minds-sdk 2.0.1

An AI-Data Mind is an LLM with the built-in power to answer data questions for Agents

Minds SDK

⚠️ API Version Notice

This documentation reflects the current SDK version, compatible with the latest Minds Cloud API.

For users of the legacy Minds Demo environment at https://demo.mdb.ai, please refer to the legacy documentation for compatibility.

Current Version: v2.x+ (New API for Minds Cloud environments)
Legacy Version: v1.x (Legacy Documentation)

Installation

To install the SDK, use pip:

pip install minds-sdk

Getting Started

1. Initialize the Client

To get started, you'll need to initialize the Client with your API key. If you're using a different server, you can also specify a custom base URL.

from minds.client import Client

# Default connection to Minds Cloud
API_KEY = "YOUR_API_KEY"
client = Client(API_KEY)

# Or with custom base URL
BASE_URL = 'https://custom_cloud.mdb.ai/api/v1'
client = Client(API_KEY, base_url=BASE_URL)

2. Creating a Datasource

Create a datasource to connect to your database:

# Create datasource
datasource = client.datasources.create(
    name='my_datasource',
    description='House sales data',
    engine='postgres',
    connection_data={
        'user': 'demo_user',
        'password': 'demo_password',
        'host': 'samples.mindsdb.com',
        'port': 5432,
        'database': 'demo',
        'schema': 'demo_data'
    }
)

3. Creating a Mind

Create a mind and associate it with your datasource:

# Create mind with datasource
mind = client.minds.create(
    name='mind_name',
    datasources=[
        {
            'name': datasource.name,
            'tables': ['house_sales']
        }
    ]
)

# Or add datasource to existing mind
mind = client.minds.create(name='mind_name')
mind.add_datasource(datasource.name, tables=['house_sales'])

4. Wait for Mind to be Ready

Before using your mind, wait for it to complete processing:

import time

def wait_for_mind(mind):
    status = mind.status
    while status != 'COMPLETED':
        print(f'Mind status: {status}')
        time.sleep(3)
        mind = client.minds.get(mind.name)
        status = mind.status
    
        if status == 'FAILED':
            raise Exception('Mind creation failed')

    print('Mind creation successful!')
 
wait_for_mind(mind)

Using Your Mind

Chat with OpenAI-Compatible API

You can use the OpenAI client to interact with your minds:

from openai import OpenAI

# Initialize OpenAI client
openai_client = OpenAI(api_key=API_KEY, base_url=BASE_URL)

# Chat without streaming
completion = openai_client.chat.completions.create(
    model=mind.name,
    messages=[
        {'role': 'user', 'content': 'How many three-bedroom houses were sold in 2008?'}
    ],
    stream=False
)
print(completion.choices[0].message.content)

# Chat with streaming
completion_stream = openai_client.chat.completions.create(
    model=mind.name,
    messages=[
        {'role': 'user', 'content': 'How many three-bedroom houses were sold in 2008?'}
    ],
    stream=True
)
for chunk in completion_stream:
    print(chunk.choices[0].delta.content)

Direct Mind Completion

You can also interact directly with the mind:

# Without streaming
response = mind.completion('How many three-bedroom houses were sold in 2008?')
print(response)

# With streaming
for chunk in mind.completion('How many three-bedroom houses were sold in 2008?', stream=True):
    print(chunk)

Managing Minds

Create or Replace

Create a new mind or replace an existing one:

mind = client.minds.create(
    name='mind_name',
    datasources=[
        {
            'name': datasource.name,
            'tables': ['home_rentals']
        }
    ],
    replace=True
)
wait_for_mind(mind)

Update Mind

Update an existing mind:

mind = client.minds.update(
    name='mind_name',  # required
    new_name='new_mind_name',  # optional
    datasources=[  # optional
        {
            'name': datasource.name,
            'tables': ['home_rentals']
        }
    ],
)
wait_for_mind(mind)

List Minds

Get all your minds:

minds = client.minds.list()
print(minds)

Get Mind by Name

Retrieve a specific mind:

mind = client.minds.get('mind_name')

Remove Mind

Delete a mind:

client.minds.drop('mind_name')

Managing Datasources

Create or Replace

Create a new datasource or replace an existing one:

datasource = client.datasources.create(
    name='my_datasource',
    description='House sales data',
    engine='postgres',
    connection_data={
        'user': 'demo_user',
        'password': 'demo_password',
        'host': 'samples.mindsdb.com',
        'port': 5432,
        'database': 'demo',
        'schema': 'demo_data'
    },
    replace=True
)

Update Datasource

Update an existing datasource:

datasource = client.datasources.update(
    name='my_datasource',
    new_name='updated_datasource',
    description='Updated House sales data',
    connection_data={
        'user': 'demo_user',
        'password': 'demo_password',
        'host': 'samples.mindsdb.com',
        'port': 5432,
        'database': 'demo',
        'schema': 'demo_data'
    }
)

List Datasources

Get all your datasources:

datasources = client.datasources.list()
print(datasources)

Get Datasource by Name

Retrieve a specific datasource:

datasource = client.datasources.get('my_datasource')

Remove Datasource

Delete a datasource:

client.datasources.drop('my_datasource')