feat(tp): Stage 7c-i — streaming SSE through TP

`chat_completion_stream` no longer returns an error for TP loads. The
new `chat_completion_tp_stream` mirrors the non-streaming TP path
(clear_kv_cache, prefill, sample, decode loop) but emits one
`ChatCompletionChunk` per generated token over an mpsc channel so the
handler can write a streaming SSE response.

Unlike the single-GPU streaming path (which runs candle's forward
inside `spawn_blocking` and uses `blocking_send`), the TP loop is
itself async — every `pool.generate_step` already awaits the leader's
own spawn_blocking forward plus every worker's recv_only. So the
orchestration runs as a plain `tokio::spawn` task using `Sender::send`.

The shared `emit_chunk` helper tracks the cumulative decoded prefix and
emits the delta — same UTF-8-safe BPE boundary handling as the
single-GPU streaming path.

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

crates/neuron/src/harness/candle.rs

@@ -526,15 +526,8 @@ impl CandleHarness {
         let loaded = match handle {
             LoadedHandle::Single(m) => m,
             #[cfg(feature = "cuda")]
-            LoadedHandle::Tp(_) => {
+            LoadedHandle::Tp(m) => {
-                // Streaming through TP is Stage 7c work — the
+                return self.chat_completion_tp_stream(m, request).await;
-                // non-streaming path drives the same forwards through
-                // the pool but doesn't have to interleave SSE writes
-                // with spawn_blocking forwards.
-                return Err(InferenceError::Other(anyhow::anyhow!(
-                    "streaming chat completions through TP are not yet supported; \
-                     retry with stream=false"
-                )));
             }
         };
 
@@ -961,6 +954,258 @@ impl CandleHarness {
             extra: serde_json::Value::Object(Default::default()),
         })
     }
+
+    /// Streaming counterpart to `chat_completion_tp`. Same per-step
+    /// orchestration (clear cache, prefill, sample, decode loop) but
+    /// emits one `ChatCompletionChunk` per token over an mpsc channel
+    /// so the handler can write an SSE stream.
+    ///
+    /// Unlike the single-GPU streaming path (which runs the candle
+    /// forward inside `spawn_blocking` and uses `blocking_send`), the
+    /// TP loop is itself async — every `pool.generate_step` awaits the
+    /// leader's spawn_blocking forward plus every worker's recv_only.
+    /// So we `tokio::spawn` the orchestration task and use plain
+    /// `Sender::send`.
+    #[cfg(feature = "cuda")]
+    async fn chat_completion_tp_stream(
+        &self,
+        tp: Arc<TpLoadedModel>,
+        request: ChatCompletionRequest,
+    ) -> Result<mpsc::Receiver<ChatCompletionChunk>, InferenceError> {
+        let prompt = format_qwen3_prompt(&request.messages);
+        let encoding = tp
+            .tokenizer
+            .encode(prompt.as_str(), true)
+            .map_err(|e| InferenceError::Other(anyhow::anyhow!("tokenize: {e}")))?;
+        let prompt_tokens: Vec<u32> = encoding.get_ids().to_vec();
+        let prompt_len = prompt_tokens.len();
+
+        let temperature = request.temperature.unwrap_or(0.7);
+        let top_p = request.top_p;
+        let max_new = request.max_tokens.unwrap_or(512) as usize;
+        let seed = unix_subsec_nanos();
+
+        let eos_id = tp
+            .tokenizer
+            .token_to_id("<|im_end|>")
+            .or_else(|| tp.tokenizer.token_to_id("<|endoftext|>"));
+
+        let model_id = request.model.clone();
+        let id = format!("chatcmpl-{:x}", unix_subsec_nanos());
+        let created = unix_now_secs();
+        let tokenizer = tp.tokenizer.clone();
+
+        // Bounded channel — back-pressures the producer when the SSE
+        // writer is slow.
+        let (tx, rx) = mpsc::channel::<ChatCompletionChunk>(32);
+
+        // Role chunk first, before kicking off the heavy work — if the
+        // receiver is gone by now there's no point starting inference.
+        let role_chunk = ChatCompletionChunk {
+            id: id.clone(),
+            object: "chat.completion.chunk".into(),
+            created,
+            model: model_id.clone(),
+            choices: vec![ChunkChoice {
+                index: 0,
+                delta: json!({"role": "assistant"}),
+                finish_reason: None,
+                extra: serde_json::Value::Object(Default::default()),
+            }],
+            usage: None,
+            extra: serde_json::Value::Object(Default::default()),
+        };
+        tx.send(role_chunk)
+            .await
+            .map_err(|_| InferenceError::Other(anyhow::anyhow!("client disconnected")))?;
+
+        // The orchestration task. Holds the pool lock for the lifetime
+        // of this inference; concurrent requests against the same TP
+        // model serialise behind it.
+        let tp_for_task = Arc::clone(&tp);
+        tokio::spawn(async move {
+            let mut pool = tp_for_task.pool.lock().await;
+            let leader_arc = tp_for_task.leader_model.clone();
+
+            if let Err(e) = pool.clear_kv_cache(&model_id, leader_arc.clone()).await {
+                tracing::warn!(model = %model_id, error = %e, "TP stream: clear_kv_cache failed");
+                return;
+            }
+
+            let mut logits_processor = {
+                let sampling = if temperature <= 0.0 {
+                    Sampling::ArgMax
+                } else {
+                    match top_p {
+                        Some(p) => Sampling::TopP { p, temperature },
+                        None => Sampling::All { temperature },
+                    }
+                };
+                LogitsProcessor::from_sampling(seed, sampling)
+            };
+
+            let mut all_tokens: Vec<u32> = Vec::new();
+            let mut decoded_prefix = String::new();
+            let mut finish_reason = "length".to_string();
+
+            // Prefill — every rank embeds the prompt, offset = 0.
+            let logits = match pool
+                .generate_step(&model_id, leader_arc.clone(), prompt_tokens.clone(), 0)
+                .await
+            {
+                Ok(l) => l,
+                Err(e) => {
+                    tracing::warn!(model = %model_id, error = %e, "TP stream: prefill failed");
+                    return;
+                }
+            };
+            let mut next_token = match sample_with_penalty(
+                &logits,
+                &all_tokens,
+                &mut logits_processor,
+            ) {
+                Ok(t) => t,
+                Err(e) => {
+                    tracing::warn!(model = %model_id, error = %e, "TP stream: prefill sample failed");
+                    return;
+                }
+            };
+
+            if Some(next_token) == eos_id {
+                finish_reason = "stop".into();
+            } else {
+                all_tokens.push(next_token);
+                if !emit_chunk(
+                    &all_tokens,
+                    &mut decoded_prefix,
+                    &tokenizer,
+                    &tx,
+                    &id,
+                    created,
+                    &model_id,
+                )
+                .await
+                {
+                    return;
+                }
+
+                for index in 0..max_new.saturating_sub(1) {
+                    let logits = match pool
+                        .generate_step(
+                            &model_id,
+                            leader_arc.clone(),
+                            vec![next_token],
+                            prompt_len + index,
+                        )
+                        .await
+                    {
+                        Ok(l) => l,
+                        Err(e) => {
+                            tracing::warn!(
+                                model = %model_id,
+                                error = %e,
+                                "TP stream: decode step failed"
+                            );
+                            return;
+                        }
+                    };
+                    next_token =
+                        match sample_with_penalty(&logits, &all_tokens, &mut logits_processor) {
+                            Ok(t) => t,
+                            Err(e) => {
+                                tracing::warn!(
+                                    model = %model_id,
+                                    error = %e,
+                                    "TP stream: decode sample failed"
+                                );
+                                return;
+                            }
+                        };
+                    if Some(next_token) == eos_id {
+                        finish_reason = "stop".into();
+                        break;
+                    }
+                    all_tokens.push(next_token);
+                    if !emit_chunk(
+                        &all_tokens,
+                        &mut decoded_prefix,
+                        &tokenizer,
+                        &tx,
+                        &id,
+                        created,
+                        &model_id,
+                    )
+                    .await
+                    {
+                        return;
+                    }
+                }
+            }
+
+            // Final chunk carrying finish_reason.
+            let final_chunk = ChatCompletionChunk {
+                id: id.clone(),
+                object: "chat.completion.chunk".into(),
+                created,
+                model: model_id.clone(),
+                choices: vec![ChunkChoice {
+                    index: 0,
+                    delta: serde_json::Value::Object(Default::default()),
+                    finish_reason: Some(finish_reason),
+                    extra: serde_json::Value::Object(Default::default()),
+                }],
+                usage: None,
+                extra: serde_json::Value::Object(Default::default()),
+            };
+            let _ = tx.send(final_chunk).await;
+        });
+
+        Ok(rx)
+    }
+}
+
+/// Decode the cumulative token list, emit the delta (substring appended
+/// since the last chunk) as a `chat.completion.chunk`. Returns `false`
+/// if the receiver has hung up — the caller should bail.
+#[cfg(feature = "cuda")]
+async fn emit_chunk(
+    all_tokens: &[u32],
+    decoded_prefix: &mut String,
+    tokenizer: &Tokenizer,
+    tx: &mpsc::Sender<ChatCompletionChunk>,
+    id: &str,
+    created: u64,
+    model_id: &str,
+) -> bool {
+    let full = match tokenizer.decode(all_tokens, true) {
+        Ok(s) => s,
+        Err(e) => {
+            tracing::warn!(error = %e, "TP stream: decode failed");
+            return false;
+        }
+    };
+    if full.len() > decoded_prefix.len() {
+        let delta = full[decoded_prefix.len()..].to_string();
+        *decoded_prefix = full;
+        let chunk = ChatCompletionChunk {
+            id: id.into(),
+            object: "chat.completion.chunk".into(),
+            created,
+            model: model_id.into(),
+            choices: vec![ChunkChoice {
+                index: 0,
+                delta: json!({ "content": delta }),
+                finish_reason: None,
+                extra: serde_json::Value::Object(Default::default()),
+            }],
+            usage: None,
+            extra: serde_json::Value::Object(Default::default()),
+        };
+        if tx.send(chunk).await.is_err() {
+            return false;
+        }
+    }
+    true
 }
 
 /// Errors returned by `CandleHarness::chat_completion`. The