Update app.py

app.py

@@ -1,34 +1,38 @@
-import openai
 import os
+from openai import OpenAI
 import streamlit as st
 from tenacity import retry, wait_fixed, stop_after_attempt
 
-# Set OpenAI API key from environment variables
-openai.api_key = os.getenv("OPENAI_API_KEY")
+# Initialize OpenAI client
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
 # Define the initial system message
-initial_messages = [{"role": "system", "content": """Please act as a marketing expert for real estate agents. Your role is
+initial_messages = [{
+    "role": "system", 
+    "content": """Please act as a marketing expert for real estate agents. Your role is
 to generate topic summary ideas for social media videos. Follow these steps in this order:
 1. Before you execute any steps, consider the last input from the user as a suggestion for the types of topics you should create if
 they submit one. If they don't submit a topic idea then assume they would like ideas for marketing videos for a real estate agent.
 2. Generate 100 total ideas for videos a real estate agent should make. Some should be ideas 
 for simple marketing videos, creative social media content, educational videos, and a few that are outside the box.
-Reply with the 10 overall best ideas. Include a short, up to 2 sentence long description of each idea. Do not return all 100 ideas."""}]
+Reply with the 10 overall best ideas. Include a short, up to 2 sentence long description of each idea. Do not return all 100 ideas."""
+}]
 
-@retry(stop=stop_after_attempt(3), wait=wait_fixed(1))
+@retry(stop=stop_after_attempt(3), wait=wait_fixed(2))
 def call_openai_api(messages):
     """
     Call OpenAI's ChatCompletion API with retries for transient errors.
     """
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
+        response = client.chat.completions.create(
+            model="gpt-4",
             messages=messages,
-            max_tokens=1000  # Adjust token limit to fit your needs
+            max_tokens=1000
         )
         return response
-    except openai.error.OpenAIError as e:
-        raise RuntimeError(f"OpenAI API error: {e}")
+    except Exception as e:
+        st.error(f"OpenAI API Error: {str(e)}")
+        raise
 
 def CustomChatGPT(user_input, messages):
     """
@@ -40,28 +44,24 @@ def CustomChatGPT(user_input, messages):
         messages.append({"role": "user", "content": "Please generate general video ideas for a real estate agent."})
     
     response = call_openai_api(messages)
-    ChatGPT_reply = response["choices"][0]["message"]["content"]
+    ChatGPT_reply = response.choices[0].message.content
     messages.append({"role": "assistant", "content": ChatGPT_reply})
     return ChatGPT_reply, messages
 
 # Streamlit app setup
 st.title("Video Idea Generator for Real Estate Agents")
-st.write("Enter a topic suggestion or leave it blank for general video ideas.")
+st.subheader("Generate tailored video content ideas for your real estate marketing!")
 
-# User input section
-user_input = st.text_input("Enter a topic:", placeholder="E.g., tips for first-time homebuyers")
-generate_button = st.button("Generate Ideas")
+# User input
+user_input = st.text_input("Enter a topic suggestion (optional)", placeholder="E.g., tips for first-time homebuyers")
 
-# Generate ideas on button click
-if generate_button:
+# Button to trigger generation
+if st.button("Generate Video Ideas"):
     messages = initial_messages.copy()
     try:
         with st.spinner("Generating video ideas..."):
-            reply, _ = CustomChatGPT(user_input, messages)
-        st.subheader("Here are the top video ideas:")
+            reply, messages = CustomChatGPT(user_input, messages)
+        st.markdown("### Suggested Video Ideas")
         st.write(reply)
-    except RuntimeError as e:
-        st.error(f"Error: {e}")
     except Exception as e:
-        st.error("An unexpected error occurred. Please try again.")
-
+        st.error(f"An error occurred: {e}")