Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the Hugging Face model
+model = "deepset/bert-base-cased-squad2"
+qa_pipeline = pipeline("question-answering", model=model, tokenizer=model)
+
+# Define the function to answer questions
+def get_answer(text):
+    result = qa_pipeline({
+        "question": text,
+        "context": knowledge_base_text
+    })
+    return result["answer"]
+
+# Define the Gradio interface
+def chatbot_interface(text):
+    answer = get_answer(text)
+    return answer
+
+knowledge_base_file = "knowledge_base.txt"  # Path to the knowledge base text file
+
+# Load the knowledge base from a text file
+with open(knowledge_base_file, "r") as f:
+    knowledge_base_text = f.read()
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=chatbot_interface,
+    inputs="Ask any questions about BATB",
+    outputs="Result",
+    title="British American Tobacco Bangladesh",
+    description="- powered by IDT",
+    theme="default"
+)
+
+# Run the Gradio interface
+iface.launch()