jdZddlmZddlmZmZmZmZd dZ d dZ d dZ ddZ ddZ dd Z y )z-Utility helpers shared across LiteLLM models.) annotations)AnyCallableDictSetct|tr|St|dr&t|jr |j Si}t |dd}|||d<t |dd}|||d<|S#t $rY7wxYw)aProduce a dict view of a LiteLLM choice regardless of response type. LiteLLM may return raw dicts, Pydantic models, or dataclasses. Normalising to a dict here keeps downstream parsing logic consistent and backwards compatible with older client versions. model_dumpmessageNlogprobs) isinstancedicthasattrcallabler TypeErrorgetattr)choice normalisedr r s |/Users/manta/Documents/Projects/TheRoad-I1/backend/.venv/lib/python3.12/site-packages/opik/evaluation/models/litellm/util.pynormalise_choicers&$ v|$&2C2C)D $$& &"$Jfi.G ' 9vz40H!) :    sA11 A=<A=ct|}|jdrt|||y|jdrt|||yy)zAdjust/drop params for specific model families before calling LiteLLM. Currently handles: - GPT-5: only honours temperature=1 and does not return log probabilities. - DashScope Qwen: enforces constraints for logprobs / top_logprobs zgpt-5Nz dashscope/)_normalize_model_name startswith_apply_gpt5_filters_apply_qwen_dashscope_filters) model_nameparamsalready_warnedwarnnormalized_model_names rapply_model_specific_filtersr !sN2*=''0FND9'' 5%fndC6cHd|vr|S|jdd\}}|dvr|S|S)z>Normalize provider-prefixed model names for capability checks./)openai anthropic)split)rprovidermodel_without_providers rrr8s= *'1'7'7Q'?$H$**%% r!c g}d|vr7|d} t|}|t|dz dkDr|j d|fdD]}||vs|j |||ft ||||y#ttf$rd}YjwxYw)zApply GPT-5 specific parameter filters. Only honours temperature=1 and does not return log probabilities. Removing those eagerly avoids provider errors while the callback surfaces a one-time warning to the caller. temperatureNg?gư>r top_logprobs)floatr ValueErrorabsappend%_drop_unsupported_params_with_warning)rrr unsupportedvalue numeric_valueparams rrrDs*,K}% !!%LM  C (;$r<r>)rr=rr?rr@r<rA) rr=r;zlist[tuple[str, Any]]rr?rr@r<rA)__doc__ __future__rtypingrrrrrr rrrr2r!rrFs3"++2  %   .      %  F  % 0 "  "- " " % "  "r!