Anki Card Creator

from scripts.card_creator import AnkiCardCreator

creator = AnkiCardCreator()

# Generate cloze cards from text
text = """
Acute inflammation is characterized by five cardinal signs: 
redness (rubor), heat (calor), swelling (tumor), pain (dolor), 
and loss of function (functio laesa). These result from 
vasodilation, increased vascular permeability, and leukocyte 
infiltration.
"""

cards = creator.create_cloze_cards(
    text=text,
    n_cards=3,  # Generate 3 cards from this text
    difficulty="intermediate",
    tags=["Pathology", "Inflammation", "General_Pathology"]
)

# Output format (Anki-compatible)
# Card 1: "Acute inflammation is characterized by {{c1::five}} cardinal signs..."
# Card 2: "...signs: {{c1::redness}} (rubor), {{c2::heat}} (calor)..."

# Create basic cards
cards = creator.create_basic_cards(
    content={
        "What is the mechanism of action of penicillin?": 
            "Inhibition of bacterial cell wall synthesis by binding to PBPs",
        "What are the major side effects of ACE inhibitors?":
            "Dry cough, hyperkalemia, angioedema, hypotension"
    },
    reversible=True,  # Create reverse cards too
    tags=["Pharmacology", "Antibiotics"]
)

# Image occlusion for anatomy
cards = creator.create_image_occlusion(
    image_path="brachial_plexus.png",
    occlude_regions=[
        {"label": "Musculocutaneous nerve", "coords": (120, 200, 200, 240)},
        {"label": "Median nerve", "coords": (300, 250, 380, 290)},
        {"label": "Ulnar nerve", "coords": (400, 280, 480, 320)}
    ],
    card_type="one_by_one"  # or "all_at_once"
)

# Auto-tag based on content
cards = creator.process_textbook_chapter(
    chapter_text=pathoma_chapter,
    source="Pathoma - Hematopoiesis",
    auto_tag=True,
    tag_hierarchy=[
        "Pathoma",
        "{{chapter_name}}",
        "{{section_name}}"
    ]
)

# Results in tags like:
# Pathoma::Hematopoiesis::Red_Cell_Disorders
# Pathoma::Hematopoiesis::White_Cell_Disorders

# Extract and convert chapter
python scripts/main.py \
  --input first_aid_cardiology.pdf \
  --chapter "Ischemic Heart Disease" \
  --card-type cloze \
  --n-cards-per-page 3 \
  --tags "First_Aid::Cardiology::IHD" \
  --output ischemic_heart_disease.apkg

# Import directly to Anki
# File ready for import with media included

# Generate drug cards with mechanisms
drugs = [
    {
        "name": "Metformin",
        "class": "Biguanide",
        "mechanism": "Activates AMPK, decreases hepatic gluconeogenesis",
        "indications": "Type 2 diabetes, PCOS",
        "side_effects": "GI upset, lactic acidosis (rare), B12 deficiency",
        "image": "metformin_structure.png"
    }
]

cards = creator.create_drug_cards(
    drugs=drugs,
    include_structures=True,
    include_mechanism_diagrams=True,
    tags=["Pharmacology", "Diabetes", "First_Line"]
)

Front: Metformin - Class?
Back: Biguanide
Tags: Pharmacology::Diabetes::First_Line

Front: Metformin - Mechanism?
Back: Activates AMPK → decreases hepatic gluconeogenesis
Image: [mechanism diagram]
Tags: Pharmacology::Diabetes::Mechanism

Front: Metformin - Side effects?
Back: GI upset, lactic acidosis (rare), B12 deficiency
Tags: Pharmacology::Diabetes::Side_Effects

# Differential diagnosis cards
cards = creator.create_differential_cards(
    condition="Cough with hemoptysis",
    differentials=[
        {"diagnosis": "Lung cancer", "key_features": "Smoker, weight loss, mass on CT"},
        {"diagnosis": "TB", "key_features": "Immigrant, night sweats, cavitary lesion"},
        {"diagnosis": "PE", "key_features": "Sudden onset, tachypnea, D-dimer elevated"},
        {"diagnosis": "Bronchiectasis", "key_features": "Chronic cough, purulent sputum, dilated airways"}
    ],
    card_type="compare_contrast"
)

# Process lecture PDF
python scripts/main.py \
  --input lecture_slides.pdf \
  --source "Dr_Smith_Cardiology_Lecture_5" \
  --card-type mixed \
  --extract-images \
  --auto-tag \
  --output cardiology_lecture_5.apkg

# Review and edit in Anki
# Delete low-yield cards
# Add personal mnemonics

# Step 1: Process multiple sources
python scripts/main.py \
  --input first_aid_pathology.pdf \
  --source "First_Aid_2024" \
  --card-type cloze \
  --tags "First_Aid::Pathology" \
  --output fa_pathology.apkg

python scripts/main.py \
  --input sketchy_pharm.pdf \
  --source "Sketchy_Pharm" \
  --card-type basic \
  --include-images \
  --tags "Sketchy::Pharm" \
  --output sketchy_pharm.apkg

# Step 2: Merge decks
python scripts/main.py \
  --merge fa_pathology.apkg sketchy_pharm.apkg \
  --output usmle_step1_master.apkg

# Step 3: Add leech tags for difficult cards
python scripts/main.py \
  --input usmle_step1_master.apkg \
  --tag-leeches \
  --leech-threshold 8 \
  --output usmle_step1_tagged.apkg

from scripts.card_creator import AnkiCardCreator
from scripts.importers import PDFImporter

# Initialize
creator = AnkiCardCreator()
importer = PDFImporter()

# Import and process textbook
content = importer.import_pdf(
    path="robbins_pathologic_basis_of_disease.pdf",
    pages="150-200",  # Inflammation chapter
    extract_images=True
)

# Create cloze cards
cards = creator.create_cloze_cards(
    text=content.text,
    images=content.images,
    n_cards=50,
    difficulty="advanced",
    tags=["Robbins", "General_Pathology", "Inflammation"]
)

# Add image occlusion for diagrams
for diagram in content.diagrams:
    occlusion_cards = creator.create_image_occlusion(
        image=diagram,
        auto_detect_labels=True
    )
    cards.extend(occlusion_cards)

# Export Anki package
creator.export_apkg(
    cards=cards,
    deck_name="Robbins_Inflammation",
    output_path="robbins_inflammation.apkg"
)

print(f"Created {len(cards)} cards ready for Anki import")