Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import docx2txt
+import PyPDF2
+
+# Load the summarizer model
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Function to extract text from supported file types
+def extract_text(file):
+    if file is None:
+        return ""
+    file_path = file.name
+    if file_path.endswith(".txt"):
+        with open(file_path, "r", encoding="utf-8") as f:
+            return f.read()
+    elif file_path.endswith(".pdf"):
+        reader = PyPDF2.PdfReader(file)
+        return "\n".join(page.extract_text() for page in reader.pages if page.extract_text())
+    elif file_path.endswith(".docx"):
+        return docx2txt.process(file)
+    else:
+        return "Unsupported file format. Please upload a .txt, .pdf, or .docx file."
+
+# Summarize either text input or uploaded file
+def summarize(text, file):
+    extracted_text = text.strip() or extract_text(file)
+    if not extracted_text:
+        return "Please enter text or upload a file."
+    summary = summarizer(extracted_text, max_length=130, min_length=30, do_sample=False)
+    return summary[0]['summary_text']
+
+# Gradio interface
+iface = gr.Interface(
+    fn=summarize,
+    inputs=[
+        gr.Textbox(lines=10, label="Enter text (optional)"),
+        gr.File(label="Upload a file (.txt, .pdf, .docx)")
+    ],
+    outputs=gr.Textbox(label="Summary"),
+    title="Text Summarizer",
+    description="Paste text or upload a file to summarize using a BART model."
+)
+
+iface.launch()