Create app.py

app.py

@@ -0,0 +1,62 @@
+import json
+import os
+from openai import OpenAI
+from dotenv import load_dotenv
+
+# Load API key from environment variables
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
+client = OpenAI(api_key=api_key)
+
+# Function to fetch weather details (mock implementation)
+def get_weather(city: str):
+    weather_data = {
+        "New York": "☀️ Sunny, 25°C",
+        "London": "🌧️ Rainy, 18°C",
+        "Mumbai": "⛅ Cloudy, 30°C"
+    }
+    return weather_data.get(city, "Weather data not available for this city.")
+
+# Function to handle user queries
+def chat_with_llm(user_query):
+    # Define function schema
+    functions = [
+        {
+            "name": "get_weather",
+            "description": "Fetch weather details for a given city.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "city": {"type": "string", "description": "Name of the city"}
+                },
+                "required": ["city"]
+            }
+        }
+    ]
+
+    # Get response from GPT with function calling enabled
+    response = client.chat.completions.create(
+        model="gpt-4-turbo",
+        messages=[{"role": "user", "content": user_query}],
+        functions=functions,
+        function_call="auto"  # GPT decides if function calling is needed
+    )
+
+    message = response.choices[0].message
+
+    # Check if function was called
+    if message.function_call:
+        try:
+            function_args = json.loads(message.function_call.arguments)
+            city = function_args.get("city")
+            if city:
+                return get_weather(city)
+        except Exception as e:
+            return f"Error processing function call: {str(e)}"
+
+    # If no function was called, return normal LLM response
+    return message.content
+
+# Example Queries
+print(chat_with_llm("What's the weather like in New York?"))  # Function Call
+print(chat_with_llm("Tell me a joke."))  # Normal LLM Response