Real-time-weather-forecast

A weather app that integrates OpenAI's GPT model with OpenWeatherMap API to deliver precise and up-to-date weather forecasts.

Table of Contents

• Overview
• Features
• Prerequisites
• Setup-and-Running
• Usage

Overview

The Weather Information App provides real-time weather information for any location using OpenAI's GPT model and the OpenWeatherMap API. It leverages LangGraph workflow to process user input and retrieve accurate weather data.

Features

• Extracts city name from user input.
• Retrieves weather information from OpenWeatherMap API.
• Provides temperature in both Celsius and Fahrenheit.

Prerequisites

• Python 3.7 or higher
• pip for package management
• .env file for API keys

Setup and Running

1. Clone the repository

   git clone https://github.com/your-username/weather-info-app.git
   cd weather-info-app

2. Create a virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages

   pip install -r requirements.txt

4. Set up environment variables

   Create a .env file in the root directory of the project and add your API keys:

   OPENWEATHERMAP_API_KEY=your_openweathermap_api_key
   OPENAI_API_KEY=your_openai_api_key
   

Running the Application

1. Run the Streamlit app

   streamlit run app.py

2. Open the app in your browser at http://localhost:8501.

Usage

1. Enter your location in the "Enter your location" field.
2. Click the "Get Weather" button to fetch weather information.
3. Review the weather report displayed on the screen.

Code Overview

• Environment Configuration: Loads API keys from the .env file and sets up Langsmith tracing.
• LangChain Workflow: Defines a graph with nodes for extracting city names, fetching weather data, and providing temperature information.
• Streamlit Interface: Provides a user-friendly interface for inputting location and viewing results.

Code Components

1. Environment Setup

   load_dotenv()
   os.environ["OPENWEATHERMAP_API_KEY"] = os.environ.get("OPENWEATHERMAP_API_KEY")
   os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")

2. Function Definitions

   • function_1: Extracts city name from user input using GPT-3.5-turbo.
   • function_2: Fetches weather data using the OpenWeatherMap API.
   • function_3: Generates temperature information in Celsius and Fahrenheit.

3. LangChain Graph Workflow

   workflow = Graph()
   workflow.add_node("agent", function_1)
   workflow.add_node("tool", function_2)
   workflow.add_node("responder", function_3)
   workflow.add_edge('agent', 'tool')
   workflow.add_edge('tool', 'responder')
   workflow.set_entry_point("agent")
   workflow.set_finish_point("responder")
   app = workflow.compile()

4. Streamlit App Configuration

   st.set_page_config(page_title="Weather Information App", page_icon="🌦️", layout="wide")
   st.markdown("...")

App Usage ScreenShorts

App Trace in LangSmith

App workflow matplotlib graph