Working tortoise install script

install_tortiose_tts.bat

@@ -0,0 +1,50 @@
+@echo off
+cd /D %~dp0
+
+:Isolation
+call conda deactivate 2>NUL
+set Path=%windir%\system32;%windir%;C:\Windows\System32\Wbem;%windir%\System32\WindowsPowerShell\v1.0\;%windir%\System32\OpenSSH\
+SET CONDA_SHLVL=
+SET PYTHONNOUSERSITE=1
+SET PYTHONPATH=
+
+rmdir /S /Q flask_session 2>NUL
+
+TITLE KoboldAI - Server
+SET /P M=<loader.settings
+IF %M%==1 GOTO drivemap
+IF %M%==2 GOTO subfolder
+IF %M%==3 GOTO drivemap_B
+
+:subfolder
+ECHO Runtime launching in subfolder mode
+call miniconda3\condabin\activate
+pip install git+https://github.com/neonbjb/tortoise-tts progressbar inflect librosa rotary-embedding-torch unidecode lazy_loader llvmlite numba joblib decorator audioread msgpack pooch scikit-learn soundfile soxr platformdirs threadpoolctl pydantic-core annotated-types pydantic --no-dependencies
+pip install torchaudio --index-url https://download.pytorch.org/whl/cu118
+cmd /k
+pause
+exit
+
+:drivemap
+ECHO Runtime launching in K: drive mode
+subst /D K: >nul
+subst K: miniconda3 >nul
+call K:\python\condabin\activate
+pip install git+https://github.com/neonbjb/tortoise-tts progressbar inflect librosa rotary-embedding-torch unidecode lazy_loader llvmlite numba joblib decorator audioread msgpack pooch scikit-learn soundfile soxr platformdirs threadpoolctl pydantic-core annotated-types pydantic --no-dependencies
+pip install torchaudio --index-url https://download.pytorch.org/whl/cu118
+pip install -r requirements.txt --no-dependencies
+cmd /k
+pause
+exit
+
+:drivemap_B
+ECHO Runtime launching in B: drive mode
+subst /D B: >nul
+subst B: miniconda3 >nul
+call B:\python\condabin\activate
+pip install git+https://github.com/neonbjb/tortoise-tts progressbar inflect librosa rotary-embedding-torch unidecode lazy_loader llvmlite numba joblib decorator audioread msgpack pooch scikit-learn soundfile soxr platformdirs threadpoolctl pydantic-core annotated-types pydantic --no-dependencies
+pip install torchaudio --index-url https://download.pytorch.org/whl/cu118
+pip install -r requirements.txt --no-dependencies
+cmd /k
+pause
+exit

install_tortiose_tts.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+bin/micromamba run -r runtime -n koboldai pip install git+https://github.com/neonbjb/tortoise-tts OmegaConf deepspeed
+bin/micromamba run -r runtime -n koboldai pip install torchaudio --index-url https://download.pytorch.org/whl/cu118
+bin/micromamba run -r runtime -n koboldai pip install -r requirements.txt --no-dependencies

koboldai_settings.py

@@ -21,6 +21,7 @@ queue = None
 multi_story = False
 global enable_whitelist
 enable_whitelist = False
+slow_tts_message_shown = False
 
 if importlib.util.find_spec("tortoise") is not None:
     from tortoise import api
@@ -2119,10 +2120,14 @@ class KoboldStoryRegister(object):
     
     def create_wave_slow(self, make_audio_queue_slow):
         import pydub
+        global slow_tts_message_shown
         sample_rate = 24000
         speaker = 'train_daws'
+        if importlib.util.find_spec("tortoise") is None and not slow_tts_message_shown:
+            logger.info("Disabling slow (and higher quality) tts as it's not installed")
+            slow_tts_message_shown=True
         if self.tortoise is None and importlib.util.find_spec("tortoise") is not None:
-           self.tortoise=api.TextToSpeech(use_deepspeed=os.environ.get('deepspeed', "true").lower()=="true", kv_cache=os.environ.get('kv_cache', "true").lower()=="true", half=True)
+           self.tortoise=api.TextToSpeech(use_deepspeed=os.environ.get('deepspeed', "false").lower()=="true", kv_cache=os.environ.get('kv_cache', "true").lower()=="true", half=True)
         
         if importlib.util.find_spec("tortoise") is not None:
             voice_samples, conditioning_latents = load_voices([speaker])

modeling/inference_models/hf_torch.py

@@ -351,7 +351,6 @@ class HFTorchInferenceModel(HFInferenceModel):
                     bad_words_ids=self.active_badwordsids,
                     use_cache=True,
                     num_return_sequences=batch_count,
-                    pad_token_id=self.tokenizer.eos_token_id,
                 )
             else:
                  genout = self.model.generate(