[router][grpc] Support E2E non-stream chat completions (#10980)

python/sglang/srt/entrypoints/grpc_request_manager.py

@@ -13,7 +13,7 @@ import sys
 import threading
 import time
 import uuid
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, AsyncGenerator, Dict, List, Optional, Union
 
 import grpc
 import zmq
@@ -156,7 +156,7 @@ class GrpcRequestManager:
         obj: TokenizedGenerateReqInput,
         request_id: Optional[str] = None,
         grpc_context: Optional[grpc.aio.ServicerContext] = None,
-    ):
+    ) -> AsyncGenerator[Union[Dict, List[Dict]], None]:
         """
         Submit a generation request to the scheduler with n>1 parallel sampling support.
 

python/sglang/srt/entrypoints/grpc_server.py

@@ -321,14 +321,14 @@ class SGLangSchedulerServicer(sglang_scheduler_pb2_grpc.SglangSchedulerServicer)
             logger.info(f"Sending health check request to request manager...")
 
             # Submit and wait for response
-            output_queue = await self.request_manager.generate_request(
+            output_generator = self.request_manager.generate_request(
                 health_request, request_id=rid
             )
 
             try:
-                # Wait for response with configurable timeout
+                # Get first response with timeout
                 response = await asyncio.wait_for(
-                    output_queue.get(), timeout=HEALTH_CHECK_TIMEOUT
+                    output_generator.__anext__(), timeout=HEALTH_CHECK_TIMEOUT
                 )
 
                 # Clean up
@@ -492,13 +492,32 @@ class SGLangSchedulerServicer(sglang_scheduler_pb2_grpc.SglangSchedulerServicer)
     ) -> sglang_scheduler_pb2.GenerateResponse:
         """Create a completion response."""
 
-        # Determine finish reason
+        # Extract meta info and finish reason details
-        finish_reason = sglang_scheduler_pb2.GenerateComplete.STOP
         meta_info = output.get("meta_info", {})
-        if meta_info.get("finish_reason") == "length":
+        finish_reason_data = meta_info.get("finish_reason")
-            finish_reason = sglang_scheduler_pb2.GenerateComplete.LENGTH
+
-        elif meta_info.get("finish_reason") == "eos_token":
+        # Determine finish reason, default is stop
-            finish_reason = sglang_scheduler_pb2.GenerateComplete.EOS_TOKEN
+        finish_reason = "stop"
+        if finish_reason_data:
+            if isinstance(finish_reason_data, dict):
+                finish_reason_type = finish_reason_data.get("type")
+            else:
+                # Handle legacy string format
+                finish_reason_type = finish_reason_data
+
+            if finish_reason_type == "length":
+                finish_reason = "length"
+            elif finish_reason_type == "abort":
+                finish_reason = "abort"
+
+        # Extract matched_stop information
+        matched_stop_kwargs = {}
+        if isinstance(finish_reason_data, dict) and "matched" in finish_reason_data:
+            matched = finish_reason_data["matched"]
+            if isinstance(matched, int):
+                matched_stop_kwargs["matched_token_id"] = matched
+            elif isinstance(matched, str):
+                matched_stop_kwargs["matched_stop_str"] = matched
 
         return sglang_scheduler_pb2.GenerateResponse(
             request_id=request_id,
@@ -510,6 +529,7 @@ class SGLangSchedulerServicer(sglang_scheduler_pb2_grpc.SglangSchedulerServicer)
                     "completion_tokens", len(output.get("token_ids", []))
                 ),
                 cached_tokens=meta_info.get("cached_tokens", 0),
+                **matched_stop_kwargs,
             ),
         )
 

python/sglang/srt/grpc/sglang_scheduler.proto

@@ -185,20 +185,8 @@ message GenerateComplete {
   // Final output
   repeated uint32 output_ids = 1;
 
-  // Finish reason
+  // Finish reason as OpenAI-compatible string ("stop", "length", "abort")
-  enum FinishReason {
+  string finish_reason = 2;
-    // The model generated a stop sequence.
-    STOP = 0;
-    // The model reached the maximum generation length.
-    LENGTH = 1;
-    // The model generated an end-of-sequence (EOS) token.
-    EOS_TOKEN = 2;
-    // The model generated a user-provided stop string.
-    STOP_STR = 3;
-    // The request was aborted by the user or system.
-    ABORT = 4;
-  }
-  FinishReason finish_reason = 2;
 
   // Token usage counts
   int32 prompt_tokens = 3;
@@ -210,6 +198,12 @@ message GenerateComplete {
 
   // All hidden states if requested
   repeated HiddenStates all_hidden_states = 7;
+
+  // Matched stop information (for stop sequences)
+  oneof matched_stop {
+    uint32 matched_token_id = 8;
+    string matched_stop_str = 9;
+  }
 }
 
 message GenerateError {

python/sglang/srt/grpc/sglang_scheduler_pb2.pyi

@@ -3,7 +3,6 @@ import datetime
 from google.protobuf import timestamp_pb2 as _timestamp_pb2
 from google.protobuf import struct_pb2 as _struct_pb2
 from google.protobuf.internal import containers as _containers
-from google.protobuf.internal import enum_type_wrapper as _enum_type_wrapper
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message
 from collections.abc import Iterable as _Iterable, Mapping as _Mapping
@@ -179,19 +178,7 @@ class GenerateStreamChunk(_message.Message):
     def __init__(self, token_ids: _Optional[_Iterable[int]] = ..., prompt_tokens: _Optional[int] = ..., completion_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., logprobs: _Optional[_Union[LogProbs, _Mapping]] = ..., hidden_states: _Optional[_Iterable[float]] = ...) -> None: ...
 
 class GenerateComplete(_message.Message):
-    __slots__ = ("output_ids", "finish_reason", "prompt_tokens", "completion_tokens", "cached_tokens", "all_logprobs", "all_hidden_states")
+    __slots__ = ("output_ids", "finish_reason", "prompt_tokens", "completion_tokens", "cached_tokens", "all_logprobs", "all_hidden_states", "matched_token_id", "matched_stop_str")
-    class FinishReason(int, metaclass=_enum_type_wrapper.EnumTypeWrapper):
-        __slots__ = ()
-        STOP: _ClassVar[GenerateComplete.FinishReason]
-        LENGTH: _ClassVar[GenerateComplete.FinishReason]
-        EOS_TOKEN: _ClassVar[GenerateComplete.FinishReason]
-        STOP_STR: _ClassVar[GenerateComplete.FinishReason]
-        ABORT: _ClassVar[GenerateComplete.FinishReason]
-    STOP: GenerateComplete.FinishReason
-    LENGTH: GenerateComplete.FinishReason
-    EOS_TOKEN: GenerateComplete.FinishReason
-    STOP_STR: GenerateComplete.FinishReason
-    ABORT: GenerateComplete.FinishReason
     OUTPUT_IDS_FIELD_NUMBER: _ClassVar[int]
     FINISH_REASON_FIELD_NUMBER: _ClassVar[int]
     PROMPT_TOKENS_FIELD_NUMBER: _ClassVar[int]
@@ -199,14 +186,18 @@ class GenerateComplete(_message.Message):
     CACHED_TOKENS_FIELD_NUMBER: _ClassVar[int]
     ALL_LOGPROBS_FIELD_NUMBER: _ClassVar[int]
     ALL_HIDDEN_STATES_FIELD_NUMBER: _ClassVar[int]
+    MATCHED_TOKEN_ID_FIELD_NUMBER: _ClassVar[int]
+    MATCHED_STOP_STR_FIELD_NUMBER: _ClassVar[int]
     output_ids: _containers.RepeatedScalarFieldContainer[int]
-    finish_reason: GenerateComplete.FinishReason
+    finish_reason: str
     prompt_tokens: int
     completion_tokens: int
     cached_tokens: int
     all_logprobs: _containers.RepeatedCompositeFieldContainer[LogProbs]
     all_hidden_states: _containers.RepeatedCompositeFieldContainer[HiddenStates]
-    def __init__(self, output_ids: _Optional[_Iterable[int]] = ..., finish_reason: _Optional[_Union[GenerateComplete.FinishReason, str]] = ..., prompt_tokens: _Optional[int] = ..., completion_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., all_logprobs: _Optional[_Iterable[_Union[LogProbs, _Mapping]]] = ..., all_hidden_states: _Optional[_Iterable[_Union[HiddenStates, _Mapping]]] = ...) -> None: ...
+    matched_token_id: int
+    matched_stop_str: str
+    def __init__(self, output_ids: _Optional[_Iterable[int]] = ..., finish_reason: _Optional[str] = ..., prompt_tokens: _Optional[int] = ..., completion_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., all_logprobs: _Optional[_Iterable[_Union[LogProbs, _Mapping]]] = ..., all_hidden_states: _Optional[_Iterable[_Union[HiddenStates, _Mapping]]] = ..., matched_token_id: _Optional[int] = ..., matched_stop_str: _Optional[str] = ...) -> None: ...
 
 class GenerateError(_message.Message):
     __slots__ = ("message", "http_status_code", "details")

sgl-router/src/proto/sglang_scheduler.proto

@@ -185,20 +185,8 @@ message GenerateComplete {
   // Final output
   repeated uint32 output_ids = 1;
 
-  // Finish reason
+  // Finish reason as OpenAI-compatible string ("stop", "length", "abort")
-  enum FinishReason {
+  string finish_reason = 2;
-    // The model generated a stop sequence.
-    STOP = 0;
-    // The model reached the maximum generation length.
-    LENGTH = 1;
-    // The model generated an end-of-sequence (EOS) token.
-    EOS_TOKEN = 2;
-    // The model generated a user-provided stop string.
-    STOP_STR = 3;
-    // The request was aborted by the user or system.
-    ABORT = 4;
-  }
-  FinishReason finish_reason = 2;
 
   // Token usage counts
   int32 prompt_tokens = 3;
@@ -210,6 +198,12 @@ message GenerateComplete {
 
   // All hidden states if requested
   repeated HiddenStates all_hidden_states = 7;
+
+  // Matched stop information (for stop sequences)
+  oneof matched_stop {
+    uint32 matched_token_id = 8;
+    string matched_stop_str = 9;
+  }
 }
 
 message GenerateError {

sgl-router/src/protocols/spec.rs

@@ -423,10 +423,25 @@ pub struct ChatCompletionResponse {
     pub system_fingerprint: Option<String>,
 }
 
+/// Response message structure for ChatCompletionResponse (different from request ChatMessage)
+#[derive(Debug, Clone, Deserialize, Serialize)]
+pub struct ChatCompletionMessage {
+    pub role: String, // Always "assistant" for responses
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub content: Option<String>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub tool_calls: Option<Vec<ToolCall>>,
+    /// Reasoning content for O1-style models (SGLang extension)
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub reasoning_content: Option<String>,
+    // Note: function_call is deprecated and not included
+    // Note: refusal, annotations, audio are not added yet
+}
+
 #[derive(Debug, Clone, Deserialize, Serialize)]
 pub struct ChatChoice {
     pub index: u32,
-    pub message: ChatMessage,
+    pub message: ChatCompletionMessage,
     #[serde(skip_serializing_if = "Option::is_none")]
     pub logprobs: Option<ChatLogProbs>,
     pub finish_reason: Option<String>, // "stop", "length", "tool_calls", "content_filter", "function_call"

sgl-router/src/routers/grpc/router.rs

@@ -8,6 +8,7 @@ use axum::{
     extract::Request,
     http::{HeaderMap, StatusCode},
     response::{IntoResponse, Response},
+    Json,
 };
 use tracing::{debug, error, info, warn};
 
@@ -18,8 +19,9 @@ use crate::metrics::RouterMetrics;
 use crate::policies::PolicyRegistry;
 use crate::protocols::spec::ChatMessage;
 use crate::protocols::spec::{
-    ChatCompletionRequest, CompletionRequest, EmbeddingRequest, GenerateRequest, RerankRequest,
+    ChatChoice, ChatCompletionMessage, ChatCompletionRequest, ChatCompletionResponse,
-    ResponsesGetParams, ResponsesRequest, StringOrArray, Tool, ToolChoice,
+    CompletionRequest, EmbeddingRequest, GenerateRequest, RerankRequest, ResponsesGetParams,
+    ResponsesRequest, StringOrArray, Tool, ToolChoice, Usage,
 };
 use crate::reasoning_parser::ParserFactory;
 use crate::routers::RouterTrait;
@@ -30,6 +32,7 @@ use crate::tokenizer::traits::Tokenizer;
 use crate::tokenizer::HuggingFaceTokenizer;
 use crate::tool_parser::ParserRegistry;
 use serde_json::Value;
+use std::time::{SystemTime, UNIX_EPOCH};
 use tokio_stream::StreamExt;
 use uuid::Uuid;
 
@@ -648,35 +651,98 @@ impl GrpcRouter {
             Err(e) => return fail_fmt("Failed to start generation: ", &e),
         };
 
-        // Get the single Complete response
+        // Collect all responses (for n>1 support)
-        let gen_response = match stream.next().await {
+        let mut all_responses = Vec::new();
-            Some(Ok(r)) => r,
+        while let Some(response) = stream.next().await {
-            Some(Err(e)) => return fail_fmt("Failed to get GenerateResponse: ", &e),
+            match response {
-            None => return fail_str("No response from server"),
+                Ok(gen_response) => match gen_response.response {
+                    Some(proto::generate_response::Response::Complete(complete)) => {
+                        all_responses.push(complete);
+                    }
+                    Some(proto::generate_response::Response::Error(err)) => {
+                        error!("Generation failed for one choice: {}", err.message);
+                        return (
+                            StatusCode::INTERNAL_SERVER_ERROR,
+                            format!("Generation failed: {}", err.message),
+                        )
+                            .into_response();
+                    }
+                    Some(proto::generate_response::Response::Chunk(_)) => {
+                        return fail_str("Unexpected chunk response for non-streaming request")
+                    }
+                    None => return fail_str("Empty response from server"),
+                },
+                Err(e) => return fail_fmt("Failed to get GenerateResponse: ", &e),
+            }
+        }
+
+        if all_responses.is_empty() {
+            return fail_str("No responses from server");
+        }
+
+        // Process each response into a ChatChoice
+        let mut choices = Vec::new();
+        for (index, complete) in all_responses.iter().enumerate() {
+            match self
+                .process_single_choice(complete, index, original_request, &mut stop_decoder)
+                .await
+            {
+                Ok(choice) => choices.push(choice),
+                Err(e) => {
+                    error!("Failed to process choice {}: {}", index, e);
+                    return (
+                        StatusCode::INTERNAL_SERVER_ERROR,
+                        format!("Failed to process choice {}: {}", index, e),
+                    )
+                        .into_response();
+                }
+            }
+        }
+
+        // Aggregate usage information from all responses
+        let total_prompt_tokens: u32 = all_responses.iter().map(|r| r.prompt_tokens as u32).sum();
+        let total_completion_tokens: u32 = all_responses
+            .iter()
+            .map(|r| r.completion_tokens as u32)
+            .sum();
+        let usage = Usage {
+            prompt_tokens: total_prompt_tokens,
+            completion_tokens: total_completion_tokens,
+            total_tokens: total_prompt_tokens + total_completion_tokens,
+            completion_tokens_details: None,
         };
 
-        // Extract the expected variant early
+        // Build final ChatCompletionResponse
-        let complete = match gen_response.response {
+        let response = ChatCompletionResponse {
-            Some(proto::generate_response::Response::Complete(c)) => c,
+            id: format!("chatcmpl-{}", Uuid::new_v4()),
-            Some(proto::generate_response::Response::Error(err)) => {
+            object: "chat.completion".to_string(),
-                error!("Generation failed: {}", err.message);
+            created: SystemTime::now()
-                return (
+                .duration_since(UNIX_EPOCH)
-                    StatusCode::INTERNAL_SERVER_ERROR,
+                .unwrap_or_default()
-                    format!("Generation failed: {}", err.message),
+                .as_secs(),
-                )
+            model: original_request.model.clone(),
-                    .into_response();
+            choices,
-            }
+            usage: Some(usage),
-            Some(proto::generate_response::Response::Chunk(_)) => {
+            system_fingerprint: None,
-                return fail_str("Unexpected chunk response for non-streaming request")
-            }
-            None => return fail_str("Empty response from server"),
         };
 
+        // Serialize and return JSON response
+        Json(response).into_response()
+    }
+
+    /// Process a single GenerateComplete response into a ChatChoice
+    async fn process_single_choice(
+        &self,
+        complete: &proto::GenerateComplete,
+        index: usize,
+        original_request: &ChatCompletionRequest,
+        stop_decoder: &mut crate::tokenizer::stop::StopSequenceDecoder,
+    ) -> Result<ChatChoice, String> {
+        stop_decoder.reset();
         // Decode tokens
-        let outputs = match stop_decoder.process_tokens(&complete.output_ids) {
+        let outputs = stop_decoder
-            Ok(o) => o,
+            .process_tokens(&complete.output_ids)
-            Err(e) => return fail_fmt("Failed to process tokens: ", &e),
+            .map_err(|e| format!("Failed to process tokens: {}", e))?;
-        };
 
         // Accumulate text with early breaks
         let mut final_text = String::new();
@@ -697,8 +763,119 @@ impl GrpcRouter {
             final_text.push_str(&t);
         }
 
-        // TODO: Create proper OpenAI-compatible response
+        // Step 1: Handle reasoning content parsing
-        (StatusCode::OK, format!("Final text: {}", final_text)).into_response()
+        let mut reasoning_text: Option<String> = None;
+        let mut processed_text = final_text;
+
+        // Check if reasoning parsing is enabled and separate_reasoning is requested
+        if original_request.separate_reasoning {
+            if let Ok(mut parser) = self
+                .reasoning_parser_factory
+                .create(&original_request.model)
+            {
+                match parser.detect_and_parse_reasoning(&processed_text) {
+                    Ok(result) => {
+                        if !result.reasoning_text.is_empty() {
+                            reasoning_text = Some(result.reasoning_text);
+                        }
+                        processed_text = result.normal_text;
+                    }
+                    Err(e) => {
+                        return Err(format!("Reasoning parsing error: {}", e));
+                    }
+                }
+            }
+        }
+
+        // Step 2: Handle tool call parsing
+        let mut tool_calls: Option<Vec<crate::protocols::spec::ToolCall>> = None;
+
+        // Check if tool calls should be processed
+        let tool_choice_enabled = !matches!(
+            &original_request.tool_choice,
+            Some(ToolChoice::Value(
+                crate::protocols::spec::ToolChoiceValue::None
+            ))
+        );
+
+        if tool_choice_enabled && original_request.tools.is_some() {
+            if let Some(parser) = self
+                .tool_parser_registry
+                .get_parser(&original_request.model)
+            {
+                match parser.parse_complete(&processed_text).await {
+                    Ok(parsed_tool_calls) => {
+                        if !parsed_tool_calls.is_empty() {
+                            let spec_tool_calls = parsed_tool_calls
+                                .into_iter()
+                                .map(|tc| crate::protocols::spec::ToolCall {
+                                    id: tc.id,
+                                    tool_type: "function".to_string(),
+                                    function: crate::protocols::spec::FunctionCallResponse {
+                                        name: tc.function.name,
+                                        arguments: Some(
+                                            serde_json::to_string(&tc.function.arguments)
+                                                .unwrap_or_else(|_| "{}".to_string()),
+                                        ),
+                                    },
+                                })
+                                .collect();
+                            tool_calls = Some(spec_tool_calls);
+                            processed_text = String::new();
+                        }
+                    }
+                    Err(e) => {
+                        error!("Tool call parsing error: {}", e);
+                        // Continue without tool calls rather than failing
+                    }
+                }
+            }
+        }
+
+        // Step 3: Use finish reason directly from proto (already OpenAI-compatible string)
+        let finish_reason_str = &complete.finish_reason;
+
+        // Override finish reason if we have tool calls
+        let final_finish_reason_str = if tool_calls.is_some() {
+            "tool_calls"
+        } else {
+            finish_reason_str
+        };
+
+        // Extract matched_stop information from proto
+        let matched_stop = match &complete.matched_stop {
+            Some(proto::generate_complete::MatchedStop::MatchedTokenId(token_id)) => Some(
+                serde_json::Value::Number(serde_json::Number::from(*token_id)),
+            ),
+            Some(proto::generate_complete::MatchedStop::MatchedStopStr(stop_str)) => {
+                Some(serde_json::Value::String(stop_str.clone()))
+            }
+            None => None,
+        };
+
+        // Step 4: Build ChatCompletionMessage (proper response message type)
+        let chat_message = ChatCompletionMessage {
+            role: "assistant".to_string(),
+            content: if processed_text.is_empty() {
+                None
+            } else {
+                Some(processed_text)
+            },
+            tool_calls,
+            reasoning_content: reasoning_text,
+        };
+
+        // Step 5: Build ChatChoice
+        let choice = ChatChoice {
+            index: index as u32,
+            message: chat_message,
+            logprobs: None,
+            finish_reason: Some(final_finish_reason_str.to_string()),
+            matched_stop,
+            hidden_states: None,
+        };
+
+        Ok(choice)
     }
 }