Files
LocalAI/backend/backend.proto
Richard Palethorpe 49ef40a187 feat(classifier/VAD): support voice control on low power devices (#10804)
* feat(llama-cpp): route Score through the slot loop

Score previously bypassed the slot loop with a direct llama_decode: a
conflict guard aborted the whole process if scoring raced generation, the
config validator had to reject score alongside chat/completion/embeddings,
and every candidate re-decoded the full shared prompt.

Add SERVER_TASK_TYPE_SCORE to the (patched) upstream server so score tasks
are scheduled like any other slot work: generation and scoring serialize
naturally, the shared prompt is decoded once per call, and the slot's
prompt cache carries the conversation prefix across calls. Context
checkpoints at the score boundary and at the cache-divergence point keep
SWA/hybrid/recurrent models (e.g. LFM2.5) from re-prefilling the whole
prompt per candidate: warm-turn scoring on a 6-option set drops from ~8s
to ~0.5s on a desktop CPU.

The conflict guard and the validation split are removed; declaring score
with generation usecases on one config is now supported and shares the
slot cache.

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

* feat(realtime): classifier wire types and pipeline config

Wire types and YAML config for realtime classifier mode: sessions carry a
localai_classifier extension (options with canned replies/tool calls,
softmax threshold, normalization, history trimming, fallback modes, and a
deterministic wake-word address gate), mirrored by pipeline.classifier in
the model YAML and surfaced in the config-meta registry. The
localai.classifier.result server event reports the full score distribution
per turn.

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

* feat(realtime): classifier response flow

Classifier-mode responses: instead of autoregressive generation, each user
turn is prefill-scored against the option list (router.ScoreClassifier
prompt/candidate shapes over the Score primitive) and the winning option's
canned reply and tool call are emitted through the existing response
machinery. Below-threshold turns take the configured fallback (none /
canned reply / generate); empty transcripts and unaddressed turns (wake
word not mentioned) skip scoring entirely. The scoring probe defaults to
the latest user message only — small scorers echo canned replies from
prior turns back as the top option otherwise.

Built for hardware that can afford prompt processing but not decode: with
slot-based Score the option list stays KV-cached across turns, so a turn
costs roughly one forward pass over the new words.

session_update_error events now carry the validation cause instead of a
generic message.

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

* fix(realtime): bound the VAD tick's scan window and buffer retention

The VAD tick loop re-scanned the entire input buffer every 300ms and only
trimmed it on zero-segment ticks or commits. Audio that keeps producing
segments without a committing pause (steady noise a mic pipeline lets
through, music, continuous speech) grew the buffer toward the 100MB cap
with each tick rescanning all of it — O(n^2), measured at ~3.3ms of silero
per buffered second: past ~90s retained, ticks run back to back and pin
~4 cores until the stream stops.

Silero's recurrent state only carries a few hundred ms of context, so
rescanning old audio buys nothing. Clip the slice handed to the VAD to the
largest silence the commit test can need to measure (server_vad silence
window or the semantic eagerness fallback) plus a warm-up margin, and
rebase the returned segment times so every downstream consumer keeps
whole-buffer coordinates. An open turn whose clipped window is all silence
now commits (the silence outran the window) instead of being discarded as
no-speech. Independently, retain at most 90s of raw buffer, rebasing the
live-feed and EOU cursors on trim — this also bounds the previously
unbounded VAD-error path. Turn boundaries are otherwise unchanged: no
forced commits, no new coordinator states.

pipeline.turn_detection.vad_window_sec can widen the scan window; values
below the automatic floor are ignored. The tick body is extracted into
vadTick so specs can drive turn detection synchronously (same shape as
classifySoundWindow); the babble reproduction that pinned 4 cores now
plateaus under 10% of one core.

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

* fix(backend): let per-model threads override the global default

ModelOptions overrode a set per-model threads value with the app-level
--threads whenever the latter was non-zero — and WithThreads defaults it
to the physical core count, so it always was. The YAML threads: knob has
been dead config: a tiny VAD model could never opt down from the global
pool size.

SetDefaults already fills an unset per-model value from the app config,
which is the intended precedence; resolve threads through a helper that
honors it (explicit threads: 0 still means unset).

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

* chore(gallery): single-thread the silero VAD

Silero is a ~2MB recurrent model with no exploitable graph parallelism:
measured per-call latency is identical at 1 and 10 ORT threads, while
every extra pool thread just spin-waits between the realtime loop's
frequent tiny inferences.

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

* docs(realtime): classifier mode, VAD scan window, threads precedence

Document the realtime classifier mode (options, threshold guidance,
wake-word address gate, empty-transcript handling), the VAD scan window
and 90s buffer retention (pipeline.turn_detection.vad_window_sec), the
per-model threads precedence, and the M3 classifier note in the realtime
state-machine design doc.

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

* perf(llama-cpp): score all candidates in one batched decode

One scoring call is now a single SERVER_TASK_TYPE_SCORE task: the slot
decodes the shared prefix (prompt + longest common candidate token
prefix) once, then forks one sequence per candidate off it
(metadata-only for the unified KV cache, copy-on-write for recurrent
state) and decodes every candidate's unique tail in one llama_decode.
Previously each candidate was its own task that restored the boundary
checkpoint and re-decoded its full tail sequentially, paying
per-candidate task and decode overhead.

The context reserves SERVER_SCORE_FORK_SEQS extra sequence ids (and
recurrent-state cells) beyond the parallel slots via the new
common_params::n_seq_score_forks. Forking requires the unified KV cache
(already this backend's default) since per-sequence streams would shrink
n_ctx_seq; an explicit kv_unified:false disables forking and Score calls
that need it fail cleanly. Candidates beyond the fork/output budget
decode in successive chunks.

Wire contract and scores are unchanged: per-token logprobs are stitched
from the shared region and the forked tails. Verified bitwise
deterministic call-to-call and independent of candidate order (no
cross-fork leakage via equal-length candidate swap); ranking matches the
per-candidate implementation on the drone battery (winner softmax
0.99996 vs 0.99997), and >16-candidate chunking, prefix-of-another and
empty candidates all pass.

Measured on a desktop CPU: warm /api/score calls 0.52s -> 0.23s; warm
realtime classifier turns 196-303ms. The 9-candidate drone turn decodes
~17 unique tail tokens in one batch instead of nine sequential ~220ms
checkpoint-restore tasks.

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

* fix(realtime): gate scoring capacity by model usecase

Reserve llama.cpp scoring slots only for models that explicitly declare the score usecase, while allowing score to coexist with chat and completion. Reject incompatible unified-KV settings and classifier activation on models without scoring capacity.

Propagate application defaults when resolving realtime and preload pipeline stages so unset thread counts are resolved consistently without overriding explicit model settings.

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

* fix(ci): honor APT mirrors in the prebuilt llama-cpp compile step

The builder-prebuilt path installs gcc-14 with apt directly and ignored
the APT_MIRROR/APT_PORTS_MIRROR build args the from-source path already
honors, so an ubuntu mirror outage broke every arm64 backend build. Pass
the args into the stage and run apt-mirror.sh (already in the build
context via COPY . /LocalAI) before the apt step.

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

* feat(realtime): classifier argument slots via constrained completion

Hybrid classify-then-complete: a classifier option's canned tool call can
declare typed argument slots (number | enum | string, with defaults and
prompt hints) referenced as "{{name}}" in the arguments template. When
the option wins, the slots are filled by a short grammar-constrained
completion that continues the exact scoring prompt — rendered by the same
cached ScoreClassifier, so the llama.cpp prompt cache is already warm —
with the chosen route JSON re-opened at the first slot field. A GBNF
grammar pins the field skeleton and frees only the values; temperature 0,
a couple dozen tokens at most (~300ms on a desktop CPU for two slots).

Slot declarations and hints ride the option descriptions in the shared
system prompt, informing scoring and the fill alike at no per-turn token
cost. The localai.classifier.result event carries the final arguments and
a fill_latency_ms. On inference failure the slots' defaults apply; a slot
without a default fails the response (or falls through with
fallback.mode: generate). Slot filling requires completion alongside
score in the scoring model's known_usecases.

Verified end-to-end on the Pi drone demo: "fly forward three meters" in
distance mode classifies forward and infers {"distance": 3, "units":
"meters"} in ~310ms, and the drone flies exactly 3 units.

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

* feat(realtime): splice filled slot values into classifier replies

A classifier option's spoken reply can now reference its tool's argument
slots ("Going forward {{distance}} {{units}}."): the values inferred by
the slot-fill completion — or the recovery defaults — are spliced into
the reply as plain text before it is emitted, so what the assistant says
confirms what it actually inferred. Placeholders without a value stay
literal, and options without slots are untouched.

FillToolArguments now returns the raw slot values alongside the spliced
arguments JSON to make the reply templating possible.

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

* fix(realtime): harden classifier slot completion

Reserve context for constrained slot filling, size completions from their encoded output, and encode enum grammar literals as valid JSON. Reject empty enum values and cover the failure modes with regression tests.

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

* feat(realtime): prewarm the classifier scoring prompt on registration

Swapping a session's classifier option list (a voice-switched command
mode, for instance) made the next turns pay a full re-prefill of the new
option-list prompt — measured 2.4s vs 0.3s warm on a desktop CPU, and
worse: on hybrid-memory models like LFM2.5, whose state cannot be
partially rewound (llama.cpp can only restore checkpoints), *every*
probe change re-prefilled from scratch whenever the last checkpoint
missed the probe boundary, so even same-list turns intermittently cost
full prefills.

Registering an option list (pipeline seed or session.update) now fires a
best-effort background prewarm: two throwaway scores with distinct
probes. The first prefills the new option-list prompt; the second,
diverging exactly where per-turn probe text starts, plants the backend's
rewind point (KV checkpoint) at the stable-prefix boundary that every
real turn reuses. The prewarm hides behind the canned mode-switch reply
— by the time it finishes speaking, the cache is warm. Idempotent per
option set, detached from the registering request's lifetime.

Measured on the drone demo (LFM2.5-1.2B, desktop CPU): first turn after
a mode switch 2374ms -> 340ms; intermittent same-list full prefills
(1.3-2.1s) all -> under 0.5s. For clients that swap lists frequently,
options: [parallel:2] on the scoring model additionally keeps one slot
per list via prefix-similarity routing (+26MB RSS, unified KV).

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

* perf(llama-cpp): checkpoint scoring at the caller-declared stable prefix

Hybrid-memory models (LFM2.5 shortconv, Qwen3.5 deltanet — where new
small models are headed) cannot rewind their state, so any prompt-cache
reuse that needs a rewind falls back to a full re-prefill. For classifier
scoring that meant every probe change re-processed the whole option-list
prompt: the server's checkpoints were placed reactively (at wherever the
previous task happened to diverge), so a checkpoint past the next
divergence was erased rather than restored — measured as intermittent
2-10s turns on prompts with a 95%+ common prefix.

The classifier now computes the probe-invariant prompt prefix once (the
byte-wise common prefix of two synthetic probe renders) and declares its
length with every Score request; the server maps it to a token boundary
and forces a KV checkpoint exactly there on each score prefill. That
checkpoint sits at or before every future divergence under the same
option list, so it always survives and always restores — repeat scoring
costs probe+candidates regardless of how the probe changes.

Also:
- prewarm reruns on every option-list registration instead of memoizing
  per list: with boundary checkpoints a redundant rewarm costs two
  probe-sized decodes, while skipping one after a slot eviction (three
  lists sharing fewer slots evict in LRU cascades) silently moves a full
  re-prefill onto the user's next turn
- new llama.cpp backend option rs_seq:N exposes bounded recurrent-state
  rollback outside speculative decoding; measured impractical for
  deltanet-scale states (65GB for 64 snapshots on Qwen3.5-4B) but cheap
  insurance for small-state models
- docs: the multi-list recipe (parallel:N + sps:0.5 — the default slot
  similarity threshold funnels distinct lists onto one slot)

Measured on the drone demo (LFM2.5-1.2B scorer, desktop CPU), steady
state: every turn 285-421ms including mode switches, vs 2.4s post-switch
and intermittent 1.3-2.9s re-prefills before.

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

* fix(realtime): align classifier cache guidance

Document the single-score prewarm behavior and clean the vendored score patch formatting.

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

* fix(llama-cpp): guard score task for fork backends

TurboQuant and Bonsai reuse the primary gRPC server against llama.cpp forks that do not carry LocalAI's slot-based Score patches. Compile the Score integration only for the patched primary backend and return UNIMPLEMENTED from fork builds instead of referencing absent task types and common_params fields.

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

* fix(dev): generate gRPC code before commit lint

The coverage phase regenerates ignored protobuf bindings, but lint runs first and can fail against missing or stale output. Generate the pinned bindings before lint so the gate always type-checks the current schema.

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

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-07-29 12:50:22 +02:00

1406 lines
51 KiB
Protocol Buffer

syntax = "proto3";
option go_package = "github.com/go-skynet/LocalAI/pkg/grpc/proto";
option java_multiple_files = true;
option java_package = "io.skynet.localai.backend";
option java_outer_classname = "LocalAIBackend";
package backend;
service Backend {
rpc Health(HealthMessage) returns (Reply) {}
rpc Free(HealthMessage) returns (Result) {}
rpc Predict(PredictOptions) returns (Reply) {}
rpc LoadModel(ModelOptions) returns (Result) {}
rpc PredictStream(PredictOptions) returns (stream Reply) {}
rpc Embedding(PredictOptions) returns (EmbeddingResult) {}
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
rpc GenerateVideo(GenerateVideoRequest) returns (Result) {}
rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
rpc AudioTranscriptionStream(TranscriptRequest) returns (stream TranscriptStreamResponse) {}
// AudioTranscriptionLive is the bidirectional live-microphone ASR RPC. The
// first message MUST carry a Config; subsequent messages carry Audio frames
// (mono float PCM at config.sample_rate, 16 kHz default). After a
// successful open the backend replies with a single ready ack
// (TranscriptLiveResponse{ready:true}); backends or models without
// cache-aware streaming support return UNIMPLEMENTED instead. Newly
// finalized text streams back as deltas; eou=true marks the model's
// end-of-utterance token. One stream spans many utterances (the decoder
// resets itself after each EOU). Closing the send side finalizes: the
// backend flushes the decoder tail and emits a terminal message carrying
// final_result. A second Config mid-stream resets the decode session.
rpc AudioTranscriptionLive(stream TranscriptLiveRequest) returns (stream TranscriptLiveResponse) {}
rpc TTS(TTSRequest) returns (Result) {}
rpc TTSStream(TTSRequest) returns (stream Reply) {}
rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
rpc Status(HealthMessage) returns (StatusResponse) {}
rpc Detect(DetectOptions) returns (DetectResponse) {}
// SoundDetection runs an audio-tagging / sound-event-classification model
// (e.g. CED over the AudioSet ontology) on a clip and returns scored labels.
rpc SoundDetection(SoundDetectionRequest) returns (SoundDetectionResponse) {}
rpc Depth(DepthRequest) returns (DepthResponse) {}
rpc FaceVerify(FaceVerifyRequest) returns (FaceVerifyResponse) {}
rpc FaceAnalyze(FaceAnalyzeRequest) returns (FaceAnalyzeResponse) {}
rpc VoiceVerify(VoiceVerifyRequest) returns (VoiceVerifyResponse) {}
rpc VoiceAnalyze(VoiceAnalyzeRequest) returns (VoiceAnalyzeResponse) {}
rpc VoiceEmbed(VoiceEmbedRequest) returns (VoiceEmbedResponse) {}
rpc StoresSet(StoresSetOptions) returns (Result) {}
rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
rpc StoresGet(StoresGetOptions) returns (StoresGetResult) {}
rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
rpc Rerank(RerankRequest) returns (RerankResult) {}
// TokenClassify runs a token-classification (NER) model on the
// supplied text and returns each detected entity span. Used by the
// PII redactor's optional NER tier — the regex tier still handles
// formatted hits cheaply, while this catches names, locations, and
// other unformatted PII that regex misses.
rpc TokenClassify(TokenClassifyRequest) returns (TokenClassifyResponse) {}
// Score evaluates the model's joint log-probability of each
// supplied candidate continuation given a shared prompt. The
// prompt's KV cache is computed once and reused across candidates.
// Used for routing-policy multi-label classification, reranking,
// calibrated confidence, and reward-model scoring — any task where
// the consumer wants the model's confidence in a pre-specified
// continuation rather than a generated one.
rpc Score(ScoreRequest) returns (ScoreResponse) {}
rpc GetMetrics(MetricsRequest) returns (MetricsResponse);
rpc VAD(VADRequest) returns (VADResponse) {}
rpc Diarize(DiarizeRequest) returns (DiarizeResponse) {}
rpc AudioEncode(AudioEncodeRequest) returns (AudioEncodeResult) {}
rpc AudioDecode(AudioDecodeRequest) returns (AudioDecodeResult) {}
rpc AudioTransform(AudioTransformRequest) returns (AudioTransformResult) {}
rpc AudioTransformStream(stream AudioTransformFrameRequest) returns (stream AudioTransformFrameResponse) {}
// AudioToAudioStream is the bidirectional any-to-any S2S RPC. Backends
// that load a speech-to-speech model consume input audio frames and emit
// interleaved audio + transcript + tool-call deltas as typed events.
// Backends without S2S support return UNIMPLEMENTED.
rpc AudioToAudioStream(stream AudioToAudioRequest) returns (stream AudioToAudioResponse) {}
rpc ModelMetadata(ModelOptions) returns (ModelMetadataResponse) {}
// Fine-tuning RPCs
rpc StartFineTune(FineTuneRequest) returns (FineTuneJobResult) {}
rpc FineTuneProgress(FineTuneProgressRequest) returns (stream FineTuneProgressUpdate) {}
rpc StopFineTune(FineTuneStopRequest) returns (Result) {}
rpc ListCheckpoints(ListCheckpointsRequest) returns (ListCheckpointsResponse) {}
rpc ExportModel(ExportModelRequest) returns (Result) {}
// Quantization RPCs
rpc StartQuantization(QuantizationRequest) returns (QuantizationJobResult) {}
rpc QuantizationProgress(QuantizationProgressRequest) returns (stream QuantizationProgressUpdate) {}
rpc StopQuantization(QuantizationStopRequest) returns (Result) {}
// Forward proxies a raw HTTP request to an upstream provider. The
// cloud-proxy backend implements this for passthrough-mode model
// configs: the client wire format is preserved end-to-end (no
// translation through internal proto), which means new provider
// fields work the day they ship. Translation-mode proxies use the
// standard Predict/PredictStream RPCs instead. Backends that don't
// support this return UNIMPLEMENTED.
//
// The request is bidirectionally streamed so large bodies can flow
// without buffering. In practice the first ForwardRequest carries
// path, method, headers, and the initial body chunk; subsequent
// messages append body chunks. The first ForwardReply carries the
// upstream status and response headers; subsequent messages stream
// body chunks (SSE frames or chunked transfer). Cancellation of the
// gRPC context closes the upstream connection.
rpc Forward(stream ForwardRequest) returns (stream ForwardReply) {}
}
// Define the empty request
message MetricsRequest {}
message MetricsResponse {
int32 slot_id = 1;
string prompt_json_for_slot = 2; // Stores the prompt as a JSON string.
float tokens_per_second = 3;
int32 tokens_generated = 4;
int32 prompt_tokens_processed = 5;
}
// TokenClassifyRequest carries the text to classify plus an optional
// score threshold. The transformers backend interprets threshold as
// the minimum confidence to include in the response; 0 = include all.
message TokenClassifyRequest {
string text = 1;
float threshold = 2;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 3;
}
// TokenClassifyEntity is one detected entity span. Byte offsets are
// into the original UTF-8 text — start..end is a half-open range that
// addresses the substring corresponding to entity_group.
//
// entity_group follows HuggingFace's aggregated-tag convention (e.g.
// "PER", "LOC", "ORG", or a PII-specific label like "EMAIL" /
// "SSN" depending on the model). The redactor's per-pattern action
// map keys off this string.
message TokenClassifyEntity {
string entity_group = 1;
int32 start = 2;
int32 end = 3;
float score = 4;
string text = 5;
}
message TokenClassifyResponse {
repeated TokenClassifyEntity entities = 1;
}
// ScoreRequest carries one shared prompt and one or more continuations
// to score against it. The backend tokenises the prompt once and reuses
// the resulting KV cache across all candidates in this request.
message ScoreRequest {
string prompt = 1;
repeated string candidates = 2;
// Return per-token logprobs for each candidate when true. Default
// false to keep the wire response small; the joint log_prob field
// covers the common ranking case.
bool include_token_logprobs = 3;
// When true, the response also populates length_normalized_log_prob
// (joint log-prob divided by candidate token count). Useful when
// candidates differ in length and the consumer wants a per-token
// measure comparable across them (PMI-style scoring).
bool length_normalize = 4;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 5;
// Byte length of the prompt prefix that stays identical across
// repeated scoring calls (e.g. a classifier's option-list system
// prompt — everything before the per-turn probe text). Backends that
// snapshot state (hybrid/recurrent models cannot rewind otherwise)
// use it to place a reuse point exactly at the boundary, so the next
// call re-processes only the tokens after it. 0 means unknown.
int32 stable_prefix_len = 6;
}
// CandidateScore is one row in the ScoreResponse, matching by index
// the candidate in ScoreRequest.candidates.
message CandidateScore {
// Sum of log P(token_i | prompt, candidate_token_<i) across the
// candidate's tokens. The primary ranking signal.
double log_prob = 1;
// log_prob / num_tokens — populated when length_normalize=true on
// the request.
double length_normalized_log_prob = 2;
// Per-token detail — populated when include_token_logprobs=true.
repeated TokenLogProb tokens = 3;
// Number of tokens the backend tokenised this candidate into, after
// any backend-specific normalisation (e.g. leading-space handling).
int32 num_tokens = 4;
}
message TokenLogProb {
string token = 1;
double log_prob = 2;
}
message ScoreResponse {
repeated CandidateScore candidates = 1;
}
message RerankRequest {
string query = 1;
repeated string documents = 2;
int32 top_n = 3;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 4;
}
message RerankResult {
Usage usage = 1;
repeated DocumentResult results = 2;
}
message Usage {
int32 total_tokens = 1;
int32 prompt_tokens = 2;
}
message DocumentResult {
int32 index = 1;
string text = 2;
float relevance_score = 3;
}
message StoresKey {
repeated float Floats = 1;
}
message StoresValue {
bytes Bytes = 1;
}
message StoresSetOptions {
repeated StoresKey Keys = 1;
repeated StoresValue Values = 2;
}
message StoresDeleteOptions {
repeated StoresKey Keys = 1;
}
message StoresGetOptions {
repeated StoresKey Keys = 1;
}
message StoresGetResult {
repeated StoresKey Keys = 1;
repeated StoresValue Values = 2;
}
message StoresFindOptions {
StoresKey Key = 1;
int32 TopK = 2;
}
message StoresFindResult {
repeated StoresKey Keys = 1;
repeated StoresValue Values = 2;
repeated float Similarities = 3;
}
message HealthMessage {}
// The request message containing the user's name.
message PredictOptions {
string Prompt = 1;
int32 Seed = 2;
int32 Threads = 3;
int32 Tokens = 4;
int32 TopK = 5;
int32 Repeat = 6;
int32 Batch = 7;
int32 NKeep = 8;
float Temperature = 9;
float Penalty = 10;
bool F16KV = 11;
bool DebugMode = 12;
repeated string StopPrompts = 13;
bool IgnoreEOS = 14;
float TailFreeSamplingZ = 15;
float TypicalP = 16;
float FrequencyPenalty = 17;
float PresencePenalty = 18;
int32 Mirostat = 19;
float MirostatETA = 20;
float MirostatTAU = 21;
bool PenalizeNL = 22;
string LogitBias = 23;
bool MLock = 25;
bool MMap = 26;
bool PromptCacheAll = 27;
bool PromptCacheRO = 28;
string Grammar = 29;
string MainGPU = 30;
string TensorSplit = 31;
float TopP = 32;
string PromptCachePath = 33;
bool Debug = 34;
repeated int32 EmbeddingTokens = 35;
string Embeddings = 36;
float RopeFreqBase = 37;
float RopeFreqScale = 38;
float NegativePromptScale = 39;
string NegativePrompt = 40;
int32 NDraft = 41;
repeated string Images = 42;
bool UseTokenizerTemplate = 43;
repeated Message Messages = 44;
repeated string Videos = 45;
repeated string Audios = 46;
string CorrelationId = 47;
string Tools = 48; // JSON array of available tools/functions for tool calling
string ToolChoice = 49; // JSON string or object specifying tool choice behavior
int32 Logprobs = 50; // Number of top logprobs to return (maps to OpenAI logprobs parameter)
int32 TopLogprobs = 51; // Number of top logprobs to return per token (maps to OpenAI top_logprobs parameter)
map<string, string> Metadata = 52; // Generic per-request metadata (e.g., enable_thinking)
float MinP = 53; // Minimum probability sampling threshold (0.0 = disabled)
// ModelIdentity names the model this request is for, so a backend can reject
// a request that reached it by mistake instead of answering from whatever
// model it happens to hold. In distributed mode a worker can recycle a
// stopped backend's gRPC port for a different model's backend, and a
// liveness-only health probe cannot tell that apart from a valid cached
// route (#10952).
//
// The value is the controller's ModelConfig.Model, the SAME expression that
// produces ModelOptions.Model at LoadModel time, so the two are equal by
// construction rather than by convention.
//
// Empty means "no identity supplied": backends MUST skip the check. That
// keeps an old controller talking to a new backend working, and covers
// callers that legitimately synthesize a PredictOptions internally.
//
// Do NOT reuse TTSRequest.model or SoundGenerationRequest.model for this
// purpose. FileStagingClient already rewrites those to worker-local absolute
// paths (core/services/nodes/file_staging_client.go), so in distributed mode
// they already differ from the load-time value and comparing them would
// reject valid requests. Extending identity to those RPCs needs a separate
// field carrying the untranslated value - which is exactly what
// TTSRequest.ModelIdentity and SoundGenerationRequest.ModelIdentity are.
//
// Every other request message that reaches a backend through the distributed
// router now carries the same ModelIdentity field, populated from the same
// ModelConfig.Model. FileStagingClient rewrites Src/Dst/Voice/Model/
// StartImage/EndImage/Audio and never ModelIdentity, so what the backend
// compares is always what the controller sent.
string ModelIdentity = 54;
// 24 was never assigned; reserve it so it is not silently reused.
reserved 24;
}
// ToolCallDelta represents an incremental tool call update from the C++ parser.
// Used for both streaming (partial diffs) and non-streaming (final tool calls).
message ToolCallDelta {
int32 index = 1; // tool call index (0-based)
string id = 2; // tool call ID (e.g., "call_abc123")
string name = 3; // function name (set on first appearance)
string arguments = 4; // arguments chunk (incremental in streaming, full in non-streaming)
}
// ChatDelta represents incremental content/reasoning/tool_call updates parsed by the C++ backend.
message ChatDelta {
string content = 1; // content text delta
string reasoning_content = 2; // reasoning/thinking text delta
repeated ToolCallDelta tool_calls = 3; // tool call deltas
}
// The response message containing the result
message Reply {
bytes message = 1;
int32 tokens = 2;
int32 prompt_tokens = 3;
double timing_prompt_processing = 4;
double timing_token_generation = 5;
bytes audio = 6;
bytes logprobs = 7; // JSON-encoded logprobs data matching OpenAI format
repeated ChatDelta chat_deltas = 8; // Parsed chat deltas from C++ autoparser (streaming + non-streaming)
}
message GrammarTrigger {
string word = 1;
}
message ModelOptions {
string Model = 1;
int32 ContextSize = 2;
int32 Seed = 3;
int32 NBatch = 4;
bool F16Memory = 5;
bool MLock = 6;
bool MMap = 7;
bool VocabOnly = 8;
bool LowVRAM = 9;
bool Embeddings = 10;
bool NUMA = 11;
int32 NGPULayers = 12;
string MainGPU = 13;
string TensorSplit = 14;
int32 Threads = 15;
float RopeFreqBase = 17;
float RopeFreqScale = 18;
float RMSNormEps = 19;
int32 NGQA = 20;
string ModelFile = 21;
// Diffusers
string PipelineType = 26;
string SchedulerType = 27;
bool CUDA = 28;
float CFGScale = 29;
bool IMG2IMG = 30;
string CLIPModel = 31;
string CLIPSubfolder = 32;
int32 CLIPSkip = 33;
string ControlNet = 48;
string Tokenizer = 34;
// LLM (llama.cpp)
string LoraBase = 35;
string LoraAdapter = 36;
float LoraScale = 42;
bool NoMulMatQ = 37;
string DraftModel = 39;
string AudioPath = 38;
// vllm
string Quantization = 40;
float GPUMemoryUtilization = 50;
bool TrustRemoteCode = 51;
bool EnforceEager = 52;
int32 SwapSpace = 53;
int32 MaxModelLen = 54;
int32 TensorParallelSize = 55;
string LoadFormat = 58;
bool DisableLogStatus = 66;
string DType = 67;
int32 LimitImagePerPrompt = 68;
int32 LimitVideoPerPrompt = 69;
int32 LimitAudioPerPrompt = 70;
string MMProj = 41;
string RopeScaling = 43;
float YarnExtFactor = 44;
float YarnAttnFactor = 45;
float YarnBetaFast = 46;
float YarnBetaSlow = 47;
string Type = 49;
string FlashAttention = 56;
bool NoKVOffload = 57;
string ModelPath = 59;
repeated string LoraAdapters = 60;
repeated float LoraScales = 61;
repeated string Options = 62;
string CacheTypeKey = 63;
string CacheTypeValue = 64;
repeated GrammarTrigger GrammarTriggers = 65;
bool Reranking = 71;
repeated string Overrides = 72;
// EngineArgs carries a JSON-encoded map of backend-native engine arguments
// applied verbatim to the backend's engine constructor (e.g. vLLM AsyncEngineArgs).
// Unknown keys produce an error at LoadModel time.
string EngineArgs = 73;
// Proxy carries the cloud-proxy backend's per-model configuration.
// Empty for non-proxy backends.
ProxyOptions Proxy = 74;
// EnableScore reserves backend resources for the Score RPC. It is derived
// from the model's explicit `known_usecases: [score]` declaration so models
// that never score retain their ordinary serving footprint.
bool EnableScore = 75;
}
// ProxyOptions configures the cloud-proxy backend. UpstreamURL and
// Mode are always meaningful; Provider only matters in translate mode.
// The two api_key_* fields are mutually exclusive and resolved by the
// backend at LoadModel — core forwards the references rather than the
// plaintext key.
message ProxyOptions {
string upstream_url = 1;
string mode = 2;
string provider = 3;
string api_key_env = 4;
string api_key_file = 5;
string upstream_model = 6;
int32 request_timeout_seconds = 7;
// cache_prompt enables automatic Anthropic prompt-cache breakpoints
// (cache_control: ephemeral) on the stable prefix — system, tools, and
// the last message block — when translating to the Anthropic provider.
// Cuts input cost on repeated/agentic calls (cache read = 0.1x). Only
// meaningful for mode=translate + provider=anthropic; ignored otherwise.
bool cache_prompt = 8;
}
message Result {
string message = 1;
bool success = 2;
}
message EmbeddingResult {
repeated float embeddings = 1;
}
message TranscriptRequest {
string dst = 2;
string language = 3;
uint32 threads = 4;
bool translate = 5;
bool diarize = 6;
string prompt = 7;
float temperature = 8;
repeated string timestamp_granularities = 9;
bool stream = 10;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 11;
}
message TranscriptResult {
repeated TranscriptSegment segments = 1;
string text = 2;
string language = 3;
float duration = 4;
// True when the decode ended on the model's end-of-utterance special token
// (<EOU>/<EOB>, emitted by cache-aware streaming models such as
// parakeet_realtime_eou_120m-v1). The marker itself is stripped from text.
bool eou = 5;
}
message TranscriptStreamResponse {
string delta = 1;
TranscriptResult final_result = 2;
}
// === AudioTranscriptionLive messages =====================================
message TranscriptLiveRequest {
oneof payload {
TranscriptLiveConfig config = 1;
TranscriptLiveAudio audio = 2;
}
}
message TranscriptLiveConfig {
string language = 1; // "" => model default
int32 sample_rate = 2; // 0 => 16000; backends may reject others
map<string, string> params = 3; // backend-specific tuning
}
message TranscriptLiveAudio {
repeated float pcm = 1; // mono PCM in [-1,1] at config.sample_rate
}
message TranscriptLiveResponse {
bool ready = 1; // open ack: sent once, before any delta
string delta = 2; // newly-finalized text since previous response
bool eou = 3; // <EOU> fired during this feed (the user yielded the turn)
repeated TranscriptWord words = 4; // words finalized by this feed (stream-relative ns)
TranscriptResult final_result = 5; // terminal message only, after the send side closes
bool eob = 6; // <EOB> fired: a backchannel ("uh-huh") ended — NOT a turn boundary
}
message TranscriptWord {
int64 start = 1;
int64 end = 2;
string text = 3;
}
message TranscriptSegment {
int32 id = 1;
int64 start = 2;
int64 end = 3;
string text = 4;
repeated int32 tokens = 5;
string speaker = 6;
repeated TranscriptWord words = 7;
}
message GenerateImageRequest {
int32 height = 1;
int32 width = 2;
int32 step = 4;
int32 seed = 5;
string positive_prompt = 6;
string negative_prompt = 7;
string dst = 8;
string src = 9;
// Diffusers
string EnableParameters = 10;
int32 CLIPSkip = 11;
// Reference images for models that support them (e.g., Flux Kontext)
repeated string ref_images = 12;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 13;
}
message GenerateVideoRequest {
string prompt = 1;
string negative_prompt = 2; // Negative prompt for video generation
string start_image = 3; // Path or base64 encoded image for the start frame
string end_image = 4; // Path or base64 encoded image for the end frame
int32 width = 5;
int32 height = 6;
int32 num_frames = 7; // Number of frames to generate
int32 fps = 8; // Frames per second
int32 seed = 9;
float cfg_scale = 10; // Classifier-free guidance scale
int32 step = 11; // Number of inference steps
string dst = 12; // Output path for the generated video
string audio = 13; // Path to staged audio for audio-conditioned video
// Backend-specific per-request generation parameters. Values are strings
// and are validated/coerced by the selected backend.
map<string, string> params = 14;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 15;
}
message TTSRequest {
string text = 1;
string model = 2;
string dst = 3;
string voice = 4;
optional string language = 5;
// instructions is a free-form, per-request style/voice description (maps to
// the OpenAI `instructions` field). Backends that support expressive synthesis
// (e.g. Qwen3-TTS CustomVoice/VoiceDesign) prefer this over the static YAML
// option when set; backends that don't simply ignore it.
optional string instructions = 6;
// params carries optional, backend-specific per-request generation parameters
// (e.g. Chatterbox exaggeration/cfg_weight/temperature). Values are strings and
// coerced by the backend; unset leaves the backend's configured defaults.
map<string, string> params = 7;
// ModelIdentity is a SEPARATE field from `model` above and carries the
// UNTRANSLATED controller-side ModelConfig.Model, so a backend can reject a
// request that reached it through a stale distributed route (#10952).
//
// `model` cannot be reused for this: FileStagingClient.TTS/.TTSStream and the
// SoundGeneration path rewrite it into a worker-local absolute path
// (core/services/nodes/file_staging_client.go), while the load-time value is
// untranslated. In distributed mode - exactly the configuration this guards -
// the two already differ, so comparing them would reject valid requests.
//
// Empty means "no identity supplied" and backends MUST skip the check.
string ModelIdentity = 8;
}
message VADRequest {
repeated float audio = 1;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 2;
}
message VADSegment {
float start = 1;
float end = 2;
}
message VADResponse {
repeated VADSegment segments = 1;
}
// --- Speaker diarization messages ---
//
// Pure speaker diarization: "who spoke when". Returns time-stamped segments
// labelled with cluster IDs (the same string for the same speaker across
// segments). Some backends (e.g. vibevoice.cpp) produce diarization as a
// by-product of ASR and may also fill in `text` per segment; backends with a
// dedicated diarization pipeline (e.g. sherpa-onnx pyannote) leave `text`
// empty and emit only the segmentation.
message DiarizeRequest {
string dst = 1; // path to audio file (HTTP layer materialises uploads to a temp file)
uint32 threads = 2;
string language = 3; // optional; only meaningful for transcription-bundling backends
int32 num_speakers = 4; // exact speaker count if known (>0 forces); 0 = auto
int32 min_speakers = 5; // hint when auto-detecting; 0 = unset
int32 max_speakers = 6; // hint when auto-detecting; 0 = unset
float clustering_threshold = 7; // distance threshold when num_speakers unknown; 0 = backend default
float min_duration_on = 8; // discard segments shorter than this (seconds); 0 = backend default
float min_duration_off = 9; // merge gaps shorter than this (seconds); 0 = backend default
bool include_text = 10; // when the backend can emit per-segment transcript for free, ask it to populate `text`
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 11;
}
message DiarizeSegment {
int32 id = 1;
float start = 2; // seconds
float end = 3; // seconds
string speaker = 4; // backend-emitted speaker label (e.g. "0", "SPEAKER_00")
string text = 5; // optional per-segment transcript (empty unless include_text and supported)
}
message DiarizeResponse {
repeated DiarizeSegment segments = 1;
int32 num_speakers = 2; // count of distinct speaker labels in `segments`
float duration = 3; // total audio duration in seconds (0 if unknown)
string language = 4; // optional, when the backend bundles transcription
}
message SoundGenerationRequest {
string text = 1;
string model = 2;
string dst = 3;
optional float duration = 4;
optional float temperature = 5;
optional bool sample = 6;
optional string src = 7;
optional int32 src_divisor = 8;
optional bool think = 9;
optional string caption = 10;
optional string lyrics = 11;
optional int32 bpm = 12;
optional string keyscale = 13;
optional string language = 14;
optional string timesignature = 15;
optional bool instrumental = 17;
// ModelIdentity is a SEPARATE field from `model` above and carries the
// UNTRANSLATED controller-side ModelConfig.Model, so a backend can reject a
// request that reached it through a stale distributed route (#10952).
//
// `model` cannot be reused for this: FileStagingClient.TTS/.TTSStream and the
// SoundGeneration path rewrite it into a worker-local absolute path
// (core/services/nodes/file_staging_client.go), while the load-time value is
// untranslated. In distributed mode - exactly the configuration this guards -
// the two already differ, so comparing them would reject valid requests.
//
// Empty means "no identity supplied" and backends MUST skip the check.
string ModelIdentity = 18;
}
message TokenizationResponse {
int32 length = 1;
repeated int32 tokens = 2;
}
message MemoryUsageData {
uint64 total = 1;
map<string, uint64> breakdown = 2;
}
message StatusResponse {
enum State {
UNINITIALIZED = 0;
BUSY = 1;
READY = 2;
ERROR = -1;
}
State state = 1;
MemoryUsageData memory = 2;
}
message Message {
string role = 1;
string content = 2;
// Optional fields for OpenAI-compatible message format
string name = 3; // Tool name (for tool messages)
string tool_call_id = 4; // Tool call ID (for tool messages)
string reasoning_content = 5; // Reasoning content (for thinking models)
string tool_calls = 6; // Tool calls as JSON string (for assistant messages with tool calls)
}
message DetectOptions {
string src = 1;
string prompt = 2; // Text prompt (for SAM 3 PCS mode)
repeated float points = 3; // Point coordinates as [x1, y1, label1, x2, y2, label2, ...] (label: 1=pos, 0=neg)
repeated float boxes = 4; // Box coordinates as [x1, y1, x2, y2, ...]
float threshold = 5; // Detection confidence threshold
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 6;
}
message Detection {
float x = 1;
float y = 2;
float width = 3;
float height = 4;
float confidence = 5;
string class_name = 6;
bytes mask = 7; // PNG-encoded binary segmentation mask
}
message DetectResponse {
repeated Detection Detections = 1;
}
// --- Sound-event classification / audio tagging messages (CED) ---
message SoundDetectionRequest {
string src = 1; // audio file path (LocalAI writes the upload to disk)
int32 top_k = 2; // number of top tags to return (0 = all classes)
float threshold = 3; // optional: drop tags scoring below this
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 4;
}
message SoundClass {
string label = 1; // AudioSet class name, e.g. "Baby cry, infant cry"
float score = 2; // per-class probability (multi-label, independent)
int32 index = 3; // class index in the model ontology
}
message SoundDetectionResponse {
repeated SoundClass detections = 1; // score-descending
}
// --- Depth estimation messages (Depth Anything 3) ---
message DepthRequest {
string src = 1; // input image (filesystem path or base64-encoded payload)
string dst = 2; // optional output directory for exports (glb/colmap)
bool include_depth = 3; // return the per-pixel metric depth map
bool include_confidence = 4; // return the per-pixel confidence map (DualDPT)
bool include_pose = 5; // return camera extrinsics/intrinsics (DualDPT)
bool include_sky = 6; // return the per-pixel sky map (mono models)
bool include_points = 7; // back-project to a 3D point cloud (DualDPT)
float points_conf_thresh = 8; // keep points with confidence >= this threshold
repeated string exports = 9; // requested exports: "glb", "colmap"
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 10;
}
message DepthResponse {
int32 width = 1; // processed depth-map width
int32 height = 2; // processed depth-map height
repeated float depth = 3; // width*height row-major metric depth
repeated float confidence = 4; // width*height row-major confidence (DualDPT)
repeated float sky = 5; // width*height row-major sky map (mono)
repeated float extrinsics = 6; // 12 floats, 3x4 row-major (world-to-camera)
repeated float intrinsics = 7; // 9 floats, 3x3 row-major
int32 num_points = 8; // number of 3D points
repeated float points = 9; // num_points*3 xyz, world space
bytes point_colors = 10; // num_points*3 uint8 rgb
repeated string export_paths = 11; // paths written for the requested exports
bool is_metric = 12; // depth is in metric units
}
// --- Face recognition messages ---
message FacialArea {
float x = 1;
float y = 2;
float w = 3;
float h = 4;
}
message FaceVerifyRequest {
string img1 = 1; // base64-encoded image
string img2 = 2; // base64-encoded image
float threshold = 3; // cosine-distance threshold; 0 = use backend default
bool anti_spoofing = 4; // run MiniFASNet liveness on each image; failed liveness forces verified=false
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 5;
}
message FaceVerifyResponse {
bool verified = 1;
float distance = 2; // 1 - cosine_similarity
float threshold = 3;
float confidence = 4; // 0-100
string model = 5; // e.g. "buffalo_l"
FacialArea img1_area = 6;
FacialArea img2_area = 7;
float processing_time_ms = 8;
bool img1_is_real = 9; // anti-spoofing result when enabled
float img1_antispoof_score = 10;
bool img2_is_real = 11;
float img2_antispoof_score = 12;
}
message FaceAnalyzeRequest {
string img = 1; // base64-encoded image
repeated string actions = 2; // subset of ["age","gender","emotion","race"]; empty = all-supported
bool anti_spoofing = 3;
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 4;
}
message FaceAnalysis {
FacialArea region = 1;
float face_confidence = 2;
float age = 3;
string dominant_gender = 4; // "Man" | "Woman"
map<string, float> gender = 5;
string dominant_emotion = 6; // reserved; empty in MVP
map<string, float> emotion = 7;
string dominant_race = 8; // not populated
map<string, float> race = 9;
bool is_real = 10; // anti-spoofing result when enabled
float antispoof_score = 11;
}
message FaceAnalyzeResponse {
repeated FaceAnalysis faces = 1;
}
// --- Voice (speaker) recognition messages ---
//
// Analogous to the Face* messages above, but for speaker biometrics.
// Audio fields accept a filesystem path (same convention as
// TranscriptRequest.dst). The HTTP layer materialises base64 / URL /
// data-URI inputs to a temp file before calling the gRPC backend.
message VoiceVerifyRequest {
string audio1 = 1; // path to first audio clip
string audio2 = 2; // path to second audio clip
float threshold = 3; // cosine-distance threshold; 0 = use backend default
bool anti_spoofing = 4; // reserved for future AASIST bolt-on
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 5;
}
message VoiceVerifyResponse {
bool verified = 1;
float distance = 2; // 1 - cosine_similarity
float threshold = 3;
float confidence = 4; // 0-100
string model = 5; // e.g. "speechbrain/spkrec-ecapa-voxceleb"
float processing_time_ms = 6;
}
message VoiceAnalyzeRequest {
string audio = 1; // path to audio clip
repeated string actions = 2; // subset of ["age","gender","emotion"]; empty = all-supported
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 3;
}
message VoiceAnalysis {
float start = 1; // segment start time in seconds (0 if single-utterance)
float end = 2; // segment end time in seconds
float age = 3;
string dominant_gender = 4;
map<string, float> gender = 5;
string dominant_emotion = 6;
map<string, float> emotion = 7;
}
message VoiceAnalyzeResponse {
repeated VoiceAnalysis segments = 1;
}
message VoiceEmbedRequest {
string audio = 1; // path to audio clip
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 2;
}
message VoiceEmbedResponse {
repeated float embedding = 1;
string model = 2;
}
message ToolFormatMarkers {
string format_type = 1; // "json_native", "tag_with_json", "tag_with_tagged"
// Tool section markers
string section_start = 2; // e.g., "<tool_call>", "[TOOL_CALLS]"
string section_end = 3; // e.g., "</tool_call>"
string per_call_start = 4; // e.g., "<|tool_call_begin|>"
string per_call_end = 5; // e.g., "<|tool_call_end|>"
// Function name markers (TAG_WITH_JSON / TAG_WITH_TAGGED)
string func_name_prefix = 6; // e.g., "<function="
string func_name_suffix = 7; // e.g., ">"
string func_close = 8; // e.g., "</function>"
// Argument markers (TAG_WITH_TAGGED)
string arg_name_prefix = 9; // e.g., "<param="
string arg_name_suffix = 10; // e.g., ">"
string arg_value_prefix = 11;
string arg_value_suffix = 12; // e.g., "</param>"
string arg_separator = 13; // e.g., "\n"
// JSON format fields (JSON_NATIVE)
string name_field = 14; // e.g., "name"
string args_field = 15; // e.g., "arguments"
string id_field = 16; // e.g., "id"
bool fun_name_is_key = 17;
bool tools_array_wrapped = 18;
reserved 19;
// Reasoning markers
string reasoning_start = 20; // e.g., "<think>"
string reasoning_end = 21; // e.g., "</think>"
// Content markers
string content_start = 22;
string content_end = 23;
// Args wrapper markers
string args_start = 24; // e.g., "<args>"
string args_end = 25; // e.g., "</args>"
// JSON parameter ordering
string function_field = 26; // e.g., "function" (wrapper key in JSON)
repeated string parameter_order = 27;
// Generated ID field (alternative field name for generated IDs)
string gen_id_field = 28; // e.g., "call_id"
// Call ID markers (position and delimiters for tool call IDs)
string call_id_position = 29; // "none", "pre_func_name", "between_func_and_args", "post_args"
string call_id_prefix = 30; // e.g., "[CALL_ID]"
string call_id_suffix = 31; // e.g., ""
}
message AudioEncodeRequest {
bytes pcm_data = 1;
int32 sample_rate = 2;
int32 channels = 3;
map<string, string> options = 4;
}
message AudioEncodeResult {
repeated bytes frames = 1;
int32 sample_rate = 2;
int32 samples_per_frame = 3;
}
message AudioDecodeRequest {
repeated bytes frames = 1;
map<string, string> options = 2;
}
message AudioDecodeResult {
bytes pcm_data = 1;
int32 sample_rate = 2;
int32 samples_per_frame = 3;
}
// Generic audio transform: an audio-in, audio-out operation, optionally
// conditioned on a second reference signal. Concrete transforms include
// AEC + noise suppression + dereverberation (LocalVQE), voice conversion
// (reference = target speaker), pitch shifting, etc.
message AudioTransformRequest {
string audio_path = 1; // required, primary input file path
string reference_path = 2; // optional auxiliary; empty => zero-fill
string dst = 3; // required, output file path
map<string, string> params = 4; // backend-specific tuning
// ModelIdentity names the model this request is for; see
// PredictOptions.ModelIdentity for the full rationale. Empty means "no
// identity supplied" and backends MUST skip the check.
string ModelIdentity = 5;
}
message AudioTransformResult {
string dst = 1;
int32 sample_rate = 2;
int32 samples = 3;
bool reference_provided = 4;
}
// Bidirectional streaming audio transform. The first message MUST carry a
// Config; subsequent messages carry Frames. A second Config mid-stream
// resets streaming state before the next frame.
message AudioTransformFrameRequest {
oneof payload {
AudioTransformStreamConfig config = 1;
AudioTransformFrame frame = 2;
}
}
message AudioTransformStreamConfig {
enum SampleFormat {
F32_LE = 0;
S16_LE = 1;
}
SampleFormat sample_format = 1;
int32 sample_rate = 2; // 0 => backend default
int32 frame_samples = 3; // 0 => backend default
map<string, string> params = 4;
bool reset = 5; // reset streaming state before next frame
}
message AudioTransformFrame {
bytes audio_pcm = 1; // frame_samples samples in stream's format
bytes reference_pcm = 2; // empty => zero-fill (silent reference)
}
message AudioTransformFrameResponse {
bytes pcm = 1;
int64 frame_index = 2;
}
// === AudioToAudioStream messages =========================================
//
// Bidirectional stream between the LocalAI core and an any-to-any audio
// model. The client opens the stream with a Config payload, then alternates
// Frame (input audio) and Control (turn boundaries, function-call results,
// session updates) payloads. The server streams back typed events: audio
// frames carry PCM in `pcm`; transcript / tool-call deltas carry JSON in
// `meta`; the stream ends with a `response.done` (success) or `error` event.
message AudioToAudioRequest {
oneof payload {
AudioToAudioConfig config = 1;
AudioToAudioFrame frame = 2;
AudioToAudioControl control = 3;
}
}
message AudioToAudioConfig {
// PCM format for client→server audio. 0 => backend default
// (16 kHz for the LFM2-Audio Conformer encoder).
int32 input_sample_rate = 1;
// Preferred server→client audio rate. 0 => backend default
// (24 kHz for the LFM2-Audio vocoder).
int32 output_sample_rate = 2;
// Optional system prompt override. Empty => backend chooses based on
// mode (e.g. "Respond with interleaved text and audio.").
string system_prompt = 3;
// Optional baked-voice id. Models that only ship a fixed set of
// voices (e.g. LFM2-Audio: us_male/us_female/uk_male/uk_female) match
// this against their voice table; an empty string keeps the default.
string voice = 4;
// JSON-encoded array of tool definitions in OpenAI Chat Completions
// format. Empty => no tools.
string tools = 5;
// Free-form sampling / decoding parameters (temperature, top_k,
// max_new_tokens, audio_top_k, etc).
map<string, string> params = 6;
// True => reset any session-scoped state before processing further
// frames on this stream. The first Config implicitly resets.
bool reset = 7;
}
message AudioToAudioFrame {
// Raw PCM s16le mono at config.input_sample_rate. Empty pcm + end_of_input
// is a valid "user finished speaking" marker without trailing audio.
bytes pcm = 1;
// Marks the last frame of a user turn. The backend may begin emitting
// a response immediately after seeing this.
bool end_of_input = 2;
}
message AudioToAudioControl {
// Free-form control event names. Initial set:
// "input_audio_buffer.commit" — user finished speaking
// "response.cancel" — abort in-flight generation
// "conversation.item.create" — inject a non-audio item (e.g.
// function_call_output as JSON in
// `payload`)
// "session.update" — re-configure mid-stream
string event = 1;
// Event-specific JSON payload.
bytes payload = 2;
}
message AudioToAudioResponse {
// Event identifies what this frame carries. Mirrors the OpenAI Realtime
// API server-event names where applicable. Initial set:
// "response.audio.delta"
// "response.audio_transcript.delta"
// "response.function_call_arguments.delta"
// "response.function_call_arguments.done"
// "response.done"
// "error"
string event = 1;
// Populated when event = response.audio.delta.
bytes pcm = 2;
// Populated alongside pcm to identify its rate. 0 => same as the
// session's negotiated output_sample_rate.
int32 sample_rate = 3;
// JSON payload for non-PCM events (transcript chunk, tool args, error
// body).
bytes meta = 4;
// Monotonic per-stream counter, useful for client reordering and
// debugging.
int64 sequence = 5;
}
message ModelMetadataResponse {
bool supports_thinking = 1;
string rendered_template = 2; // The rendered chat template with enable_thinking=true (empty if not applicable)
ToolFormatMarkers tool_format = 3; // Auto-detected tool format markers from differential template analysis
string media_marker = 4; // Marker the backend expects in the prompt for each multimodal input (images/audio/video). Empty when the backend does not use a marker.
}
// Fine-tuning messages
message FineTuneRequest {
// Model identification
string model = 1; // HF model name or local path
string training_type = 2; // "lora", "loha", "lokr", "full" — what parameters to train
string training_method = 3; // "sft", "dpo", "grpo", "rloo", "reward", "kto", "orpo", "network_training"
// Adapter config (universal across LoRA/LoHa/LoKr for LLM + diffusion)
int32 adapter_rank = 10; // LoRA rank (r), default 16
int32 adapter_alpha = 11; // scaling factor, default 16
float adapter_dropout = 12; // default 0.0
repeated string target_modules = 13; // layer names to adapt
// Universal training hyperparameters
float learning_rate = 20; // default 2e-4
int32 num_epochs = 21; // default 3
int32 batch_size = 22; // default 2
int32 gradient_accumulation_steps = 23; // default 4
int32 warmup_steps = 24; // default 5
int32 max_steps = 25; // 0 = use epochs
int32 save_steps = 26; // 0 = only save final
float weight_decay = 27; // default 0.01
bool gradient_checkpointing = 28;
string optimizer = 29; // adamw_8bit, adamw, sgd, adafactor, prodigy
int32 seed = 30; // default 3407
string mixed_precision = 31; // fp16, bf16, fp8, no
// Dataset
string dataset_source = 40; // HF dataset ID, local file/dir path
string dataset_split = 41; // train, test, etc.
// Output
string output_dir = 50;
string job_id = 51; // client-assigned or auto-generated
// Resume training from a checkpoint
string resume_from_checkpoint = 55; // path to checkpoint dir to resume from
// Backend-specific AND method-specific extensibility
map<string, string> extra_options = 60;
}
message FineTuneJobResult {
string job_id = 1;
bool success = 2;
string message = 3;
}
message FineTuneProgressRequest {
string job_id = 1;
}
message FineTuneProgressUpdate {
string job_id = 1;
int32 current_step = 2;
int32 total_steps = 3;
float current_epoch = 4;
float total_epochs = 5;
float loss = 6;
float learning_rate = 7;
float grad_norm = 8;
float eval_loss = 9;
float eta_seconds = 10;
float progress_percent = 11;
string status = 12; // queued, caching, loading_model, loading_dataset, training, saving, completed, failed, stopped
string message = 13;
string checkpoint_path = 14; // set when a checkpoint is saved
string sample_path = 15; // set when a sample is generated (video/image backends)
map<string, float> extra_metrics = 16; // method-specific metrics
}
message FineTuneStopRequest {
string job_id = 1;
bool save_checkpoint = 2;
}
message ListCheckpointsRequest {
string output_dir = 1;
}
message ListCheckpointsResponse {
repeated CheckpointInfo checkpoints = 1;
}
message CheckpointInfo {
string path = 1;
int32 step = 2;
float epoch = 3;
float loss = 4;
string created_at = 5;
}
message ExportModelRequest {
string checkpoint_path = 1;
string output_path = 2;
string export_format = 3; // lora, loha, lokr, merged_16bit, merged_4bit, gguf, diffusers
string quantization_method = 4; // for GGUF: q4_k_m, q5_k_m, q8_0, f16, etc.
string model = 5; // base model name (for merge operations)
map<string, string> extra_options = 6;
}
// Quantization messages
message QuantizationRequest {
string model = 1; // HF model name or local path
string quantization_type = 2; // q4_k_m, q5_k_m, q8_0, f16, etc.
string output_dir = 3; // where to write output files
string job_id = 4; // client-assigned job ID
map<string, string> extra_options = 5; // hf_token, custom flags, etc.
}
message QuantizationJobResult {
string job_id = 1;
bool success = 2;
string message = 3;
}
message QuantizationProgressRequest {
string job_id = 1;
}
message QuantizationProgressUpdate {
string job_id = 1;
float progress_percent = 2;
string status = 3; // queued, downloading, converting, quantizing, completed, failed, stopped
string message = 4;
string output_file = 5; // set when completed — path to the output GGUF file
map<string, float> extra_metrics = 6; // e.g. file_size_mb, compression_ratio
}
message QuantizationStopRequest {
string job_id = 1;
}
// ForwardHeader is one HTTP header on the request or response. Headers
// like Authorization are typically injected by the backend (from the
// resolved API key) rather than passed through from the client.
message ForwardHeader {
string name = 1;
string value = 2;
}
// ForwardRequest is a streamed HTTP request to the upstream. First
// message carries path/method/headers; subsequent messages carry
// body_chunk only. All fields except body_chunk are honoured on the
// first message and ignored thereafter.
message ForwardRequest {
string path = 1; // e.g. "/v1/chat/completions" — appended to the model's upstream_url
string method = 2; // usually "POST"
repeated ForwardHeader headers = 3;
bytes body_chunk = 4;
}
// ForwardReply is a streamed HTTP response from the upstream. First
// message carries status/headers; subsequent messages carry body_chunk
// only. SSE responses arrive as a sequence of body_chunk frames; the
// caller is responsible for any parsing.
message ForwardReply {
int32 status = 1;
repeated ForwardHeader headers = 2;
bytes body_chunk = 3;
}