Merge 71943a78fd into 9ffb82e139

2026-11-14 09:03:16 +00:00 · 2026-11-06 05:00:38 +00:00 · 2026-11-06 05:00:38 +00:00 · 2f943fcdc8
commit 2f943fcdc8
parent 9ffb82e139 71943a78fd
5 changed files with 170 additions and 25 deletions
--- a/litellm/litellm_core_utils/exception_mapping_utils.py
+++ b/litellm/litellm_core_utils/exception_mapping_utils.py
@ -969,10 +969,10 @@ def _came_from_bedrock_converse(original_exception: _ProviderHTTPException) -> b

 def _get_bedrock_mantle_context_window_message(error_str: str) -> str | None:
    """
-    Mantle reports context overflow as a validation_error carrying the token counts, or as
-    OpenAI's context_length_exceeded code, either in a 400 body or in a streamed error event
-    with no error type. Clients such as Claude Code only treat "prompt is too long" as
-    overflow (litellm/litellm#36546).
+    Mantle reports context overflow as a validation_error carrying the token counts, as
+    OpenAI's context_length_exceeded code, or as the served model's own overflow text, either
+    in a 400 body or in a streamed error event with no error type. Clients such as Claude Code
+    only treat "prompt is too long" as overflow (litellm/litellm#36546).
    """
    match = _BEDROCK_MANTLE_CONTEXT_WINDOW_PATTERN.search(error_str)
    if match is not None:
@ -980,9 +980,17 @@ def _get_bedrock_mantle_context_window_message(error_str: str) -> str | None:
        return f"prompt is too long: {prompt_tokens} tokens > {max_tokens} maximum"
    if _BEDROCK_MANTLE_CONTEXT_LENGTH_EXCEEDED_CODE_PATTERN.search(error_str) is not None:
        return _BEDROCK_MANTLE_CONTEXT_WINDOW_GENERIC_MESSAGE
+    if ExceptionCheckers.is_error_str_context_window_exceeded(error_str):
+        return _with_prompt_is_too_long(error_str)
    return None


+def _with_prompt_is_too_long(error_str: str) -> str:
+    if "prompt is too long" in error_str:
+        return error_str
+    return f"prompt is too long: {error_str}"
+
+
 def _map_bedrock_exception(
    *,
    model: str,
@ -1009,9 +1017,10 @@ def _map_bedrock_exception(
        or "prompt is too long" in error_str
        or "prompt: length: 1.." in error_str
        or "Too many input tokens" in error_str
+        or ExceptionCheckers.is_error_str_context_window_exceeded(error_str)
    ):
        raise ContextWindowExceededError(
-            message=f"BedrockException: Context Window Error - {error_str}",
+            message=f"BedrockException: Context Window Error - {_with_prompt_is_too_long(error_str)}",
            model=model,
            llm_provider="bedrock",
            response=getattr(original_exception, "response", None),
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@ -44336,7 +44336,7 @@
        "input_cost_per_token_batches": 3e-07,
        "input_cost_per_token_priority": 1.05e-06,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token": 2.5e-06,
@ -44357,7 +44357,7 @@
        "input_cost_per_token_flex": 3e-07,
        "input_cost_per_token_priority": 1.05e-06,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token": 3e-06,
@ -45632,7 +45632,7 @@
        "input_cost_per_token_flex": 3e-08,
        "input_cost_per_token_priority": 1.1e-07,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token": 2.4e-07,
@ -48109,7 +48109,7 @@
        "input_cost_per_token_flex": 7e-08,
        "input_cost_per_token_priority": 2.6e-07,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token": 1.2e-06,
@ -48260,7 +48260,7 @@
        "input_cost_per_token_flex": 2.5e-07,
        "input_cost_per_token_priority": 8.75e-07,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token": 1.2e-06,
@ -70383,7 +70383,7 @@
        "output_cost_per_token": 2.5e-06,
        "output_cost_per_token_flex": 1.25e-06,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token_batches": 1.25e-06,
@ -70404,7 +70404,7 @@
        "output_cost_per_token": 8.8e-07,
        "output_cost_per_token_flex": 4.4e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token_batches": 4.4e-07,
@ -70425,7 +70425,7 @@
        "output_cost_per_token": 6e-07,
        "output_cost_per_token_flex": 3e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 32000,
+        "max_input_tokens": 32768,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token_batches": 3e-07,
@ -70448,7 +70448,7 @@
        "output_cost_per_token": 6e-07,
        "output_cost_per_token_flex": 3e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token_batches": 3e-07,
@ -70490,7 +70490,7 @@
        "output_cost_per_token": 1.2e-06,
        "output_cost_per_token_flex": 6e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token_batches": 6e-07,
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@ -44336,7 +44336,7 @@
        "input_cost_per_token_batches": 3e-07,
        "input_cost_per_token_priority": 1.05e-06,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token": 2.5e-06,
@ -44357,7 +44357,7 @@
        "input_cost_per_token_flex": 3e-07,
        "input_cost_per_token_priority": 1.05e-06,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token": 3e-06,
@ -45632,7 +45632,7 @@
        "input_cost_per_token_flex": 3e-08,
        "input_cost_per_token_priority": 1.1e-07,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token": 2.4e-07,
@ -48109,7 +48109,7 @@
        "input_cost_per_token_flex": 7e-08,
        "input_cost_per_token_priority": 2.6e-07,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token": 1.2e-06,
@ -48260,7 +48260,7 @@
        "input_cost_per_token_flex": 2.5e-07,
        "input_cost_per_token_priority": 8.75e-07,
        "litellm_provider": "bedrock_converse",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token": 1.2e-06,
@ -70383,7 +70383,7 @@
        "output_cost_per_token": 2.5e-06,
        "output_cost_per_token_flex": 1.25e-06,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token_batches": 1.25e-06,
@ -70404,7 +70404,7 @@
        "output_cost_per_token": 8.8e-07,
        "output_cost_per_token_flex": 4.4e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token_batches": 4.4e-07,
@ -70425,7 +70425,7 @@
        "output_cost_per_token": 6e-07,
        "output_cost_per_token_flex": 3e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 32000,
+        "max_input_tokens": 32768,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token_batches": 3e-07,
@ -70448,7 +70448,7 @@
        "output_cost_per_token": 6e-07,
        "output_cost_per_token_flex": 3e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 16000,
        "mode": "chat",
        "output_cost_per_token_batches": 3e-07,
@ -70490,7 +70490,7 @@
        "output_cost_per_token": 1.2e-06,
        "output_cost_per_token_flex": 6e-07,
        "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
+        "max_input_tokens": 262144,
        "max_output_tokens": 8000,
        "mode": "chat",
        "output_cost_per_token_batches": 6e-07,
--- a/tests/unit/litellm_core_utils/test_exception_mapping_utils.py
+++ b/tests/unit/litellm_core_utils/test_exception_mapping_utils.py
@ -1613,6 +1613,7 @@ PROVIDERS_THAT_RECOGNISE_A_FULL_CONTEXT_WINDOW = (
    "anthropic",
    "azure",
    "azure_ai",
+    "bedrock",
    "databricks",
    "deepseek",
    "fireworks_ai",
@ -1840,6 +1841,32 @@ def test_bedrock_mantle_openai_envelope_context_overflow_maps_to_context_window_
    assert "prompt is too long" in excinfo.value.message


+def test_bedrock_mantle_served_model_overflow_text_maps_to_prompt_is_too_long():
+    from litellm.llms.base_llm.chat.transformation import BaseLLMException
+
+    original_exception: Final = BaseLLMException(
+        status_code=400,
+        message=(
+            '{"error":{"code":"validation_error","message":"ErrorEvent { error: APIError { type: '
+            '\\"BadRequestError\\", code: Some(400), message: \\"This model\'s maximum context length is 262144 '
+            "tokens. However, you requested 16 output tokens and your prompt contains at least 262129 input tokens"
+            '\\", param: None } }","param":null,"type":"invalid_request_error"}}'
+        ),
+    )
+
+    with pytest.raises(litellm.ContextWindowExceededError) as excinfo:
+        exception_type(
+            model="qwen.qwen3-next-80b-a3b-instruct",
+            original_exception=original_exception,
+            custom_llm_provider="bedrock_mantle",
+        )
+
+    assert excinfo.value.status_code == 400
+    assert excinfo.value.llm_provider == "bedrock_mantle"
+    assert "prompt is too long" in excinfo.value.message
+    assert "your prompt contains at least 262129 input tokens" in excinfo.value.message
+
+
 def test_bedrock_mantle_streamed_context_overflow_event_maps_to_context_window_exceeded():
    from litellm.responses.streaming_iterator import map_stream_error_to_exception

@ -2053,6 +2080,46 @@ def test_bedrock_500_preserves_provider_response_headers():
    assert exc_info.value.response.headers["x-amzn-requestid"] == "req-map-500"


+def test_bedrock_converse_maximum_context_length_error_maps_to_context_window_exceeded():
+    original_exception: Final = BedrockError(
+        status_code=400,
+        message=(
+            '{"message":"The model returned the following errors: ErrorEvent { error: APIError { type: '
+            '\\"BadRequestError\\", code: Some(400), message: \\"This model\'s maximum context length is 262144 '
+            "tokens. However, you requested 16 output tokens and your prompt contains at least 262129 input tokens"
+            '\\" } }"}'
+        ),
+    )
+
+    with pytest.raises(litellm.ContextWindowExceededError) as exc_info:
+        exception_type(
+            model="qwen.qwen3-coder-next",
+            original_exception=original_exception,
+            custom_llm_provider="bedrock",
+        )
+
+    assert exc_info.value.status_code == 400
+    assert "maximum context length is 262144 tokens" in exc_info.value.message
+    assert "prompt is too long" in exc_info.value.message
+
+
+def test_bedrock_overflow_that_already_says_prompt_is_too_long_is_not_repeated():
+    original_exception: Final = BedrockError(
+        status_code=400,
+        message='{"message":"prompt is too long: 210000 tokens > 200000 maximum"}',
+    )
+
+    with pytest.raises(litellm.ContextWindowExceededError) as exc_info:
+        exception_type(
+            model="anthropic.claude-sonnet-4-5-20250929-v1:0",
+            original_exception=original_exception,
+            custom_llm_provider="bedrock",
+        )
+
+    assert exc_info.value.message.count("prompt is too long") == 1
+    assert "210000 tokens > 200000 maximum" in exc_info.value.message
+
+
@pytest.mark.parametrize(
    "custom_llm_provider, status_code, provider_message, expected_exception",
    [
--- a/tests/unit/test_model_prices_and_context_window.py
+++ b/tests/unit/test_model_prices_and_context_window.py
@ -3,6 +3,8 @@ from __future__ import annotations
 import json
 import re
 from collections.abc import Iterator, Mapping
+from itertools import groupby
+from operator import itemgetter
 from pathlib import Path
 from types import MappingProxyType
 from typing import Final
@ -1024,3 +1026,70 @@ def test_bedrock_gpt_oss_rows_declare_vision_support_like_their_safeguard_siblin
 def test_bedrock_gpt_oss_vision_is_explicitly_disabled_for_the_router_gate() -> None:
    assert litellm.utils.is_vision_explicitly_disabled("bedrock/openai.gpt-oss-120b-1:0") is True
    assert litellm.utils.is_vision_explicitly_disabled("bedrock_mantle/openai.gpt-oss-20b") is True
+
+
+class _BedrockWindowRow(BaseModel):
+    model_config = ConfigDict(frozen=True, extra="ignore")
+
+    litellm_provider: str
+    max_input_tokens: int | None = None
+
+
+_BEDROCK_PROVIDERS: Final = frozenset({"bedrock", "bedrock_converse", "bedrock_mantle"})
+_ROWS_NAMING_A_MODEL_UNDER_ANOTHER_ID: Final = (
+    ("moonshot.kimi-k2-thinking", "moonshotai.kimi-k2-thinking"),
+    ("bedrock_mantle/moonshotai.kimi-k2-thinking", "moonshotai.kimi-k2-thinking"),
+    ("bedrock_mantle/qwen.qwen3-next-80b-a3b-instruct", "qwen.qwen3-next-80b-a3b"),
+    ("bedrock_mantle/qwen.qwen3-235b-a22b-2507", "qwen.qwen3-235b-a22b-2507-v1:0"),
+    ("bedrock_mantle/qwen.qwen3-coder-30b-a3b-instruct", "qwen.qwen3-coder-30b-a3b-v1:0"),
+    ("bedrock_mantle/qwen.qwen3-32b", "qwen.qwen3-32b-v1:0"),
+)
+_BEDROCK_PREFIXED_ROW: Final = re.compile(r"bedrock/(?:[a-z0-9-]+/)?(?P<model>[^/]+)")
+
+
+def _bedrock_input_windows(path: Path) -> Mapping[str, int]:
+    prices: Final = TypeAdapter(dict[str, JsonValue]).validate_json(path.read_bytes())
+    rows: Final = tuple(
+        (key, _BedrockWindowRow.model_validate(row))
+        for key, row in prices.items()
+        if isinstance(row, dict) and row.get("litellm_provider") in _BEDROCK_PROVIDERS
+    )
+    return MappingProxyType({key: row.max_input_tokens for key, row in rows if row.max_input_tokens is not None})
+
+
+def _widest_prefixed_window_per_model(windows: Mapping[str, int]) -> Mapping[str, int]:
+    prefixed: Final = sorted(
+        (match["model"], window) for key, window in windows.items() if (match := _BEDROCK_PREFIXED_ROW.fullmatch(key))
+    )
+    return MappingProxyType(
+        {model: max(window for _, window in group) for model, group in groupby(prefixed, key=itemgetter(0))}
+    )
+
+
+@pytest.mark.parametrize("path", (PRICES_PATH, BACKUP_PRICES_PATH), ids=("main", "backup"))
+def test_bare_bedrock_rows_admit_every_prompt_their_prefixed_rows_admit(path: Path) -> None:
+    windows: Final = _bedrock_input_windows(path)
+    widest: Final = _widest_prefixed_window_per_model(windows)
+    bare_with_prefixed_rows: Final = tuple(key for key in windows if "/" not in key and key in widest)
+    assert bare_with_prefixed_rows, f"No bare Bedrock row with a bedrock/ counterpart in {path}"
+    narrower: Final = tuple(
+        f"{key}: {windows[key]} < {widest[key]}" for key in bare_with_prefixed_rows if windows[key] < widest[key]
+    )
+    assert narrower == ()
+
+
+def _widest_window_of_model(windows: Mapping[str, int], model: str) -> int:
+    return max(
+        window
+        for key, window in windows.items()
+        if key == model or ((match := _BEDROCK_PREFIXED_ROW.fullmatch(key)) is not None and match["model"] == model)
+    )
+
+
+@pytest.mark.parametrize("path", (PRICES_PATH, BACKUP_PRICES_PATH), ids=("main", "backup"))
+@pytest.mark.parametrize(("row", "model"), _ROWS_NAMING_A_MODEL_UNDER_ANOTHER_ID)
+def test_bedrock_rows_under_another_model_id_admit_every_prompt_that_model_admits(
+    path: Path, row: str, model: str
+) -> None:
+    windows: Final = _bedrock_input_windows(path)
+    assert windows[row] >= _widest_window_of_model(windows, model)