newspresso 2025.12.21175020

A new package that processes text-based news or announcement summaries, such as changes in chart inclusion rules for platforms like YouTube on the U.S. Billboard Charts. It uses structured LLM interac

newspresso

A Python package for processing text-based news or announcement summaries using structured LLM interactions. It extracts key details—such as effective dates, criteria adjustments, and impacted metrics—from text inputs, ensuring consistent and reliable output for media analysis or reporting workflows.

Installation

Install the package via pip:

pip install newspresso

Usage

Import the newspresso function and pass your text to process:

from newspresso import newspresso

user_input = "Your news or announcement text here..."
result = newspresso(user_input)
print(result)

Parameters

• user_input (str): The text input to process (e.g., news summary or announcement).
• llm (Optional[BaseChatModel]): A LangChain LLM instance. If not provided, the default ChatLLM7 is used.
• api_key (Optional[str]): API key for LLM7. If not provided, the environment variable LLM7_API_KEY is used, or a default key is attempted.

Using a Custom LLM

You can use any LangChain-compatible LLM by passing it to the llm parameter. For example:

Using OpenAI

from langchain_openai import ChatOpenAI
from newspresso import newspresso

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

Using Anthropic

from langchain_anthropic import ChatAnthropic
from newspresso import newspresso

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

Using Google

from langchain_google_genai import ChatGoogleGenerativeAI
from newspresso import newspresso

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

API Key for Default LLM7

The default LLM (ChatLLM7) is provided via the langchain_llm7 package (see PyPI). The free tier rate limits are sufficient for most use cases. For higher limits, provide your own API key:

• Set the environment variable: LLM7_API_KEY="your_api_key"
• Or pass directly: newspresso(user_input, api_key="your_api_key")

Get a free API key by registering at https://token.llm7.io/.

Example

from newspresso import newspresso

news_text = """
YouTube announced changes to its chart inclusion rules effective January 2025. 
Streams will now require a minimum of 1,000 plays per track, up from 500. 
These updates impact the U.S. Billboard Charts and global metrics.
"""

details = newspresso(news_text)
print(details)
# Output may include: ['effective_date: January 2025', 'criteria_adjustment: minimum streams increased to 1000', ...]

Dependencies

• langchain_core
• langchain_llm7 (for default LLM)
• llmatch_messages (for pattern matching)

Issues

Report issues or contribute via GitHub: https://github.com/chigwell/newspresso

Author

Eugene Evstafev – [e-mail]