1. Basic Attributes - Instance configuration attributes. Include analysis_type, params, generator_llm, analysis_llm, context, logger.
  2. Data Related Attributes - Input dataset and vector store connections. Include df_dict, database_connector, vector_store.
  3. Analysis Related Attributes - Values generated during analysis. Include analysis_code, analysis_guide, analysis_output, plot_code.
  4. Output Attributes - Output values returned as responses. Include plot_output, insights_output, recommendations_output, tasks_output, ai_queries_output.

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Basic Attributes

analysis_type
Literal['sql', 'ml', 'skip']

The type of analysis to be performed.

params
ParamsDict

Dictionary of class parameters.

generator_llm
LiteLLM

LLM instance for generating analysis. Default LLM used is GPT-4o.

For details on configuring the LLM, see the Large Language Models guide.

analysis_llm
LiteLLM

LLM instance for performing analysis. Default LLM used is GPT-4o.

For details on configuring the LLM, see the Large Language Models guide.

context
ContextDict

Context dictionary for the analysis.

logger
logging.Logger

Logger object for logging messages.

df_dict
dictionary

Dictionary of dataframes loaded from files or databases.

df_dict = {
    "table_name": pandas.DataFrame,
}
database_connector
DatabaseConnector

Database connector object for connecting to databases.

vector_store
ChromaDBVectorStore

Vector store object for storing questions and their SQL queries or Python code.

For details on configuring the vector store, see the Vector Store guide.

analysis_code
string

Code generated by the LLM for analysis.

analysis_guide
string

Guide used to generate the analysis code.

analysis_output
pandas.DataFrame or dictionary or string

Output generated by executing the analysis code.

plot_code
string

Code generated by the LLM for generating visualisations.

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Output Attributes

plot_output
string

Path to a PNG file containing the plot generated by executing the plot code.

insights_output
string

Insights generated by the LLM.

recommendations_output
string

Recommendations generated by the LLM.

tasks_output
string

Tasks generated by the LLM.

ai_queries_output
dictionary

AI queries generated by the LLM.

ai_queries_output = {
    "type_of_analysis1": ["query1", "query2", "query3", "query4"],
    "type_of_analysis2": ["query1", "query2", "query3", "query4"],
    "type_of_analysis3": ["query1", "query2", "query3", "query4"],
}
Get ResultsAdditional Methods