How to Use Agents

Agents enable conversation with data, including structured and unstructured data connected to MindsDB.

CREATE AGENT Syntax

Here is the syntax for creating an agent:

CREATE AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4o",
        "api_key": "sk-abc123",
        "base_url": "http://example.com",
        "api_version": "2024-02-01"
    },
    data = {
         "knowledge_bases": ["project_name.kb_name", ...],
         "tables": ["datasource_conn_name.table_name", ...]
    },
    prompt_template='describe data',
    timeout=10,
    mode='text';

It creates an agent that uses the defined model and has access to the connected data.

SHOW AGENTS
WHERE name = 'my_agent';

    ...
    data = {
         "knowledge_bases": ["project_name.*", ...],
         "tables": ["datasource_conn_name.*", ...]
    },
    ...

model

This parameter defines the underlying language model, including:

• provider It is a required parameter. It defines the model provider from the list below.

• model_name It is a required parameter. It defines the model name from the list below.

• api_key It is an optional parameter (applicable to selected providers), which stores the API key to access the model. Users can provide it either in this api_key parameter, or using environment variables.

• base_url It is an optional parameter (applicable to selected providers), which stores the base URL for accessing the model. It is the root URL used to send API requests.

• api_version It is an optional parameter (applicable to selected providers), which defines the API version.

The available models and providers include the following.

Note that in order to use Bedrock as a model provider, you should ensure the following packages are installed: langchain_aws and transformers.

The following parameters are specific to this provider:

• aws_region_name is a required parameter.
• aws_access_key_id is a required parameter.
• aws_secret_access_key is a required parameter.
• aws_session_token is an optional parameter. It may be required depending on the AWS permissions setup. </Accordion>

Users can define the model for the agent choosing one of the following options.

Option 1. Use the model parameter to define the specification.

CREATE AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "got-4o",
        "api_key": "sk-abc123",
        "base_url": "https://example.com/",
        "api_version": "2024-02-01"
    },
    ...

Option 2. Define the default model in the MindsDB configuration file.

If you define default_llm in the configuration file, you do not need to provide the model parameter when creating an agent. If provide both, then the values from the model parameter are used.

"default_llm": {

      "provider": "openai",
      "model_name" : "got-4o",
      "api_key": "sk-abc123",
      "base_url": "https://example.com/",
      "api_version": "2024-02-01"

}

data

This parameter stores data connected to the agent, including knowledge bases and data sources connected to MindsDB.

The following parameters store the list of connected data.

• knowledge_bases stores the list of knowledge bases to be used by the agent.

• tables stores the list of tables from data sources connected to MindsDB.

prompt_template

This parameter stores instructions for the agent.

It is recommended to provide data description of the data sources listed in the knowledge_bases and tables parameters to help the agent locate relevant data for answering questions.

timeout

This parameter defines the time the agent can take to come back with an answer.

For example, when the timeout parameter is set to 10, the agent has 10 seconds to return an answer. If the agent takes longer than 10 seconds, it aborts the process and comes back with an answer indicating its failure to return an answer within the defined time interval.

mode

This parameter defines the agent's response style, allowing users to partially control the output format. Supported values include text and sql.

When set, the agent will tailor its responses to match the specified format. Note that the agent may still adapt its output when necessary to ensure clarity or correctness.

SELECT FROM AGENT Syntax

Query an agent to generate responses to questions.

SELECT answer
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';

-- or

SELECT customer_name, avg_number_of_orders
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';

You can redefine the agent's parameters at the query time as below.

SELECT answer
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4.1",
        "api_key": "sk-abc123"
    },
    data = {
         "knowledge_bases": ["project_name.kb_name", ...],
         "tables": ["datasource_conn_name.table_name", ...]
    },
    prompt_template='describe data',
    timeout=10;

The USING clause may contain any combination of parameters from the CREATE AGENT command, depending on which parameters users want to update for the query.

For example, users may want to check the performance of other models to decide which model works better for their use case.

SELECT answer
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';
USING
    model = {
        "provider": "google",
        "model_name" : "gemini-2.5-flash",
        "api_key": "ABc123"
    };

ALTER AGENT Syntax

Update existing agents with new data, model, or prompt.

ALTER AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4.1",
        "api_key": "sk-abc123",
        "base_url": "http://example.com",
        "api_version": "2024-02-01"
    },
    data = {
         "knowledge_bases": ["project_name.kb_name", ...],
         "tables": ["datasource_conn_name.table_name", ...]
    },
    prompt_template='describe data';

Note that all parameters are optional. Users can update any combination of parameters.

Here is how to connect new data to an agent.

ALTER AGENT my_agent
USING
    data = {
         "knowledge_bases": ["mindsdb.sales_kb"],
         "tables": ["mysql_db.car_sales", "mysql_db.car_info"]
    };

And here is how to update a model used by the agent.

ALTER AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4.1",
        "api_key": "sk-abc123"
    };

DROP AGENT Syntax

Here is the syntax for deleting an agent:

DROP AGENT my_agent;