A dynamic AI-powered platform that leverages OpenAI's GPT model and the Korea Meteorological Administration (KMA) API to provide not only real-time weather data but also versatile responses based on user queries. The platform offers both a chatbot interface for direct user interaction and API services for weather data retrieval. Users can query weather conditions, and the system will fetch the latest data from the KMA API and provide real-time, context-aware responses.
24.09.05 - 24.09.10
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Front-End
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Back-End
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APIs
To set up and run the project, follow these steps:
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Clone the project repository:
git clone https://github.com/kimwoolina/llm_pjt.git
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Navigate to the project directory:
cd /Users/YourPC/Your_Cloned_Folder/llm_pjt/
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Install the required dependencies:
pip install -r requirements.txt
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Create and configure the
config.py
file:Create a file named
config.py
in the project root directory and add the following content:# config.py DJANGO_SECRET_KEY = "your_django_secret_key_here" OPENAI_API_KEY = "your_openai_api_key_here" # Weather API SERVICE_KEY = "your_weather_api_key_here"
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Configure the Django settings:
Update the
settings.py
file in your Django project to include the configuration fromconfig.py
:from . import config SECRET_KEY = config.DJANGO_SECRET_KEY OPEN_API_KEY = config.OPENAI_API_KEY SERVICE_KEY = config.SERVICE_KEY
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Apply database migrations:
python manage.py makemigrations python manage.py migrate
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Run the development server:
python manage.py runserver
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Open your browser and visit:
Name | Endpoint | Method | Description |
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Weather Query | /chatgpt/weather-chat/ |
GET | Retrieves real-time weather data from the Weather API, enhanced by an LLM |
Location Data | /myapp/location-data/ |
GET | Retrieves location data from an Excel file. |
For any issues or inquiries, please contact kimwoolina@gmail.com