LocalAI/backend/backend.proto

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 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 AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
  rpc TTS(TTSRequest) returns (Result) {}
  rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
  rpc Status(HealthMessage) returns (StatusResponse) {}
}

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;
}

// The response message containing the result
message Reply {
  bytes message = 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;
  string LibrarySearchPath = 16;
  float RopeFreqBase = 17;
  float RopeFreqScale = 18;
  float RMSNormEps = 19;
  int32 NGQA = 20;
  string ModelFile = 21;

  // AutoGPTQ
  string Device = 22;
  bool UseTriton = 23;
  string ModelBaseName = 24;
  bool UseFastTokenizer = 25;

  // 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;

  string MMProj = 41;

  string RopeScaling = 43;
  float YarnExtFactor = 44;
  float YarnAttnFactor = 45;
  float YarnBetaFast = 46;
  float YarnBetaSlow = 47;
}

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;
}

message TranscriptResult {
  repeated TranscriptSegment segments = 1;
  string text = 2;
}

message TranscriptSegment {
  int32 id = 1;
  int64 start = 2;
  int64 end = 3;
  string text = 4;
  repeated int32 tokens = 5;
}

message GenerateImageRequest {
  int32 height = 1;
  int32 width = 2;
  int32 mode = 3;
  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;
}

message TTSRequest {
  string text = 1;
  string model = 2;
  string dst = 3;
}

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;
}