https://github.com/chigwell/newspresso
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
https://github.com/chigwell/newspresso
announcement-summaries automated-parsing chart-inclusion-rules consistent-output criteria-adjustments effective-dates formatted-insights impacted-metrics key-details-extraction media-analysis no-raw-media-handling reliable-output reporting-workflows structured-llm-interactions text-based-news-processing text-input-focus
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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
- Host: GitHub
- URL: https://github.com/chigwell/newspresso
- Owner: chigwell
- Created: 2025-12-21T17:50:20.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-12-21T17:50:32.000Z (6 months ago)
- Last Synced: 2025-12-23T06:55:33.476Z (6 months ago)
- Topics: announcement-summaries, automated-parsing, chart-inclusion-rules, consistent-output, criteria-adjustments, effective-dates, formatted-insights, impacted-metrics, key-details-extraction, media-analysis, no-raw-media-handling, reliable-output, reporting-workflows, structured-llm-interactions, text-based-news-processing, text-input-focus
- Language: Python
- Homepage: https://pypi.org/project/newspresso/
- Size: 3.91 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: newspresso/__init__.py
Awesome Lists containing this project
README
# newspresso
[](https://badge.fury.io/py/newspresso)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/project/newspresso)
[](https://www.linkedin.com/in/eugene-evstafev-716669181/)
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:
```bash
pip install newspresso
```
## Usage
Import the `newspresso` function and pass your text to process:
```python
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
```python
from langchain_openai import ChatOpenAI
from newspresso import newspresso
llm = ChatOpenAI()
response = newspresso(user_input, llm=llm)
```
#### Using Anthropic
```python
from langchain_anthropic import ChatAnthropic
from newspresso import newspresso
llm = ChatAnthropic()
response = newspresso(user_input, llm=llm)
```
#### Using Google
```python
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](https://pypi.org/project/langchain-llm7/)). 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/](https://token.llm7.io/).
## Example
```python
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](https://github.com/chigwell/newspresso)
## Author
Eugene Evstafev – hi@euegne.plus