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| """ | |
| Translation layer — translates between the user's language and English. | |
| The main LLM always receives and produces English. | |
| This module handles conversion in both directions so the UI shows the user's language. | |
| Formatting rules: | |
| Text inside (parentheses) and *asterisks* is roleplay markup — it must be | |
| preserved as-is so the parser can still identify actions and thoughts. | |
| """ | |
| import logging | |
| import time | |
| from huggingface_hub import InferenceClient | |
| logger = logging.getLogger(__name__) | |
| _TO_EN = ( | |
| "You are a professional translator. " | |
| "Translate the following text to English. " | |
| "Translate ALL content, including text inside parentheses ( ) and asterisks *. " | |
| "Keep the parentheses ( ) and asterisks * markers exactly in place — do not remove or add them. " | |
| "Return ONLY the translated text, no explanations or extra text." | |
| ) | |
| _FROM_EN = ( | |
| "You are a professional translator. " | |
| "Translate the following text to {language}. " | |
| "Translate ALL content, including text inside parentheses ( ) and asterisks *. " | |
| "Keep the parentheses ( ) and asterisks * markers exactly in place — do not remove or add them. " | |
| "Return ONLY the translated text, no explanations or extra text." | |
| ) | |
| def translate_to_english( | |
| text: str, | |
| source_language: str, | |
| client: InferenceClient, | |
| model: str, | |
| ) -> str: | |
| """ | |
| Translate `text` from `source_language` to English. | |
| Returns the original text unchanged if already English or on any failure. | |
| """ | |
| if not text.strip() or source_language.strip().lower() == "english": | |
| logger.debug("[Translator] to_english skipped (already English or empty).") | |
| return text | |
| logger.info(f"[Translator] ▶ {source_language}→EN | model='{model}' | {len(text)} chars") | |
| start = time.time() | |
| try: | |
| response = client.chat_completion( | |
| messages=[ | |
| {"role": "system", "content": _TO_EN}, | |
| {"role": "user", "content": text}, | |
| ], | |
| model=model, | |
| max_tokens=1024, | |
| stream=False, | |
| temperature=0.1, | |
| ) | |
| result = response.choices[0].message.content.strip() | |
| elapsed = time.time() - start | |
| logger.info(f"[Translator] ✓ {source_language}→EN | {elapsed:.1f}s | {len(result)} chars") | |
| logger.debug(f"[Translator] {source_language}→EN: {text[:80]!r} → {result[:80]!r}") | |
| return result | |
| except Exception as e: | |
| logger.error(f"[Translator] to_english FAILED | model='{model}' | error: {e}", exc_info=True) | |
| return text | |
| def translate_from_english( | |
| text: str, | |
| target_language: str, | |
| client: InferenceClient, | |
| model: str, | |
| ) -> str: | |
| """ | |
| Translate `text` from English to `target_language`. | |
| Returns the original text unchanged if target is English or on any failure. | |
| """ | |
| if not text.strip() or target_language.strip().lower() == "english": | |
| logger.debug("[Translator] from_english skipped (target is English or empty).") | |
| return text | |
| logger.info(f"[Translator] ▶ EN→{target_language} | model='{model}' | {len(text)} chars") | |
| start = time.time() | |
| try: | |
| system = _FROM_EN.format(language=target_language) | |
| response = client.chat_completion( | |
| messages=[ | |
| {"role": "system", "content": system}, | |
| {"role": "user", "content": text}, | |
| ], | |
| model=model, | |
| max_tokens=1024, | |
| stream=False, | |
| temperature=0.1, | |
| ) | |
| result = response.choices[0].message.content.strip() | |
| elapsed = time.time() - start | |
| logger.info(f"[Translator] ✓ EN→{target_language} | {elapsed:.1f}s | {len(result)} chars") | |
| logger.debug(f"[Translator] EN→{target_language}: {text[:80]!r} → {result[:80]!r}") | |
| return result | |
| except Exception as e: | |
| logger.error(f"[Translator] from_english FAILED | model='{model}' | error: {e}", exc_info=True) | |
| return text |