unix4summary

unix4summary is a lightweight Python package that extracts structured summaries and key information from textual prompts related to Unix Fourth Edition.
It parses user inputs—such as command descriptions, system behaviours, or feature overviews—and returns concise, well‑formatted details (e.g., command syntax, explanations, or expected outputs).
The tool relies on regular‑expression matching and a retry mechanism to guarantee consistent return formats, making it ideal for quick reference or documentation generation without handling multimedia content.

Table of Contents

• Installation
• Basic Usage
• Custom Language Model
  • OpenAI
  • Anthropic
  • Google Gemini
• Configuration
• Contributing
• License
• Author

Installation

pip install unix4summary

Basic Usage

from unix4summary import unix4summary

user_input = """
Explain the `exec` system call in Unix 4th Edition.
Provide the syntax and typical use cases.
"""

# Use the default LLM7 model
summary = unix4summary(user_input)

print(summary)

Output (example)

[
  "- Syntax: execve(const char *pathname, char *const argv[], char *const envp[])",
  "- Purpose: Replaces the current process image with a new process image.",
  "- Typical Usage: Executing a shell program from a custom script."
]

Custom Language Model

unix4summary uses ChatLLM7 (from langchain_llm7) by default.
You can provide any LangChain BaseChatModel instance to switch providers.

OpenAI

from langchain_openai import ChatOpenAI
from unix4summary import unix4summary

llm = ChatOpenAI()

response = unix4summary(user_input, llm=llm)
print(response)

Anthropic

from langchain_anthropic import ChatAnthropic
from unix4summary import unix4summary

llm = ChatAnthropic()

response = unix4summary(user_input, llm=llm)
print(response)

Google Gemini

from langchain_google_genai import ChatGoogleGenerativeAI
from unix4summary import unix4summary

llm = ChatGoogleGenerativeAI()

response = unix4summary(user_input, llm=llm)
print(response)

Tip: If you prefer to keep using the default ChatLLM7 but need higher rate limits, set an API key via the environment variable LLM7_API_KEY or pass it directly:

response = unix4summary(user_input, api_key="YOUR_LLM7_TOKEN")

You can obtain a free API key at https://token.llm7.io/.

Configuration Parameters

Contributing

Issues and pull requests are welcome!

• Issues: https://github.com/chigwell/unix4summary/issues

License

MIT © Eugene Evstafev

Author

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