debug().Msgf("Response: %s", jsonResult)
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// Return the prediction in the response body
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return c.JSON(resp)
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return c.JSON(rawResponse.Value)
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}
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}
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