Agents

Agents#

Datatune Agent allows large language models (LLMs) to autonomously plan and execute data transformation steps using natural language prompts.

Basic Usage#

import datatune as dt
from datatune.llm.llm import OpenAI
import dask.dataframe as dd

# Initialize LLM
llm = OpenAI(model_name="gpt-3.5-turbo")

# Load data
df = dd.read_csv("data.csv")

# Initialize Agent
agent = dt.Agent(llm,verbose=True)

# Transform data with natural language prompt
prompt = "your prompt for data transfromation"
df = agent.do(prompt,df,verbose=False)
 

# Compute DataFrame
result.compute().to_csv("transformed_data.csv")

Parameters#

  • llm (LLM, required): The large language model backend to be used for data tranformations (e.g. OpenAI, Azure etc)

  • verbose (bool, optional, default=False): If set to True, the agent will print the full generated plan, show detailed information for each transformation step and display error messages if a step fails.

Methods#

Agent.do()#

do(prompt: str, df: dask.dataframe.DataFrame) -> dask.dataframe.DataFrame

  • Executes a natural language prompt to transform the given dataframe.

Parameters

  • prompt (str, required): Natural language instruction describing the desired transformation.

  • df (dask.dataframe.DataFrame, required): Input dataframe to transform.

  • verbose (bool, optional, default=None): Controls logging behavior for this call.

    • If set to True, the agent will print the full generated plan, show detailed information for each transformation step and display error messages if a step fails.

    • If verbose is not provided, method uses Agent’s verbose setting.

Returns

  • pandas.DataFrame: A transformed pandas dataframe.

Examples#

For more advanced usage, see the examples folder.

Contents