agent-skills
weaviate/agent-skills/AGENTS.md
This document provides setup instructions for AI agents using the Weaviate skill and plugin. 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. External Provider Keys (auto-detected): Set only the keys your collections use: Check if variables are set: All scripts require Python 3.11+. Scripts use uv for dependency management. Check if uv is installed: Install uv if needed: All…
AGENTS.md103 starsChanged 7 months ago
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# Weaviate Agent Skills - Setup Instructions This document provides setup instructions for AI agents using the Weaviate skill and plugin. ## Prerequisites ### 1. 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](https://console.weaviate.cloud/signin?utm_source=github&utm_campaign=agent_skills). ### 2. Environment Variables **Required:** ```bash WEAVIATE_URL="https://your-cluster.weaviate.cloud" WEAVIATE_API_KEY="your-api-key" ``` **External Provider Keys (auto-detected):** Set only the keys your collections use: - `OPENAI_API_KEY` - `COHERE_API_KEY` - `HUGGINGFACE_API_KEY` - `JINAAI_API_KEY` - `VOYAGE_API_KEY` - `MISTRAL_API_KEY` - `NVIDIA_API_KEY` - `VERTEX_API_KEY` - `STUDIO_API_KEY` - `AZURE_API_KEY` - `ANTHROPIC_API_KEY` - `ANYSCALE_API_KEY` - `DATABRICKS_TOKEN` - `FRIENDLI_TOKEN` - `XAI_API_KEY` - `AWS_ACCESS_KEY` - `AWS_SECRET_KEY` **Check if variables are set:** ```bash [ -z "$WEAVIATE_URL" ] && echo "WEAVIATE_URL is NOT set" || echo "WEAVIATE_URL is set" [ -z "$WEAVIATE_API_KEY" ] && echo "WEAVIATE_API_KEY is NOT set" || echo "WEAVIATE_API_KEY is set" ``` ### 3. Python Runtime All scripts require Python 3.11+. ```bash python3 --version ``` ### 4. uv Package Manager (Recommended) Scripts use [uv](https://docs.astral.sh/uv/getting-started/installation/) for dependency management. **Check if uv is installed:** ```bash uv --version ``` **Install uv if needed:** ```bash # macOS/Linux curl -LsSf https://astral.sh/uv/install.sh | sh # Or with pip pip install uv # Or with Homebrew brew install uv ``` ### Project Structure | Skill | Path | Description | | ---------------------- | ---------------------------- | --------------------------------------------------------------------------------- | | **weaviate** | `skills/weaviate/` | Scripts and references for searching, querying, and managing Weaviate collections | | **weaviate-cookbooks** | `skills/weaviate-cookbooks/` | Implementation guides for building full-stack AI applications with Weaviate | ## Running Scripts All scripts are in `skills/weaviate/scripts/`. Run from that directory. ## Available Scripts For full parameter details, examples, and usage guidance, see the linked references. ### Search & Query - [Query Agent - Ask Mode](./skills/weaviate/references/ask.md): Generate AI-powered answers with source citations across multiple collections. - [Query Agent - Search Mode](./skills/weaviate/references/query_search.md): Retrieve raw objects using natural language queries across multiple collections. - [Hybrid Search](./skills/weaviate/references/hybrid_search.md): Combine vector similarity and keyword matching — the default choice for most searches. - [Semantic Search](./skills/weaviate/references/semantic_search.md): Pure vector similarity search for finding conceptually similar content. - [Keyword Search](./skills/weaviate/references/keyword_search.md): BM25 keyword matching for exact terms, IDs, or specific text patterns. ### Collection Management - [List Collections](./skills/weaviate/references/list_collections.md): Show all available collections with their properties. - [Get Collection Details](./skills/weaviate/references/get_collection.md): Get detailed configuration of a specific collection including vectorizer, properties, and multi-tenancy settings. - [Explore Collection](./skills/weaviate/references/explore_collection.md): Get statistical insights, aggregation metrics, and sample data from a collection. - [Create Collection](./skills/weaviate/references/create_collection.md): Create a new collection with custom schema, optional vectorizer, and multi-tenancy support. ### Data Operations - [Fetch and Filter](./skills/weaviate/references/fetch_filter.md): Fetch objects by UUID or with complex nested filters (AND, OR logic). - [Import Data](./skills/weaviate/references/import_data.md): Import data from CSV, JSON, or JSONL files with automatic type conversion and column mapping. ## Dependencies All scripts use inline dependency declarations (auto-installed via `uv run`): | Package | Version | Used By | | ----------------- | -------- | ----------------------- | | `weaviate-client` | >=4.19.2 | All scripts | | `weaviate-agents` | >=1.2.0 | ask.py, query_search.py | | `typer` | >=0.21.0 | All scripts | ## Weaviate Cookbooks Weaviate cookbooks are implementation guides for building full-stack AI applications with Weaviate. All cookbooks are in the `skills/weaviate-cookbooks/` skill. For full details and best practices, see the linked references. - [Query Agent Chatbot](./skills/weaviate-cookbooks/references/query_agent_chatbot.md): Build a full-stack chatbot using Weaviate Query Agent with streaming and chat history support. - [Data Explorer](./skills/weaviate-cookbooks/references/data_explorer.md): Build a full-stack data explorer app with sorting, keyword search, and tabular data view. - [Basic RAG](./skills/weaviate-cookbooks/references/basic_rag.md): Implement basic retrieval and generation with Weaviate — covers vector, keyword, hybrid, and image search. - [Advanced RAG](./skills/weaviate-cookbooks/references/advanced_rag.md): Extend basic RAG with query rewriting, decomposition, LLM-created filters, and re-ranking. - [Multimodal RAG (PDF)](./skills/weaviate-cookbooks/references/pdf_multimodal_rag.md): Build a multimodal RAG system for PDF documents using Weaviate Embeddings (ModernVBERT/colmodernvbert) and Ollama with Qwen3-VL for generation. - [Basic Agent](./skills/weaviate-cookbooks/references/basic_agent.md): Build tool-calling AI agents with structured outputs using DSPy. - [Agentic RAG](./skills/weaviate-cookbooks/references/agentic_rag.md): Build RAG-powered AI agents combining retrieval with agent logic — covers naive RAG tools, hierarchical RAG, vector DB memory, and Weaviate Query Agent. ### Optional Frontend Guide - [Frontend Interface](./skills/weaviate-cookbooks/references/frontend_interface.md): Build a Next.js frontend (App Router, Tailwind v4, shadcn/ui) to interact with Weaviate backends. ## Contributing For full guidelines, see [CONTRIBUTING.md](./CONTRIBUTING.md). ### Adding a Reference 1. Create a new `.md` file in `skills/<skill-name>/references/`. 2. Include usage, parameters, examples, and prerequisites. 3. Link the new reference from the skill's `SKILL.md`. ### Creating a New Skill 1. Create directory: `mkdir -p skills/my-skill/references` 2. Add a `SKILL.md` with YAML frontmatter (`name`, `description`) and reference links. 3. Add reference markdown files in `references/`. Skills follow the [Agent Skills Open Standard](https://agentskills.io/).
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