Create app.py

app.py

@@ -0,0 +1,56 @@
+import torch
+import gradio as gr 
+import os
+from PyPDF2 import PdfReader
+from docx import Document
+import io
+
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+question_answer = pipeline("question-answering", model="deepset/roberta-base-squad2")
+
+
+
+def extract_file_content(file_obj):
+    filename = file_obj.name
+    file_ext = filename.split('.')[-1].lower()
+
+    try:
+        if file_ext == "pdf":
+            reader = PdfReader(file_obj)
+            text = ""
+            for page in reader.pages:
+                text += page.extract_text() + "\n"
+            return text.strip()
+
+        elif file_ext == "txt":
+            return file_obj.read().decode('utf-8')
+
+        elif file_ext == "docx":
+            doc = Document(io.BytesIO(file_obj.read()))
+            text = ""
+            for para in doc.paragraphs:
+                text += para.text + "\n"
+            return text.strip()
+
+        else:
+            return "Unsupported file format. Please upload PDF, TXT, or DOCX."
+
+    except Exception as e:
+        return f"Error reading file: {str(e)}"
+
+def get_ans(file,question):
+    context = extract_file_content(file)
+    answer = question_answer(question=question ,context=context)
+    return answer["answer"]
+
+
+demo = gr.Interface(
+    fn=get_ans,
+    inputs=[gr.File(label="Upload Your File"), gr.Textbox(label="Enter question",lines=4)],
+    outputs=[gr.Textbox(label="Answer", lines=5)],
+    title="@RosangenAi Project 3: Document question answer")
+
+demo.launch()