repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 20h ago
dataease/SQLBot
🔥 基于大模型和 RAG 的智能问数系统，对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 46%Assemble Each RAG Generation Prompt from a Base Prompt Plus the Rules Each Question Needs - Towards Data Science →
- PossiblePossibly related (embedding) · 45%Setting Up Your Own Large Language Model - Towards Data Science →
- PossiblePossibly related (embedding) · 50%Any text-to-SQL benchmark should address difficulties of real-world data stores →
- PossiblePossibly related (embedding) · 52%Spider 2.0-AIFunc: Extending Real-World Text-to-SQL to AI-Native SQL Workflows →
- PossiblePossibly related (embedding) · 46%Show HN: Sqlsure – deterministic semantic checks for AI-generated SQL →
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Related across the graph
newsSetting Up Your Own Large Language Model - Towards Data SciencenewsAny text-to-SQL benchmark should address difficulties of real-world data storesnewsAssemble Each RAG Generation Prompt from a Base Prompt Plus the Rules Each Question Needs - Towards Data SciencepaperSpider 2.0-AIFunc: Extending Real-World Text-to-SQL to AI-Native SQL WorkflowsnewsShow HN: Sqlsure – deterministic semantic checks for AI-generated SQL