The Creative Ad Generator is a powerful web application designed to automate the creation of advertisements using state-of-the-art generative AI technologies. By leveraging GPT-4 for text generation, DALL-E for image generation, and Runway ML for video generation, this tool offers a comprehensive solution for producing engaging and dynamic ad content.

• Text Generation: Uses GPT-4 to create engaging ad copy based on the provided input and context.
• Image Generation: Generates custom ad images using DALL-E, based on textual descriptions.
• Video Generation: Creates ad videos using Runway ML's video generation models.
• Customizable Content: Users can tailor the generated content to match their brand's voice and style.

• Azure OpenAI: GPT-4 for text generation and content creation.
• RapidAPI: API integration for seamless communication with generative AI services.
• Runway ML: For video generation and other media creation tasks.
• DALL-E: For generating images based on text descriptions.
• React: Frontend for interactive and responsive UI.
• Tailwind CSS: For a modern, utility-first CSS framework to style the application.
• TypeScript: Provides static typing and better code maintainability.
• Python: For backend processes, integration, and handling AI model requests.

• Node.js (v14.0 or above)
• Python (v3.8 or above)
• API keys for GPT-4, DALL-E, and Runway ML (sign up at their respective platforms for access)

1. Text Generation: Users input a brief description or context for their ad, and GPT-4 generates the corresponding text.
2. Image Generation: The generated text is then used to create an image with DALL-E based on the provided description.
3. Video Generation: For more dynamic ads, the text and images are used to create a short video using Runway ML.
4. Final Output: The app compiles the generated text, image, and Video into a unified advertisement for the user to download or share.

• Thanks to OpenAI for GPT-4 and DALL-E APIs
• Thanks to Runway ML for their video generation technology
• All contributors who have helped improve this project