cleanup and refactor

backend/chat_with_user.py

@@ -6,12 +6,12 @@
 
 def get_system_message(content_type: ContentType):
     return f"""
-    1. You're a super-intelligent AI. Your task is to understand what audiocast the user wants to listen to.
+    1. You're a super-intelligent AI. Your task is to understand what audiocast a user wants to listen to.
     2. You will steer the conversation until you have enough context after which you should terminate.
-    3. Keep the conversation short, say 2-3 back and forth - questions and answers.
-    4. As soon as the user's request is clear terminate the conversation by saying, "Ok, thanks for clarifying! Please click the button below to start generating the audiocast."
+    3. Keep the conversation short, say 3-5 back and forth i.e., questions and answers.
+    4. As soon as the user's request is clear terminate the conversation by saying, "Ok, thanks for clarifying! Based on your specifications, you want to listen to [Best case summary of user request so far]. Please click the button below to start generating the audiocast."
     5. You can also terminate the conversation using a varied response strictly similar to (4) above.
-    6. If the user's request remains unclear after 3 responses for clarity, terminate the conversation by saying, "Your request is not very specific but from what I understand, you want to listen to [Best case summary of user request so far]. Please click the button below to start generating the audiocast."
+    6. If the user's request remains unclear after 5 responses for clarity, terminate the conversation by saying, "Your request is not very specific but from what I understand, you want to listen to [Best case summary of user request so far]. Please click the button below to start generating the audiocast."
 
 
     GENERAL IDEA AND WORKFLOW:

frontend/app.py

@@ -2,8 +2,9 @@
 
 import httpx
 import streamlit as st
+from chat_utils import chat_request, content_types
 from env_var import APP_URL, BACKEND_URL
-from example_utils import content_types, display_example_cards
+from example_utils import display_example_cards
 
 # Initialize session state
 if "chat_session_id" not in st.session_state:
@@ -46,22 +47,9 @@
     with st.chat_message("user"):
         st.write(prompt)
 
-    # Send message to backend
-    response = httpx.post(
-        f"{BACKEND_URL}/api/chat/{st.session_state.chat_session_id}",
-        json={
-            "message": {"role": "user", "content": prompt},
-            "content_type": content_type,
-        },
-        timeout=None,
-    )
-
-    response.raise_for_status()
-
-    if response.status_code == 200:
-        ai_message = ""
-        for line in response.iter_lines():
-            ai_message += line
+    ai_message = chat_request(prompt, content_type)
+
+    if ai_message:
         st.session_state.messages.append({"role": "assistant", "content": ai_message})
 
         with st.chat_message("assistant"):

frontend/chat_utils.py

@@ -0,0 +1,38 @@
+from typing import Dict, List, Literal
+
+import httpx
+import streamlit as st
+from env_var import BACKEND_URL
+
+ContentType = Literal["story", "podcast", "sermon", "science"]
+
+content_types: List[ContentType] = ["story", "podcast", "sermon", "science"]
+
+content_examples: Dict[ContentType, str] = {
+    "story": "Tell me a story about a magical kingdom with dragons and wizards.",
+    "podcast": "Create a podcast about the history of space exploration.",
+    "sermon": "Write a sermon about finding peace in times of trouble.",
+    "science": "Explain the concept of black holes in simple terms.",
+}
+
+
+def chat_request(prompt: str, content_type: ContentType):
+    """
+    Send a chat request to the backend server and return the AI response.
+    """
+    response = httpx.post(
+        f"{BACKEND_URL}/api/chat/{st.session_state.chat_session_id}",
+        json={
+            "message": {"role": "user", "content": prompt},
+            "content_type": content_type,
+        },
+        timeout=None,
+    )
+
+    response.raise_for_status()
+
+    ai_message = ""
+    for line in response.iter_lines():
+        ai_message += line
+
+    return ai_message

frontend/example_utils.py

@@ -1,19 +1,5 @@
-from typing import Dict, List, Literal
-
-import httpx
 import streamlit as st
-from env_var import BACKEND_URL
-
-ContentType = Literal["story", "podcast", "sermon", "science"]
-
-content_types: List[ContentType] = ["story", "podcast", "sermon", "science"]
-
-content_examples: Dict[ContentType, str] = {
-    "story": "Tell me a story about a magical kingdom with dragons and wizards.",
-    "podcast": "Create a podcast about the history of space exploration.",
-    "sermon": "Write a sermon about finding peace in times of trouble.",
-    "science": "Explain the concept of black holes in simple terms.",
-}
+from chat_utils import chat_request, content_examples
 
 
 def display_example_cards():
@@ -48,23 +34,13 @@ def display_example_cards():
             if st.button(example, use_container_width=True):
                 # Add selected example to messages and trigger rerun to enter chat mode
                 st.session_state.messages.append({"role": "user", "content": example})
-                response = httpx.post(
-                    f"{BACKEND_URL}/api/chat/{st.session_state.chat_session_id}",
-                    json={
-                        "message": {"role": "user", "content": example},
-                        "content_type": content_type,
-                    },
-                    timeout=None,
-                )
-
-                response.raise_for_status()
 
-                if response.status_code == 200:
-                    ai_message = ""
-                    for line in response.iter_lines():
-                        ai_message += line
+                ai_message = chat_request(example, content_type)
+                if ai_message:
                     st.session_state.messages.append(
                         {"role": "assistant", "content": ai_message}
                     )
 
                     st.rerun()
+                else:
+                    st.error("Failed to generate AI response. Please try again.")