Weather Assistant using LangChain & OpenWeatherMap

LangChain aur OpenWeatherMap ke Saath 🌤️

Pyaare Developers! Aaj hum ek cool Weather Assistant banayenge jo LangChain aur OpenWeatherMap API ka use karke real-time mausam ka data laata hai. Yeh project dikhata hai ki kaise AI aur open APIs milkar ek smart assistant create kar sakte hain!

🧩 Prerequisites

Python 3.7+ installed
OpenWeatherMap API key (free account se)
LangChain aur pyowm libraries

Step 1: Installation ⚙️

Sabse pehle, zaruri libraries install karein:

pip install langchain pyowm

Step 2: API Key Setup 🔑

OpenWeatherMap se API key lein:

OpenWeatherMap par jaake free account banao
Profile → API Keys me jaake ek key generate karo

Step 3: Code Implementation 💻

from langchain_community.document_loaders import WeatherDataLoader
from langchain_community.utilities import OpenWeatherMapAPIWrapper
import os

# API Key set karo
os.environ["OPENWEATHERMAP_API_KEY"] = "your_api_key_here"

# Weather Wrapper initialize karo
weather_wrapper = OpenWeatherMapAPIWrapper()

# Weather data retrieve karne ka function
def get_weather_info(city):
    try:
        # City ke liye weather data fetch karo
        weather_data = weather_wrapper.run(city)
        return weather_data
    except Exception as e:
        return f"Error: {str(e)}"

# Main function
def weather_assistant():
    print("🌦️ Namaste! Main aapka Mausam Assistant hoon!")
    
    while True:
        city = input("\nKis city ka mausam jaanna chahte hain? (Exit ke liye 'quit' type karein): ")
        
        if city.lower() == 'quit':
            print("Alvida! Phir milenge!")
            break
        
        weather_info = get_weather_info(city)
        print(f"\n{city} ka Mausam Report:\n{weather_info}")

# Assistant start karo
if __name__ == "__main__":
    weather_assistant()

🧠 Deep Dive: Code Explanation

WeatherDataLoader: LangChain ka module jo weather data handle karta hai
OpenWeatherMapAPIWrapper: OpenWeatherMap API ke sath interact karne ka utility
os: Environment variables (API key) securely manage karta hai

get_weather_info(): city ke liye data fetch karta hai aur exceptions handle karta hai.

weather_assistant(): continuous user loop hai jisme city input liya jata hai aur result print hota hai.

🚀 Advanced Features To Try

🌍 Multiple language support
📅 Detailed forecast (hourly/daily)
🌡️ Temperature unit conversion (Celsius ↔ Fahrenheit)
⚙️ Error handling improvements

💡 Best Practices

API key ko secure rakho (environment variables ya .env file use karo)
Rate limiting handle karo (avoid frequent API calls)
Error scenarios jaise “Invalid City” ya “No Data Found” ko cover karo

🧩 Challenges & Solutions

API Limits: Free tier me request limit hoti hai — caching use karo.
Data Accuracy: Different sources se cross-verify karna useful hai.
Performance: Repeated queries ke liye local cache implement karo.

🎯 Conclusion

Bas itna sa effort lagake aapne ek powerful weather assistant bana liya! 🌦️ Yeh project dikhata hai ki kaise AI aur Open APIs ko combine karke practical, real-world solutions banaye ja sakte hain. Ab aap apna AI-based weather chatbot aur advanced bana sakte ho!

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