Create app.py

app.py

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+import gradio as gr
+import fitz  # PyMuPDF
+from transformers import pipeline
+
+# Load BERT QA pipeline
+qa_pipeline = pipeline("question-answering", model="bert-large-uncased-whole-word-masking-finetuned-squad")
+
+# Extract text from uploaded PDF
+def extract_text(pdf_file):
+    text = ""
+    with fitz.open(stream=pdf_file.read(), filetype="pdf") as doc:
+        for page in doc:
+            text += page.get_text()
+    return text
+
+# Main function for Gradio
+def qa_from_pdf_upload(pdf_file, question):
+    if not pdf_file:
+        return "❌ Please upload a PDF.", "", "", ""
+
+    context = extract_text(pdf_file)
+    if not context.strip():
+        return "❌ Could not extract text from the PDF.", "", "", ""
+
+    result = qa_pipeline(question=question, context=context)
+    return result["answer"], round(result["score"] * 100, 2), result["start"], result["end"]
+
+# Gradio UI
+gr.Interface(
+    fn=qa_from_pdf_upload,
+    inputs=[
+        gr.File(label="📥 Upload Fund PDF"),
+        gr.Textbox(label="❓ Your Question", placeholder="e.g., Who is the fund manager?")
+    ],
+    outputs=[
+        gr.Textbox(label="✅ Answer"),
+        gr.Textbox(label="📊 Confidence Score (%)"),
+        gr.Textbox(label="Start Index"),
+        gr.Textbox(label="End Index")
+    ],
+    title="📘 Morningstar Fund QA from PDF",
+    description="Upload a fund report in PDF format and ask questions using BERT."
+).launch()