Create app.py

app.py

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+import os
+import openai
+import json
+import requests
+import streamlit as st
+#from dotenv import load_dotenv
+
+# Set API keys
+openai.api_key = os.environ['OPENAI_API_KEY']
+OPENWEATHER_API_KEY = os.environ['OPENWEATHER_API_KEY']
+
+# Function to get the current weather
+def get_current_weather(location):
+    """Get the current weather in a given location"""
+    base_url = "http://api.openweathermap.org/data/2.5/weather?"
+    complete_url = f"{base_url}appid={OPENWEATHER_API_KEY}&q={location}"
+
+    response = requests.get(complete_url)
+
+    if response.status_code == 200:
+        data = response.json()
+        weather = data['weather'][0]['main']
+        temperature = data['main']['temp'] - 273.15  # Convert Kelvin to Celsius
+        return {
+            "city": location,
+            "weather": weather,
+            "temperature": round(temperature, 2)
+        }
+    else:
+        return {"city": location, "weather": "Data Fetch Error", "temperature": "N/A"}
+
+# Streamlit app
+st.title("Weather Info Assistant")
+#st.write("Get the current weather information for a specific location. Just replace Gurgaon with the location")
+
+user_input = st.text_input("Get the current weather information for a specific location. Just replace Gurgaon with the location", "What is the weather like in Gurgaon?")
+
+if st.button("Get Weather"):
+    # Use GPT-3.5-turbo to parse the user query
+    response = openai.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {
+                "role": "user",
+                "content": user_input
+            }
+        ],
+        temperature=0,
+        max_tokens=300,
+        functions=[
+            {
+                "name": "get_current_weather",
+                "description": "Get the current weather in a given location",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {
+                            "type": "string",
+                            "description": "The city and state, e.g. San Francisco, CA",
+                        },
+                    },
+                    "required": ["location"],
+                },
+            }
+        ],
+        function_call="auto"
+    )
+
+    # Extract the location from the response
+    try:
+        # Extract the function call information
+        function_call_info = response.choices[0].message.function_call
+        function_name = function_call_info.name  # This should be 'get_current_weather'
+        function_arguments = function_call_info.arguments  # This is a JSON string
+
+        # Parse the JSON string to get the arguments dictionary
+        args = json.loads(function_arguments)
+        location = args['location']
+
+        # Now you can fetch the weather information using the extracted location
+        weather_info = get_current_weather(location)
+
+        # Define a dictionary to map weather conditions to emoticons
+        weather_icons = {
+            "Clear": "☀️",  # Sun icon
+            "Clouds": "☁️",  # Cloud icon
+            "Rain": "🌧️",  # Rain icon
+            "Snow": "❄️",  # Snow icon
+            "Thunderstorm": "⛈️",  # Thunderstorm icon
+            "Mist": "🌫️",  # Fog icon
+            "Smoke": "💨",  # Smoke icon
+            "Haze": "🌫️",  # Haze icon
+            "Dust": "🌪️",  # Dust icon
+            "Fog": "🌫️",  # Fog icon
+            "Sand": "🏜️",  # Sand icon
+            "Ash": "🌋",  # Volcanic ash icon
+            "Squall": "🌬️",  # Wind face icon
+            "Tornado": "🌪️"  # Tornado icon
+        }
+
+        if weather_info["weather"] != "Data Fetch Error":
+            icon = weather_icons.get(weather_info["weather"], "❓")  # Default to question mark if no match
+            weather_description = f"The weather in **{weather_info['city']}** is currently `{weather_info['weather']}` with a temperature of `{weather_info['temperature']}°C`."
+            chat_response = openai.chat.completions.create(
+                model="gpt-3.5-turbo",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": "Generate a conversational response for weather information. Please include the weather and temperature details in the response and provide suggestion on things that can be done best in this weather"
+                    },
+                    {
+                        "role": "user",
+                        "content": weather_description
+                    }
+                ],
+                temperature=0.5,
+                max_tokens=300
+            )
+                        
+            # Use HTML to style the font size, color, and include the icon in the displayed message
+            st.markdown(f"<div style='font-size: 24px; color: blue; font-weight: bold;'> Weather: {weather_info['weather']} {icon} &emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp; Temperature: {weather_info['temperature']}°C</div>", unsafe_allow_html=True)
+            st.markdown(f"<div style='font-size: 20px;'> {chat_response.choices[0].message.content}", unsafe_allow_html=True)
+        else:
+            st.markdown(f"<div style='font-size: 20px;'>**Could not fetch weather data for {weather_info['city']}. Please try again.**</div>", unsafe_allow_html=True)
+    except Exception as e:
+        print(f"Error processing the response or fetching the weather: {e}")