feat(server): enable reasoning_effort on /v1/chat/completions

python/freetoken/server/api_models.py

@@ -77,6 +77,7 @@ class ChatCompletionRequest(BaseModel):
     presence_penalty: float = 0.0
     frequency_penalty: float = 0.0
     chat_template_kwargs: dict[str, Any] = Field(default_factory=dict)
+    reasoning_effort: str | None = None
     ignore_eos: bool = False
     tools: list[Tool] | None = None
     tool_choice: Literal["none", "auto", "required"] | ToolChoiceObject | None = None

python/freetoken/server/generation.py

@@ -317,6 +317,10 @@ def _make_reasoning_parser(spec: GenSpec, state: Any) -> ReasoningParser | None:
         # enable_thinking is explicitly false, so the model emits only the closing
         # </think>. Mirror that default here, else the chain-of-thought leaks into content.
         force_reasoning = (spec.chat_template_kwargs or {}).get("enable_thinking") is not False
+    elif parser_name == "glm":
+        # GLM's template honors enable_thinking (default on) even with tools; the
+        # generic fallback would force thinking and mislabel disabled output as reasoning.
+        force_reasoning = (spec.chat_template_kwargs or {}).get("enable_thinking") is not False
     elif parser_name == "gemma4":
         # Gemma4 defaults thinking off even when tools are present: its template injects an
         # empty thought channel before generation. Do not let Codex tool definitions make all

python/freetoken/server/model_meta.py

@@ -67,6 +67,32 @@ def think_toggle_kwargs(reasoning_parser: str | None, enabled: bool) -> dict:
     return think_chat_template_kwargs(reasoning_parser, gear)
 
 
+_THINKING_KWARG_KEYS = ("enable_thinking", "thinking", "thinking_mode", "reasoning_effort")
+_DISABLE_EFFORTS = ("none", "off")
+
+
+def effort_toggle_kwargs(
+    reasoning_parser: str | None,
+    effort: str | None,
+    chat_template_kwargs: dict | None,
+) -> dict:
+    """Fold a protocol-level reasoning-effort request into the template kwargs.
+    An explicit thinking-related key wins wholesale; unrelated extras ride along.
+    Effort "none"/"off" (case-insensitive) disables thinking; any other or absent
+    effort enables it, forwarded for templates that grade it (gpt-oss)."""
+    ctk = dict(chat_template_kwargs or {})
+    if any(key in ctk for key in _THINKING_KWARG_KEYS):
+        return ctk
+    if isinstance(effort, str):
+        effort = effort.strip().lower()
+    disabled = effort in _DISABLE_EFFORTS
+    mapped = dict(think_toggle_kwargs(reasoning_parser, not disabled))
+    if effort and not disabled:
+        mapped.setdefault("reasoning_effort", effort)
+    mapped.update(ctk)
+    return mapped
+
+
 def moe_total_experts(config: Any) -> int:
     """Total routed-expert slots the model has: experts per layer x MoE layers. Matches the
     engine's own basis (``Engine._resolve_auto_moe_cache_size``), so a residency rate derived

python/freetoken/server/openai_api.py

@@ -37,8 +37,17 @@
 )
 
 
-def chat_request_to_genspec(req: ChatCompletionRequest, model_sampling: dict[str, Any]) -> GenSpec:
+def chat_request_to_genspec(
+    req: ChatCompletionRequest,
+    model_sampling: dict[str, Any],
+    reasoning_parser: str | None = None,
+) -> GenSpec:
     """OpenAI ChatCompletionRequest -> GenSpec (the OpenAI 'to_sampling_params')."""
+    from .model_meta import effort_toggle_kwargs
+
+    ctk = req.chat_template_kwargs
+    if req.reasoning_effort:
+        ctk = effort_toggle_kwargs(reasoning_parser, req.reasoning_effort, ctk)
     return GenSpec(
         messages=render_messages([m.model_dump(exclude_none=True) for m in req.messages]),
         sampling_params=resolve_sampling(
@@ -50,7 +59,7 @@ def chat_request_to_genspec(req: ChatCompletionRequest, model_sampling: dict[str
             model_sampling=model_sampling,
             stop=req.stop,
         ),
-        chat_template_kwargs=req.chat_template_kwargs,
+        chat_template_kwargs=ctk,
         template_tools=_tools_for_template(req),
         parser_tools=(_all_tool_dicts(req.tools) if _should_parse_tools(req) else None),
     )
@@ -133,7 +142,9 @@ async def handle_chat_completion(
         return create_error_response("Only n=1 is supported", param="n")
 
     try:
-        spec = chat_request_to_genspec(req, model_sampling)
+        spec = chat_request_to_genspec(
+            req, model_sampling, reasoning_parser=getattr(state.config, "reasoning_parser", None)
+        )
     except ValueError as exc:
         return create_error_response(str(exc))
     uid = await submit_generation(spec, state)
@@ -182,7 +193,9 @@ async def stream_chat_completion_chunks(
 ) -> AsyncIterator[bytes]:
     """Format generate_events() into the OpenAI chat.completion.chunk SSE stream."""
     if spec is None:
-        spec = chat_request_to_genspec(req, {})
+        spec = chat_request_to_genspec(
+            req, {}, reasoning_parser=getattr(state.config, "reasoning_parser", None)
+        )
     yield _sse(
         _chat_chunk(
             req,

python/freetoken/server/responses_api.py

@@ -230,19 +230,11 @@ def convert_responses_to_genspec(
     else:
         template_tools, parser_tools = split_tool_lists(raw_tools, selected)
 
-    # Thinking toggle: an explicit chat_template_kwargs extra field wins; else
-    # the protocol-native `reasoning` object drives the template through the
-    # per-family mapping in model_meta. effort "none" disables thinking (vLLM
-    # semantics); other efforts enable it and are forwarded for templates that
-    # grade them (gpt-oss).
-    from .model_meta import think_toggle_kwargs
+    from .model_meta import effort_toggle_kwargs
 
     ctk = dict(getattr(req, "chat_template_kwargs", None) or {})
-    if req.reasoning and not ctk:
-        effort = req.reasoning.get("effort")
-        ctk = dict(think_toggle_kwargs(reasoning_parser, effort != "none"))
-        if effort and effort != "none":
-            ctk.setdefault("reasoning_effort", effort)
+    if req.reasoning:
+        ctk = effort_toggle_kwargs(reasoning_parser, req.reasoning.get("effort"), ctk)
 
     return GenSpec(
         messages=render_messages(messages),

tests/server/test_openai_api.py

@@ -161,6 +161,65 @@ def test_chat_request_reasoning_replay_field_aliases():
         assert asst["thinking"] == "prior thought", field
 
 
+def test_chat_reasoning_effort_enables_thinking():
+    spec = chat_request_to_genspec(chat_request(reasoning_effort="high"), {})
+    assert spec.chat_template_kwargs == {"enable_thinking": True, "reasoning_effort": "high"}
+
+    # an explicit thinking-related chat_template_kwargs key wins over the mapping
+    spec = chat_request_to_genspec(
+        chat_request(reasoning_effort="none", chat_template_kwargs={"enable_thinking": True}), {}
+    )
+    assert spec.chat_template_kwargs == {"enable_thinking": True}
+
+    # unrelated extra kwargs ride along without discarding the effort mapping
+    spec = chat_request_to_genspec(
+        chat_request(reasoning_effort="none", chat_template_kwargs={"custom_var": 1}), {}
+    )
+    assert spec.chat_template_kwargs == {"enable_thinking": False, "custom_var": 1}
+
+    # absent effort -> kwargs pass through untouched
+    assert chat_request_to_genspec(chat_request(), {}).chat_template_kwargs == {}
+
+
+def test_chat_reasoning_effort_none_disables_thinking():
+    # vLLM-compatible semantics: an explicit effort "none" DISABLES thinking.
+    spec = chat_request_to_genspec(chat_request(reasoning_effort="none"), {})
+    assert spec.chat_template_kwargs == {"enable_thinking": False}
+
+
+def test_chat_reasoning_effort_routes_through_family_mapping():
+    """The toggle goes through model_meta's per-family mapping -- for M3 that is
+    thinking_mode, not the (inert) enable_thinking key."""
+    on = chat_request(reasoning_effort="high")
+    spec = chat_request_to_genspec(on, {}, reasoning_parser="minimax_m3")
+    assert spec.chat_template_kwargs == {"thinking_mode": "enabled", "reasoning_effort": "high"}
+
+    off = chat_request(reasoning_effort="none")
+    spec = chat_request_to_genspec(off, {}, reasoning_parser="minimax_m3")
+    assert spec.chat_template_kwargs == {"thinking_mode": "disabled"}
+
+    # gpt-oss: the template grades effort and has no off gear
+    spec = chat_request_to_genspec(on, {}, reasoning_parser="gpt_oss")
+    assert spec.chat_template_kwargs == {"reasoning_effort": "high"}
+    spec = chat_request_to_genspec(off, {}, reasoning_parser="gpt_oss")
+    assert spec.chat_template_kwargs == {}
+
+
+def test_glm_reasoning_parser_honors_disabled_thinking_with_tools():
+    # The parse side must match the encode side: thinking off + tools present
+    # must not start the parser inside a think block.
+    from freetoken.server.generation import _make_reasoning_parser
+
+    state = FakeState([], reasoning_parser="glm")
+    off = chat_request_to_genspec(chat_request(reasoning_effort="none"), {}, reasoning_parser="glm")
+    parser = _make_reasoning_parser(off, state)
+    assert parser is not None and parser.detector.force_reasoning is False
+
+    on = chat_request_to_genspec(chat_request(), {}, reasoning_parser="glm")
+    parser = _make_reasoning_parser(on, state)
+    assert parser is not None and parser.detector.force_reasoning is True
+
+
 def test_non_stream_chat_completion_returns_openai_tool_calls_and_sends_tools():
     output = '[TOOL_CALLS] [{"name":"get_weather","arguments":{"city":"Paris"}}]'
     state = FakeState(

tests/server/test_responses_api.py

@@ -867,17 +867,26 @@ def test_convert_reasoning_field_enables_thinking():
     spec = RP.convert_responses_to_genspec(req, {})
     assert spec.chat_template_kwargs == {"enable_thinking": True, "reasoning_effort": "high"}
 
-    # explicit chat_template_kwargs extra field wins over the reasoning mapping
+    # an explicit thinking-related chat_template_kwargs key wins over the mapping
     req2 = ResponsesRequest.model_validate(
         {"model": "m", "input": "hi", "reasoning": {"effort": "low"},
          "chat_template_kwargs": {"thinking_mode": "chat"}}
     )
     spec2 = RP.convert_responses_to_genspec(req2, {})
     assert spec2.chat_template_kwargs == {"thinking_mode": "chat"}
 
+    # unrelated extra kwargs ride along without discarding the reasoning mapping
+    req3 = ResponsesRequest.model_validate(
+        {"model": "m", "input": "hi", "reasoning": {"effort": "none"},
+         "chat_template_kwargs": {"custom_var": 1}}
+    )
+    assert RP.convert_responses_to_genspec(req3, {}).chat_template_kwargs == {
+        "enable_thinking": False, "custom_var": 1,
+    }
+
     # absent reasoning -> no kwargs
-    req3 = ResponsesRequest.model_validate({"model": "m", "input": "hi"})
-    assert RP.convert_responses_to_genspec(req3, {}).chat_template_kwargs == {}
+    req4 = ResponsesRequest.model_validate({"model": "m", "input": "hi"})
+    assert RP.convert_responses_to_genspec(req4, {}).chat_template_kwargs == {}
 
 
 def test_convert_reasoning_effort_none_disables_thinking():