feat(neuron,candle): log per-device VRAM at chat_completion start

Every "starting" log line now carries vram_free_mb / vram_total_mb for
the request's serving device (the leader device on TP). On the 2026-05-26
incident this would have made the 14k-token prefill OOM diagnosable from
the first log line: with ~412 MB free, that prompt was never going to
fit, and the operator could have caught the imbalance before the CUDA
context got poisoned.

`device_vram_mb` mirrors the existing helper in tp_qwen3_5.rs and is
kept separate to avoid coupling the inference path to the TP module.
TpLoadedModel gains a `leader_device: Device` clone so the request
path reads the device without locking the leader model (which would
contend with an in-flight forward).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

crates/neuron/src/harness/candle.rs

@@ -105,6 +105,11 @@ pub struct TpLoadedModel {
     /// story.
     pub pool: tokio::sync::Mutex<super::tp::WorkerPool>,
     pub leader_model: Arc<tokio::sync::Mutex<super::tp::TpLeaderModel>>,
+    /// Candle device for rank 0. Mirrors what `leader_model.device()`
+    /// would return, but stored separately so the request path can
+    /// query VRAM without locking the leader (which would contend with
+    /// the in-flight forward).
+    pub leader_device: Device,
 }
 
 /// Architecture-specific weights. Each variant covers one (family,
@@ -354,6 +359,36 @@ fn resolve_hf_cache(explicit: Option<PathBuf>) -> Option<PathBuf> {
     None
 }
 
+/// Free/total VRAM on the candle `Device` in MiB. Returns `(0, 0)` if
+/// the query fails or the device is the CPU fallback so logging never
+/// crashes the request path. Mirrors the existing helper in
+/// `tp_qwen3_5.rs`; kept separate to avoid coupling the inference path
+/// to the TP-specific module.
+#[cfg(feature = "cuda")]
+fn device_vram_mb(device: &Device) -> (u64, u64) {
+    use candle_core::cuda::cudarc::driver::result;
+    use candle_core::cuda_backend::WrapErr;
+    let Device::Cuda(dev) = device else {
+        return (0, 0);
+    };
+    let Ok(()) = dev.cuda_stream().context().bind_to_thread().w() else {
+        return (0, 0);
+    };
+    match result::mem_get_info() {
+        Ok((free, total)) => (
+            (free / (1024 * 1024)) as u64,
+            (total / (1024 * 1024)) as u64,
+        ),
+        Err(_) => (0, 0),
+    }
+}
+
+#[cfg(not(feature = "cuda"))]
+#[allow(dead_code)]
+fn device_vram_mb(_device: &Device) -> (u64, u64) {
+    (0, 0)
+}
+
 /// A short hex tag used to group every log line emitted on behalf of
 /// one chat-completion request. Six hex digits is unique enough across
 /// a 4-hour journal window (24 bits ≈ 16M values, while a busy neuron
@@ -838,12 +873,15 @@ impl CandleHarness {
                 .token_to_id("<|im_end|>")
                 .or_else(|| loaded.tokenizer.token_to_id("<|endoftext|>"));
 
+            let (vram_free_mb, vram_total_mb) = device_vram_mb(&loaded.device);
             tracing::info!(
                 prompt_len,
                 max_new,
                 temperature,
                 ?top_p,
                 ?eos_id,
+                vram_free_mb,
+                vram_total_mb,
                 "chat_completion: starting"
             );
 
@@ -1018,12 +1056,15 @@ impl CandleHarness {
         let span_for_task = span.clone();
         {
             let _g = span_for_starting.enter();
+            let (vram_free_mb, vram_total_mb) = device_vram_mb(&loaded.device);
             tracing::info!(
                 prompt_len,
                 max_new,
                 temperature,
                 ?top_p,
                 ?eos_id,
+                vram_free_mb,
+                vram_total_mb,
                 "chat_completion (stream): starting"
             );
         }
@@ -1290,6 +1331,7 @@ impl CandleHarness {
             devices: devices.clone(),
             pool: TMutex::new(pool),
             leader_model,
+            leader_device: leader_device.clone(),
         });
 
         let mut models = self.models.write().await;
@@ -1428,6 +1470,7 @@ impl CandleHarness {
             model = %model_id
         );
         let req_start = std::time::Instant::now();
+        let (vram_free_mb, vram_total_mb) = device_vram_mb(&tp.leader_device);
         tracing::info!(
             parent: &span,
             prompt_len,
@@ -1435,6 +1478,8 @@ impl CandleHarness {
             temperature,
             ?top_p,
             ?eos_id,
+            vram_free_mb,
+            vram_total_mb,
             "TP chat_completion (stream): starting"
         );
         let tp_for_task = Arc::clone(&tp);
@@ -1641,6 +1686,7 @@ async fn chat_completion_tp_inner(
         .token_to_id("<|im_end|>")
         .or_else(|| tp.tokenizer.token_to_id("<|endoftext|>"));
 
+    let (vram_free_mb, vram_total_mb) = device_vram_mb(&tp.leader_device);
     tracing::info!(
         model = %model_id,
         prompt_len,
@@ -1648,6 +1694,8 @@ async fn chat_completion_tp_inner(
         temperature,
         ?top_p,
         ?eos_id,
+        vram_free_mb,
+        vram_total_mb,
         "TP chat_completion: starting"
     );