Files
cortex/cortex.example.toml
rob thijssen 0da68833af feat: scaffold cortex workspace
Rust reverse-proxy for multi-node mistral.rs inference clusters.
Includes crate structure (cortex-core, cortex-gateway, cortex-agent,
cortex-cli), config loading, OpenAI/Anthropic translation stubs,
model routing, eviction, polling, and streaming proxy scaffolding.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 18:13:30 +03:00

46 lines
1.2 KiB
TOML

# cortex.example.toml — example configuration
#
# Copy to cortex.toml and adjust for your environment.
#
# Environment variable overrides use CORTEX_ prefix with __ separators:
# CORTEX_GATEWAY__LISTEN=0.0.0.0:9000
[gateway]
listen = "0.0.0.0:8000"
metrics_listen = "0.0.0.0:9100"
[eviction]
strategy = "lru"
# Restart mistralrs after this many load/unload cycles to defragment VRAM.
# Set to 0 to disable.
defrag_after_cycles = 50
# -- Nodes ---------------------------------------------------------------
# Each [[nodes]] entry declares a mistral.rs instance in the fleet.
# Models are discovered by polling the node's /v1/models endpoint.
# Pinned models are never evicted.
[[nodes]]
name = "gpu-large"
endpoint = "http://gpu-large.internal:8080"
vram_mb = 49152 # e.g. 2x RTX 4090 (48 GB combined)
pinned = [
"your-org/large-model",
]
[[nodes]]
name = "gpu-medium"
endpoint = "http://gpu-medium.internal:8080"
vram_mb = 24576 # e.g. RTX 4090 (24 GB)
pinned = [
"your-org/medium-model",
]
[[nodes]]
name = "gpu-small"
endpoint = "http://gpu-small.internal:8080"
vram_mb = 12288 # e.g. RTX 3060 (12 GB)
pinned = [
"your-org/embedding-model",
]