Spaces:
Sleeping
Sleeping
File size: 18,576 Bytes
5a65ad6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 |
"""
Translation Module
This module provides text translation capabilities using multiple backends
including Google Translate API and local transformer models.
"""
import logging
import time
from typing import Dict, List, Optional, Union, Any
from abc import ABC, abstractmethod
from googletrans import Translator as GoogleTranslator, LANGUAGES
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
from ..config import DEFAULT_TRANSLATION_SERVICE, SUPPORTED_LANGUAGES
class TranslationEngine(ABC):
"""Abstract base class for translation engines."""
@abstractmethod
def translate(self, text: str, source_lang: str, target_lang: str) -> Dict[str, Any]:
"""Translate text from source language to target language."""
pass
@abstractmethod
def detect_language(self, text: str) -> Dict[str, Any]:
"""Detect the language of input text."""
pass
@abstractmethod
def get_supported_languages(self) -> Dict[str, str]:
"""Get supported language codes and names."""
pass
class GoogleTranslateEngine(TranslationEngine):
"""Google Translate API implementation."""
def __init__(self, timeout: int = 10, retries: int = 3):
"""
Initialize Google Translate engine.
Args:
timeout: Request timeout in seconds
retries: Number of retry attempts
"""
self.translator = GoogleTranslator()
self.timeout = timeout
self.retries = retries
self.logger = logging.getLogger(__name__)
def translate(self, text: str, source_lang: str, target_lang: str) -> Dict[str, Any]:
"""
Translate text using Google Translate.
Args:
text: Text to translate
source_lang: Source language code
target_lang: Target language code
Returns:
Dictionary with translation results
"""
if not text.strip():
return {
'text': text,
'translated_text': text,
'source_language': source_lang,
'target_language': target_lang,
'confidence': 1.0,
'engine': 'google'
}
# Validate language codes
self._validate_language_codes(source_lang, target_lang)
for attempt in range(self.retries):
try:
self.logger.debug(f"Translating text (attempt {attempt + 1}): "
f"{source_lang} -> {target_lang}")
# Perform translation
result = self.translator.translate(
text,
src=source_lang,
dest=target_lang
)
# Extract results
translation_result = {
'text': text,
'translated_text': result.text,
'source_language': result.src,
'target_language': target_lang,
'confidence': getattr(result, 'confidence', 0.95),
'engine': 'google',
'extra_data': result.extra_data if hasattr(result, 'extra_data') else {}
}
self.logger.debug(f"Translation successful: '{text}' -> '{result.text}'")
return translation_result
except Exception as e:
self.logger.warning(f"Translation attempt {attempt + 1} failed: {str(e)}")
if attempt == self.retries - 1:
raise RuntimeError(f"Translation failed after {self.retries} attempts: {str(e)}")
time.sleep(1) # Wait before retry
def detect_language(self, text: str) -> Dict[str, Any]:
"""
Detect language using Google Translate.
Args:
text: Text for language detection
Returns:
Dictionary with detection results
"""
if not text.strip():
return {
'language': 'unknown',
'confidence': 0.0,
'engine': 'google'
}
try:
detection = self.translator.detect(text)
return {
'language': detection.lang,
'confidence': detection.confidence,
'engine': 'google',
'text': text
}
except Exception as e:
self.logger.error(f"Language detection failed: {str(e)}")
raise RuntimeError(f"Language detection failed: {str(e)}")
def get_supported_languages(self) -> Dict[str, str]:
"""Get supported languages from Google Translate."""
return LANGUAGES
def _validate_language_codes(self, source_lang: str, target_lang: str) -> None:
"""Validate language codes."""
supported_languages = self.get_supported_languages()
if source_lang not in supported_languages and source_lang != 'auto':
raise ValueError(f"Unsupported source language: {source_lang}")
if target_lang not in supported_languages:
raise ValueError(f"Unsupported target language: {target_lang}")
class LocalTranslationEngine(TranslationEngine):
"""Local transformer model implementation."""
def __init__(self, model_name: Optional[str] = None, device: str = "auto"):
"""
Initialize local translation engine.
Args:
model_name: Hugging Face model name (uses default if None)
device: Device to run model on (auto, cpu, cuda)
"""
self.device = self._setup_device(device)
self.model_name = model_name or "Helsinki-NLP/opus-mt-en-mul"
self.model = None
self.tokenizer = None
self.pipeline = None
self.logger = logging.getLogger(__name__)
# Language mapping for Helsinki models
self.language_mapping = {
'en': 'eng',
'es': 'spa',
'fr': 'fra',
'de': 'deu',
'it': 'ita',
'pt': 'por',
'ru': 'rus'
}
def _setup_device(self, device: str) -> str:
"""Setup device configuration."""
if device == "auto":
return "cuda" if torch.cuda.is_available() else "cpu"
return device
def load_model(self) -> None:
"""Load the translation model."""
try:
self.logger.info(f"Loading translation model: {self.model_name}")
# Load tokenizer and model
self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
self.model = AutoModelForSeq2SeqLM.from_pretrained(self.model_name)
# Move to device
self.model = self.model.to(self.device)
# Create pipeline for easier use
self.pipeline = pipeline(
"translation",
model=self.model,
tokenizer=self.tokenizer,
device=0 if self.device == "cuda" else -1
)
self.logger.info("Translation model loaded successfully")
except Exception as e:
self.logger.error(f"Failed to load translation model: {str(e)}")
raise RuntimeError(f"Model loading failed: {str(e)}")
def translate(self, text: str, source_lang: str, target_lang: str) -> Dict[str, Any]:
"""
Translate text using local model.
Args:
text: Text to translate
source_lang: Source language code
target_lang: Target language code
Returns:
Dictionary with translation results
"""
if self.pipeline is None:
self.load_model()
if not text.strip():
return {
'text': text,
'translated_text': text,
'source_language': source_lang,
'target_language': target_lang,
'confidence': 1.0,
'engine': 'local'
}
try:
# Prepare input for Helsinki models (may need language prefixes)
input_text = self._prepare_input(text, target_lang)
# Perform translation
results = self.pipeline(input_text, max_length=512)
if isinstance(results, list) and len(results) > 0:
translated_text = results[0]['translation_text']
else:
translated_text = results['translation_text']
# Clean up output
translated_text = self._clean_output(translated_text)
return {
'text': text,
'translated_text': translated_text,
'source_language': source_lang,
'target_language': target_lang,
'confidence': 0.85, # Placeholder confidence for local models
'engine': 'local',
'model_name': self.model_name
}
except Exception as e:
self.logger.error(f"Local translation failed: {str(e)}")
raise RuntimeError(f"Local translation failed: {str(e)}")
def _prepare_input(self, text: str, target_lang: str) -> str:
"""Prepare input text for translation (add language prefixes if needed)."""
# For Helsinki models, may need to add target language prefix
if "Helsinki-NLP" in self.model_name:
# Some Helsinki models use language codes as prefixes
mapped_lang = self.language_mapping.get(target_lang, target_lang)
return f">>{mapped_lang}<< {text}"
return text
def _clean_output(self, text: str) -> str:
"""Clean translation output."""
# Remove any language prefixes that might be in output
for lang_code in self.language_mapping.values():
prefix = f">>{lang_code}<< "
if text.startswith(prefix):
text = text[len(prefix):]
return text.strip()
def detect_language(self, text: str) -> Dict[str, Any]:
"""
Detect language (placeholder - local models don't typically do detection).
Args:
text: Text for language detection
Returns:
Dictionary with detection results
"""
# Most local translation models don't include language detection
# This is a placeholder that could be enhanced with a separate detection model
self.logger.warning("Language detection not implemented for local models")
return {
'language': 'unknown',
'confidence': 0.0,
'engine': 'local',
'note': 'Language detection not available with local models'
}
def get_supported_languages(self) -> Dict[str, str]:
"""Get supported languages for local model."""
# Return basic supported languages - could be enhanced by parsing model config
return {code: name for code, name in SUPPORTED_LANGUAGES.items()
if code in self.language_mapping}
class TranslationService:
"""Main translation service that manages multiple engines."""
def __init__(
self,
primary_engine: str = DEFAULT_TRANSLATION_SERVICE,
fallback_engine: Optional[str] = None
):
"""
Initialize translation service.
Args:
primary_engine: Primary translation engine ('google' or 'local')
fallback_engine: Fallback engine if primary fails
"""
self.primary_engine_name = primary_engine
self.fallback_engine_name = fallback_engine
self.engines = {}
self.logger = logging.getLogger(__name__)
# Initialize engines
self._initialize_engines()
def _initialize_engines(self) -> None:
"""Initialize translation engines."""
try:
# Initialize Google Translate engine
self.engines['google'] = GoogleTranslateEngine()
self.logger.info("Google Translate engine initialized")
except Exception as e:
self.logger.warning(f"Failed to initialize Google Translate: {str(e)}")
try:
# Initialize local engine
self.engines['local'] = LocalTranslationEngine()
self.logger.info("Local translation engine initialized")
except Exception as e:
self.logger.warning(f"Failed to initialize local engine: {str(e)}")
def translate(
self,
text: str,
source_lang: str,
target_lang: str,
engine: Optional[str] = None
) -> Dict[str, Any]:
"""
Translate text with automatic fallback.
Args:
text: Text to translate
source_lang: Source language code
target_lang: Target language code
engine: Specific engine to use (optional)
Returns:
Dictionary with translation results
"""
# Determine which engine to use
engine_name = engine or self.primary_engine_name
# Try primary engine
try:
if engine_name in self.engines:
return self.engines[engine_name].translate(text, source_lang, target_lang)
else:
raise ValueError(f"Engine '{engine_name}' not available")
except Exception as e:
self.logger.warning(f"Primary engine '{engine_name}' failed: {str(e)}")
# Try fallback engine if available
if (self.fallback_engine_name and
self.fallback_engine_name in self.engines and
self.fallback_engine_name != engine_name):
try:
self.logger.info(f"Trying fallback engine: {self.fallback_engine_name}")
return self.engines[self.fallback_engine_name].translate(
text, source_lang, target_lang
)
except Exception as fallback_error:
self.logger.error(f"Fallback engine also failed: {str(fallback_error)}")
# If all engines fail, raise the original error
raise RuntimeError(f"Translation failed: {str(e)}")
def detect_language(self, text: str, engine: Optional[str] = None) -> Dict[str, Any]:
"""
Detect text language.
Args:
text: Text for language detection
engine: Specific engine to use (optional)
Returns:
Dictionary with detection results
"""
engine_name = engine or self.primary_engine_name
if engine_name in self.engines:
return self.engines[engine_name].detect_language(text)
else:
raise ValueError(f"Engine '{engine_name}' not available")
def batch_translate(
self,
texts: List[str],
source_lang: str,
target_lang: str,
engine: Optional[str] = None
) -> List[Dict[str, Any]]:
"""
Translate multiple texts.
Args:
texts: List of texts to translate
source_lang: Source language code
target_lang: Target language code
engine: Specific engine to use (optional)
Returns:
List of translation results
"""
results = []
for i, text in enumerate(texts):
try:
self.logger.debug(f"Translating text {i+1}/{len(texts)}")
result = self.translate(text, source_lang, target_lang, engine)
results.append(result)
except Exception as e:
self.logger.error(f"Failed to translate text {i+1}: {str(e)}")
# Add error result
results.append({
'text': text,
'translated_text': text, # Fallback to original
'source_language': source_lang,
'target_language': target_lang,
'confidence': 0.0,
'engine': 'error',
'error': str(e)
})
return results
def get_available_engines(self) -> List[str]:
"""Get list of available engines."""
return list(self.engines.keys())
def get_supported_languages(self, engine: Optional[str] = None) -> Dict[str, str]:
"""
Get supported languages.
Args:
engine: Specific engine (uses primary if None)
Returns:
Dictionary of language codes and names
"""
engine_name = engine or self.primary_engine_name
if engine_name in self.engines:
return self.engines[engine_name].get_supported_languages()
else:
return SUPPORTED_LANGUAGES
# Utility functions
def create_translation_service(
primary_engine: str = DEFAULT_TRANSLATION_SERVICE,
fallback_engine: str = "google"
) -> TranslationService:
"""Create and initialize translation service."""
return TranslationService(primary_engine, fallback_engine)
def quick_translate(
text: str,
source_lang: str,
target_lang: str,
engine: str = DEFAULT_TRANSLATION_SERVICE
) -> str:
"""Quick translation function for simple use cases."""
service = create_translation_service(primary_engine=engine)
result = service.translate(text, source_lang, target_lang)
return result['translated_text'] |