Update Notes Extractor

A Python package designed to extract and structure release notes from software update announcements. This tool parses raw text input about software releases and formats key details such as version numbers, new features, bug fixes, and compatibility information.

Features

• Extracts structured release notes from raw text
• Supports custom LLM integration
• Focuses on technical software updates
• Avoids sensitive or non-technical content

Installation

pip install update_notes_extractor

Usage

Basic Usage

from update_notes_extractor import update_notes_extractor

user_input = "Your software update announcement text here"
response = update_notes_extractor(user_input)
print(response)

Using a Custom LLM

You can use any LLM compatible with LangChain. Here are examples with different LLMs:

Using OpenAI

from langchain_openai import ChatOpenAI
from update_notes_extractor import update_notes_extractor

llm = ChatOpenAI()
response = update_notes_extractor(user_input, llm=llm)
print(response)

Using Anthropic

from langchain_anthropic import ChatAnthropic
from update_notes_extractor import update_notes_extractor

llm = ChatAnthropic()
response = update_notes_extractor(user_input, llm=llm)
print(response)

Using Google

from langchain_google_genai import ChatGoogleGenerativeAI
from update_notes_extractor import update_notes_extractor

llm = ChatGoogleGenerativeAI()
response = update_notes_extractor(user_input, llm=llm)
print(response)

Using LLM7 API Key

By default, the package uses the ChatLLM7 from langchain_llm7. You can pass your own API key via an environment variable or directly in the function call.

Using Environment Variable

import os
from update_notes_extractor import update_notes_extractor

os.environ["LLM7_API_KEY"] = "your_api_key"
response = update_notes_extractor(user_input)
print(response)

Directly Passing API Key

from update_notes_extractor import update_notes_extractor

response = update_notes_extractor(user_input, api_key="your_api_key")
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 environment variable LLM7_API_KEY will be used.

Rate Limits

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If you need higher rate limits, you can get a free API key by registering at LLM7.

Issues

If you encounter any issues, please report them on the GitHub issues page.

Author

• Eugene Evstafev
• Email: hi@eugene.plus
• GitHub: chigwell