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e2971e0af4
* refactor(litellm): migrate private usage in llms Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(litellm): preserve Bedrock batch signature marker Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(litellm): migrate llms private usage symbols Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(litellm): preserve UUID Watsonx project IDs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(litellm): retarget llms mocks to public names Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(litellm): limit llms changes to renames and forwarders Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(litellm): keep GCS mock client patching private Vertex auth methods Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(litellm): assert forwarder arguments and type forwarder signatures Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: mateo <mateo@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
94 lines
3.1 KiB
Python
94 lines
3.1 KiB
Python
"""
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Validate Claude Fable 5 and Claude Fable 5.1 model configuration entries.
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Fable 5 is a new tier above Opus ($10/$50 per MTok) with the same adaptive-only
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API surface as Opus 4.7/4.8. The cost-map entries below are what make the model
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resolvable across Anthropic, Bedrock, Vertex AI, and Azure AI (Microsoft
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Foundry), and the ``supports_adaptive_thinking`` flag is what makes LiteLLM send
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``thinking.type='adaptive'`` instead of the legacy ``enabled``/``budget_tokens``
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shape, which Fable 5 rejects with a 400.
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"""
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import json
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import os
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import pytest
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from litellm.constants import BEDROCK_CONVERSE_MODELS
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from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap
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REPO_ROOT = os.path.join(os.path.dirname(__file__), "../..")
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def _load_root_cost_map() -> dict:
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json_path = os.path.join(REPO_ROOT, "model_prices_and_context_window.json")
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with open(json_path) as f:
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return json.load(f)
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def test_fable_5_registered_for_bedrock_converse():
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assert "anthropic.claude-fable-5" in BEDROCK_CONVERSE_MODELS
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@pytest.mark.parametrize(
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"model",
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[
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"claude-fable-5",
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"anthropic/claude-fable-5",
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"anthropic.claude-fable-5",
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"bedrock/us.anthropic.claude-fable-5",
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"bedrock/invoke/eu.anthropic.claude-fable-5",
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"bedrock/global.anthropic.claude-fable-5",
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"vertex_ai/claude-fable-5",
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"azure_ai/claude-fable-5",
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],
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)
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def test_adaptive_thinking_detected_for_fable_5(local_model_cost_map, model):
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"""Provider-routed ids must resolve to a flagged entry so ``reasoning_effort``
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maps to ``thinking.type='adaptive'`` + ``output_config.effort``."""
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from litellm.llms.anthropic.common_utils import AnthropicModelInfo
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assert AnthropicModelInfo.is_adaptive_thinking_model(model, "anthropic") is True
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FABLE_5_1_VARIANTS = (
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"claude-fable-5-1",
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"anthropic.claude-fable-5-1",
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"global.anthropic.claude-fable-5-1",
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"us.anthropic.claude-fable-5-1",
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"eu.anthropic.claude-fable-5-1",
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"vertex_ai/claude-fable-5-1",
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"vertex_ai/claude-fable-5-1@default",
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"azure_ai/claude-fable-5-1",
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)
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def test_fable_5_1_present_in_bundled_backup():
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backup = GetModelCostMap.load_local_model_cost_map()
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root = _load_root_cost_map()
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for model_name in FABLE_5_1_VARIANTS:
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assert model_name in backup, f"Missing from backup cost map: {model_name}"
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assert backup[model_name] == root[model_name], model_name
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def test_fable_5_1_registered_for_bedrock_converse():
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assert "anthropic.claude-fable-5-1" in BEDROCK_CONVERSE_MODELS
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@pytest.mark.parametrize(
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"model",
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[
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"claude-fable-5-1",
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"anthropic/claude-fable-5-1",
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"anthropic.claude-fable-5-1",
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"bedrock/us.anthropic.claude-fable-5-1",
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"bedrock/invoke/eu.anthropic.claude-fable-5-1",
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"bedrock/global.anthropic.claude-fable-5-1",
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"vertex_ai/claude-fable-5-1",
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"azure_ai/claude-fable-5-1",
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],
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)
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def test_adaptive_thinking_detected_for_fable_5_1(local_model_cost_map, model):
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from litellm.llms.anthropic.common_utils import AnthropicModelInfo
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assert AnthropicModelInfo.is_adaptive_thinking_model(model, "anthropic") is True
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