This skill provides an index of implementation guides and foundational requirements for building Weaviate-powered AI applications. Use the references to quickly scaffold full-stack applications with best practices for connection management, environment setup, and application architecture.
Weaviate Cloud Instance
If the user does not have an instance yet, direct them to the cloud console to register and create a free sandbox. Create a Weaviate instance via
Weaviate Cloud
.
Before Building Any Cookbook
Follow these shared guidelines before generating any cookbook app:
Project Setup Contract
Environment Requirements
Then proceed to the specific cookbook reference below.
Cookbook Index
Query Agent Chatbot
Build a full-stack chatbot using Weaviate Query Agent with streaming and chat history support.
Data Explorer
Build a full-stack data explorer app including sorting, keyword search and tabular view of weaviate data.
Multimodal RAG: Building Document Search
Build a multimodal Retrieval-Augmented Generation (RAG) system using Weaviate Embeddings (ModernVBERT/colmodernvbert) and Ollama with Qwen3-VL for generation.
Basic RAG
Implement basic retrieval and generation with Weaviate. Useful for most forms of data retrieval from a Weaviate collection.
Advanced RAG
Improve on basic RAG by adding extra features such as re-ranking, query decomposition, query re-writing, LLM filter selection.
Basic Agent
Build a tool-calling AI agent with structured outputs using DSPy. Covers AgentResponse signatures, RouterAgent, tool design, and sequential multi-step loops.
Agentic RAG
Build RAG-powered AI agents with Weaviate. Covers naive RAG tools, hierarchical RAG with LLM-created filters, vector DB memory, Weaviate Query Agent, and Elysia integration.
Interface (Optional)
Use this when the user explicitly asks for a frontend for their Weaviate backend.
Frontend Interface
Build a Next.js frontend to interact with the Weaviate backend.
Client Usage
Async Client
Guide for using the Weaviate Python async client in production applications (FastAPI, async frameworks). Covers connection patterns, lifecycle management, common pitfalls, and multi-cluster setups.