Use a Mind via OpenAI Chat Completions API

from openai import OpenAI

your_minds_api_key = <YOUR API KEY>
minds_name = <NAME YOU GAVE TO YOUR MIND>

# point the Openai SDK to the Minds Cloud
client = OpenAI(
    api_key= your_minds_api_key,
    base_url='https://llm.mdb.ai/'
)

# print the message before making the API request
print('Answering the question may take up to 30 seconds...')

# chat with the Mind you created
completion = client.chat.completions.create(
    model=minds_name,
    messages=[
        {'role': 'user', 'content': 'How many three-bedroom houses were sold in 2008?'}
    ],
    stream=False
)

print(completion.choices[0].message.content)

There were 8 three-bedroom houses sold in 2008.

from openai import OpenAI

your_minds_api_key = <YOUR API KEY>
minds_name = <NAME YOU GAVE TO YOUR MIND>

# point the Openai SDK to the Minds Cloud
client = OpenAI(
    api_key= your_minds_api_key,
    base_url='https://llm.mdb.ai/'
)

# print the message before making the API request
print('Answering the question may take up to 30 seconds...')

# chat with the Mind you created
completion = client.chat.completions.create(
    model=minds_name,
    messages=[
        {'role': 'user', 'content': 'How many three-bedroom houses were sold in 2008?'}
    ],
    stream=True
)

# print output in the form of chunks
for chunk in completion:
    print(chunk.choices[0].delta.content)
    print()

Answering the question may take up to 30 seconds...
I understand your request. I'm working on a detailed response for you.

content='Thought: I need to check the schema of the `house_sales` table to understand the structure and identify the relevant columns for querying the number of three-bedroom houses sold in 2008.\n\nAction: sql_db_schema714\nAction Input: mind_d315ac7e-8c53-467c-a378-0e20274cf0ee_datasource_03c058391f7c4716970edfea20c6f097.house_sales'

content='Table named `house_sales`\n\n/* Sample with first 3 rows from table `mind_d315ac7e-8c53-467c-a378-0e20274cf0ee_datasource_03c058391f7c4716970edfea20c6f097`.house_sales:\nsaledate\tma\ttype\tbedrooms\tcreated_at\n2007-09-30\t441854\thouse\t2\t2007-02-02 15:41:51.922127\n2007-12-31\t441854\thouse\t2\t2007-02-23 22:36:08.540248\n2008-03-31\t441854\thouse\t2\t2007-02-25 19:23:52.585358\n*/\nColumn data types: `saledate` : `date`,\t`ma` : `integer`,\t`type` : `text`,\t`bedrooms` : `integer`,\t`created_at` : `timestamp without time zone`\n'

content="To determine the number of three-bedroom houses sold in 2008, I need to query the `house_sales` table using the `bedrooms` and `saledate` columns. Specifically, I will filter for records where `bedrooms` is 3 and the `saledate` falls within the year 2008.\n\nFirst, I will ensure the SQL query is correct using the MindsDB SQL parser tool.\n\nAction: mindsdb_sql_parser_tool714\nAction Input: SELECT COUNT(*) FROM house_sales WHERE bedrooms = 3 AND saledate BETWEEN '2008-01-01' AND '2008-12-31'"

content="valid query: SELECT count(*) FROM house_sales WHERE bedrooms = 3 AND saledate BETWEEN '2008-01-01' AND '2008-12-31'"

content="The SQL query has been validated. Now, I will execute the query to find out how many three-bedroom houses were sold in 2008.\n\nAction: sql_db_query714\nAction Input: SELECT COUNT(*) FROM house_sales WHERE bedrooms = 3 AND saledate BETWEEN '2008-01-01' AND '2008-12-31'"

content="Output columns: 'count'\nResult:\n8"

In 2008, a total of 8 three-bedroom houses were sold.