[Frontend] Support reasoning content for deepseek r1 (#12473)

Signed-off-by: Ce Gao <cegao@tensorchord.ai>
Co-authored-by: Rafael Vasquez <rafvasq21@gmail.com>
Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>
Co-authored-by: Michael Goin <mgoin@redhat.com>

tests/entrypoints/openai/reasoning_parsers/utils.py

@@ -0,0 +1,93 @@
+from typing import List, Optional, Tuple, Union
+
+from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
+                                              DeltaMessage)
+from vllm.entrypoints.openai.reasoning_parsers import ReasoningParser
+
+
+class StreamingReasoningReconstructor:
+
+    def __init__(self):
+        self.reasoning_content = None
+        self.other_content = None
+
+    def append_delta(self, delta: DeltaMessage):
+        # content and the reasoning content should not be present
+        # at the same time
+        assert delta.content is None or delta.reasoning_content is None, (
+            "Both content and reasoning content are present in the "
+            "delta message")
+        if delta.content is not None:
+            if self.other_content is None:
+                self.other_content = delta.content
+            else:
+                self.other_content += delta.content
+        else:
+            if self.reasoning_content is None:
+                self.reasoning_content = delta.reasoning_content
+            else:
+                self.reasoning_content += delta.reasoning_content
+
+
+def run_reasoning_extraction(
+    reasoning_parser: ReasoningParser,
+    model_output: List[str],
+    request: Union[ChatCompletionRequest, None] = None,
+    streaming: bool = False,
+) -> Tuple[Optional[str], Optional[str]]:
+    if streaming:
+        reconstructor = run_reasoning_extraction_streaming(
+            reasoning_parser,
+            model_output,
+            request,
+        )
+        return (
+            reconstructor.reasoning_content,
+            reconstructor.other_content or None,
+        )
+    else:
+        reasoning, content = run_reasoning_extraction_nonstreaming(
+            reasoning_parser, model_output, request)
+        return reasoning, content
+
+
+def run_reasoning_extraction_nonstreaming(
+    reasoning_parser: ReasoningParser,
+    model_output: List[str],
+    request: Union[ChatCompletionRequest, None] = None,
+) -> Tuple[Optional[str], Optional[str]]:
+    request = request or ChatCompletionRequest(messages=[], model="test-model")
+    return reasoning_parser.extract_reasoning_content(
+        model_output=''.join(model_output), request=request)
+
+
+def run_reasoning_extraction_streaming(
+    reasoning_parser: ReasoningParser,
+    model_deltas: List[str],
+    request: Union[ChatCompletionRequest, None] = None,
+) -> StreamingReasoningReconstructor:
+    request = request or ChatCompletionRequest(messages=[], model="test-model")
+    reconstructor = StreamingReasoningReconstructor()
+    previous_text = ""
+    previous_tokens: List[int] = []
+    for delta in model_deltas:
+        token_delta = [
+            reasoning_parser.vocab.get(token)
+            for token in reasoning_parser.model_tokenizer.tokenize(delta)
+            if token in reasoning_parser.vocab
+        ]
+        current_text = previous_text + delta
+        current_tokens = previous_tokens + token_delta
+        delta_message = reasoning_parser.extract_reasoning_content_streaming(
+            previous_text,
+            current_text,
+            delta,
+            previous_tokens,
+            current_tokens,
+            token_delta,
+        )
+        if delta_message is not None:
+            reconstructor.append_delta(delta_message)
+        previous_text = current_text
+        previous_tokens = current_tokens
+    return reconstructor