from markdrop import markdrop, MarkDropConfig, add_downloadable_tables
from pathlib import Path
import logging

config = MarkDropConfig(
    image_resolution_scale=2.0,
    download_button_color="#444444",
    log_level=logging.INFO,
    log_dir="logs",
    excel_dir="markdrop-excel-tables",
)

html_path = markdrop("path/to/input.pdf", "output", config)
downloadable_html = add_downloadable_tables(html_path, config)

import asyncio
from markdrop import process_markdown, ProcessorConfig, AIProvider, setup_keys

# One-time key setup (writes to user config ~/.config/markdrop/.env)
setup_keys("anthropic")

config = ProcessorConfig(
    input_path="out/report-markdroped.md",
    output_dir="output",
    ai_provider=AIProvider.ANTHROPIC,  # GEMINI | OPENAI | ANTHROPIC | GROQ | OPENROUTER | LITELLM
    remove_images=False,
    remove_tables=False,
    table_descriptions=True,
    image_descriptions=True,
    max_retries=3,
    retry_delay=2,
    # Override default models (all providers have matching config fields):
    anthropic_model_name="claude-opus-5",
    anthropic_text_model_name="claude-sonnet-5",
)

output_path = asyncio.run(process_markdown(config))

config = ProcessorConfig(
    input_path="doc.md",
    output_dir="output",
    ai_provider=AIProvider.OPENROUTER,
    openrouter_model_name="meta-llama/llama-4-scout",  # any model on openrouter.ai/models
    openrouter_text_model_name="anthropic/claude-sonnet-5",
    openrouter_site_url="https://yoursite.com",
    openrouter_site_name="My App",
)

import os

os.environ["ANTHROPIC_API_KEY"] = "..."  # set any provider's key

config = ProcessorConfig(
    input_path="doc.md",
    output_dir="output",
    ai_provider=AIProvider.LITELLM,
    litellm_model_name="anthropic/claude-opus-5",
    litellm_text_model_name="openai/gpt-5.6-luna",
)

from markdrop import generate_descriptions

generate_descriptions(
    input_path="images/",
    output_dir="output/",
    prompt="Give a highly detailed description of this image.",
    llm_client=["gemini", "llama-vision"],
)