Files
LocalAI/core/http/endpoints/openai/completion.go
LocalAI [bot] 8af963bdd9 fix(streaming): comply with OpenAI usage / stream_options spec (#9815)
* 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>
2026-05-14 08:53:46 +02:00

281 lines
8.7 KiB
Go

package openai
import (
"encoding/json"
"errors"
"fmt"
"time"
"github.com/labstack/echo/v4"
"github.com/mudler/LocalAI/core/backend"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/middleware"
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/xlog"
)
// CompletionEndpoint is the OpenAI Completion API endpoint https://platform.openai.com/docs/api-reference/completions
// @Summary Generate completions for a given prompt and model.
// @Tags inference
// @Param request body schema.OpenAIRequest true "query params"
// @Success 200 {object} schema.OpenAIResponse "Response"
// @Router /v1/completions [post]
func CompletionEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator *templates.Evaluator, appConfig *config.ApplicationConfig) echo.HandlerFunc {
process := func(id string, s string, req *schema.OpenAIRequest, config *config.ModelConfig, loader *model.ModelLoader, responses chan schema.OpenAIResponse, extraUsage bool) error {
tokenCallback := func(s string, tokenUsage backend.TokenUsage) bool {
created := int(time.Now().Unix())
usage := schema.OpenAIUsage{
PromptTokens: tokenUsage.Prompt,
CompletionTokens: tokenUsage.Completion,
TotalTokens: tokenUsage.Prompt + tokenUsage.Completion,
}
if extraUsage {
usage.TimingTokenGeneration = tokenUsage.TimingTokenGeneration
usage.TimingPromptProcessing = tokenUsage.TimingPromptProcessing
}
// Usage rides on the struct for the consumer to track the
// running cumulative; the consumer strips it before marshalling
// so intermediate chunks stay OpenAI-spec compliant.
usageForChunk := usage
resp := schema.OpenAIResponse{
ID: id,
Created: created,
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []schema.Choice{
{
Index: 0,
Text: s,
FinishReason: nil,
},
},
Object: "text_completion",
Usage: &usageForChunk,
}
xlog.Debug("Sending goroutine", "text", s)
responses <- resp
return true
}
_, _, _, err := ComputeChoices(req, s, config, cl, appConfig, loader, func(s string, c *[]schema.Choice) {}, tokenCallback)
close(responses)
return err
}
return func(c echo.Context) error {
created := int(time.Now().Unix())
// Handle Correlation
id := c.Request().Header.Get("X-Correlation-ID")
if id == "" {
id = uuid.New().String()
}
extraUsage := c.Request().Header.Get("Extra-Usage") != ""
input, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.OpenAIRequest)
if !ok || input.Model == "" {
return echo.ErrBadRequest
}
config, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
if !ok || config == nil {
return echo.ErrBadRequest
}
if config.ResponseFormatMap != nil {
d := schema.ChatCompletionResponseFormat{}
dat, _ := json.Marshal(config.ResponseFormatMap)
_ = json.Unmarshal(dat, &d)
if d.Type == "json_object" {
input.Grammar = functions.JSONBNF
}
}
config.Grammar = input.Grammar
xlog.Debug("Parameter Config", "config", config)
if input.Stream {
xlog.Debug("Stream request received")
c.Response().Header().Set("Content-Type", "text/event-stream")
c.Response().Header().Set("Cache-Control", "no-cache")
c.Response().Header().Set("Connection", "keep-alive")
if len(config.PromptStrings) > 1 {
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
}
predInput := config.PromptStrings[0]
templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.CompletionPromptTemplate, *config, templates.PromptTemplateData{
Input: predInput,
SystemPrompt: config.SystemPrompt,
ReasoningEffort: input.ReasoningEffort,
Metadata: input.Metadata,
})
if err == nil {
predInput = templatedInput
xlog.Debug("Template found, input modified", "input", predInput)
}
responses := make(chan schema.OpenAIResponse)
ended := make(chan error)
go func() {
ended <- process(id, predInput, input, config, ml, responses, extraUsage)
}()
var latestUsage *schema.OpenAIUsage
LOOP:
for {
select {
case ev := <-responses:
if len(ev.Choices) == 0 {
xlog.Debug("No choices in the response, skipping")
continue
}
// Capture running cumulative usage for the optional trailer
// emitted after the final stop chunk when include_usage=true.
if ev.Usage != nil {
latestUsage = ev.Usage
}
// OpenAI streaming spec: intermediate chunks must NOT
// carry a `usage` field. Strip the tracking copy now.
ev.Usage = nil
respData, err := json.Marshal(ev)
if err != nil {
xlog.Debug("Failed to marshal response", "error", err)
continue
}
xlog.Debug("Sending chunk", "chunk", string(respData))
_, err = fmt.Fprintf(c.Response().Writer, "data: %s\n\n", string(respData))
if err != nil {
return err
}
c.Response().Flush()
case err := <-ended:
if err == nil {
break LOOP
}
xlog.Error("Stream ended with error", "error", err)
stopReason := FinishReasonStop
errorResp := schema.OpenAIResponse{
ID: id,
Created: created,
Model: input.Model,
Choices: []schema.Choice{
{
Index: 0,
FinishReason: &stopReason,
Text: "Internal error: " + err.Error(),
},
},
Object: "text_completion",
}
errorData, marshalErr := json.Marshal(errorResp)
if marshalErr != nil {
xlog.Error("Failed to marshal error response", "error", marshalErr)
// Send a simple error message as fallback
fmt.Fprintf(c.Response().Writer, "data: {\"error\":\"Internal error\"}\n\n")
} else {
fmt.Fprintf(c.Response().Writer, "data: %s\n\n", string(errorData))
}
c.Response().Flush()
return nil
}
}
stopReason := FinishReasonStop
resp := &schema.OpenAIResponse{
ID: id,
Created: created,
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []schema.Choice{
{
Index: 0,
FinishReason: &stopReason,
},
},
Object: "text_completion",
}
respData, _ := json.Marshal(resp)
fmt.Fprintf(c.Response().Writer, "data: %s\n\n", respData)
// Trailing usage chunk per OpenAI spec: emit only when the caller
// opted in via stream_options.include_usage.
if input.StreamOptions != nil && input.StreamOptions.IncludeUsage && latestUsage != nil {
trailer := streamUsageTrailerJSON(id, input.Model, created, *latestUsage)
_, _ = fmt.Fprintf(c.Response().Writer, "data: %s\n\n", trailer)
}
fmt.Fprintf(c.Response().Writer, "data: [DONE]\n\n")
c.Response().Flush()
return nil
}
var result []schema.Choice
totalTokenUsage := backend.TokenUsage{}
for k, i := range config.PromptStrings {
templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.CompletionPromptTemplate, *config, templates.PromptTemplateData{
SystemPrompt: config.SystemPrompt,
Input: i,
ReasoningEffort: input.ReasoningEffort,
Metadata: input.Metadata,
})
if err == nil {
i = templatedInput
xlog.Debug("Template found, input modified", "input", i)
}
r, tokenUsage, _, err := ComputeChoices(
input, i, config, cl, appConfig, ml, func(s string, c *[]schema.Choice) {
stopReason := FinishReasonStop
*c = append(*c, schema.Choice{Text: s, FinishReason: &stopReason, Index: k})
}, nil)
if err != nil {
return err
}
totalTokenUsage.TimingTokenGeneration += tokenUsage.TimingTokenGeneration
totalTokenUsage.TimingPromptProcessing += tokenUsage.TimingPromptProcessing
result = append(result, r...)
}
usage := schema.OpenAIUsage{
PromptTokens: totalTokenUsage.Prompt,
CompletionTokens: totalTokenUsage.Completion,
TotalTokens: totalTokenUsage.Prompt + totalTokenUsage.Completion,
}
if extraUsage {
usage.TimingTokenGeneration = totalTokenUsage.TimingTokenGeneration
usage.TimingPromptProcessing = totalTokenUsage.TimingPromptProcessing
}
resp := &schema.OpenAIResponse{
ID: id,
Created: created,
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
Usage: &usage,
}
jsonResult, _ := json.Marshal(resp)
xlog.Debug("Response", "response", string(jsonResult))
// Return the prediction in the response body
return c.JSON(200, resp)
}
}