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>

crates/cortex-agent/Cargo.toml

@@ -0,0 +1,14 @@
+[package]
+name = "cortex-agent"
+version.workspace = true
+edition.workspace = true
+license.workspace = true
+
+[dependencies]
+cortex-core.workspace = true
+tokio.workspace = true
+serde.workspace = true
+serde_json.workspace = true
+reqwest.workspace = true
+tracing.workspace = true
+anyhow.workspace = true

crates/cortex-agent/src/agent.rs

@@ -0,0 +1,72 @@
+//! Per-node agent sidecar.
+//!
+//! This is a future component that runs on each GPU node alongside mistralrs.
+//! It handles:
+//!   - VRAM defragmentation (restarting the mistralrs systemd unit when the
+//!     gateway signals that lifecycle_cycles has exceeded the threshold)
+//!   - Local nvidia-smi polling for actual VRAM usage reporting
+//!   - Systemd unit management for mistralrs process restarts
+//!
+//! For now this is a stub. The gateway's poller + evictor handle the critical
+//! path (model lifecycle via the mistralrs HTTP API). The agent adds
+//! operational niceties that can be built incrementally.
+
+/// Placeholder for agent configuration.
+#[derive(Debug, Clone)]
+pub struct AgentConfig {
+    /// The local mistralrs endpoint to monitor.
+    pub mistralrs_endpoint: String,
+    /// The systemd unit name for mistralrs (e.g. "mistralrs.service").
+    pub systemd_unit: String,
+}
+
+/// Restart the local mistralrs process via systemd.
+/// This is the nuclear option for VRAM defragmentation.
+pub async fn restart_mistralrs(config: &AgentConfig) -> anyhow::Result<()> {
+    tracing::warn!(
+        unit = %config.systemd_unit,
+        "restarting mistralrs for VRAM defragmentation"
+    );
+
+    let output = tokio::process::Command::new("systemctl")
+        .args(["restart", &config.systemd_unit])
+        .output()
+        .await?;
+
+    if output.status.success() {
+        tracing::info!(unit = %config.systemd_unit, "mistralrs restarted successfully");
+        Ok(())
+    } else {
+        let stderr = String::from_utf8_lossy(&output.stderr);
+        anyhow::bail!("systemctl restart failed: {stderr}");
+    }
+}
+
+/// Query nvidia-smi for current VRAM usage on this node.
+/// Returns (used_mb, total_mb) for each GPU.
+pub async fn query_vram() -> anyhow::Result<Vec<(u64, u64)>> {
+    let output = tokio::process::Command::new("nvidia-smi")
+        .args([
+            "--query-gpu=memory.used,memory.total",
+            "--format=csv,noheader,nounits",
+        ])
+        .output()
+        .await?;
+
+    if !output.status.success() {
+        let stderr = String::from_utf8_lossy(&output.stderr);
+        anyhow::bail!("nvidia-smi failed: {stderr}");
+    }
+
+    let stdout = String::from_utf8_lossy(&output.stdout);
+    let mut gpus = Vec::new();
+    for line in stdout.lines() {
+        let parts: Vec<&str> = line.split(',').map(|s| s.trim()).collect();
+        if parts.len() == 2 {
+            let used: u64 = parts[0].parse().unwrap_or(0);
+            let total: u64 = parts[1].parse().unwrap_or(0);
+            gpus.push((used, total));
+        }
+    }
+    Ok(gpus)
+}

crates/cortex-agent/src/lib.rs

@@ -0,0 +1 @@
+pub mod agent;