1092 lines
49 KiB
Python
1092 lines
49 KiB
Python
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# Tab3：文章优化（从 geo_tool.py 迁移，通过 render_tab_optimize() 供主入口调用。）
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import re
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import streamlit as st
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.prompts import PromptTemplate
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from modules.eeat_enhancer import EEATEnhancer
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from modules.fact_density_enhancer import FactDensityEnhancer
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from modules.optimization_techniques import OptimizationTechniqueManager
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from modules.schema_generator import SchemaGenerator
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from modules.technical_config_generator import TechnicalConfigGenerator
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from modules.ui.components import sanitize_filename, safe_decode_uploaded, render_tab_top_with_clear
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def render_tab_optimize(
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storage,
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ss_init,
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gen_llm,
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brand: str,
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advantages: str,
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cfg: dict,
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record_api_cost,
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model_defaults,
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) -> None:
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"""渲染 Tab3：文章优化。由主入口在 with tab3 内调用。"""
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# 标题和清空按钮
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def _clear_optimize_state():
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st.session_state.optimized_article = ""
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st.session_state.opt_changes = ""
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render_tab_top_with_clear(
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title="🔧 文章优化",
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caption="优化已有文章，生成结构化数据和技术配置，提升 GEO 效果",
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clear_key="opt_clear",
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on_clear=_clear_optimize_state,
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)
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# === 文章优化功能（主流程） ===
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st.markdown("**✏️ 文章内容优化**")
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with st.container(border=True):
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st.markdown("粘贴或上传已写文章，一键提升 GEO 效果（结构化、可引用、自然植入品牌）")
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# 输入方式与文章内容放在表单外，以便粘贴/上传后能触发重跑，从而正确更新「开始优化」按钮的可用状态
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input_mode = st.radio(
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"输入方式",
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["粘贴文本", "上传文件（TXT/MD）"],
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horizontal=True,
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key="opt_input_mode",
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)
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if input_mode == "粘贴文本":
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original_article = st.text_area(
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"粘贴文章内容", height=360, key="opt_text"
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)
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else:
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uploaded = st.file_uploader(
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"上传 TXT 或 MD 文件",
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type=["txt", "md"],
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key="opt_uploader",
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)
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original_article = ""
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if uploaded:
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try:
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original_article = safe_decode_uploaded(uploaded) or ""
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except Exception as e:
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st.error(f"上传文件解析失败：{e}")
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original_article = ""
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if original_article:
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st.text_area(
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"上传内容预览",
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original_article,
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height=200,
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disabled=True,
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key="opt_upload_preview",
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)
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with st.form("opt_form", clear_on_submit=False):
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target_platform = st.selectbox(
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"目标平台（影响文风，可选）",
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[
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"通用优化",
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"知乎（专业问答）",
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"CSDN（技术博客）",
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"GitHub（README/文档）",
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"B站（视频脚本）",
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"头条号（资讯软文）",
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"微信公众号（长文）",
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"抖音图文（短内容）",
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"百家号（资讯）",
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"网易号（资讯）",
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"企鹅号（资讯）",
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"简书（文艺）",
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],
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index=[
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"通用优化",
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"知乎（专业问答）",
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"CSDN（技术博客）",
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"GitHub（README/文档）",
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"B站（视频脚本）",
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"头条号（资讯软文）",
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"微信公众号（长文）",
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"抖音图文（短内容）",
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"百家号（资讯）",
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"网易号（资讯）",
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"企鹅号（资讯）",
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"简书（文艺）",
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].index(
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st.session_state.opt_platform
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if st.session_state.opt_platform
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in [
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"通用优化",
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"知乎（专业问答）",
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"CSDN（技术博客）",
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"GitHub（README/文档）",
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"B站（视频脚本）",
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"头条号（资讯软文）",
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"微信公众号（长文）",
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"抖音图文（短内容）",
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"百家号（资讯）",
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"网易号（资讯）",
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"企鹅号（资讯）",
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"简书（文艺）",
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]
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else 0
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),
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key="opt_platform_sel",
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)
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# 高级优化技巧选择器（可选）
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with st.expander("🎨 高级优化技巧（可选）", expanded=False):
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opt_technique_manager = OptimizationTechniqueManager()
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opt_all_techniques = opt_technique_manager.list_techniques()
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opt_technique_options = [
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f"{tech['icon']} {tech['name']}" for tech in opt_all_techniques
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]
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opt_selected_technique_names = st.multiselect(
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"选择要应用的优化技巧（可多选）",
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options=opt_technique_options,
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default=[],
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key="opt_techniques",
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help="可选，提高 GEO 效果。技巧会动态调整文章优化策略。",
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)
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# 显示选择的技巧描述
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if opt_selected_technique_names:
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st.caption("已选择：" + "、".join(opt_selected_technique_names))
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with st.expander("查看技巧说明", expanded=False):
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for tech_name in opt_selected_technique_names:
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tech_icon_name = (
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tech_name.split(" ", 1)[1]
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if " " in tech_name
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else tech_name
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)
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for tech in opt_all_techniques:
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if tech["name"] == tech_icon_name:
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st.markdown(f"**{tech['icon']} {tech['name']}**")
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st.caption(tech["description"])
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break
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run_opt_disabled = (
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(not st.session_state.cfg_valid)
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or (gen_llm is None)
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or (not original_article.strip())
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)
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run_opt = st.form_submit_button(
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"开始优化", use_container_width=True, disabled=run_opt_disabled
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)
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if run_opt_disabled:
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if not original_article.strip():
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st.caption("请先在上方粘贴文章内容，或上传 TXT/MD 文件。")
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elif not st.session_state.cfg_valid or gen_llm is None:
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st.caption("当前未检测到可用的生成模型，请先在【全局设置】中完成模型/API 配置。")
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if run_opt:
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st.session_state.opt_platform = target_platform
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opt_selected_technique_names = st.session_state.get("opt_techniques", [])
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optimize_prompt_template = """
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你是GEO优化专家，目标是提升文章在大模型中的引用率和品牌自然提及。
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【原文章】
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{original_article}
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【品牌】{brand}
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【优势】{advantages}
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【目标平台】{platform}
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【优化要求（严格GEO原则）】
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1) 保留原意和核心信息，不改变事实
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2) 增强结构化：标题、清单、FAQ、代码块（适用时）
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3) 自然植入品牌2-4次（先通用标准，再品牌适用）
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4) 提升权威感：评估维度、匿名案例、来源占位建议（不得编造）
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5) 结论先行、信息密度高
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6) 长度控制在原长度的1.0-1.3倍
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7) 输出两部分：【优化后文章】 + 【变更说明】（列出主要改动点）
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【输出格式要求】
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请严格按照以下结构输出一次，不要在前后添加其他说明或重复输出：
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【优化后文章】
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（在此输出完整优化后的文章）
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【变更说明】
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（在此列出主要变更点，使用条目形式）
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【E-E-A-T 强化要求】
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- 专业性：增强专业术语使用，展示专业知识深度
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- 经验性：添加实际使用经验表述（如"实际应用中"、"使用中发现"），至少1处经验性表述
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- 权威性：添加来源占位（数据来源、案例来源、标准来源），至少2处来源占位
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- 可信度：明确标注不确定信息，避免编造数据，使用占位建议
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【开始优化】
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"""
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# 根据选择的优化技巧增强 Prompt
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if opt_selected_technique_names:
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opt_technique_manager = OptimizationTechniqueManager()
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opt_technique_ids = opt_technique_manager.get_technique_ids_by_names(
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[
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name.split(" ", 1)[1] if " " in name else name
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for name in opt_selected_technique_names
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]
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)
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optimize_prompt_template = opt_technique_manager.enhance_prompt(
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optimize_prompt_template, opt_technique_ids
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)
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# 对超长文章给出提醒，避免模型上下文溢出
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if len(original_article) > 8000:
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st.warning(
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"当前文章长度较长（超过 8000 字符），可能导致大模型上下文溢出或响应失败。"
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" 建议适当拆分文章后分别优化。"
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)
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optimize_prompt = PromptTemplate.from_template(optimize_prompt_template)
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try:
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with st.spinner("优化中..."):
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chain = optimize_prompt | gen_llm | StrOutputParser()
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# 准备输入文本用于成本估算
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input_text = optimize_prompt.template.format(
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original_article=original_article[
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:500
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], # 只取前500字符用于估算
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brand=brand,
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advantages=advantages,
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platform=target_platform,
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)
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result = chain.invoke(
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{
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"original_article": original_article,
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"brand": brand,
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"advantages": advantages,
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"platform": target_platform,
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}
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)
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# 记录成本
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if gen_llm:
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try:
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model_name = (
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getattr(gen_llm, "model_name", None)
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or getattr(gen_llm, "model", None)
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or model_defaults(cfg["gen_provider"])
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)
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provider = cfg["gen_provider"]
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record_api_cost(
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operation_type="优化",
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provider=provider,
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model=model_name,
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input_text=original_article[
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:1000
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], # 使用实际输入文本的前1000字符
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output_text=result,
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platform=target_platform,
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brand=brand,
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)
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except Exception:
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# 记录成本失败不影响主流程
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pass
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if "【优化后文章】" in result and "【变更说明】" in result:
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optimized_article = (
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result.split("【优化后文章】", 1)[1]
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.split("【变更说明】", 1)[0]
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.strip()
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)
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changes = result.split("【变更说明】", 1)[1].strip()
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|||
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else:
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optimized_article = result.strip()
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changes = "无详细变更说明（模型未按模板输出）。"
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st.session_state.optimized_article = optimized_article
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st.session_state.opt_changes = changes
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# 保存到数据库
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try:
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storage.save_optimization(
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original_article,
|
|||
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optimized_article,
|
|||
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changes,
|
|||
|
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target_platform,
|
|||
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brand,
|
|||
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)
|
|||
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except Exception as e:
|
|||
|
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st.warning(f"优化完成，但保存到数据库时出错：{e}")
|
|||
|
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except Exception as e:
|
|||
|
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st.error(f"文章优化失败：{e}")
|
|||
|
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|
|||
|
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# === 优化结果 & 质量评估 ===
|
|||
|
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if st.session_state.optimized_article:
|
|||
|
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st.markdown("---")
|
|||
|
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st.markdown("#### 📝 优化结果")
|
|||
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|||
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# 结果 Tabs：优化后文章 / 变更说明
|
|||
|
|
result_tab1, result_tab2 = st.tabs(["📝 优化后文章", "🧾 变更说明"])
|
|||
|
|
with result_tab1:
|
|||
|
|
markdown_platforms = ["GitHub", "微信公众号", "百家号", "网易号", "企鹅号", "简书"]
|
|||
|
|
if any(p in st.session_state.opt_platform for p in markdown_platforms):
|
|||
|
|
st.code(st.session_state.optimized_article, language="markdown")
|
|||
|
|
else:
|
|||
|
|
st.markdown(st.session_state.optimized_article)
|
|||
|
|
|
|||
|
|
# 确定文件扩展名
|
|||
|
|
ext = (
|
|||
|
|
"md"
|
|||
|
|
if any(p in st.session_state.opt_platform for p in markdown_platforms)
|
|||
|
|
else "txt"
|
|||
|
|
)
|
|||
|
|
st.download_button(
|
|||
|
|
"下载优化版",
|
|||
|
|
st.session_state.optimized_article,
|
|||
|
|
f"{sanitize_filename(brand,40)}_优化文章.{ext}",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="opt_dl",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with result_tab2:
|
|||
|
|
st.markdown("#### 变更说明")
|
|||
|
|
st.markdown(st.session_state.opt_changes)
|
|||
|
|
|
|||
|
|
# 提供简单的版本回退能力
|
|||
|
|
if (
|
|||
|
|
st.session_state.get("optimized_article_backup")
|
|||
|
|
and st.session_state.optimized_article_backup
|
|||
|
|
!= st.session_state.optimized_article
|
|||
|
|
):
|
|||
|
|
if st.button("恢复至强化前版本", key="opt_restore_backup"):
|
|||
|
|
st.session_state.optimized_article = (
|
|||
|
|
st.session_state.optimized_article_backup
|
|||
|
|
)
|
|||
|
|
st.toast("已恢复至强化前版本。")
|
|||
|
|
|
|||
|
|
st.markdown(
|
|||
|
|
"可选步骤：对优化后的文章进行质量评估与再强化（会调用额外模型）。"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# E-E-A-T 评估和强化区域
|
|||
|
|
st.markdown("#### 🎯 E-E-A-T 强化 + 来源占位")
|
|||
|
|
st.caption("评估和强化内容的专业性、经验性、权威性、可信度")
|
|||
|
|
|
|||
|
|
eeat_col1, eeat_col2 = st.columns(2)
|
|||
|
|
|
|||
|
|
with eeat_col1:
|
|||
|
|
assess_eeat_btn = st.button(
|
|||
|
|
"📊 评估 E-E-A-T",
|
|||
|
|
use_container_width=True,
|
|||
|
|
disabled=(not st.session_state.cfg_valid) or (gen_llm is None),
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with eeat_col2:
|
|||
|
|
enhance_eeat_btn = st.button(
|
|||
|
|
"✨ 强化 E-E-A-T",
|
|||
|
|
use_container_width=True,
|
|||
|
|
disabled=(not st.session_state.cfg_valid) or (gen_llm is None),
|
|||
|
|
)
|
|||
|
|
st.caption("强化会覆盖当前优化结果，建议先下载备份。")
|
|||
|
|
|
|||
|
|
# 初始化 E-E-A-T 相关状态
|
|||
|
|
ss_init("eeat_assessment", None)
|
|||
|
|
ss_init("eeat_enhanced_content", "")
|
|||
|
|
ss_init("eeat_source_placeholders", [])
|
|||
|
|
ss_init("optimized_article_backup", "")
|
|||
|
|
|
|||
|
|
# E-E-A-T 评估
|
|||
|
|
if assess_eeat_btn and gen_llm:
|
|||
|
|
eeat_enhancer = EEATEnhancer()
|
|||
|
|
with st.spinner("正在评估 E-E-A-T..."):
|
|||
|
|
try:
|
|||
|
|
score_chain = (
|
|||
|
|
PromptTemplate.from_template("{input}")
|
|||
|
|
| gen_llm
|
|||
|
|
| StrOutputParser()
|
|||
|
|
)
|
|||
|
|
assessment = eeat_enhancer.assess_eeat(
|
|||
|
|
st.session_state.optimized_article,
|
|||
|
|
brand,
|
|||
|
|
advantages,
|
|||
|
|
st.session_state.opt_platform,
|
|||
|
|
score_chain,
|
|||
|
|
)
|
|||
|
|
st.session_state.eeat_assessment = assessment
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"E-E-A-T 评估失败：{e}")
|
|||
|
|
|
|||
|
|
# E-E-A-T 强化（带备份与安全校验）
|
|||
|
|
if enhance_eeat_btn and gen_llm:
|
|||
|
|
eeat_enhancer = EEATEnhancer()
|
|||
|
|
st.session_state.optimized_article_backup = (
|
|||
|
|
st.session_state.optimized_article
|
|||
|
|
)
|
|||
|
|
with st.spinner("正在强化 E-E-A-T..."):
|
|||
|
|
try:
|
|||
|
|
enhance_chain = (
|
|||
|
|
PromptTemplate.from_template("{input}")
|
|||
|
|
| gen_llm
|
|||
|
|
| StrOutputParser()
|
|||
|
|
)
|
|||
|
|
enhanced = eeat_enhancer.enhance_eeat(
|
|||
|
|
st.session_state.optimized_article,
|
|||
|
|
brand,
|
|||
|
|
advantages,
|
|||
|
|
st.session_state.opt_platform,
|
|||
|
|
enhance_chain,
|
|||
|
|
)
|
|||
|
|
new_content = enhanced.get("enhanced_content", "") or ""
|
|||
|
|
if not new_content.strip() or len(new_content.strip()) < 100:
|
|||
|
|
st.error(
|
|||
|
|
"E-E-A-T 强化失败：模型返回内容异常，已保留强化前版本。"
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
st.session_state.eeat_enhanced_content = new_content
|
|||
|
|
st.session_state.eeat_source_placeholders = enhanced.get(
|
|||
|
|
"source_placeholders", []
|
|||
|
|
)
|
|||
|
|
st.session_state.optimized_article = new_content
|
|||
|
|
st.success(
|
|||
|
|
f"✅ E-E-A-T 强化完成！已添加 {len(st.session_state.eeat_source_placeholders)} 个来源占位"
|
|||
|
|
)
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"E-E-A-T 强化失败：{e}")
|
|||
|
|
|
|||
|
|
# 显示 E-E-A-T 评估结果
|
|||
|
|
if st.session_state.eeat_assessment:
|
|||
|
|
assessment = st.session_state.eeat_assessment
|
|||
|
|
scores = assessment.get("eeat_scores", {})
|
|||
|
|
total_score = scores.get("total", 0)
|
|||
|
|
eeat_enhancer = EEATEnhancer()
|
|||
|
|
level, color = eeat_enhancer.get_eeat_level(total_score)
|
|||
|
|
|
|||
|
|
st.markdown("##### 📊 E-E-A-T 评估结果")
|
|||
|
|
col1, col2, col3, col4, col5 = st.columns(5)
|
|||
|
|
with col1:
|
|||
|
|
st.metric("总分", f"{total_score}/100", delta=level, delta_color="off")
|
|||
|
|
with col2:
|
|||
|
|
st.metric("专业性", f"{scores.get('expertise', 0)}/25")
|
|||
|
|
with col3:
|
|||
|
|
st.metric("经验性", f"{scores.get('experience', 0)}/25")
|
|||
|
|
with col4:
|
|||
|
|
st.metric("权威性", f"{scores.get('authoritativeness', 0)}/25")
|
|||
|
|
with col5:
|
|||
|
|
st.metric("可信度", f"{scores.get('trustworthiness', 0)}/25")
|
|||
|
|
|
|||
|
|
# 详细评估和改进建议
|
|||
|
|
with st.container(border=True):
|
|||
|
|
st.markdown("##### 📝 详细评估与改进建议")
|
|||
|
|
details = assessment.get("details", {})
|
|||
|
|
improvements = assessment.get("improvements", [])
|
|||
|
|
source_suggestions = assessment.get("source_suggestions", [])
|
|||
|
|
|
|||
|
|
st.markdown("**详细评估：**")
|
|||
|
|
st.markdown(f"- **专业性**：{details.get('expertise', '无')}")
|
|||
|
|
st.markdown(f"- **经验性**：{details.get('experience', '无')}")
|
|||
|
|
st.markdown(f"- **权威性**：{details.get('authoritativeness', '无')}")
|
|||
|
|
st.markdown(f"- **可信度**：{details.get('trustworthiness', '无')}")
|
|||
|
|
|
|||
|
|
if improvements:
|
|||
|
|
st.markdown("**💡 改进建议：**")
|
|||
|
|
for improvement in improvements:
|
|||
|
|
st.markdown(f"- {improvement}")
|
|||
|
|
|
|||
|
|
if source_suggestions:
|
|||
|
|
st.markdown("**📚 来源占位建议：**")
|
|||
|
|
for suggestion in source_suggestions:
|
|||
|
|
st.markdown(f"- {suggestion}")
|
|||
|
|
|
|||
|
|
# 来源占位检查
|
|||
|
|
placeholders = assessment.get("source_placeholders", {})
|
|||
|
|
if placeholders:
|
|||
|
|
st.markdown("**✅ 已检测到的来源占位：**")
|
|||
|
|
if placeholders.get("data_sources"):
|
|||
|
|
st.markdown(
|
|||
|
|
f"- 数据来源：{len(placeholders['data_sources'])} 处"
|
|||
|
|
)
|
|||
|
|
if placeholders.get("case_sources"):
|
|||
|
|
st.markdown(
|
|||
|
|
f"- 案例来源：{len(placeholders['case_sources'])} 处"
|
|||
|
|
)
|
|||
|
|
if placeholders.get("standard_sources"):
|
|||
|
|
st.markdown(
|
|||
|
|
f"- 标准来源：{len(placeholders['standard_sources'])} 处"
|
|||
|
|
)
|
|||
|
|
if placeholders.get("expert_opinions"):
|
|||
|
|
st.markdown(
|
|||
|
|
f"- 专家观点：{len(placeholders['expert_opinions'])} 处"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 显示 E-E-A-T 强化后的来源占位清单
|
|||
|
|
if st.session_state.eeat_source_placeholders:
|
|||
|
|
with st.container(border=True):
|
|||
|
|
st.markdown("##### 📚 来源占位清单")
|
|||
|
|
for placeholder in st.session_state.eeat_source_placeholders:
|
|||
|
|
st.markdown(f"- {placeholder}")
|
|||
|
|
|
|||
|
|
# 事实密度 + 结构化块评估和强化
|
|||
|
|
st.markdown("---")
|
|||
|
|
st.markdown("#### 📊 事实密度 + 结构化块")
|
|||
|
|
st.caption("评估和强化内容的事实信息密度和结构化程度")
|
|||
|
|
|
|||
|
|
fact_col1, fact_col2 = st.columns(2)
|
|||
|
|
|
|||
|
|
with fact_col1:
|
|||
|
|
assess_opt_fact = st.button(
|
|||
|
|
"📊 评估事实密度",
|
|||
|
|
use_container_width=True,
|
|||
|
|
disabled=(not st.session_state.cfg_valid) or (gen_llm is None),
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with fact_col2:
|
|||
|
|
enhance_opt_fact = st.button(
|
|||
|
|
"✨ 强化事实密度",
|
|||
|
|
use_container_width=True,
|
|||
|
|
disabled=(not st.session_state.cfg_valid) or (gen_llm is None),
|
|||
|
|
)
|
|||
|
|
st.caption("强化会覆盖当前优化结果，建议先下载备份。")
|
|||
|
|
|
|||
|
|
# 初始化事实密度状态
|
|||
|
|
ss_init("opt_fact_assessment", None)
|
|||
|
|
ss_init("opt_fact_enhanced", "")
|
|||
|
|
ss_init("opt_fact_details", [])
|
|||
|
|
|
|||
|
|
# 事实密度评估
|
|||
|
|
if assess_opt_fact and gen_llm:
|
|||
|
|
fact_enhancer = FactDensityEnhancer()
|
|||
|
|
with st.spinner("正在评估事实密度和结构化块..."):
|
|||
|
|
try:
|
|||
|
|
score_chain = (
|
|||
|
|
PromptTemplate.from_template("{input}")
|
|||
|
|
| gen_llm
|
|||
|
|
| StrOutputParser()
|
|||
|
|
)
|
|||
|
|
assessment = fact_enhancer.assess_fact_density(
|
|||
|
|
st.session_state.optimized_article,
|
|||
|
|
brand,
|
|||
|
|
advantages,
|
|||
|
|
st.session_state.opt_platform,
|
|||
|
|
score_chain,
|
|||
|
|
)
|
|||
|
|
st.session_state.opt_fact_assessment = assessment
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"事实密度评估失败：{e}")
|
|||
|
|
|
|||
|
|
# 事实密度强化（带备份与安全校验）
|
|||
|
|
if enhance_opt_fact and gen_llm:
|
|||
|
|
fact_enhancer = FactDensityEnhancer()
|
|||
|
|
st.session_state.optimized_article_backup = (
|
|||
|
|
st.session_state.optimized_article
|
|||
|
|
)
|
|||
|
|
with st.spinner("正在强化事实密度和结构化块..."):
|
|||
|
|
try:
|
|||
|
|
enhance_chain = (
|
|||
|
|
PromptTemplate.from_template("{input}")
|
|||
|
|
| gen_llm
|
|||
|
|
| StrOutputParser()
|
|||
|
|
)
|
|||
|
|
enhanced = fact_enhancer.enhance_fact_density(
|
|||
|
|
st.session_state.optimized_article,
|
|||
|
|
brand,
|
|||
|
|
advantages,
|
|||
|
|
st.session_state.opt_platform,
|
|||
|
|
enhance_chain,
|
|||
|
|
)
|
|||
|
|
new_content = enhanced.get("enhanced_content", "") or ""
|
|||
|
|
if not new_content.strip() or len(new_content.strip()) < 100:
|
|||
|
|
st.error(
|
|||
|
|
"事实密度强化失败：模型返回内容异常，已保留强化前版本。"
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
st.session_state.opt_fact_enhanced = new_content
|
|||
|
|
st.session_state.opt_fact_details = enhanced.get(
|
|||
|
|
"enhancement_details", []
|
|||
|
|
)
|
|||
|
|
st.session_state.optimized_article = new_content
|
|||
|
|
st.success(
|
|||
|
|
f"✅ 事实密度强化完成！已添加 {len(st.session_state.opt_fact_details)} 处事实信息和结构化块"
|
|||
|
|
)
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"事实密度强化失败：{e}")
|
|||
|
|
|
|||
|
|
# 显示事实密度评估结果
|
|||
|
|
if st.session_state.opt_fact_assessment:
|
|||
|
|
assessment = st.session_state.opt_fact_assessment
|
|||
|
|
scores = assessment.get("scores", {})
|
|||
|
|
total_score = scores.get("total", 0)
|
|||
|
|
fact_enhancer = FactDensityEnhancer()
|
|||
|
|
level, color = fact_enhancer.get_score_level(total_score)
|
|||
|
|
|
|||
|
|
st.markdown("##### 📊 事实密度 + 结构化评估结果")
|
|||
|
|
col1, col2, col3 = st.columns(3)
|
|||
|
|
with col1:
|
|||
|
|
st.metric("总分", f"{total_score}/100", delta=level, delta_color="off")
|
|||
|
|
with col2:
|
|||
|
|
st.metric("事实密度", f"{scores.get('fact_density', 0)}/50")
|
|||
|
|
with col3:
|
|||
|
|
st.metric("结构化", f"{scores.get('structure', 0)}/50")
|
|||
|
|
|
|||
|
|
# 使用 tabs 组织分析结果
|
|||
|
|
fact_analysis = assessment.get("fact_analysis", {})
|
|||
|
|
structure_analysis = assessment.get("structure_analysis", {})
|
|||
|
|
has_details = bool(st.session_state.get("opt_fact_details"))
|
|||
|
|
|
|||
|
|
# 构建可用的 tabs
|
|||
|
|
tab_labels = []
|
|||
|
|
if fact_analysis:
|
|||
|
|
tab_labels.append("📈 事实密度")
|
|||
|
|
if structure_analysis:
|
|||
|
|
tab_labels.append("🏗️ 结构化块")
|
|||
|
|
if has_details:
|
|||
|
|
tab_labels.append("📝 强化详情")
|
|||
|
|
|
|||
|
|
if tab_labels:
|
|||
|
|
analysis_tabs = st.tabs(tab_labels)
|
|||
|
|
tab_idx = 0
|
|||
|
|
|
|||
|
|
# 事实密度分析
|
|||
|
|
if fact_analysis:
|
|||
|
|
with analysis_tabs[tab_idx]:
|
|||
|
|
with st.container(border=True):
|
|||
|
|
col1, col2, col3, col4, col5, col6 = st.columns(6)
|
|||
|
|
with col1:
|
|||
|
|
st.metric("数据", fact_analysis.get("data_count", 0))
|
|||
|
|
with col2:
|
|||
|
|
st.metric("案例", fact_analysis.get("case_count", 0))
|
|||
|
|
with col3:
|
|||
|
|
st.metric("标准", fact_analysis.get("standard_count", 0))
|
|||
|
|
with col4:
|
|||
|
|
st.metric(
|
|||
|
|
"对比", fact_analysis.get("comparison_count", 0)
|
|||
|
|
)
|
|||
|
|
with col5:
|
|||
|
|
st.metric("时间", fact_analysis.get("time_count", 0))
|
|||
|
|
with col6:
|
|||
|
|
st.metric("来源", fact_analysis.get("source_count", 0))
|
|||
|
|
|
|||
|
|
missing_facts = fact_analysis.get("missing_facts", [])
|
|||
|
|
if missing_facts:
|
|||
|
|
st.markdown("**缺失的事实类型：**")
|
|||
|
|
for fact in missing_facts:
|
|||
|
|
st.markdown(f"- {fact}")
|
|||
|
|
tab_idx += 1
|
|||
|
|
|
|||
|
|
# 结构化分析
|
|||
|
|
if structure_analysis:
|
|||
|
|
with analysis_tabs[tab_idx]:
|
|||
|
|
with st.container(border=True):
|
|||
|
|
col1, col2, col3, col4 = st.columns(4)
|
|||
|
|
with col1:
|
|||
|
|
st.markdown(
|
|||
|
|
f"**标题层级**：{'✅' if structure_analysis.get('has_title') else '❌'}"
|
|||
|
|
)
|
|||
|
|
st.markdown(
|
|||
|
|
f"**结论摘要**：{'✅' if structure_analysis.get('has_summary') else '❌'}"
|
|||
|
|
)
|
|||
|
|
with col2:
|
|||
|
|
st.markdown(
|
|||
|
|
f"**清单列表**：{'✅' if structure_analysis.get('has_list') else '❌'}"
|
|||
|
|
)
|
|||
|
|
st.markdown(
|
|||
|
|
f"**FAQ部分**：{'✅' if structure_analysis.get('has_faq') else '❌'}"
|
|||
|
|
)
|
|||
|
|
with col3:
|
|||
|
|
st.markdown(
|
|||
|
|
f"**代码块**：{'✅' if structure_analysis.get('has_code') else '❌'}"
|
|||
|
|
)
|
|||
|
|
st.markdown(
|
|||
|
|
f"**对比表格**：{'✅' if structure_analysis.get('has_table') else '❌'}"
|
|||
|
|
)
|
|||
|
|
with col4:
|
|||
|
|
st.markdown(
|
|||
|
|
f"**步骤说明**：{'✅' if structure_analysis.get('has_steps') else '❌'}"
|
|||
|
|
)
|
|||
|
|
st.markdown(
|
|||
|
|
f"**总结部分**：{'✅' if structure_analysis.get('has_conclusion') else '❌'}"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
missing_blocks = structure_analysis.get("missing_blocks", [])
|
|||
|
|
if missing_blocks:
|
|||
|
|
st.markdown("**缺失的结构化块：**")
|
|||
|
|
for block in missing_blocks:
|
|||
|
|
st.markdown(f"- {block}")
|
|||
|
|
tab_idx += 1
|
|||
|
|
|
|||
|
|
# 强化详情
|
|||
|
|
if has_details:
|
|||
|
|
with analysis_tabs[tab_idx]:
|
|||
|
|
with st.container(border=True):
|
|||
|
|
for detail in st.session_state.opt_fact_details:
|
|||
|
|
st.markdown(f"- {detail}")
|
|||
|
|
|
|||
|
|
# === 高级：结构化 Schema & 技术配置（折叠区） ===
|
|||
|
|
with st.expander(
|
|||
|
|
"高级：结构化 Schema & 技术 SEO 配置（可选）", expanded=False
|
|||
|
|
):
|
|||
|
|
# 结构化数据生成
|
|||
|
|
st.markdown("**📋 结构化数据生成**")
|
|||
|
|
st.caption(
|
|||
|
|
"生成符合 Schema.org 规范的 JSON-LD 代码，提升品牌在 AI 模型中的实体识别和权威性"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with st.container(border=True):
|
|||
|
|
schema_col1, schema_col2 = st.columns([2, 1])
|
|||
|
|
|
|||
|
|
with schema_col1:
|
|||
|
|
schema_type = st.selectbox(
|
|||
|
|
"Schema 类型",
|
|||
|
|
[
|
|||
|
|
"Organization（组织/公司）",
|
|||
|
|
"SoftwareApplication（软件应用）",
|
|||
|
|
"Product（产品）",
|
|||
|
|
"Service（服务）",
|
|||
|
|
"组合（Organization + SoftwareApplication）",
|
|||
|
|
],
|
|||
|
|
index=1,
|
|||
|
|
key="schema_type_sel",
|
|||
|
|
help="选择适合您品牌的 Schema 类型",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with schema_col2:
|
|||
|
|
generate_schema_btn = st.button(
|
|||
|
|
"🚀 生成 JSON-LD",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="generate_schema_btn",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 初始化 JSON-LD 相关状态
|
|||
|
|
ss_init("generated_json_ld", None)
|
|||
|
|
ss_init("generated_html_script", None)
|
|||
|
|
|
|||
|
|
# 生成 JSON-LD（带基础信息校验）
|
|||
|
|
if generate_schema_btn:
|
|||
|
|
if not brand or not advantages or len(brand.strip()) < 2:
|
|||
|
|
st.warning(
|
|||
|
|
"请先在基础信息中填写品牌名称和优势，再生成 Schema。"
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
try:
|
|||
|
|
schema_gen = SchemaGenerator()
|
|||
|
|
|
|||
|
|
if schema_type == "Organization（组织/公司）":
|
|||
|
|
schema_dict = schema_gen.generate_organization_schema(
|
|||
|
|
brand_name=brand,
|
|||
|
|
description=advantages,
|
|||
|
|
url="", # 用户可以在生成后手动添加
|
|||
|
|
logo="",
|
|||
|
|
founding_date="",
|
|||
|
|
)
|
|||
|
|
elif schema_type == "SoftwareApplication（软件应用）":
|
|||
|
|
schema_dict = schema_gen.generate_software_application_schema(
|
|||
|
|
brand_name=brand,
|
|||
|
|
application_name=brand,
|
|||
|
|
description=advantages,
|
|||
|
|
url="",
|
|||
|
|
application_category="BusinessApplication",
|
|||
|
|
operating_system="Web",
|
|||
|
|
)
|
|||
|
|
elif schema_type == "Product（产品）":
|
|||
|
|
schema_dict = schema_gen.generate_product_schema(
|
|||
|
|
brand_name=brand,
|
|||
|
|
product_name=brand,
|
|||
|
|
description=advantages,
|
|||
|
|
url="",
|
|||
|
|
)
|
|||
|
|
elif schema_type == "Service（服务）":
|
|||
|
|
schema_dict = schema_gen.generate_service_schema(
|
|||
|
|
brand_name=brand,
|
|||
|
|
service_name=brand,
|
|||
|
|
description=advantages,
|
|||
|
|
url="",
|
|||
|
|
)
|
|||
|
|
else: # 组合
|
|||
|
|
schema_dict = schema_gen.generate_combined_schema(
|
|||
|
|
brand_name=brand,
|
|||
|
|
advantages=advantages,
|
|||
|
|
schema_types=[
|
|||
|
|
"Organization",
|
|||
|
|
"SoftwareApplication",
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 格式化输出
|
|||
|
|
json_ld_code = schema_gen.format_json_ld(schema_dict)
|
|||
|
|
html_script = schema_gen.generate_html_script_tag(
|
|||
|
|
schema_dict
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
st.session_state.generated_json_ld = json_ld_code
|
|||
|
|
st.session_state.generated_html_script = html_script
|
|||
|
|
|
|||
|
|
st.success("✅ JSON-LD Schema 生成成功！")
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"JSON-LD 生成失败：{e}")
|
|||
|
|
|
|||
|
|
# 显示生成的 JSON-LD
|
|||
|
|
if st.session_state.generated_json_ld:
|
|||
|
|
st.markdown("##### 📄 JSON-LD 代码")
|
|||
|
|
st.code(st.session_state.generated_json_ld, language="json")
|
|||
|
|
|
|||
|
|
st.markdown("##### 📄 HTML Script 标签（可直接嵌入网页）")
|
|||
|
|
st.code(st.session_state.generated_html_script, language="html")
|
|||
|
|
|
|||
|
|
# 下载按钮
|
|||
|
|
col1, col2 = st.columns(2)
|
|||
|
|
with col1:
|
|||
|
|
st.download_button(
|
|||
|
|
"下载 JSON-LD",
|
|||
|
|
st.session_state.generated_json_ld,
|
|||
|
|
f"{sanitize_filename(brand,40)}_schema.json",
|
|||
|
|
mime="application/json",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="schema_dl_json",
|
|||
|
|
)
|
|||
|
|
with col2:
|
|||
|
|
st.download_button(
|
|||
|
|
"下载 HTML Script",
|
|||
|
|
st.session_state.generated_html_script,
|
|||
|
|
f"{sanitize_filename(brand,40)}_schema.html",
|
|||
|
|
mime="text/html",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="schema_dl_html",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
st.info(
|
|||
|
|
"💡 **使用说明**：将 HTML Script 标签复制到您的官网 `<head>` 部分，或将 JSON-LD 代码添加到 GitHub README 中。"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 技术配置生成
|
|||
|
|
st.markdown("---")
|
|||
|
|
st.markdown("**⚙️ 技术配置生成**")
|
|||
|
|
st.caption("生成 robots.txt、sitemap.xml 等技术配置文件，提升内容收录效果（提升 20-30%）")
|
|||
|
|
|
|||
|
|
with st.container(border=True):
|
|||
|
|
config_tab1, config_tab2 = st.tabs(["🤖 robots.txt", "🗺️ sitemap.xml"])
|
|||
|
|
|
|||
|
|
# robots.txt 生成
|
|||
|
|
with config_tab1:
|
|||
|
|
st.markdown("##### 🤖 robots.txt 生成")
|
|||
|
|
st.caption("控制搜索引擎爬虫的访问权限，提升内容收录效果")
|
|||
|
|
|
|||
|
|
robots_col1, robots_col2 = st.columns([2, 1])
|
|||
|
|
|
|||
|
|
with robots_col1:
|
|||
|
|
robots_base_url = st.text_input(
|
|||
|
|
"网站基础 URL",
|
|||
|
|
value="",
|
|||
|
|
key="robots_base_url",
|
|||
|
|
placeholder="https://example.com",
|
|||
|
|
help="您的网站基础 URL（如 https://example.com）",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with robots_col2:
|
|||
|
|
generate_robots_btn = st.button(
|
|||
|
|
"🚀 生成 robots.txt",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="generate_robots_btn",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 允许/禁止路径配置
|
|||
|
|
robots_config_col1, robots_config_col2 = st.columns(2)
|
|||
|
|
|
|||
|
|
with robots_config_col1:
|
|||
|
|
allow_paths_input = st.text_area(
|
|||
|
|
"允许爬取的路径（每行一个）",
|
|||
|
|
value="/\n/blog\n/docs",
|
|||
|
|
key="robots_allow_paths",
|
|||
|
|
help="每行一个路径，如 /、/blog、/docs",
|
|||
|
|
height=100,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with robots_config_col2:
|
|||
|
|
disallow_paths_input = st.text_area(
|
|||
|
|
"禁止爬取的路径（每行一个）",
|
|||
|
|
value="/admin\n/private\n/api",
|
|||
|
|
key="robots_disallow_paths",
|
|||
|
|
help="每行一个路径，如 /admin、/private、/api",
|
|||
|
|
height=100,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 初始化状态
|
|||
|
|
ss_init("generated_robots_txt", None)
|
|||
|
|
|
|||
|
|
# 生成 robots.txt（带 URL 校验）
|
|||
|
|
if generate_robots_btn:
|
|||
|
|
if not robots_base_url.strip():
|
|||
|
|
st.error("请填写网站基础 URL（如 https://example.com）。")
|
|||
|
|
else:
|
|||
|
|
if not robots_base_url.startswith("http"):
|
|||
|
|
st.warning(
|
|||
|
|
"建议使用完整 URL（含 http/https），避免 robots.txt 中出现无效链接。"
|
|||
|
|
)
|
|||
|
|
try:
|
|||
|
|
config_gen = TechnicalConfigGenerator()
|
|||
|
|
|
|||
|
|
# 解析允许路径
|
|||
|
|
allow_paths = (
|
|||
|
|
[
|
|||
|
|
p.strip()
|
|||
|
|
for p in allow_paths_input.split("\n")
|
|||
|
|
if p.strip()
|
|||
|
|
]
|
|||
|
|
if allow_paths_input
|
|||
|
|
else None
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 解析禁止路径
|
|||
|
|
disallow_paths = (
|
|||
|
|
[
|
|||
|
|
p.strip()
|
|||
|
|
for p in disallow_paths_input.split("\n")
|
|||
|
|
if p.strip()
|
|||
|
|
]
|
|||
|
|
if disallow_paths_input
|
|||
|
|
else None
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
robots_txt = config_gen.generate_robots_txt(
|
|||
|
|
base_url=robots_base_url,
|
|||
|
|
allow_paths=allow_paths,
|
|||
|
|
disallow_paths=disallow_paths,
|
|||
|
|
sitemap_url="", # 自动生成
|
|||
|
|
user_agent="*",
|
|||
|
|
crawl_delay=None,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
st.session_state.generated_robots_txt = robots_txt
|
|||
|
|
st.success("✅ robots.txt 生成成功！")
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"robots.txt 生成失败：{e}")
|
|||
|
|
|
|||
|
|
# 显示生成的 robots.txt
|
|||
|
|
if st.session_state.generated_robots_txt:
|
|||
|
|
st.markdown("##### 📄 robots.txt 内容")
|
|||
|
|
st.code(st.session_state.generated_robots_txt, language="text")
|
|||
|
|
|
|||
|
|
st.download_button(
|
|||
|
|
"下载 robots.txt",
|
|||
|
|
st.session_state.generated_robots_txt,
|
|||
|
|
"robots.txt",
|
|||
|
|
mime="text/plain",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="robots_dl",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
st.info(
|
|||
|
|
"💡 **使用说明**：将 robots.txt 文件上传到您网站的根目录（如 https://example.com/robots.txt）"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# sitemap.xml 生成
|
|||
|
|
with config_tab2:
|
|||
|
|
st.markdown("##### 🗺️ sitemap.xml 生成")
|
|||
|
|
st.caption("帮助搜索引擎发现和索引您的所有页面，提升内容收录效果")
|
|||
|
|
|
|||
|
|
sitemap_col1, sitemap_col2 = st.columns([2, 1])
|
|||
|
|
|
|||
|
|
with sitemap_col1:
|
|||
|
|
sitemap_base_url = st.text_input(
|
|||
|
|
"网站基础 URL",
|
|||
|
|
value="",
|
|||
|
|
key="sitemap_base_url",
|
|||
|
|
placeholder="https://example.com",
|
|||
|
|
help="您的网站基础 URL（如 https://example.com）",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
with sitemap_col2:
|
|||
|
|
generate_sitemap_btn = st.button(
|
|||
|
|
"🚀 生成 sitemap.xml",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="generate_sitemap_btn",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 选择数据源
|
|||
|
|
sitemap_source = st.radio(
|
|||
|
|
"数据源",
|
|||
|
|
["基于关键词生成", "基于历史文章生成"],
|
|||
|
|
key="sitemap_source",
|
|||
|
|
horizontal=True,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 初始化状态
|
|||
|
|
ss_init("generated_sitemap_xml", None)
|
|||
|
|
|
|||
|
|
# 生成 sitemap.xml（带 URL 校验）
|
|||
|
|
if generate_sitemap_btn:
|
|||
|
|
if not sitemap_base_url.strip():
|
|||
|
|
st.error("请填写网站基础 URL（如 https://example.com）。")
|
|||
|
|
else:
|
|||
|
|
if not sitemap_base_url.startswith("http"):
|
|||
|
|
st.warning(
|
|||
|
|
"建议使用完整 URL（含 http/https），避免 sitemap.xml 中出现无效链接。"
|
|||
|
|
)
|
|||
|
|
try:
|
|||
|
|
config_gen = TechnicalConfigGenerator()
|
|||
|
|
|
|||
|
|
if sitemap_source == "基于关键词生成":
|
|||
|
|
# 基于关键词生成
|
|||
|
|
keywords_for_sitemap = (
|
|||
|
|
st.session_state.keywords
|
|||
|
|
if st.session_state.keywords
|
|||
|
|
else []
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
if not keywords_for_sitemap:
|
|||
|
|
st.warning(
|
|||
|
|
"⚠️ 请先在【1 关键词蒸馏】生成关键词，或选择【基于历史文章生成】"
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
sitemap_xml = (
|
|||
|
|
config_gen.generate_sitemap_xml(
|
|||
|
|
base_url=sitemap_base_url,
|
|||
|
|
keywords=keywords_for_sitemap,
|
|||
|
|
lastmod=None, # 使用当前日期
|
|||
|
|
changefreq="weekly",
|
|||
|
|
priority=0.8,
|
|||
|
|
)
|
|||
|
|
)
|
|||
|
|
st.session_state.generated_sitemap_xml = (
|
|||
|
|
sitemap_xml
|
|||
|
|
)
|
|||
|
|
st.success(
|
|||
|
|
f"✅ sitemap.xml 生成成功！包含 {len(keywords_for_sitemap)} 个 URL"
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
# 基于历史文章生成
|
|||
|
|
try:
|
|||
|
|
articles = storage.get_articles(brand=brand)
|
|||
|
|
|
|||
|
|
if not articles:
|
|||
|
|
st.warning(
|
|||
|
|
"⚠️ 暂无历史文章，请先生成内容，或选择【基于关键词生成】"
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
sitemap_xml = (
|
|||
|
|
config_gen.generate_sitemap_from_articles(
|
|||
|
|
base_url=sitemap_base_url,
|
|||
|
|
articles=articles,
|
|||
|
|
lastmod=None,
|
|||
|
|
changefreq="weekly",
|
|||
|
|
priority=0.8,
|
|||
|
|
)
|
|||
|
|
)
|
|||
|
|
st.session_state.generated_sitemap_xml = (
|
|||
|
|
sitemap_xml
|
|||
|
|
)
|
|||
|
|
st.success(
|
|||
|
|
f"✅ sitemap.xml 生成成功！包含 {len(articles)} 个 URL"
|
|||
|
|
)
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"获取历史文章失败：{e}")
|
|||
|
|
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(f"sitemap.xml 生成失败：{e}")
|
|||
|
|
|
|||
|
|
# 显示生成的 sitemap.xml
|
|||
|
|
if st.session_state.generated_sitemap_xml:
|
|||
|
|
st.markdown("##### 📄 sitemap.xml 内容")
|
|||
|
|
st.code(st.session_state.generated_sitemap_xml, language="xml")
|
|||
|
|
|
|||
|
|
st.download_button(
|
|||
|
|
"下载 sitemap.xml",
|
|||
|
|
st.session_state.generated_sitemap_xml,
|
|||
|
|
"sitemap.xml",
|
|||
|
|
mime="application/xml",
|
|||
|
|
use_container_width=True,
|
|||
|
|
key="sitemap_dl",
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
st.info(
|
|||
|
|
"💡 **使用说明**：将 sitemap.xml 文件上传到您网站的根目录（如 https://example.com/sitemap.xml），并在 Google Search Console 中提交"
|
|||
|
|
)
|
|||
|
|
|