diff --git a/litellm/integrations/arize/_utils.py b/litellm/integrations/arize/_utils.py index 8dfaa8b1425a..a1bf65141c97 100644 --- a/litellm/integrations/arize/_utils.py +++ b/litellm/integrations/arize/_utils.py @@ -220,23 +220,57 @@ def _set_structured_outputs(span: "Span", response_obj, msg_attrs, span_attrs): safe_set_attribute(span, f"{prefix}.{msg_attrs.MESSAGE_ROLE}", message_role) +def _safe_get(obj, key, default=None): + """Read ``key`` from a dict-like or Pydantic-model-like object. + + The arize/langfuse_otel logger receives ``usage`` objects from many sources: + plain dicts, litellm ``Usage`` (which exposes ``.get``), and raw OpenAI + Pydantic models (e.g. ``openai.types.completion_usage.CompletionUsage`` and + nested ``CompletionTokensDetails`` / ``OutputTokensDetails``) which do NOT + expose ``.get``. Calling ``.get`` on the latter raised ``AttributeError`` — + see https://github.com/BerriAI/litellm/issues/13672. + """ + if obj is None: + return default + getter = getattr(obj, "get", None) + if callable(getter): + try: + return getter(key, default) + except TypeError: + # Some objects expose `.get` with a different signature + pass + return getattr(obj, key, default) + + def _set_usage_outputs(span: "Span", response_obj, span_attrs): usage = response_obj and response_obj.get("usage") if not usage: return safe_set_attribute( - span, span_attrs.LLM_TOKEN_COUNT_TOTAL, usage.get("total_tokens") + span, span_attrs.LLM_TOKEN_COUNT_TOTAL, _safe_get(usage, "total_tokens") + ) + completion_tokens = _safe_get(usage, "completion_tokens") or _safe_get( + usage, "output_tokens" ) - completion_tokens = usage.get("completion_tokens") or usage.get("output_tokens") if completion_tokens: safe_set_attribute( span, span_attrs.LLM_TOKEN_COUNT_COMPLETION, completion_tokens ) - prompt_tokens = usage.get("prompt_tokens") or usage.get("input_tokens") + prompt_tokens = _safe_get(usage, "prompt_tokens") or _safe_get( + usage, "input_tokens" + ) if prompt_tokens: safe_set_attribute(span, span_attrs.LLM_TOKEN_COUNT_PROMPT, prompt_tokens) - reasoning_tokens = usage.get("output_tokens_details", {}).get("reasoning_tokens") + + # Reasoning tokens live in `completion_tokens_details` for Chat Completions + # API (Usage) and in `output_tokens_details` for Responses API + # (ResponseAPIUsage). Both nested objects may be plain Pydantic models + # without `.get`. + token_details = _safe_get(usage, "completion_tokens_details") or _safe_get( + usage, "output_tokens_details" + ) + reasoning_tokens = _safe_get(token_details, "reasoning_tokens") if reasoning_tokens: safe_set_attribute( span, diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index f6de40717d15..5cccd5f00af6 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -4645,6 +4645,169 @@ "supports_vision": true, "supports_web_search": true }, + "azure/gpt-5.5": { + "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_priority": 1e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 2e-06, + "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_priority": 1e-05, + "input_cost_per_token_above_272k_tokens_priority": 2e-05, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_priority": 6e-05, + "output_cost_per_token_above_272k_tokens_priority": 9e-05, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": false + }, + "azure/gpt-5.5-2026-04-23": { + "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_priority": 1e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 2e-06, + "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_priority": 1e-05, + "input_cost_per_token_above_272k_tokens_priority": 2e-05, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_priority": 6e-05, + "output_cost_per_token_above_272k_tokens_priority": 9e-05, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true + }, + "azure/gpt-5.5-pro": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "supported_endpoints": [ + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": false, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_low_reasoning_effort": false + }, + "azure/gpt-5.5-pro-2026-04-23": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "supported_endpoints": [ + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure/gpt-5.4-mini": { "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 7.5e-07, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 2d13c5cd00f0..12a0d8fe0a7e 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -4659,6 +4659,169 @@ "supports_vision": true, "supports_web_search": true }, + "azure/gpt-5.5": { + "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_priority": 1e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 2e-06, + "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_priority": 1e-05, + "input_cost_per_token_above_272k_tokens_priority": 2e-05, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_priority": 6e-05, + "output_cost_per_token_above_272k_tokens_priority": 9e-05, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": false + }, + "azure/gpt-5.5-2026-04-23": { + "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_priority": 1e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 2e-06, + "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_priority": 1e-05, + "input_cost_per_token_above_272k_tokens_priority": 2e-05, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_priority": 6e-05, + "output_cost_per_token_above_272k_tokens_priority": 9e-05, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true + }, + "azure/gpt-5.5-pro": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "supported_endpoints": [ + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": false, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_low_reasoning_effort": false + }, + "azure/gpt-5.5-pro-2026-04-23": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "litellm_provider": "azure", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "supported_endpoints": [ + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure/gpt-5.4-mini": { "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 7.5e-07, diff --git a/tests/test_litellm/integrations/arize/test_arize_utils.py b/tests/test_litellm/integrations/arize/test_arize_utils.py index a87a4167899c..86c5448d4684 100644 --- a/tests/test_litellm/integrations/arize/test_arize_utils.py +++ b/tests/test_litellm/integrations/arize/test_arize_utils.py @@ -273,6 +273,91 @@ def test_arize_set_attributes_responses_api(): ) +def test_set_usage_outputs_pydantic_completion_usage(): + """ + Regression test for https://github.com/BerriAI/litellm/issues/13672 + + `_set_usage_outputs` previously called `usage.get(...)` which crashes when + `usage` is a plain Pydantic model (e.g. openai.types.completion_usage.CompletionUsage) + that does not implement dict-style `.get()`. Same crash for nested + `output_tokens_details` / `completion_tokens_details`. + + The function must: + 1. Read total/prompt/completion tokens from a Pydantic usage without `.get`. + 2. Read reasoning_tokens from `completion_tokens_details` (chat completions API) + OR `output_tokens_details` (responses API), even when those nested objects + are Pydantic models without `.get`. + 3. Not raise AttributeError; not call span.record_exception. + """ + from unittest.mock import MagicMock + + from openai.types.completion_usage import ( + CompletionTokensDetails, + CompletionUsage, + ) + + from litellm.integrations.arize._utils import _set_usage_outputs + + span = MagicMock() + + # Plain OpenAI Pydantic model — has no `.get()` + usage = CompletionUsage( + completion_tokens=60, + prompt_tokens=40, + total_tokens=100, + completion_tokens_details=CompletionTokensDetails(reasoning_tokens=25), + ) + assert not hasattr(usage, "get"), "precondition: CompletionUsage must lack .get" + + response_obj = {"usage": usage} + + # Must not raise + _set_usage_outputs(span, response_obj, SpanAttributes) + + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, 100) + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_PROMPT, 40) + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, 60) + # reasoning_tokens for chat completions live in completion_tokens_details + span.set_attribute.assert_any_call( + SpanAttributes.LLM_TOKEN_COUNT_COMPLETION_DETAILS_REASONING, 25 + ) + + +def test_set_usage_outputs_pydantic_response_api_usage(): + """ + Same crash also affects Responses API with `output_tokens_details` as a + Pydantic model that lacks `.get()`. Verifies the responses-API path. + """ + from unittest.mock import MagicMock + + from litellm.integrations.arize._utils import _set_usage_outputs + from litellm.types.llms.openai import OutputTokensDetails + + # Build an object that mimics openai ResponsesAPI usage but lacks `.get` + # (uses a plain class — not BaseLiteLLMOpenAIResponseObject) + class PlainResponsesUsage: + def __init__(self): + self.total_tokens = 370 + self.input_tokens = 120 + self.output_tokens = 250 + self.output_tokens_details = OutputTokensDetails(reasoning_tokens=180) + + usage = PlainResponsesUsage() + assert not hasattr(usage, "get") + + span = MagicMock() + response_obj = {"usage": usage} + + _set_usage_outputs(span, response_obj, SpanAttributes) + + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, 370) + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_PROMPT, 120) + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, 250) + span.set_attribute.assert_any_call( + SpanAttributes.LLM_TOKEN_COUNT_COMPLETION_DETAILS_REASONING, 180 + ) + + class TestArizeLogger(CustomLogger): """ Custom logger implementation to capture standard_callback_dynamic_params. diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index dc344a433bcb..93c61e003d94 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -769,6 +769,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "uses_embed_content": {"type": "boolean"}, "supports_reasoning": {"type": "boolean"}, "supports_minimal_reasoning_effort": {"type": "boolean"}, + "supports_low_reasoning_effort": {"type": "boolean"}, "supports_none_reasoning_effort": {"type": "boolean"}, "supports_xhigh_reasoning_effort": {"type": "boolean"}, "supports_max_reasoning_effort": {"type": "boolean"},