removed tesseract ref

README.md

@@ -48,105 +48,14 @@ datafog-instructor show-fogprint
 
 What is a fogprint? A fogprint is a template that you can re-use, with specific configuration settings for the models, filenames, model_ids, and other important information to instruct an LLM to detect entities. This file is currently saved as fogprint.json.
 
-## Features
+### Verify the installation:
 
-### Detect Entities
-
-### Manage Entity Types
-
-## Default Entity Types
-
-## Error Handling
-
-## Development and Testing
-
-For development purposes, you can install additional dependencies:
-
-```
-pip install requirements-dev.txt
-
-## Documentation
-
-To build the documentation locally:
-
-```
-
-pip install datafog-instructor[docs]
-cd docs
-sphinx
-
-```
-
-The documentation will be available in the `docs/_build/html` directory.
-
-## Contributing
-
-Contributions to the DataFog Instructor SDK are welcome! Please feel free to submit a Pull Request.
-
-## License
-
-This project is licensed under the MIT License.
-
-## Support
-
-If you encounter any problems or have any questions, please open an issue on the GitHub repository or join our Discord community at https://discord.gg/bzDth394R4.
-
-## Links
-
-- Homepage: https://datafog.ai
-- Documentation: https://docs.datafog.ai
-- Twitter: https://twitter.com/datafoginc
-- GitHub: https://github.com/datafog/datafog-instructor
-
-# Entity Detection SDK: Installation and Getting Started Guide
-
-Welcome to the Entity Detection SDK! This powerful tool uses transformers and regex-constrained outputs to accurately identify entities in text. Follow this guide to get up and running quickly.
-
-## Installation
-
-1. Clone the repository:
-
-```
-
-git clone https://github.com/your-username/entity-detection-sdk.git
-cd entity-detection-sdk
-
-```
-
-2. Create a virtual environment (recommended):
-
-```
-
-python -m venv venv
-source venv/bin/activate # On Windows, use `venv\Scripts\activate`
-
-```
-
-3. Install the required dependencies:
-```
-
-pip install -r requirements.txt
-
-```
-
-## Getting Started
-
-1. Initialize the SDK:
-
-```
-
-python -m entity_detection init
-
-```
-
-This will create a `fogprint.json` file with default settings.
-
-2. Verify the installation:
 ```
 
 python -m entity_detection list-entities
 
 ```
+
 You should see a list of default entity types: PERSON, COMPANY, LOCATION, and ORG.
 
 ## Sample Operations
@@ -177,11 +86,13 @@ To change the default model or pattern:
 
 1. Edit the `fogprint.json` file directly, or
 2. Use the `init` command with the `--force` flag:
+
 ```
 
 python -m entity_detection init --force
 
 ```
+
 Follow the prompts to update your configuration.
 
 ## Advanced Usage
@@ -204,4 +115,47 @@ Exciting features are coming soon to enhance the SDK's capabilities:
 2. **Embeddings Layer**: Future versions will incorporate an embeddings layer to improve entity recognition accuracy.
 
 Stay tuned for updates!
+
 ```
+
+
+## Development and Testing
+
+For development purposes, you can install additional dependencies:
+
+```
+
+pip install requirements-dev.txt
+
+## Documentation
+
+To build the documentation locally:
+
+```
+
+pip install datafog-instructor[docs]
+cd docs
+sphinx
+
+```
+
+The documentation will be available in the `docs/_build/html` directory.
+
+## Contributing
+
+Contributions to the DataFog Instructor SDK are welcome! Please feel free to submit a Pull Request.
+
+## License
+
+This project is licensed under the MIT License.
+
+## Support
+
+If you encounter any problems or have any questions, please open an issue on the GitHub repository or join our Discord community at https://discord.gg/bzDth394R4.
+
+## Links
+
+- Homepage: https://datafog.ai
+- Documentation: https://docs.datafog.ai
+- Twitter: https://twitter.com/datafoginc
+- GitHub: https://github.com/datafog/datafog-instructor

config.json

@@ -0,0 +1,7 @@
+{
+  "model_id": "gpt2",
+  "filename": "gpt2",
+  "default_pattern": "(PERSON|COMPANY|LOCATION|ORG)",
+  "model_type": "huggingface",
+  "test_key": "test_value"
+}

tox.ini

@@ -1,5 +1,5 @@
 [tox]
-envlist = py310,py311,py312
+envlist = py310
 isolated_build = True
 
 [testenv]
@@ -10,11 +10,9 @@ deps =
     -r requirements-dev.txt
 extras = all
 allowlist_externals =
-    tesseract
     pip
 commands =
     pip install --no-cache-dir -r requirements-dev.txt
-    tesseract --version
     pytest {posargs} -v -s --cov=datafog --cov-report=term-missing
 
 [testenv:lint]