

Album AI
Overview :
Album AI is an experimental project that uses gpt-4o-mini as the visual model, automatically recognizes the metadata of image files in the album, and uses RAG technology to realize dialogue with the album. It can be used as a traditional album, or as an image knowledge base to assist large language models in content generation.
Target Users :
Album AI is designed for photography enthusiasts and professionals who need image knowledge base. It can automatically manage and retrieve large-scale image data, while interacting with images through conversation to improve work efficiency and experience.
Use Cases
Photography enthusiasts organize and manage personal photos using Album AI.
Designers use Album AI as an image knowledge base to aid in design inspiration.
Content creators use Album AI for image searching and conversation to generate new creative content.
Features
Automatically discover images in the album and store them using a PgSQL database.
Automatically generate image metadata using gpt-4o-mini.
Use OpenAI's Embedding API to vectorize metadata.
Provide two APIs: search API and chat API.
One-click deployment to platforms that support Docker container deployment.
Open source license allowing integration and modification.
How to Use
Clone the project to the local environment.
Modify the .env.prod file to configure local proxy and OpenAI API key.
Build and run the project.
Access http://localhost:8080 in a browser to view the demonstration.
Add new photos to the images directory in the project, and the backend will automatically identify and vectorize the metadata.
Use the search and chat features in the demonstration to interact with these photos.
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