Query vector databases and manage AI agents for RAG workflows.
npx skills add https://github.com/Maximilien-ai/weave-cli-skills --skill weave-search
Please help me install this Agent Skill. Skill: weave-search Source: https://github.com/Maximilien-ai/weave-cli-skills/tree/main/skills/weave-search Command: npx skills add https://github.com/Maximilien-ai/weave-cli-skills --skill weave-search
Query vector databases and manage AI agents to enable robust retrieval and orchestration for RAG, QA, and summarization workflows.
Run a semantic search over a document collection and return the top results.
High-intent search queries and answers about installing and using this skill.
You can create and manage weave agents to automate information workflows for RAG, QA, and summarization. Agent orchestration supports managing rag, qa, summarize, or custom agents.
You can compare embedding models and tune search parameters to optimize relevance. Re-embedding collections allows you to evaluate and adjust embedding models for better retrieval accuracy.
You can create and manage weave agents to automate information workflows for RAG, QA, and summarization. Agent orchestration supports managing rag, qa, summarize, or custom agents.
Multi-mode search configuration via weave-cli allows you to set up semantic, BM25, or hybrid search parameters. This enables precise query retrieval tailored to your document collections.
FilipcsupkaEnable semantic vector search across large document collections with HNSW indexing.
LauraFlorentinRetrieves relevant documents from a knowledge base to ground responses.
CarlosAndresBF1Build RAG pipelines with vector stores and retrieval strategies for document Q&A.
moongci38-ossPerform semantic and hybrid vector plus BM25 search on document collections.
