Update app.py

app.py

@@ -37,7 +37,7 @@ Context: {' - '.join(['&&& '+d.meta['document_name']+' ref. '+str(d.meta['ref_id
 model_options = ['chatGPT','Llama2']
 
 # Create a list of options for the dropdown
-country_options = ['Angola','Botswana','Lesotho','Kenya','Malawi','Mozambique','Namibia','Rwanda','South Africa','Zambia','Zimbabwe']
+country_options = ['ALL','Angola','Botswana','Lesotho','Kenya','Malawi','Mozambique','Namibia','Rwanda','South Africa','Zambia','Zimbabwe']
 
 # List of examples
 examples = [
@@ -51,10 +51,10 @@ def get_docs(input_query, country = None):
     Construct a hacky query to focus the retriever on the target country (see notes below)
     We take the top 150 k because we want to make sure we have 10 pertaining to the selected country
     '''
-    if country:
-        query = "For the country of "+country+", "+input_query
-    else:
+    if country == 'ALL':
         query = input_query
+    else:
+        query = "For the country of "+country+", "+input_query
     # Retrieve top k documents
     docs = retriever.retrieve(query=query,top_k = 150)
     # Break out the key fields and convert to pandas for filtering