[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-weaviate-weaviate-cookbooks":3,"mdc--58dfv9-key":36,"related-org-weaviate-weaviate-cookbooks":255,"related-repo-weaviate-weaviate-cookbooks":276},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"weaviate-cookbooks","build AI applications with Weaviate","Use this skill when the user wants to build AI applications with Weaviate. It contains a high-level index of architectural patterns, 'one-shot' blueprints, and best practices for common use cases. Currently, it includes references for building a Query Agent Chatbot, Data Explorer, Multimodal PDF RAG (Document Search), Basic RAG, Advanced RAG, Basic Agent, Agentic RAG, and optional guidance on how to build a frontend for each of them.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"weaviate","Weaviate","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fweaviate.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"RAG","rag","tag",{"name":17,"slug":18,"type":15},"Database","database",{"name":20,"slug":21,"type":15},"Search","search",{"name":23,"slug":24,"type":15},"AI Infrastructure","ai-infrastructure",101,"https:\u002F\u002Fgithub.com\u002Fweaviate\u002Fagent-skills","2026-07-17T06:05:43.91763",null,17,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"Agent Skills to empower developers building AI applications with Weaviate.","https:\u002F\u002Fgithub.com\u002Fweaviate\u002Fagent-skills\u002Ftree\u002FHEAD\u002Fskills\u002Fweaviate-cookbooks","---\nname: weaviate-cookbooks\ndescription: Use this skill when the user wants to build AI applications with Weaviate. It contains a high-level index of architectural patterns, 'one-shot' blueprints, and best practices for common use cases. Currently, it includes references for building a Query Agent Chatbot, Data Explorer, Multimodal PDF RAG (Document Search), Basic RAG, Advanced RAG, Basic Agent, Agentic RAG, and optional guidance on how to build a frontend for each of them.\n---\n\n# Weaviate Cookbooks\n\n## Overview\n\nThis 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.\n\n### Weaviate Cloud Instance\n\nIf 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](https:\u002F\u002Fconsole.weaviate.cloud\u002Fsignin?utm_source=github&utm_campaign=agent_skills).\n\n## Before Building Any Cookbook\n\nFollow these shared guidelines before generating any cookbook app:\n\n- [Project Setup Contract](references\u002Fproject_setup.md)\n- [Environment Requirements](references\u002Fenvironment_requirements.md)\n\nThen proceed to the specific cookbook reference below.\n\n## Cookbook Index\n\n- [Query Agent Chatbot](references\u002Fquery_agent_chatbot.md): Build a full-stack chatbot using Weaviate Query Agent with streaming and chat history support.\n- [Data Explorer](references\u002Fdata_explorer.md): Build a full-stack data explorer app including sorting, keyword search and tabular view of weaviate data.\n- [Multimodal RAG: Building Document Search](references\u002Fpdf_multimodal_rag.md): Build a multimodal Retrieval-Augmented Generation (RAG) system using Weaviate Embeddings (ModernVBERT\u002Fcolmodernvbert) and Ollama with Qwen3-VL for generation.\n- [Basic RAG](references\u002Fbasic_rag.md): Implement basic retrieval and generation with Weaviate. Useful for most forms of data retrieval from a Weaviate collection.\n- [Advanced RAG](references\u002Fadvanced_rag.md): Improve on basic RAG by adding extra features such as re-ranking, query decomposition, query re-writing, LLM filter selection.\n- [Basic Agent](references\u002Fbasic_agent.md): Build a tool-calling AI agent with structured outputs using DSPy. Covers AgentResponse signatures, RouterAgent, tool design, and sequential multi-step loops.\n- [Agentic RAG](references\u002Fagentic_rag.md): 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.\n\n## Interface (Optional)\n\nUse this when the user explicitly asks for a frontend for their Weaviate backend.\n\n- [Frontend Interface](references\u002Ffrontend_interface.md): Build a Next.js frontend to interact with the Weaviate backend.\n\n## Client Usage\n\n- [Async Client](references\u002Fasync_client.md): 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.\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,49,56,62,69,85,91,96,119,124,130,210,216,221,235,241],{"type":42,"tag":43,"props":44,"children":45},"element","h1",{"id":4},[46],{"type":47,"value":48},"text","Weaviate Cookbooks",{"type":42,"tag":50,"props":51,"children":53},"h2",{"id":52},"overview",[54],{"type":47,"value":55},"Overview",{"type":42,"tag":57,"props":58,"children":59},"p",{},[60],{"type":47,"value":61},"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.",{"type":42,"tag":63,"props":64,"children":66},"h3",{"id":65},"weaviate-cloud-instance",[67],{"type":47,"value":68},"Weaviate Cloud Instance",{"type":42,"tag":57,"props":70,"children":71},{},[72,74,83],{"type":47,"value":73},"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 ",{"type":42,"tag":75,"props":76,"children":80},"a",{"href":77,"rel":78},"https:\u002F\u002Fconsole.weaviate.cloud\u002Fsignin?utm_source=github&utm_campaign=agent_skills",[79],"nofollow",[81],{"type":47,"value":82},"Weaviate Cloud",{"type":47,"value":84},".",{"type":42,"tag":50,"props":86,"children":88},{"id":87},"before-building-any-cookbook",[89],{"type":47,"value":90},"Before Building Any Cookbook",{"type":42,"tag":57,"props":92,"children":93},{},[94],{"type":47,"value":95},"Follow these shared guidelines before generating any cookbook app:",{"type":42,"tag":97,"props":98,"children":99},"ul",{},[100,110],{"type":42,"tag":101,"props":102,"children":103},"li",{},[104],{"type":42,"tag":75,"props":105,"children":107},{"href":106},"references\u002Fproject_setup.md",[108],{"type":47,"value":109},"Project Setup Contract",{"type":42,"tag":101,"props":111,"children":112},{},[113],{"type":42,"tag":75,"props":114,"children":116},{"href":115},"references\u002Fenvironment_requirements.md",[117],{"type":47,"value":118},"Environment Requirements",{"type":42,"tag":57,"props":120,"children":121},{},[122],{"type":47,"value":123},"Then proceed to the specific cookbook reference below.",{"type":42,"tag":50,"props":125,"children":127},{"id":126},"cookbook-index",[128],{"type":47,"value":129},"Cookbook Index",{"type":42,"tag":97,"props":131,"children":132},{},[133,144,155,166,177,188,199],{"type":42,"tag":101,"props":134,"children":135},{},[136,142],{"type":42,"tag":75,"props":137,"children":139},{"href":138},"references\u002Fquery_agent_chatbot.md",[140],{"type":47,"value":141},"Query Agent Chatbot",{"type":47,"value":143},": Build a full-stack chatbot using Weaviate Query Agent with streaming and chat history support.",{"type":42,"tag":101,"props":145,"children":146},{},[147,153],{"type":42,"tag":75,"props":148,"children":150},{"href":149},"references\u002Fdata_explorer.md",[151],{"type":47,"value":152},"Data Explorer",{"type":47,"value":154},": Build a full-stack data explorer app including sorting, keyword search and tabular view of weaviate data.",{"type":42,"tag":101,"props":156,"children":157},{},[158,164],{"type":42,"tag":75,"props":159,"children":161},{"href":160},"references\u002Fpdf_multimodal_rag.md",[162],{"type":47,"value":163},"Multimodal RAG: Building Document Search",{"type":47,"value":165},": Build a multimodal Retrieval-Augmented Generation (RAG) system using Weaviate Embeddings (ModernVBERT\u002Fcolmodernvbert) and Ollama with Qwen3-VL for generation.",{"type":42,"tag":101,"props":167,"children":168},{},[169,175],{"type":42,"tag":75,"props":170,"children":172},{"href":171},"references\u002Fbasic_rag.md",[173],{"type":47,"value":174},"Basic RAG",{"type":47,"value":176},": Implement basic retrieval and generation with Weaviate. Useful for most forms of data retrieval from a Weaviate collection.",{"type":42,"tag":101,"props":178,"children":179},{},[180,186],{"type":42,"tag":75,"props":181,"children":183},{"href":182},"references\u002Fadvanced_rag.md",[184],{"type":47,"value":185},"Advanced RAG",{"type":47,"value":187},": Improve on basic RAG by adding extra features such as re-ranking, query decomposition, query re-writing, LLM filter selection.",{"type":42,"tag":101,"props":189,"children":190},{},[191,197],{"type":42,"tag":75,"props":192,"children":194},{"href":193},"references\u002Fbasic_agent.md",[195],{"type":47,"value":196},"Basic Agent",{"type":47,"value":198},": Build a tool-calling AI agent with structured outputs using DSPy. Covers AgentResponse signatures, RouterAgent, tool design, and sequential multi-step loops.",{"type":42,"tag":101,"props":200,"children":201},{},[202,208],{"type":42,"tag":75,"props":203,"children":205},{"href":204},"references\u002Fagentic_rag.md",[206],{"type":47,"value":207},"Agentic RAG",{"type":47,"value":209},": 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.",{"type":42,"tag":50,"props":211,"children":213},{"id":212},"interface-optional",[214],{"type":47,"value":215},"Interface (Optional)",{"type":42,"tag":57,"props":217,"children":218},{},[219],{"type":47,"value":220},"Use this when the user explicitly asks for a frontend for their Weaviate backend.",{"type":42,"tag":97,"props":222,"children":223},{},[224],{"type":42,"tag":101,"props":225,"children":226},{},[227,233],{"type":42,"tag":75,"props":228,"children":230},{"href":229},"references\u002Ffrontend_interface.md",[231],{"type":47,"value":232},"Frontend Interface",{"type":47,"value":234},": Build a Next.js frontend to interact with the Weaviate backend.",{"type":42,"tag":50,"props":236,"children":238},{"id":237},"client-usage",[239],{"type":47,"value":240},"Client Usage",{"type":42,"tag":97,"props":242,"children":243},{},[244],{"type":42,"tag":101,"props":245,"children":246},{},[247,253],{"type":42,"tag":75,"props":248,"children":250},{"href":249},"references\u002Fasync_client.md",[251],{"type":47,"value":252},"Async Client",{"type":47,"value":254},": 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.",{"items":256,"total":275},[257,268],{"slug":8,"name":8,"fn":258,"description":259,"org":260,"tags":261,"stars":25,"repoUrl":26,"updatedAt":267},"search and manage Weaviate vector collections","Search, query, and manage Weaviate vector database collections. Use for semantic search, hybrid search, keyword search, natural language queries with AI-generated answers, collection management, data exploration, filtered fetching, data imports from PDF\u002FCSV\u002FJSON\u002FJSONL files, create example data and collection creation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[262,265,266],{"name":263,"slug":264,"type":15},"AI","ai",{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-07-17T06:07:22.572532",{"slug":4,"name":4,"fn":5,"description":6,"org":269,"tags":270,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[271,272,273,274],{"name":23,"slug":24,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},2,{"items":277,"total":275},[278,284],{"slug":8,"name":8,"fn":258,"description":259,"org":279,"tags":280,"stars":25,"repoUrl":26,"updatedAt":267},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[281,282,283],{"name":263,"slug":264,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":4,"name":4,"fn":5,"description":6,"org":285,"tags":286,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[287,288,289,290],{"name":23,"slug":24,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15}]