Update app.py

app.py

@@ -58,20 +58,22 @@ def initialize_agents():
 
     os.environ["OPENAI_API_KEY"] = openai_key
     try:
-        if st.session_state["app"] is not None:
-            return st.session_state["app"]  # Prevent re-initialization
+        # Prevent re-initialization
+        if "app" in st.session_state and st.session_state["app"] is not None:
+            return st.session_state["app"]
         
-        essay_writer = EssayWriter().graph
-        st.session_state["chat_active"] = False
+        # Initialize the full EssayWriter instance
+        essay_writer = EssayWriter()  # ✅ Store the full instance
+        st.session_state["app"] = essay_writer  # ✅ Now contains `graph`
+        st.session_state["chat_active"] = False  # ✅ Enable chat after successful initialization
 
-        # Success message
-        #st.success("✅ Agents successfully initialized!")
         return essay_writer
     except Exception as e:
         st.error(f"❌ Error initializing agents: {e}")
         st.session_state["chat_active"] = True
         return None
 
+
 # Automatically initialize agents on app load
 if st.session_state["app"] is None:
     st.session_state["app"] = initialize_agents()
@@ -83,11 +85,12 @@ app = st.session_state["app"]
 
 # Function to invoke the agent and generate a response
 def generate_response(topic, length):
-    if not app:
+    if not app or not hasattr(app, "graph"):
         st.error("⚠️ Agents are not initialized. Please check the system or restart the app.")
         return {"response": "Error: Agents not initialized."}
 
-    return app.invoke(input={"topic": topic, "length": length})
+    return app.graph.invoke(input={"topic": topic, "length": length})  # Ensure `graph` is invoked
+
 
 # Define Tabs
 tab1, tab2 = st.tabs(["📜 Essay Generation", "📊 Workflow Visualization"])
@@ -97,10 +100,12 @@ with tab1:
     st.subheader("📝 Generate an Essay")
 
     # Display chat messages from the session
-    if "messages" in st.session_state:
-        for message in st.session_state["messages"]:
-            with st.chat_message(message["role"]):
-                st.markdown(message["content"], unsafe_allow_html=True)
+    if "messages" not in st.session_state:
+        st.session_state["messages"] = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
+
+    for message in st.session_state["messages"]:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"], unsafe_allow_html=True)
 
     # Handle user input
     if topic := st.chat_input(placeholder="📝 Ask a question or provide an essay topic...", disabled=st.session_state["chat_active"]):
@@ -108,33 +113,45 @@ with tab1:
         st.session_state["messages"].append({"role": "user", "content": topic})
 
         with st.spinner("⏳ Generating your essay..."):
-            response = generate_response(topic, essay_length)  
+            response = None
+            if app:
+                response = app.write_essay({"topic": topic})
+            else:
+                st.error("⚠️ Agents are not initialized. Please check the system or restart the app.")
 
         # Handle the assistant's response
         with st.chat_message("assistant"):
-            if "essay" in response:  # Display essay preview and download link
+            if response and "essay" in response:  # Display essay preview and download link
+                essay = response["essay"]
                 st.markdown(f"### 📝 Essay Preview ({essay_length} words)")
-                st.markdown(f"#### {response['essay']['header']}")
-                st.markdown(response["essay"]["entry"])
-                for para in response["essay"]["paragraphs"]:
+                st.markdown(f"#### {essay['header']}")
+                st.markdown(essay["entry"])
+                
+                for para in essay["paragraphs"]:
                     st.markdown(f"**{para['sub_header']}**")
                     st.markdown(para["paragraph"])
+                
                 st.markdown("**🖊️ Conclusion:**")
-                st.markdown(response["essay"]["conclusion"])
+                st.markdown(essay["conclusion"])
 
-                # Provide download link for the PDF
-                with open(response["pdf_name"], "rb") as pdf_file:
-                    b64 = base64.b64encode(pdf_file.read()).decode()
-                    href = f"<a href='data:application/octet-stream;base64,{b64}' download='{response['pdf_name']}'>📄 Click here to download the PDF</a>"
-                    st.markdown(href, unsafe_allow_html=True)
+                # Provide download link for the PDF (only if available)
+                pdf_name = response.get("pdf_name")
+                if pdf_name and os.path.exists(pdf_name):
+                    with open(pdf_name, "rb") as pdf_file:
+                        b64 = base64.b64encode(pdf_file.read()).decode()
+                        href = f"<a href='data:application/octet-stream;base64,{b64}' download='{pdf_name}'>📄 Click here to download the PDF</a>"
+                        st.markdown(href, unsafe_allow_html=True)
 
-                # Save the assistant's message to session state
+                # Save response in session state
                 st.session_state["messages"].append(
                     {"role": "assistant", "content": f"Here is your {essay_length}-word essay preview and the download link."}
                 )
-            else:  # For other responses (e.g., general answers)
+            elif response:  # Other responses (fallback)
                 st.markdown(response["response"])
                 st.session_state["messages"].append({"role": "assistant", "content": response["response"]})
+            else:
+                st.error("⚠️ No response received. Please try again.")
+
 
 # 📊 Tab 2: Workflow Visualization
 with tab2: