Delete app.py

app.py

@@ -1,121 +0,0 @@
-
-import os
-import gradio as gr
-import pdfplumber
-from openai import OpenAI
-
-client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
-
-SUMMARY_STYLES = ["Child-Friendly", "Academic", "Tweet"]
-LANGUAGES = ["English", "Turkish", "French", "German", "Spanish"]
-
-PROMPT_TEMPLATES = {
-    "English": """
-Please summarize the following text in a {style} style and keep it within approximately {char_limit} characters.
-Then provide 5 relevant keywords.
-Also generate 2 multiple choice questions, each with 4 options (A, B, C, D).
-
-TEXT:
-{text}
-""",
-    "Turkish": """
-Lütfen aşağıdaki metni {style} tarzında ve yaklaşık {char_limit} karakter olacak şekilde özetle.
-Ardından 5 anahtar kelime ver.
-Ayrıca 2 adet çoktan seçmeli quiz sorusu üret, her biri dört seçenek (A, B, C, D) içersin.
-
-METİN:
-{text}
-""",
-    "French": """
-Veuillez résumer le texte suivant dans un style {style}, en environ {char_limit} caractères.
-Fournissez ensuite 5 mots-clés pertinents.
-Générez également 2 questions à choix multiples avec 4 options (A, B, C, D).
-
-TEXTE :
-{text}
-""",
-    "German": """
-Fassen Sie den folgenden Text im {style}-Stil mit etwa {char_limit} Zeichen zusammen.
-Geben Sie anschließend 5 relevante Schlüsselwörter an.
-Erstellen Sie außerdem 2 Multiple-Choice-Fragen mit jeweils 4 Optionen (A, B, C, D).
-
-TEXT:
-{text}
-""",
-    "Spanish": """
-Resume el siguiente texto en un estilo {style} y con un límite de aproximadamente {char_limit} caracteres.
-Luego proporciona 5 palabras clave relevantes.
-También genera 2 preguntas de opción múltiple con 4 opciones (A, B, C, D).
-
-TEXTO:
-{text}
-"""
-}
-
-def extract_text_from_pdf(file):
-    try:
-        with pdfplumber.open(file.name) as pdf:
-            text = ""
-            for page in pdf.pages:
-                page_text = page.extract_text()
-                if page_text:
-                    text += page_text + "\n"
-        if not text.strip():
-            return None, "The PDF appears to contain no extractable text."
-        return text.strip(), None
-    except Exception as e:
-        return None, f"PDF reading error: {str(e)}"
-
-def generate_output(text, summary_lang, style, char_limit):
-    prompt_template = PROMPT_TEMPLATES.get(summary_lang, PROMPT_TEMPLATES["English"])
-    prompt = prompt_template.format(style=style, char_limit=char_limit, text=text[:2000])
-
-    try:
-        response = client.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=[
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            max_tokens=800
-        )
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"OpenAI error: {str(e)}"
-
-def process_input(text_input, pdf_file, summary_lang, style, char_limit):
-    if not char_limit.isdigit():
-        return "⚠️ Please enter a numeric character limit."
-    text = ""
-    error = None
-    if pdf_file:
-        text, error = extract_text_from_pdf(pdf_file)
-    elif text_input and text_input.strip():
-        text = text_input.strip()
-    if error:
-        return f"⚠️ {error}"
-    if not text:
-        return "⚠️ No text provided."
-    return generate_output(text, summary_lang, style, char_limit)
-
-with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 Smart Note Summarizer (Stable Version)")
-
-    with gr.Row():
-        summary_lang = gr.Dropdown(choices=LANGUAGES, value="English", label="Summary Language")
-        summary_style = gr.Dropdown(choices=SUMMARY_STYLES, value="Academic", label="Summary Style")
-        char_limit = gr.Textbox(label="Character Limit", value="300")
-
-    with gr.Row():
-        text_input = gr.Textbox(lines=8, placeholder="Paste your text here...", label="Text Input")
-        pdf_file = gr.File(label="Or Upload PDF")
-
-    output = gr.Textbox(label="Output", lines=14)
-
-    run_btn = gr.Button("Summarize")
-
-    run_btn.click(fn=process_input,
-                  inputs=[text_input, pdf_file, summary_lang, summary_style, char_limit],
-                  outputs=output)
-
-demo.launch()