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)

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

# 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)

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.

Returns

  • dask.dataframe.DataFrame: A transformed dataframe, ready for .compute() or further processing.

Agent.do() internally finalizes the resultant DataFrame and therefore can be readily computed.

Examples#

For more advanced usage, see the examples folder.

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