Add LiveKit Egress service #15
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lebaudantoine
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lebaudantoine
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LiveKit server configuration was the default ones. These configurations were not connecting to any Redis instance. When running a standalone LiveKit server, Redis is not needed. However, when adding other LiveKit ecosystem service, e.g. Egress, LiveKit server publish jobs to a Redis queue, that are handled by the Egress workers. (Precisely, they use Redis Pub/Sub to communicate but I am no expert) The LiveKit server and the Egress need to be connected to the same Redis instance. This commit configure the LiveKit server before adding the Egress service to the compose stack.
LiveKit offers Universal Egress, designed to provide universal exports of LiveKit sessions or tracks to a file or stream data. Egress is kept outside of the server to keep the load off the SFU and avoid impacting real-time audio or video performance/quality. Followed the "Running Locally" steps from the https://github.com/livekit/egress repository, but I adapted them to docker-compose. By default, I chose to run both the LiveKit server and the Egress when you up the stack. If we see any performance issue, we could only run the LiveKit server, which is the barebone of the product. Egress will be usefull only when dealing with recording/exporting data. Egress service will output file recordings to "./docker/livekit/out" Note: the Egress service doesn't run as root. You need to update the "/out" permissions, so all user could write to it.
This .json file will be useful when calling the LiveKit CLI command "start-egress", which takes a "--request" params as a path to a json file.
LiveKit CLI is essential to interact with the running server and its ecosystem. I recommend installing it, as you can list rooms, find participant identity, create egress to record room, etc. It helped a lot debugging the Egress service, and discovering its features.
Soon we will have a proper Python API, that will interact with the Egress service. Until this point, I shared how recording data from a meeting. So we could extract data from the LiveKit server, and use it as sample to build the AI pipeline. Please note this documentation is minimal, it's a mini-tutorial.
No need to wrap string environment values in quotes.
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Purpose
Run locally the Egress service.
Proposal
Necessary for the issue #12.
I have cleaned the closed PR #13, which was a draft.
Everything is explained in commits' body.