media/subtitles

Subtitle pipeline — align word-level timestamps + burn subtitles into video.

Category: media
Source: workflows/media/subtitles.py

Input Schema

Field	Type	Default	Description
`media_path`	`string`	`""`
`regenerate`	`object`	—	When set, this run is a regeneration. Workflows may read `direction` / `keep` / `extra_instructions` to modulate prompts; the engine persists `parent_run_id` and `parent_variant_index` as run lineage columns.
`subtitle_max_chars`	`integer`	`40`
`transcript`	`any[]`	—
`variants`	`integer`	`1`	Number of independent variant executions (1–10). When > 1, the engine runs the workflow N times with different sampling, producing N outputs.
`vertical_path`	`object`	—

Output Schema

No schema defined.

Task Pipeline

align_words → render_subtitles

Task	Description
`align_words`	Format transcript segments into subtitle entries with word-level timing.
`render_subtitles`	Burn subtitles into the video using FFmpeg’s drawtext or ASS filter.

Run-spec example

Save the YAML below as my-run.yaml, edit the values, and run with the CLI or POST it to the API. Required fields are uncommented; optional knobs are documented above the input: block — copy any line under input: and uncomment to set.

workflow: media/subtitles

# Optional fields — copy any line(s) under `input:` and uncomment to set:
#   media_path: ""
#
#   subtitle_max_chars: 40
#
#   transcript: []
#
#   vertical_path: null
#

input: {}

Run it locally:

fab-workflow --from-file my-run.yaml

Or submit over the wire — the same file is the request body:

curl -X POST 'https://gofabric.dev/v1/workflows/runs?name=media/subtitles' \
  -H 'Authorization: Bearer fab_xxx' \
  -H 'content-type: application/yaml' \
  --data-binary @my-run.yaml

Every workflow also accepts the universal WorkflowInput fields — variants (1–10 fan-out) and regenerate (creative-direction hints with run lineage). See Run-specs (YAML / TOML / JSON) for the full top-level shape (metadata, priority, bundle, parent, etc.).

Warnings

Last user task render_subtitles has no Pydantic return type — workflow output schema is null. Declare a WorkflowOutput subclass and pass it to Flow(output=…) for a strict contract.