Upload app.py

app.py

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+
+import os
+import gradio as gr
+import pdfplumber
+from openai import OpenAI
+
+client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
+
+LANGUAGES = ["English", "Turkish", "Arabic", "French", "German", "Spanish"]
+
+TRANSLATIONS = {
+    "English": {
+        "summary_lang": "🗣️ Summary Language",
+        "char_limit": "🔢 Character Limit (approximate)",
+        "text_input": "📥 Paste Text Here",
+        "text_placeholder": "Or paste a document here...",
+        "pdf_upload": "📄 Or Upload a PDF File",
+        "output": "🧠 Output (Summary, Title, Keywords)",
+        "run_button": "Summarize"
+    },
+    "Turkish": {
+        "summary_lang": "🗣️ Özetleme Dili",
+        "char_limit": "🔢 Karakter Sınırı (yaklaşık)",
+        "text_input": "📥 Metni Buraya Yapıştırın",
+        "text_placeholder": "Ya da bir belge yapıştırın...",
+        "pdf_upload": "📄 Ya da bir PDF Yükleyin",
+        "output": "🧠 Çıktı (Özet, Başlık, Anahtar Kelimeler)",
+        "run_button": "Özetle"
+    }
+    # Diğer diller buraya eklenebilir...
+}
+
+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 translate_text(text, target_lang):
+    try:
+        prompt = f"Translate the following text to {target_lang}:\n\n{text}"
+        response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": "You are a helpful translator."},
+                {"role": "user", "content": prompt}
+            ],
+            temperature=0.3,
+            max_tokens=3000
+        )
+        return response.choices[0].message.content
+    except Exception:
+        return text
+
+def analyze_text(text, summary_lang, char_limit):
+    translated_text = translate_text(text, summary_lang)
+    prompt = f"""You are a helpful assistant.
+
+Please provide the following in {summary_lang}:
+1. A clear and concise summary (limited to approximately {char_limit} characters).
+2. A suitable title.
+3. 5 relevant keywords.
+
+Document:
+{translated_text[:3000]}"""
+    try:
+        response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt}
+            ],
+            temperature=0.7,
+            max_tokens=400
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"❌ OpenAI Error: {str(e)}"
+
+def analyze_input(summary_lang, char_limit, text_input, pdf_file):
+    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"⚠️ PDF Error: {error}"
+    if not text:
+        return "⚠️ No text provided or extracted."
+
+    return analyze_text(text, summary_lang, char_limit)
+
+def interface_selector(interface_lang):
+    t = TRANSLATIONS.get(interface_lang, TRANSLATIONS["English"])
+    return (
+        gr.update(visible=True),
+        gr.update(label=t["summary_lang"]),
+        gr.update(label=t["char_limit"]),
+        gr.update(label=t["text_input"], placeholder=t["text_placeholder"]),
+        gr.update(label=t["pdf_upload"]),
+        gr.update(label=t["output"]),
+        gr.update(value=t["run_button"])
+    )
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🌐 Select Interface Language")
+
+    with gr.Accordion("📘 View README / Usage Guide", open=False):
+        gr.Markdown("""This application allows you to upload a PDF or paste text, select your preferred summary language, and receive:
+
+- A clear summary ✂️  
+- An auto-generated title 🏷️  
+- 5 relevant keywords 🔑  
+
+If the content language and summary language differ, the app will auto-translate before summarizing 🌐  
+
+Powered by OpenAI GPT-3.5 and Gradio.""")
+
+    lang_select = gr.Dropdown(label="Interface Language", choices=LANGUAGES, value="English")
+    next_btn = gr.Button("Continue")
+
+    with gr.Column(visible=False) as summary_section:
+        summary_lang = gr.Dropdown(choices=LANGUAGES, value="English")
+        char_limit = gr.Textbox(value="300")
+        text_input = gr.Textbox(lines=10)
+        pdf_file = gr.File()
+        output = gr.Textbox()
+        run_btn = gr.Button()
+
+    next_btn.click(fn=interface_selector, inputs=[lang_select], outputs=[
+        summary_section,
+        summary_lang,
+        char_limit,
+        text_input,
+        pdf_file,
+        output,
+        run_btn
+    ])
+
+    run_btn.click(fn=analyze_input, inputs=[summary_lang, char_limit, text_input, pdf_file], outputs=output)
+
+demo.launch()