We should be able to use other transcription services,
those usually relie on response_format="diarized_json"
to produce what we need.
Note that as part of this change, we stop using
openai library for making this call to avoid
casting the result to a payload that doesn't
contain the elements we used to rely on.
(setting this specific format auto cast the
results in openai lib). We keep the old
result class used.
When going through AlbertAPI, timestamp are not provided at the word level.
This adds default values so that the summary external contract stays the same,
while giving us compatibility wisht AlbertAPI.
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
Update the link label to use explicit text "Download your recording"
instead of generic "following this link."
This ensures blind users understand the purpose of the link
and the behavior of opening a new window.
Refactor the summary service to better separate concerns, making components
easier to isolate and test. Unify logging logic to ensure consistent
behavior and reduce duplication across the service layer. These changes
set up the codebase for granular testing.
Transcription and summarization results were always generated
using a French text structure (e.g. "Réunion du..."), regardless
of user preference or meeting language. Introduced basic localization
support to adapt generated string languages.
Pip was removed before copying the builder stage output, which caused
it to be reinstalled unintentionally. Adjust the order to align with
the backend image behavior.
Reduce surface area and keep the runtime image minimal.
Alpine 3.22 provides ffmpeg v6 as the latest version.
Alpine 3.23 does not include ffmpeg v7, so upgrade directly to v8.
Install pip temporarily for build steps, then remove it from the
production image.
Florent Chehab