🔍大模型应用开发实战一:RAG 技术全栈指南,在线阅读地址:https://datawhalechina.github.io/all-in-rag/
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Each channel contributes 0-1. Per-channel tiers: GitHub (breakout 1.0 / hot 0.7 / rising 0.4), HN (front-page 1.0 / ≥3 mentions 0.7 / 1-2 mentions 0.4), Bluesky (≥5 mentions 1.0 / 2-4 0.7 / 1 0.4), dev.to (≥3 articles 1.0 / 2 0.7 / 1 0.4), Reddit (corpus-normalized 48h velocity).
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Open Source AI Platform - AI Chat with advanced features that works with every LLM
LLM驱动的 A/H/美股智能分析器:多数据源行情 + 实时新闻 + LLM决策仪表盘 + 多渠道推送,零成本定时运行,纯白嫖. LLM-powered stock analysis system for A/H/US markets.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
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* Reddit bar shows a per-repo velocity proxy (raw score / 100); the score formula uses the corpus-normalized version so a single repo's bar may not match its contribution to the corpus-wide ranking.
Known repo, package, launch, and site surfaces.