feat: ChatBI 业界主流实现方案深度对比分析报告（阿里/腾讯/字节/帆软） - #2
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Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
…d customer cases Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
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…ernal service deployment architecture Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
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…abels (in-kernel, control-plane, sync-pipeline, external-service) Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
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…with阿里/腾讯/字节/帆软 comparison Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
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…cture diagram (HTML) Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
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…t architecture diagram Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
…, and value-demo test cases Co-authored-by: wangyangyang <XIDIANcoding@users.noreply.github.com>
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业界主流 ChatBI 深度技术架构与实现方案对比分析报告（阿里 / 腾讯 / 字节 / 帆软）
概述与核心发现
本报告针对业界主流对话式商业智能（ChatBI / Data Agent）的技术实现进行系统化拆解与横向对比，深入分析了 阿里云 Quick BI（智能小Q）、腾讯云 BI（智能小腾）、火山引擎 DataWind（Data Agent / ByteHouse） 以及 帆软 FineChatBI 的核心技术方案。
核心结论与行业共识：
产出文件
chatbi-industry-architecture-report.html：单页自包含独立 HTML 报告（四厂商对比）。tencent-chatbi-architecture.html：腾讯云 ChatBI 组件交互与分层部署架构图（含落地开发能力清单：MySQL+库内LLM 场景）。alibaba-chatbi-architecture.html：阿里云 Quick BI（智能小Q）组件交互与分层部署架构图（应用层 / AI中间层BI Agent / 自研领域模型层 / 知识与建模层 / BI基座引擎层 / 数据源层；L/K 总线与步骤对应；落地能力对照表）。build_chatbi_report.py：生成与更新 HTML 报告的代码脚本。