92 lines
2.9 KiB
Python
92 lines
2.9 KiB
Python
"""
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海运协同群文字意图：DeepSeek A 判断补字段 / 产品报价 / 解散 / 其它。
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本文件职责：只分类，不写主账、不发企微。
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禁止：把「解散群」写成唯一口令；私聊按钮不走这里。
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"""
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from __future__ import annotations
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import logging
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from typing import Optional
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from agent.llm.extract_text import extract_collab_fields
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logger = logging.getLogger(__name__)
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INTENT_FIELDS = "collab_fields"
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INTENT_QUOTE = "product_quote"
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INTENT_DISSOLVE = "dissolve"
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INTENT_OTHER = "other"
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_VALID = {INTENT_FIELDS, INTENT_QUOTE, INTENT_DISSOLVE, INTENT_OTHER}
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def classify_group_text(
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text: str,
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*,
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injected: str = "",
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allow_network: Optional[bool] = None,
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) -> str:
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"""
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群里一句文字的意图。单测可注入；正式走模型。
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模型不可用时：只认带标签的协同字段（键：值是合同，不是口令），其余当其它。
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"""
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hint = (injected or "").strip()
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if hint in _VALID:
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return hint
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raw = (text or "").strip()
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if not raw:
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return INTENT_OTHER
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try:
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from agent.config import get_settings
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settings = get_settings()
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use_net = (
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allow_network
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if allow_network is not None
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else bool(getattr(settings, "llm_allow_network", False))
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)
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if use_net and getattr(settings, "llm_data_usage_confirmed", False):
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got = _classify_with_model(raw, settings)
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if got in _VALID:
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return got
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except Exception:
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logger.exception("群意图模型失败，回退标签字段")
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if extract_collab_fields(raw):
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return INTENT_FIELDS
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from agent.llm.extract_text import extract_product_quote
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if extract_product_quote(raw):
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return INTENT_QUOTE
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return INTENT_OTHER
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def _classify_with_model(text: str, settings) -> str:
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"""DeepSeek 只回一个意图词。失败空串。"""
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from agent.llm.http_client import LlmHttpClient
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from agent.llm.modes import LlmMode
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client = LlmHttpClient.from_settings(settings)
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system = (
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"你是海运协同群意图分类。只回复一个英文词，不要解释。"
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"collab_fields=在补贸易条款/货好时间/商品海关编码/含油含电含磁；"
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"product_quote=产品在报价格或费用；"
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"dissolve=要把这个协同群解散；"
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"other=闲聊、问候、对询价港口的随口更正（不当改单）。"
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"一句话里既补字段又报价，回 product_quote。"
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)
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data = client.chat(
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mode=LlmMode.ORDERED_ACTIONS,
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messages=[
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{"role": "system", "content": system},
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{"role": "user", "content": text[:2000]},
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],
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)
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content = str(getattr(data, "content", "") or "").strip().lower()
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for token in (INTENT_QUOTE, INTENT_DISSOLVE, INTENT_FIELDS, INTENT_OTHER):
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if token in content:
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return token
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return ""
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