AI Integrations
MindsDB integrates with numerous AI frameworks, facilitating deployment and management of AI models.
MindsDB offers a wide range of AI engines used to create models and incorporate them in the data landscape as virtual AI tables. MinsdDB abstracts AI models as virtual tables, or Generative AI Tables, that can generate data from the underlying model upon being queried.
This section contains instructions on how to create and deploy models within MindsDB, utilizing different AI/ML frameworks.
Large Language Models
Anthropic
Anyscale Endpoints
Cohere
Google Gemini
Hugging Face
Hugging Face Inference API
LangChain
LlamaIndex
MonkeyLearn
Minds Endpoint
Ollama
OpenAI
Replicate (LLM)
RAG
Vertex AI
Bring Your Own Models
Anomaly Detection
AutoML
Time Series Models
Recommender Models
Audio Models
Image Models
Video Models
If you don’t find an AI/ML framework of your interest, you can request a feature here or build an AI/ML handler following this instruction.
Metadata about AI handlers and AI engines
AI handlers represent a raw implementation of the integration between MindsDB and an AI/ML framework. These are used to create AI engines.
Here is how you can query for all the available AI handlers used to create AI engines.
SELECT *
FROM information_schema.handlers
WHERE type = 'ml';
Or, alternatively:
SHOW HANDLERS
WHERE type = 'ml';
And here is how you can query for all the created AI engines:
SELECT *
FROM information_schema.ml_engines;
Or, alternatively:
SHOW ML_ENGINES;