Welcome to the Targeted Advertisement Project (TAP) repository! Our project aims to revolutionize the world of advertisements by creating personalized and relevant ads for specific users. We achieve this by leveraging the power of Langchain and Generative AI, particularly using the GPT model.
By utilizing personal, flight, and weather data, we generate a prompt using an OpenAI model. This prompt serves as the basis for creating a brief, personalized advertisement that resonates with the individual user. To enhance the user experience further, we are also working on implementing image generation, which will complement the generated text.
We believe that targeted advertising can greatly enhance the effectiveness of promotional campaigns while providing users with ads that are genuinely meaningful and tailored to their interests. Through the combination of advanced technologies and data analysis, our project aims to deliver a new level of personalized advertising.
Our project is developed and maintained by:
To set up the project and install the required dependencies, please follow these steps:
-
Clone the repository:
git clone https://github.com/LeonardoRocca-13/Project_Advertisement.git -
Navigate to the project directory:
cd (YOUR-REPO-PATH) -
Create a virtual environment (optional but recommended):
conda create -n (TAP) -
Activate the virtual environment:
conda activate TAP
(OR using venv:
-
Create a virtual environment (optional but recommended):
python -m venv env -
Activate the virtual environment: -For Windows:
.\env\Scripts\activate-For macOS/Linux:source env/bin/activate) -
Install the required dependencies from the requirements.txt file:
pip install -r requirements.txt
Now you have successfully installed all the required dependencies. You are ready to use the TAP!
Once the environment is setup, all you need to do is execute main.py!
We welcome contributions from anyone interested in improving our project! If you have an idea or suggestion, feel free to create an issue or submit a pull request.
This project is released under the MIT License. Please refer to the LICENSE file for the full license text.