mirror of
https://github.com/mudler/LocalAI.git
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* fix(streaming): comply with OpenAI usage / stream_options spec (#8546) LocalAI emitted `"usage":{"prompt_tokens":0,...}` on every streamed chunk because `OpenAIResponse.Usage` was a value type without `omitempty`. The official OpenAI Node SDK and its consumers (continuedev/continue, Kilo Code, Roo Code, Zed, IntelliJ Continue) filter on a truthy `result.usage` to detect the trailing usage chunk; LocalAI's zero-but-non-null usage on every intermediate chunk made that filter swallow every content chunk and surface an empty chat response while the server log looked successful. Changes: - `core/schema/openai.go`: `Usage *OpenAIUsage \`json:"usage,omitempty"\`` so intermediate chunks no longer carry a `usage` key. Add `OpenAIRequest.StreamOptions` with `include_usage` to mirror OpenAI's request field. - `core/http/endpoints/openai/chat.go` and `completion.go`: keep using the `Usage` struct field as an in-process channel for the running cumulative, but strip it before JSON marshalling. When the request set `stream_options.include_usage: true`, emit a dedicated trailing chunk with `"choices": []` and the populated usage (matching the OpenAI spec and llama.cpp's server behavior). - `chat_emit.go`: new `streamUsageTrailerJSON` helper; drop the `usage` parameter from `buildNoActionFinalChunks` since chunks no longer carry usage. - Update `image.go`, `inpainting.go`, `edit.go` to wrap their Usage values with `&` for the new pointer field. - UI: send `stream_options:{include_usage:true}` from the React (`useChat.js`) and legacy (`static/chat.js`) chat clients so the token-count badge keeps populating now that the server is spec-compliant. Tests: - New `chat_stream_usage_test.go` pins the spec invariants: intermediate chunks have no `usage` key, the trailer JSON has `"choices":[]` and a populated `usage`, and `OpenAIRequest` parses `stream_options.include_usage`. - Update `chat_emit_test.go` to reflect that finals no longer embed usage. Verified against the live LocalAI instance: before the fix Continue's filter logic swallowed 16/16 token chunks; with the new shape it yields 4/5 and routes usage through the dedicated trailer chunk. Fixes #8546 Assisted-by: Claude:opus-4.7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(streaming): silence errcheck on usage trailer Fprintf The new spec-compliant `stream_options.include_usage` trailer writes were flagged by errcheck since they're new code (golangci-lint runs new-from-merge-base on master); the surrounding `fmt.Fprintf` data: writes are grandfathered. Drop the return values explicitly to match the linter's contract without adding a nolint shim. Assisted-by: Claude:opus-4.7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
280 lines
8.6 KiB
Go
280 lines
8.6 KiB
Go
package openai
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import (
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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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"net/url"
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"os"
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"path/filepath"
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"strconv"
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"time"
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"github.com/google/uuid"
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"github.com/labstack/echo/v4"
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"github.com/mudler/xlog"
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"github.com/mudler/LocalAI/core/backend"
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/core/http/middleware"
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"github.com/mudler/LocalAI/core/schema"
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model "github.com/mudler/LocalAI/pkg/model"
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)
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// InpaintingEndpoint handles POST /v1/images/inpainting
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//
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// Swagger / OpenAPI docstring (swaggo):
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// @Summary Image inpainting
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// @Description Perform image inpainting. Accepts multipart/form-data with `image` and `mask` files.
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// @Tags images
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// @Accept multipart/form-data
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// @Produce application/json
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// @Param model formData string true "Model identifier"
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// @Param prompt formData string true "Text prompt guiding the generation"
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// @Param steps formData int false "Number of inference steps (default 25)"
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// @Param image formData file true "Original image file"
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// @Param mask formData file true "Mask image file (white = area to inpaint)"
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// @Success 200 {object} schema.OpenAIResponse
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// @Failure 400 {object} map[string]string
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// @Failure 500 {object} map[string]string
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// @Router /v1/images/inpainting [post]
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func InpaintingEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) echo.HandlerFunc {
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return func(c echo.Context) error {
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// Parse basic form values
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modelName := c.FormValue("model")
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prompt := c.FormValue("prompt")
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stepsStr := c.FormValue("steps")
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if modelName == "" || prompt == "" {
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xlog.Error("Inpainting Endpoint - missing model or prompt")
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return echo.ErrBadRequest
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}
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// steps default
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steps := 25
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if stepsStr != "" {
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if v, err := strconv.Atoi(stepsStr); err == nil {
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steps = v
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}
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}
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// Get uploaded files
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imageFile, err := c.FormFile("image")
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if err != nil {
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xlog.Error("Inpainting Endpoint - missing image file", "error", err)
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return echo.NewHTTPError(http.StatusBadRequest, "missing image file")
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}
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maskFile, err := c.FormFile("mask")
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if err != nil {
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xlog.Error("Inpainting Endpoint - missing mask file", "error", err)
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return echo.NewHTTPError(http.StatusBadRequest, "missing mask file")
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}
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// Read files into memory (small files expected)
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imgSrc, err := imageFile.Open()
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if err != nil {
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return err
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}
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defer imgSrc.Close()
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imgBytes, err := io.ReadAll(imgSrc)
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if err != nil {
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return err
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}
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maskSrc, err := maskFile.Open()
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if err != nil {
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return err
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}
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defer maskSrc.Close()
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maskBytes, err := io.ReadAll(maskSrc)
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if err != nil {
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return err
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}
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// Create JSON with base64 fields expected by backend
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b64Image := base64.StdEncoding.EncodeToString(imgBytes)
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b64Mask := base64.StdEncoding.EncodeToString(maskBytes)
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// get model config from context (middleware set it)
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cfg, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
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if !ok || cfg == nil {
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xlog.Error("Inpainting Endpoint - model config not found in context")
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return echo.ErrBadRequest
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}
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// Use the GeneratedContentDir so the generated PNG is placed where the
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// HTTP static handler serves `/generated-images`.
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tmpDir := appConfig.GeneratedContentDir
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// Ensure the directory exists
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if err := os.MkdirAll(tmpDir, 0750); err != nil {
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xlog.Error("Inpainting Endpoint - failed to create generated content dir", "error", err, "dir", tmpDir)
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return echo.NewHTTPError(http.StatusInternalServerError, "failed to prepare storage")
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}
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id := uuid.New().String()
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jsonPath := filepath.Join(tmpDir, fmt.Sprintf("inpaint_%s.json", id))
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jsonFile := map[string]string{
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"image": b64Image,
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"mask_image": b64Mask,
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}
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jf, err := os.CreateTemp(tmpDir, "inpaint_")
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if err != nil {
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return err
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}
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// setup cleanup on error; if everything succeeds we set success = true
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success := false
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var dst string
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var origRef string
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var maskRef string
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defer func() {
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if !success {
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// Best-effort cleanup; log any failures
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if jf != nil {
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if cerr := jf.Close(); cerr != nil {
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xlog.Warn("Inpainting Endpoint - failed to close temp json file in cleanup", "error", cerr)
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}
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if name := jf.Name(); name != "" {
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if rerr := os.Remove(name); rerr != nil && !os.IsNotExist(rerr) {
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xlog.Warn("Inpainting Endpoint - failed to remove temp json file in cleanup", "error", rerr, "file", name)
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}
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}
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}
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if jsonPath != "" {
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if rerr := os.Remove(jsonPath); rerr != nil && !os.IsNotExist(rerr) {
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xlog.Warn("Inpainting Endpoint - failed to remove json file in cleanup", "error", rerr, "file", jsonPath)
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}
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}
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if dst != "" {
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if rerr := os.Remove(dst); rerr != nil && !os.IsNotExist(rerr) {
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xlog.Warn("Inpainting Endpoint - failed to remove dst file in cleanup", "error", rerr, "file", dst)
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}
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}
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if origRef != "" {
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if rerr := os.Remove(origRef); rerr != nil && !os.IsNotExist(rerr) {
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xlog.Warn("Inpainting Endpoint - failed to remove orig ref file in cleanup", "error", rerr, "file", origRef)
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}
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}
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if maskRef != "" {
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if rerr := os.Remove(maskRef); rerr != nil && !os.IsNotExist(rerr) {
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xlog.Warn("Inpainting Endpoint - failed to remove mask ref file in cleanup", "error", rerr, "file", maskRef)
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}
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}
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}
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}()
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// write original image and mask to disk as ref images so backends that
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// accept reference image files can use them (maintainer request).
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origTmp, err := os.CreateTemp(tmpDir, "refimg_")
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if err != nil {
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return err
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}
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if _, err := origTmp.Write(imgBytes); err != nil {
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_ = origTmp.Close()
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_ = os.Remove(origTmp.Name())
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return err
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}
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if cerr := origTmp.Close(); cerr != nil {
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xlog.Warn("Inpainting Endpoint - failed to close orig temp file", "error", cerr)
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}
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origRef = origTmp.Name()
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maskTmp, err := os.CreateTemp(tmpDir, "refmask_")
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if err != nil {
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// cleanup origTmp on error
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_ = os.Remove(origRef)
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return err
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}
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if _, err := maskTmp.Write(maskBytes); err != nil {
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_ = maskTmp.Close()
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_ = os.Remove(maskTmp.Name())
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_ = os.Remove(origRef)
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return err
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}
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if cerr := maskTmp.Close(); cerr != nil {
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xlog.Warn("Inpainting Endpoint - failed to close mask temp file", "error", cerr)
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}
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maskRef = maskTmp.Name()
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// write JSON
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enc := json.NewEncoder(jf)
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if err := enc.Encode(jsonFile); err != nil {
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if cerr := jf.Close(); cerr != nil {
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xlog.Warn("Inpainting Endpoint - failed to close temp json file after encode error", "error", cerr)
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}
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return err
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}
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if cerr := jf.Close(); cerr != nil {
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xlog.Warn("Inpainting Endpoint - failed to close temp json file", "error", cerr)
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}
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// rename to desired name
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if err := os.Rename(jf.Name(), jsonPath); err != nil {
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return err
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}
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// prepare dst
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outTmp, err := os.CreateTemp(tmpDir, "out_")
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if err != nil {
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return err
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}
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if cerr := outTmp.Close(); cerr != nil {
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xlog.Warn("Inpainting Endpoint - failed to close out temp file", "error", cerr)
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}
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dst = outTmp.Name() + ".png"
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if err := os.Rename(outTmp.Name(), dst); err != nil {
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return err
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}
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// Determine width/height default
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width := 512
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height := 512
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// Call backend image generation via indirection so tests can stub it
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// Note: ImageGenerationFunc will call into the loaded model's GenerateImage which expects src JSON
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// Also pass ref images (orig + mask) so backends that support ref images can use them.
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refImages := []string{origRef, maskRef}
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fn, err := backend.ImageGenerationFunc(height, width, steps, 0, prompt, "", jsonPath, dst, ml, *cfg, appConfig, refImages)
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if err != nil {
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return err
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}
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// Execute generation function (blocking)
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if err := fn(); err != nil {
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return err
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}
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// On success, build response URL using BaseURL middleware helper and
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// the same `generated-images` prefix used by the server static mount.
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baseURL := middleware.BaseURL(c)
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// Build response using url.JoinPath for correct URL escaping
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imgPath, err := url.JoinPath(baseURL, "generated-images", filepath.Base(dst))
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if err != nil {
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return err
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}
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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: []schema.Item{{
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URL: imgPath,
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}},
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Usage: &schema.OpenAIUsage{
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PromptTokens: 0,
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CompletionTokens: 0,
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TotalTokens: 0,
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InputTokens: 0,
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OutputTokens: 0,
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InputTokensDetails: &schema.InputTokensDetails{
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TextTokens: 0,
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ImageTokens: 0,
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},
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},
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}
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// mark success so defer cleanup will not remove output files
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success = true
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return c.JSON(http.StatusOK, resp)
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}
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}
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