This documentation describes the integration of MindsDB with LangChain, a framework for developing applications powered by language models. The integration allows for the deployment of LangChain models within MindsDB, providing the models with access to data from various data sources.
Before proceeding, ensure the following prerequisites are met:
Create an AI/ML engine from the LangChain Embedding handler.
Create a model using embedding
as an engine and providing your OpenAI API key.
The following are the required and optional parameters:
engine
is a required parameter. It defines the AI engine, as created with the CREATE ML_ENGINE
statement, to be used.class
is a required parameter. It defines the model provider, such as "OpenAI"
or "HuggingFace"
.model
is a required parameter. It defined the embedding model, such as text-embedding-3-small
.openai_api_key
is a required parameter when using OpenAI as a provider.input_columns
is an optional parameter. It defines the column(s) to be processed by the embedding model.The following usage examples utilize embedding
to create a model with the CREATE MODEL
statement.
Ensure that the model has been created successfully before using it. To do that, use the DESCRIBE
command and look at the status
column.
Next Steps
Go to the Use Cases section to see more examples.