87 lines
1.9 KiB
Python
87 lines
1.9 KiB
Python
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"""
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Language helpers (local-only).
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We want AI analysis output language to follow the frontend UI language.
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Frontend sends `X-App-Lang` (and also `Accept-Language`) on each request.
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"""
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from __future__ import annotations
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from typing import Optional
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SUPPORTED_LANGS = {
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"en-US",
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"zh-CN",
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"zh-TW",
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"ja-JP",
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"ko-KR",
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"vi-VN",
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"th-TH",
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"ar-SA",
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"fr-FR",
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"de-DE",
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}
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def _normalize_lang(raw: Optional[str]) -> Optional[str]:
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if not raw:
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return None
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s = str(raw).strip()
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if not s:
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return None
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# Accept-Language can be like: "en-US,en;q=0.9"
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if "," in s:
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s = s.split(",", 1)[0].strip()
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if ";" in s:
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s = s.split(";", 1)[0].strip()
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# Normalize short tags
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lower = s.lower()
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if lower in ("en", "en-us"):
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return "en-US"
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if lower in ("zh", "zh-cn", "zh-hans"):
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return "zh-CN"
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if lower in ("zh-tw", "zh-hant"):
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return "zh-TW"
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# Keep canonical casing if already supported
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for lang in SUPPORTED_LANGS:
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if lang.lower() == lower:
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return lang
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return None
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def detect_request_language(flask_request, body: Optional[dict] = None, default: str = "en-US") -> str:
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"""
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Detect language for the current request.
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Priority:
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1) Header X-App-Lang (frontend UI language)
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2) body["language"] or query ?language=
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3) Header Accept-Language
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"""
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# 1) Custom header
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lang = _normalize_lang(flask_request.headers.get("X-App-Lang"))
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if lang:
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return lang
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# 2) Explicit parameter
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if body and isinstance(body, dict):
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lang = _normalize_lang(body.get("language"))
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if lang:
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return lang
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lang = _normalize_lang(flask_request.args.get("language"))
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if lang:
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return lang
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# 3) Browser default
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lang = _normalize_lang(flask_request.headers.get("Accept-Language"))
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if lang:
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return lang
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return default
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