feat(base): add message_tool_names field for per-message tool attribution

renderers/__init__.py

@@ -33,6 +33,7 @@
     build_trajectory_step,
     create_renderer,
     create_renderer_pool,
+    extract_message_tool_names,
     is_multimodal,
     reject_assistant_in_extension,
     trim_to_turn_close,
@@ -168,6 +169,7 @@ def __dir__() -> list[str]:
     "config_from_name",
     "create_renderer",
     "create_renderer_pool",
+    "extract_message_tool_names",
     "is_multimodal",
     "reject_assistant_in_extension",
     "trim_to_turn_close",

renderers/base.py

@@ -6,6 +6,7 @@
 import logging
 import queue
 import threading
+from collections.abc import Mapping
 from contextlib import contextmanager
 from dataclasses import dataclass, field
 from typing import (
@@ -117,6 +118,68 @@ class Message(TypedDict, total=False):
     reasoning_content: str
 
 
+def extract_message_tool_names(messages: list[Message]) -> list[str | None]:
+    """Per-message tool function names parallel to ``message_roles``.
+
+    Returns one entry per message: the function name for ``role="tool"``
+    messages, ``None`` for every other message. Length matches the
+    input list.
+
+    For tool messages the name is taken from ``msg["name"]`` when set
+    (caller-provided), otherwise recovered by joining
+    ``msg["tool_call_id"]`` against any prior assistant's
+    ``tool_calls[i].function.name`` in the same list. Tool messages
+    whose issuing assistant lives outside the provided list (e.g. on
+    a :meth:`Renderer.bridge_to_next_turn` call where ``new_messages``
+    covers only the new turn) resolve to ``None``.
+
+    Pure metadata: this never mutates the caller's messages and has
+    no effect on the rendered token stream. It runs independently of
+    the render path so the renderer can populate the field on
+    :class:`RenderedTokens` without breaking HF byte parity for tool
+    messages that carry no ``name``. Callers who *also* want the
+    function name to appear in the rendered scaffold (e.g. GPT-OSS
+    Harmony's ``functions.{name}`` prefix) must attach ``name`` to
+    their tool messages before calling :meth:`Renderer.render`
+    themselves — renderers don't synthesize ``name`` into the input,
+    only into this metadata field.
+
+    Trainers join this list with :attr:`RenderedTokens.message_indices`
+    to recover per-token tool attribution — the canonical use case is
+    SFT on tool response bodies while RL acts only on assistant tokens
+    (tool body tokens get a constant positive advantage so the model
+    learns to anticipate tool outputs without learning to emit
+    ``<|tool_response>`` itself).
+
+    Per-message rather than per-token because the data is naturally
+    per-message — storing it per-token would duplicate the same
+    string across every body token of the same tool message.
+    """
+    lookup: dict[str, str] = {}
+    for m in messages:
+        if not isinstance(m, Mapping) or m.get("role") != "assistant":
+            continue
+        for tc in m.get("tool_calls") or []:
+            if not isinstance(tc, Mapping):
+                continue
+            tc_id = tc.get("id")
+            fn = tc.get("function")
+            tc_name = fn.get("name") if isinstance(fn, Mapping) else None
+            if isinstance(tc_id, str) and isinstance(tc_name, str):
+                lookup[tc_id] = tc_name
+    out: list[str | None] = []
+    for m in messages:
+        if not isinstance(m, Mapping) or m.get("role") != "tool":
+            out.append(None)
+            continue
+        name = m.get("name")
+        if not (isinstance(name, str) and name):
+            tc_id = m.get("tool_call_id")
+            name = lookup.get(tc_id) if isinstance(tc_id, str) else None
+        out.append(name if isinstance(name, str) and name else None)
+    return out
+
+
 # ---------------------------------------------------------------------------
 # Renderer data types
 # ---------------------------------------------------------------------------
@@ -208,6 +271,32 @@ class RenderedTokens:
     renderer doesn't provide the signal. ``DefaultRenderer`` leaves it
     empty for the same reason.
 
+    ``message_tool_names`` is the per-message tool function name list,
+    parallel to ``message_roles`` (same length). For tool-role
+    messages it carries the function name — either taken from
+    ``msg["name"]`` (caller-provided) or recovered by joining
+    ``msg["tool_call_id"]`` against a prior assistant's
+    ``tool_calls[i].function.name`` in the rendered slice. Every
+    other message is ``None``, as are tool messages whose issuing
+    assistant lives outside the rendered slice (e.g. on a
+    :meth:`Renderer.bridge_to_next_turn` call where ``new_messages``
+    covers only the new turn).
+
+    This is pure metadata, computed by :func:`extract_message_tool_names`
+    independently of the render path: populating it never touches the
+    rendered token stream, so HF chat-template byte parity is
+    preserved for tool messages carrying no ``name``. Callers who
+    *also* want the function name to appear in the rendered scaffold
+    (e.g. GPT-OSS Harmony's ``functions.{name}`` prefix) must attach
+    ``name`` to their tool messages before calling
+    :meth:`Renderer.render` themselves.
+
+    Trainers join this with ``message_indices`` to build per-tool
+    selective loss masks (SFT on tool response bodies of a specific
+    tool while RL acts on assistant tokens). Empty
+    ``message_tool_names`` (``[]``) means the renderer doesn't
+    provide the signal.
+
     ``multi_modal_data`` is populated by multimodal renderers (e.g.
     ``Qwen3VLRenderer``) when image / video content parts are present;
     text-only renderers leave it as ``None``.
@@ -218,6 +307,7 @@ class RenderedTokens:
     sampled_mask: list[bool] = field(default_factory=list)
     is_content: list[bool] = field(default_factory=list)
     message_roles: list[str] = field(default_factory=list)
+    message_tool_names: list[str | None] = field(default_factory=list)
     multi_modal_data: "MultiModalData | None" = None
 
     def tokens_per_message(

renderers/deepseek_v3.py

@@ -22,6 +22,7 @@
     RenderedTokens,
     ToolSpec,
     attribute_text_segments,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     trim_to_turn_close,
 )
@@ -247,6 +248,7 @@ def emit_text_segments(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def render_ids(
@@ -390,6 +392,7 @@ def emit_text(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     # ------------------------------------------------------------------

renderers/default.py

@@ -18,6 +18,7 @@
     ParsedResponse,
     RenderedTokens,
     ToolSpec,
+    extract_message_tool_names,
 )
 from renderers.configs import DefaultRendererConfig
 from renderers.parsers import (
@@ -141,6 +142,7 @@ def render(
             token_ids=token_ids,
             message_indices=message_indices,
             message_roles=message_roles,
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def _apply(self, messages, *, tools=None, add_generation_prompt=False) -> list[int]:

renderers/glm45.py

@@ -21,6 +21,7 @@
     RenderedTokens,
     ToolSpec,
     attribute_text_segments,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     should_preserve_past_thinking,
 )
@@ -265,6 +266,7 @@ def emit_text_segments(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def render_ids(
@@ -445,6 +447,7 @@ def emit_text_segments(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     def _render_assistant(

renderers/glm5.py

@@ -22,6 +22,7 @@
     RenderedTokens,
     ToolSpec,
     attribute_text_segments,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     should_preserve_past_thinking,
 )
@@ -281,6 +282,7 @@ def emit_text_segments(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def render_ids(
@@ -456,6 +458,7 @@ def emit_text_segments(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     def _render_assistant(

renderers/gpt_oss.py

@@ -56,6 +56,7 @@
     ParsedResponse,
     RenderedTokens,
     ToolSpec,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     should_preserve_past_thinking,
     trim_to_turn_close,
@@ -465,6 +466,7 @@ def emit_harmony_message(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def render_ids(
@@ -594,6 +596,7 @@ def bridge_to_next_turn(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     # ── message conversion ───────────────────────────────────────────────────

renderers/kimi_k2.py

@@ -23,6 +23,7 @@
     ParsedResponse,
     RenderedTokens,
     ToolSpec,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     trim_to_turn_close,
 )
@@ -305,6 +306,7 @@ def emit_text(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in caller_messages],
+            message_tool_names=extract_message_tool_names(caller_messages),
         )
 
     def render_ids(
@@ -454,6 +456,7 @@ def emit_text(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     def _render_assistant(

renderers/kimi_k25.py

@@ -36,6 +36,7 @@
     RenderedTokens,
     ToolCallParseStatus,
     ToolSpec,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     should_preserve_past_thinking,
     trim_to_turn_close,
@@ -946,6 +947,7 @@ def emit_image(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
             multi_modal_data=mm_data,
         )
 
@@ -1188,13 +1190,15 @@ def emit_image(
             merged_items.setdefault(modality, []).extend(vals)
 
         bridge_roles = [m.get("role") or "" for m in new_messages]
+        bridge_tool_names = extract_message_tool_names(new_messages)
         if not (merged_hashes or merged_placeholders or merged_items):
             return RenderedTokens(
                 token_ids=tokens,
                 message_indices=indices,
                 sampled_mask=sampled,
                 is_content=content_mask,
                 message_roles=bridge_roles,
+                message_tool_names=bridge_tool_names,
             )
 
         mm_data = MultiModalData(
@@ -1208,6 +1212,7 @@ def emit_image(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=bridge_roles,
+            message_tool_names=bridge_tool_names,
             multi_modal_data=mm_data,
         )
 

renderers/laguna_xs2.py

@@ -36,6 +36,7 @@
     RenderedTokens,
     ToolSpec,
     attribute_text_segments,
+    extract_message_tool_names,
     reject_assistant_in_extension,
 )
 from renderers.configs import LagunaXS2RendererConfig
@@ -275,6 +276,7 @@ def emit_text_segments(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def render_ids(
@@ -426,6 +428,7 @@ def emit_text_segments(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     def _render_assistant(

renderers/minimax_m2.py

@@ -22,6 +22,7 @@
     RenderedTokens,
     ToolSpec,
     attribute_text_segments,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     should_preserve_past_thinking,
     trim_to_turn_close,
@@ -278,6 +279,7 @@ def emit_token_overlap_body(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in messages],
+            message_tool_names=extract_message_tool_names(messages),
         )
 
     def render_ids(
@@ -459,6 +461,7 @@ def emit_token_overlap_body(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     def _render_assistant(

renderers/nemotron3.py

@@ -25,6 +25,7 @@
     RenderedTokens,
     ToolSpec,
     attribute_text_segments,
+    extract_message_tool_names,
     reject_assistant_in_extension,
     should_preserve_past_thinking,
     trim_to_turn_close,
@@ -411,6 +412,7 @@ def emit_text_segments(
             sampled_mask=sampled,
             is_content=content_mask,
             message_roles=[m.get("role") or "" for m in original_messages],
+            message_tool_names=extract_message_tool_names(original_messages),
         )
 
     def render_ids(
@@ -581,6 +583,7 @@ def emit_text_segments(
             sampled_mask=[False] * total_len,
             is_content=[False] * len(previous_ids) + ext_content,
             message_roles=[m.get("role") or "" for m in new_messages],
+            message_tool_names=extract_message_tool_names(new_messages),
         )
 
     # ------------------------------------------------------------------