ui.py

import gradio as gr
import tempfile  
from ocr_engine import extract_text_from_image
from pdf_reader import extract_text_chunks_from_pdf
from summarizer import summarize_long_text
from utils import chunk_text_by_tokens 

def process_input(pdf, image, manual_text, mode, model_name, start_page, end_page, lang_mode, is_table):
    if is_table and model_name != "anthropic/claude-3-haiku":
        return "Tablo içeriği için yalnızca Claude önerilir.","",None

    if pdf is not None:
        text_chunks = extract_text_chunks_from_pdf(pdf, start=int(start_page), end=int(end_page))
        if any("[ERROR]" in chunk for chunk in text_chunks):
            return text_chunks[0], "", None
    elif image is not None:
        text = extract_text_from_image(image)
        if "[ERROR]" in text:
            return text, "", None
        text_chunks = [text]
    elif manual_text.strip() != "":
        text_chunks = [manual_text]
    else:
        return "Lütfen bir giriş türü seçin.", "", None

    all_text = "\n\n".join(text_chunks)
    chunk_count = len(chunk_text_by_tokens(all_text, max_tokens=1300))

    info_block = f"""
     Sayfa Aralığı: {start_page}–{end_page}
     Model: {model_name}
     Chunk Sayısı: {chunk_count}
""".strip()

    full_summary = summarize_long_text(all_text, mode, model_name, lang_mode, is_table)
    full_summary = f"{info_block}\n\n{full_summary}"

    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".txt", mode='w', encoding='utf-8')
    temp_file.write(full_summary)
    temp_file.close()

    return all_text, full_summary, temp_file.name


with gr.Blocks() as demo:
    gr.Markdown("## VizSum")

    with gr.Row():
        pdf_input = gr.File(label="PDF Yükle", file_types=[".pdf"])
        image_input = gr.Image(type="filepath", label="Görsel Yükle")

    manual_input = gr.Textbox(lines=5, label="Metni Manuel Gir")

    with gr.Row(visible=False) as page_controls:
        start_page = gr.Number(label="Başlangıç Sayfası", value=1, minimum=1, precision=0)
        end_page = gr.Number(label="Bitiş Sayfası", value=5, minimum=1, precision=0)

    def show_page_controls(pdf):
        return gr.update(visible=True)

    pdf_input.change(
        fn=show_page_controls,
        inputs=[pdf_input],
        outputs=[page_controls]
    )


        
    def enable_page_inputs(pdf):
        return gr.update(interactive=True), gr.update(interactive=True)

    pdf_input.change(
        fn=enable_page_inputs,
        inputs=[pdf_input],
        outputs=[start_page, end_page]
    )

    mode_selector = gr.Dropdown(
        choices=[
            "Teknik Özet",
            "Sade Anlatım",
            "Eleştir ve Değerlendir",
            "Başlık Çıkar",
            "Not Formatı",
            "Karma Özet",
            "Chat Özeti (Yazışma/Not)"
        ],
        label="Özetleme Modu",
        value="Teknik Özet"
    )

    model_selector = gr.Dropdown(
        choices=[
            "anthropic/claude-3-haiku",
            "openai/gpt-3.5-turbo",
            "mistralai/mistral-7b-instruct"
        ],
        label="Dil Modeli",
        value="anthropic/claude-3-haiku"
    )

    with gr.Row():
        submit_btn = gr.Button("Özetle")

    with gr.Row():
        text_output = gr.Textbox(label="Giriş Metni")
        summary_output = gr.Textbox(label="AI Özeti", lines=10, show_copy_button=True)
        summary_file = gr.File(label="Özeti İndir", interactive=True)
    
    lang_mode = gr.Radio(
        choices=["Otomatik", "Sadece Türkçe", "Sadece İngilizce", "Türkçeye Çevir", "İngilizceye Çevir"],
        label="Dil Algılama / Çeviri Modu",
        value="Otomatik"
    )
    
    is_table = gr.Checkbox(label="Tablo içeriyor (Claude tablo gibi özetlesin)", value=False)

    submit_btn.click(
        fn=process_input,
        inputs=[pdf_input, image_input, manual_input, mode_selector, model_selector, start_page, end_page, lang_mode, is_table],
        outputs=[text_output, summary_output, summary_file]
    )



if __name__ == "__main__":
    demo.launch(share=True)