Files
LocalAI/core/http/middleware/request.go
T
Richard Palethorpe d10374f849 feat(router): make KNN a first-class classifier with a persisted, curated corpus (#10652)
* feat(router): make KNN a first-class classifier with a persisted, curated corpus

Add `classifier: knn` — similarity-weighted voting over labelled
example prompts. Unlike score/colbert it needs no classifier model:
label knowledge lives in a corpus seeded and curated through the
admin API, so routing decisions are deterministic, auditable, and
grounded in graded experience rather than a model's opinion.

Epistemic gate: corpus entries below knn.similarity_threshold cannot
vote; when none clears it the classifier activates no labels and the
router uses the fallback — a prompt unlike all labelled experience is
treated as undecidable, not guessed. Decisions record
nearest_similarity (also on fallback rows) so admins can see how far
the nearest labelled experience was; the Routing tab explains
out-of-corpus fallbacks and shows per-label corpus counts.

Persistence: one JSONL file per router under
<data path>/router-corpus (text, labels, vector, embedder
fingerprint). The file is the source of truth; the local-store index
is rebuilt from it at classifier build time and stays a pure
in-memory index. Entries recorded under a different embedding model
re-embed on load. Also corrects the docs' false claim that
local-store collections persist — the embedding cache never survived
restarts (and still doesn't); the corpus does.

Corpus input is API-only by design (entries may contain example user
content): POST /api/router/{name}/corpus seeds (labels validated
against declared policies, embedded server-side, indexed
immediately), GET .../corpus/stats inspects — label counts only,
entry texts are never returned by any surface — DELETE .../corpus
wipes. Admin-gated like the sibling router endpoints, and exposed as
MCP tools (seed_router_corpus / get_router_corpus_stats /
clear_router_corpus) in both the httpapi and inproc clients with
coverage-test route mappings.

Plumbing: VectorStore gains SearchK (top-K was hardcoded to 1);
local-store gets InsertBatch/Delete as optional fast paths;
RouterConfig gains a knn block (embedding_model, k,
similarity_threshold, vote_threshold, store_name) with meta-registry
fields; the classifier dropdown now offers knn and the
previously-missing colbert; embedding_cache is ignored (with a
warning) for knn — it IS an embedding-KNN lookup; the stale
/api/instructions intelligent-routing entry is rewritten (it
described a classifier that no longer exists); swagger regenerated.

Tests: KNN vote/gate specs with hand-computed vote shares, corpus
manager suite (restart reload without re-embedding, fingerprint
re-embed, dedupe, hostile store names), middleware specs (corpus
routing, gate fallback, config validation, cache-wrap refusal),
corpus endpoint specs pinning the texts-never-returned contract, MCP
catalog + route-mapping gates, and a Playwright spec for corpus
stats and the out-of-corpus decision detail.

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(router): name consulted corpus neighbours in knn decisions

Every knn decision (decision log rows and the /api/router/decide
response) now carries neighbors: the K retrieved corpus entries by
descending similarity - including ones below the epistemic gate, which
is what makes fallback decisions diagnosable - each as {id, similarity,
labels}. The id is the entry's content hash (first 8 bytes of the
SHA-256 of its text, hex): stable across reseeds and re-embeds, and
text-free, so an external platform that seeded the corpus can recompute
text->id on its own copy and bucket decisions by corpus region (per-
region reliability accounting) without corpus text ever leaving the
server. A corrupt index payload surfaces as an id-less neighbour at a
real similarity instead of disappearing.

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* refactor(router): deduplicate knn plumbing and cut corpus hot-path waste

Post-review cleanup of the knn-first-class-router branch; no behaviour
changes on the API surface.

Reuse/altitude:
- RouterKNNConfig.ResolvedStoreName is now the single source of the
  router-corpus-<name> default (was hand-derived in four files).
- corpus.ResolveKNNRouter + corpus.Seed carry the shared model
  resolution and seed validation; the REST endpoints and the assistant
  MCP client are thin transport adapters over them, with sentinel
  errors mapped to HTTP statuses at the echo boundary.
- middleware.NewClassifierDeps assembles the classifier dependency set
  once for all five entry points (OpenAI, Anthropic, realtime, decide,
  corpus) instead of five hand-copied literals.
- router.AllClassifiers feeds both the status endpoint and the
  unknown-classifier error, ending the classifier-list drift.
- Per-classifier requirements moved out of validateRouterPolicies into
  their buildClassifier arms; the knn arm owns its embedding_cache
  opt-out instead of a name-check in the shared wrap tail.
- adminOnly replaces four inline copies of the admin gate in the
  middleware routes.
- localVectorStore.Search delegates to SearchK (identical traces).

Efficiency:
- Manager.Add embeds outside the manager mutex and appends to the
  JSONL file (O(new) instead of O(corpus) rewrite); a torn tail from a
  crash mid-append is tolerated on read and repaired on next write.
- Stats memoises per store keyed on the file's stat fingerprint and no
  longer takes the manager mutex, so the 5s status poll stops parsing
  vector-laden JSONL and stops blocking behind seeds.
- KNN Classify decodes each neighbour payload once (was twice) and
  builds refs and votes in a single pass with one fallback return.
- Corpus file writes fsync before rename/close.
- The corpus manager is built eagerly in newApplication (sync.Once
  dropped); test helper dead branch removed.

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(router): bind knn corpus vectors to an embedder fingerprint and fail closed on mismatch

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* chore(mcp): align corpus tool prompts and the mutating-tool safety list

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(proto,backend): report embedding shape from the llama-cpp backend

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(embeddings): Go-side pooling — mean/last/decayed_mean with half-life

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(embeddings): accept chat messages[] and per-request pooling on /v1/embeddings

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* chore(middleware): name the failing fields when post-merge validation 400s

An intermittent post-merge validation failure surfaced as an opaque 400
during integration (pooling scheme mismatch that no client had sent).
Log the model, the request's pooling override, and the merged config's
pooling fields at the failure point so the next occurrence identifies
whether the request or the stored config carried the bad value.

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(embeddings): scheme override must not inherit the config's half-life

A model config defaulting to decayed_mean pooling carries
pooling_half_life_tokens; a request overriding the scheme to mean/last
without its own half-life inherited that value, and post-merge
validation rejected the pair the server itself had assembled. Zero the
inherited half-life when the overridden scheme is not decayed_mean; a
request that explicitly pairs a half-life with a non-decayed scheme
still 400s.

Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix embedding pooling validation and router bounds

Declare backend embedding layouts and reject incompatible pooling modes. Reset local-store dimensions after a full clear, validate KNN thresholds, and add real backend and store integration coverage.

Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* ci: run local-store integration tests

Build and install the local-store backend in the Linux test job, then run the existing store integration suite so new specs are discovered automatically.

Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-08-18 09:37:43 +02:00

790 lines
26 KiB
Go

package middleware
import (
"context"
"encoding/json"
"fmt"
"net/http"
"strconv"
"strings"
"github.com/google/uuid"
"github.com/labstack/echo/v4"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/galleryop"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/distributedhdr"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/mudler/xlog"
)
type correlationIDKeyType string
// CorrelationIDKey to track request across process boundary
const CorrelationIDKey correlationIDKeyType = "correlationID"
type RequestExtractor struct {
modelConfigLoader *config.ModelConfigLoader
modelLoader *model.ModelLoader
applicationConfig *config.ApplicationConfig
}
func NewRequestExtractor(modelConfigLoader *config.ModelConfigLoader, modelLoader *model.ModelLoader, applicationConfig *config.ApplicationConfig) *RequestExtractor {
return &RequestExtractor{
modelConfigLoader: modelConfigLoader,
modelLoader: modelLoader,
applicationConfig: applicationConfig,
}
}
const CONTEXT_LOCALS_KEY_MODEL_NAME = "MODEL_NAME"
const CONTEXT_LOCALS_KEY_LOCALAI_REQUEST = "LOCALAI_REQUEST"
const CONTEXT_LOCALS_KEY_MODEL_CONFIG = "MODEL_CONFIG"
// TODO: Refactor to not return error if unchanged
func (re *RequestExtractor) setModelNameFromRequest(c echo.Context) {
model, ok := c.Get(CONTEXT_LOCALS_KEY_MODEL_NAME).(string)
if ok && model != "" {
return
}
model = c.Param("model")
if model == "" {
model = c.QueryParam("model")
}
// Check FormValue for multipart/form-data requests (e.g., /v1/images/inpainting)
if model == "" {
model = c.FormValue("model")
}
if model == "" {
// Set model from bearer token, if available
auth := c.Request().Header.Get("Authorization")
bearer := strings.TrimPrefix(auth, "Bearer ")
if bearer != "" && bearer != auth {
exists, err := galleryop.CheckIfModelExists(re.modelConfigLoader, re.modelLoader, bearer, galleryop.ALWAYS_INCLUDE)
if err == nil && exists {
model = bearer
}
}
}
c.Set(CONTEXT_LOCALS_KEY_MODEL_NAME, model)
}
func (re *RequestExtractor) BuildConstantDefaultModelNameMiddleware(defaultModelName string) echo.MiddlewareFunc {
return func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
re.setModelNameFromRequest(c)
localModelName, ok := c.Get(CONTEXT_LOCALS_KEY_MODEL_NAME).(string)
if !ok || localModelName == "" {
c.Set(CONTEXT_LOCALS_KEY_MODEL_NAME, defaultModelName)
xlog.Debug("context local model name not found, setting to default", "defaultModelName", defaultModelName)
}
return next(c)
}
}
}
func (re *RequestExtractor) BuildFilteredFirstAvailableDefaultModel(filterFn config.ModelConfigFilterFn) echo.MiddlewareFunc {
return func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
re.setModelNameFromRequest(c)
localModelName := c.Get(CONTEXT_LOCALS_KEY_MODEL_NAME).(string)
if localModelName != "" { // Don't overwrite existing values
return next(c)
}
modelNames, err := galleryop.ListModels(re.modelConfigLoader, re.modelLoader, filterFn, galleryop.SKIP_IF_CONFIGURED)
if err != nil {
xlog.Error("non-fatal error calling ListModels during SetDefaultModelNameToFirstAvailable()", "error", err)
return next(c)
}
if len(modelNames) == 0 {
xlog.Warn("SetDefaultModelNameToFirstAvailable used with no matching models installed")
// This is non-fatal - making it so was breaking the case of direct installation of raw models
// return errors.New("this endpoint requires at least one model to be installed")
return next(c)
}
c.Set(CONTEXT_LOCALS_KEY_MODEL_NAME, modelNames[0])
xlog.Debug("context local model name not found, setting to the first model", "first model name", modelNames[0])
return next(c)
}
}
}
// TODO: If context and cancel above belong on all methods, move that part of above into here!
// Otherwise, it's in its own method below for now
func (re *RequestExtractor) SetModelAndConfig(initializer func() schema.LocalAIRequest) echo.MiddlewareFunc {
return func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
input := initializer()
if input == nil {
return echo.NewHTTPError(http.StatusBadRequest, "unable to initialize body")
}
if err := c.Bind(input); err != nil {
return echo.NewHTTPError(http.StatusBadRequest, fmt.Sprintf("failed parsing request body: %v", err))
}
// If this request doesn't have an associated model name, fetch it from earlier in the middleware chain
if input.ModelName(nil) == "" {
localModelName, ok := c.Get(CONTEXT_LOCALS_KEY_MODEL_NAME).(string)
if ok && localModelName != "" {
xlog.Debug("overriding empty model name in request body with value found earlier in middleware chain", "context localModelName", localModelName)
input.ModelName(&localModelName)
}
}
modelName := input.ModelName(nil)
cfg, err := re.modelConfigLoader.LoadModelConfigFileByNameDefaultOptions(modelName, re.applicationConfig)
if err != nil {
xlog.Warn("Model Configuration File not found", "model", modelName, "error", err)
} else if cfg.Model == "" && modelName != "" {
xlog.Debug("config does not include model, using input", "input.ModelName", modelName)
cfg.Model = modelName
}
// If a model name was specified, verify it actually exists before proceeding.
// Check both configured models and loose model files in the model path.
// Skip the check for HuggingFace model IDs (contain "/") since backends
// like diffusers may download these on the fly.
if modelName != "" && !strings.Contains(modelName, "/") {
exists, existsErr := galleryop.CheckIfModelExists(re.modelConfigLoader, re.modelLoader, modelName, galleryop.ALWAYS_INCLUDE)
if existsErr == nil && !exists {
return c.JSON(http.StatusNotFound, schema.ErrorResponse{
Error: &schema.APIError{
Message: fmt.Sprintf("model %q not found. To see available models, call GET /v1/models", modelName),
Code: http.StatusNotFound,
Type: "invalid_request_error",
},
})
}
}
// Resolve a model alias to its target before the disabled check and
// before storing MODEL_CONFIG, so every modality (chat, embeddings,
// tts, image, ...) inherits redirection. The response keeps echoing
// the alias name (input.ModelName is left unchanged); usage accounting
// records requested=alias / served=target.
if cfg != nil && cfg.IsAlias() {
resolved, _, aliasErr := re.modelConfigLoader.ResolveAlias(cfg)
if aliasErr != nil {
return c.JSON(http.StatusBadRequest, schema.ErrorResponse{
Error: &schema.APIError{
Message: aliasErr.Error(),
Code: http.StatusBadRequest,
Type: "invalid_request_error",
},
})
}
c.Set(ContextKeyRequestedModel, modelName)
c.Set(ContextKeyServedModel, resolved.Name)
cfg = resolved
}
// Check if the model is disabled
if cfg != nil && cfg.IsDisabled() {
return c.JSON(http.StatusForbidden, schema.ErrorResponse{
Error: &schema.APIError{
Message: fmt.Sprintf("model %q is disabled and cannot be loaded. Enable it via the System page or API to use it.", modelName),
Code: http.StatusForbidden,
Type: "model_disabled",
},
})
}
c.Set(CONTEXT_LOCALS_KEY_LOCALAI_REQUEST, input)
c.Set(CONTEXT_LOCALS_KEY_MODEL_CONFIG, cfg)
return next(c)
}
}
}
func (re *RequestExtractor) SetOpenAIRequest(c echo.Context) error {
input, ok := c.Get(CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.OpenAIRequest)
if !ok || input.Model == "" {
return echo.ErrBadRequest
}
cfg, ok := c.Get(CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
if !ok || cfg == nil {
return echo.ErrBadRequest
}
// Extract or generate the correlation ID
correlationID := c.Request().Header.Get("X-Correlation-ID")
if correlationID == "" {
correlationID = uuid.New().String()
}
c.Response().Header().Set("X-Correlation-ID", correlationID)
// Use the request context directly - Echo properly supports context cancellation!
// No need for workarounds like handleConnectionCancellation
reqCtx := c.Request().Context()
c1, cancel := context.WithCancel(re.applicationConfig.Context)
// Cancel when request context is cancelled (client disconnects)
go func() {
select {
case <-reqCtx.Done():
cancel()
case <-c1.Done():
// Already cancelled
}
}()
// Add the correlation ID to the new context
ctxWithCorrelationID := context.WithValue(c1, CorrelationIDKey, correlationID)
ctxWithCorrelationID = distributedhdr.Inherit(ctxWithCorrelationID, reqCtx)
input.Context = ctxWithCorrelationID
input.Cancel = cancel
err := mergeOpenAIRequestAndModelConfig(cfg, input)
if err != nil {
return err
}
if cfg.Model == "" {
xlog.Debug("replacing empty cfg.Model with input value", "input.Model", input.Model)
cfg.Model = input.Model
}
c.Set(CONTEXT_LOCALS_KEY_LOCALAI_REQUEST, input)
c.Set(CONTEXT_LOCALS_KEY_MODEL_CONFIG, cfg)
return nil
}
// extractToolChoiceFunctionName parses a tool_choice map and returns the
// specific function name. Accepts both the OpenAI-spec nested shape
// ({type:function, function:{name:...}}) and the legacy/Anthropic-compat
// flat shape ({type:function, name:...}); the nested form wins when both
// are present. Returns "" for malformed input or when the shape names a
// mode rather than a specific tool.
func extractToolChoiceFunctionName(m map[string]any) string {
tcType, ok := m["type"].(string)
if !ok || tcType != "function" {
return ""
}
if fn, ok := m["function"].(map[string]any); ok {
if n, ok := fn["name"].(string); ok && n != "" {
return n
}
}
if n, ok := m["name"].(string); ok {
return n
}
return ""
}
func mergeOpenAIRequestAndModelConfig(config *config.ModelConfig, input *schema.OpenAIRequest) error {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != nil {
config.TopK = input.TopK
}
if input.TopP != nil {
config.TopP = input.TopP
}
if input.MinP != nil {
config.MinP = input.MinP
}
if input.Backend != "" {
config.Backend = input.Backend
}
if input.ClipSkip != 0 {
config.Diffusers.ClipSkip = input.ClipSkip
}
if input.NegativePromptScale != 0 {
config.NegativePromptScale = input.NegativePromptScale
}
if input.NegativePrompt != "" {
config.NegativePrompt = input.NegativePrompt
}
if input.RopeFreqBase != 0 {
config.RopeFreqBase = input.RopeFreqBase
}
if input.RopeFreqScale != 0 {
config.RopeFreqScale = input.RopeFreqScale
}
if input.Grammar != "" {
config.Grammar = input.Grammar
}
if input.Temperature != nil {
config.Temperature = input.Temperature
}
// Resolve the effective reasoning effort (request overrides the model config
// default), store it so gRPCPredictOpts forwards it to the backend as the
// reasoning_effort chat_template_kwarg (what gpt-oss / LFM2.5 read), and map
// it onto the enable_thinking toggle. "none" disables thinking (the #10072
// use case); a level enables it unless the config already disabled reasoning
// (an operator's explicit disable wins over a request asking to think).
config.ApplyReasoningEffort(input.ReasoningEffort)
// Forward the client's request metadata so chat-template kwargs set per-request
// (enable_thinking, reasoning_effort, preserve_thinking, ...) reach the backend
// and override the model's reasoning-config defaults. See gRPCPredictOpts.
if len(input.Metadata) > 0 {
config.RequestMetadata = input.Metadata
}
// Collapse the modern max_completion_tokens alias into the
// legacy Maxtokens field so downstream code reads exactly one.
// MaxCompletionTokens wins on conflict — it's the canonical
// name per OpenAI's deprecation guidance, and a client that
// took the trouble to send it intends that value. Clearing
// the sibling prevents both names from being emitted if input
// is re-marshaled (cloud-proxy passthrough).
if input.MaxCompletionTokens != nil {
input.Maxtokens = input.MaxCompletionTokens
input.MaxCompletionTokens = nil
}
if input.Maxtokens != nil {
config.Maxtokens = input.Maxtokens
}
if input.ResponseFormat != nil {
switch responseFormat := input.ResponseFormat.(type) {
case string:
config.ResponseFormat = responseFormat
case map[string]any:
config.ResponseFormatMap = responseFormat
}
}
switch stop := input.Stop.(type) {
case string:
if stop != "" {
config.StopWords = append(config.StopWords, stop)
}
case []any:
for _, pp := range stop {
if s, ok := pp.(string); ok {
config.StopWords = append(config.StopWords, s)
}
}
}
if len(input.Tools) > 0 {
for _, tool := range input.Tools {
input.Functions = append(input.Functions, tool.Function)
}
}
if input.ToolsChoice != nil {
// OpenAI tool_choice has three valid shapes plus one tolerated
// non-spec form seen in the wild:
//
// 1. string mode: "auto" | "none" | "required"
// 2. specific tool: {"type":"function", "function":{"name":"..."}} (current spec)
// 3. legacy: {"type":"function", "name":"..."} (older / Anthropic-compat)
// 4. double-encoded: "{\"type\":\"function\", ...}" (some clients serialize the object)
//
// The pre-#9559 code unmarshalled the string case through
// json.Unmarshal([]byte(content), &functions.Tool{}), which:
// - failed for plain string modes (so "required" / "none" were
// silently ignored and tools stayed enabled regardless), but
// - happened to handle shape 4 by accident.
// It also could not parse shape 3 because functions.Tool has no
// flat top-level Name field.
//
// Mirror the parsing pattern from MergeOpenResponsesConfig (#9509),
// route results through the existing input.FunctionCall string/map
// dispatch downstream (see the switch on input.FunctionCall in this
// same function), and preserve the shape-4 fallback so non-spec
// clients don't silently break. Tracked in #9508; sibling fix in #9526.
switch content := input.ToolsChoice.(type) {
case string:
// "auto" is the default and needs no override. "none" and "required"
// both reach SetFunctionCallString via the input.FunctionCall string
// branch below; ShouldUseFunctions() then returns false for "none"
// (tools disabled) and true for "required" (mode engaged).
//
// If the string looks like a JSON object, try shape 4 first: parse
// it as a tool_choice map and use the resulting name. Falling back
// to mode-string handling when the parse yields no usable name keeps
// genuinely-malformed input from accidentally engaging a mode.
if content == "" || content == "auto" {
break
}
if strings.HasPrefix(strings.TrimSpace(content), "{") {
var nested map[string]any
if err := json.Unmarshal([]byte(content), &nested); err == nil {
if name := extractToolChoiceFunctionName(nested); name != "" {
input.FunctionCall = map[string]any{"name": name}
break
}
}
}
input.FunctionCall = content
case map[string]any:
if name := extractToolChoiceFunctionName(content); name != "" {
input.FunctionCall = map[string]any{"name": name}
}
}
}
// Decode each request's message content
imgIndex, vidIndex, audioIndex := 0, 0, 0
for i, m := range input.Messages {
nrOfImgsInMessage := 0
nrOfVideosInMessage := 0
nrOfAudiosInMessage := 0
switch content := m.Content.(type) {
case string:
input.Messages[i].StringContent = content
case []any:
dat, _ := json.Marshal(content)
c := []schema.Content{}
json.Unmarshal(dat, &c)
textContent := ""
// we will template this at the end
CONTENT:
for _, pp := range c {
switch pp.Type {
case "text":
textContent += pp.Text
//input.Messages[i].StringContent = pp.Text
case "video", "video_url":
// Decode content as base64 either if it's an URL or base64 text
base64, err := utils.GetContentURIAsBase64(pp.VideoURL.URL)
if err != nil {
xlog.Error("Failed encoding video", "error", err)
continue CONTENT
}
input.Messages[i].StringVideos = append(input.Messages[i].StringVideos, base64) // TODO: make sure that we only return base64 stuff
vidIndex++
nrOfVideosInMessage++
case "audio_url", "audio":
// Decode content as base64 either if it's an URL or base64 text
base64, err := utils.GetContentURIAsBase64(pp.AudioURL.URL)
if err != nil {
xlog.Error("Failed encoding audio", "error", err)
continue CONTENT
}
input.Messages[i].StringAudios = append(input.Messages[i].StringAudios, base64) // TODO: make sure that we only return base64 stuff
audioIndex++
nrOfAudiosInMessage++
case "input_audio":
// TODO: make sure that we only return base64 stuff
input.Messages[i].StringAudios = append(input.Messages[i].StringAudios, pp.InputAudio.Data)
audioIndex++
nrOfAudiosInMessage++
case "image_url", "image":
// Decode content as base64 either if it's an URL or base64 text
base64, err := utils.GetContentURIAsBase64(pp.ImageURL.URL)
if err != nil {
xlog.Error("Failed encoding image", "error", err)
continue CONTENT
}
input.Messages[i].StringImages = append(input.Messages[i].StringImages, base64) // TODO: make sure that we only return base64 stuff
imgIndex++
nrOfImgsInMessage++
}
}
// When the backend handles templating itself (UseTokenizerTemplate),
// it also injects media markers server-side (see
// oaicompat_chat_params_parse in llama.cpp). Emitting our own markers
// here would double-mark them and downstream consumers ignore
// StringContent in that path anyway, so just pass through plain text.
if config.TemplateConfig.UseTokenizerTemplate {
input.Messages[i].StringContent = textContent
} else {
input.Messages[i].StringContent, _ = templates.TemplateMultiModal(config.TemplateConfig.Multimodal, templates.MultiModalOptions{
TotalImages: imgIndex,
TotalVideos: vidIndex,
TotalAudios: audioIndex,
ImagesInMessage: nrOfImgsInMessage,
VideosInMessage: nrOfVideosInMessage,
AudiosInMessage: nrOfAudiosInMessage,
}, textContent)
}
}
}
if input.RepeatPenalty != 0 {
config.RepeatPenalty = input.RepeatPenalty
}
if input.FrequencyPenalty != 0 {
config.FrequencyPenalty = input.FrequencyPenalty
}
if input.PresencePenalty != 0 {
config.PresencePenalty = input.PresencePenalty
}
if input.Keep != 0 {
config.Keep = input.Keep
}
if input.Batch != 0 {
config.Batch = input.Batch
}
if input.IgnoreEOS {
config.IgnoreEOS = input.IgnoreEOS
}
if input.Seed != nil {
config.Seed = input.Seed
}
if input.TypicalP != nil {
config.TypicalP = input.TypicalP
}
xlog.Debug("input.Input", "input", fmt.Sprintf("%+v", input.Input))
switch inputs := input.Input.(type) {
case string:
if inputs != "" {
config.InputStrings = append(config.InputStrings, inputs)
}
case []any:
for _, pp := range inputs {
switch i := pp.(type) {
case string:
config.InputStrings = append(config.InputStrings, i)
case []any:
tokens := []int{}
inputStrings := []string{}
for _, ii := range i {
switch ii := ii.(type) {
case int:
tokens = append(tokens, ii)
case float64:
tokens = append(tokens, int(ii))
case string:
inputStrings = append(inputStrings, ii)
default:
xlog.Error("Unknown input type", "type", fmt.Sprintf("%T", ii))
}
}
config.InputToken = append(config.InputToken, tokens)
config.InputStrings = append(config.InputStrings, inputStrings...)
}
}
}
// Per-request Go-side pooling override for /v1/embeddings (LocalAI
// extension) — copy-if-set onto the per-request config like the Input
// handling above; the embeddings endpoint validates the merged values.
if input.Pooling != "" {
config.Pooling = input.Pooling
// The config's default half-life belongs to its own decayed_mean
// default. A request that overrides the scheme without sending its
// own half-life must not inherit it, or the merged pair (e.g.
// "mean" + 256) fails validation through no fault of the client.
// (literal because the `config` parameter shadows the package;
// this is config.PoolingDecayedMean)
if input.PoolingHalfLifeTokens == 0 && input.Pooling != "decayed_mean" {
config.PoolingHalfLifeTokens = 0
}
}
if input.PoolingHalfLifeTokens != 0 {
config.PoolingHalfLifeTokens = input.PoolingHalfLifeTokens
}
// Can be either a string or an object
switch fnc := input.FunctionCall.(type) {
case string:
if fnc != "" {
config.SetFunctionCallString(fnc)
}
case map[string]any:
var name string
n, exists := fnc["name"]
if exists {
nn, e := n.(string)
if e {
name = nn
}
}
config.SetFunctionCallNameString(name)
}
switch p := input.Prompt.(type) {
case string:
config.PromptStrings = append(config.PromptStrings, p)
case []any:
for _, pp := range p {
if s, ok := pp.(string); ok {
config.PromptStrings = append(config.PromptStrings, s)
}
}
}
// If a quality was defined as number, convert it to step
if input.Quality != "" {
q, err := strconv.Atoi(input.Quality)
if err == nil {
config.Step = q
}
}
if valid, err := config.Validate(); !valid {
// The base config validated at load time, so a post-merge failure
// can only come from request-supplied fields: surface it as a 400
// with the underlying cause rather than an opaque 500.
xlog.Warn("post-merge validation failed",
"model", config.Name, "err", err,
"inputPooling", input.Pooling, "cfgPooling", config.Pooling,
"cfgHalfLife", config.PoolingHalfLifeTokens, "options", config.Options)
return echo.NewHTTPError(http.StatusBadRequest, fmt.Sprintf("unable to validate configuration after merging: %v", err))
}
return nil
}
func (re *RequestExtractor) SetOpenResponsesRequest(c echo.Context) error {
input, ok := c.Get(CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.OpenResponsesRequest)
if !ok || input.Model == "" {
return echo.ErrBadRequest
}
// Convert input items to Messages (this will be done in the endpoint handler)
// We store the input in the request for the endpoint to process
cfg, ok := c.Get(CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
if !ok || cfg == nil {
return echo.ErrBadRequest
}
// Extract or generate the correlation ID (Open Responses uses x-request-id)
correlationID := c.Request().Header.Get("x-request-id")
if correlationID == "" {
correlationID = uuid.New().String()
}
c.Response().Header().Set("x-request-id", correlationID)
// Use the request context directly - Echo properly supports context cancellation!
reqCtx := c.Request().Context()
c1, cancel := context.WithCancel(re.applicationConfig.Context)
// Cancel when request context is cancelled (client disconnects)
go func() {
select {
case <-reqCtx.Done():
cancel()
case <-c1.Done():
// Already cancelled
}
}()
// Add the correlation ID to the new context
ctxWithCorrelationID := context.WithValue(c1, CorrelationIDKey, correlationID)
ctxWithCorrelationID = distributedhdr.Inherit(ctxWithCorrelationID, reqCtx)
input.Context = ctxWithCorrelationID
input.Cancel = cancel
err := MergeOpenResponsesConfig(cfg, input)
if err != nil {
return err
}
if cfg.Model == "" {
xlog.Debug("replacing empty cfg.Model with input value", "input.Model", input.Model)
cfg.Model = input.Model
}
c.Set(CONTEXT_LOCALS_KEY_LOCALAI_REQUEST, input)
c.Set(CONTEXT_LOCALS_KEY_MODEL_CONFIG, cfg)
return nil
}
// MergeOpenResponsesConfig merges request parameters into the model configuration.
func MergeOpenResponsesConfig(config *config.ModelConfig, input *schema.OpenResponsesRequest) error {
// Temperature
if input.Temperature != nil {
config.Temperature = input.Temperature
}
// TopP
if input.TopP != nil {
config.TopP = input.TopP
}
// MaxOutputTokens -> Maxtokens
if input.MaxOutputTokens != nil {
config.Maxtokens = input.MaxOutputTokens
}
// Convert tools to functions - this will be handled in the endpoint handler
// We just validate that tools are present if needed
// Handle tool_choice
if input.ToolChoice != nil {
switch tc := input.ToolChoice.(type) {
case string:
// "auto", "required", or "none"
if tc == "required" {
config.SetFunctionCallString("required")
} else if tc == "none" {
// Don't use tools - handled in endpoint
}
// "auto" is default - let model decide
case map[string]any:
// Specific tool. OpenAI spec nests the function name under "function":
// {"type":"function", "function":{"name":"..."}}
// Legacy/Anthropic-compat form puts it at the top level:
// {"type":"function", "name":"..."}
// The old code only handled the legacy shape AND used the wrong
// setter (SetFunctionCallString writes the mode field; the
// specific-function name lives in a separate field read by
// ShouldCallSpecificFunction / FunctionToCall). Net effect: a
// correctly-formed OpenAI tool_choice never engaged grammar-based
// forcing, the model got the tools but no selection hint, and
// streamed raw JSON as delta.content instead of delta.tool_calls.
if tcType, ok := tc["type"].(string); ok && tcType == "function" {
var name string
if fn, ok := tc["function"].(map[string]any); ok {
if n, ok := fn["name"].(string); ok {
name = n
}
}
if name == "" {
if n, ok := tc["name"].(string); ok {
name = n
}
}
if name != "" {
config.SetFunctionCallNameString(name)
}
}
}
}
if valid, err := config.Validate(); !valid {
// The base config validated at load time, so a post-merge failure
// can only come from request-supplied fields: surface it as a 400
// with the underlying cause rather than an opaque 500.
return echo.NewHTTPError(http.StatusBadRequest, fmt.Sprintf("unable to validate configuration after merging: %v", err))
}
return nil
}