Update app.py

app.py

@@ -2,49 +2,34 @@ import openai
 import streamlit as st
 from tenacity import retry, stop_after_attempt, wait_fixed
 
-# Streamlit app initialization
-st.title("AI-powered Home Staging Assistant")
+# Assuming the OpenAI API key is stored in Streamlit's secrets
+openai.api_key = st.secrets["OPENAI_API_KEY"]
 
-# If using Streamlit Cloud or Hugging Face Spaces, set up your OPENAI_API_KEY in the secrets.toml file
-# Otherwise, replace "your_actual_openai_api_key_here" with your actual OpenAI API key
-openai.api_key = st.secrets.get("OPENAI_API_KEY", "your_actual_openai_api_key_here")
+st.title("Website Feature Code Generator")
 
-# Define the initial system message for the AI
-initial_messages_staging = [{
-    "role": "system",
-    "content": """
-        You are an AI assistant that provides home staging recommendations for real estate agents. Your role is to help agents visualize and execute staging setups that highlight the best features of the homes they're selling. When providing recommendations, ensure:
-        1. They are actionable and specific to the home's features and the target buyer demographic.
-        2. You include low-cost, DIY options for agents working with limited budgets.
-        3. You suggest staging strategies that can make the space appear larger and more inviting.
-        4. You consider current home decor trends and advise on how they can be applied effectively.
-        5. You offer ideas for both indoor and outdoor spaces.
-        Always conclude your response with a suggestion for professional staging services for agents who prefer expert assistance.
-    """
-}]
+# User inputs for the feature they want to add
+feature_description = st.text_area(
+    "Describe the website feature you'd like to implement:",
+    "E.g., A contact form with name, email, and message fields that emails the site owner."
+)
 
-# Add retry logic to the OpenAI API call
 @retry(stop=stop_after_attempt(3), wait=wait_fixed(1))
-def call_openai_api(messages):
-    return openai.ChatCompletion.create(
-        model="gpt-4",
-        messages=messages
-    )
+def call_openai_api(prompt):
+    try:
+        response = openai.Completion.create(
+            model="gpt-4",
+            prompt=prompt,
+            max_tokens=150
+        )
+        return response.choices[0].text
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+        return None
 
-# Function to generate the AI response
-def generate_staging_advice(home_details, location):
-    user_input = f"I have a home for sale with these details: {home_details}. It's located in {location}. How should I stage it for potential buyers?"
-    messages = initial_messages_staging.copy()
-    messages.append({"role": "user", "content": user_input})
-    response = call_openai_api(messages)
-    return response.choices[0].message["content"]
-
-# Streamlit UI elements for user input
-home_details = st.text_area("Home Details", placeholder="Describe the home's features, size, style, etc.")
-location = st.text_input("Location", placeholder="Enter the home's location or neighborhood.")
-generate_button = st.button('Get Staging Recommendations')
-
-# Handling the button click to generate staging advice
-if generate_button:
-    staging_advice = generate_staging_advice(home_details, location)
-    st.text_area("Staging Recommendations", staging_advice, height=300)
+if st.button("Generate Code"):
+    prompt = f"Write the HTML, CSS, and JavaScript code for a website feature described as follows: {feature_description}"
+    code = call_openai_api(prompt)
+    if code:
+        st.code(code, language="html")
+    else:
+        st.write("Could not generate the code. Please check the feature description and try again.")