🧑🍳 Spice.ai OSS Cookbook
67 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.
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Featured Recipes
Sample Applications and Guides
Example apps and guides for real-world Spice.ai usage and best practices. Sample application implementing the CQRS pattern with Spice.Command Query Responsibility Segregation (CQRS)
Core Features
Discover core capabilities like data federation, acceleration, search, and LLM inference to enhance your applications.
Models, AI, and Agents
Integrate with popular AI models, LLMs, and build intelligent agents using Spice.ai. Ask natural language (NLP) questions of your datasets using the built-in text-to-SQL tool.Text to SQL (NSQL)
Data Acceleration, Materialization, and Federation
Optimize query performance with local acceleration, data materialization, and federation techniques.
Data Connectors
Connect to various data sources and systems to query, analyze, and manage your data efficiently. Connect to and query Databricks instances using Delta Lake or Spark Connect. Stream MySQL changes using Debezium with SASL/SCRAM authentication.Databricks Connector
Debezium CDC with SASL/SCRAM
Catalog Connectors
Connect to data catalogs to discover, manage, and utilize your data assets effectively.
API Clients
Use API clients for data access and integration.
Performance and Benchmarking
Measure and optimize performance with benchmarks and best practices for your Spice.ai deployment.
Configuration
Fine-tune your Spice.ai deployment with advanced configuration options for optimal performance.
SDKs
Use SDKs for different programming languages.
Security
Secure your Spice.ai deployment and data access with robust security practices and configurations.