inmydata 0.0.15

This package provides simple API access to the inmydata platform

Agent SDK

The inmydata agent SDK enables you to build AI agents that can rapidly access data from the inmydata platform.

Features

• Conversational data interface - retrieve data with natural language queries
• Structured data interface - rapidly build data interfaces for you AI agents
• Calendar assistant - empower your AI agent with detailed knowledge of your financial calendars

Installation

Install the inmydata agent SDK with pip

  pip install inmydata

Documentation

See https://developer.inmydata.com for quickstarts, documentation, and examples.

Usage/Examples

For these examples you will need to set the following environment variables:

• INMYDATA_API_KEY
• INMYDATA_TENANT
• INMYDATA_CALENDAR

Example of retrieving structured data

import os
from dotenv import load_dotenv
from inmydata.StructuredData import StructuredDataDriver, AIDataSimpleFilter, AIDataFilter, LogicalOperator, ConditionOperator
load_dotenv()

driver = StructuredDataDriver(os.environ['INMYDATA_TENANT'])

# -- Use get_data_simple when your filter is simple (only equality filters, no bracketing, no ORs, etc.)

# Build our simple filter
filter = []
filter.append(
    AIDataSimpleFilter(
        "Store", # Field to filter on
        "Edinburgh") # Value to filter by
    ) 
df = driver.get_data_simple(
    "Inmystore Sales", # Name of the subject we want to extract data from
    ["Financial Year","Sales Value"], # List of fields we want to extract
    filter, # Filters to apply
    False) # Whether filters are case sensitive

print(df)

# -- Use get_data when your filter more complex (non-equality matches, bracketing, ORs, etc.) --

# Build our filter
filter = [] 
filter.append(
    AIDataFilter(
        "Store",
        ConditionOperator.Equals, # Condition to use in the filter
        LogicalOperator.And, # Logical operator to use in the filter
        "Edinburgh", # Value to filter by
        0, # Number of brackets before this condition
        0, # Number of brackets after this condition
        False # Whether the filter is case sensitiv
    )
)
filter.append(
    AIDataFilter(
        "Store",
        ConditionOperator.Equals, # Condition to use in the filter
        LogicalOperator.Or, # Logical operator to use in the filter
        "London", # Value to filter by
        0, # Number of brackets before this condition
        0, # Number of brackets after this condition
        False # Whether the filter is case sensitiv
    )
)
df = driver.get_data(
    "Inmystore Sales", # Name of the subject we want to extract data from
    ["Financial Year","Store","Sales Value"], # List of fields we want to extract
    filter) # Filters to apply

print(df)

Example of retrieving conversational data

import os

from dotenv import load_dotenv
from inmydata.ConversationalData import ConversationalDataDriver
import asyncio

load_dotenv()

# get_answer is an async function, so we need to run it in an event loop
async def main():
    driver = ConversationalDataDriver(os.environ['INMYDATA_TENANT'])

    # Register a callback to handle AI question updates
    def on_ai_question_update(caller, message):  
        print(message)

    # Register the callback handler for AI question updates
    driver.on("ai_question_update", on_ai_question_update) 

    question = "Give me the top 10 stores this year"
    answer = await driver.get_answer(question)
    
    print("=================================================================")
    print(f"The answer was: {answer.answer}")
    print(f"The subject used to generate the answer was: {answer.subject}")


asyncio.run(main())

Example of retrieving calendar periods

import os

from datetime import date
from dotenv import load_dotenv
from inmydata.CalendarAssistant import CalendarAssistant

load_dotenv()

# Get today's date
today = date.today()

# Initialize the Calendar Assistant with tenant and calendar name
assistant = CalendarAssistant(os.environ['INMYDATA_TENANT'], os.environ['INMYDATA_CALENDAR'])

# Get the current financial year
print("The current financial year is:  " + str(assistant.get_financial_year(today)))
# Get the current financial quarter
print("The current financial quarter is: " + str(assistant.get_quarter(today)))
# Get the current financial month
print("The current financial month is: " + str(assistant.get_month(today)))
# Get the current financial week
print("The current financial week is: " + str(assistant.get_week_number(today)))
# Get the current financial periods
print("The current periods are:")
print(assistant.get_financial_periods(today))