| |
| """Prompting + decode settings for Qwen3-4B translation.""" |
| from __future__ import annotations |
|
|
| import re |
| import time |
|
|
| from openai import OpenAI |
|
|
| SYSTEM = ( |
| "You are a professional translator for invoices, notices, medical instructions, " |
| "and news. Translate faithfully into the requested target language.\n" |
| "Rules:\n" |
| "- Output only the translation. No quotes, labels, romanization notes, or commentary.\n" |
| "- Copy the listed preserve tokens exactly (IDs, emails, amounts, Latin brand names, acronyms).\n" |
| "- If a preserve token is already Latin, keep it in Latin letters; do not transliterate it.\n" |
| "- Do not replace a proper name with a similar-sounding different name.\n" |
| "- receipt ≠ invoice. receipt → Arabic إيصال, French reçu, German Quittung, Spanish recibo. " |
| "invoice → Arabic فاتورة, French facture, German Rechnung, Spanish factura, Italian fattura, " |
| "Portuguese fatura, Turkish fatura, Greek τιμολόγιο, Russian счёт.\n" |
| "- digital identity → Arabic هوية رقمية (not اعتماد).\n" |
| "- In a banking context, Arabic حوّل / حول المبلغ إلى الحساب means transfer (wire) money, " |
| "not convert a currency, unless the source is clearly about an exchange rate.\n" |
| "- Keep technical acronyms GPU, OCR, CPU, CUDA, API in Latin letters when the source uses them.\n" |
| "- Modern Standard Arabic; keep the definite article on city names (الرياض، الدوحة، أبوظبي).\n" |
| "- Translate meaning, but never drop a number, date, or identifier." |
| ) |
|
|
| _ID = re.compile(r"\b[A-Z]{2,}[A-Z0-9._/-]*\d[A-Z0-9._/-]*\b") |
| _EMAIL = re.compile(r"\b[\w.+-]+@[\w.-]+\.[A-Za-z]{2,}\b") |
| _ACRONYM = re.compile( |
| r"\b(?:GPU|OCR|CPU|CUDA|API|AWB|LLC|USD|AED|EUR|VAT|TTC|IBAN|SWIFT|SKU|PO)\b" |
| ) |
| _HYPHEN_NAME = re.compile(r"\b[A-Z][a-z]+-[A-Z][a-z]+\b") |
| _NAME_RUN = re.compile( |
| r"\b[A-Z][a-z]+(?:\s+(?:and|&|of|de|del|al|the)\s+[A-Z][a-z]+)*(?:\s+[A-Z][a-z]+){1,3}\b" |
| ) |
| _SKIP_NAMES = { |
| "The Total", "The Patient", "Please Reset", "Please Send", "Please Pay", |
| "On August", "Each Page", "This Stainless", "Dear Mr", |
| } |
|
|
|
|
| def copy_spans(source: str) -> list[str]: |
| found: list[str] = [] |
| for rx in (_EMAIL, _ID, _ACRONYM, _HYPHEN_NAME): |
| found.extend(rx.findall(source)) |
| for m in _NAME_RUN.finditer(source): |
| span = m.group(0) |
| if span in _SKIP_NAMES: |
| continue |
| if span.lower().startswith(("the ", "this ", "please ", "dear ")): |
| continue |
| found.append(span) |
| out: list[str] = [] |
| for tok in found: |
| if tok not in out: |
| out.append(tok) |
| return out[:12] |
|
|
|
|
| def term_hints(source: str, src_lang: str, tgt_lang: str) -> list[str]: |
| hints: list[str] = [] |
| sl, tl = src_lang.lower(), tgt_lang.lower() |
| low = source.lower() |
| if tl == "arabic": |
| if re.search(r"\breceipts?\b", low): |
| hints.append("receipt → إيصال") |
| if re.search(r"\binvoices?\b", low): |
| hints.append("invoice → فاتورة") |
| if "identity" in low: |
| hints.append("digital identity → هوية رقمية") |
| if re.search(r"\b(gpu|ocr|cuda)\b", low): |
| hints.append("keep GPU / OCR / CUDA as Latin acronyms") |
| if "cafe" in low or "café" in low: |
| hints.append("Cafe in a brand name stays Latin (Harbor and Rye Cafe)") |
| if "tablet" in low: |
| hints.append("tablet → قرص") |
| if "customs" in low: |
| hints.append("customs officer → موظف الجمارك") |
| if re.search(r"\bgoods\b", low): |
| hints.append("goods → البضائع") |
| if "finance" in low: |
| hints.append("Finance department → قسم المالية") |
| if "flight" in low: |
| hints.append("flight → رحلة") |
| if sl == "arabic" and tl == "english": |
| if re.search(r"حو[ّ]?ل", source) and "حساب" in source: |
| hints.append("حوّل المبلغ إلى الحساب = transfer (not convert)") |
| if "إيصال" in source: |
| hints.append("إيصال = receipt") |
| if "فاتورة" in source: |
| hints.append("فاتورة = invoice") |
| if "هوية" in source: |
| hints.append("هوية = identity") |
| if "رحلة" in source and "مطار" in source: |
| hints.append("الرحلة from an airport = flight (not trip)") |
| if tl == "greek" and "invoice" in low: |
| hints.append("invoice → τιμολόγιο") |
| if tl == "russian" and "invoice" in low: |
| hints.append("invoice → счёт") |
| return hints |
|
|
|
|
| def prompt_for(case: dict) -> tuple[str, str]: |
| src, tgt = case["src_lang"], case["tgt_lang"] |
| preserve = list(case.get("preserve") or []) |
| for span in copy_spans(case["source"]): |
| if span not in preserve: |
| preserve.append(span) |
| hints = term_hints(case["source"], src, tgt) |
| lines = [ |
| f"Translate from {src} to {tgt}.", |
| "Output only the translation.", |
| ] |
| if preserve: |
| lines.append( |
| "Your translation MUST contain each of these strings verbatim: " |
| + ", ".join(preserve) |
| + "." |
| ) |
| if hints: |
| lines.append("Term hints: " + "; ".join(hints) + ".") |
| lines.append("") |
| lines.append(case["source"]) |
| return SYSTEM, "\n".join(lines) |
|
|
|
|
| def max_tokens_for(source: str) -> int: |
| return min(512, max(96, 48 + 4 * max(1, len(source.split())))) |
|
|
|
|
| def strip_fences(text: str) -> str: |
| text = (text or "").strip() |
| text = re.sub(r"^```(?:\w+)?\s*", "", text) |
| text = re.sub(r"\s*```$", "", text) |
| text = re.sub( |
| r"^(?:translation|arabic|english|french|german|spanish|italian|portuguese|" |
| r"turkish|russian|greek)\s*:\s*", |
| "", |
| text, |
| flags=re.I, |
| ) |
| return text.strip().strip('"“”«»') |
|
|
|
|
| def translate_text( |
| client: OpenAI, |
| source: str, |
| src_lang: str, |
| tgt_lang: str, |
| model: str = "Qwen/Qwen3-4B-Instruct-2507", |
| preserve: list[str] | None = None, |
| ) -> tuple[str, float]: |
| return translate( |
| client, |
| model, |
| { |
| "source": source, |
| "src_lang": src_lang, |
| "tgt_lang": tgt_lang, |
| "preserve": preserve or [], |
| }, |
| ) |
|
|
|
|
| def translate(client: OpenAI, model: str, case: dict) -> tuple[str, float]: |
| system, user = prompt_for(case) |
| messages = [ |
| {"role": "system", "content": system}, |
| {"role": "user", "content": user}, |
| ] |
| kwargs = dict( |
| model=model, |
| temperature=0.0, |
| top_p=1.0, |
| max_tokens=max_tokens_for(case["source"]), |
| messages=messages, |
| ) |
| t0 = time.perf_counter() |
| try: |
| resp = client.chat.completions.create(**kwargs, seed=0) |
| except TypeError: |
| resp = client.chat.completions.create(**kwargs) |
| dt = time.perf_counter() - t0 |
| return strip_fences(resp.choices[0].message.content or ""), dt |
|
|
