Update app.py

app.py

@@ -1,51 +1,39 @@
+
 import gradio as gr
 import anthropic
 import os
 
 # Function to call Claude AI API and get a personalized meal plan
 def get_meal_plan(fasting_sugar, pre_meal_sugar, post_meal_sugar, dietary_preferences):
-    ani_sa_api = os.getenv('claude_api')  # Ensure your API key is set correctly
-    print(f"API Key: {anti_api_key}")  # Debugging: Check if the API key is loaded
-    
-    if not anti_api_key:
-        return "Error: API key is missing or not set."
-    
-    try:
-        client = anthropic.Anthropic(api_key=ani_sa_api)
-        
-        # Define the prompt to send to Claude AI
-        prompt = (
-            f"My fasting sugar level is {fasting_sugar} mg/dL, "
-            f"my pre-meal sugar level is {pre_meal_sugar} mg/dL, "
-            f"and my post-meal sugar level is {post_meal_sugar} mg/dL. "
-            f"My dietary preferences are {dietary_preferences}. "
-            "Please provide a personalized meal plan that can help me manage my blood sugar levels effectively."
-        )
-        
-        # Call Claude AI API
-        message = client.messages.create(
-            model="claude-3-5-sonnet-20240620",
-            max_tokens=250,
-            temperature=0.7,
-            system="You are a world-class nutritionist who specializes in diabetes management.",
-            messages=[
-                {
-                    "role": "user",
-                    "content": prompt
-                }
-            ]
-        )
-        
-        # Debugging: Check the response content
-        print(f"Response: {message.content}")
-        
-        raw_context = message.content
-        meal_plan = raw_context[0].text
-        return meal_plan
-    
-    except Exception as e:
-        print(f"Error: {e}")
-        return f"An error occurred while generating the meal plan: {e}"
+    ani_sa_api = os.getenv('claude_api')  # Replace with your actual API key or environment variable
+    client = anthropic.Anthropic(api_key=ani_sa_api)
+    
+    # Define the prompt to send to Claude AI
+    prompt = (
+        f"My fasting sugar level is {fasting_sugar} mg/dL, "
+        f"my pre-meal sugar level is {pre_meal_sugar} mg/dL, "
+        f"and my post-meal sugar level is {post_meal_sugar} mg/dL. "
+        f"My dietary preferences are {dietary_preferences}. "
+        "Please provide a personalized meal plan that can help me manage my blood sugar levels effectively."
+    )
+    
+    # Call Claude AI API
+    message = client.messages.create(
+        model="claude-3-5-sonnet-20240620",
+        max_tokens=250,
+        temperature=0.7,
+        system="You are a world-class nutritionist who specializes in diabetes management.",
+        messages=[
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ]
+    )
+    
+    raw_context = message.content
+    meal_plan = raw_context[0].text
+    return meal_plan
 
 # Gradio interface
 def generate_meal_plan(fasting_sugar, pre_meal_sugar, post_meal_sugar, dietary_preferences):