Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: embedding-vectors

영문 디렉토리

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

17K
Stars
87/100
신뢰
카테고리: rag-knowledge감사

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

15K
Stars
86/100
신뢰
카테고리: document-processing감사

AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding

9.7K
Stars
86/100
신뢰
카테고리: ml-automation감사
Yn77

A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.

6.6K
Stars
77/100
신뢰
카테고리: document-processing감사

Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.

5.2K
Stars
72/100
신뢰
카테고리: rag-knowledge감사

Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.

4.3K
Stars
80/100
신뢰
카테고리: rag-knowledge감사

Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

4.2K
Stars
83/100
신뢰
카테고리: rag-knowledge감사

MTEB: Massive Text Embedding Benchmark

3.3K
Stars
80/100
신뢰
카테고리: rag-knowledge감사

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

3.1K
Stars
77/100
신뢰
카테고리: data감사

🕵️‍♂️ (2-in-1) Email & Username OSINT suite for deep data extraction. Analyzes 240+ scan vectors (100+ email / 140+ username) for security research, investigations, and digital footprinting.

2.2K
Stars
84/100
신뢰
카테고리: security감사

Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available in cloud https://endee.io/

1.3K
Stars
83/100
신뢰
카테고리: rag-knowledge감사

Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.

1.3K
Stars
80/100
신뢰
카테고리: media-automation감사