feat(translate): 加星火 Spark(Lite)作为优先翻译引擎
- 新增 app/services/translation/spark.py: OpenAI 兼容协议客户端, URL = https://spark-api-open.xf-yun.com/v1/chat/completions, 鉴权 = Bearer <APIPassword>, model = lite(默认)/generalv3.5/4.0Ultra 可切换 - service.py 引擎链路调整为: spark → tencent(配额)→ maas → agnes → local。 优先级降序: spark 配了 key 就用它,失败再走 tencent(继续吃配额,不绕过)。 要完全绕开 tencent,把 TENCENTCLOUD_SECRET_ID 留空即可。 - 配置: 新增 SPARK_API_PASSWORD / SPARK_BASE_URL / SPARK_MODEL / SPARK_INTERVAL_SEC (留空 SPARK_API_PASSWORD = 走原 tencent 主链路,向后兼容) - 缓存白名单 / 配额计数逻辑保持原行为,只把 spark 加入允许缓存的引擎集合
This commit is contained in:
Mavis
@@ -1,15 +1,18 @@
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"""翻译服务门面:配额检查 + 缓存 + 引擎选择 + 月度计数。
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引擎链路(优先级降序):
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1. tencent TMT(主,按月配额;快满时主动切走)
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2. tencent_maas(备用,OpenAI 兼容,无配额;主失败/TMT 配额耗尽时启用)
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3. agnes(第三级,通用 LLM 做翻译;MaaS 不可用时启用 — 质量次之但够用)
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4. local(最后兜底,需 settings.local_translate_enabled=true)
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1. spark(主,Lite 免费;spark_api_password 配了才用)
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2. tencent TMT(第二级,按月配额;快满时主动切走)
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3. tencent_maas(备用,OpenAI 兼容,无配额;主失败/TMT 配额耗尽时启用)
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4. agnes(第三级,通用 LLM 做翻译;MaaS 不可用时启用 — 质量次之但够用)
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5. local(最后兜底,需 settings.local_translate_enabled=true)
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注:
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- TMT 是按月计费的(腾讯云后台可能计费口径是请求字节,我们 redis 累加的是字符数,
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差异约 2-3x);用户从腾讯云后台看"已用 2M"时,我们 redis 显示约 80 万字符
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- 用户决策:以腾讯云后台数字为准,快满时降级
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- spark 是 Lite 免费,默认走它;spark 不可用时降级到 tencent(继续吃配额)。
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想要完全绕开 tencent,把 TENCENTCLOUD_SECRET_ID 留空即可。
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"""
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from __future__ import annotations
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@@ -24,6 +27,7 @@ from app.redis_client import get_redis
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from app.services.translation.agnes import AgnesTranslator
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from app.services.translation.base import BaseTranslator, TranslationResult
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from app.services.translation.local import LocalTranslator
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from app.services.translation.spark import SparkTranslator
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from app.services.translation.tencent import TencentTranslator
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from app.services.translation.tencent_maas import TencentMaaSTranslator
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@@ -43,6 +47,7 @@ def _month_key() -> str:
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class TranslationService:
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def __init__(self):
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self._spark: BaseTranslator | None = None
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self._tencent: BaseTranslator | None = None
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self._tencent_maas: BaseTranslator | None = None
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self._agnes: BaseTranslator | None = None
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@@ -50,8 +55,18 @@ class TranslationService:
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# 串行:1 个并发;避免触发腾讯 TMT 限速
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self._sem = asyncio.Semaphore(1)
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def _spark_translator(self) -> BaseTranslator | None:
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"""主引擎:星火 Spark(Lite 免费)。配了 spark_api_password 才启用。"""
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if self._spark is None and settings.spark_api_password:
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try:
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self._spark = SparkTranslator()
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except Exception as e:
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logger.warning("spark init failed: %s", e)
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self._spark = None
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return self._spark
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def _primary(self) -> BaseTranslator | None:
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"""主引擎:腾讯 TMT(初始化失败返回 None 表示不可用)。"""
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"""第二级:腾讯 TMT(初始化失败返回 None 表示不可用)。"""
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if self._tencent is None:
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try:
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self._tencent = TencentTranslator()
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@@ -139,19 +154,21 @@ class TranslationService:
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if cached is not None:
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return TranslationResult(text=cached, engine="cache", chars=chars, cached=True)
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# 2) 选引擎(主 → maas 备用 → local 兜底)
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use_tencent = await self.can_use_tencent(chars)
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if use_tencent:
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engine: BaseTranslator | None = self._primary()
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# 2) 选引擎
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# 优先级:spark → tencent(配额)→ maas → agnes → local
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engine: BaseTranslator | None = None
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if self._spark_translator() is not None:
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engine = self._spark_translator()
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elif await self.can_use_tencent(chars):
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engine = self._primary()
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if engine is None:
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# TMT 配了 key 但初始化失败 → 直接走 maas
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logger.warning("TMT unavailable, falling back to MaaS")
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engine = self._maas()
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else:
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engine = None
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if engine is None:
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# 配额耗尽 / TMT 不可用:走备用链(maas → agnes → local)
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# spark 不可用 + 配额耗尽 / TMT 不可用:走备用链(maas → agnes → local)
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engine = self._fallback()
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if engine is None:
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# 全无可用:返回原文 + 标记
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@@ -161,7 +178,7 @@ class TranslationService:
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chars=chars,
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)
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logger.info(
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"tencent quota exhausted, fallback to %s for %d chars",
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"primary engines unavailable, fallback to %s for %d chars",
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engine.name, chars,
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)
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@@ -172,8 +189,16 @@ class TranslationService:
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res = await engine.translate(text, source=source, target=target)
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except Exception as e:
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logger.exception("translate failed with %s: %s", engine.name, e)
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# 按 maas → local 顺序找一个不同的 fallback
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fb = self._maas() if engine.name != "tencent_maas" else None
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# 失败时按 tencent_maas → local 顺序找一个不同的 fallback
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# spark 失败时也要走 tencent(继续吃配额,因优先级只是降低不是禁用)
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fb: BaseTranslator | None = None
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if engine.name == "spark":
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if await self.can_use_tencent(chars):
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fb = self._primary()
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if fb is None:
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fb = self._maas() if engine.name != "tencent_maas" else None
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elif engine.name == "tencent":
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fb = self._maas() if engine.name != "tencent_maas" else None
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if fb is None and settings.local_translate_enabled and engine.name != "local":
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fb = self._local_translator()
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if fb is not None:
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@@ -186,19 +211,15 @@ class TranslationService:
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if res is None:
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raise RuntimeError(f"translation failed for {chars} chars (engine={engine.name})")
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# 注:engine 已经设好但运行时降级需要重新判断 fallback 链
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# 上面 translate() 调用失败时,会重试 _fallback() 里下一个可用引擎
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# 这里 engine 已经在 _fallback() 中按顺序选了一个最合适的,直接使用即可
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# 4) 写缓存 — 只缓存真实翻译结果;失败/降级文本不缓存(避免污染 30 天)
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if res.engine in ("tencent", "tencent_maas", "agnes", "nllb") and not res.cached:
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if res.engine in ("spark", "tencent", "tencent_maas", "agnes", "nllb") and not res.cached:
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if "[翻译失败" not in res.text and "[本条未翻译" not in res.text:
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try:
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await r.set(ck, res.text, ex=60 * 60 * 24 * 30) # 30 天
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except Exception:
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pass
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# 5) 计数(只在 tencent TMT 上计;maas / agnes / local 都不计腾讯云配额)
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# 5) 计数(只在 tencent TMT 上计;spark / maas / agnes / local 都不计腾讯云配额)
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if res.engine == "tencent":
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try:
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await self.add_usage(res.chars or chars)
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114
backend/app/services/translation/spark.py
Normal file
114
backend/app/services/translation/spark.py
Normal file
@@ -0,0 +1,114 @@
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"""星火 Spark 翻译(OpenAI 兼容协议)。
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- 端点:https://spark-api-open.xf-yun.com/v1/chat/completions
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- 模型:lite(也支持 generalv3.5 等,但该项目用 Lite,免费额度)
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- 鉴权:Bearer token(APIPassword 直接当 Bearer 用)
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- 请求:POST /chat/completions,system prompt 告诉模型做翻译
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设计上独立于 LlmClient,专门走 spark_* 配置,避免和 LLM 智能增强共用 client 的节流。
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"""
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from __future__ import annotations
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import asyncio
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import logging
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import random
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import httpx
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from app.config import settings
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from app.services.translation.base import BaseTranslator, TranslationResult
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logger = logging.getLogger("news.translate.spark")
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# 经过实测,这套 prompt 在 Spark Lite 上输出稳定(不夹带 reasoning / 注释)。
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# Lite 不支持 system 角色(早期 Lite 模型),但 v1 OpenAI 兼容的 Lite 接受 system;
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# 保留 system prompt 走 4.0Ultra/Max/Pro 时也通用。
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_SYSTEM_PROMPT = """你是一个即时翻译助手。对于用户输入的英文或日文文章,请直接输出对应的简体中文译文。严格遵守:
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不要进行任何分步思考、不要输出分析、不要添加注释或说明。
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只输出中文译文本身,不包含任何额外文字(如"翻译结果:"、"以下是中文:"等)。
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如果输入内容既非英文也非日文,仅回复:"仅支持英文或日文翻译为中文。" """
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class SparkTranslator(BaseTranslator):
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"""星火 Spark 翻译(OpenAI 兼容协议,模型 lite / generalv3.5 等)。"""
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name = "spark"
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def __init__(self):
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if not settings.spark_api_password:
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raise RuntimeError("Spark APIPassword missing")
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self.api_password = settings.spark_api_password
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self.base_url = settings.spark_base_url.rstrip("/")
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self.model = settings.spark_model
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self.interval_sec = settings.spark_interval_sec
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def is_configured(self) -> bool:
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return bool(self.api_password)
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async def translate(
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self, text: str, source: str = "auto", target: str = "zh"
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) -> TranslationResult:
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"""翻译接口。source/target 当前固定 EN/JA → ZH(由 prompt 控制)。"""
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if not text.strip():
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return TranslationResult(text=text, engine=self.name, chars=0)
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if not self.is_configured():
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raise RuntimeError("Spark APIPassword missing")
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system = _SYSTEM_PROMPT
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user = text
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url = f"{self.base_url}/chat/completions"
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payload = {
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"model": self.model,
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"messages": [
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{"role": "system", "content": system},
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{"role": "user", "content": user},
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],
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"temperature": 0.0,
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"max_tokens": max(256, len(text) * 3),
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}
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headers = {
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"Authorization": f"Bearer {self.api_password}",
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"Content-Type": "application/json",
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}
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# 简单串行 + 重试 1 次
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last_exc: Exception | None = None
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for attempt in range(2):
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try:
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async with httpx.AsyncClient(timeout=60.0) as client:
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r = await client.post(url, json=payload, headers=headers)
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if r.status_code >= 500:
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raise RuntimeError(f"Spark 5xx: {r.status_code} {r.text[:200]}")
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if r.status_code != 200:
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raise RuntimeError(f"Spark {r.status_code}: {r.text[:300]}")
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data = r.json()
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# 错误响应:{"error": {...}}
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if "error" in data:
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raise RuntimeError(f"Spark error: {data['error']}")
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content = (
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data.get("choices", [{}])[0]
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.get("message", {})
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.get("content", "")
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.strip()
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)
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if not content:
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raise RuntimeError(f"Spark empty content: {r.text[:300]}")
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await asyncio.sleep(self.interval_sec)
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return TranslationResult(
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text=content, engine=self.name, chars=len(text), cached=False
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)
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except Exception as e:
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last_exc = e
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logger.warning("spark attempt %s failed: %s", attempt, e)
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if attempt == 0:
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await asyncio.sleep(0.5 + random.random())
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else:
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raise
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assert last_exc is not None
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raise last_exc
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