Initial README

README.md

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+# datasette-extract
+
+[![PyPI](https://img.shields.io/pypi/v/datasette-extract.svg)](https://pypi.org/project/datasette-extract/)
+[![Changelog](https://img.shields.io/github/v/release/datasette/datasette-extract?include_prereleases&label=changelog)](https://github.com/datasette/datasette-extract/releases)
+[![Tests](https://github.com/datasette/datasette-extract/workflows/Test/badge.svg)](https://github.com/datasette/datasette-extract/actions?query=workflow%3ATest)
+[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/datasette/datasette-extract/blob/main/LICENSE)
+
+Import unstructured data (text and images) into structured tables
+
+## Installation
+
+Install this plugin in the same environment as [Datasette](https://datasette.io/).
+```bash
+datasette install datasette-extract
+```
+
+## Configuration
+
+This plugin requires an `OPENAI_API_KEY` environment variable with an [OpenAI API key](https://platform.openai.com/api-keys).
+
+## Usage
+
+This plugin provides the following features:
+
+- In the database action cog menu for a database select "Create table with extracted data" to create a new table with data extracted from text or an image
+- In the table action cog menu select "Extract data into this table" to extract data into an existing table
+
+When creating a table you can specify the column names, types and provide an optional hint (like "YYYY-MM-DD" for dates) to influence how the data should be extracted.
+
+When populating an existing table you can provide hints and select which columns should be populated.
+
+Text input can be pasted directly into the textarea.
+
+Drag and drop a PDF or text file onto the textarea to populate it with the contents of that file. PDF files will have their text extracted, but only if the file contains text as opposed to scanned images.
+
+Images can be uploaded directly. These will have OCR run against them using GPT-4 Vision and then that text will be used for structured data extraction.
+
+## Development
+
+To set up this plugin locally, first checkout the code. Then create a new virtual environment:
+```bash
+cd datasette-extract
+python3 -m venv venv
+source venv/bin/activate
+```
+Now install the dependencies and test dependencies:
+```bash
+pip install -e '.[test]'
+```
+To run the tests:
+```bash
+pytest
+```