budgetscribe 2025.12.21124349

A new package that analyzes user-provided text descriptions of their monthly expenses and income to generate a structured affordability assessment. It categorizes spending, identifies potential saving

BudgetScribe Package

A new package that analyzes user-provided text descriptions of their monthly expenses and income to generate a structured affordability assessment.

Overview

This package categorizes spending, identifies potential savings areas, and returns a clear breakdown of financial health without requiring sensitive data like bank statements. It helps users understand their budget can be optimized in a private, non-intrusive way.

Installation

pip install budgetscribe

Usage

from budgetscribe import budgetscribe

user_input = "I spend $500 on rent, $300 on groceries, and $200 on entertainment."
response = budgetscribe(user_input)
print(response)

Parameters

• user_input: str : the user input text to process
• llm: Optional[BaseChatModel] : the langchain llm instance to use, if not provided the default ChatLLM7 will be used.
• api_key: Optional[str] : the api key for llm7, if not provided the LLM7_API_KEY environment variable will be used.

LLM Integration

This package uses ChatLLM7 from langchain_llm7 by default. However, developers can safely pass their own llm instance (based on https://docs.langchain.com) if they want to use another LLM.

For example, to use the openai LLM:

from langchain_openai import ChatOpenAI
from budgetscribe import budgetscribe

llm = ChatOpenAI()
response = budgetscribe(user_input, llm=llm)

or to use the anthropic LLM:

from langchain_anthropic import ChatAnthropic
from budgetscribe import budgetscribe

llm = ChatAnthropic()
response = budgetscribe(user_input, llm=llm)

or to use the google LLM:

from langchain_google_genai import ChatGoogleGenerativeAI
from budgetscribe import budgetscribe

llm = ChatGoogleGenerativeAI()
response = budgetscribe(user_input, llm=llm)

LLM7 Rate Limits

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. However, if higher rate limits are needed, developers can pass their own api_key via environment variable LLM7_API_KEY or directly like budgetscribe(user_input, api_key="their_api_key").

To get a free API key, visit https://token.llm7.io/.

Documentation and Support

Issues and feature requests: https://github.com/chigwell/budgetscribe

Author: Eugene Evstafev ([e-mail])