Update app.py

app.py

@@ -80,16 +80,19 @@ def determine_mood(data: dict) -> str:
 def create_narrative(city: str, data: dict) -> str:
     return f"In {city}, the weather is {data['weather_condition']} with a temperature of {data['temperature']}°C."
 
-# Function to generate a story using OpenAI Completion API
+# Function to generate a story using OpenAI
 def generate_story_with_ai(narrative: str, mood: str) -> str:
-    prompt = f"{narrative} The mood is '{mood}'. Write a short story about how the environment feels in 50 words."
-    response = openai.Completion.create(
-        engine="text-davinci-003",
-        prompt=prompt,
-        max_tokens=50,
+    messages = [
+        {"role": "system", "content": "You are a creative storyteller using characters and imagery."},
+        {"role": "user", "content": f"{narrative} The mood is '{mood}', write a story about how the environment feels in 50 words."}
+    ]
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=messages,
+        max_tokens=150,
         temperature=0.7
     )
-    return response.choices[0].text.strip()
+    return response.choices[0].message['content'].strip()
 
 # Function to generate simulated environmental data
 def generate_simulated_data(city: str) -> dict:
@@ -97,13 +100,13 @@ def generate_simulated_data(city: str) -> dict:
         f"Generate simulated environmental data for {city} in JSON format with fields:\n"
         f"1. AQI\n2. Deforestation Rate\n3. Water Quality\n4. Biodiversity Impact"
     )
-    response = openai.Completion.create(
-        engine="text-davinci-003",
-        prompt=prompt,
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
         max_tokens=100,
         temperature=0.8
     )
-    response_content = response.choices[0].text.strip()
+    response_content = response.choices[0].message['content'].strip()
     try:
         return eval(response_content)
     except Exception as e: