mirror of https://github.com/suitenumerique/meet.git synced 2026-07-28 04:39:16 +00:00

Files

T

Florent Chehab 9b7c449ca5 🐛(summary) explicit transcription response format

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.

2026-06-18 18:10:50 +02:00

summary

🐛(summary) explicit transcription response format

2026-06-18 18:10:50 +02:00

tests

✨(summary) add optional satisfaction survey footer

2026-06-15 17:33:24 +02:00

Dockerfile

🩹(summary) fix pip uninstall order in build stages

2026-02-20 18:27:17 +01:00

pyproject.toml

🔖(minor) bump release to 1.21.0

2026-06-15 18:29:52 +02:00

README.md

📝(docs) add summarization documentation

2025-10-06 14:53:56 +02:00

README.md

Experimental Stack

This is an experimental part of the stack. It currently lacks proper observability, unit tests, and other production-grade features. This serves as the base for AI features in Visio.

How it works

Please refer to the Recording feature documentation and the Transcription feature documentation.

How to develop

(To develop locally follow the instructions on developing La Suite Meet locally)

From the root of the project:

make bootstrap

Configure your env values in env.d/summary to properly set up WhisperX and the LLM API you will call.

make run

When the stack is up, configure the MinIO webhook (TODO: add this step to make bootstrap)

make minio-webhook-setup

If you want to develop on the Celery workers with hot reloading, run:

docker compose watch celery-summary-transcribe celery-summary-summarize

Celery workers will hot reload on any change.