meta:media

You can search and retrieve past media assets using hybrid semantic search combined with metadata filtering. This approach matches conversational meaning against stored descriptions, tags, and extracted text to instantly locate specific screenshots, recordings, or documents.

Multimodal media memory stores images, video, audio, and documents with rich descriptions, tags, and extracted transcripts. It solves the problem of scattered assets by providing persistent tracking, enabling you to find and reuse files without losing context.

You store generated images and diagrams by ingesting them with detailed descriptions, relevant tags, source tracking, and any extracted text. This rich metadata capture enables accurate hybrid retrieval and proactive recall during future conversations.

Yes, ChromaDB enables local embedding generation to search media memory effectively. It generates semantic embeddings locally from your stored images, video, audio, and documents, allowing hybrid semantic-plus-metadata retrieval without relying on external embedding APIs.

Yes, hybrid retrieval works for finding specific architecture diagrams and mockups by searching across both semantic meaning and metadata. It indexes extracted text and descriptions to locate exact files and display their metadata for easy reopening.

You store generated images and diagrams by ingesting them with detailed descriptions, relevant tags, source tracking, and any extracted text. This rich metadata capture enables accurate hybrid retrieval and proactive recall during future conversations.