* Update the v2 create transcribe payload to support
publishing directly to docs and performing automatically
a summary if requested
* Note that title computation is to be handled by the caller
now as it makes more sense and avoids throwing a bunch
of parameters to the endpoint.
* All files are send as signed URL now, we don't read
directly from s3 anymore,
* Docs integration is now explicit in summary settings
* To make analytics work properly accross projects,
we use the user sub as distinct id,
this will require a new posthog project to be deployed
to work properly.
We create a post hog event at the creation request processing,
to make sure feature flags work properly after that.
* User email should now be provided to the API, it's not
mandatory to avoid a breaking change.
* Use a specific user agent for better tracking
Finally note that existing helpers don't always make use of
the pydantic models, so that's why there
are model_dump in some places. To avoid bigger changes.
This commit cleans up most of the code related to v1 route that
is used only by visio.
This is first step before introducing an update to the v2 route.
Rarely media files may have one or multiple
empty streams when they are badly formatted.
The extract metadata code would crash when that happened.
We now avoid crashing and create a clean file
from the bad one to make sure API calls with that data
works properly (observed some failures otherwise
in my tests).
Add a footer to transcription outputs linking to an external satisfaction
survey. The survey URL is built from TRANSCRIPTION_SATISFACTION_FORM_BASE_URL.
When TRANSCRIPTION_SATISFACTION_FORM_BASE_URL is unset or None, the
footer is omitted.
* Removed constraint on file extension
* Infer audio/video streams from the media with ffmpeg
* Infer the correct processed audio file extension based on actual
codec to avoid ffmpeg errors
We need to support more extensions and make audio extraction dynamic,
as we shipped transcript in production and it led to user complaints
requesting more formats.
Speaker-to-participant assignment relie on WhisperX word timings, but
incorrect word durations in the output can lead to inaccurate overlap
scoring and wrong user attribution. Add a custom heuristic to trim
overly long word durations before computing assignments.
When duration is not reported in the files metadata,
we directly infer the duration from the audio packets.
This prevents errors on webm files.
Very simple audio & video test files have been added
that cover relevant usecases to prevent regressions.
Introduce a new user assignment mechanism to for more friendly output
than the current (SPEAKER_0, SPEAKER_1, ...). Use the VAD metadata to
compare speech intervals with those returned by WhisperX. User with the
highest overlap score above a defined threshold is assigned to each segment.
This method allows for multi-speaker scenarios for a single account.
The tasks endpoint used non-timezone-aware date and time values and split
them into separate variables, which is unconventional. Refactor the
implementation to use timezone-aware datetime objects and align transcription
formatting with the user-declared timezone. Update the source of truth for
recording start time to FileInfo.started_at for improved precision. Adjust
the task signature in preparation for upcoming user assignment work, which
will require `started_at`, `ended_at`, and `metadata_filename`.
Updated taskV2 API contract to be closer to the target gateway contract.
GET operations return the same things as the webhook payload.
Also store the summary on S3 to be iso with transcript.
Add multitenancy support to Summary sub-app. The V1 routes / tasks
behave like before, with the default tenant being "meet".
V2 routes / tasks support being called frm any tenant, and don't have
meet related logic.
V2 tasks are created in separate queues to avoid mix / match,i
Florent Chehab