LocalAI/core/http/endpoints/openai/image.go
Ettore Di Giacinto 59ef426fbf
feat(model-list): be consistent, skip known files from listing (#2760)
fix(model-list): be consistent, skip known files from listing

This changeset does two things:

- Removes the dependency of listing models from the OpenAI schema.
- Tries to reduce confusion between ListModels() in model loader and in
  the service - now there is only one ListModels which is in services
and does not depend anymore on the OpenAI schema
- The OpenAI-schema functions were moved nearby the OpenAI specific
  endpoints that needs the schema
- Drops the ListModel Service structure as there was no real need for
  it.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-07-10 15:28:39 +02:00

243 lines
5.5 KiB
Go

package openai
import (
"bufio"
"encoding/base64"
"encoding/json"
"fmt"
"io"
"net/http"
"os"
"path/filepath"
"strconv"
"strings"
"time"
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/backend"
"github.com/gofiber/fiber/v2"
model "github.com/mudler/LocalAI/pkg/model"
"github.com/rs/zerolog/log"
)
func downloadFile(url string) (string, error) {
// Get the data
resp, err := http.Get(url)
if err != nil {
return "", err
}
defer resp.Body.Close()
// Create the file
out, err := os.CreateTemp("", "image")
if err != nil {
return "", err
}
defer out.Close()
// Write the body to file
_, err = io.Copy(out, resp.Body)
return out.Name(), err
}
//
/*
*
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "A cute baby sea otter",
"n": 1,
"size": "512x512"
}'
*
*/
// ImageEndpoint is the OpenAI Image generation API endpoint https://platform.openai.com/docs/api-reference/images/create
// @Summary Creates an image given a prompt.
// @Param request body schema.OpenAIRequest true "query params"
// @Success 200 {object} schema.OpenAIResponse "Response"
// @Router /v1/images/generations [post]
func ImageEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readRequest(c, cl, ml, appConfig, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
if m == "" {
m = model.StableDiffusionBackend
}
log.Debug().Msgf("Loading model: %+v", m)
config, input, err := mergeRequestWithConfig(m, input, cl, ml, appConfig.Debug, 0, 0, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
src := ""
if input.File != "" {
fileData := []byte{}
// check if input.File is an URL, if so download it and save it
// to a temporary file
if strings.HasPrefix(input.File, "http://") || strings.HasPrefix(input.File, "https://") {
out, err := downloadFile(input.File)
if err != nil {
return fmt.Errorf("failed downloading file:%w", err)
}
defer os.RemoveAll(out)
fileData, err = os.ReadFile(out)
if err != nil {
return fmt.Errorf("failed reading file:%w", err)
}
} else {
// base 64 decode the file and write it somewhere
// that we will cleanup
fileData, err = base64.StdEncoding.DecodeString(input.File)
if err != nil {
return err
}
}
// Create a temporary file
outputFile, err := os.CreateTemp(appConfig.ImageDir, "b64")
if err != nil {
return err
}
// write the base64 result
writer := bufio.NewWriter(outputFile)
_, err = writer.Write(fileData)
if err != nil {
outputFile.Close()
return err
}
outputFile.Close()
src = outputFile.Name()
defer os.RemoveAll(src)
}
log.Debug().Msgf("Parameter Config: %+v", config)
switch config.Backend {
case "stablediffusion":
config.Backend = model.StableDiffusionBackend
case "tinydream":
config.Backend = model.TinyDreamBackend
case "":
config.Backend = model.StableDiffusionBackend
}
sizeParts := strings.Split(input.Size, "x")
if len(sizeParts) != 2 {
return fmt.Errorf("invalid value for 'size'")
}
width, err := strconv.Atoi(sizeParts[0])
if err != nil {
return fmt.Errorf("invalid value for 'size'")
}
height, err := strconv.Atoi(sizeParts[1])
if err != nil {
return fmt.Errorf("invalid value for 'size'")
}
b64JSON := config.ResponseFormat == "b64_json"
// src and clip_skip
var result []schema.Item
for _, i := range config.PromptStrings {
n := input.N
if input.N == 0 {
n = 1
}
for j := 0; j < n; j++ {
prompts := strings.Split(i, "|")
positive_prompt := prompts[0]
negative_prompt := ""
if len(prompts) > 1 {
negative_prompt = prompts[1]
}
mode := 0
step := config.Step
if step == 0 {
step = 15
}
if input.Mode != 0 {
mode = input.Mode
}
if input.Step != 0 {
step = input.Step
}
tempDir := ""
if !b64JSON {
tempDir = appConfig.ImageDir
}
// Create a temporary file
outputFile, err := os.CreateTemp(tempDir, "b64")
if err != nil {
return err
}
outputFile.Close()
output := outputFile.Name() + ".png"
// Rename the temporary file
err = os.Rename(outputFile.Name(), output)
if err != nil {
return err
}
baseURL := c.BaseURL()
fn, err := backend.ImageGeneration(height, width, mode, step, *config.Seed, positive_prompt, negative_prompt, src, output, ml, *config, appConfig)
if err != nil {
return err
}
if err := fn(); err != nil {
return err
}
item := &schema.Item{}
if b64JSON {
defer os.RemoveAll(output)
data, err := os.ReadFile(output)
if err != nil {
return err
}
item.B64JSON = base64.StdEncoding.EncodeToString(data)
} else {
base := filepath.Base(output)
item.URL = baseURL + "/generated-images/" + base
}
result = append(result, *item)
}
}
id := uuid.New().String()
created := int(time.Now().Unix())
resp := &schema.OpenAIResponse{
ID: id,
Created: created,
Data: result,
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}