Files
LocalAI/core/http/routes/openai.go
LocalAI [bot] b0959d4756 feat(api): add GET /v1/models/capabilities endpoint (#10687)
Additive superset of /v1/models that enriches each model entry with the
capabilities it supports plus its input/output modalities
(text / image / audio / video). Clients that only understand /v1/models
are unaffected -- they simply never call the new route.

Audio and video *input* are derived from the model's multimodal limits
(vLLM limit_mm_per_prompt), which no single usecase FLAG expresses. That
gap is exactly why a plain capability list is insufficient and this
enriched endpoint exists: an attachment router can now decide whether an
image/audio/video file can go to the active model directly, or must be
converted/transcribed first.

Capability derivation lives in core/config as the single source of truth
(ModelConfig.Capabilities / InputModalities / OutputModalities /
VisionSupported / ...); the Ollama capability surface now delegates to
it instead of keeping a parallel copy. Vision is gated on
chat/completion capability so a MediaMarker hydrated onto a non-chat
model (e.g. a pure ASR/TTS backend) no longer reports a false vision
capability.

Read-only listing: no new FLAG_* flag, reuses the existing `models`
swagger tag, and intentionally exposes no MCP admin tool (there is
nothing to manage conversationally).

Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-07-05 08:51:55 +02:00

267 lines
13 KiB
Go

package routes
import (
"github.com/labstack/echo/v4"
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/endpoints/localai"
mcpTools "github.com/mudler/LocalAI/core/http/endpoints/mcp"
"github.com/mudler/LocalAI/core/http/endpoints/openai"
"github.com/mudler/LocalAI/core/http/middleware"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/routing/pii"
"github.com/mudler/LocalAI/core/services/routing/piiadapter"
"github.com/mudler/LocalAI/core/services/routing/router"
)
func RegisterOpenAIRoutes(app *echo.Echo,
re *middleware.RequestExtractor,
application *application.Application,
) {
// openAI compatible API endpoint
traceMiddleware := middleware.TraceMiddleware(application)
usageMiddleware := middleware.UsageMiddleware(application.StatsRecorder(), application.FallbackUser())
// X-LocalAI-Node attribution middleware: wraps the response writer and
// stamps the header on first write when --expose-node-header is on. No-op
// otherwise. Applied to every inference path that routes through
// ml.Load (chat, completion, embeddings, audio transcriptions/speech,
// image generation/inpainting) so distributed-mode operators can observe
// which worker served each request.
nodeHeaderMiddleware := middleware.ExposeNodeHeader(application.ApplicationConfig())
// realtime
// TODO: Modify/disable the API key middleware for this endpoint to allow ephemeral keys created by sessions
app.GET("/v1/realtime", openai.Realtime(application))
app.POST("/v1/realtime/sessions", openai.RealtimeTranscriptionSession(application), traceMiddleware)
app.POST("/v1/realtime/transcription_session", openai.RealtimeTranscriptionSession(application), traceMiddleware)
app.POST("/v1/realtime/calls", openai.RealtimeCalls(application), traceMiddleware)
// NATS client for distributed MCP tool routing (nil when not in distributed mode)
var natsClient mcpTools.MCPNATSClient
if d := application.Distributed(); d != nil {
natsClient = d.Nats
}
// chat
chatHandler := openai.ChatEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.TemplatesEvaluator(), application.ApplicationConfig(), natsClient, application.LocalAIAssistant())
chatMiddleware := []echo.MiddlewareFunc{
nodeHeaderMiddleware,
usageMiddleware,
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_CHAT)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
// RouteModel runs AFTER the schema-specific request parser so
// the classifier sees a populated *schema.OpenAIRequest. When
// the resolved model has a Router config, the middleware
// rewrites input.Model to the chosen candidate, swaps
// MODEL_CONFIG, and stamps RequestedModel/ServedModel for the
// usage log. Models without a Router pass through.
middleware.RouteModel(
application.ModelConfigLoader(),
application.ApplicationConfig(),
application.RouterDecisions(),
application.FallbackUser(),
middleware.OpenAIProbe,
router.SourceChat,
middleware.ClassifierDeps{
Scorer: application.Scorer,
TokenCounter: application.TokenCounter,
Embedder: application.Embedder,
VectorStore: application.VectorStore,
Reranker: application.Reranker,
ModelLookup: application.ModelConfigLookup(),
Registry: application.RouterClassifierRegistry(),
Evaluator: application.TemplatesEvaluator(),
},
),
// Admission control runs after RouteModel so the SERVED
// model's limits apply — a router fanout that lands on a
// saturated downstream gets rejected even when the requested
// router-model has slack.
middleware.AdmissionControl(application.AdmissionLimiter(), application.PIIEvents()),
// PII redaction runs INNERMOST, after RouteModel has resolved
// the actual served model. This is what makes per-model PII
// configs honour the routed target (e.g., a router fans out to
// claude-strict; that model's pii block applies, not the
// router model's).
pii.RequestMiddleware(application.PIIRedactor(), application.PIIEvents(), piiadapter.OpenAI(), application.FallbackUser(), pii.WithNERResolver(application.PIINERResolver()), pii.WithPolicyResolver(application.PIIPolicyResolver())),
}
app.POST("/v1/chat/completions", chatHandler, chatMiddleware...)
app.POST("/chat/completions", chatHandler, chatMiddleware...)
// edit
editHandler := openai.EditEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.TemplatesEvaluator(), application.ApplicationConfig())
editMiddleware := []echo.MiddlewareFunc{
usageMiddleware,
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_EDIT)),
re.BuildConstantDefaultModelNameMiddleware("gpt-4o"),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
pii.RequestMiddleware(application.PIIRedactor(), application.PIIEvents(), piiadapter.OpenAICompletion(), application.FallbackUser(), pii.WithNERResolver(application.PIINERResolver()), pii.WithPolicyResolver(application.PIIPolicyResolver())),
}
app.POST("/v1/edits", editHandler, editMiddleware...)
app.POST("/edits", editHandler, editMiddleware...)
// completion
completionHandler := openai.CompletionEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.TemplatesEvaluator(), application.ApplicationConfig())
completionMiddleware := []echo.MiddlewareFunc{
nodeHeaderMiddleware,
usageMiddleware,
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_COMPLETION)),
re.BuildConstantDefaultModelNameMiddleware("gpt-4o"),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
pii.RequestMiddleware(application.PIIRedactor(), application.PIIEvents(), piiadapter.OpenAICompletion(), application.FallbackUser(), pii.WithNERResolver(application.PIINERResolver()), pii.WithPolicyResolver(application.PIIPolicyResolver())),
}
app.POST("/v1/completions", completionHandler, completionMiddleware...)
app.POST("/completions", completionHandler, completionMiddleware...)
app.POST("/v1/engines/:model/completions", completionHandler, completionMiddleware...)
// embeddings
embeddingHandler := openai.EmbeddingsEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
embeddingMiddleware := []echo.MiddlewareFunc{
nodeHeaderMiddleware,
usageMiddleware,
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_EMBEDDINGS)),
re.BuildConstantDefaultModelNameMiddleware("gpt-4o"),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
pii.RequestMiddleware(application.PIIRedactor(), application.PIIEvents(), piiadapter.OpenAICompletion(), application.FallbackUser(), pii.WithNERResolver(application.PIINERResolver()), pii.WithPolicyResolver(application.PIIPolicyResolver())),
}
app.POST("/v1/embeddings", embeddingHandler, embeddingMiddleware...)
app.POST("/embeddings", embeddingHandler, embeddingMiddleware...)
app.POST("/v1/engines/:model/embeddings", embeddingHandler, embeddingMiddleware...)
audioHandler := openai.TranscriptEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
audioMiddleware := []echo.MiddlewareFunc{
nodeHeaderMiddleware,
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_TRANSCRIPT)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
}
// audio
app.POST("/v1/audio/transcriptions", audioHandler, audioMiddleware...)
app.POST("/audio/transcriptions", audioHandler, audioMiddleware...)
diarizationHandler := openai.DiarizationEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
diarizationMiddleware := []echo.MiddlewareFunc{
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_DIARIZATION)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
}
app.POST("/v1/audio/diarization", diarizationHandler, diarizationMiddleware...)
app.POST("/audio/diarization", diarizationHandler, diarizationMiddleware...)
soundClassificationHandler := openai.SoundClassificationEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
soundClassificationMiddleware := []echo.MiddlewareFunc{
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_SOUND_CLASSIFICATION)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
}
app.POST("/v1/audio/classification", soundClassificationHandler, soundClassificationMiddleware...)
app.POST("/audio/classification", soundClassificationHandler, soundClassificationMiddleware...)
audioSpeechHandler := localai.TTSEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
audioSpeechMiddleware := []echo.MiddlewareFunc{
nodeHeaderMiddleware,
traceMiddleware,
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_TTS)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.TTSRequest) }),
}
app.POST("/v1/audio/speech", audioSpeechHandler, audioSpeechMiddleware...)
app.POST("/audio/speech", audioSpeechHandler, audioSpeechMiddleware...)
// images
imageHandler := openai.ImageEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
imageMiddleware := []echo.MiddlewareFunc{
nodeHeaderMiddleware,
traceMiddleware,
// Default: use the first available image generation model
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_IMAGE)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.OpenAIRequest) }),
func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
if err := re.SetOpenAIRequest(c); err != nil {
return err
}
return next(c)
}
},
}
app.POST("/v1/images/generations", imageHandler, imageMiddleware...)
app.POST("/images/generations", imageHandler, imageMiddleware...)
// inpainting endpoint (image + mask) - reuse same middleware config as images
inpaintingHandler := openai.InpaintingEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig())
app.POST("/v1/images/inpainting", inpaintingHandler, imageMiddleware...)
app.POST("/images/inpainting", inpaintingHandler, imageMiddleware...)
// List models
app.GET("/v1/models", openai.ListModelsEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig(), application.AuthDB()))
app.GET("/models", openai.ListModelsEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig(), application.AuthDB()))
// List models enriched with capabilities + input/output modalities
// (LocalAI-specific, additive superset of /v1/models).
capabilitiesHandler := openai.ListModelCapabilitiesEndpoint(application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig(), application.AuthDB())
app.GET("/v1/models/capabilities", capabilitiesHandler)
app.GET("/models/capabilities", capabilitiesHandler)
}