De la autor
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.
Instalare
npx skills add giuseppe-trisciuoglio/developer-kit --skill qdrant -a claude-code
Se instalează în .claude/skills/qdrant/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
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De ce 83
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Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
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- langchain4j-rag-implementation-patternsgiuseppe-trisciuoglio/developer-kitProvides Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j for Java. Generates document ingestion pipelines, embedding stores, vector search, and semantic search capabilities. Use when building chat-with-documents systems, document Q&A over PDFs or text files, AI assistants with knowledge bases, semantic search over document repositories, or knowledge-enhanced AI applications with source attribution.Altele★ 362
- vector-searchdatadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionImplement semantic vector search for construction data. Build AI-powered search using embeddings and vector databases (Qdrant, ChromaDB) for intelligent querying of specifications, standards, and project documents.Planificare★ 371
- vector-database-opsBagelHole/DevOps-Security-Agent-SkillsDeploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search workloads.Date★ 1.2K
- similarity-search-patternswshobson/agentsImplement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.Altele★ 41.6K
- langchain4j-testing-strategiesgiuseppe-trisciuoglio/developer-kitProvides unit test, integration test, and mock AI patterns for LangChain4j applications. Creates mock LLM responses, tests retrieval chains, validates RAG workflows, and implements Testcontainers-based integration tests for Java AI services. Use when unit testing AI services, integration testing LangChain4j components, mocking AI models, or testing LLM-based Java applications.Testare★ 362
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