Update app.py

app.py

@@ -6,28 +6,22 @@ import gradio as gr
 openai.api_key = os.getenv('OPENAI_API_KEY')
 
 def generate_health_advice(health_goals, dietary_preferences, dietary_restrictions, nutritional_interests):
-    # System and user messages for the chat completion API
-    system_message = {"role": "system", "content": "You are a helpful assistant, providing health and nutrition advice."}
-    health_goals_message = {"role": "user", "content": f"My health goals are: {health_goals}."}
-    dietary_preferences_message = {"role": "user", "content": f"My dietary preferences are: {dietary_preferences}."}
-    dietary_restrictions_message = {"role": "user", "content": f"I have the following dietary restrictions: {dietary_restrictions}."}
-    nutritional_interests_message = {"role": "user", "content": f"I'm interested in learning more about: {nutritional_interests}."}
+    # Construct the prompt
+    prompt = f"You are a helpful assistant, providing health and nutrition advice.\nMy health goals are: {health_goals}.\nMy dietary preferences are: {dietary_preferences}.\nI have the following dietary restrictions: {dietary_restrictions}.\nI'm interested in learning more about: {nutritional_interests}."
 
-    messages = [
-        system_message,
-        health_goals_message,
-        dietary_preferences_message,
-        dietary_restrictions_message,
-        nutritional_interests_message
-    ]
-
-    # Generating chat completions using the OpenAI API
-    response = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages=messages
+    # Generate the response using the OpenAI Completion API
+    response = openai.Completion.create(
+        model="text-davinci-003",  # Adjust model as necessary
+        prompt=prompt,
+        temperature=0.5,
+        max_tokens=150,
+        top_p=1.0,
+        frequency_penalty=0.0,
+        presence_penalty=0.0
     )
 
-    return response.choices[0].message['content']
+    # Return the text of the first choice
+    return response.choices[0].text.strip()
 
 # Gradio interface setup
 iface = gr.Interface(