from __future__ import annotations import json import logging from dataclasses import dataclass from .file_summary.workflow_trigger import ( evaluate_attachment_reader_trigger, evaluate_file_summary_trigger, ) from .application_form_fill.constants import FORM_FILL_TRIGGER_KEYWORDS, WORKFLOW_TYPE as FORM_FILL_WORKFLOW_TYPE from .llm import LLMConfigurationError, LLMRequestError, generate_completion from .models import Conversation, FileAttachment from .regulatory_info_package.constants import ( REGULATORY_INFO_PACKAGE_TRIGGER_KEYWORDS, WORKFLOW_TYPE as REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE, ) logger = logging.getLogger(__name__) ROUTE_ACTIONS = {"normal_chat", "attachment_reader", "file_summary"} ROUTE_ACTIONS.add("regulatory_review") ROUTE_ACTIONS.add(FORM_FILL_WORKFLOW_TYPE) ROUTE_ACTIONS.add(REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE) @dataclass(frozen=True) class SkillRoute: action: str skill_name: str = "" workflow_type: str = "" confidence: float = 0.0 reason: str = "" source: str = "llm" @property def uses_attachment_reader(self) -> bool: return self.action == "attachment_reader" @property def starts_file_summary(self) -> bool: return self.action == "file_summary" @property def starts_regulatory_review(self) -> bool: return self.action == "regulatory_review" @property def starts_application_form_fill(self) -> bool: return self.action == FORM_FILL_WORKFLOW_TYPE @property def starts_regulatory_info_package(self) -> bool: return self.action == REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE @property def is_normal_chat(self) -> bool: return self.action == "normal_chat" def route_message_intent(conversation: Conversation, content: str) -> SkillRoute: deterministic_route = _deterministic_workflow_route(conversation, content) if deterministic_route: return deterministic_route attachments = list(_active_attachments(conversation)) try: route = _route_with_llm(conversation, content, attachments) logger.info( "LLM skill route selected", extra={ "conversation_id": conversation.pk, "action": route.action, "skill_name": route.skill_name, "workflow_type": route.workflow_type, "confidence": route.confidence, "route_source": route.source, "reason": route.reason, }, ) return route except (LLMConfigurationError, LLMRequestError, ValueError, json.JSONDecodeError) as exc: logger.warning( "LLM skill route failed, fallback to rules", extra={"conversation_id": conversation.pk, "error": str(exc)}, ) return _route_with_rules(conversation, content) def _deterministic_workflow_route(conversation: Conversation, content: str) -> SkillRoute | None: if _matches_regulatory_info_package(content): return SkillRoute( action=REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE, workflow_type=REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE, confidence=0.9, reason="命中明确第1章监管信息材料包生成关键词。", source="rule_preflight", ) if _matches_application_form_fill(content): return SkillRoute( action=FORM_FILL_WORKFLOW_TYPE, workflow_type=FORM_FILL_WORKFLOW_TYPE, confidence=0.9, reason="命中明确申报文件自动填表关键词。", source="rule_preflight", ) if _matches_regulatory_review(content): return SkillRoute( action="regulatory_review", workflow_type="regulatory_review", confidence=0.9, reason="命中明确法规核查关键词。", source="rule_preflight", ) file_summary = evaluate_file_summary_trigger(conversation, content) if file_summary.should_start or file_summary.reason == "missing_attachment": return SkillRoute( action="file_summary", workflow_type="file_summary", confidence=0.8, reason=file_summary.reason, source="rule_preflight", ) return None def _route_with_llm( conversation: Conversation, content: str, attachments: list[FileAttachment], ) -> SkillRoute: raw = generate_completion( [ {"role": "system", "content": _router_system_prompt()}, { "role": "user", "content": _router_user_prompt( user_message=content, attachments=attachments, ), }, ], temperature=0.0, ) payload = _parse_json_object(raw) action = str(payload.get("action", "normal_chat")).strip() if action not in ROUTE_ACTIONS: raise ValueError(f"不支持的路由动作：{action}") if action in {"attachment_reader", "file_summary"} and not attachments: return SkillRoute( action=action, skill_name="attachment_reader" if action == "attachment_reader" else "", workflow_type="file_summary" if action == "file_summary" else "", confidence=_float_or_zero(payload.get("confidence")), reason=str(payload.get("reason") or "LLM 判断需要附件，但当前无附件。"), source="llm_missing_attachment", ) return SkillRoute( action=action, skill_name="attachment_reader" if action == "attachment_reader" else "", workflow_type=action if action in {"file_summary", "regulatory_review", FORM_FILL_WORKFLOW_TYPE, REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE} else "", confidence=_float_or_zero(payload.get("confidence")), reason=str(payload.get("reason") or ""), source="llm", ) def _route_with_rules(conversation: Conversation, content: str) -> SkillRoute: if _matches_regulatory_info_package(content): return SkillRoute( action=REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE, workflow_type=REGULATORY_INFO_PACKAGE_WORKFLOW_TYPE, confidence=0.7, reason="命中第1章监管信息材料包生成关键词。", source="rule_fallback", ) if _matches_application_form_fill(content): return SkillRoute( action=FORM_FILL_WORKFLOW_TYPE, workflow_type=FORM_FILL_WORKFLOW_TYPE, confidence=0.7, reason="命中申报文件自动填表关键词。", source="rule_fallback", ) if _matches_regulatory_review(content): return SkillRoute( action="regulatory_review", workflow_type="regulatory_review", confidence=0.7, reason="命中法规核查关键词。", source="rule_fallback", ) file_summary = evaluate_file_summary_trigger(conversation, content) if file_summary.should_start or file_summary.reason == "missing_attachment": return SkillRoute( action="file_summary", workflow_type="file_summary", confidence=0.5, reason=file_summary.reason, source="rule_fallback", ) attachment_reader = evaluate_attachment_reader_trigger(conversation, content) if attachment_reader.should_start or attachment_reader.reason == "missing_attachment": return SkillRoute( action="attachment_reader", skill_name="attachment_reader", confidence=0.5, reason=attachment_reader.reason, source="rule_fallback", ) return SkillRoute( action="normal_chat", confidence=0.5, reason="未匹配到需要调用 Skill 或工作流的意图。", source="rule_fallback", ) def _active_attachments(conversation: Conversation): return ( FileAttachment.objects.filter(conversation=conversation, is_active=True) .exclude(upload_status=FileAttachment.UploadStatus.DELETED) .order_by("original_name", "-version_no") ) def _router_system_prompt() -> str: return ( "你是审核智能体的工具路由器，只判断是否需要调用工具，不直接回答用户。" "你必须只输出 JSON 对象，不要输出 Markdown。" "可选 action：normal_chat、attachment_reader、file_summary、regulatory_review、application_form_fill、regulatory_info_package。" "attachment_reader 用于用户要求阅读、提取、分析、总结、查看上传附件内容。" "file_summary 用于用户要求自动汇总文件目录、页数、清单或生成目录页数报告。" "regulatory_review 用于用户要求法规核查、NMPA核查、完整性核查、章节一致性核查、风险预警或整改建议。" "application_form_fill 用于用户要求填注册证、生成申报模板、填写对应表格、安全和性能基本原则清单或自动填表。" "regulatory_info_package 用于用户要求根据说明书生成第1章监管信息、监管信息材料包、申请表、产品列表或声明材料包。" "normal_chat 用于不需要读取附件或执行工作流的一般问答。" "输出字段：action、confidence、reason。" ) def _router_user_prompt(*, user_message: str, attachments: list[FileAttachment]) -> str: attachment_lines = [ f"- id={attachment.pk}, name={attachment.original_name}, active={attachment.is_active}, status={attachment.upload_status}" for attachment in attachments ] attachment_text = "\n".join(attachment_lines) if attachment_lines else "无 active 附件" return ( f"用户消息：{user_message}\n\n" f"当前 active 附件：\n{attachment_text}\n\n" "请判断应调用哪个 action。只输出 JSON。" ) def _parse_json_object(raw: str) -> dict: text = (raw or "").strip() if text.startswith("```"): text = text.strip("`").strip() if text.lower().startswith("json"): text = text[4:].strip() start = text.find("{") end = text.rfind("}") if start == -1 or end == -1 or end < start: raise json.JSONDecodeError("未找到 JSON 对象", text, 0) return json.loads(text[start : end + 1]) def _float_or_zero(value) -> float: try: return float(value) except (TypeError, ValueError): return 0.0 def _matches_regulatory_review(content: str) -> bool: normalized = content.lower() keywords = [ "法规核查", "nmpa核查", "nmpa 核查", "完整性核查", "风险预警", "整改建议", "章节核查", "一致性核查", ] return any(keyword in normalized for keyword in keywords) def _matches_regulatory_info_package(content: str) -> bool: normalized = "".join((content or "").lower().split()) return any("".join(keyword.lower().split()) in normalized for keyword in REGULATORY_INFO_PACKAGE_TRIGGER_KEYWORDS) def _matches_application_form_fill(content: str) -> bool: normalized = content.lower() return any(keyword.lower() in normalized for keyword in FORM_FILL_TRIGGER_KEYWORDS)