Update app.py

app.py

@@ -68,7 +68,7 @@ def create_embeddings(text_chunks):
     return chunk_embeddings
 
 charity_embeddings = create_embeddings(cleaned_charities)
-finance_embeddings2 = create_embeddings(cleaned_finance)
+finance_embeddings = create_embeddings(cleaned_finance)
 # Call the create_embeddings function and store the result in a new chunk_embeddings variable
 #chunk_embeddings = create_embeddings(cleaned_chunks) # Complete this line
 
@@ -116,15 +116,11 @@ client= InferenceClient("openai/gpt-oss-20b")
 information=""
 
 def respond(message,history):
-    topic_chunks=[]
-    if chatbot_topic=="Helping Charities":
-        
-        topic_chunks=get_top_chunks(message, charity_embeddings, cleaned_charities)
-        #print(topic_chunks)
-
-    elif chatbot_topic=="Financial Aid":
-        topic_chunks=get_top_chunks(message, finance_embeddings, cleaned_finance)
-        #print(topic_chunks)
+    topic_chunks = []
+    if chatbot_topic and "Helping Charities" in chatbot_topic:
+        topic_chunks = get_top_chunks(message, charity_embeddings, cleaned_charities)
+    elif chatbot_topic and "Financial Aid" in chatbot_topic:
+        topic_chunks = get_top_chunks(message, finance_embeddings, cleaned_finance)
 
 
     #return information
@@ -148,9 +144,9 @@ def respond(message,history):
 ### STEP 6
 # Call the preprocess_text function and store the result in a cleaned_chunks variable
 cleaned_chunks = preprocess_text(financial_advice_text) # Complete this line
-top_results = get_top_chunks("What financial advice you give me?", chunk_embeddings2, cleaned_chunks2) 
+top_results = get_top_chunks("What financial advice you give me?", finance_embeddings, cleaned_finance) 
 
-print(top_results)
+#print(top_results)
 
 #Defining chatbot giving user a UI to interact, see their conversation history, and see new messages using built in gr feature
 #ChatInterface requires at least one parameter(a function)