Improve reasoning and tool-call parsers

[lvhan028]

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Modification

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[Copilot]

Pull request overview

This PR refactors streaming reasoning/tool-call parsing by centralizing “previous/current text + token ids” into a shared, request-attached streaming state and updates the OpenAI API server + parsers to use the new streaming interfaces.

Changes:

• Introduces StreamingParserState + get_streaming_state(request) and a shared ThinkingReasoningParser base for <think>...</think>-style models.
• Simplifies streaming parser method signatures (tool + reasoning) to accept deltas only and read previous/current context from request-attached state.
• Renames/reshuffles parser modules (*_tool_parser.py, qwen_reasoning_parser.py) and updates imports accordingly.

Reviewed changes

Copilot reviewed 15 out of 15 changed files in this pull request and generated 6 comments.

Show a summary per file

File	Description
tests/test_lmdeploy/test_qwen3coder_parser.py	Updates tool parser import path (but streaming call sites still need updating to new API).
tests/test_lmdeploy/test_qwen3_parser.py	Updates reasoning/tool parser import paths (but streaming call sites still need updating to new API).
lmdeploy/serve/openai/tool_parser/tool_parser.py	Updates abstract streaming tool parser signature + docs to rely on request-attached streaming state.
lmdeploy/serve/openai/tool_parser/qwen3coder_tool_parser.py	Adapts Qwen3Coder streaming parsing to read current_text via get_streaming_state.
lmdeploy/serve/openai/tool_parser/qwen3_tool_parser.py	Adapts Qwen3 streaming parsing to read current_text via get_streaming_state.
lmdeploy/serve/openai/tool_parser/qwen2d5_tool_parser.py	Adapts streaming parsing to shared state (but still uses parser-instance state).
lmdeploy/serve/openai/tool_parser/llama3_tool_parser.py	Adapts streaming parsing to shared state (but still uses parser-instance state).
lmdeploy/serve/openai/tool_parser/internlm2_tool_parser.py	Adapts streaming parsing to shared state (but still uses parser-instance state).
lmdeploy/serve/openai/tool_parser/init.py	Updates exports to new *_tool_parser.py module names.
lmdeploy/serve/openai/reasoning_parser/reasoning_parser.py	Adds shared streaming state + ThinkingReasoningParser base; updates reasoning parser streaming API.
lmdeploy/serve/openai/reasoning_parser/qwen_reasoning_parser.py	New Qwen QwQ / Intern-S1 reasoning parser based on ThinkingReasoningParser.
lmdeploy/serve/openai/reasoning_parser/qwen_qwq_reasoning_parser.py	Removes the prior Qwen QwQ reasoning parser implementation.
lmdeploy/serve/openai/reasoning_parser/deepseek_r1_reasoning_parser.py	Refactors DeepSeek-R1 reasoning parser onto ThinkingReasoningParser.
lmdeploy/serve/openai/reasoning_parser/init.py	Updates exports to include new shared state utilities + new module path.
lmdeploy/serve/openai/api_server.py	Uses StreamingParserState in the streaming loop and calls updated parser streaming APIs.

Comments suppressed due to low confidence (3)

lmdeploy/serve/openai/tool_parser/qwen2d5_tool_parser.py:52

• Qwen2d5ToolParser stores streaming parse state (self.position, self.current_tool_id, self.current_tool_name_sent, etc.) on the parser instance, but the server uses a single global parser instance across requests. This is not safe under concurrent streaming requests and can lead to mixed tool-call parsing. Please move per-request state to the request object (e.g., request._tool_parser_state) or another request-scoped structure.
  lmdeploy/serve/openai/tool_parser/llama3_tool_parser.py:83
• Llama3JsonToolParser relies on instance attributes (self.current_tool_id, self.current_tool_name_sent, self.prev_tool_call_arr, etc.) for streaming state. Since the API server stores a single global parser instance, concurrent streaming requests can race and corrupt this state. Please migrate the streaming state to be request-scoped (e.g., attach a parser-state object to request).
  lmdeploy/serve/openai/tool_parser/internlm2_tool_parser.py:56
• Internlm2ToolParser keeps streaming parse state (self.position, self.current_tool_id, self.current_tool_name_sent, etc.) on the parser instance, but VariableInterface.tool_parser is a single global instance shared across requests. With concurrent streaming requests, this state can interleave and corrupt parsing. Consider moving per-request state onto the request object (e.g., request._tool_parser_state) similar to Qwen3ToolParser, or into the shared StreamingParserState.

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[Copilot]

Docstring mentions overriding on_missing_start_tag, but the actual configurable attribute is on_missing_end_tag. Please fix the docstring to avoid confusing subclass authors.

Suggested change

	override `strip_newlines` and `on_missing_start_tag` to customize behavior.
	override `strip_newlines` and `on_missing_end_tag` to customize behavior.

[Copilot]

This test file still calls extract_tool_calls_streaming(...) / extract_reasoning_content_streaming(...) with the removed previous_text/current_text and previous_token_ids/current_token_ids parameters (see _chat_completion_v1 below). Update the test harness to match the new parser API (and to update/step the shared StreamingParserState via get_streaming_state(request) similarly to api_server.py).

[Copilot]

This test file still calls extract_tool_calls_streaming(...) / extract_reasoning_content_streaming(...) using the old signature with previous_text/current_text and token id args (see _chat_completion_v1 below). Update the test harness to the new streaming parser API and maintain the shared StreamingParserState on the request (as api_server.py now does).

[Copilot]

StreamingParserState uses mutable list defaults (previous_token_ids / current_token_ids). In a dataclass these lists are shared across all instances, which can leak token ids between requests. Use field(default_factory=list) for these fields.

[Copilot]

StreamingParserState.step() assigns previous_token_ids = current_token_ids, which aliases the same list. Because update() mutates current_token_ids in place, previous_token_ids will also change, breaking any logic that compares previous vs current tokens (and can cause incorrect detection of start/end tags). Snapshot via .copy() (or store lengths / use an immutable sequence).

[Copilot]

The return type annotation for extract_reasoning_content is tuple[str, str], but the docstring and implementations return None for either element (e.g., ThinkingReasoningParser.extract_reasoning_content returns (None, model_output) and vice versa). Update the annotation to allow None (e.g., tuple[str | None, str | None]) to match behavior.