auracaster/auracast-translator
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use_bumble (#1)

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Adapt the project to use the bumble auracaster

Reviewed-on: https://gitea.pstruebi.xyz/auracaster/multilang-translator-local/pulls/1
This commit was merged in pull request #1.
This commit is contained in:
pstruebi
2025-02-25 13:32:37 +01:00
parent 56b942ce39
commit a9acfd2d2c
15 changed files with 219 additions and 275 deletions
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multilang_translator/translator/llm_translator.py
+29 -30
View File
@@ -1,10 +1,18 @@
import time
import requests
import json
import logging as log
import time
import ollama
from . import credentials
from . import syspromts
from multilang_translator.translator import credentials
from multilang_translator.translator import syspromts
from multilang_translator.translator import test_content
# ollama.create( # TODO: create models on startup
# model='example',
# from_='llama3.2', system="You are Mario from Super Mario Bros."
# )
def query_model(model, query):
url = f'{credentials.BASE_URL}/api/chat/completions'
@@ -21,42 +29,33 @@ def query_model(model, query):
return response.json()
def translate_de_to_x(target_language: str, text:str, model ='llama3.2:3b-instruct-q4_0'):
def translate_de_to_x(text:str, target_language: str, model='llama3.2:3b-instruct-q4_0'): # remember to use instruct models
start=time.time()
s = getattr(syspromts, f"TRANSLATOR_DE_{target_language.upper()}")
return query_model(model, s + text)['choices'][0]['message']['content']
def translator_de_en(query):
MODEL = 'llama3.2:3b-instruct-q4_0'
#MODEL = 'llama3.1:8b-instruct-q4_0'
return query_model(MODEL, syspromts.TRANSLATOR_DE_EN + query)['choices'][0]['message']['content']
def translator_de_fr(query):
MODEL = 'llama3.2:3b-instruct-q4_0'
return query_model(MODEL, syspromts.TRANSLATOR_DE_FR + query)['choices'][0]['message']['content']
def translator_de_es(query):
MODEL = 'llama3.2:3b-instruct-q4_0'
return query_model(MODEL, syspromts.TRANSLATOR_DE_ES + query)['choices'][0]['message']['content']
def translator_de_it(query):
MODEL = 'llama3.2:3b-instruct-q4_0'
return query_model(MODEL, syspromts.TRANSLATOR_DE_IT + query)['choices'][0]['message']['content']
response = ollama.chat(
model = model,
messages = [
{'role': 'system', 'content': s},
{'role': 'user', 'content': text}
],
)
log.info('Running the translator to %s took %s s', target_language, round(time.time() - start, 3))
return response['message']['content']
if __name__ == "__main__":
import time
TESTSENTENCE_DE_BROKER = 'Ein Broker (oder Makler) ist eine Person oder ein Unternehmen, das sich zwischen dem Kauf- und Verkaufsberechtigten einer Wirtschaftsgüter (z.B. Aktien, Optionen, Derivate, Währungen, Rohstoffe usw.) stellt und als Vermittler fungiert. Sein Hauptziel ist es, Transaktionen zu erleichtern und Geld für sich selbst zu verdienen.'
start=time.time()
response = translator_de_en(TESTSENTENCE_DE_BROKER)
print("First query took", start - time.time())
print(json.dumps(response, indent=2))
response = translate_de_to_x('Der Zug ist da.', target_language='en', model='llama3.2:1b-instruct-q4_0')
print("Query took", time.time() - start)
print(response)
start=time.time()
response = translator_de_fr(TESTSENTENCE_DE_BROKER)
print("Second query took", start - time.time())
response = translate_de_to_x(test_content.TESTSENTENCE_DE_RAINBOW, target_language='en')
print("query took", time.time() - start)
print(response)
start=time.time()
response = translate_de_to_x(test_content.TESTSENTENCE_DE_RAINBOW, target_language='fr')
print("query took", time.time() - start)
print(response)