news-summerizer 2025.12.20202646

A new package that processes news headlines or short text snippets to generate structured summaries. It takes a headline or brief news text as input and uses an LLM to extract key information such as

news-summerizer

A lightweight Python package that turns concise news headlines or short snippets into structured summaries in a simple XML‑like format.
The output is well‑defined and machine‑readable, making the data usable for news aggregation, content tagging, or quick briefing generation.

Features

• Extract key facts from a headline or short text: event, location, involved parties, significance.
• Output is constrained by a regular expression so the result is always predictable.
• Works with any LangChain BaseChatModel, falling back to the default LLM7 model.
• Zero‑configuration: install once, drop into any project and call news_summerizer.

Installation

pip install news_summerizer

Quick Example

from news_summerizer import news_summerizer

user_input = (
    "Tesla's new Gigafactory in Austin expands production capacity for the Model 3 "
    "and the new Cybertruck, boosting U.S. manufacturing jobs."
)

summary = news_summerizer(user_input)
print(summary)
# [
#   "<summary>",
#   "  <event>Expanding production capacity</event>",
#   "  <location>Austin</location>",
#   "  <parties>Tesla, Model 3, Cybertruck</parties>",
#   "  <significance>Boosts U.S. manufacturing jobs</significance>",
#   "</summary>"
# ]

Parameters

Parameter	Type	Description
user_input	str	The headline or news snippet to process.
llm	Optional[BaseChatModel]	A LangChain chat model instance. If omitted, the package automatically creates a ChatLLM7 instance.
api_key	Optional[str]	LLM7 API key. If not supplied, the package looks for the LLM7_API_KEY environment variable, otherwise defaults to the free tier key ("None").

Custom LLMs

news_summerizer works with any LangChain model. Simply pass your own model instance:

OpenAI

from langchain_openai import ChatOpenAI
from news_summerizer import news_summerizer

llm = ChatOpenAI()
summary = news_summerizer(user_input, llm=llm)

Anthropic

from langchain_anthropic import ChatAnthropic
from news_summerizer import news_summerizer

llm = ChatAnthropic()
summary = news_summerizer(user_input, llm=llm)

Google Gemini

from langchain_google_genai import ChatGoogleGenerativeAI
from news_summerizer import news_summerizer

llm = ChatGoogleGenerativeAI()
summary = news_summerizer(user_input, llm=llm)

LLM7 API Key

The default free tier of LLM7 is usually sufficient. For higher rate limits:

• Set the LLM7_API_KEY environment variable, or
• Pass the key directly: news_summerizer(user_input, api_key="your_api_key")

Free API keys can be obtained by registering at https://token.llm7.io/.

Project Links

• GitHub: https://github.com/chigwell/news-summerizer
• Issues: https://github.com/chigwell/news-summerizer/issues

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Author

Eugene Evstafev
📧 [e-mail]
👤 LinkedIn

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License: MIT
Version: 0.1.0 (check PyPI for the latest release)