Attributes of the DataAnalyzr Class

Overview of the attributes of the DataAnalyzr class in the lyzr library

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.

Basic Attributes

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

The type of analysis to be performed.

params · ParamsDict

Dictionary of class parameters.

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max_retries · integer

Maximum number of retries for the LLM calls and analysis. Default is 10.

time_limit · integer

Time limit in seconds for the LLM calls and analysis. Default is 45 for analysis and 60 for visualisation.

auto_train · boolean

Whether to automatically add questions with their SQL query or Python code to the vector store. Default is True.

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.

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model · string

Name of the LLM model to use.

api_key · string

API key for accessing LLM services. May also be set as an environment variable.

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.

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model · string

Name of the LLM model to use.

api_key · string

API key for accessing LLM services. May also be set as an environment variable.

context · ContextDict

Context dictionary for the analysis.

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analysis · string

Context for the analysis.

visualisation · string

Context for the visualisation generation.

insights · string

Context for the insights generation.

recommendations · string

Context for the recommendations generation.

tasks · string

Context for the tasks generation.

logger · logging.Logger

Logger object for logging messages.

Data Related Attributes

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.

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host · string

Hostname of the database server. Applicable for PostgreSQL and Redshift databases.

port · string

Port number of the database server. Applicable for PostgreSQL and Redshift databases.

user · string

Username for the database connection. Applicable for PostgreSQL and Redshift databases.

database · string

Name of the database to connect to. Applicable for PostgreSQL and Redshift databases.

password · string

Password for the database connection. Applicable for PostgreSQL and Redshift databases.

schema · list

Schema names to load. Applicable for PostgreSQL and Redshift databases.

tables · list

Table names to load. Applicable for PostgreSQL and Redshift databases.

conn · psycopg2.connect or redshift_connector.connect or sqlite3.connect

Connection object for the database.

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.

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path · string

Path to the vector store file.

chroma_client · chromadb.PersistentClient

ChromaDB client object for storing vectors.

documentation_collection · chromadb.Collection

Collection object for storing documentation.

ddl_collection · chromadb.Collection

Collection object for storing DDL queries.

sql_collection · chromadb.Collection

Collection object for storing question and SQL query pairs.

python_collection · chromadb.Collection

Collection object for storing question and Python code pairs.

plot_collection · chromadb.Collection

Collection object for storing question and plot code pairs.

Analysis Related Attributes

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.

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"],
}