Yes, you can use LlamaIndex with non-textual data such as audio or video, but it requires some additional steps to process that data into a suitable format. LlamaIndex is primarily designed for working with textual data, so to incorporate audio or video, you will first need to convert these files into text. This typically involves using speech recognition tools for audio files to transcribe the spoken content into text, while video files may require extracting the audio track followed by transcription, or you might need to process the visual components depending on your needs.
For instance, if you have a collection of audio recordings of meetings, you could use a tool like Google Speech-to-Text or an open-source library like Mozilla’s DeepSpeech to transcribe the audio into written text. Once you have the text data, you can then proceed to integrate it with LlamaIndex just like any other textual data. This allows you to build features such as searchability or querying over the content of your audio recordings. Similarly, for video data, you might use a combination of computer vision and speech recognition to create a comprehensive text representation of the video's content.
In summary, while LlamaIndex can be used with audio and video data, it requires preprocessing to make that non-textual data compatible. By converting the content of these files into a text format, you can leverage LlamaIndex’s capabilities to manage, search, and analyze the resulting textual information effectively. Understanding these preprocessing steps is crucial for developers looking to expand the types of data they work with in LlamaIndex.