reasoning

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-#from openai import OpenAI
+from openai import OpenAI
 from together import Together
 from datetime import datetime
 import time
@@ -22,6 +22,7 @@ st.markdown(
 
 ### Setting up the session state 
 def generate_tokens(response):
+    # for deepseek
     for token in response:
         if hasattr(token, 'choices') and token.choices:
             content = token.choices[0].delta.content
@@ -39,7 +40,6 @@ def format_personalization(text):
     return text
     
 if 'inserted' not in st.session_state:
-    ### read in txts
     with open('base.txt', 'r') as file:
         st.session_state.base_text = file.read()
     with open('knowledge.txt', 'r') as file:
@@ -49,9 +49,9 @@ if 'inserted' not in st.session_state:
 
     # web app state
     st.session_state.gotit = False
-    st.session_state.inserted = 0
     st.session_state.submitted = False
-    st.session_state["model"] = "deepseek-ai/DeepSeek-V3"
+    st.session_state.inserted = 0
+    st.session_state["model"] = "o3-mini-2025-01-31" #"deepseek-ai/DeepSeek-V3"
     st.session_state.max_messages = 50
     st.session_state.messages = []
     st.session_state.user_data = {}
@@ -69,7 +69,6 @@ if 'inserted' not in st.session_state:
 
     st.session_state.recycling = 0
 
-    # timers
     st.session_state.start_time = datetime.now()
     st.session_state.convo_start_time = ''
 
@@ -77,10 +76,7 @@ if 'p' not in st.query_params:
     st.query_params['p'] = 't'
 
 def setup_messages():
-    # t = personalization 
-    # k = knowledge
-    # f = formatting
-    # n = no chat
+    # t = personalization, k = knowledge, f = formatting, n = no chat
 
     if st.query_params["p"] == "f" or st.query_params["p"] == "n":
         st.session_state.system_message = st.session_state.base_text 
@@ -92,7 +88,10 @@ def setup_messages():
     st.session_state.messages = [{ "role": "system", "content": st.session_state.system_message}]
     st.session_state.convo_start_time = datetime.now()
 
-client = Together(api_key=st.secrets["TOGETHER_API_KEY"])
+if st.session_state.model.startswith("deepseek"):
+    client = Together(api_key=st.secrets["TOGETHER_API_KEY"])
+else:
+    client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
 
 ### App interface 
 with st.sidebar:
@@ -265,28 +264,25 @@ elif prompt := st.chat_input("Ask a question about climate action..."):
                     {"role": m["role"], "content": m["content"]}
                     for m in st.session_state.messages
                 ],
-                max_tokens=None,
-                temperature=0.6,
-                top_p=0.7,
-                top_k=50,
-                stop=["<｜end▁of▁sentence｜>"],
                 stream=True
             )
             
-            response = st.write_stream(generate_tokens(stream)) 
-            print(response)
+            if st.session_state.model.startswith("deepseek"):
+                response = st.write_stream(generate_tokens(stream)) 
+            else:
+                response = st.write_stream(stream)
+
             st.session_state.messages.append(
                 {"role": "assistant", "content": response}
             )
         except:
-            st.session_state.max_messages = len(st.session_state.messages)
             rate_limit_message = """
-                Oops! Sorry, I can't talk now. Too many people have used
-                this service recently.
+                An error has occured or you've reached the maximum conversation length. Please submit the conversation.
             """
             st.session_state.messages.append(
                 {"role": "assistant", "content": rate_limit_message}
             )
+            st.session_state.max_messages = len(st.session_state.messages)
             st.rerun()
 
 if len(st.session_state.messages) > 10 or st.session_state.max_messages == len(st.session_state.messages):