wehub-resource-sync
72 lines
3.1 KiB
Python
72 lines
3.1 KiB
Python
"""Modal deploy glue for the Omnigent server.
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Runs the standard server image (``ghcr.io/omnigent-ai/omnigent-server``)
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as a single always-on Modal web server, proxying HTTP / SSE / WebSocket
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traffic to the same Docker entrypoint every other container platform
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uses (``deploy/docker/entrypoint.py``). See README.md for the
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walkthrough.
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"""
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import subprocess
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import modal
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# The CI-built server image — ships the gitignored web UI bundle that a
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# source build can't produce (same reason every other platform pulls it;
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# see deploy/docker/Dockerfile.prebuilt). Modal injects its client
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# runtime into the image's Python at image-build time.
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SERVER_IMAGE = "ghcr.io/omnigent-ai/omnigent-server:latest"
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# The image's uvicorn port (deploy/docker/Dockerfile: EXPOSE 8000).
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SERVER_PORT = 8000
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# First boot runs DB migrations over the network (~1 minute on Neon);
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# 300 s leaves comfortable headroom before Modal declares startup failed.
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STARTUP_TIMEOUT_S = 300
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app = modal.App("omnigent")
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# Persists uploaded agent bundles / artifacts across container restarts
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# and redeploys — unlike Heroku / Cloudflare Containers, the artifact
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# store is durable here.
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artifacts = modal.Volume.from_name("omnigent-artifacts", create_if_missing=True)
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@app.function(
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image=modal.Image.from_registry(SERVER_IMAGE),
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# DATABASE_URL, OMNIGENT_ACCOUNTS_COOKIE_SECRET, and
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# OMNIGENT_ACCOUNTS_BASE_URL — created in the README's step 1.
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secrets=[modal.Secret.from_name("omnigent-deploy")],
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volumes={"/data/artifacts": artifacts},
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# One always-on container: the runner registry lives in server
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# memory, so traffic must not be spread across containers
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# (max_containers), and scale-to-zero would tear down live runner
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# tunnels (min_containers).
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min_containers=1,
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max_containers=1,
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# The server's working-set floor (~512 MB–1 GB; see deploy/README.md's
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# memory-floor note) — Modal's defaults sit below it.
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cpu=1.0,
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memory=1024,
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# Each proxied request / WebSocket holds one Modal "input" for its
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# lifetime, and an input ends when this timeout lapses — so use the
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# platform maximum (24 h). Runners auto-reconnect after the cut.
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timeout=24 * 60 * 60,
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)
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# Every in-flight request / SSE stream / WebSocket holds one input on the
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# single container, so this is the simultaneous-connection budget; 1000
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# comfortably covers a small team's runners + browser tabs + terminals.
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@modal.concurrent(max_inputs=1000)
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@modal.web_server(port=SERVER_PORT, startup_timeout=STARTUP_TIMEOUT_S)
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def server() -> None:
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"""
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Launch the standard Docker entrypoint and let Modal proxy to it.
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``@modal.web_server`` forwards HTTP / SSE / WebSocket traffic to
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``SERVER_PORT`` once the process starts listening. Running the
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entrypoint as a subprocess (rather than importing the FastAPI app
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into Modal's own ASGI runner) keeps this deploy on the exact same
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code path as every other container platform: migrations, store
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wiring, auth defaults, and uvicorn flags like the runner tunnel's
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``ws_max_size`` all come from ``deploy/docker/entrypoint.py``.
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"""
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subprocess.Popen(["python", "/app/entrypoint.py"])
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