🧑🍳 Spice.ai Cookbook
78 guides and samples to help you build data-grounded AI apps and agents with Spice.ai Open-Source. Find ready-to-use examples for data acceleration, AI agents, LLM memory, and more.
Featured Recipes
Most popular cookbook recipes for SQL federation, local models, acceleration, and LLM memory.
Run Llama3 Locally
Use Llama models from HuggingFace with Spice. Includes video walkthrough.
Data Acceleration with DuckDB
Speed up queries using DuckDB. Includes video walkthrough.
Core Features
Discover core capabilities like data federation, acceleration, search, and LLM inference to enhance your applications.
DuckDB Data Accelerator
Accelerate data locally using DuckDB. Includes video walkthrough.
Amazon S3 Vectors Search
Use Amazon S3 Vectors to store embeddings and run efficient vector search. Includes video walkthrough.
Spice Cayenne Data Accelerator
Accelerate data locally using the Spice Cayenne Data Accelerator.
Models, AI, and Agents
Integrate with popular AI models, LLMs, and build intelligent agents using Spice.ai.
Running Llama3 Locally
Use the Llama family of models locally from HuggingFace using Spice. Includes video walkthrough.
Text to SQL (NSQL)
Ask natural language (NLP) questions of your datasets using the built-in text-to-SQL tool.
Generative Visualizations
Generate SQL queries and Chart.js visualizations from natural language using AI.
Nvidia NIM on Kubernetes
Deploy Nvidia NIM infrastructure on Kubernetes with GPUs connected to Spice.
Nvidia NIM on AWS EC2
Deploy Nvidia NIM on AWS GPU-optimized EC2 instances connected to Spice.
Searching GitHub Files
Search GitHub files with embeddings and vector similarity search. Includes video walkthrough.
Hybrid-Search with RRF
Combine multiple search methods using Reciprocal Rank Fusion (RRF) for improved search results.
Web Search Tools using Perplexity
Provide LLMs with web search access for more informed answers.
LLM as a Judge
Define LLM judge models to evaluate the performance of other language models.
Amazon S3 Vectors
Use Amazon S3 Vectors to store embeddings and perform efficient vector search. Includes video walkthrough.
Data Acceleration, Materialization, and Federation
Optimize query performance with local acceleration, data materialization, and federation techniques.
DuckDB Data Accelerator
Accelerate data locally using DuckDB. Includes video walkthrough.
Database Snapshots
Bootstrap DuckDB accelerations from object storage to skip cold starts.
Search & Embeddings
Implement advanced search capabilities and leverage embeddings for vector similarity search.
Searching GitHub Files
Search GitHub files with embeddings and vector similarity search. Includes video walkthrough.
Hybrid-Search with RRF
Combine multiple search methods using Reciprocal Rank Fusion (RRF) for improved search results.
Amazon S3 Vectors
Use Amazon S3 Vectors to store embeddings and perform efficient vector search. Includes video walkthrough.
Data Connectors
Connect to various data sources and systems to query, analyze, and manage your data efficiently.
Databricks Connector
Connect to and query Databricks instances using Delta Lake or Spark Connect.
Debezium CDC with SASL/SCRAM
Stream MySQL changes using Debezium with SASL/SCRAM authentication.
Live Orders Analytics with Apache Kafka Data Connector
Combine real-time data streaming from Kafka with other datasets using Spice.
Catalog Connectors
Connect to data catalogs to discover, manage, and utilize your data assets effectively.
Iceberg Catalog Connector
Connect to Iceberg catalog with support for reading and writing Iceberg tables.
Visualization
Visualize data with BI and analytics tools.
API Clients
Use API clients for data access and integration.
Deployment
Deploy Spice.ai in different environments.
Microservice Deployment Architecture
Deploy Spice as a standalone microservice architecture.
Advanced Topics
Explore advanced deployment and data architecture patterns for production workloads.
Local Dataset Replication
Link datasets in a parent/child relationship within the current Spicepod.
Performance and Benchmarking
Measure and optimize performance with benchmarks and best practices for your Spice.ai deployment.
Caching Accelerator
Use intelligent HTTP response caching with stale-while-revalidate (SWR).
Configuration
Fine-tune your Spice.ai deployment with advanced configuration options for optimal performance.
SDKs
Use SDKs for different programming languages.
Spice.js JavaScript (Node.js) SDK
Query Spice.ai using the JavaScript (Node.js) SDK with examples.
Security
Secure your Spice.ai deployment and data access with robust security practices and configurations.
FAQs
Common questions about using the Spice.ai OSS Cookbook and choosing the right recipe to start with.
What is the Spice.ai OSS Cookbook?
The cookbook is a curated set of practical, ready-to-run recipes for Spice.ai Open Source. Recipes cover connectors, federation, acceleration, hybrid search, model integration, and deployment patterns.
Which recipe should I start with?
If you are new to Spice, start with a recipe that matches your immediate goal: federated SQL for multi-source queries, DuckDB acceleration for faster performance, or OpenAI SDK and MCP recipes for AI agent use cases.
Do cookbook recipes work with Spice Cloud?
Yes. Cookbook patterns are based on Spice OSS capabilities and can be adapted to Spice Cloud workflows. You can start locally with OSS and move to managed deployments as workloads grow. See Spice Cloud pricing.
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