turbovec

核心特点

• •Online ingest. Add vectors, they're indexed — no train step, no parameter tuning, no rebuilds as the corpus grows.
• •Pure local. No managed service, no data leaving your machine or VPC. Pair with any open-source embedding model for a fully air-gapped RAG stack.
• •LangChain — pip install turbovec[langchain] · replaces langchain_core.vectorstores.InMemoryVectorStore
• •LlamaIndex — pip install turbovec[llama-index] · replaces llama_index.core.vector_stores.SimpleVectorStore
• •Haystack — pip install turbovec[haystack] · replaces haystack.document_stores.in_memory.InMemoryDocumentStore
• •Agno — pip install turbovec[agno] · replaces agno.vectordb.lancedb.LanceDb