restructure the project

src/multilang_translator/main_local.py

@@ -7,18 +7,16 @@ from __future__ import print_function, unicode_literals
 from typing import List
 from dataclasses import asdict
 import asyncio
-from copy import copy
 import time
 import logging as log
 import aioconsole
 
-import multilang_translator.translator_config as translator_config
-from utils import resample
-from translator import llm_translator, test_content
-from text_to_speech import text_to_speech
 from auracast import multicast_control
 from auracast import auracast_config
+import multilang_translator.translator_config as translator_config
+from translator import llm_translator
 from translator.test_content import TESTSENTENCE
+from voice_provider import text_to_speech
 
 # TODO: look for a end to end translation solution
 

src/multilang_translator/translator_config.py

@@ -2,9 +2,7 @@ import os
 from pydantic import BaseModel
 from auracast import auracast_config
 
-ANNOUNCEMENT_DIR = os.path.join(os.path.dirname(__file__), 'announcements')
-VENV_DIR = os.path.join(os.path.dirname(__file__), '../venv')
-PIPER_EXE_PATH = f'{VENV_DIR}/bin/piper'
+VENV_DIR = os.path.join(os.path.dirname(__file__), './../../venv')
 
 class TranslatorBaseconfig(BaseModel):
     big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigDe()

src/voice_provider/text_to_speech.py

@@ -1,27 +1,33 @@
 import os
+import shutil
 import subprocess
 import time
 import json
 import logging as log
 import numpy as np
-from multilang_translator import translator_config
-from multilang_translator.utils.resample import resample_array
-from multilang_translator.text_to_speech import encode_lc3
+from voice_provider.utils.resample import resample_array
+from voice_provider.utils.encode_lc3 import encode_lc3
+
+PIPER_EXE = shutil.which('piper')
 
 TTS_DIR = os.path.join(os.path.dirname(__file__))
-PIPER_DIR = f'{TTS_DIR}/piper'
+PIPER_WORKDIR = f'{TTS_DIR}/piper'
+
+if not PIPER_EXE:
+    PIPER_EXE = f'{TTS_DIR}/../../venv/bin/piper'
 
 def synth_piper(text, model="en_US-lessac-medium"):
     pwd = os.getcwd()
-    os.chdir(PIPER_DIR)
+    os.chdir(PIPER_WORKDIR)
     start = time.time()
     
     # make sure piper has voices.json in working directory, otherwise it attempts to always load models
     ret = subprocess.run( # TODO: wrap this whole thing in a class and open a permanent pipe to the model 
-        [translator_config.PIPER_EXE_PATH, 
-        '--cuda',
-        '--model', model, 
-        '--output-raw'
+        [
+            PIPER_EXE, 
+            '--cuda',
+            '--model', model, 
+            '--output-raw'
         ], 
         input=text.encode('utf-8'),
         capture_output=True
@@ -34,7 +40,7 @@ def synth_piper(text, model="en_US-lessac-medium"):
 
     log.info("Running piper for model %s took %s s", model, round(time.time() - start, 3))
 
-    with open (f'{PIPER_DIR}/{model}.onnx.json') as f: # TODO: wrap everyth0ing into a class, store the json permanently
+    with open (f'{PIPER_WORKDIR}/{model}.onnx.json') as f: # TODO: wrap everyth0ing into a class, store the json permanently
         model_json = json.load(f)
 
     return model_json, audio
@@ -59,7 +65,7 @@ def synthesize(text, target_sample_rate, framework, model="en_US-lessac-medium",
 
     if return_lc3:
         audio_pcm = (audio * 2**15-1).astype(np.int16)
-        lc3 = encode_lc3.encode(audio_pcm, target_sample_rate, 40) # TODO: octetts per frame should be parameter
+        lc3 = encode_lc3(audio_pcm, target_sample_rate, 40) # TODO: octetts per frame should be parameter
         return lc3
     else:
         return audio

src/voice_provider/utils/encode_lc3.py

@@ -1,7 +1,7 @@
 import numpy as np
 import lc3
 
-def encode(
+def encode_lc3(
         audio: np.array,
         output_sample_rate_hz,
         octets_per_frame,