unstructured

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History

feat: add ability to pass headers in partition_html (#397 )

Also adds pytest-mock requirement, those fixtures are nice to have!

Implements issue/feature #396 .

2023-03-23 20:14:57 -07:00

.gitignore

docs: example notebooks from community repo (#187 )

2023-01-31 10:37:32 -05:00

fetch.py

feat: add ability to pass headers in partition_html (#397 )

2023-03-23 20:14:57 -07:00

README.md

Resolve numerous typos (#280 )

2023-02-24 17:48:23 -08:00

requirements.in

build(deps): bump dependencies; resolve security issues in example dependencies (#300 )

2023-02-27 12:45:28 -05:00

requirements.txt

build(deps): bump dependencies; resolve security issues in example dependencies (#300 )

2023-02-27 12:45:28 -05:00

sec-sentiment-analysis.ipynb

docs: update sec-sentiment-analysis.ipynb (#342 )

2023-03-06 15:16:14 +00:00

README.md

SEC Sentiment Analysis Model

This directory contains an example of how to use the SEC API, the Unstructured SEC pipeline API, and several bricks from the unstructured library to train a sentiment analysis model for the risk factors section of S-1 filings. To get started, use the following steps:

Ensure you have Python 3.8 or higher installed on your system
Create a new Python virtual environment
Run pip install -r requirements.txt to install the dependencies
Run PYTHONPATH=. jupyter notebook from this directory to launch the notebook

At this point, you'll be able to run the sentiment analysis example notebook.