Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import textwrap
+
+# Load the question-answering pipeline
+qa_pipeline = pipeline("question-answering")
+
+def chatbot(document, question):
+    # Define a set of greeting phrases
+    greetings = ["hi", "hello", "hey", "greetings", "what's up", "howdy"]
+
+    # Check if the input question is a greeting
+    question_lower = question.lower().strip()
+    if question_lower in greetings or any(question_lower.startswith(greeting) for greeting in greetings):
+        return "Hello! How can I assist you with the document today?"
+    
+    # Otherwise, handle the question using the QA pipeline
+    result = qa_pipeline(question=question, context=document)
+    
+    # Wrap the answer to ensure it is 3 to 4 lines long
+    wrapped_answer = textwrap.fill(result['answer'], width=70)
+    
+    # Split the wrapped answer into lines and limit it to 3 to 4 lines
+    answer_lines = wrapped_answer.split('\n')
+    limited_answer = '\n'.join(answer_lines[:4])
+    
+    return limited_answer
+
+interface = gr.Interface(
+    fn=chatbot,
+    inputs=[
+        gr.components.Textbox(lines=20, placeholder="Paste your document here..."),
+        gr.components.Textbox(lines=2, placeholder="Ask a question about the document or say hello...")
+    ],
+    outputs="text",
+    title="Document Chatbot",
+    description="Upload a document and ask questions about its content or just say hello."
+)
+
+if __name__ == "__main__":
+    interface.launch(debug=True)