Haystack is a framework designed to work with various types of data, including non-textual data types. Non-textual data can include images, videos, audio files, and other formats that aren't purely text-based. The framework approaches these data types by providing specialized components and connectors that allow developers to process, store, and retrieve them effectively.
One key aspect of how Haystack handles non-textual data is through the use of custom pipelines and encoders. For instance, developers can create pipelines that include specific preprocessing steps for images or audio files. Imagine you are working with images; you can use libraries like OpenCV or PIL to resize and normalize them before they enter the Haystack framework. Once preprocessed, these images can be encoded into embeddings using models designed for computer vision, such as ResNet or EfficientNet, allowing for similarity searches or quick retrieval alongside textual data.
Additionally, Haystack supports different storage backends, which means that you can choose a solution that is best suited for your non-textual data. For example, you might store video files in a dedicated media server while using a database like Elasticsearch for textual information. Haystack's flexible architecture allows you to query both text and non-text data together, making it easier to build comprehensive applications that can search across various data types. This integration is useful in scenarios like multimedia applications, where users may want to search for relevant videos or images associated with specific text queries.