File size: 4,510 Bytes
651b002 cd017fd 651b002 b74f760 cd017fd 651b002 4246b36 48f4086 0fdc9b3 4246b36 cd017fd 651b002 4246b36 cd017fd 651b002 cd017fd 651b002 cd017fd 651b002 4246b36 7405c46 cd017fd 7405c46 1f530a5 7405c46 651b002 7405c46 651b002 4246b36 7405c46 272015d 7405c46 d011873 651b002 b74f760 651b002 a79f7cd b74f760 651b002 cd017fd 651b002 cd017fd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
import gradio as gr
import pytz
import os
from datetime import datetime
from markdown import instructions_markdown, faq_markdown
from fsrs4anki_optimizer import Optimizer
from pathlib import Path
from utilities import cleanup
def get_w_markdown(w):
return f"""
# Updated Parameters
Copy and paste these as shown in step 5 of the instructions:
`{w}`
Check out the Analysis tab for more detailed information."""
def anki_optimizer(file: gr.File, timezone, next_day_starts_at, revlog_start_date, requestRetention,
progress=gr.Progress(track_tqdm=True)):
now = datetime.now()
files = ['prediction.tsv', 'revlog.csv', 'revlog_history.tsv', 'stability_for_analysis.tsv',
'expected_time.csv', 'evaluation.tsv']
prefix = now.strftime(f'%Y_%m_%d_%H_%M_%S')
suffix = file.name.split('/')[-1].replace(".", "_").replace("@", "_")
proj_dir = Path(f'projects/{prefix}/{suffix}')
proj_dir.mkdir(parents=True, exist_ok=True)
print(proj_dir)
os.chdir(proj_dir)
proj_dir = Path('.')
optimizer = Optimizer()
optimizer.anki_extract(file.name)
analysis_markdown = optimizer.create_time_series(timezone, revlog_start_date, next_day_starts_at).replace("\n", "\n\n")
optimizer.define_model()
optimizer.train()
w_markdown = get_w_markdown(optimizer.w)
optimizer.predict_memory_states()
difficulty_distribution = optimizer.difficulty_distribution.to_string().replace("\n", "\n\n")
plot_output = optimizer.find_optimal_retention()[0]
suggested_retention_markdown = f"""# Suggested Retention: `{optimizer.optimal_retention:.2f}`"""
rating_markdown = optimizer.preview(requestRetention).replace("\n", "\n\n")
loss_before, loss_after = optimizer.evaluate()
loss_markdown = f"""
**Loss before training**: {loss_before}
**Loss after training**: {loss_after}
"""
# optimizer.calibration_graph()
# optimizer.compare_with_sm2()
markdown_out = f"""{suggested_retention_markdown}
# Loss Information
{loss_markdown}
# Difficulty Distribution
{difficulty_distribution}
# Ratings
{rating_markdown}
"""
files_out = [file for file in files if (proj_dir / file).exists()]
cleanup(proj_dir, files)
return w_markdown, markdown_out, plot_output, files_out
description = """
# FSRS4Anki Optimizer App - v3.24.1
Based on the [tutorial](https://medium.com/@JarrettYe/how-to-use-the-next-generation-spaced-repetition-algorithm-fsrs-on-anki-5a591ca562e2)
of [Jarrett Ye](https://github.com/L-M-Sherlock). This application can give you personalized anki parameters without having to code.
Read the `Instructions` if its your first time using the app.
"""
with gr.Blocks() as demo:
with gr.Tab("FSRS4Anki Optimizer"):
with gr.Box():
gr.Markdown(description)
with gr.Box():
with gr.Row():
with gr.Column():
file = gr.File(label='Review Logs (Step 1)')
with gr.Column():
next_day_starts_at = gr.Number(value=4,
label="Next Day Starts at (Step 2)",
precision=0)
timezone = gr.Dropdown(label="Timezone (Step 3.1)", choices=pytz.all_timezones)
with gr.Accordion(label="Advanced Settings (Step 3.2)", open=False):
requestRetention = gr.Number(value=.9, label="Desired Retention: Recommended to set between 0.8 0.9")
revlog_start_date = gr.Textbox(value="2006-10-05",
label="Revlog Start Date: Optimize review logs after this date.")
with gr.Row():
btn_plot = gr.Button('Optimize your Anki!')
with gr.Row():
w_output = gr.Markdown()
with gr.Tab("Instructions"):
with gr.Box():
gr.Markdown(instructions_markdown)
with gr.Tab("Analysis"):
with gr.Row():
markdown_output = gr.Markdown()
with gr.Column():
plot_output = gr.Plot()
files_output = gr.Files(label="Analysis Files")
with gr.Tab("FAQ"):
gr.Markdown(faq_markdown)
btn_plot.click(anki_optimizer,
inputs=[file, timezone, next_day_starts_at, revlog_start_date, requestRetention],
outputs=[w_output, markdown_output, plot_output, files_output])
demo.queue().launch(show_error=True)
|