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README.md
107
README.md
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@ -1,76 +1,67 @@
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# AnkiAI - Automated Anki Deck Creator
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# AnkiAI
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AnkiAI is a tool that leverages OCR (Optical Character Recognition) and GPT-3's powerful natural language processing capabilities to automatically generate Anki decks from images containing text.
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AnkiAI is a robust system that converts images containing text into structured Anki cards using Optical Character Recognition (OCR) and OpenAI's GPT-4 language model. Users can quickly generate decks of flashcards from their images for effective study.
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### Overview
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## Features
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- Converts image content to textual content using OCR.
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- Uses OpenAI's GPT-4 model to structure the content into Anki decks and cards.
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- Outputs the structured content as an Anki package.
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- AnkiAI is designed to streamline the process of creating Anki decks from images.
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- The core idea is to use OCR to extract text from images and then use GPT-3 to transform this text into a structured Anki deck format.
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- Users can make a POST request to a Flask server endpoint with their images to receive the Anki deck (.apkg file).
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## Dependencies
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- genanki: Used for creating Anki decks and cards.
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- Pillow: Image processing library.
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- openai: API library for OpenAI's GPT-4 model.
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- flask: Web server to host the service.
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### Directory Structure
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- `.vscode/`: Contains configuration for VSCode debugger for Flask applications.
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- `ankiai.py`: The main script that drives the creation of Anki decks from images.
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- `constants.py`: Contains constant variables used across the project.
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- `deck_creation.py`: Contains logic for communicating with OpenAI's API and deck creation using genanki.
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- `image_processing.py`: Processes images, converting them for OCR and then performing OCR to extract text.
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- `logging_config.py`: Logging configuration for the entire project.
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- `server.py`: Flask server that provides an API endpoint to upload images and get back an Anki deck.
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### Requirements
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To run AnkiAI, you'll need to have the following dependencies installed:
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```
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genanki==0.8.0
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Pillow
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openai
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flask
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```
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You can install these via `pip` using the `requirements.txt` file:
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```bash
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pip install -r requirements.txt
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```
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### How to Run
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1. **Environment Variables**: Make sure to set the `OPENAI_API_KEY` environment variable to your OpenAI API key.
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2. **Run the Flask server**:
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## Setup and Installation
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1. Clone this repository:
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```bash
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python server.py
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git clone https://git.rudefox.io/bj/anki-json2ankicards.git
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cd json2ankicards
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```
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This will start the Flask server. You can then make a POST request to `http://localhost:5000/deck-from-images` with your images to get an Anki deck.
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3. **Run Directly**:
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If you prefer not to use the Flask server, you can also run `ankiai.py` directly:
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2. Set up a virtual environment and activate it:
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```bash
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python ankiai.py <directory_path_containing_images>
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python3 -m venv venv
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source venv/bin/activate
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```
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### How to Debug (VSCode Users)
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3. Install the required packages:
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```bash
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pip install -r requirements.txt
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```
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- Open the project in VSCode.
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- Set up your breakpoints.
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- Use the VSCode debugger and select "Python: Flask" to start debugging the Flask server.
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4. Set up the OpenAI API key:
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```bash
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export OPENAI_API_KEY=your_openai_api_key
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```
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### Important Notes
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5. Run the server:
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```bash
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python server.py
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```
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- **API Key**: For the project to work, it is essential to have the `OPENAI_API_KEY` environment variable set.
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- **Image Types**: Currently, the image processing module supports PNG, JPG, and JPEG formats.
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- **Output**: The output `.apkg` file (Anki package file) will be named `out.apkg`.
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## Usage
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### Acknowledgements
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1. Start the server as mentioned above.
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This project heavily relies on the `openai` library for processing and the `genanki` library for deck generation.
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2. Use a tool like [Postman](https://www.postman.com/) or `curl` to send images to `http://localhost:5000/deck-from-images` as a multi-part POST request.
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### Contributions
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3. The server will respond with a downloadable Anki package. Import this into your Anki app and start studying!
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Contributions are always welcome. Please create a new issue or a pull request for any bug fixes or feature requests.
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## Modules
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1. **ankiai.py**: The main module that orchestrates the flow.
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2. **images2text.py**: Converts image content into text using OCR.
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3. **json2deck.py**: Converts structured JSON data into an Anki package.
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4. **prompt4cards.py**: Uses OpenAI to structure the content into Anki decks and cards.
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5. **server.py**: Flask server to host the service.
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## Contributing
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Contributions are welcome! Please submit a pull request or open an issue to discuss changes or fixes.
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## License
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[MIT License](LICENSE)
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17
ankiai.py
17
ankiai.py
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@ -2,18 +2,18 @@ import sys
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import logging
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from logging_config import setup_logging
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from image_processing import process_images
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from deck_creation import prompt_for_card_content, response_to_json, to_package
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APKG_FILE = "out.apkg"
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from images2text import main as ocr_images
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from prompt4cards import prompt_for_card_content, response_to_json
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from json2deck import to_package
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setup_logging()
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def images_to_package(directory_path):
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ocr_text = process_images(directory_path)
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def images_to_package(directory_path, outfile):
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ocr_text = ocr_images(directory_path)
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response_text = prompt_for_card_content(ocr_text)
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deck_json = response_to_json(response_text)
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return to_package(deck_json)
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to_package(deck_json).write_to_file(outfile)
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logging.info(f"Deck created at: {outfile}")
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if __name__ == "__main__":
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print("Usage: python ankiai.py <directory_path_containing_images>")
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sys.exit(1)
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images_to_package(sys.argv[1]).write_to_file(APKG_FILE)
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logging.info(f"Deck created at: {APKG_FILE}")
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images_to_package(sys.argv[1])
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# File and Directory Constants
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IMAGE_KEY="image"
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APKG_FILE="out.apkg"
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CONVERTED_DIR = "converted"
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TEXT_OCR_FILE = "final.txt"
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FINAL_OUTPUT = "final.txt"
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IMAGE_EXTENSIONS = ['.png', '.jpg', '.jpeg']
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DECK_JSON_FILE = "output_deck.json"
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OUTPUT_FILENAME = "output_deck.json"
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# API Constants
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API_KEY_ENV = "OPENAI_API_KEY"
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20
image_processing.py → images2text.py
Normal file → Executable file
20
image_processing.py → images2text.py
Normal file → Executable file
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from logging_config import setup_logging
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from subprocess import run, CalledProcessError
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from concurrent.futures import ThreadPoolExecutor
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from constants import CONVERTED_DIR, TEXT_OCR_FILE, IMAGE_EXTENSIONS
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from utilities import is_image_file, ensure_directory_exists
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from constants import CONVERTED_DIR, FINAL_OUTPUT
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setup_logging()
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def is_image_file(path):
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return any(path.lower().endswith(ext) for ext in IMAGE_EXTENSIONS)
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def ensure_directory_exists(directory):
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if not os.path.exists(directory):
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os.mkdir(directory)
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def convert_image(image_path):
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logging.info(f"Converting {image_path}...")
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converted_path = os.path.join(CONVERTED_DIR, os.path.basename(image_path))
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return None
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def process_images(directory_path):
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def main(directory_path):
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final_text = []
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ensure_directory_exists(CONVERTED_DIR)
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# Filter out any None values and write the text to final.txt
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final_text = [text for text in final_text if text is not None]
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with open(TEXT_OCR_FILE, 'w') as f:
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with open(FINAL_OUTPUT, 'w') as f:
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f.write("\n".join(final_text))
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logging.info(f"All images processed! Final output saved to {TEXT_OCR_FILE}")
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logging.info(f"All images processed! Final output saved to {FINAL_OUTPUT}")
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return final_text # Add this line
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if len(sys.argv) != 2:
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print("Usage: python images2text.py <directory_path>")
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sys.exit(1)
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process_images(sys.argv[1])
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main(sys.argv[1])
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61
json2deck.py
Normal file
61
json2deck.py
Normal file
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import json
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import genanki
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import sys
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import logging
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from logging_config import setup_logging
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setup_logging()
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# Create a new model for our cards. This is necessary for genanki.
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MY_MODEL = genanki.Model(
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1607372319,
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"Simple Model",
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fields=[
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{"name": "Title"},
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{"name": "Question"},
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{"name": "Answer"},
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],
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templates=[
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{
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"name": "{{Title}}",
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"qfmt": "{{Question}}",
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"afmt": "{{FrontSide}}<hr id='answer'>{{Answer}}",
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},
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])
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def json_file_to_package(json_path):
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with open(json_path, 'r', encoding='utf-8') as f:
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json_data = json.load(f)
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package = to_package(json_data)
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return package
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def to_package(deck_json):
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deck_title = deck_json["DeckTitle"]
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deck = genanki.Deck(1607372319, deck_title)
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for card_json in deck_json["Cards"]:
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title = card_json["Title"]
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question = card_json["Question"]
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answer = card_json["Answer"]
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note = genanki.Note(
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model=MY_MODEL,
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fields=[title, question, answer]
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)
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deck.add_note(note)
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return genanki.Package(deck)
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if __name__ == "__main__":
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if len(sys.argv) != 3:
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print("Usage: python convert.py <input_json> <output_apkg>")
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sys.exit(1)
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input_json = sys.argv[1]
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output_apkg = sys.argv[2]
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json_file_to_package(input_json).write_to_file(output_apkg)
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logging.info(f"Deck created at: {output_apkg}")
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import openai
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import os
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import sys
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import json
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import genanki
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from logging_config import setup_logging
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from constants import API_KEY_ENV, CHAT_MODEL
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setup_logging()
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from constants import API_KEY_ENV, CHAT_MODEL, OUTPUT_FILENAME
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API_KEY = os.environ.get(API_KEY_ENV)
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}
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# Create a new model for our cards. This is necessary for genanki.
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MY_MODEL = genanki.Model(
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1607372319,
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"Simple Model",
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fields=[
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{"name": "Title"},
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{"name": "Question"},
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{"name": "Answer"},
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],
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templates=[
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{
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"name": "{{Title}}",
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"qfmt": "{{Question}}",
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"afmt": "{{FrontSide}}<hr id='answer'>{{Answer}}",
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},
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])
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if __name__ == "__main__":
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if len(sys.argv) != 2:
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print("Usage: python prompt4cards.py <text_file_path>")
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sys.exit(1)
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text_file_path = sys.argv[1]
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def json_file_to_package(json_path):
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with open(json_path, 'r', encoding='utf-8') as f:
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json_data = json.load(f)
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package = to_package(json_data)
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# Read the text content
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with open(text_file_path, 'r') as file:
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text_content = file.read()
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return package
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response_text = prompt_for_card_content(text_content)
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deck_json = response_to_json(response_text)
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def to_package(deck_json):
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deck_title = deck_json["DeckTitle"]
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deck = genanki.Deck(1607372319, deck_title)
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with open(OUTPUT_FILENAME, 'w') as json_file:
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json.dump(deck_json, json_file)
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for card_json in deck_json["Cards"]:
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title = card_json["Title"]
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question = card_json["Question"]
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answer = card_json["Answer"]
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note = genanki.Note(
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model=MY_MODEL,
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fields=[title, question, answer]
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)
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deck.add_note(note)
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return genanki.Package(deck)
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print(f"Saved generated deck to {OUTPUT_FILENAME}")
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10
server.py
10
server.py
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import shutil
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import logging
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from logging_config import setup_logging
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from flask import Flask, request, send_from_directory, jsonify
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from werkzeug.utils import secure_filename
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from ankiai import images_to_package
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from constants import IMAGE_KEY, APKG_FILE, NO_IMAGE_PART_ERROR, NO_SELECTED_FILE_ERROR, INVALID_FILENAME_ERROR
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from constants import IMAGE_KEY, OUTPUT_FILE, NO_IMAGE_PART_ERROR, NO_SELECTED_FILE_ERROR, INVALID_FILENAME_ERROR
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from logging_config import setup_logging
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setup_logging()
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from logging_config import setup_logging
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app = Flask(__name__)
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def save_uploaded_images(images, directory):
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save_uploaded_images(images, temp_dir)
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try:
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images_to_package(temp_dir).write_to_file(APKG_FILE)
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logging.info(f"Anki package written to {APKG_FILE}")
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return send_from_directory('.', APKG_FILE, as_attachment=True)
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images_to_package(temp_dir, OUTPUT_FILE)
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return send_from_directory('.', OUTPUT_FILE, as_attachment=True)
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except Exception as e:
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logging.error("Exception occurred: "+str(e), exc_info=True)
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return jsonify({'error': str(e)}), 500
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9
utilities.py
Normal file
9
utilities.py
Normal file
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import os
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from constants import IMAGE_EXTENSIONS
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def is_image_file(path):
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return any(path.lower().endswith(ext) for ext in IMAGE_EXTENSIONS)
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def ensure_directory_exists(directory):
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if not os.path.exists(directory):
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os.mkdir(directory)
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