Plugins
1 pluginResults for “re-embedding”
24 skills
neuralblitz Embeddings
Explains dense vector embeddings, their key concepts, common use cases, and best practices for semantic search and RAG applications.
1
github Qdrant Model Migration
Guides embedding model migration in Qdrant without downtime, covering alias swap, side-by-side, and hybrid search strategies.
36.2k
nvidia Vss Deploy Video Embedding
Deploy and operate the VSS 3.2 GA RT-Embed Video Embedding microservice using Docker Compose, covering GPU prerequisites, REST API usage for file uploads, text/video embeddings, live RTSP streams, Redis/Kafka/OTel integration, and troubleshooting.
2.2k · bundle
orchestra-research Sentence Transformers
Generate high-quality sentence and text embeddings for semantic similarity, clustering, and retrieval using 5000+ pre-trained models. Supports multilingual and domain-specific embeddings for RAG and semantic search.
10.4k · bundle
github Qdrant Search Quality
Diagnoses and improves Qdrant search relevance by isolating embedding model, configuration, or query strategy issues.
36.2k
nvidia Nemotron Retrieval Recipes
Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.
2.2k · bundle
More results
majiayu000 RAG
Builds Retrieval-Augmented Generation systems with document chunking, embedding generation, vector storage, and retrieval pipelines, including evaluation and optimization.
567 · bundle
github Qdrant Search Quality Diagnosis
Diagnoses Qdrant search quality issues by isolating causes like HNSW approximation, quantization, embedding model, or search pipeline problems.
36.2k
oyi77 Ruvector
Generates and manages vector embeddings for semantic search and RAG retrieval across knowledge bases, with self-learning capabilities.
10
orchestra-research Chroma
Store and query embeddings with metadata filtering, vector search, and full-text search using an open-source database that scales from notebooks to production.
10.4k · bundle
jeffallan RAG Architect
Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality.
10.4k · bundle
composiohq Openai Automation
Automate OpenAI API operations: generate text and multimodal responses with structured output, create embeddings, generate images, and list models via the Composio MCP integration.
66.9k
nvidia Tao Mine Aoi Images
Embeds target and source image parquets, then mines nearest-neighbour source images for augmentation in VCN AOI workflows.
2.2k · bundle
tools-only 014 API F0515c8f
Reference for configuring and using LangChain4j vector stores, covering setup, search, filtering, and ingestion.
7 · bundle
mukul975 Assessing Vector And Embedding Weaknesses
Test vector stores for embedding inversion, cross-tenant leakage, and poisoning.
24.6k · bundle
neuralblitz Langchain
Build LLM-powered applications with modular components for chains, agents, memory, and retrieval, supporting Python and JavaScript frameworks.
1
rootcastleco AI Engineer
Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.
6
alirezarezvani RAG Architect
Design, tune, and evaluate production RAG pipelines with deterministic tools for chunking, pipeline design, and retrieval evaluation.
20.4k · bundle
mukul975 Testing Prompt Injection In RAG Pipelines
Probe RAG applications for prompt injection via poisoned retrieved context and embedding manipulation.
24.6k · bundle
antigravity Arrowspace
Augments nearest-neighbour search with graph Laplacian features to retrieve items based on both semantic similarity and structural role.
42.4k
goldentrii Agent Recall
Provides persistent, compounding memory for AI agents across sessions using local markdown files, with optional Supabase-backed semantic search.
365 · bundle
joshuashepherd Book Chunk
Chunks a book into canonical retrieval units with heading-aware structure splitting, recursive token targets, and contextual prefixes for downstream RAG ingestion.
1
antigravity AI Engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search, multimodal AI, and enterprise integrations.
42.4k
antigravity Mesh Memory
Provides persistent, self-hosted semantic memory for AI agents via MCP, storing worklogs, decisions, and notes in PostgreSQL with pgvector for meaning-based retrieval across sessions.
42.4k