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Yandrik 2024-02-01 12:56:34 +01:00
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12
.gitignore vendored Normal file
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/.ing
apikey.secret
*.secret
*.pdf
*.jpg
*.png
*.PNG
out.md
out.old.md
/__pycache__

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# Default ignored files
/shelf/
/workspace.xml
# Editor-based HTTP Client requests
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml

8
.idea/anki-from-dictionary.iml Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$" />
<orderEntry type="inheritedJdk" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
</module>

6
.idea/inspectionProfiles/profiles_settings.xml Normal file
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<component name="InspectionProjectProfileManager">
<settings>
<option name="USE_PROJECT_PROFILE" value="false" />
<version value="1.0" />
</settings>
</component>

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.idea/misc.xml Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="Black">
<option name="sdkName" value="Poetry (anki-from-dictionary)" />
</component>
<component name="ProjectRootManager" version="2" project-jdk-name="Poetry (anki-from-dictionary)" project-jdk-type="Python SDK" />
</project>

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.idea/modules.xml Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/.idea/anki-from-dictionary.iml" filepath="$PROJECT_DIR$/.idea/anki-from-dictionary.iml" />
</modules>
</component>
</project>

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.idea/vcs.xml Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="$PROJECT_DIR$" vcs="Git" />
</component>
</project>

156
dict_to_anki.py Normal file
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import base64
from typing import Any
import requests
from PIL import Image
from io import BytesIO
# OpenAI API Key
import prompt
try:
with open('apikey.secret') as f:
api_key = f.read().strip()
except FileNotFoundError:
print('Couldn\'t read API key from file \'apikey.secret\'w. Does it exist?')
# Function to encode image
def encode_image(image):
buffered = BytesIO()
image.save(buffered, format="JPEG", quality=95)
img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
return img_str
# Function to resize the image
def resize_image(input_image_path, max_height, max_width):
original_image = Image.open(input_image_path)
width, height = original_image.size
# resize amount required
wr = max_width / width
hr = max_height / height
if wr < 1 or hr < 1:
ratio = min(wr, hr)
image = original_image.resize((int(ratio * width), int(ratio * height)))
else:
image = original_image
return image
def crop_image_to_left_side(image: Image, crop_width) -> Image:
return image.crop((0, 0, min(image.size[0], crop_width), image.size[1]))
# Resize the image and get base64 string
# resized_image = resize_image(image_path, 1024, 512)
def image_to_anki(image_paths: str | list[str]) -> tuple[str | None, Any]:
images = []
if isinstance(image_paths, str):
image_paths = [image_paths]
for image_path in image_paths:
resized_image = resize_image(image_path, 1536, 1024) # seems to work good for these dict pages
cropped_image = crop_image_to_left_side(resized_image, 512)
# cropped_image.show()
# print(cropped_image.size)
# exit(1)
base64_image = encode_image(cropped_image)
images.append(base64_image)
# print(resized_image.size)
# exit(1)
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"model": "gpt-4-vision-preview",
"messages": [
{
"role": "system",
"content": [
{
"type": "text",
"text": prompt.SYSTEM_PROMPT,
}
]
},
{
"role": "user",
"content": [
{
"type": "text",
"text": "Transform this image into Anki cards."
},
# {
# "type": "image_url",
# "image_url": {
# "url": f"data:image/jpeg;base64,{base64_image}"
# }
# }
] + [{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{base64_image}"
}
}
for base64_image in images]
}
],
"max_tokens": 600 * len(images), # in general, around 350 tokens per page, so around double to be safe
"temperature": 0.0,
}
response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
response_json = response.json()
# print(response_json)
# Extracting the completion
try:
completion = response_json['choices'][0]['message']['content']
except KeyError:
completion = None
# print(completion)
return completion, response_json
def test():
# Path to your image
# image_paths = "IMG_5334.PNG"
# image_path = 'tmp.jpg'
image_path = [
'./.img/dict.pdf_7.png',
'./.img/dict.pdf_8.png',
]
text, meta = image_to_anki(image_path)
print(text)
usage = meta['usage']
print(
f'usage for page:\n{usage["prompt_tokens"]} prompt tokens and {usage["completion_tokens"]} completion tokens')
print(
f'approx. cost: 0.0075$ per picture, {usage["prompt_tokens"] * 0.01 / 1000}$ for prompt tokens and {usage["completion_tokens"] * 0.01 / 1000}$ for completion tokens')
cost_this = usage["prompt_tokens"] * 0.01 / 1000 + usage["completion_tokens"] * 0.01 / 1000 + 0.0075
print(f'this page: {cost_this}$')
if __name__ == '__main__':
test()

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main.py Normal file
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import argparse
import os
from pdf2image import convert_from_path
import dict_to_anki # ensure dict_to_anki is imported
IMGS_PER_REQUEST = 2
def is_parsable_to_int(input_string):
try:
int(input_string)
return True
except ValueError:
return False
def main():
parser = argparse.ArgumentParser(description='Parse PDF pages to MD.')
parser.add_argument('--pages', type=str, required=True, help='Specify pages to parse in format <num>-<num>')
parser.add_argument('--output-file', type=str, default='out.md', help='Specify output file')
parser.add_argument('--images-path', type=str, default='./.img/', help='Specify output file')
parser.add_argument('pdf_file', type=str, help='Specify PDF file name')
args = parser.parse_args()
# check if page is a single digit
if is_parsable_to_int(args.pages):
start_page = int(args.pages)
end_page = start_page
else:
# parse pages into start and end page
start_page, end_page = map(int, args.pages.split('-'))
# todo: validate output file
# Create the images directory if it doesn't exist
os.makedirs(args.images_path, exist_ok=True)
# Create output file or throw error if not possible
try:
with open(args.output_file, 'w') as file:
pass
except OSError:
raise Exception("Couldn't create output file")
# convert PDF to images for the given page
images = convert_from_path(args.pdf_file, first_page=start_page, last_page=end_page)
# for each image, run dict_to_anki.convert(filename)
out = ''
cost = 0.0
paths = []
for i, image in enumerate(images, start=start_page):
print(f'extracting image for page {i}...')
image_path = f"{args.images_path.rstrip('/')}/{args.pdf_file}_{i}.png"
image.save(image_path, 'PNG')
paths.append(image_path)
break_outer = False
for i in range(len(paths) // IMGS_PER_REQUEST + 1):
# print(i)
# collect images
while True:
to_process = paths[i * IMGS_PER_REQUEST:i * IMGS_PER_REQUEST + IMGS_PER_REQUEST]
# print(to_process)
if len(to_process) == 0:
# skip if remaining list is empty (e.g. if 4 pages at package size 2)
break
print(f'processing {len(to_process)} image{"s" if len(to_process) != 1 else ""}')
cards, meta = dict_to_anki.image_to_anki(to_process)
if not cards:
print("Error processing! Response: " + meta)
user_response = input("Retry? [y/N] > ")
if user_response != 'y' or 'yes' or 'Y' or 'YES' or 'Yes':
break_outer = True
break
else:
continue
# usage logging
usage = meta['usage']
print(f'usage for page {i}:\n{usage["prompt_tokens"]} prompt tokens and {usage["completion_tokens"]} completion tokens')
print(f'approx. cost: , {usage["prompt_tokens"] * 0.01 / 1000}$ for prompt tokens (pictures approx {0.00745 * len(to_process)}$ of this), {usage["completion_tokens"] * 0.03 / 1000}$ for completion tokens')
cost_this = (usage["prompt_tokens"] * 0.01 / 1000
+ usage["completion_tokens"] * 0.03 / 1000)
cost += cost_this
print(f'this page: {cost_this}$, total: {cost}$')
out += cards + '\n\n\n'
break
if break_outer:
break
print("total cost:", cost)
with open(args.output_file, 'w') as file:
file.write(out)
if __name__ == "__main__":
main()

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poetry.lock generated Normal file
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51
prompt.py Normal file
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@ -0,0 +1,51 @@
SYSTEM_PROMPT = '''
You are AnkiBot, a program that converts dictionary pictures into Anki cards.
You will get Dictionary Images as input, and you will write Anki cards as an output.
Anki cards follow the following format:
Q: How do you use this style?
A: Just like this.
Q: Can the question
run over multiple lines?
A: Yes, and
So can the answer
Q: Does the answer need to be immediately after the question?
A: No, and preceding whitespace will be ignored.
Q: How is this possible?
A: The 'magic' of regular expressions!
MAKE SURE that there is a space after Q: and A:.
Here are some example cards created from the dictionary:
Q: eigen
A: adv/adj.自己的，自身的，个人的 表示归属
Q: im Hof
A: 在院子
If there is a singular and a plural listed, DO NOT create extra cards for the plural Instead, MAKE SURE to create cards like this:
Q: der Beamte -n
A: 公务员
Q: der Job -s
A: 工作
ONLY write down the words in the dictionary. Output NOTHING ELSE than the words in the dictionary.
If a page does not contain any words (e.g. grammar info, title, ...), SKIP THAT PAGE and do not write down ANYTHING for it.
You have perfect OCR for roman letters, and chinese characters, and never make a mistake.
Make sure to write Anki cards for EVERY word. DO NOT leave any out. Try to always use the chinese words used in the dictionary, don't reword.
DO NOT modify the dictionary content, just transform the entries as-is into Anki cards.
'''
# DO NOT reword or rewrite chinese translation, just copy them from the dictionary!
# note: doesn't really work well, as it writes more wrong translations if it can't recognize something properly

19
pyproject.toml Normal file
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[tool.poetry]
name = "anki-from-dictionary"
version = "0.1.0"
description = "GPT-4V application to extract Anki cards from dictionaries"
authors = ["Yandrik <me@yandrik.dev>"]
license = "MIT"
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.10"
openai = "^1.10.0"
requests = "^2.31.0"
pillow = "^10.2.0"
pdf2image = "^1.17.0"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"