feat(transformers): add support to OuteTTS

backend/python/transformers/backend.py

@@ -24,7 +24,7 @@
 from transformers import AutoTokenizer, AutoModel, set_seed, TextIteratorStreamer, StoppingCriteriaList, StopStringCriteria
 from transformers import AutoProcessor, MusicgenForConditionalGeneration
 from scipy.io import wavfile
-
+import outetts
 
 _ONE_DAY_IN_SECONDS = 60 * 60 * 24
 
@@ -87,6 +87,7 @@ def LoadModel(self, request, context):
 
         self.CUDA = torch.cuda.is_available()
         self.OV=False
+        self.OuteTTS=False
 
         device_map="cpu"
 
@@ -195,7 +196,45 @@ def LoadModel(self, request, context):
                 self.OV = True
             elif request.Type == "MusicgenForConditionalGeneration":
                 self.processor = AutoProcessor.from_pretrained(model_name)
-                self.model = MusicgenForConditionalGeneration.from_pretrained(model_name)                
+                self.model = MusicgenForConditionalGeneration.from_pretrained(model_name)
+            elif request.Type == "OuteTTS":
+                options = request.Options
+                MODELNAME = "OuteAI/OuteTTS-0.3-1B"
+                TOKENIZER = "OuteAI/OuteTTS-0.3-1B"
+                VERSION = "0.3"
+                SPEAKER = "en_male_1"
+                for opt in options:
+                    if opt.startswith("tokenizer:"):
+                        TOKENIZER = opt.split(":")[1]
+                        break
+                    if opt.startswith("version:"):
+                        VERSION = opt.split(":")[1]
+                        break
+                    if opt.startswith("speaker:"):
+                        SPEAKER = opt.split(":")[1]
+                        break
+
+                if model_name != "":
+                    MODELNAME = model_name
+
+                # Configure the model
+                model_config = outetts.HFModelConfig_v2(
+                    model_path=MODELNAME,
+                    tokenizer_path=TOKENIZER
+                )
+                # Initialize the interface
+                self.interface = outetts.InterfaceHF(model_version=VERSION, cfg=model_config)
+                self.OuteTTS = True
+
+                self.interface.print_default_speakers()
+                if request.AudioPath:
+                    if os.path.isabs(request.AudioPath):
+                        self.AudioPath = request.AudioPath
+                    else:
+                        self.AudioPath = os.path.join(request.ModelPath, request.AudioPath)
+                    self.speaker = self.interface.create_speaker(audio_path=self.AudioPath)
+                else:
+                    self.speaker = self.interface.load_default_speaker(name=SPEAKER)               
             else:
                 print("Automodel", file=sys.stderr)
                 self.model = AutoModel.from_pretrained(model_name, 
@@ -206,7 +245,7 @@ def LoadModel(self, request, context):
                                                        torch_dtype=compute)
             if request.ContextSize > 0:
                 self.max_tokens = request.ContextSize
-            elif request.Type != "MusicgenForConditionalGeneration":
+            elif hasattr(self.model, 'config') and hasattr(self.model.config, 'max_position_embeddings'):
                 self.max_tokens = self.model.config.max_position_embeddings
             else:
                 self.max_tokens = 512
@@ -445,9 +484,30 @@ def SoundGeneration(self, request, context):
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
         return backend_pb2.Result(success=True)
 
+    def OuteTTS(self, request, context):
+        try:
+            print("[OuteTTS] generating TTS", file=sys.stderr)
+            gen_cfg = outetts.GenerationConfig(
+                text="Speech synthesis is the artificial production of human speech.",
+                temperature=0.1,
+                repetition_penalty=1.1,
+                max_length=self.max_tokens,
+                speaker=self.speaker,
+                # voice_characteristics="upbeat enthusiasm, friendliness, clarity, professionalism, and trustworthiness"
+            )
+            output = self.interface.generate(config=gen_cfg)
+            print("[OuteTTS] Generated TTS", file=sys.stderr)
+            output.save(request.dst)
+            print("[OuteTTS] TTS done", file=sys.stderr)
+        except Exception as err:
+            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
+        return backend_pb2.Result(success=True)
 
 # The TTS endpoint is older, and provides fewer features, but exists for compatibility reasons
     def TTS(self, request, context):
+        if self.OuteTTS:
+            return self.OuteTTS(request, context)
+
         model_name = request.model
         try:
             if self.processor is None:
@@ -463,7 +523,7 @@ def TTS(self, request, context):
                 padding=True,
                 return_tensors="pt",
             )
-            tokens = 512 # No good place to set the "length" in TTS, so use 10s as a sane default
+            tokens = self.max_tokens # No good place to set the "length" in TTS, so use 10s as a sane default
             audio_values = self.model.generate(**inputs, max_new_tokens=tokens)
             print("[transformers-musicgen] TTS generated!", file=sys.stderr)
             sampling_rate = self.model.config.audio_encoder.sampling_rate

backend/python/transformers/requirements-cpu.txt

@@ -1,4 +1,6 @@
 torch==2.4.1
+llvmlite==0.43.0
 accelerate
 transformers
-bitsandbytes
+bitsandbytes
+outetts

backend/python/transformers/requirements-cublas11.txt

@@ -1,5 +1,7 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
 torch==2.4.1+cu118
+llvmlite==0.43.0
 accelerate
 transformers
-bitsandbytes
+bitsandbytes
+outetts

backend/python/transformers/requirements-cublas12.txt

@@ -1,4 +1,6 @@
 torch==2.4.1
 accelerate
+llvmlite==0.43.0
 transformers
-bitsandbytes
+bitsandbytes
+outetts

backend/python/transformers/requirements-hipblas.txt

@@ -2,4 +2,6 @@
 torch==2.4.1+rocm6.0
 accelerate
 transformers
-bitsandbytes
+llvmlite==0.43.0
+bitsandbytes
+outetts

backend/python/transformers/requirements-intel.txt

@@ -3,5 +3,7 @@ intel-extension-for-pytorch==2.3.110+xpu
 torch==2.3.1+cxx11.abi
 oneccl_bind_pt==2.3.100+xpu
 optimum[openvino]
+llvmlite==0.43.0
 intel-extension-for-transformers
-bitsandbytes
+bitsandbytes
+outetts

backend/python/transformers/requirements.txt

@@ -2,4 +2,6 @@ grpcio==1.69.0
 protobuf
 certifi
 setuptools
-scipy==1.14.0
+scipy==1.14.0
+numpy>=2.0.0
+numba==0.60.0