马一丁
84 lines
2.6 KiB
Python
84 lines
2.6 KiB
Python
"""
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章节篇幅规划节点。
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"""
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from __future__ import annotations
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import json
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from typing import Any, Dict, List
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from loguru import logger
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from ..core import TemplateSection
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from ..prompts import (
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SYSTEM_PROMPT_WORD_BUDGET,
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build_word_budget_prompt,
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)
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from .base_node import BaseNode
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class WordBudgetNode(BaseNode):
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"""
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规划各章节字数与重点。
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输出总字数、全局写作准则以及每章/小节的 target/min/max 字数约束。
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"""
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def __init__(self, llm_client):
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"""仅记录LLM客户端引用，方便run阶段发起请求"""
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super().__init__(llm_client, "WordBudgetNode")
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def run(
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self,
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sections: List[TemplateSection],
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design: Dict[str, Any],
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reports: Dict[str, str],
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forum_logs: str,
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query: str,
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template_overview: Dict[str, Any] | None = None,
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) -> Dict[str, Any]:
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"""根据设计稿和所有素材规划章节字数，让LLM写作时有明确篇幅目标"""
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# 输入中除了章节骨架外，还包含布局节点输出，方便约束篇幅时参考视觉主次
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payload = {
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"query": query,
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"design": design,
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"sections": [section.to_dict() for section in sections],
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"templateOverview": template_overview
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or {
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"title": sections[0].title if sections else "",
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"chapters": [section.to_dict() for section in sections],
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},
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"reports": reports,
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"forumLogs": forum_logs,
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}
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user = build_word_budget_prompt(payload)
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response = self.llm_client.stream_invoke_to_string(
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SYSTEM_PROMPT_WORD_BUDGET,
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user,
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temperature=0.25,
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top_p=0.85,
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)
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plan = self._parse_response(response)
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logger.info("章节字数规划已生成")
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return plan
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def _parse_response(self, raw: str) -> Dict[str, Any]:
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"""将LLM输出的JSON文本转为字典，失败时提示规划异常"""
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cleaned = raw.strip()
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if cleaned.startswith("```json"):
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cleaned = cleaned[7:]
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if cleaned.startswith("```"):
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cleaned = cleaned[3:]
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if cleaned.endswith("```"):
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cleaned = cleaned[:-3]
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cleaned = cleaned.strip()
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if not cleaned:
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raise ValueError("篇幅规划LLM返回空内容")
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try:
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return json.loads(cleaned)
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except json.JSONDecodeError as exc:
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raise ValueError(f"篇幅规划JSON解析失败: {exc}") from exc
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__all__ = ["WordBudgetNode"]
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