update mock database with wireguard internal addresses

.gitignore

@@ -1,5 +1,6 @@
 *.pyc
 *.wav
+!/src/voice_provider/speaker_wav/*
 *.lc3
 *.onnx
 *.onnx.json

Dockerfile

@@ -0,0 +1,35 @@
+FROM python:3.11-slim
+
+# Install system dependencies and poetry
+RUN apt-get update && apt-get install -y \
+    git \
+    gcc \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+# accept new ssh server
+RUN sed /^StrictHostKeyChecking/d /etc/ssh/ssh_config; \
+echo StrictHostKeyChecking no >> /etc/ssh/ssh_config
+
+# Install and configure poetry
+RUN --mount=type=cache,target=/root/.cache \
+    pip install poetry
+RUN poetry config virtualenvs.create false
+
+WORKDIR /app
+
+# copy the app code
+COPY ./src .
+COPY poetry.lock .
+COPY pyproject.toml .
+
+# Install the project with all dependencies 
+RUN --mount=type=cache,target=/root/.cache \
+    --mount=type=ssh,required=true \
+    poetry install --no-interaction --without dev --no-root
+
+# Expose the API port
+EXPOSE 7999
+
+# Run the translator server directly from the module path
+CMD ["python", "-m", "auracast_translator.translator_server.translator_server"]

docker-compose.yml

@@ -0,0 +1,13 @@
+services:
+  auracast-translator:
+    build:
+      context: .
+      dockerfile: Dockerfile
+      ssh: 
+        - default=~/.ssh/id_ed25519 #lappi
+    ports:
+      - "7999:7999"
+    environment:
+      - PYTHONUNBUFFERED=1
+    restart: unless-stopped
+

pyproject.toml

@@ -1,27 +1,43 @@
-[project]
+[tool.poetry]
-name = "multilang_translator"
+name = "auracast_translator"
-requires-python = ">= 3.11"
+version = "0.1.0"
-version = '0.1'
+authors = ["Patrick S <pstruebi>"]
-
+description = "Announcement System"
-dependencies = [
+readme = "readme.md"
-    "auracast @git+https://git@gitea.pstruebi.xyz/auracaster/bumble-auracast",
+packages = [
-    "requests==2.32.3",
+    { include = "translator_models", from = "src" },
-    "ollama==0.4.7",
+    { include = "translator_client", from = "src" },
-    "aioconsole==0.8.1",
+    { include = "auracast_translator", from = "src" },
-    "fastapi==0.115.11",
-    "uvicorn==0.34.0",
-    "aiohttp==3.9.3",
 ]
 
-[project.optional-dependencies]
+[tool.poetry.dependencies]
-test = [
+python = "~3.11"
-    "pytest >= 8.2",
+setuptools= ">=77"
-]
+coqui-tts = "0.26"
 
-[tool.poetry.group.tts.dependencies]
+[tool.poetry.group.general.dependencies]
-piper-phonemize = "==1.1.0"
+requests="2.32.3"
-piper-tts = "==1.2.0"
+aiohttp="3.9.3"
+fastapi="0.115.11"
+uvicorn="0.34.0"
+ollama="0.4.7"
+piper-tts="1.2.0"
+librosa="0.10.1"
+aioconsole="0.8.1"
+lc3 = { git = "ssh://git@ssh.pstruebi.xyz:222/auracaster/liblc3.git", rev = "7558637303106c7ea971e7bb8cedf379d3e08bcc" }
+auracast = { git = "ssh://git@ssh.pstruebi.xyz:222/auracaster/bumble-auracast.git" }
 
+#[tool.poetry.group.gpu.dependencies]
+#onnxruntime-gpu = "^1.20.1"
+# TODO: for running piper on gpu investigate
+# https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements
+# put everything in pytorch container according to piper github:
+# https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch
+# Use a seperate container for the voice provider
+
+
+[tool.poetry.group.dev.dependencies]
+pytest = {version=">8.2", optional=true}
 
 [tool.pytest.ini_options]
 addopts = [
@@ -29,5 +45,5 @@ addopts = [
 ]
 
 [build-system]
-requires = ["setuptools>=61", "wheel", "setuptools_scm>=8"]
+requires = ["poetry-core"]
-build-backend = "setuptools.build_meta"
+build-backend = "poetry.core.masonry.api"

readme.md

@@ -1,11 +1,6 @@
-# Prerequisites
+# Install the project
-sudo apt install liblc3-tools
+poetry env use python3.11
-
+poetry install
-use python3.9
-pip install piper-tts soundfile librosa pyserial pytest
 
 # Piper update voices
 piper --update-voices -m en_US-lessac-medium
-
-# TODO:
-- investigate using a pipeline instead of writing to intermediate files to gain performance

src/auracast_translator/main_cloud.py

@@ -10,14 +10,14 @@ from auracast import auracast_config
 import voice_client
 import voice_models
 
-from multilang_translator import translator_config
+from auracast_translator.translator_models import translator_models
-from multilang_translator.translator import llm_translator
+from auracast_translator.translator import llm_translator
 import voice_client.tts_client
 import voice_models.request_models
 
 
 async def announcement_from_german_text(
-        config: translator_config.TranslatorConfigGroup,
+        config: translator_models.TranslatorConfigGroup,
         text_de
         ):
     base_lang = "deu"

src/auracast_translator/main_local.py

@@ -9,9 +9,9 @@ from auracast import multicast_control
 from auracast import auracast_config
 from voice_provider import text_to_speech
 
-from multilang_translator import translator_config
+from auracast_translator import translator_config
-from multilang_translator.translator import llm_translator
+from auracast_translator.translator import llm_translator
-from multilang_translator.translator.test_content import TESTSENTENCE
+from auracast_translator.translator.test_content import TESTSENTENCE
 
 # TODO: look for a end to end translation solution
 

src/auracast_translator/translator/llm_translator.py

@@ -6,7 +6,7 @@ import time
 import ollama
 import aiohttp
 
-from multilang_translator.translator import syspromts
+from auracast_translator.translator import syspromts
 
 # ollama.create( # TODO: create models on startup 
 #     model='example', 
@@ -125,7 +125,7 @@ async def translate_de_to_x_async(
 
 if __name__ == "__main__":
     import time
-    from multilang_translator.translator import test_content
+    from auracast_translator.translator import test_content
 
 
     start=time.time()

src/auracast_translator/translator_server/endpoints_db.py

@@ -3,7 +3,7 @@ Database file for endpoint definitions.
 This file contains configurations for auracast endpoints including their IP addresses and capabilities.
 """
 from typing import List, Optional
-from multilang_translator.translator_models.translator_models import EndpointGroup, Endpoint
+from translator_models.translator_models import EndpointGroup, Endpoint
 
 
 SUPPORTED_LANGUAGES = ["deu", "eng", "fra", "spa", "ita"]
@@ -13,19 +13,19 @@ ENDPOINTS: dict[int: Endpoint] = { # for now make sure, .id and key are the same
     0: Endpoint(
         id=0,
         name="Local Endpoint",
-        url="http://localhost:5000",
+        url="http://10.13.13.3:5000", #"http://localhost:5000", #patricks laptop
         max_broadcasts=3,
     ),
     1: Endpoint(
         id=1,
         name="Gate 1",
-        url="http://pi3:5000",
+        url="http://10.13.13.4:5000", #pi4
         max_broadcasts=3,
     ),
     2: Endpoint(
         id=2,
         name="Gate 2",
-        url="http://192.168.1.102:5000",
+        url="http://10.13.13.5:5000",
         max_broadcasts=3,
     ),
 }

src/auracast_translator/translator_server/main_translator_api.py

@@ -7,7 +7,7 @@ import logging as log
 import sys
 import os
 
-# Add the parent directory to the Python path to find the multilang_translator package
+# Add the parent directory to the Python path to find the auracast_translator package
 current_dir = os.path.dirname(os.path.abspath(__file__))
 parent_dir = os.path.dirname(os.path.dirname(os.path.dirname(current_dir)))
 if parent_dir not in sys.path:
@@ -20,7 +20,7 @@ if __name__ == "__main__":
     )
     log.info("Starting Translator API server")
     uvicorn.run(
-        "multilang_translator.translator_server.translator_server:app",
+        "auracast_translator.translator_server.translator_server:app",
         host="0.0.0.0",
         port=7999,
         reload=True,

src/auracast_translator/translator_server/translator_server.py

@@ -11,9 +11,9 @@ from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 
 # Import models
-from multilang_translator.translator_models.translator_models import AnnouncementStates, Endpoint, EndpointGroup
+from translator_models.translator_models import AnnouncementStates, Endpoint, EndpointGroup
-from multilang_translator.translator import llm_translator
+from auracast_translator.translator import llm_translator
-from multilang_translator.translator_server import endpoints_db
+from auracast_translator.translator_server import endpoints_db
 from voice_provider import text_to_speech
 
 # Import the endpoints database and multicast client
@@ -154,7 +154,10 @@ async def make_announcement(text: str, ep_group: EndpointGroup):
             ep_group.sampling_rate_hz,
             trans_conf.tts_system,
             trans_conf.tts_model,
-            return_lc3=True
+            return_lc3=True,
+            language=trans_conf.xtts_language,
+            speaker=trans_conf.xtts_speaker,
+            speaker_wav=trans_conf.xtts_speaker_wav
         )
         synthesis_tasks.append(task)
     
@@ -329,9 +332,10 @@ async def get_available_languages():
 
 
 if __name__ == "__main__":
+    import os
     import uvicorn
     log.basicConfig(
-        level=log.DEBUG,
+        level=os.environ.get('LOG_LEVEL', log.DEBUG),
         format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
     )
     # with reload=True logging of modules does not function as expected
@@ -342,5 +346,5 @@ if __name__ == "__main__":
         port=7999,
         #reload=True,
         #log_config=None,
-        #log_level="info"
+        log_level="debug"
         )

src/multilang_translator/translator_config.py

@@ -1,20 +0,0 @@
-import os
-from pydantic import BaseModel
-
-VENV_DIR = os.path.join(os.path.dirname(__file__), './../../venv')
-
-class TranslatorLangConfig(BaseModel):
-    translator_llm: str = 'llama3.2:3b-instruct-q4_0' # TODO: this was migrated to translator_models - remove this
-    llm_client: str = 'ollama'
-    llm_host_url: str | None = 'http://localhost:11434'
-    llm_host_token: str | None = None
-    tts_system: str = 'piper'
-    tts_model: str ='de_DE-kerstin-low'
-
-class TranslatorConfig(BaseModel):
-    deu: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'de_DE-thorsten-high')
-    eng: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'en_GB-alba-medium')
-    fra: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'fr_FR-siwis-medium')
-    spa: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'es_ES-sharvard-medium')
-    ita: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'it_IT-paola-medium')
-

src/translator_client/translator_client.py

@@ -3,10 +3,9 @@ API client functions for interacting with the Translator API.
 """
 import requests
 from typing import List, Optional, Dict, Any, Tuple
-from enum import Enum
 
 
-from multilang_translator.translator_models.translator_models import AnnouncementStates, Endpoint, EndpointGroup
+from translator_models.translator_models import AnnouncementStates, Endpoint, EndpointGroup
 
 
 # This can be overridden through environment variables

src/translator_models/translator_models.py

@@ -35,12 +35,19 @@ class TranslatorLangConfig(BaseModel):
     # llm_host_url: str | None = 'http://localhost:11434'
     # llm_host_token: str | None = None
     
-    tts_system: str = 'piper'
+    tts_system: str = 'piper'  # Options: 'piper', 'xtts'
-    tts_model: str ='de_DE-kerstin-low'
+    tts_model: str = 'de_DE-kerstin-low'  # For piper: model name, for xtts: unused
+    xtts_language: str = 'de'  # Language code for XTTS
+    xtts_speaker: Optional[str] = None  # Speaker name for XTTS
+    xtts_speaker_wav: Optional[str] = None  # Path to speaker sample for XTTS voice cloning
 
 
 class TranslatorConfig(BaseModel):
-    deu: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'de_DE-thorsten-high')
+    deu: TranslatorLangConfig = TranslatorLangConfig(
+        tts_system='xtts',
+        xtts_language='de',
+        xtts_speaker_wav='female.wav'
+    )
     eng: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'en_GB-alba-medium')
     fra: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'fr_FR-siwis-medium')
     spa: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'es_ES-sharvard-medium')

src/voice_models/request_models.py

@@ -1,4 +1,5 @@
 from pydantic import BaseModel
+from typing import Optional
 
 class SynthesizeRequest(BaseModel):
     text: str
@@ -6,4 +7,6 @@ class SynthesizeRequest(BaseModel):
     framework: str = "piper"
     model: str = "en_US-lessac-medium"
     return_lc3: bool = False
-
+    language: str = "en"  # Language code for XTTS
+    speaker: Optional[str] = None  # Speaker name for XTTS
+    speaker_wav: Optional[str] = None  # Path to speaker sample for XTTS voice cloning

src/voice_provider/text_to_speech.py

@@ -1,4 +1,7 @@
 import os
+# Set environment variable to auto-accept Coqui TTS license
+os.environ["COQUI_TOS_AGREED"] = "1"
+
 import shutil
 import subprocess
 import time
@@ -6,16 +9,35 @@ import json
 import logging as log
 import numpy as np
 import asyncio
+import torch
 from voice_provider.utils.resample import resample_array
 from voice_provider.utils.encode_lc3 import encode_lc3
 
+# Now import TTS - the license will be auto-accepted
+from TTS.api import TTS
+
+# Get device for XTTS
+if torch.cuda.is_available():
+    log.info('XTTS will run on GPU')
+    XTTS_DEVICE = "cuda"  
+else:
+    log.info('XTTS will run on CPU')
+    XTTS_DEVICE = "cpu"
+
+# Load XTTS model globally - only once
+log.info("Initializing XTTS model...")
+start_init = time.time()
+XTTS_MODEL = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(XTTS_DEVICE)
+end_init = time.time()
+log.info(f"XTTS initialization completed in {end_init - start_init:.2f} seconds")
+
 PIPER_EXE = shutil.which('piper')
 
 TTS_DIR = os.path.join(os.path.dirname(__file__))
 PIPER_WORKDIR = f'{TTS_DIR}/piper'
 
 if not PIPER_EXE:
-    PIPER_EXE = f'{TTS_DIR}/../../venv/bin/piper'
+    PIPER_EXE = f'{TTS_DIR}/../../.venv/bin/piper'
 
 def synth_piper(text, model="en_US-lessac-medium"):
     pwd = os.getcwd()
@@ -26,7 +48,7 @@ def synth_piper(text, model="en_US-lessac-medium"):
     ret = subprocess.run( # TODO: wrap this whole thing in a class and open a permanent pipe to the model 
         [
             PIPER_EXE, 
-            '--cuda',
+            #'--cuda',
             '--model', model, 
             '--output-raw'
         ], 
@@ -52,7 +74,10 @@ def synthesize(
         target_sample_rate, 
         framework, 
         model="en_US-lessac-medium", 
-        return_lc3=True
+        return_lc3=True,
+        language="en",
+        speaker=None,
+        speaker_wav=None
         ):
 
     if framework == 'piper':
@@ -64,7 +89,40 @@ def synthesize(
     elif framework == 'koro':
         pass
     elif framework == 'xtts':
-        pass
+        start = time.time()
+        
+        # Generate audio using XTTS
+        # XTTS always outputs at 24kHz
+        xtts_sample_rate = 24000  
+        
+        # Validate speaker parameters - XTTS needs either speaker or speaker_wav
+        if speaker is None and speaker_wav is None:
+            # Use the first available speaker if none specified
+            speaker = XTTS_MODEL.speakers[0]
+            log.info(f"No speaker specified, using default: {speaker}")
+        
+        # Generate audio samples using tts.tts
+        if speaker_wav:
+            # expand path to speaker_wav folder
+            speaker_wav = os.path.join(os.path.dirname(__file__), 'speaker_wav', speaker_wav)
+            log.info(f"Generating XTTS audio with speaker_wav: {speaker_wav}")
+            audio_list = XTTS_MODEL.tts(text=text, speaker_wav=speaker_wav, language=language)
+        else:
+            log.info(f"Generating XTTS audio with speaker: {speaker}")
+            audio_list = XTTS_MODEL.tts(text=text, speaker=speaker, language=language)
+        
+        # Ensure audio_np is a numpy array and properly scaled
+        audio_np = np.array(audio_list, dtype=np.float32)# / (2**15-1)
+
+        # Log some info about the audio data
+        log.info(f"XTTS audio shape: {audio_np.shape}, dtype: {audio_np.dtype}, " 
+                f"min: {audio_np.min():.4f}, max: {audio_np.max():.4f}")
+        
+        # Resample from 24kHz to target sample rate with speedup factor
+        audio = resample_array(audio_np, xtts_sample_rate, target_sample_rate)
+        
+        log.info(f"XTTS synthesis completed in {time.time() - start:.2f} seconds")
+
     elif framework == 'zonos':
         pass
     else: raise NotImplementedError('unknown framework')
@@ -82,7 +140,10 @@ async def synthesize_async(
         target_sample_rate, 
         framework, 
         model="en_US-lessac-medium", 
-        return_lc3=True
+        return_lc3=True,
+        language="en",
+        speaker=None,
+        speaker_wav=None
         ):
     """
     Asynchronous version of the synthesize function that runs in a thread pool.
@@ -90,9 +151,12 @@ async def synthesize_async(
     Args:
         text: Text to synthesize
         target_sample_rate: Target sample rate for the audio
-        framework: TTS framework to use (e.g., 'piper')
+        framework: TTS framework to use (e.g., 'piper', 'xtts')
         model: Model to use for synthesis
         return_lc3: Whether to return LC3-encoded audio
+        language: Language code (used by XTTS)
+        speaker: Speaker ID for XTTS
+        speaker_wav: Path to speaker sample for XTTS voice cloning
         
     Returns:
         LC3-encoded audio as string or raw audio as numpy array
@@ -101,23 +165,53 @@ async def synthesize_async(
     loop = asyncio.get_event_loop()
     result = await loop.run_in_executor(
         None,
-        lambda: synthesize(text, target_sample_rate, framework, model, return_lc3)
+        lambda: synthesize(
+            text, 
+            target_sample_rate, 
+            framework, 
+            model, 
+            return_lc3,
+            language,
+            speaker,
+            speaker_wav
+        )
     )
     return result
 
 
 if __name__ == '__main__':
-    import logging
     import soundfile as sf
 
-    logging.basicConfig(
+    log.basicConfig(
-        level=logging.INFO,
+        level=log.INFO,
         format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
     )
-    target_rate=16000
+    target_rate = 16000
 
-    audio = synthesize('Hello World', target_rate, 'piper', model= 'de_DE-kerstin-low', return_lc3=False)
+    # First, print available XTTS speakers
+    print("Available XTTS speakers:")
+    print(XTTS_MODEL.speakers)
     
-    sf.write('hello.wav', audio, target_rate)
+    # Demo of Piper
+    print("Testing Piper TTS...")
+    audio_piper = synthesize('Hello World', target_rate, 'piper', model='de_DE-kerstin-low', return_lc3=False)
+    sf.write('hello_piper.wav', audio_piper, target_rate)
+
+    # Demo of XTTS with Annmarie Nele for German
+    speaker_wav = 'female.wav'
+    print(f"Testing XTTS with German language using speaker: {speaker_wav}")
+    text_to_synthesize = "Dies ist ein Test der XTTS Stimme auf Deutsch mit Annmarie Nele als Sprecherin."
+    
+    audio_xtts = synthesize(
+        text=text_to_synthesize,
+        target_sample_rate=target_rate,
+        framework='xtts',
+        language='de',
+        speaker_wav=speaker_wav,
+        return_lc3=False
+    )
+    
+    # Save the wav file
+    sf.write('hello_xtts_german.wav', audio_xtts, target_rate)
     
     print('Done.')

src/voice_provider/tts_server.py

@@ -17,7 +17,10 @@ async def synthesize_speech(request: SynthesizeRequest):
             target_sample_rate=request.target_sample_rate,
             framework=request.framework,
             model=request.model,
-            return_lc3=request.return_lc3
+            return_lc3=request.return_lc3,
+            language=request.language,
+            speaker=request.speaker,
+            speaker_wav=request.speaker_wav
         )
 
         if request.return_lc3:

src/voice_provider/utils/resample.py

@@ -24,16 +24,25 @@ def resample_file(filename, out_filename, target_rate):
     log.info("Resampling of %s took  %s s", os.path.basename(filename), round(time.time() - start, 3))
 
 
-def resample_array(audio, rate, target_rate):
+def resample_array(audio, rate, target_rate, speedup=1.0):
     start=time.time()
     # Load the original audio file
 
-    if rate == target_rate: # Nothing to do 
+    if rate == target_rate and speedup == 1.0: # Nothing to do 
-        log.info('audio already at target rate, skipping resample')
+        log.info('audio already at target rate with no speedup, skipping resample')
         return audio
 
+    # Apply speedup if needed
+    if speedup != 1.0:
+        # When speeding up, we need to resample to a lower rate first
+        # This effectively shortens the audio duration
+        effective_orig_sr = rate * speedup
+        log.info(f"Applying speedup factor of {speedup}")
+    else:
+        effective_orig_sr = rate
+
     # Convert the sample rate to target rate
-    resampled_audio = librosa.resample(audio, orig_sr=rate, target_sr=target_rate)
+    resampled_audio = librosa.resample(audio, orig_sr=effective_orig_sr, target_sr=target_rate)
 
     # Save the resampled audio as a new .wav file
     
@@ -45,4 +54,4 @@ if __name__ == "__main__":
     import os
     os.chdir(os.path.dirname(__file__))
     file_dir = '../text_to_speech/'
-    resample_file(f'{file_dir}/welcome.wav', f'{file_dir}/welcome_resampled.wav')
+    resample_file(f'{file_dir}/welcome.wav', f'{file_dir}/welcome_resampled.wav', 16000)

tests/conftest.py

@@ -4,9 +4,9 @@ import time
 import os
 import subprocess
 
-from multilang_translator.backend_controller.broadcaster_config import broadcaster_config, BROADCAST_CONFIG
+from auracast_translator.backend_controller.broadcaster_config import broadcaster_config, BROADCAST_CONFIG
-from multilang_translator.backend_controller.broadcaster_play_once import broadcaster_play_file
+from auracast_translator.backend_controller.broadcaster_play_once import broadcaster_play_file
-from multilang_translator.backend_controller.broadcaster_copy_files import copy_to_broadcaster
+from auracast_translator.backend_controller.broadcaster_copy_files import copy_to_broadcaster
 
 log.basicConfig(
     level=log.INFO,

tests/test_backend.py

@@ -4,9 +4,9 @@ import time
 import os
 import subprocess
 
-from multilang_translator.translator_config import LANG_CONFIG
+from auracast_translator.translator_config import LANG_CONFIG
-from multilang_translator.backend_controller.broadcaster_play_once import broadcaster_play_file
+from auracast_translator.backend_controller.broadcaster_play_once import broadcaster_play_file
-from multilang_translator.backend_controller.broadcaster_copy_files import copy_to_broadcaster
+from auracast_translator.backend_controller.broadcaster_copy_files import copy_to_broadcaster
 
 
 def test_config_broadcaster(ft_configure_broadcaster):

tests/test_system.py

@@ -1,5 +1,5 @@
-from multilang_translator.main_local import announcement_from_german_text
+from auracast_translator.main_local import announcement_from_german_text
-from multilang_translator.translator import test_content
+from auracast_translator.translator import test_content
 
 
 def test_announcement_from_german_text(

tests/test_translator.py

@@ -1,6 +1,6 @@
-from multilang_translator.translator.llm_translator import translator_de_en, translator_de_fr, translator_de_it
+from auracast_translator.translator.llm_translator import translator_de_en, translator_de_fr, translator_de_it
-from multilang_translator.translator.test_content import TESTSENTENCE_DE_BROKER, TESTSENTENCE_DE_RAINBOW
+from auracast_translator.translator.test_content import TESTSENTENCE_DE_BROKER, TESTSENTENCE_DE_RAINBOW
-from multilang_translator.main_local import translate_from_german
+from auracast_translator.main_local import translate_from_german
 
 
 import time

tests/test_tts.py

@@ -1,4 +1,4 @@
-from multilang_translator.text_to_speech.text_to_speech import synthesize
+from auracast_translator.text_to_speech.text_to_speech import synthesize
 
 def test_synthesize():
     synthesize("Hello, how are you?", "en_US-lessac-medium", "hello.wav")