restructure the project
This commit is contained in:
@@ -0,0 +1,20 @@
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import subprocess
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import logging as log
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def encode_lc3(file, frame_dur_ms=10, bps=48000):
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file = file.replace('.wav', '')
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cmd = ['elc3', '-m', f'{frame_dur_ms}' , '-b', f'{bps}', f'{file}.wav', f'{file}.lc3']
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log.info("Executing: %s", " ".join(cmd))
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ret = subprocess.run(cmd, check=True)
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return ret.returncode, ret.stdout, ret.stderr
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if __name__ == '__main__':
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import os
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os.chdir(os.path.dirname(__file__))
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r, stdout, stderr = encode_lc3('welcome_resampled.wav')
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print(r)
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print(stdout)
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print(stderr)
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@@ -0,0 +1,137 @@
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# -*- coding: utf-8 -*-
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"""
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list prompt example
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"""
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from __future__ import print_function, unicode_literals
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from typing import List
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from dataclasses import asdict
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import asyncio
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import time
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import logging as log
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import aioconsole
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from auracast import multicast_control
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from auracast import auracast_config
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import multilang_translator.translator_config as translator_config
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from translator import llm_translator
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from translator.test_content import TESTSENTENCE
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from voice_provider import text_to_speech
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# TODO: look for a end to end translation solution
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def transcribe():
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pass # TODO: Implement transcribing input audio e.g. with whisper
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async def announcement_from_german_text(
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global_config: auracast_config.AuracastGlobalConfig,
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translator_config: List[translator_config.TranslatorConfigDe],
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caster: multicast_control.Multicaster,
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text_de
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):
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base_lang = "deu"
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for i, trans in enumerate(translator_config):
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if trans.big.language == base_lang:
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text = text_de
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else:
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text = llm_translator.translate_de_to_x(
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text_de,
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trans.big.language,
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model=trans.translator_llm,
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client = trans.llm_client,
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host=trans.llm_host_url,
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token=trans.llm_host_token
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)
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log.info('%s', text)
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lc3_audio = text_to_speech.synthesize(
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text,
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global_config.auracast_sampling_rate_hz,
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trans.tts_system,
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trans.tts_model,
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return_lc3=True
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)
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caster.big_conf[i].audio_source = lc3_audio
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start = time.time()
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caster.start_streaming()
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log.info("Starting all broadcasts took %s s", round(time.time() - start, 3))
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async def command_line_ui(global_conf, translator_conf, caster: multicast_control.Multicaster):
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while True:
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# make a list of all available testsentence
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sentence_list = list(asdict(TESTSENTENCE).values())
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prompt = "Enter your Announcement|quit or choose:] > \n"
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prompt += "\n".join([f"{i}: {s}" for i,s in enumerate(sentence_list)])
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prompt += "\n"
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command = await aioconsole.ainput(prompt)
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if command.strip().lower() == "quit":
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print("👋 Exiting...")
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if caster.device:
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caster.stop_streaming()
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await caster.shutdown()
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break # Exit loop
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elif command.strip() == '':
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print('Nothing to Announce')
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# Check if command is a single number
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elif command.strip().isdigit():
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ind = int(command.strip())
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await announcement_from_german_text(
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global_conf,
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translator_conf,
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caster,
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sentence_list[ind])
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await asyncio.wait([caster.streamer.task])
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# Interpret the command as announcement
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else:
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await announcement_from_german_text(caster, command)
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await asyncio.wait([caster.streamer.task])
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async def main():
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log.basicConfig(
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level=log.INFO,
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format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s'
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)
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global_conf = auracast_config.AuracastGlobalConfig()
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#global_conf.transport='serial:/dev/serial/by-id/usb-SEGGER_J-Link_001057705357-if02,1000000,rtscts' # transport for nrf54l15dk
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global_conf.transport='serial:/dev/serial/by-id/usb-ZEPHYR_Zephyr_HCI_UART_sample_81BD14B8D71B5662-if00,115200,rtscts' #nrf52dongle hci_uart usb cdc
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translator_conf = [
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translator_config.TranslatorConfigDe(),
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translator_config.TranslatorConfigEn(),
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translator_config.TranslatorConfigFr(),
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#auracast_config.broadcast_es,
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#auracast_config.broadcast_it,
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]
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for conf in translator_conf:
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conf.big.loop = False
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conf.llm_client = 'openwebui' # comment out for local llm
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conf.llm_host_url = 'https://ollama.pstruebi.xyz'
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conf.llm_host_token = 'sk-17124cb84df14cc6ab2d9e17d0724d13'
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caster = multicast_control.Multicaster(global_conf, [conf.big for conf in translator_conf])
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await caster.init_broadcast()
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# await announcement_from_german_text(
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# global_conf,
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# translator_conf,
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# caster,
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# test_content.TESTSENTENCE.DE_HELLO
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# )
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# await asyncio.wait([caster.streamer.task])
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await command_line_ui(global_conf, translator_conf, caster)
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if __name__ == '__main__':
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asyncio.run(main())
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# TODO: add support for multiple radios
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@@ -0,0 +1,91 @@
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import time
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import requests
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import json
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import logging as log
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import time
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import ollama
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from multilang_translator.translator import syspromts
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# ollama.create( # TODO: create models on startup
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# model='example',
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# from_='llama3.2', system="You are Mario from Super Mario Bros."
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# )
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async def chat():
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message = {'role': 'user', 'content': 'Why is the sky blue?'}
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response = await ollama.AsyncClient().chat(model='llama3.2', messages=[message])
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def query_openwebui(model, system, query, url, token):
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url = f'{url}/api/chat/completions'
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headers = {
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'Authorization': f'Bearer {token}',
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}
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payload = {
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'model': model,
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'messages': [
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{'role': 'system', 'content': system},
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{'role': 'user', 'content': query}
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],
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}
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start = time.time()
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response = requests.post(url, headers=headers, json=payload)
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log.info("Translating the text took %s s", round(time.time() - start, 2))
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return response.json()['choices'][0]['message']['content']
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def query_ollama(model, system, query, host='http://localhost:11434'):
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client = ollama.Client(
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host=host,
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)
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response = client.chat(
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model = model,
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messages = [
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{'role': 'system', 'content': system},
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{'role': 'user', 'content': query}
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],
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)
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return response.message.content
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def translate_de_to_x( # TODO: use async ollama client later - implenent a translate async function
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text:str,
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target_language: str,
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client='ollama',
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model='llama3.2:3b-instruct-q4_0', # remember to use instruct models
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host = None,
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token = None
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):
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start=time.time()
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s = getattr(syspromts, f"TRANSLATOR_DEU_{target_language.upper()}")
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if client == 'ollama':
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response = query_ollama(model, s, text, host=host)
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elif client == 'openwebui':
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response = query_openwebui(model, s, text, url=host, token=token)
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else: raise NotImplementedError('llm client not implemented')
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log.info('Running the translator to %s took %s s', target_language, round(time.time() - start, 3))
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return response
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if __name__ == "__main__":
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import time
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from multilang_translator.translator import test_content
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start=time.time()
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response = translate_de_to_x('Der Zug ist da.', target_language='en', model='llama3.2:1b-instruct-q4_0')
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print("Query took", time.time() - start)
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print(response)
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start=time.time()
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response = translate_de_to_x(test_content.TESTSENTENCE_DE_RAINBOW, target_language='en')
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print("query took", time.time() - start)
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print(response)
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start=time.time()
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response = translate_de_to_x(test_content.TESTSENTENCE_DE_RAINBOW, target_language='fr')
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print("query took", time.time() - start)
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print(response)
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@@ -0,0 +1,6 @@
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# TODO: make this more elegant. this can probably be generated and the base lang be assumed by the llm?
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TRANSLATOR_DEU_ENG = 'Du bist ein Übersetzer. Übersetze die folgende Satz aus dem Deutschen ins Englische. Antworte nur mit der übersetzten Satz.\n'
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TRANSLATOR_DEU_FRA = 'Du bist ein Übersetzer. Übersetze die folgende Satz aus dem Deutschen ins Französische. Antworte nur mit der übersetzten Satz.\n'
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TRANSLATOR_DEU_SPA = 'Du bist ein Übersetzer. Übersetze die folgende Satz aus dem Deutschen ins Spanische. Antworte nur mit der übersetzten Satz.\n'
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TRANSLATOR_DEU_ITA = 'Du bist ein Übersetzer. Übersetze die folgende Satz aus dem Deutschen ins Italienische. Antworte nur mit der übersetzten Satz.\n'
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@@ -0,0 +1,10 @@
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from dataclasses import dataclass, fields, asdict
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@dataclass
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class TestContent:
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DE_HELLO: str = 'Hallo Welt.'
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DE_GATE_OPENED: str = "Gate 23 ist jetzt geöffnet."
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DE_TRAIN_ARRIVING: str = "Der Zug Nach Wien fährt heute von Gleis 3."
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DE_SECURITY_CHECKPOINT_OPENING: str = "Sicherheitskontrolle 5 ist jetzt geöffnet. Bitte setzen Sie sich in Bewegung, um Ihre Wartezeit während Sicherheitsüberprüfungen zu minimieren."
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DE_RAINBOW: str = 'Der Regenbogen ist ein atmosphärisch-optisches Phänomen, das als kreisbogenförmiges farbiges Lichtband in einer von der Sonne beschienenen Wolke oder Regenwand wahrgenommen wird und ein großes Farbspektrum anzeigt.'
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TESTSENTENCE = TestContent()
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@@ -0,0 +1,35 @@
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import os
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from pydantic import BaseModel
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from auracast import auracast_config
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VENV_DIR = os.path.join(os.path.dirname(__file__), './../../venv')
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class TranslatorBaseconfig(BaseModel):
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big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigDe()
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translator_llm: str = 'llama3.2:3b-instruct-q4_0'
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llm_client: str = 'ollama'
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llm_host_url: str | None = 'http://localhost:11434'
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llm_host_token: str | None = None
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tts_system: str = 'piper'
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tts_model: str ='de_DE-kerstin-low'
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class TranslatorConfigDe(TranslatorBaseconfig):
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big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigDe()
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tts_model: str ='de_DE-thorsten-high'
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class TranslatorConfigEn(TranslatorBaseconfig):
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big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigEn()
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tts_model: str = 'en_GB-alba-medium'
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class TranslatorConfigFr(TranslatorBaseconfig):
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big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigFr()
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tts_model: str = 'fr_FR-siwis-medium'
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class TranslatorConfigEs(TranslatorBaseconfig):
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big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigEs()
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tts_model: str = 'es_ES-sharvard-medium'
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class TranslatorConfigIt(TranslatorBaseconfig):
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big: auracast_config.AuracastBigConfig = auracast_config.AuracastBigConfigIt()
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tts_model: str = 'it_IT-paola-medium'
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