restructure_for_cloud (#3)

- implement a presentable working version of translator_Server

Reviewed-on: https://gitea.pstruebi.xyz/auracaster/multilang-translator-local/pulls/3

.vscode/tasks.json

@@ -17,7 +17,8 @@
         {
             "label": "pip install -e auracast",
             "type": "shell",
-            "command": "./venv/bin/python -m pip install -e ../bumble-auracast --config-settings editable_mode=compat"
+            "command": "./venv/bin/python -m pip install -e ../bumble-auracast --config-settings editable_mode=compat",
+            "problemMatcher": []
         }
     ]
 }

multilang_translator/translator_config.py

@@ -1,37 +0,0 @@
-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'
-
-class TranslatorBaseconfig(BaseModel):
-    big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigDe()
-    translator_llm: str = 'llama3.2:3b-instruct-q4_0'
-    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 TranslatorConfigDe(TranslatorBaseconfig):
-    big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigDe()
-    tts_model: str ='de_DE-thorsten-high'
-
-class TranslatorConfigEn(TranslatorBaseconfig):
-    big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigEn()
-    tts_model: str = 'en_GB-alba-medium'
-
-class TranslatorConfigFr(TranslatorBaseconfig):
-    big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigFr()
-    tts_model: str = 'fr_FR-siwis-medium'
-
-class TranslatorConfigEs(TranslatorBaseconfig):
-    big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigEs()
-    tts_model: str = 'es_ES-sharvard-medium'
-
-class TranslatorConfigIt(TranslatorBaseconfig):
-    big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigIt()
-    tts_model: str = 'it_IT-paola-medium'

pyproject.toml

@@ -8,8 +8,9 @@ dependencies = [
     "requests==2.32.3",
     "ollama==0.4.7",
     "aioconsole==0.8.1",
-    "piper-phonemize==1.1.0",
-    "piper-tts==1.2.0",
+    "fastapi==0.115.11",
+    "uvicorn==0.34.0",
+    "aiohttp==3.9.3",
 ]
 
 [project.optional-dependencies]
@@ -17,6 +18,11 @@ test = [
     "pytest >= 8.2",
 ]
 
+[tool.poetry.group.tts.dependencies]
+piper-phonemize = "==1.1.0"
+piper-tts = "==1.2.0"
+
+
 [tool.pytest.ini_options]
 addopts = [
     "--import-mode=importlib","--count=1","-s","-v" 

src/multilang_translator/main_cloud.py

@@ -0,0 +1,89 @@
+from typing import List
+import time
+import asyncio
+
+import logging as log
+
+from auracast import multicast_client
+from auracast import auracast_config
+
+import voice_client
+import voice_models
+
+from multilang_translator import translator_config
+from multilang_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,
+        text_de
+        ):
+    base_lang = "deu"
+
+    audio_data_dict = {}
+    for i, big in enumerate(config.bigs):
+        if big.language == base_lang:
+            text = text_de
+        else:
+            text = llm_translator.translate_de_to_x(
+                text_de,
+                big.language,
+                model=big.translator_llm,
+                client = big.llm_client,
+                host=big.llm_host_url,
+                token=big.llm_host_token
+            )
+
+        log.info('%s', text)
+        request_data = voice_models.request_models.SynthesizeRequest(
+            text=text,
+            target_sample_rate=config.auracast_sampling_rate_hz,
+            framework=big.tts_system, 
+            model=big.tts_model,
+            return_lc3=True
+        )
+        start = time.time()
+        lc3_audio = voice_client.tts_client.request_synthesis(
+            request_data
+        )
+        log.info('Voice synth took %s', time.time() - start)
+        audio_data_dict[big.language] = lc3_audio.decode('latin-1') # TODO: should be .hex in the future
+
+    await multicast_client.send_audio(
+        audio_data_dict
+    )
+
+
+async def main():
+    log.basicConfig(
+        level=log.INFO,
+        format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
+    )
+
+    config = translator_config.TranslatorConfigGroup(
+        bigs=[
+            translator_config.TranslatorConfigDe(),
+            translator_config.TranslatorConfigEn(),
+            translator_config.TranslatorConfigFr(),
+        ]
+    )
+
+    config.transport='serial:/dev/serial/by-id/usb-ZEPHYR_Zephyr_HCI_UART_sample_81BD14B8D71B5662-if00,115200,rtscts' #nrf52dongle hci_uart usb cdc
+
+    for conf in config.bigs:
+        conf.loop = False
+        conf.llm_client = 'openwebui' # comment out for local llm
+        conf.llm_host_url = 'https://ollama.pstruebi.xyz' 
+        conf.llm_host_token = 'sk-17124cb84df14cc6ab2d9e17d0724d13'
+
+    await multicast_client.init(
+        config
+    )
+
+    await announcement_from_german_text(config, 'Hello')
+
+
+if __name__ == '__main__':
+    asyncio.run(main())

src/multilang_translator/main_local.py

@@ -1,24 +1,17 @@
-# -*- coding: utf-8 -*-
-"""
-list prompt example
-"""
-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
-from translator.test_content import TESTSENTENCE
+from voice_provider import text_to_speech
+
+from multilang_translator import translator_config
+from multilang_translator.translator import llm_translator
+from multilang_translator.translator.test_content import TESTSENTENCE
 
 # TODO: look for a end to end translation solution
 
@@ -27,33 +20,32 @@ def transcribe():
 
 
 async def announcement_from_german_text(
-        global_config: auracast_config.AuracastGlobalConfig,
-        translator_config: List[translator_config.TranslatorConfigDe],
+        config: translator_config.TranslatorConfigGroup,
         caster: multicast_control.Multicaster,
         text_de
         ):
     base_lang = "deu"
 
-    for i, trans in enumerate(translator_config):
-        if trans.big.language == base_lang:
+    for i, big in enumerate(config.bigs):
+        if big.language == base_lang:
             text = text_de
         else:
             text = llm_translator.translate_de_to_x(
                 text_de,
-                trans.big.language,
-                model=trans.translator_llm,
-                client = trans.llm_client,
-                host=trans.llm_host_url,
-                token=trans.llm_host_token
+                big.language,
+                model=big.translator_llm,
+                client = big.llm_client,
+                host=big.llm_host_url,
+                token=big.llm_host_token
             )
 
         log.info('%s', text)
 
         lc3_audio = text_to_speech.synthesize(
             text,
-            global_config.auracast_sampling_rate_hz,
-            trans.tts_system,
-            trans.tts_model,
+            config.auracast_sampling_rate_hz,
+            big.tts_system,
+            big.tts_model,
             return_lc3=True
             )
         caster.big_conf[i].audio_source = lc3_audio
@@ -64,7 +56,7 @@ async def announcement_from_german_text(
     log.info("Starting all broadcasts took %s s", round(time.time() - start, 3))
 
 
-async def command_line_ui(global_conf, translator_conf, caster: multicast_control.Multicaster):
+async def command_line_ui(config: translator_config.TranslatorConfigGroup, translator_conf, caster: multicast_control.Multicaster):
     while True:
         # make a list of all available testsentence
         sentence_list = list(asdict(TESTSENTENCE).values())
@@ -86,8 +78,7 @@ async def command_line_ui(global_conf, translator_conf, caster: multicast_contro
         elif command.strip().isdigit():
             ind = int(command.strip())
             await announcement_from_german_text(
-                global_conf,
-                translator_conf,
+                config,
                 caster, 
                 sentence_list[ind])
             await asyncio.wait([caster.streamer.task])
@@ -103,35 +94,41 @@ async def main():
         format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
     )
 
-    global_conf = auracast_config.AuracastGlobalConfig()
-    #global_conf.transport='serial:/dev/serial/by-id/usb-SEGGER_J-Link_001057705357-if02,1000000,rtscts' # transport for nrf54l15dk
-    global_conf.transport='serial:/dev/serial/by-id/usb-ZEPHYR_Zephyr_HCI_UART_sample_81BD14B8D71B5662-if00,115200,rtscts' #nrf52dongle hci_uart usb cdc
-
-
-    translator_conf = [
-        translator_config.TranslatorConfigDe(),
-        translator_config.TranslatorConfigEn(),
-        translator_config.TranslatorConfigFr(),
-        #auracast_config.broadcast_es,
-        #auracast_config.broadcast_it,
+    config = translator_config.TranslatorConfigGroup(
+        bigs=[
+            translator_config.TranslatorConfigDe(),
+            translator_config.TranslatorConfigEn(),
+            translator_config.TranslatorConfigFr(),
         ]
-    for conf in translator_conf:
-        conf.big.loop = False
+    )
+
+    #config = auracast_config.AuracastGlobalConfig()
+    #config.transport='serial:/dev/serial/by-id/usb-SEGGER_J-Link_001057705357-if02,1000000,rtscts' # transport for nrf54l15dk
+    config.transport='serial:/dev/serial/by-id/usb-ZEPHYR_Zephyr_HCI_UART_sample_81BD14B8D71B5662-if00,115200,rtscts' #nrf52dongle hci_uart usb cdc
+
+    for conf in config.bigs:
+        conf.loop = False
         conf.llm_client = 'openwebui' # comment out for local llm
         conf.llm_host_url = 'https://ollama.pstruebi.xyz' 
         conf.llm_host_token = 'sk-17124cb84df14cc6ab2d9e17d0724d13'
 
-    caster = multicast_control.Multicaster(global_conf, [conf.big for conf in translator_conf])
+    caster = multicast_control.Multicaster(
+        config, 
+        [big for big in config.bigs]
+        )
     await caster.init_broadcast()
 
     # await announcement_from_german_text(
-    #     global_conf,
-    #     translator_conf,
+    #     config,
     #     caster, 
     #     test_content.TESTSENTENCE.DE_HELLO
     #     )
     # await asyncio.wait([caster.streamer.task])
-    await command_line_ui(global_conf, translator_conf, caster)
+    await command_line_ui(
+        config, 
+        [big for big in config.bigs], 
+        caster
+        )
 
 if __name__ == '__main__':
     asyncio.run(main())

src/multilang_translator/translator/llm_translator.py

@@ -4,6 +4,7 @@ import json
 import logging as log
 import time
 import ollama
+import aiohttp
 
 from multilang_translator.translator import syspromts
 
@@ -12,10 +13,6 @@ from multilang_translator.translator import syspromts
 #     from_='llama3.2', system="You are Mario from Super Mario Bros."
 #     )
 
-async def chat():
-  message = {'role': 'user', 'content': 'Why is the sky blue?'}
-  response = await ollama.AsyncClient().chat(model='llama3.2', messages=[message])
-
 
 def query_openwebui(model, system, query, url, token):
     url = f'{url}/api/chat/completions'
@@ -50,6 +47,41 @@ def query_ollama(model, system, query, host='http://localhost:11434'):
     return response.message.content
 
 
+async def query_openwebui_async(model, system, query, url, token):
+    url = f'{url}/api/chat/completions'
+    headers = {
+        'Authorization': f'Bearer {token}',
+    }
+    payload = {
+        'model': model,
+        'messages': [
+            {'role': 'system', 'content': system},
+            {'role': 'user', 'content': query}
+        ],
+    }
+    start = time.time()
+    async with aiohttp.ClientSession() as session:
+        async with session.post(url, headers=headers, json=payload) as response:
+            response_json = await response.json()
+            log.info("Translating the text took %s s", round(time.time() - start, 2))
+            return response_json['choices'][0]['message']['content']
+
+
+async def query_ollama_async(model, system, query, host='http://localhost:11434'):
+    client = ollama.AsyncClient(
+        host=host,
+    )
+
+    response = await client.chat(
+        model=model,
+        messages=[
+            {'role': 'system', 'content': system},
+            {'role': 'user', 'content': query}
+        ],
+    )
+    return response.message.content
+
+
 def translate_de_to_x( # TODO: use async ollama client later - implenent a translate async function
         text:str, 
         target_language: str, 
@@ -70,6 +102,27 @@ def translate_de_to_x( # TODO: use async ollama client later - implenent a trans
     log.info('Running the translator to %s took %s s', target_language, round(time.time() - start, 3))
     return response
 
+async def translate_de_to_x_async(
+        text:str, 
+        target_language: str, 
+        client='ollama', 
+        model='llama3.2:3b-instruct-q4_0', # remember to use instruct models
+        host = None, 
+        token = None
+    ): 
+    start=time.time()
+    s = getattr(syspromts, f"TRANSLATOR_DEU_{target_language.upper()}")
+ 
+    if client == 'ollama':
+        response = await query_ollama_async(model, s, text, host=host)
+    elif client == 'openwebui':
+        response = await query_openwebui_async(model, s, text, url=host, token=token)
+    else: raise NotImplementedError('llm client not implemented')
+
+    log.info('Running the translator to %s took %s s', target_language, round(time.time() - start, 3))
+    return response
+
+
 if __name__ == "__main__":
     import time
     from multilang_translator.translator import test_content

src/multilang_translator/translator_client/translator_client.py

@@ -0,0 +1,94 @@
+"""
+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
+
+
+# This can be overridden through environment variables
+API_BASE_URL = "http://localhost:7999"
+
+def get_groups() -> List[EndpointGroup]:
+    """Get all endpoint groups."""
+    response = requests.get(f"{API_BASE_URL}/groups")
+    response.raise_for_status()
+    return [EndpointGroup.model_validate(group) for group in response.json()]
+
+def get_group(group_id: int) -> Optional[EndpointGroup]:
+    """Get a specific endpoint group by ID."""
+    response = requests.get(f"{API_BASE_URL}/groups/{group_id}")
+    if response.status_code == 404:
+        return None
+    response.raise_for_status()
+    return EndpointGroup.model_validate(response.json())
+
+def create_group(group: EndpointGroup) -> EndpointGroup:
+    """Create a new endpoint group."""
+    # Convert the model to a dict with enum values as their primitive values
+    payload = group.model_dump(mode='json')
+    response = requests.post(f"{API_BASE_URL}/groups", json=payload)
+    response.raise_for_status()
+    return EndpointGroup.model_validate(response.json())
+
+def update_group(group_id: int, updated_group: EndpointGroup) -> EndpointGroup:
+    """Update an existing endpoint group."""
+    # Convert the model to a dict with enum values as their primitive values
+    payload = updated_group.model_dump(mode='json')
+    response = requests.put(f"{API_BASE_URL}/groups/{group_id}", json=payload)
+    response.raise_for_status()
+    return EndpointGroup.model_validate(response.json())
+
+def delete_group(group_id: int) -> None:
+    """Delete an endpoint group."""
+    response = requests.delete(f"{API_BASE_URL}/groups/{group_id}")
+    response.raise_for_status()
+
+def start_announcement(text: str, group_id: int) -> Dict[str, Any]:
+    """
+    Start a new announcement.
+    
+    Args:
+        text: The text content of the announcement
+        group_id: The ID of the endpoint group to send the announcement to
+        
+    Returns:
+        Dictionary with status information
+    """
+    response = requests.post(f"{API_BASE_URL}/announcement", params={"text": text, "group_id": group_id})
+    response.raise_for_status()
+    return response.json()
+
+def get_group_state(group_id: int) -> Tuple[str, float]:
+    """
+    Get the status of the current announcement for a specific group.
+    
+    Args:
+        group_id: The ID of the group to check the announcement status for
+        
+    Returns:
+        Tuple containing (state_name, state_value)
+    """
+    response = requests.get(f"{API_BASE_URL}/groups/{group_id}/state")
+    response.raise_for_status()
+    state_data = response.json()
+    return (state_data["name"], state_data["value"])
+
+
+def get_available_endpoints() -> List[Endpoint]:
+    """Get all available endpoints."""
+    response = requests.get(f"{API_BASE_URL}/endpoints")
+    response.raise_for_status()
+    endpoints_dict = response.json()
+    # API returns a dictionary with endpoint IDs as keys
+    # Convert this to a list of Endpoint objects
+    return [Endpoint.model_validate(endpoint_data) for endpoint_id, endpoint_data in endpoints_dict.items()]
+
+def get_available_languages() -> List[str]:
+    """Get all available languages for announcements."""
+    response = requests.get(f"{API_BASE_URL}/languages")
+    response.raise_for_status()
+    return response.json()

src/multilang_translator/translator_config.py

@@ -0,0 +1,20 @@
+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/multilang_translator/translator_models/__init__.py

@@ -0,0 +1 @@
+# Empty file to make the directory a package

src/multilang_translator/translator_models/translator_models.py

@@ -0,0 +1,58 @@
+"""
+Models for the translator API.
+Similar to the models used in auracaster-webui but simplified for the translator middleware.
+"""
+from enum import Enum
+from typing import List, Optional
+from pydantic import BaseModel
+
+
+class AnnouncementStates(Enum):
+    IDLE = 0
+    INIT = 0.1
+    TRANSLATING = 0.2
+    GENERATING_VOICE = 0.4
+    ROUTING = 0.6
+    BROADCASTING = 0.8
+    COMPLETED = 1
+    ERROR = 0
+
+
+class Endpoint(BaseModel):
+    """Defines an endpoint with its URL and capabilities."""
+    id: int
+    name: str
+    url: str
+    max_broadcasts: int = 1  # Maximum number of simultaneous broadcasts
+
+class TranslatorLangConfig(BaseModel):
+    translator_llm: str = 'llama3.2:3b-instruct-q4_0'
+    
+    llm_client: str = 'openwebui'  # remote (homserver)
+    llm_host_url: str = 'https://ollama.pstruebi.xyz'
+    llm_host_token: str = 'sk-17124cb84df14cc6ab2d9e17d0724d13'
+    # llm_client: str = 'ollama' #local
+    # 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')
+
+
+class EndpointGroup(BaseModel):
+    id: int
+    name: str
+    languages: List[str]
+    endpoints: List[Endpoint]
+    sampling_rate_hz: int = 16000
+    translator_config: TranslatorConfig = TranslatorConfig()
+    current_state: AnnouncementStates = AnnouncementStates.IDLE
+    anouncement_start_time: float = 0.0

src/multilang_translator/translator_server/__init__.py

@@ -0,0 +1 @@
+# Empty file to make the directory a package

src/multilang_translator/translator_server/endpoints_db.py

@@ -0,0 +1,143 @@
+"""
+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
+
+
+SUPPORTED_LANGUAGES = ["deu", "eng", "fra", "spa", "ita"]
+
+# Database of endpoints
+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",
+        max_broadcasts=3,
+    ),
+    1: Endpoint(
+        id=1,
+        name="Gate 1",
+        url="http://pi3:5000",
+        max_broadcasts=3,
+    ),
+    2: Endpoint(
+        id=2,
+        name="Gate 2",
+        url="http://192.168.1.102:5000",
+        max_broadcasts=3,
+    ),
+}
+
+# Database of endpoint groups with default endpoints
+ENDPOINT_GROUPS: dict[int:EndpointGroup] = { # for now make sure , .id and key are the same
+    0: EndpointGroup(
+        id=0,
+        name="Local Group",
+        languages=["deu", "eng"],
+        endpoints=[ENDPOINTS[0]],
+    ),
+    1: EndpointGroup(
+        id=1,
+        name="Gate1",
+        languages=["deu", "fra"],
+        endpoints=[ENDPOINTS[1]],
+    )
+}
+
+def get_available_languages() -> List[str]:
+    """Get a list of all supported languages."""
+    return SUPPORTED_LANGUAGES
+
+# Endpoint functions
+def get_all_endpoints() -> List[Endpoint]:
+    """Get all active endpoints."""
+    return ENDPOINTS
+
+def get_endpoint_by_id(endpoint_id: str) -> Optional[Endpoint]:
+    """Get an endpoint by its ID."""
+    return ENDPOINTS[endpoint_id]
+
+
+def add_endpoint(endpoint: Endpoint) -> Endpoint:
+    """Add a new endpoint to the database."""
+    if endpoint.id in ENDPOINTS:
+        raise ValueError(f"Endpoint with ID {endpoint.id} already exists")
+    ENDPOINTS[endpoint.id] = endpoint
+    return endpoint
+
+
+def update_endpoint(endpoint_id: str, updated_endpoint: Endpoint) -> Endpoint:
+    """Update an existing endpoint in the database."""
+    if endpoint_id not in ENDPOINTS:
+        raise ValueError(f"Endpoint {endpoint_id} not found")
+    
+    # Ensure the ID is preserved
+    updated_endpoint.id = endpoint_id
+    ENDPOINTS[endpoint_id] = updated_endpoint
+    return updated_endpoint
+
+
+def delete_endpoint(endpoint_id: str) -> None:
+    """Delete an endpoint from the database."""
+    if endpoint_id not in ENDPOINTS:
+        raise ValueError(f"Endpoint {endpoint_id} not found")
+    
+    # Check if this endpoint is used in any groups
+    for group in ENDPOINT_GROUPS.values():
+        if endpoint_id in group.endpoints:
+            raise ValueError(f"Cannot delete endpoint {endpoint_id}, it is used in group {group.id}")
+    
+    del ENDPOINTS[endpoint_id]
+
+
+# Endpoint Group functions
+def get_all_groups() -> List[EndpointGroup]:
+    """Get all endpoint groups."""
+    return list(ENDPOINT_GROUPS.values())
+
+
+def get_group_by_id(group_id: int) -> Optional[EndpointGroup]:
+    """Get an endpoint group by its ID."""
+    return ENDPOINT_GROUPS.get(group_id)
+
+
+def add_group(group: EndpointGroup) -> EndpointGroup:
+    """Add a new endpoint group to the database."""
+    if group.id in ENDPOINT_GROUPS:
+        raise ValueError(f"Group with ID {group.id} already exists")
+    
+    # Validate that all referenced endpoints exist
+    for endpoint_id in group.endpoints:
+        if endpoint_id not in ENDPOINTS:
+            raise ValueError(f"Endpoint {endpoint_id} not found")
+    
+    ENDPOINT_GROUPS[group.id] = group
+    return group
+
+
+def update_group(group_id: int, updated_group: EndpointGroup) -> EndpointGroup:
+    """Update an existing endpoint group in the database."""
+    if group_id not in ENDPOINT_GROUPS:
+        raise ValueError(f"Group {group_id} not found")
+
+    # Validate that all referenced endpoints exist
+    for endpoint in updated_group.endpoints:
+        if endpoint.id not in ENDPOINTS.keys():
+            raise ValueError(f"Endpoint with id {endpoint.id} not found")
+
+    # Ensure the ID is preserved
+    updated_group.id = group_id
+    ENDPOINT_GROUPS[group_id] = updated_group
+    return updated_group
+
+
+def delete_group(group_id: int) -> None:
+    """Delete an endpoint group from the database."""
+    if group_id not in ENDPOINT_GROUPS:
+        raise ValueError(f"Group {group_id} not found")
+    
+    del ENDPOINT_GROUPS[group_id]
+
+

src/multilang_translator/translator_server/main_translator_api.py

@@ -0,0 +1,28 @@
+"""
+Entry point for the Translator API server.
+This file starts the FastAPI server with the translator_server.
+"""
+import uvicorn
+import logging as log
+import sys
+import os
+
+# Add the parent directory to the Python path to find the multilang_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:
+    sys.path.insert(0, parent_dir)
+
+if __name__ == "__main__":
+    log.basicConfig(
+        level=log.INFO,
+        format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
+    )
+    log.info("Starting Translator API server")
+    uvicorn.run(
+        "multilang_translator.translator_server.translator_server:app",
+        host="0.0.0.0",
+        port=7999,
+        reload=True,
+        log_level="debug"
+    )

src/multilang_translator/translator_server/translator_server.py

@@ -0,0 +1,346 @@
+"""
+FastAPI implementation of the Multilang Translator API.
+This API mimics the mock_api from auracaster-webui to allow integration.
+"""
+import time
+import logging as log
+import asyncio
+import random
+
+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 multilang_translator.translator import llm_translator
+from multilang_translator.translator_server import endpoints_db
+from voice_provider import text_to_speech
+
+# Import the endpoints database and multicast client
+from auracast import multicast_client, auracast_config
+
+# Create FastAPI app
+app = FastAPI()
+
+# Add CORS middleware to allow cross-origin requests
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Endpoint configuration cache
+CURRENT_ENDPOINT_CONFIG = {}
+
+async def init_endpoint(endpoint: Endpoint, languages: list[str], sampling_rate_hz: int):
+    """Initialize a specific endpoint for multicast."""
+
+    current_config = CURRENT_ENDPOINT_CONFIG.get(endpoint.id)
+
+    if current_config is not None:
+        current_langs = [big.language for big in current_config.bigs]
+        # if languages are unchanged and the caster client status is initiailized, skip init
+        if current_langs == languages:
+            # Get status asynchronously
+            status = await multicast_client.get_status(base_url=endpoint.url)
+            if status['is_initialized']:
+                log.info('Endpoint %s was already initialized', endpoint.name)
+                return
+
+    log.info(f"Initializing endpoint: {endpoint.name} at {endpoint.url}")
+    # Load a default config
+    config = auracast_config.AuracastConfigGroup(
+        bigs=[getattr(auracast_config, f"AuracastBigConfig{lang.capitalize()}")()
+              for lang in languages]
+    )
+
+    # overwrite some default configs
+    config.transport = 'auto'
+    config.auracast_device_address = ':'.join(f"{random.randint(0, 255):02X}" for _ in range(6))
+    config.auracast_sampling_rate_hz = sampling_rate_hz
+
+    # Configure the bigs
+    for big in config.bigs:
+        big.loop = False
+        big.name = endpoint.name
+        big.random_address = ':'.join(f"{random.randint(0, 255):02X}" for _ in range(6))
+        big.id = random.randint(0, 2**16) #TODO: how many bits is this ?
+        #big.program_info = big.program_info + ' ' + endpoint.name
+
+    # make async init request
+    ret = await multicast_client.init(config, base_url=endpoint.url)
+    # if ret != 200: # TODO: this is not working, should probably be handled async
+    #     log.error('Init of endpoint %s was unsucessfull', endpoint.name)
+    #     raise Exception(f"Init was of endpoint {endpoint.name} was unsucessfull")
+    CURRENT_ENDPOINT_CONFIG[endpoint.id] = config.model_copy()
+    log.info(f"Endpoint {endpoint.name} initialized successfully")
+   #else:
+     #   log.info('Endpoint %s was already initialized', endpoint.name)
+
+
+async def make_announcement(text: str, ep_group: EndpointGroup):
+    """
+    Make an announcement to a group of endpoints.
+    """
+
+    if text == "":
+        log.warning("Announcement text is empty")
+        return {"error": "Announcement text is empty"}
+
+    ep_group.current_state = AnnouncementStates.IDLE
+    ep_group.anouncement_start_time = time.time()
+    # update the database with the new state and start time so this can be read by another process
+    endpoints_db.update_group(ep_group.id, ep_group)
+
+    # Initialize all endpoints in the group concurrently
+    ep_group.current_state = AnnouncementStates.INIT
+    endpoints_db.update_group(ep_group.id, ep_group)
+    
+    # Create init tasks and run them concurrently
+    init_tasks = [
+        init_endpoint(endpoint, ep_group.languages, ep_group.sampling_rate_hz)
+        for endpoint in ep_group.endpoints
+    ]
+
+    # make sure init finished
+    await asyncio.gather(*init_tasks)
+
+    # Translate the text for each language (concurrently)
+    base_lang = "deu"  # German is the base language
+    target_langs = ep_group.languages.copy()
+    if base_lang in target_langs:
+        target_langs.remove(base_lang)
+
+    ep_group.current_state = AnnouncementStates.TRANSLATING
+    endpoints_db.update_group(ep_group.id, ep_group)
+
+    # Create translation tasks
+    translations = {base_lang: text}
+    translation_tasks = []
+    
+    for lang in target_langs:
+            # Prepare translation task
+            trans_conf = getattr(ep_group.translator_config, lang)
+            task = llm_translator.translate_de_to_x_async(
+                text=text,
+                target_language=lang,
+                client=trans_conf.llm_client,
+                model=trans_conf.translator_llm,
+                host=trans_conf.llm_host_url,
+                token=trans_conf.llm_host_token
+            )
+            translation_tasks.append(task)
+    
+    # Wait for all translations to complete concurrently
+    results = await asyncio.gather(*translation_tasks)
+    for i, translation in enumerate(results):
+        lang = target_langs[i]
+        translations[lang] = translation
+        log.info(f"Translated to {lang}: {translation}")
+
+    # Generate voices concurrently
+    ep_group.current_state = AnnouncementStates.GENERATING_VOICE
+    endpoints_db.update_group(ep_group.id, ep_group)
+
+    # Prepare synthesis tasks and run them concurrently
+    synth_langs = ep_group.languages
+    synthesis_tasks = []
+    for lang in synth_langs:
+        trans_conf = getattr(ep_group.translator_config, lang)
+        task = text_to_speech.synthesize_async(
+            translations[lang],
+            ep_group.sampling_rate_hz,
+            trans_conf.tts_system,
+            trans_conf.tts_model,
+            return_lc3=True
+        )
+        synthesis_tasks.append(task)
+    
+    # Wait for all synthesis tasks to complete concurrently
+    audio = {}
+    if synthesis_tasks:
+        results = await asyncio.gather(*synthesis_tasks)
+        for i, audio_data in enumerate(results):
+            audio[synth_langs[i]] = audio_data
+
+    # Start the monitoring coroutine to wait for streaming to complete
+    # This will set the state to COMPLETED when finished
+    asyncio.create_task(monitor_streaming_completion(ep_group))
+
+    # Broadcast to all endpoints in group concurrently
+    broadcast_tasks = []
+    for endpoint in ep_group.endpoints:
+        log.info(f"Broadcasting to {endpoint.name} for languages: {', '.join(audio.keys())}")
+        task = multicast_client.send_audio(audio, base_url=endpoint.url)
+        broadcast_tasks.append(task)
+    
+    # Wait for all broadcasts to complete
+    await asyncio.gather(*broadcast_tasks)
+
+    # Return the translations
+    return {"translations": translations}
+
+
+async def monitor_streaming_completion(ep_group: EndpointGroup):
+    """
+    Monitor streaming status after audio is sent and update group state when complete.
+
+    Args:
+        ep_group: The endpoint group being monitored
+    """
+    log.info(f"Starting streaming completion monitoring for endpoint group {ep_group.id}")
+
+
+    # Set a shorter timeout as requested
+    max_completion_time = 60  # seconds
+
+    # First check if we are actually in streaming state
+    streaming_started = False
+    initial_check_timeout = 10  # seconds
+    initial_check_start = time.time()
+
+    # Wait for streaming to start (with timeout)
+    while time.time() - initial_check_start < initial_check_timeout:
+        # Wait before checking again
+        await asyncio.sleep(1)
+
+        any_streaming = False
+        for endpoint in ep_group.endpoints:
+            status = await multicast_client.get_status(base_url=endpoint.url)
+            if status.get("is_streaming", False):
+                any_streaming = True
+                log.info(f"Streaming confirmed started on endpoint {endpoint.name}")
+                break
+
+        if any_streaming:
+            streaming_started = True
+            break
+
+    if not streaming_started:
+        log.warning(f"No endpoints started streaming for group {ep_group.id} after {initial_check_timeout}s")
+        # Still update to completed since there's nothing to wait for
+        ep_group.current_state = AnnouncementStates.ERROR
+        endpoints_db.update_group(ep_group.id, ep_group)
+        return
+
+    # Update group progress
+    ep_group.current_state = AnnouncementStates.BROADCASTING
+    endpoints_db.update_group(ep_group.id, ep_group)
+
+    # Now monitor until streaming completes on all endpoints
+    check_completion_start_time = time.time()
+    completed = [False for _ in ep_group.endpoints]
+    while not all(completed) or time.time() - check_completion_start_time > max_completion_time:
+        await asyncio.sleep(1)
+
+        # Check status of each endpoint
+        for i, endpoint in enumerate(ep_group.endpoints):
+            status = await multicast_client.get_status(base_url=endpoint.url)
+            completed[i] = not status['is_streaming']
+
+    if all(completed):
+        log.info(f"All endpoints completed streaming for group {ep_group.id}")
+        # Update group state to completed
+        ep_group.current_state = AnnouncementStates.COMPLETED
+        endpoints_db.update_group(ep_group.id, ep_group)
+        log.info(f"Updated group {ep_group.id} state to COMPLETED")
+
+    else:
+        log.error(f"Max wait time reached for group {ep_group.id}. Forcing completion.")
+
+
+@app.get("/groups")
+async def get_groups():
+    """Get all endpoint groups with their current status."""
+    return endpoints_db.get_all_groups()
+
+
+@app.post("/groups")
+async def create_group(group: endpoints_db.EndpointGroup):
+    """Add a new endpoint group."""
+    try:
+        return endpoints_db.add_group(group)
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+@app.get("/groups/{group_id}/state") # TODO: think about progress tracking
+async def get_group_state(group_id: int):
+    """Get the status of a specific endpoint."""
+    # Check if the endpoint exists
+    ep_group = endpoints_db.get_group_by_id(group_id)
+    if not ep_group:
+        raise HTTPException(status_code=404, detail=f"Endpoint {group_id} not found")
+
+    return {"name": ep_group.current_state.name, "value": ep_group.current_state.value}
+
+
+@app.put("/groups/{group_id}")
+async def update_group(group_id: int, updated_group: endpoints_db.EndpointGroup):
+    """Update an existing endpoint group."""
+    try:
+        return endpoints_db.update_group(group_id, updated_group)
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@app.delete("/groups/{group_id}")
+async def delete_group(group_id: int):
+    """Delete an endpoint group."""
+    try:
+        endpoints_db.delete_group(group_id)
+        return {"message": f"Group {group_id} deleted successfully"}
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@app.post("/announcement")
+async def start_announcement(text: str, group_id: int):
+    """Start a new announcement to the specified endpoint group."""
+    global announcement_task
+
+    # Get the group from active groups or database
+    group = endpoints_db.get_group_by_id(group_id)
+    if not group:
+        raise HTTPException(status_code=400, detail=f"Group {group_id} not found")
+
+    # Check if we're already processing an announcement
+    #if announcement_task and not announcement_task.done():
+    #    raise HTTPException(status_code=400, detail="Already processing an announcement")
+
+    # Start the announcement task
+    announcement_task = asyncio.create_task(make_announcement(text, group))
+    return {"status": "Announcement started", "group_id": group_id}
+
+
+
+@app.get("/endpoints")
+async def get_available_endpoints():
+    """Get all available endpoints with their capabilities."""
+    return endpoints_db.get_all_endpoints()
+
+
+@app.get("/languages")
+async def get_available_languages():
+    """Get all available languages for announcements."""
+    return endpoints_db.get_available_languages()
+
+
+
+if __name__ == "__main__":
+    import uvicorn
+    log.basicConfig(
+        level=log.DEBUG,
+        format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
+    )
+    # with reload=True logging of modules does not function as expected
+    uvicorn.run(
+        app,
+        #'translator_server:app',
+        host="0.0.0.0",
+        port=7999,
+        #reload=True,
+        #log_config=None,
+        #log_level="info"
+        )

src/voice_client/tts_client.py

@@ -0,0 +1,44 @@
+import requests
+import numpy as np
+import soundfile as sf
+
+from voice_models.request_models import SynthesizeRequest
+
+
+API_URL = "http://127.0.0.1:8099/synthesize/"
+
+def request_synthesis(request_data: SynthesizeRequest):
+    response = requests.post(API_URL, json=request_data.model_dump())
+
+    if response.status_code == 200:
+        response_data = response.json()
+        
+        if request_data.return_lc3:
+            # Save LC3 audio as binary file
+            lc3_bytes = bytes.fromhex(response_data["audio_lc3"])
+            return lc3_bytes
+        
+        else:
+            # Convert hex-encoded PCM bytes back to numpy array and save as WAV
+            audio_bytes = bytes.fromhex(response_data["audio_pcm"])
+            audio_array = np.frombuffer(audio_bytes, dtype=np.float32)
+            return audio_array
+    
+    else:
+        print(f"Error: {response.status_code}, {response.text}")
+
+if __name__ == "__main__":
+
+    target_rate=16000
+
+    # Example request
+    request_data = SynthesizeRequest(
+        text="Hello, this is a test.",
+        target_sample_rate=target_rate,
+        framework="piper",
+        model="de_DE-kerstin-low",
+        return_lc3=False  # Set to True to receive LC3 compressed output
+    )
+
+    audio = request_synthesis(request_data)
+    sf.write('hello.wav', audio, target_rate)

src/voice_models/request_models.py

@@ -0,0 +1,9 @@
+from pydantic import BaseModel
+
+class SynthesizeRequest(BaseModel):
+    text: str
+    target_sample_rate: int = 16000
+    framework: str = "piper"
+    model: str = "en_US-lessac-medium"
+    return_lc3: bool = False
+

src/voice_provider/text_to_speech.py

@@ -1,27 +1,34 @@
 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
+import asyncio
+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
@@ -34,14 +41,19 @@ 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
 
 
-# TODO: framework should probably be a dataclass that holds all the relevant informations, also model
-def synthesize(text, target_sample_rate, framework, model="en_US-lessac-medium", return_lc3=True):
+def synthesize(
+        text, 
+        target_sample_rate, 
+        framework, 
+        model="en_US-lessac-medium", 
+        return_lc3=True
+        ):
 
     if framework == 'piper':
         model_json, audio_raw = synth_piper(text, model)
@@ -59,12 +71,41 @@ 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
 
 
+async def synthesize_async(
+        text, 
+        target_sample_rate, 
+        framework, 
+        model="en_US-lessac-medium", 
+        return_lc3=True
+        ):
+    """
+    Asynchronous version of the synthesize function that runs in a thread pool.
+    
+    Args:
+        text: Text to synthesize
+        target_sample_rate: Target sample rate for the audio
+        framework: TTS framework to use (e.g., 'piper')
+        model: Model to use for synthesis
+        return_lc3: Whether to return LC3-encoded audio
+        
+    Returns:
+        LC3-encoded audio as string or raw audio as numpy array
+    """
+    # Run the CPU-intensive synthesis in a thread pool
+    loop = asyncio.get_event_loop()
+    result = await loop.run_in_executor(
+        None,
+        lambda: synthesize(text, target_sample_rate, framework, model, return_lc3)
+    )
+    return result
+
+
 if __name__ == '__main__':
     import logging
     import soundfile as sf
@@ -79,5 +120,4 @@ if __name__ == '__main__':
 
     sf.write('hello.wav', audio, target_rate)
 
-    # TODO: "WARNING:piper.download:Wrong size (expected=5952, actual=4158
     print('Done.')

src/voice_provider/tts_server.py

@@ -0,0 +1,43 @@
+from fastapi import FastAPI, HTTPException
+import numpy as np
+
+from voice_models.request_models import SynthesizeRequest
+from voice_provider.text_to_speech import synthesize_async
+
+app = FastAPI()
+
+HOST_PORT = 8099
+
+
+@app.post("/synthesize/")
+async def synthesize_speech(request: SynthesizeRequest):
+    try:
+        audio = await synthesize_async(
+            text=request.text,
+            target_sample_rate=request.target_sample_rate,
+            framework=request.framework,
+            model=request.model,
+            return_lc3=request.return_lc3
+        )
+
+        if request.return_lc3:
+            # If it's already a string (LC3 data), convert it to bytes for hex encoding
+            if isinstance(audio, str):
+                audio_bytes = audio.encode('latin-1')
+                return {"audio_lc3": audio_bytes.hex()}
+            # If it's already bytes
+            elif isinstance(audio, bytes):
+                return {"audio_lc3": audio.hex()}
+            else:
+                raise ValueError(f"Unexpected audio type: {type(audio)}")
+        else:
+            # If it's numpy array (non-LC3), convert to bytes
+            audio_bytes = audio.astype(np.float32).tobytes()
+            return {"audio_pcm": audio_bytes.hex()}
+        
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="127.0.0.1", port=HOST_PORT)

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,

tests/get_group_state.py

@@ -0,0 +1,9 @@
+import requests
+import time
+
+if __name__ == '__main__':
+    # get the group state every 0.5s 
+    while True:
+        response = requests.get('http://localhost:7999/groups/0/state')
+        print(response.json())
+        time.sleep(0.5)