mirror of
https://github.com/mudler/LocalAI.git
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feat: elevenlabs sound-generation
api (#3355)
* initial version of elevenlabs compatible soundgeneration api and cli command Signed-off-by: Dave Lee <dave@gray101.com> * minor cleanup Signed-off-by: Dave Lee <dave@gray101.com> * restore TTS, add test Signed-off-by: Dave Lee <dave@gray101.com> * remove stray s Signed-off-by: Dave Lee <dave@gray101.com> * fix Signed-off-by: Dave Lee <dave@gray101.com> --------- Signed-off-by: Dave Lee <dave@gray101.com> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
This commit is contained in:
parent
84d6e5a987
commit
81ae92f017
@ -16,6 +16,7 @@ service Backend {
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rpc GenerateImage(GenerateImageRequest) returns (Result) {}
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rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
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rpc TTS(TTSRequest) returns (Result) {}
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rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
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rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
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rpc Status(HealthMessage) returns (StatusResponse) {}
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@ -270,6 +271,17 @@ message TTSRequest {
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optional string language = 5;
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}
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message SoundGenerationRequest {
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string text = 1;
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string model = 2;
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string dst = 3;
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optional float duration = 4;
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optional float temperature = 5;
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optional bool sample = 6;
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optional string src = 7;
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optional int32 src_divisor = 8;
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}
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message TokenizationResponse {
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int32 length = 1;
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repeated int32 tokens = 2;
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@ -15,7 +15,7 @@ import backend_pb2_grpc
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import grpc
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from scipy.io.wavfile import write as write_wav
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from scipy.io import wavfile
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from transformers import AutoProcessor, MusicgenForConditionalGeneration
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_ONE_DAY_IN_SECONDS = 60 * 60 * 24
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@ -63,6 +63,61 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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return backend_pb2.Result(message="Model loaded successfully", success=True)
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def SoundGeneration(self, request, context):
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model_name = request.model
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if model_name == "":
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return backend_pb2.Result(success=False, message="request.model is required")
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try:
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self.processor = AutoProcessor.from_pretrained(model_name)
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self.model = MusicgenForConditionalGeneration.from_pretrained(model_name)
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inputs = None
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if request.text == "":
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inputs = self.model.get_unconditional_inputs(num_samples=1)
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elif request.HasField('src'):
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# TODO SECURITY CODE GOES HERE LOL
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# WHO KNOWS IF THIS WORKS???
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sample_rate, wsamples = wavfile.read('path_to_your_file.wav')
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if request.HasField('src_divisor'):
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wsamples = wsamples[: len(wsamples) // request.src_divisor]
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inputs = self.processor(
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audio=wsamples,
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sampling_rate=sample_rate,
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text=[request.text],
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padding=True,
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return_tensors="pt",
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)
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else:
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inputs = self.processor(
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text=[request.text],
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padding=True,
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return_tensors="pt",
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)
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tokens = 256
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if request.HasField('duration'):
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tokens = int(request.duration * 51.2) # 256 tokens = 5 seconds, therefore 51.2 tokens is one second
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guidance = 3.0
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if request.HasField('temperature'):
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guidance = request.temperature
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dosample = True
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if request.HasField('sample'):
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dosample = request.sample
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audio_values = self.model.generate(**inputs, do_sample=dosample, guidance_scale=guidance, max_new_tokens=tokens)
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print("[transformers-musicgen] SoundGeneration generated!", file=sys.stderr)
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sampling_rate = self.model.config.audio_encoder.sampling_rate
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wavfile.write(request.dst, rate=sampling_rate, data=audio_values[0, 0].numpy())
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print("[transformers-musicgen] SoundGeneration saved to", request.dst, file=sys.stderr)
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print("[transformers-musicgen] SoundGeneration for", file=sys.stderr)
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print("[transformers-musicgen] SoundGeneration requested tokens", tokens, file=sys.stderr)
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print(request, file=sys.stderr)
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except Exception as err:
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return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
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return backend_pb2.Result(success=True)
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# The TTS endpoint is older, and provides fewer features, but exists for compatibility reasons
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def TTS(self, request, context):
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model_name = request.model
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if model_name == "":
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@ -75,8 +130,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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padding=True,
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return_tensors="pt",
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)
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tokens = 256
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# TODO get tokens from request?
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tokens = 512 # No good place to set the "length" in TTS, so use 10s as a sane default
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audio_values = self.model.generate(**inputs, max_new_tokens=tokens)
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print("[transformers-musicgen] TTS generated!", file=sys.stderr)
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sampling_rate = self.model.config.audio_encoder.sampling_rate
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@ -63,7 +63,7 @@ class TestBackendServicer(unittest.TestCase):
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def test_tts(self):
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"""
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This method tests if the embeddings are generated successfully
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This method tests if TTS is generated successfully
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"""
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try:
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self.setUp()
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@ -79,3 +79,22 @@ class TestBackendServicer(unittest.TestCase):
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self.fail("TTS service failed")
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finally:
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self.tearDown()
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def test_sound_generation(self):
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"""
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This method tests if SoundGeneration is generated successfully
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"""
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.LoadModel(backend_pb2.ModelOptions(Model="facebook/musicgen-small"))
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self.assertTrue(response.success)
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sg_request = backend_pb2.SoundGenerationRequest(text="80s TV news production music hit for tonight's biggest story")
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sg_response = stub.SoundGeneration(sg_request)
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self.assertIsNotNone(sg_response)
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except Exception as err:
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print(err)
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self.fail("SoundGeneration service failed")
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finally:
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self.tearDown()
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@ -87,7 +87,7 @@ func ModelInference(ctx context.Context, s string, messages []schema.Message, im
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case string:
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protoMessages[i].Content = ct
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default:
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return nil, fmt.Errorf("Unsupported type for schema.Message.Content for inference: %T", ct)
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return nil, fmt.Errorf("unsupported type for schema.Message.Content for inference: %T", ct)
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}
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}
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}
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74
core/backend/soundgeneration.go
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74
core/backend/soundgeneration.go
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@ -0,0 +1,74 @@
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package backend
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import (
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"context"
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"fmt"
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"os"
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"path/filepath"
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/pkg/grpc/proto"
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"github.com/mudler/LocalAI/pkg/model"
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"github.com/mudler/LocalAI/pkg/utils"
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)
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func SoundGeneration(
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backend string,
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modelFile string,
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text string,
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duration *float32,
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temperature *float32,
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doSample *bool,
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sourceFile *string,
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sourceDivisor *int32,
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loader *model.ModelLoader,
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appConfig *config.ApplicationConfig,
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backendConfig config.BackendConfig,
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) (string, *proto.Result, error) {
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if backend == "" {
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return "", nil, fmt.Errorf("backend is a required parameter")
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}
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grpcOpts := gRPCModelOpts(backendConfig)
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opts := modelOpts(config.BackendConfig{}, appConfig, []model.Option{
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model.WithBackendString(backend),
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model.WithModel(modelFile),
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model.WithContext(appConfig.Context),
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model.WithAssetDir(appConfig.AssetsDestination),
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model.WithLoadGRPCLoadModelOpts(grpcOpts),
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})
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soundGenModel, err := loader.BackendLoader(opts...)
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if err != nil {
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return "", nil, err
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}
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if soundGenModel == nil {
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return "", nil, fmt.Errorf("could not load sound generation model")
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}
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if err := os.MkdirAll(appConfig.AudioDir, 0750); err != nil {
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return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
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}
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fileName := utils.GenerateUniqueFileName(appConfig.AudioDir, "sound_generation", ".wav")
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filePath := filepath.Join(appConfig.AudioDir, fileName)
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res, err := soundGenModel.SoundGeneration(context.Background(), &proto.SoundGenerationRequest{
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Text: text,
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Model: modelFile,
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Dst: filePath,
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Sample: doSample,
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Duration: duration,
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Temperature: temperature,
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Src: sourceFile,
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SrcDivisor: sourceDivisor,
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})
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// return RPC error if any
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if !res.Success {
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return "", nil, fmt.Errorf(res.Message)
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}
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return filePath, res, err
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}
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@ -9,26 +9,10 @@ import (
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/pkg/grpc/proto"
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model "github.com/mudler/LocalAI/pkg/model"
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"github.com/mudler/LocalAI/pkg/model"
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"github.com/mudler/LocalAI/pkg/utils"
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)
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func generateUniqueFileName(dir, baseName, ext string) string {
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counter := 1
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fileName := baseName + ext
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for {
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filePath := filepath.Join(dir, fileName)
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_, err := os.Stat(filePath)
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if os.IsNotExist(err) {
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return fileName
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}
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counter++
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fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
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}
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}
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func ModelTTS(
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backend,
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text,
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@ -66,7 +50,7 @@ func ModelTTS(
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return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
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}
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fileName := generateUniqueFileName(appConfig.AudioDir, "tts", ".wav")
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fileName := utils.GenerateUniqueFileName(appConfig.AudioDir, "tts", ".wav")
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filePath := filepath.Join(appConfig.AudioDir, fileName)
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// If the model file is not empty, we pass it joined with the model path
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@ -12,6 +12,7 @@ var CLI struct {
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Federated FederatedCLI `cmd:"" help:"Run LocalAI in federated mode"`
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Models ModelsCMD `cmd:"" help:"Manage LocalAI models and definitions"`
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TTS TTSCMD `cmd:"" help:"Convert text to speech"`
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SoundGeneration SoundGenerationCMD `cmd:"" help:"Generates audio files from text or audio"`
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Transcript TranscriptCMD `cmd:"" help:"Convert audio to text"`
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Worker worker.Worker `cmd:"" help:"Run workers to distribute workload (llama.cpp-only)"`
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Util UtilCMD `cmd:"" help:"Utility commands"`
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110
core/cli/soundgeneration.go
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110
core/cli/soundgeneration.go
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package cli
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import (
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"context"
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"fmt"
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"os"
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"path/filepath"
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"strconv"
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"strings"
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"github.com/mudler/LocalAI/core/backend"
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cliContext "github.com/mudler/LocalAI/core/cli/context"
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/pkg/model"
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"github.com/rs/zerolog/log"
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)
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type SoundGenerationCMD struct {
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Text []string `arg:""`
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Backend string `short:"b" required:"" help:"Backend to run the SoundGeneration model"`
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Model string `short:"m" required:"" help:"Model name to run the SoundGeneration"`
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Duration string `short:"d" help:"If specified, the length of audio to generate in seconds"`
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Temperature string `short:"t" help:"If specified, the temperature of the generation"`
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InputFile string `short:"i" help:"If specified, the input file to condition generation upon"`
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InputFileSampleDivisor string `short:"f" help:"If InputFile and this divisor is specified, the first portion of the sample file will be used"`
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DoSample bool `short:"s" default:"true" help:"Enables sampling from the model. Better quality at the cost of speed. Defaults to enabled."`
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OutputFile string `short:"o" type:"path" help:"The path to write the output wav file"`
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ModelsPath string `env:"LOCALAI_MODELS_PATH,MODELS_PATH" type:"path" default:"${basepath}/models" help:"Path containing models used for inferencing" group:"storage"`
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BackendAssetsPath string `env:"LOCALAI_BACKEND_ASSETS_PATH,BACKEND_ASSETS_PATH" type:"path" default:"/tmp/localai/backend_data" help:"Path used to extract libraries that are required by some of the backends in runtime" group:"storage"`
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ExternalGRPCBackends []string `env:"LOCALAI_EXTERNAL_GRPC_BACKENDS,EXTERNAL_GRPC_BACKENDS" help:"A list of external grpc backends" group:"backends"`
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}
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func parseToFloat32Ptr(input string) *float32 {
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f, err := strconv.ParseFloat(input, 32)
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if err != nil {
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return nil
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}
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f2 := float32(f)
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return &f2
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}
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func parseToInt32Ptr(input string) *int32 {
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i, err := strconv.ParseInt(input, 10, 32)
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if err != nil {
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return nil
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}
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i2 := int32(i)
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return &i2
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}
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func (t *SoundGenerationCMD) Run(ctx *cliContext.Context) error {
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outputFile := t.OutputFile
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outputDir := t.BackendAssetsPath
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if outputFile != "" {
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outputDir = filepath.Dir(outputFile)
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}
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text := strings.Join(t.Text, " ")
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externalBackends := make(map[string]string)
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// split ":" to get backend name and the uri
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for _, v := range t.ExternalGRPCBackends {
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backend := v[:strings.IndexByte(v, ':')]
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uri := v[strings.IndexByte(v, ':')+1:]
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externalBackends[backend] = uri
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fmt.Printf("TMP externalBackends[%q]=%q\n\n", backend, uri)
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}
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opts := &config.ApplicationConfig{
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ModelPath: t.ModelsPath,
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Context: context.Background(),
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AudioDir: outputDir,
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AssetsDestination: t.BackendAssetsPath,
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ExternalGRPCBackends: externalBackends,
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}
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ml := model.NewModelLoader(opts.ModelPath)
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defer func() {
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err := ml.StopAllGRPC()
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if err != nil {
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log.Error().Err(err).Msg("unable to stop all grpc processes")
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}
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}()
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options := config.BackendConfig{}
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options.SetDefaults()
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var inputFile *string
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if t.InputFile != "" {
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inputFile = &t.InputFile
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}
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filePath, _, err := backend.SoundGeneration(t.Backend, t.Model, text,
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parseToFloat32Ptr(t.Duration), parseToFloat32Ptr(t.Temperature), &t.DoSample,
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inputFile, parseToInt32Ptr(t.InputFileSampleDivisor), ml, opts, options)
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if err != nil {
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return err
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}
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if outputFile != "" {
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if err := os.Rename(filePath, outputFile); err != nil {
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return err
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}
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fmt.Printf("Generate file %s\n", outputFile)
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} else {
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fmt.Printf("Generate file %s\n", filePath)
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}
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return nil
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}
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65
core/http/endpoints/elevenlabs/soundgeneration.go
Normal file
65
core/http/endpoints/elevenlabs/soundgeneration.go
Normal file
@ -0,0 +1,65 @@
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package elevenlabs
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import (
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"github.com/gofiber/fiber/v2"
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"github.com/mudler/LocalAI/core/backend"
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"github.com/mudler/LocalAI/core/config"
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fiberContext "github.com/mudler/LocalAI/core/http/ctx"
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"github.com/mudler/LocalAI/core/schema"
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"github.com/mudler/LocalAI/pkg/model"
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"github.com/rs/zerolog/log"
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)
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// SoundGenerationEndpoint is the ElevenLabs SoundGeneration endpoint https://elevenlabs.io/docs/api-reference/sound-generation
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// @Summary Generates audio from the input text.
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// @Param request body schema.ElevenLabsSoundGenerationRequest true "query params"
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// @Success 200 {string} binary "Response"
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// @Router /v1/sound-generation [post]
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func SoundGenerationEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
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input := new(schema.ElevenLabsSoundGenerationRequest)
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// Get input data from the request body
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if err := c.BodyParser(input); err != nil {
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return err
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}
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modelFile, err := fiberContext.ModelFromContext(c, cl, ml, input.ModelID, false)
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if err != nil {
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modelFile = input.ModelID
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log.Warn().Str("ModelID", input.ModelID).Msg("Model not found in context")
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}
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cfg, err := cl.LoadBackendConfigFileByName(modelFile, appConfig.ModelPath,
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config.LoadOptionDebug(appConfig.Debug),
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config.LoadOptionThreads(appConfig.Threads),
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config.LoadOptionContextSize(appConfig.ContextSize),
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config.LoadOptionF16(appConfig.F16),
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)
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if err != nil {
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modelFile = input.ModelID
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log.Warn().Str("Request ModelID", input.ModelID).Err(err).Msg("error during LoadBackendConfigFileByName, using request ModelID")
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} else {
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if input.ModelID != "" {
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modelFile = input.ModelID
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} else {
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modelFile = cfg.Model
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}
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}
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log.Debug().Str("modelFile", "modelFile").Str("backend", cfg.Backend).Msg("Sound Generation Request about to be sent to backend")
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if input.Duration != nil {
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log.Debug().Float32("duration", *input.Duration).Msg("duration set")
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}
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if input.Temperature != nil {
|
||||
log.Debug().Float32("temperature", *input.Temperature).Msg("temperature set")
|
||||
}
|
||||
|
||||
// TODO: Support uploading files?
|
||||
filePath, _, err := backend.SoundGeneration(cfg.Backend, modelFile, input.Text, input.Duration, input.Temperature, input.DoSample, nil, nil, ml, appConfig, *cfg)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return c.Download(filePath)
|
||||
|
||||
}
|
||||
}
|
@ -16,4 +16,6 @@ func RegisterElevenLabsRoutes(app *fiber.App,
|
||||
// Elevenlabs
|
||||
app.Post("/v1/text-to-speech/:voice-id", auth, elevenlabs.TTSEndpoint(cl, ml, appConfig))
|
||||
|
||||
app.Post("/v1/sound-generation", auth, elevenlabs.SoundGenerationEndpoint(cl, ml, appConfig))
|
||||
|
||||
}
|
||||
|
@ -4,3 +4,11 @@ type ElevenLabsTTSRequest struct {
|
||||
Text string `json:"text" yaml:"text"`
|
||||
ModelID string `json:"model_id" yaml:"model_id"`
|
||||
}
|
||||
|
||||
type ElevenLabsSoundGenerationRequest struct {
|
||||
Text string `json:"text" yaml:"text"`
|
||||
ModelID string `json:"model_id" yaml:"model_id"`
|
||||
Duration *float32 `json:"duration_seconds,omitempty" yaml:"duration_seconds,omitempty"`
|
||||
Temperature *float32 `json:"prompt_influence,omitempty" yaml:"prompt_influence,omitempty"`
|
||||
DoSample *bool `json:"do_sample,omitempty" yaml:"do_sample,omitempty"`
|
||||
}
|
||||
|
@ -0,0 +1,23 @@
|
||||
meta {
|
||||
name: musicgen
|
||||
type: http
|
||||
seq: 1
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/v1/sound-generation
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model_id": "facebook/musicgen-small",
|
||||
"text": "Exciting 80s Newscast Interstitial",
|
||||
"duration_seconds": 8
|
||||
}
|
||||
}
|
3
go.sum
3
go.sum
@ -509,6 +509,9 @@ github.com/onsi/ginkgo v1.16.5 h1:8xi0RTUf59SOSfEtZMvwTvXYMzG4gV23XVHOZiXNtnE=
|
||||
github.com/onsi/ginkgo v1.16.5/go.mod h1:+E8gABHa3K6zRBolWtd+ROzc/U5bkGt0FwiG042wbpU=
|
||||
github.com/onsi/ginkgo/v2 v2.20.0 h1:PE84V2mHqoT1sglvHc8ZdQtPcwmvvt29WLEEO3xmdZw=
|
||||
github.com/onsi/ginkgo/v2 v2.20.0/go.mod h1:lG9ey2Z29hR41WMVthyJBGUBcBhGOtoPF2VFMvBXFCI=
|
||||
github.com/onsi/gomega v1.7.1/go.mod h1:XdKZgCCFLUoM/7CFJVPcG8C1xQ1AJ0vpAezJrB7JYyY=
|
||||
github.com/onsi/gomega v1.10.1/go.mod h1:iN09h71vgCQne3DLsj+A5owkum+a2tYe+TOCB1ybHNo=
|
||||
github.com/onsi/gomega v1.16.0/go.mod h1:HnhC7FXeEQY45zxNK3PPoIUhzk/80Xly9PcubAlGdZY=
|
||||
github.com/onsi/gomega v1.34.1 h1:EUMJIKUjM8sKjYbtxQI9A4z2o+rruxnzNvpknOXie6k=
|
||||
github.com/onsi/gomega v1.34.1/go.mod h1:kU1QgUvBDLXBJq618Xvm2LUX6rSAfRaFRTcdOeDLwwY=
|
||||
github.com/opencontainers/go-digest v1.0.0 h1:apOUWs51W5PlhuyGyz9FCeeBIOUDA/6nW8Oi/yOhh5U=
|
||||
|
@ -41,6 +41,7 @@ type Backend interface {
|
||||
PredictStream(ctx context.Context, in *pb.PredictOptions, f func(s []byte), opts ...grpc.CallOption) error
|
||||
GenerateImage(ctx context.Context, in *pb.GenerateImageRequest, opts ...grpc.CallOption) (*pb.Result, error)
|
||||
TTS(ctx context.Context, in *pb.TTSRequest, opts ...grpc.CallOption) (*pb.Result, error)
|
||||
SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequest, opts ...grpc.CallOption) (*pb.Result, error)
|
||||
AudioTranscription(ctx context.Context, in *pb.TranscriptRequest, opts ...grpc.CallOption) (*schema.TranscriptionResult, error)
|
||||
TokenizeString(ctx context.Context, in *pb.PredictOptions, opts ...grpc.CallOption) (*pb.TokenizationResponse, error)
|
||||
Status(ctx context.Context) (*pb.StatusResponse, error)
|
||||
|
@ -61,6 +61,10 @@ func (llm *Base) TTS(*pb.TTSRequest) error {
|
||||
return fmt.Errorf("unimplemented")
|
||||
}
|
||||
|
||||
func (llm *Base) SoundGeneration(*pb.SoundGenerationRequest) error {
|
||||
return fmt.Errorf("unimplemented")
|
||||
}
|
||||
|
||||
func (llm *Base) TokenizeString(opts *pb.PredictOptions) (pb.TokenizationResponse, error) {
|
||||
return pb.TokenizationResponse{}, fmt.Errorf("unimplemented")
|
||||
}
|
||||
|
@ -210,6 +210,26 @@ func (c *Client) TTS(ctx context.Context, in *pb.TTSRequest, opts ...grpc.CallOp
|
||||
return client.TTS(ctx, in, opts...)
|
||||
}
|
||||
|
||||
func (c *Client) SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequest, opts ...grpc.CallOption) (*pb.Result, error) {
|
||||
if !c.parallel {
|
||||
c.opMutex.Lock()
|
||||
defer c.opMutex.Unlock()
|
||||
}
|
||||
c.setBusy(true)
|
||||
defer c.setBusy(false)
|
||||
if c.wd != nil {
|
||||
c.wd.Mark(c.address)
|
||||
defer c.wd.UnMark(c.address)
|
||||
}
|
||||
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
defer conn.Close()
|
||||
client := pb.NewBackendClient(conn)
|
||||
return client.SoundGeneration(ctx, in, opts...)
|
||||
}
|
||||
|
||||
func (c *Client) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest, opts ...grpc.CallOption) (*schema.TranscriptionResult, error) {
|
||||
if !c.parallel {
|
||||
c.opMutex.Lock()
|
||||
|
@ -53,6 +53,10 @@ func (e *embedBackend) TTS(ctx context.Context, in *pb.TTSRequest, opts ...grpc.
|
||||
return e.s.TTS(ctx, in)
|
||||
}
|
||||
|
||||
func (e *embedBackend) SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequest, opts ...grpc.CallOption) (*pb.Result, error) {
|
||||
return e.s.SoundGeneration(ctx, in)
|
||||
}
|
||||
|
||||
func (e *embedBackend) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest, opts ...grpc.CallOption) (*schema.TranscriptionResult, error) {
|
||||
r, err := e.s.AudioTranscription(ctx, in)
|
||||
if err != nil {
|
||||
|
@ -17,6 +17,7 @@ type LLM interface {
|
||||
GenerateImage(*pb.GenerateImageRequest) error
|
||||
AudioTranscription(*pb.TranscriptRequest) (schema.TranscriptionResult, error)
|
||||
TTS(*pb.TTSRequest) error
|
||||
SoundGeneration(*pb.SoundGenerationRequest) error
|
||||
TokenizeString(*pb.PredictOptions) (pb.TokenizationResponse, error)
|
||||
Status() (pb.StatusResponse, error)
|
||||
|
||||
|
@ -84,7 +84,19 @@ func (s *server) TTS(ctx context.Context, in *pb.TTSRequest) (*pb.Result, error)
|
||||
if err != nil {
|
||||
return &pb.Result{Message: fmt.Sprintf("Error generating audio: %s", err.Error()), Success: false}, err
|
||||
}
|
||||
return &pb.Result{Message: "Audio generated", Success: true}, nil
|
||||
return &pb.Result{Message: "TTS audio generated", Success: true}, nil
|
||||
}
|
||||
|
||||
func (s *server) SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequest) (*pb.Result, error) {
|
||||
if s.llm.Locking() {
|
||||
s.llm.Lock()
|
||||
defer s.llm.Unlock()
|
||||
}
|
||||
err := s.llm.SoundGeneration(in)
|
||||
if err != nil {
|
||||
return &pb.Result{Message: fmt.Sprintf("Error generating audio: %s", err.Error()), Success: false}, err
|
||||
}
|
||||
return &pb.Result{Message: "Sound Generation audio generated", Success: true}, nil
|
||||
}
|
||||
|
||||
func (s *server) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest) (*pb.TranscriptResult, error) {
|
||||
|
@ -38,3 +38,19 @@ func SanitizeFileName(fileName string) string {
|
||||
safeName := strings.ReplaceAll(baseName, "..", "")
|
||||
return safeName
|
||||
}
|
||||
|
||||
func GenerateUniqueFileName(dir, baseName, ext string) string {
|
||||
counter := 1
|
||||
fileName := baseName + ext
|
||||
|
||||
for {
|
||||
filePath := filepath.Join(dir, fileName)
|
||||
_, err := os.Stat(filePath)
|
||||
if os.IsNotExist(err) {
|
||||
return fileName
|
||||
}
|
||||
|
||||
counter++
|
||||
fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
|
||||
}
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user