🐾 fix(mantle): survive Mantle's 20k output ceiling on tool-heavy turns

Two new Mantle shims, auto-installed alongside the existing pair:

- Opt out of the fine-grained-tool-streaming beta. Under it, an
  output-token cutoff mid-tool_use ends the stream without
  content_block_stop; fast-agent raises "Streaming completed but tool
  call never finished" and burns its retry ladder against the same
  wall (the observed ~700s Alan revise_workspace_file failures on
  Taurus).

- Clamp default maxTokens to Mantle's observed 20 000-token server
  ceiling, so the model stops gracefully (proper block close +
  stop_reason=max_tokens) instead of being cut off by the gateway.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-04 16:49:21 -04:00
parent d528192bee
commit b5a3aa214b
3 changed files with 197 additions and 21 deletions

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@@ -218,7 +218,7 @@ anthropic:
That's the whole configuration. Pallas auto-detects the That's the whole configuration. Pallas auto-detects the
`bedrock-mantle` hostname in `anthropic.base_url` at startup and installs `bedrock-mantle` hostname in `anthropic.base_url` at startup and installs
two compatibility shims so fast-agent's default request shape matches four compatibility shims so fast-agent's default request shape matches
what Mantle expects (see `pallas/mantle_shims.py`): what Mantle expects (see `pallas/mantle_shims.py`):
1. **Wire-name prefix** — re-adds the `anthropic.` prefix that fast-agent's 1. **Wire-name prefix** — re-adds the `anthropic.` prefix that fast-agent's
@@ -233,6 +233,25 @@ what Mantle expects (see `pallas/mantle_shims.py`):
Input should be a valid dictionary or object"`, which would otherwise Input should be a valid dictionary or object"`, which would otherwise
break the MCP tool-use loop on the second turn. break the MCP tool-use loop on the second turn.
3. **Fine-grained tool streaming opt-out** — stops fast-agent sending the
`fine-grained-tool-streaming-2025-05-14` beta. Under that beta an
output-token cutoff mid-`tool_use` block ends the stream without
`content_block_stop`, which fast-agent surfaces as
`Streaming completed but tool call never finished` and then retries
into the same wall (~700 s agent failures on large tool bodies).
Without the beta a cutoff closes blocks properly and lands in
fast-agent's graceful `stop_reason=max_tokens` handling.
4. **`max_tokens` clamp** — Mantle enforces a server-side output ceiling
of 20 000 tokens per response regardless of the requested
`max_tokens` (fast-agent asks for the model's full 128 000). The shim
clamps default `maxTokens` to `MANTLE_MAX_OUTPUT_TOKENS` (20 000) so
the model stops gracefully at the limit instead of the gateway
cutting the stream. A single agent turn — thinking, prose, and tool
input combined — cannot exceed this on Mantle; agents that must emit
more output in one turn need to split the work (e.g. patch-style
edits instead of full-document rewrites).
The Anthropic SDK appends `/v1/messages` to `base_url` automatically. The Anthropic SDK appends `/v1/messages` to `base_url` automatically.
**Feature support.** Mantle accepts the same Messages API request shape **Feature support.** Mantle accepts the same Messages API request shape

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@@ -24,7 +24,23 @@ before the wire traffic is valid:
Upstream SDK tracker: https://github.com/anthropics/anthropic-sdk-python/issues/1454 Upstream SDK tracker: https://github.com/anthropics/anthropic-sdk-python/issues/1454
Both shims are idempotent and may be installed at process startup before any 3. **Fine-grained tool streaming truncation.** Fast-agent unconditionally
sends the ``fine-grained-tool-streaming-2025-05-14`` beta on tool-bearing
requests. Under that beta, an output-token cutoff mid-``tool_use`` block
ends the stream *without* ``content_block_stop``, which fast-agent's
stream accounting surfaces as ``Streaming completed but tool call never
finished`` — followed by a full retry ladder against the same wall
(observed as ~700 s agent failures on large ``revise_workspace_file``
bodies). We disable that one beta so a cutoff closes blocks properly and
lands in fast-agent's graceful ``stop_reason=max_tokens`` handling.
4. **Output-token ceiling.** Mantle clamps ``max_tokens`` to 20 000
server-side (streams complete at exactly 20 000 output tokens regardless
of the requested 128 000). We clamp the request to that ceiling so the
*model* stops gracefully at the limit — emitting proper block-stop events
and ``stop_reason`` — instead of being cut off by the gateway's clamp.
All shims are idempotent and may be installed at process startup before any
fast-agent ``FastAgent`` instance is constructed. fast-agent ``FastAgent`` instance is constructed.
""" """
from __future__ import annotations from __future__ import annotations
@@ -129,12 +145,90 @@ def install_tool_use_caller_strip() -> None:
logger.info("Mantle tool_use.caller strip shim installed") logger.info("Mantle tool_use.caller strip shim installed")
# ── Shim 3: disable fine-grained tool streaming ──────────────────────────────
_beta_opt_out_installed = False
def install_fine_grained_tool_streaming_opt_out() -> None:
"""Stop fast-agent requesting the fine-grained tool streaming beta.
Under that beta a ``max_tokens`` cutoff mid-``tool_use`` ends the stream
without ``content_block_stop``; fast-agent then raises
``Streaming completed but tool call never finished`` and burns its whole
retry ladder against the same ceiling. Without the beta the cutoff closes
blocks properly and fast-agent's ``stop_reason=max_tokens`` handling
applies. Safe to call more than once.
"""
global _beta_opt_out_installed
if _beta_opt_out_installed:
return
from fast_agent.llm.provider.anthropic.llm_anthropic import AnthropicLLM
original_supports = AnthropicLLM.supports_direct_anthropic_beta
def patched_supports(self: Any, feature: str) -> bool:
if feature == "fine_grained_tool_streaming":
return False
return original_supports(self, feature)
AnthropicLLM.supports_direct_anthropic_beta = patched_supports # type: ignore[method-assign]
_beta_opt_out_installed = True
logger.info("Mantle fine-grained tool streaming opt-out shim installed")
# ── Shim 4: clamp max_tokens to Mantle's output ceiling ──────────────────────
# Observed server-side clamp: Mantle streams stop at exactly 20 000 output
# tokens however large the requested max_tokens. Requesting the ceiling
# explicitly makes the model stop gracefully (proper block close + stop_reason)
# instead of the gateway cutting the stream at its own limit.
MANTLE_MAX_OUTPUT_TOKENS = 20_000
_max_tokens_clamp_installed = False
def install_max_tokens_clamp() -> None:
"""Clamp default ``maxTokens`` to Mantle's output ceiling.
Wraps ``AnthropicLLM._initialize_default_params`` so every agent's
default request params carry an explicit ``maxTokens`` no higher than the
ceiling. Per-request ``RequestParams`` overrides bypass this — none of
our agent modules set one. Safe to call more than once.
"""
global _max_tokens_clamp_installed
if _max_tokens_clamp_installed:
return
from fast_agent.llm.provider.anthropic.llm_anthropic import AnthropicLLM
original_init = AnthropicLLM._initialize_default_params # noqa: SLF001
def patched_init(self: Any, kwargs: dict) -> Any:
params = original_init(self, kwargs)
if params.maxTokens is None or params.maxTokens > MANTLE_MAX_OUTPUT_TOKENS:
params.maxTokens = MANTLE_MAX_OUTPUT_TOKENS
return params
AnthropicLLM._initialize_default_params = patched_init # noqa: SLF001
_max_tokens_clamp_installed = True
logger.info(
"Mantle max_tokens clamp shim installed (ceiling %d)",
MANTLE_MAX_OUTPUT_TOKENS,
)
# ── Orchestrator ───────────────────────────────────────────────────────────── # ── Orchestrator ─────────────────────────────────────────────────────────────
def install_all() -> None: def install_all() -> None:
"""Install all Mantle shims. Call once at process startup.""" """Install all Mantle shims. Call once at process startup."""
install_wire_name_prefix() install_wire_name_prefix()
install_tool_use_caller_strip() install_tool_use_caller_strip()
install_fine_grained_tool_streaming_opt_out()
install_max_tokens_clamp()
def maybe_install(anthropic_base_url: str | None) -> bool: def maybe_install(anthropic_base_url: str | None) -> bool:

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@@ -114,34 +114,97 @@ def test_install_tool_use_caller_strip_is_idempotent() -> None:
mantle_shims.install_tool_use_caller_strip() # must not raise or re-wrap mantle_shims.install_tool_use_caller_strip() # must not raise or re-wrap
# ── install_fine_grained_tool_streaming_opt_out ──────────────────────────────
def test_fine_grained_beta_opt_out() -> None:
from fast_agent.llm.provider.anthropic.llm_anthropic import AnthropicLLM
mantle_shims.install_fine_grained_tool_streaming_opt_out()
# The patched method never touches self, so a bare object suffices.
stub = object()
assert AnthropicLLM.supports_direct_anthropic_beta(stub, "fine_grained_tool_streaming") is False
# Every other beta keeps the base-class answer (True).
assert AnthropicLLM.supports_direct_anthropic_beta(stub, "interleaved_thinking") is True
assert AnthropicLLM.supports_direct_anthropic_beta(stub, "long_context") is True
def test_fine_grained_beta_opt_out_is_idempotent() -> None:
mantle_shims.install_fine_grained_tool_streaming_opt_out()
mantle_shims.install_fine_grained_tool_streaming_opt_out() # must not re-wrap
from fast_agent.llm.provider.anthropic.llm_anthropic import AnthropicLLM
assert (
AnthropicLLM.supports_direct_anthropic_beta(object(), "fine_grained_tool_streaming")
is False
)
# ── install_max_tokens_clamp ─────────────────────────────────────────────────
@pytest.mark.parametrize(
"initial,expected",
[
(128000, mantle_shims.MANTLE_MAX_OUTPUT_TOKENS), # over the ceiling → clamped
(None, mantle_shims.MANTLE_MAX_OUTPUT_TOKENS), # unset → pinned to ceiling
(4096, 4096), # under the ceiling → untouched
],
)
def test_max_tokens_clamp(
monkeypatch: pytest.MonkeyPatch, initial: int | None, expected: int
) -> None:
from fast_agent.llm.provider.anthropic.llm_anthropic import AnthropicLLM
from fast_agent.types import RequestParams
# Stub the underlying initializer, then force a fresh wrap around it.
monkeypatch.setattr(
AnthropicLLM,
"_initialize_default_params",
lambda self, kwargs: RequestParams(maxTokens=initial),
)
monkeypatch.setattr(mantle_shims, "_max_tokens_clamp_installed", False)
mantle_shims.install_max_tokens_clamp()
params = AnthropicLLM._initialize_default_params(object(), {})
assert params.maxTokens == expected
def test_max_tokens_clamp_is_idempotent() -> None:
mantle_shims.install_max_tokens_clamp()
mantle_shims.install_max_tokens_clamp() # must not raise or re-wrap
# ── maybe_install ──────────────────────────────────────────────────────────── # ── maybe_install ────────────────────────────────────────────────────────────
def test_maybe_install_installs_when_mantle(monkeypatch: pytest.MonkeyPatch) -> None: _INSTALLER_NAMES = [
("install_wire_name_prefix", "wire"),
("install_tool_use_caller_strip", "tool_use"),
("install_fine_grained_tool_streaming_opt_out", "beta_opt_out"),
("install_max_tokens_clamp", "max_tokens"),
]
def _patch_installers(monkeypatch: pytest.MonkeyPatch) -> list[str]:
calls: list[str] = [] calls: list[str] = []
for attr, label in _INSTALLER_NAMES:
monkeypatch.setattr( monkeypatch.setattr(
mantle_shims, "install_wire_name_prefix", mantle_shims, attr,
lambda: calls.append("wire"), lambda label=label: calls.append(label),
)
monkeypatch.setattr(
mantle_shims, "install_tool_use_caller_strip",
lambda: calls.append("tool_use"),
) )
return calls
def test_maybe_install_installs_when_mantle(monkeypatch: pytest.MonkeyPatch) -> None:
calls = _patch_installers(monkeypatch)
installed = mantle_shims.maybe_install("https://bedrock-mantle.us-east-1.api.aws/anthropic") installed = mantle_shims.maybe_install("https://bedrock-mantle.us-east-1.api.aws/anthropic")
assert installed is True assert installed is True
assert calls == ["wire", "tool_use"] assert calls == ["wire", "tool_use", "beta_opt_out", "max_tokens"]
def test_maybe_install_noop_for_non_mantle(monkeypatch: pytest.MonkeyPatch) -> None: def test_maybe_install_noop_for_non_mantle(monkeypatch: pytest.MonkeyPatch) -> None:
calls: list[str] = [] calls = _patch_installers(monkeypatch)
monkeypatch.setattr(
mantle_shims, "install_wire_name_prefix",
lambda: calls.append("wire"),
)
monkeypatch.setattr(
mantle_shims, "install_tool_use_caller_strip",
lambda: calls.append("tool_use"),
)
assert mantle_shims.maybe_install("https://api.anthropic.com") is False assert mantle_shims.maybe_install("https://api.anthropic.com") is False
assert mantle_shims.maybe_install(None) is False assert mantle_shims.maybe_install(None) is False