Add reasoning parser mechanism + qwen3 parser + bugfixes

qwen3_6_scripts/reasoning/qwen3_reasoning_parser.py

@@ -0,0 +1,108 @@
+"""
+Reasoning parser for Qwen3 / Qwen3.5 / Qwen3.6 model family.
+Adapted from vllm-original/vllm/reasoning/qwen3_reasoning_parser.py.
+
+The model uses <think>...</think> to wrap chain-of-thought output.
+For Qwen3.5+ the chat template injects <think> into the prompt, so only
+</think> appears in the generated tokens; older templates generate <think>
+themselves.  Both styles are handled.
+"""
+
+from typing import Optional, Sequence, Any
+
+from vllm.reasoning.abs_reasoning_parsers import (
+    BaseThinkingReasoningParser,
+    ReasoningParserManager,
+)
+
+
+class Qwen3ReasoningParser(BaseThinkingReasoningParser):
+
+    def __init__(self, tokenizer: Any, *args, **kwargs):
+        super().__init__(tokenizer, *args, **kwargs)
+        chat_kwargs = kwargs.get("chat_template_kwargs", {}) or {}
+        self.thinking_enabled = chat_kwargs.get("enable_thinking", True)
+
+    @property
+    def start_token(self) -> str:
+        return "<think>"
+
+    @property
+    def end_token(self) -> str:
+        return "</think>"
+
+    def extract_reasoning(
+        self, model_output: str, request: Any
+    ) -> "tuple[Optional[str], Optional[str]]":
+        # Strip <think> if the model generated it (old template / edge case).
+        parts = model_output.partition(self.start_token)
+        model_output = parts[2] if parts[1] else parts[0]
+
+        if self.end_token not in model_output:
+            if not self.thinking_enabled:
+                return None, model_output
+            # Thinking enabled but output truncated before </think>.
+            return model_output, None
+
+        reasoning, _, content = model_output.partition(self.end_token)
+        return reasoning, content or None
+
+    def count_reasoning_tokens(self, token_ids: Sequence[int]) -> int:
+        token_ids = list(token_ids)
+        if self.start_token_id in token_ids:
+            # Old-style template: model generates <think> itself.
+            # Use depth-counting from the base class.
+            return super().count_reasoning_tokens(token_ids)
+        elif self.end_token_id in token_ids:
+            # New-style template (Qwen3.5+): <think> is injected into the
+            # prompt, so output starts already inside the thinking block.
+            # Every token before </think> is a reasoning token.
+            return token_ids.index(self.end_token_id)
+        else:
+            # No </think> in output: either truncated (all reasoning)
+            # or thinking disabled (none).
+            return len(token_ids) if self.thinking_enabled else 0
+
+    def extract_reasoning_streaming(
+        self,
+        previous_text: str,
+        current_text: str,
+        delta_text: str,
+        previous_token_ids: Sequence[int],
+        current_token_ids: Sequence[int],
+        delta_token_ids: Sequence[int],
+    ):
+        from vllm.entrypoints.openai.protocol import DeltaMessage
+
+        if not self.thinking_enabled:
+            return DeltaMessage(content=delta_text) if delta_text else None
+
+        # Strip <think> from delta if the model generates it itself.
+        if self.start_token_id in delta_token_ids:
+            start_idx = delta_text.find(self.start_token)
+            if start_idx >= 0:
+                delta_text = delta_text[start_idx + len(self.start_token):]
+
+        if self.end_token_id in delta_token_ids:
+            end_idx = delta_text.find(self.end_token)
+            if end_idx >= 0:
+                reasoning = delta_text[:end_idx]
+                content = delta_text[end_idx + len(self.end_token):]
+                if not reasoning and not content:
+                    return None
+                return DeltaMessage(
+                    reasoning_content=reasoning or None,
+                    content=content or None,
+                )
+            return None
+
+        if not delta_text:
+            return None
+        elif self.end_token_id in previous_token_ids:
+            return DeltaMessage(content=delta_text)
+        else:
+            return DeltaMessage(reasoning_content=delta_text)
+
+
+# Register immediately when this module is imported.
+ReasoningParserManager.register_module("qwen3", Qwen3ReasoningParser)