vector-database

What problem does it solve?

This Skill simplifies the management and querying of vector databases, essential for building knowledge bases and enabling semantic search capabilities within AI systems.

Core Features & Use Cases

• Vector Database Operations: Perform CRUD operations (Create, Read, Update, Delete) on vector collections.
• Semantic Search: Query the database using natural language to find semantically similar documents.
• RAG Implementation: Facilitates the Retrieval-Augmented Generation pattern by fetching relevant context for LLM prompts.
• Custom Embeddings: Supports integration with various embedding functions, including OpenAI and Sentence Transformers.
• Filtering: Enables precise querying using metadata and document content filters.
• Use Case: Integrate this Skill into an AI assistant to allow users to ask questions about a large corpus of documents, with the AI retrieving relevant information from the vector database to formulate its answers.

Quick Start

Use the vector-database skill to add a document with the ID 'doc_001' to the 'knowledge_base' collection.