Update app.py

app.py

@@ -24,7 +24,9 @@ os.environ['LANGCHAIN_API_KEY'] = 'lsv2_pt_ce80aac3833643dd893527f566a06bf9_667d
 
 @st.cache_resource
 def load_model():
-    model_name = "bigscience/bloom-560m"
+    # model_name = "bigscience/bloom-560m"
+    model_name = "distilbert-base-uncased"
+
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     model = AutoModelForCausalLM.from_pretrained(model_name)
     return model, tokenizer
@@ -137,7 +139,7 @@ def run_with_timeout(func, args, timeout):
     return result[0]
 # In your Streamlit app
 def generate_response(chain, query, context):
-    timeout_seconds = 60
+    timeout_seconds = 120
     result = run_with_timeout(chain.invoke, ({"question": query, "chat_history": st.session_state.messages},), timeout_seconds)
     if result is None:
         return "I apologize, but I couldn't generate a response in time. The query might be too complex for me to process quickly. Could you try simplifying your question?"