Lum1104/Understand-Anything+606 stars 24hREPO
anthropics/financial-services-plugins+396 stars 24hREPO
rohitg00/ai-engineering-from-scratch+331 stars 24hREPO
addyosmani/agent-skills+327 stars 24hREPO
colbymchenry/codegraph+327 stars 24hREPOLum1104/Understand-Anything+606 stars 24hREPOanthropics/financial-services-plugins+396 stars 24hREPOrohitg00/ai-engineering-from-scratch+331 stars 24hREPOaddyosmani/agent-skills+327 stars 24hREPOcolbymchenry/codegraph+327 stars 24hSemantic search finds results by meaning rather than exact keywords, comparing embeddings of the query and documents to surface conceptually similar matches.
Instead of matching literal words, semantic search embeds the query and the corpus into vectors and returns the nearest neighbours. That handles synonyms and paraphrase, and is the retrieval step behind most RAG systems.
In practice it is often combined with traditional keyword search — a hybrid approach — to get both conceptual recall and exact-term precision. Open-source vector databases provide the index that makes it fast.
FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature.
Incremental engine for long horizon agents 🌟 Star if you like it!
Claude + Obsidian knowledge companion. Persistent, compounding wiki vault based on Karpathy's LLM Wiki pattern. /wiki /save /autoresearch
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/