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40 lines
2.3 KiB
Plaintext
40 lines
2.3 KiB
Plaintext
# Clinical Intelligence — Environment Variables
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# Copy to .env and fill in your values. Never commit .env itself.
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# ─── Required ────────────────────────────────────────────────────
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# NVIDIA NGC API Key — used for two things:
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# 1) Docker login to nvcr.io (pulls the OpenFold3 NIM image).
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# Run `make ngc-login` after editing this file, or:
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# echo "$NGC_API_KEY" | docker login nvcr.io -u '$oauthtoken' --password-stdin
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# 2) Runtime credential injected into the OpenFold3 container.
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# Get one at: https://ngc.nvidia.com/setup/api-key
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NGC_API_KEY=nvapi-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
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# ─── LLM Model ──────────────────────────────────────────────────
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# Ollama model to pull and use for inference (~86 GB on disk)
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OLLAMA_MODEL=nemotron-3-super:120b-a12b
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# ─── GPU Selection ───────────────────────────────────────────────
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# Index of the GPU to dedicate to each container. Find with:
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# nvidia-smi --query-gpu=index,name --format=csv,noheader
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# On multi-GPU stations (e.g. RTX PRO 6000 + GB300) you MUST set both
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# to the GB300 index — the RTX PRO 6000 (98 GB) cannot fit Nemotron 3 Super
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# safely, and OpenFold3 crashes when more than one GPU is exposed.
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LLM_GPU=0
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OPENFOLD_GPU=0
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# ─── Service Ports ───────────────────────────────────────────────
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# If host Ollama is already bound to 11434, change OLLAMA_PORT to e.g. 11435.
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# `make setup` sources this file so the sandbox provider picks up the override.
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OLLAMA_PORT=11434
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PROXY_PORT=11435
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OPENFOLD_PORT=8000
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GATEWAY_PORT=18789
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# ─── OpenShell Sandbox ───────────────────────────────────────────
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SANDBOX_NAME=clinical-sandbox
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# ─── FHIR Server ────────────────────────────────────────────────
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# Public synthetic data server (no PHI, no auth required)
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FHIR_BASE_URL=https://r4.smarthealthit.org
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