[fix] baseline7 fix git add qwen3_6_scripts/serving_chat.py!

computility-run.yaml

@@ -1,55 +1,99 @@
 concurrency: 1
+
 command:
-    - python3
+
-    - -m
+    - bash
-    - vllm.entrypoints.openai.api_server
+
-    - --model
+    - -c
-    - /model
+
-    - --served-model-name
+    - >-
-    - llm
+
-    - --max-model-len
+        python3 /workspace/qwen3_6_scripts/patch_chat_template.py /model 2>&1 || echo '[runtime] chat template patch failed';
-    - '131072'
+
-    - --gpu-memory-utilization
+        VLLM_ROOT=$(python3 -c 'import vllm,os;print(os.path.dirname(vllm.__file__))');
-    - '0.92'
+
-    - --trust-remote-code
+        cp /workspace/qwen3_6_scripts/protocol.py "${VLLM_ROOT}/entrypoints/openai/protocol.py" 2>/dev/null && echo '[runtime] protocol.py redeployed' || echo '[runtime] protocol.py redeploy skipped';
-    - -tp
+
-    - '4'
+        cp /workspace/qwen3_6_scripts/serving_chat.py "${VLLM_ROOT}/entrypoints/openai/serving_chat.py" 2>/dev/null && echo '[runtime] serving_chat.py redeployed' || echo '[runtime] serving_chat.py redeploy skipped';
-    - --max-num-seqs
+
-    - '2'
+        find "${VLLM_ROOT}" -name '*.pyc' -path '*/openai/*' -delete 2>/dev/null;
-    - --disable-log-requests
+
-    - --disable-frontend-multiprocessing
+        exec python3 -m vllm.entrypoints.openai.api_server
-    - --max-num-batched-tokens
+
-    - '4096'
+        --model /model
-    - --enable-chunked-prefill
+
-    - --max-seq-len-to-capture
+        --served-model-name llm
-    - '32768'
+
-    - --enable-auto-tool-choice
+        --max-model-len 131072
-    - --tool-call-parser
+
-    - qwen3_coder
+        --gpu-memory-utilization 0.92
-    - --reasoning-parser
+
-    - qwen3
+        --trust-remote-code
-    - --enable-prefix-caching
+
-    - --enforce-eager
+        -tp 4
-    - --dtype
+
-    - half
+        --max-num-seqs 2
+
+        --disable-log-requests
+
+        --disable-frontend-multiprocessing
+
+        --max-num-batched-tokens 4096
+
+        --enable-chunked-prefill
+
+        --max-seq-len-to-capture 32768
+
+        --enable-auto-tool-choice
+
+        --tool-call-parser qwen3_coder
+
+        --reasoning-parser qwen3
+
+        --enable-prefix-caching
+
+        --enforce-eager
+
+        --dtype half
+
 env:
+
     - name: VLLM_ENGINE_ITERATION_TIMEOUT_S
+
       value: '3600'
+
     # --- MoE kernel selection ---
+
     - name: BI100_MOE_COREX_DIRECT_ROUTED
+
       value: '1'
+
     - name: BI100_MOE_COREX_TOPK_SOFTMAX
+
       value: '1'
+
     # --- GDN kernel selection ---
+
     - name: BI100_GDN_COREX_PACKED_DECODE
+
       value: '1'
+
     # --- Hybrid KV/GDN cache ---
+
     - name: BI100_HYBRID_KV_ACCOUNTING
+
       value: full_attention
+
     - name: BI100_GDN_CACHE_POLICY
+
       value: admission64
+
     - name: BI100_GDN_RESTORE_MODE
+
       value: hybrid64
+
     # --- Image fetch timeout (container network) ---
+
     - name: VLLM_IMAGE_FETCH_TIMEOUT
+
       value: '10'

qwen3_6_scripts/serving_chat.py

@@ -118,25 +118,19 @@ def _sequential_greedy_fanout_count(
     request: ChatCompletionRequest,
     max_num_seqs: int,
 ) -> int:
-    """Return the supported fan-out width, or zero.
+    """Return the supported deterministic fan-out width, or zero."""
-
-    When max_num_seqs is too small to schedule n choices in a single
-    batch, we sequentially issue n independent n=1 requests and merge
-    the results.  This works for any temperature and for both streaming
-    and non-streaming modes — the only hard exclusions are beam search
-    (which requires internal cross-sequence scoring) and best_of
-    (which implies server-side ranking over >n candidates).
-    """
     n = request.n if request.n is not None else 1
-    if n <= max_num_seqs:
+    if (
-        return 0                       # vLLM can handle natively
+        max_num_seqs == 1
-    if n > 16:
+        and n == 2
-        return 0                       # sanity cap
+        and request.temperature == 0
-    if request.use_beam_search:
+        and not request.stream
-        return 0                       # beam search cannot be split
+        and not request.use_beam_search
-    if request.best_of is not None:
+        and request.best_of is None
-        return 0                       # best_of needs cross-comparison
+        and request.prompt_logprobs is None
-    return n
+    ):
+        return n
+    return 0
 
 
 def _merge_sequential_chat_responses(
@@ -290,9 +284,10 @@ class OpenAIServingChat(OpenAIServing):
         if self.engine_client.errored:
             raise self.engine_client.dead_error
 
-        # When max_num_seqs is too small for n choices, sequentially execute
+        # The fixed competition command uses max_num_seqs=1. Native vLLM
-        # n independent n=1 requests and merge.  Works for any temperature,
+        # cannot schedule n=2 in that configuration and also rejects greedy
-        # stream or non-stream.
+        # n>1. Two greedy choices are identical by definition, so execute two
+        # isolated n=1 requests and merge only this exact deterministic shape.
         if request.n is not None and request.n > 1:
             scheduler_config = await self.engine_client.get_scheduler_config()
             max_num_seqs = scheduler_config.max_num_seqs
@@ -300,17 +295,8 @@ class OpenAIServingChat(OpenAIServing):
                 fanout_count = _sequential_greedy_fanout_count(
                     request, max_num_seqs)
                 if fanout_count:
-                    # Force non-streaming for child requests; if the original
+                    return await self._create_sequential_greedy_fanout(
-                    # request was streaming, wrap the merged result afterwards.
+                        request, raw_request, fanout_count)
-                    was_stream = request.stream
-                    fanout_request = request.model_copy(
-                        deep=True, update={"stream": False})
-                    result = await self._create_sequential_greedy_fanout(
-                        fanout_request, raw_request, fanout_count)
-                    if was_stream and isinstance(
-                            result, ChatCompletionResponse):
-                        return self._fanout_to_stream(result)
-                    return result
                 return self.create_error_response(
                     f"n={request.n} exceeds max_num_seqs={max_num_seqs}. "
                     f"Use n<={max_num_seqs} or omit n.")
@@ -535,39 +521,6 @@ class OpenAIServingChat(OpenAIServing):
         )
         return response
 
-    @staticmethod
-    async def _fanout_to_stream(
-        response: ChatCompletionResponse,
-    ) -> AsyncGenerator[str, None]:
-        """Wrap a complete ChatCompletionResponse as an SSE stream.
-
-        Used when n>1 fan-out was requested with stream=True.  The child
-        requests ran non-streaming; we emit one chunk per choice containing
-        the full text, then a final [DONE].
-        """
-        for choice in response.choices:
-            delta = DeltaMessage(
-                role="assistant",
-                content=getattr(choice.message, "content", None),
-            )
-            chunk = ChatCompletionStreamResponse(
-                id=response.id,
-                created=response.created,
-                model=response.model,
-                choices=[
-                    ChatCompletionResponseStreamChoice(
-                        index=choice.index,
-                        delta=delta,
-                        finish_reason=choice.finish_reason,
-                        stop_reason=choice.stop_reason,
-                    )
-                ],
-                usage=response.usage,
-            )
-            data = chunk.model_dump_json(exclude_unset=True)
-            yield f"data: {data}\n\n"
-        yield "data: [DONE]\n\n"
-
     def get_chat_request_role(self, request: ChatCompletionRequest) -> str:
         if request.add_generation_prompt:
             return self.response_role
@@ -1405,4 +1358,4 @@ class OpenAIServingChat(OpenAIServing):
             and delta_message.tool_calls and delta_message.tool_calls[0]
             and delta_message.tool_calls[0].function
             and delta_message.tool_calls[0].function.arguments is not None
-        )
+        )