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Found 8 Skills
Provides Qdrant vector database integration patterns with LangChain4j. Handles embedding storage, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, semantic search, or recommendation engines.
Configure Qdrant vector database for GrepAI. Use this skill for high-performance vector search.
Sets up vector databases for semantic search including Pinecone, Chroma, pgvector, and Qdrant with embedding generation and similarity search. Use when users request "vector database", "semantic search", "embeddings storage", "Pinecone setup", or "similarity search".
Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similar
Vector database implementation for AI/ML applications, semantic search, and RAG systems. Use when building chatbots, search engines, recommendation systems, or similarity-based retrieval. Covers Qdrant (primary), Pinecone, Milvus, pgvector, Chroma, embedding generation (OpenAI, Voyage, Cohere), chunking strategies, and hybrid search patterns.
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
Build Retrieval-Augmented Generation systems with vector databases
Convert images (screenshots, photos, whiteboard) to Mermaid or DOT/Graphviz diagrams