Update app.py

app.py

@@ -72,28 +72,26 @@ def classify_csv(file):
     except Exception as e:
         return None, f"Error: {str(e)}"
 
-def chatbot_response(history, user_input, source, text_input=None, file_input=None):
+def chatbot_response(history, user_input, text_input=None, file_input=None):
     # Always use the user input as a question for the QA pipeline
     user_input = user_input.lower()  # Optionally make it lowercase
     
-    # Determine context based on the source
+    # Initialize context as empty
     context = ""
     
-    if source == "Single Article":
-        # If the source is single article, use the text_input (single article content)
-        context = text_input if text_input else ""
+    # Combine the context from text_input and file_input
+    if text_input:
+        context += text_input  # Add the single article text as context
     
-    elif source == "Bulk Classification":
-        # If the source is bulk articles, use the file input (context for multiple articles)
-        if file_input:
-            # Assuming `classify_csv` method processes the file and sets the bulk context
-            df, _ = classify_csv(file_input)  # This function should return the dataframe and context
-            context = context_storage["bulk_context"]
+    if file_input:
+        # Process the CSV file and extract the content for bulk context
+        df, _ = classify_csv(file_input)  # Assuming classify_csv processes the file and gets the context
+        context += context_storage["bulk_context"]  # Append bulk context to the overall context
     
-    # Make sure there's context for QA pipeline to run
+    # Make sure there's context for the QA pipeline
     if context:
         with st.spinner("Finding answer..."):
-            # Run QA pipeline with the user's question and context from either text_input or file_input
+            # Run QA pipeline with the user's question and combined context from both text_input and file_input
             result = qa_pipeline(question=user_input, context=context)
             answer = result["answer"]