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Description

With MindsDB, you can create and deploy AI agents that comprise AI models and customizable skills such as knowledge bases and text-to-SQL.

AI agents comprise of skills, such as text2sql and knowledge_base, and a conversational model.
  • Skills provide data resources to an agent, enabling it to answer questions about available data. Learn more about skills here. Learn more about knowledge bases here.
  • A conversational model (like OpenAI) from LangChain utilizes tools as skills to respond to user input. Users can customize these models with their own prompts to fit their use cases.

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Syntax

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Creating an agent

When creating an agent, you can use the default conversational model: 
agent = server.agents.create('new_demo_agent')
Or specify model parameters: 
agent = server.agents.create(
    name='new_demo_agent',
    model='gpt-4',
    openai_api_key='OPENAI_API_KEY',
    prompt_template='Hello! Ask a question: {{question}}',
    temperature=0.0,
    max_tokens=1000,
    top_p=1.0,
    top_k=0
)
Or use an existing model: 
model = server.models.get('existing_model')
agent = server.agents.create('demo_agent', model)
Furthermore, you can list all existing agents, get agents by name, update agents, and delete agents. 
# list all agents
agents = agents.list()

# get an agent by name
agent = agents.get('my_agent')

# update an agent
new_model = models.get('new_model')
agent.model_name = new_model.name
new_skill = skills.create('new_skill', 'sql', { 'tables': ['new_table'], 'database': 'new_database' })
updated_agent.skills.append(new_skill)
updated_agent = agents.update('my_agent', agent)

# delete an agent by name
agents.delete('my_agent')

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Assigning skills to an agent

You can add skills to an agent, providing it with data stored in databases, files, or webpages. The retrieval skill is similar to knowledge bases. 
# add data from one or more files as skills
agent.add_file('./file_name.txt', 'file content description')
agent.add_files(['./file_name.pdf', './file_name.pdf', ...], 'files content description')

# add data from one or more webpages as skills
agent.add_webpages(['example1.com', 'example2.com', ...], 'webpages content description')
The text2SQL skill retrieves relevant information from databases. 
# add data from a database connected to mindsdb as skills
db = server.databases.create('datasource_name', 'engine_name', {'database': 'db.db_name'})
db = server.databases.get('datasource_name')
agent.add_database(db.name, ['table_name'], 'data description')
Learn more about all data sources integrated with MindsDB.

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Querying an agent

Once you created an agent and assigned it a set of skills, you can ask questions related to your data. 
question = 'ask a question'
answer = agent.completion([{'question': question, 'answer': None}])
print(answer.content)

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Example

Here is a sample Python code to deploy an agent: 
import mindsdb_sdk
con = mindsdb_sdk.connect()

# IMPORTANT: This code requires to set OPENAI_API_KEY as env variable

agent = con.agents.create(f'new_demo_agent')

print('Adding Hooblyblob details...')
agent.add_file('./hooblyblob.txt', 'Details about the company Hooblyblob')

print('Adding rulebook details...')
agent.add_files(['./codenames-rulebook.pdf'], 'Rulebooks for various board games')

print('Adding MindsDB docs...')
agent.add_webpages(['docs.mindsdb.com'], 'Documentation for MindsDB')

print('Agent ready to use.')
while True:
    print('Ask a question: ')
    question = input()
    answer = agent.completion([{'question': question, 'answer': None}])
    print(answer.content)