Create app.py

app.py

@@ -0,0 +1,37 @@
+import torch
+from transformers import DistilBertTokenizerFast, DistilBertForQuestionAnswering
+
+model_name = "distilbert-base-cased"
+tokenizer = DistilBertTokenizerFast.from_pretrained(model_name)
+model = DistilBertForQuestionAnswering.from_pretrained(model_name)
+
+def format_response(start_index, end_index, raw_answer):
+    answer_tokens = tokenizer.convert_tokens_to_string([tokenizer.convert_ids_to_tokens(i)[0] for i in range(start_index, end_index+1)])
+    return answer_tokens.strip()
+
+def get_answers(question, context):
+    inputs = tokenizer.encode_plus(question, context, return_tensors="pt")
+    start_scores, end_scores = model(**inputs).values()
+    start_index = torch.argmax(start_scores)
+    end_index = torch.argmax(end_scores) + 1
+    formatted_answer = format_response(start_index, end_index - 1, context[start_index:end_index].tolist())
+    return formatted_answer
+
+def main():
+    print("Hi! I am a simple AI chatbot built using Hugging Face.")
+    print("Type 'quit' to exit the program.")
+    query = ""
+    while True:
+        query = input("\nYour Question: ")
+        if query.lower() == "quit":
+            break
+        if len(query) > 0:
+            context = "The capital of France is Paris."
+            try:
+                response = get_answers(query, context)
+                print(f"Response: {response}")
+            except Exception as e:
+                print(f"Error occurred: {str(e)}")
+
+if __name__ == "__main__":
+    main()