Update app.py

app.py

@@ -2,28 +2,34 @@ import openai
 import os
 import gradio as gr
 
-# Ensure OPENAI_API_KEY is set in your environment variables
+# Set the OpenAI API key using an environment variable
 openai.api_key = os.getenv('OPENAI_API_KEY')
 
 def generate_health_advice(health_goals, dietary_preferences, dietary_restrictions, nutritional_interests):
-    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}."
+    # Construct the prompt for the completion request
+    prompt_text = f"""
+    You are a helpful assistant, providing health and nutrition advice.
+    My health goals are: {health_goals}.
+    My dietary preferences are: {dietary_preferences}.
+    I have the following dietary restrictions: {dietary_restrictions}.
+    I'm interested in learning more about: {nutritional_interests}.
+    """
 
-    try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant, providing health and nutrition advice."},
-                {"role": "user", "content": f"My health goals are: {health_goals}."},
-                {"role": "user", "content": f"My dietary preferences are: {dietary_preferences}."},
-                {"role": "user", "content": f"I have the following dietary restrictions: {dietary_restrictions}."},
-                {"role": "user", "content": f"I'm interested in learning more about: {nutritional_interests}."}
-            ]
-        )
-    except Exception as e:
-        return str(e)
+    # Make the completion request
+    response = openai.Completion.create(
+        model="text-davinci-003",  # Or another model of your choice
+        prompt=prompt_text,
+        temperature=0.7,
+        max_tokens=150,
+        top_p=1.0,
+        frequency_penalty=0.0,
+        presence_penalty=0.0
+    )
 
-    return response.choices[0].message['content']
+    # Return the generated text
+    return response.choices[0].text.strip()
 
+# Gradio interface setup
 iface = gr.Interface(
     fn=generate_health_advice,
     inputs=[
@@ -37,4 +43,5 @@ iface = gr.Interface(
     description="Get personalized health advice based on your goals, preferences, and restrictions. Input your information below and receive guidance."
 )
 
+# Launch the Gradio interface
 iface.launch()