Beta version 5

app.py

@@ -13,10 +13,13 @@ from langchain.schema import HumanMessage, SystemMessage, AIMessage
 st.set_page_config(page_title = "Magical Healer")
 st.header("Welcome, How can I help you?")
 
-#General Instruction
+
+class AIMessage(BaseModel):
+    content: str
+
 if "sessionMessages" not in st.session_state:
     st.session_state["sessionMessages"]=[]
-
+#General Instruction
 if "sessionMessages" not in st.session_state:
     st.session_state.sessionMessage=[
         SystemMessage(content="You are a medievel magical healer known for your peculiar sarcasm")
@@ -34,20 +37,27 @@ llm = ChatGoogleGenerativeAI(
 )
 
 #User message
-def get_text():
-    input_text=st.text_input("You: ", key=input)
-    return input_text
-
-#Working with Responses
 def load_answer(question):
-    #This is code, where we are adding new message to the model
     st.session_state.sessionMessages.append(HumanMessage(content=question))
-    #We will get output from the model
-    assistant_answer=llm.invoke(st.session_state.sessionMessages)
-    #Appending the assistance answer in conversation
-    st.session_state.sessionMessages.append(AIMessage(content = assistant_answer))
+    assistant_response = llm.invoke(st.session_state.sessionMessages)
+    
+    # Assuming assistant_response is an object with a 'content' attribute
+    if hasattr(assistant_response, 'content') and isinstance(assistant_response.content, str):
+        processed_content = assistant_response.content
+        st.session_state.sessionMessages.append(AIMessage(content=processed_content))
+    else:
+        st.error("Invalid response received from AI.")
+        processed_content = "Sorry, I couldn't process your request."
+
+    return processed_content
 
-    return assistant_answer.content
+#Working with Responses
+#def load_answer(question):
+    
+#    st.session_state.sessionMessages.append(HumanMessage(content=question))
+#    assistant_answer=llm.invoke(st.session_state.sessionMessages)
+#    st.session_state.sessionMessages.append(AIMessage(content = assistant_answer))
+#    return assistant_answer.content
 
 def get_text():
     input_text=st.text_input("You: ", key=input)