81 lines
4.3 KiB
Python
81 lines
4.3 KiB
Python
from pathlib import Path
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import shutil
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helper = ''' def _wait_for_database_voice(self, fp, *, visible_voice=False):
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"""Yield this task while local ASR works; unrelated conversations continue."""
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from voice_messages import voice_batch_status
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state = self._pending_reply_state(fp)
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context = getattr(self, "_last_database_read", None)
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bound = isinstance(context, dict) and context.get("fp_hex") == bytes(fp or b"").hex()
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voice = voice_batch_status(context) if bound else {"status": "none"}
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if visible_voice and voice["status"] == "none":
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voice = {"status": "pending", "key": "visible-voice:" + bytes(fp or b"").hex(),
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"reason": "等待语音对应的本机消息库和音频文件"}
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if voice["status"] in {"none", "ready"}:
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if state:
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state.pop("voice_wait_key", None)
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state.pop("voice_wait_started_at", None)
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return False
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if state is None:
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return True # No durable task identity: never guess or answer an unheard voice.
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now = time.time()
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if state.get("voice_wait_key") != voice.get("key"):
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state.update(voice_wait_key=voice.get("key"), voice_wait_started_at=now)
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waiting = voice["status"] == "pending" and now - float(state.get("voice_wait_started_at") or now) < 180
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if waiting:
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state["ready_at"] = now + 2
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self._set_task_stage(fp, "voice_transcribing", detail=voice.get("reason") or "语音正在本机转文字")
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else:
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reason = voice.get("reason") if voice["status"] == "error" else "语音转文字等待超时，尚未取得可核验文字，请人工处理"
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state.update(manual_required=True, manual_reason=reason, awaiting_review=False,
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reply_text="", staged_reply_text="", chat_text=str((context or {}).get("text") or ""))
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self._set_task_stage(fp, "error", detail="语音需要人工核对", error=reason)
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self._register_assistant_review(fp)
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self._persist_pending_replies()
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return True
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'''
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for label, project in [('source', Path('C:/kefu/wechat_rpa')), ('production', Path('C:/wechat_rpa'))]:
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path = project / 'wechat_bot.py'
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backup = Path(__file__).parent / 'before-voice-integration' / label
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backup.mkdir(parents=True, exist_ok=True)
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shutil.copy2(path, backup / path.name)
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text = path.read_text(encoding='utf-8')
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needle = ' def _database_message_direction(self, fp: bytes, text: str):\n'
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assert text.count(needle) == 1
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text = text.replace(needle, helper + needle)
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needle = ''' database_text = self._database_chat_text(fp)
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if database_text:
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chat_text = database_text
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'''
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assert text.count(needle) == 1
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text = text.replace(needle, needle + ''' if self._wait_for_database_voice(fp):
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return None
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from voice_messages import voice_batch_status
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database_voice_ready = bool(database_text and voice_batch_status(getattr(self, "_last_database_read", None))["status"] == "ready")
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''')
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needle = ''' first_untrusted_batch = bool(
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first_record_batch and not first_explicit_customer_text
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)
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'''
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assert text.count(needle) == 1
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text = text.replace(needle, ''' first_untrusted_batch = bool(
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first_record_batch and not first_explicit_customer_text and not database_voice_ready
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)
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if database_voice_ready:
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# Exact database identity and successful ASR make voice text available to normal model/risk processing.
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reliable_text_pending = True
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force_media_check = False
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''')
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needle = ''' self.report_operation("AI 准备", 2, 3, "语音没有转写，生成安全追问", fp)
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print(" [AI] 检测到未转写语音，使用不猜测内容的安全回复")
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ai_reply = safe_media_reply(media_types)
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'''
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assert text.count(needle) == 1
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text = text.replace(needle, ''' self._wait_for_database_voice(fp, visible_voice=True)
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return None
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''')
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path.write_text(text, encoding='utf-8')
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print('Visual voice waiting/model flow integrated with targeted edits in both variants.')
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