alibabacloud-oss-manage-metaquery

You can perform semantic search over OSS media assets by running a Python script to open MetaQuery in semantic mode, which builds vector indexes for your stored images, videos, audio, and documents to enable qualitative content retrieval.

Yes, enabling OSS MetaQuery with AI content awareness automatically generates descriptive metadata for your media files. The search results will include AI-generated descriptions and concise summaries for the retrieved assets.

You can manage the vector index lifecycle directly through the Python script provided. It supports opening, querying, checking the status, and closing MetaQuery for production-grade data indexing and retrieval on your OSS storage.

Yes, OSS vector search supports scalar and vector hybrid searches. This allows you to filter assets by metadata like size, creation time, or tags while maintaining semantic relevance to the search query.

You need the oss2 and alibabacloud-credentials Python packages to run the script. These dependencies handle the OSS storage connection and authentication required to enable and query MetaQuery.

The best way to index large volumes of OSS files is to enable MetaQuery with vector search and AI content awareness. This builds semantic indexes across your media assets, allowing rapid location of files matching qualitative queries.