Update app.py

app.py

@@ -1,80 +1,80 @@
-import streamlit as st
-from groq import Groq
-from typing import List, Optional
-from dotenv import load_dotenv
-import json, os
-from pydantic import BaseModel
-from dspy_inference import get_expanded_query_and_topic
-
-load_dotenv()
-
-client = Groq(api_key=os.getenv("GROQ_API_KEY"))
-USER_AVATAR = "👤"
-BOT_AVATAR = "🤖"
-
-if "messages" not in st.session_state:
-    st.session_state.messages = [{"role": "assistant", "content": "Hi, How can I help you today?"}]
-if "conversation_state" not in st.session_state:
-        st.session_state["conversation_state"] = [{"role": "assistant", "content": "Hi, How can I help you today?"}]
-
-def main():
-    st.title("Assignment")
-    
-    for message in st.session_state.messages:
-        image = USER_AVATAR if message["role"] == "user" else BOT_AVATAR
-        with st.chat_message(message["role"], avatar=image):
-            st.markdown(message["content"])
-    
-    system_prompt = f'''You are a helpful assistant who can answer any question that the user asks.
-'''
-    if prompt := st.chat_input("User input"):
-        st.chat_message("user", avatar=USER_AVATAR).markdown(prompt)
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        conversation_context = st.session_state["conversation_state"]
-        conversation_context.append({"role": "user", "content": prompt})
-        
-        # Use dspy to expand the query and get the topic
-        expanded_query = get_expanded_query_and_topic(prompt, conversation_context)
-        
-        context = []
-        context.append({"role": "system", "content": system_prompt})
-        context.extend(st.session_state["conversation_state"])
-        
-        # Add the expanded query to the context
-        if expanded_query.expand != "None":
-            context.append({"role": "system", "content": f"Expanded query: {expanded_query.expand}"})
-        context.append({"role": "system", "content": f"Topic: {expanded_query.topic}"})
-        
-        response = client.chat.completions.create(
-            messages=context,
-            model="llama3-70b-8192",
-            temperature=0,
-            top_p=1,
-            stop=None,
-            stream=True,
-        )
-        
-        with st.chat_message("assistant", avatar=BOT_AVATAR):
-            result = ""
-            res_box = st.empty()
-            for chunk in response:
-                if chunk.choices[0].delta.content:
-                    new_content = chunk.choices[0].delta.content
-                    result += new_content
-                    res_box.markdown(f'{result}')
-            
-            # Display expanded question and tags separately
-            st.markdown("---")
-            # st.markdown("**Query Analysis:**")
-            if expanded_query.expand != "None":
-                st.markdown(f"**Expanded Question:** {expanded_query.expand}")
-            else:
-                st.markdown("**Expanded Question:** No expansion needed")
-            st.markdown(f"**Topic:** {expanded_query.topic}")
-        
-        assistant_response = result
-        st.session_state.messages.append({"role": "assistant", "content": assistant_response})
-        conversation_context.append({"role": "assistant", "content": assistant_response})
-
-if __name__ == '__main__':
+import streamlit as st
+from groq import Groq
+from typing import List, Optional
+from dotenv import load_dotenv
+import json, os
+from pydantic import BaseModel
+from dspy_inference import get_expanded_query_and_topic
+
+load_dotenv()
+
+client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+USER_AVATAR = "👤"
+BOT_AVATAR = "🤖"
+
+if "messages" not in st.session_state:
+    st.session_state.messages = [{"role": "assistant", "content": "Hi, How can I help you today?"}]
+if "conversation_state" not in st.session_state:
+        st.session_state["conversation_state"] = [{"role": "assistant", "content": "Hi, How can I help you today?"}]
+
+def main():
+    st.title("Query expansion and tagging")
+    
+    for message in st.session_state.messages:
+        image = USER_AVATAR if message["role"] == "user" else BOT_AVATAR
+        with st.chat_message(message["role"], avatar=image):
+            st.markdown(message["content"])
+    
+    system_prompt = f'''You are a helpful assistant who can answer any question that the user asks.
+'''
+    if prompt := st.chat_input("User input"):
+        st.chat_message("user", avatar=USER_AVATAR).markdown(prompt)
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        conversation_context = st.session_state["conversation_state"]
+        conversation_context.append({"role": "user", "content": prompt})
+        
+        # Use dspy to expand the query and get the topic
+        expanded_query = get_expanded_query_and_topic(prompt, conversation_context)
+        
+        context = []
+        context.append({"role": "system", "content": system_prompt})
+        context.extend(st.session_state["conversation_state"])
+        
+        # Add the expanded query to the context
+        if expanded_query.expand != "None":
+            context.append({"role": "system", "content": f"Expanded query: {expanded_query.expand}"})
+        context.append({"role": "system", "content": f"Topic: {expanded_query.topic}"})
+        
+        response = client.chat.completions.create(
+            messages=context,
+            model="llama3-70b-8192",
+            temperature=0,
+            top_p=1,
+            stop=None,
+            stream=True,
+        )
+        
+        with st.chat_message("assistant", avatar=BOT_AVATAR):
+            result = ""
+            res_box = st.empty()
+            for chunk in response:
+                if chunk.choices[0].delta.content:
+                    new_content = chunk.choices[0].delta.content
+                    result += new_content
+                    res_box.markdown(f'{result}')
+            
+            # Display expanded question and tags separately
+            st.markdown("---")
+            # st.markdown("**Query Analysis:**")
+            if expanded_query.expand != "None":
+                st.markdown(f"**Expanded Question:** {expanded_query.expand}")
+            else:
+                st.markdown("**Expanded Question:** No expansion needed")
+            st.markdown(f"**Topic:** {expanded_query.topic}")
+        
+        assistant_response = result
+        st.session_state.messages.append({"role": "assistant", "content": assistant_response})
+        conversation_context.append({"role": "assistant", "content": assistant_response})
+
+if __name__ == '__main__':
     main()