Update app.py

app.py

@@ -7,11 +7,16 @@ model_path = './QAModel'  # Path to your fine-tuned model
 # Load the question-answering pipeline
 qa_pipeline = pipeline("question-answering", model=model_path, tokenizer=model_path)
 
+# Load the context from a file
+context_file = 'context.txt'  # Replace with your context file path
+
+with open(context_file, 'r', encoding='utf-8') as f:
+    default_context = f.read()
+
 # Set the title for the Streamlit app
 st.title("Movie Trivia Question Answering")
 
-# Text inputs for the user
-context = st.text_area("Enter the context (movie-related text):")
+# Text input for the user question
 question = st.text_area("Enter your question:")
 
 def generate_answer(question, context):
@@ -20,15 +25,15 @@ def generate_answer(question, context):
     return result['answer']
 
 if st.button("Get Answer"):
-    if context and question:
-        generated_answer = generate_answer(question, context)
+    if question:
+        generated_answer = generate_answer(question, default_context)
         # Display the generated answer
         st.subheader("Answer")
         st.write(generated_answer)
     else:
-        st.warning("Please enter both context and question.")
+        st.warning("Please enter a question.")
 
 # Optionally, add instructions or information about the app
 st.write("""
-    Enter a movie-related context and a question related to the context above. The model will provide the answer based on the context provided.
-    """)
+    Enter a question related to the provided movie-related context above. The model will provide the answer based on the context provided.
+    """)