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Getting Started

The following setup will show you how to enable semantic search on arbitrary video in the Eluvio Content Fabric. Everything is done through the Content Search API: you create an index over your contents, and tagging, shot detection, and embedding all run automatically from there.

1. Create a content object for the index​

A search index must be associated with a content object in the Content Fabric. The easiest way to create one is through the Fabric Browser application.

  • Navigate to https://core.v3.contentfabric.io/apps/Fabric%20Browser#/ and sign in with your private key
  • Click on the library you wish to add the content object to
  • Click on "More Options" -> "Create"
  • Once the creation finalizes: copy the object's content id (qid) and the Auth Token for the next step.

2. Create the index​

Create the index on that content object, listing the qids of the contents to search over and the features to search on. See the API docs: Create an index.

POST /vector_search/indexes/<index_qid> HTTP/1.1
Host: ai-04.contentfabric.io
Authorization: Bearer <token>
Content-Type: application/json

{
  "qids": ["<qid1>", "<qid2>"],
  "features": ["scene_description", "celeb"]
}

Each feature names a tagger model. Creating the index starts those tagging jobs on every content, runs shot detection so clips align to shot boundaries, and indexes the tags as they are produced. For a list of available features see List available models.

Note: in order for the clip search API to return playable clips, the given qids must be VOD/Title-Mezzanine type.

Features, aggregation, and search defaults can all be changed later — see Search Configuration.

Using tags you already have​

If you would rather index tags you produced yourself, give the feature a list of tracks instead of letting it run a model. No tagging job is started, and you are responsible for the tracks existing in the tagstore.

{
  "qids": ["<qid1>"],
  "features": [{"name": "captions", "tracks": ["subtitles_en", "subtitles_es"]}]
}

Tags can be written directly with the tagstore API: Post tags. Tagging jobs can also be driven by hand with the tagger API: Start tagging.

3. Check progress​

Tagging and indexing are asynchronous. A single call reports both the per-content tagging jobs and the share of tags embedded so far. See the API docs: Check indexing progress.

GET /vector_search/indexes/<index_qid>/status HTTP/1.1
Host: ai-04.contentfabric.io
Authorization: Bearer <token>

Search is available as soon as tags start landing. See the API docs: Search for clips.

GET /vector_search/indexes/<index_qid>/clip_search?terms=<query> HTTP/1.1
Host: ai-04.contentfabric.io
Authorization: Bearer <token>

EVIE​

Click on index configuration

Index configuration

Select Add Existing Index and enter the content id for the index.

Add existing index

Search results