app.py

"""
Entry point for DescribePDF Hugging Face Space.
"""

import gradio as gr
import os
import sys

# Asegurarnos de que el directorio actual esté en el path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

# Importar solo las partes necesarias
from describepdf import config, core

# Definir tema 
theme = gr.themes.Soft(
    primary_hue="red",
    secondary_hue="rose",
    spacing_size="lg",
)

# Variables globales para configuración predeterminada
SUGGESTED_VLMS = [
    "qwen/qwen2.5-vl-72b-instruct", 
    "google/gemini-2.5-pro-preview-03-25",
    "openai/chatgpt-4o-latest"
]

SUGGESTED_LLMS = [
    "google/gemini-2.5-flash-preview", 
    "openai/chatgpt-4o-latest",
    "anthropic/claude-3.5-sonnet"
]

SUGGESTED_LANGUAGES = [
    "English", "Spanish", "French", "German", 
    "Chinese", "Japanese", "Italian", 
    "Portuguese", "Russian", "Korean"
]

def generate(
    pdf_file_obj, 
    ui_api_key, 
    ui_vlm_model, 
    ui_lang, 
    ui_use_md, 
    ui_use_sum, 
    ui_sum_model, 
    progress=gr.Progress()
):
    """Wrapper function to call the core conversion process"""
    if pdf_file_obj is None:
        return "Please upload a PDF file.", gr.update(value=None, visible=False), None

    # Load environment config
    env_config = config.get_config()

    # Prepare configuration for this run
    api_key = ui_api_key.strip() if ui_api_key.strip() else env_config.get("openrouter_api_key")

    current_run_config = {
        "provider": "openrouter",
        "openrouter_api_key": api_key,
        "vlm_model": ui_vlm_model,
        "output_language": ui_lang,
        "use_markitdown": ui_use_md,
        "use_summary": ui_use_sum,
        "summary_llm_model": ui_sum_model if ui_sum_model else env_config.get("or_summary_model")
    }

    # Validate API key
    if not current_run_config.get("openrouter_api_key"):
        error_msg = "Error: OpenRouter API Key is missing. Provide it in the UI."
        return error_msg, gr.update(value=None, visible=False), None

    # Create progress callback for Gradio
    def progress_callback(progress_value, status):
        clamped_progress = max(0.0, min(1.0, progress_value))
        progress(clamped_progress, desc=status)

    # Run the conversion
    status_message, result_markdown = core.convert_pdf_to_markdown(
        pdf_file_obj.name,
        current_run_config,
        progress_callback
    )

    # Handle the download file
    if result_markdown:
        try:
            import tempfile
            import secrets
            
            # Get base filename from the uploaded PDF
            base_name = os.path.splitext(os.path.basename(pdf_file_obj.name))[0]
            download_filename = f"{base_name}_description.md"
            
            # Create a temporary file
            random_suffix = secrets.token_hex(4)
            temp_dir = tempfile.gettempdir()
            download_filepath = os.path.join(temp_dir, f"{base_name}_{random_suffix}.md")

            # Write markdown result to the temporary file
            with open(download_filepath, "w", encoding="utf-8") as md_file:
                md_file.write(result_markdown)
                
            download_button_update = gr.update(value=download_filepath, visible=True, label=f"Download '{download_filename}'")
        except Exception as e:
            status_message += f" (Error creating download file: {str(e)})"
            download_button_update = gr.update(value=None, visible=False)
    else:
        download_button_update = gr.update(value=None, visible=False)

    return status_message, download_button_update, result_markdown

# Crear interfaz de usuario manualmente en lugar de usar la función create_ui()
with gr.Blocks(title="DescribePDF", theme=theme) as app:
    gr.Markdown("<center><img src='https://davidlms.github.io/DescribePDF/assets/poster.png' alt='Describe PDF Logo' width='600px'/></center>")
    gr.Markdown(
        """<div style="display: flex;align-items: center;justify-content: center">
        [<a href="https://davidlms.github.io/describepdf/">Project Page</a>] | [<a href="https://github.com/DavidLMS/describepdf">Github</a>]</div>
        """
    )
    gr.Markdown(
        "DescribePDF is an open-source tool designed to convert PDF files into detailed page-by-page descriptions in Markdown format using Vision-Language Models (VLMs). Unlike traditional PDF extraction tools that focus on replicating the text layout, DescribePDF generates rich, contextual descriptions of each page's content, making it perfect for visually complex documents like catalogs, scanned documents, and presentations."
    )

    with gr.Tabs():
        # Generate tab
        with gr.TabItem("Generate"):
            with gr.Row():
                with gr.Column(scale=1):
                    pdf_input = gr.File(
                        label="Upload PDF", 
                        file_types=['.pdf'], 
                        type="filepath"
                    )
                    convert_button = gr.Button(
                        "Describe", 
                        variant="primary"
                    )
                    progress_output = gr.Textbox(
                        label="Progress", 
                        interactive=False, 
                        lines=2
                    )
                    download_button = gr.File(
                        label="Download Markdown", 
                        visible=False, 
                        interactive=False
                    )

                with gr.Column(scale=2):
                    markdown_output = gr.Markdown(label="Result (Markdown)")

        # Configuration tab
        with gr.TabItem("Settings"):
            gr.Markdown(
                "Adjust settings for the *next* generation."
            )
            api_key_input = gr.Textbox(
                label="OpenRouter API Key",
                type="password",
                placeholder="Enter your OpenRouter API key",
                value="" 
            )
            vlm_model_input = gr.Dropdown(
                label="VLM Model", 
                choices=SUGGESTED_VLMS,
                value=SUGGESTED_VLMS[0],
                allow_custom_value=True,
                info="Select or type the OpenRouter VLM model name"
            )
            output_language_input = gr.Dropdown(
                label="Output Language", 
                choices=SUGGESTED_LANGUAGES,
                value="English",
                allow_custom_value=True,
                info="Select or type the desired output language"
            )
            with gr.Row():
                use_markitdown_checkbox = gr.Checkbox(
                    label="Use Markitdown for extra text context",
                    value=False
                )
                use_summary_checkbox = gr.Checkbox(
                    label="Use PDF summary for augmented context",
                    value=False
                )
            summary_llm_model_input = gr.Dropdown(
                label="LLM Model for Summary", 
                choices=SUGGESTED_LLMS,
                value=SUGGESTED_LLMS[0],
                allow_custom_value=True,
                info="Select or type the OpenRouter LLM model name for summaries"
            )

    # Connect UI components
    conversion_inputs = [
        pdf_input, api_key_input, vlm_model_input, output_language_input,
        use_markitdown_checkbox, use_summary_checkbox, summary_llm_model_input
    ]
    conversion_outputs = [
        progress_output, download_button, markdown_output
    ]
    convert_button.click(
        fn=generate,
        inputs=conversion_inputs,
        outputs=conversion_outputs
    )

# Para Hugging Face Spaces
if __name__ == "__main__":
    app.launch()