tPj RddlZddlmZddlmZmZmZddlmZddl m Z ddl m Z m Z ddlmZddlmZdd lmZmZmZerdd lmZdd lmZmZmZmZmZmZmZm Z m!Z!Gd d e Z"dFdZ#dFdZ$dFdZ%dFdZ&dFdZ'dFdZ(dGdZ)dFdZ*de+dzde+fdZ,ddde-dzde-dzfdZ.ddde/e fdZ0d e1dzde1fd!Z2ddd"edzddfd#Z3d"edzde-dzfd$Z4d e1de-dzfd%Z5ddd&ed e1d'e1fd(Z6ddd)e1dzddfd*Z7d+e+ddfd,Z8ddd-e1ddfd.Z9d/Z:de+dzfd0Z;d1Zde+fd4Z?ddd5e+ddfd6Z@ddd5e+d7e1ddfd8ZAddd-e1ddfd9ZBdHd:ZCde+dzdeDfd;ZEddd-e1ddfd<ZFdHd=ZGddd>e1ddfd?ZHd@ZIddd-ee+eJfd&edzdAeJddf dBZKdCeJdeDfdDZLdddAeJddfdEZMy)IN)Mapping) TYPE_CHECKINGAnyFinal)override)verbose_logger)BaseLLMObsOTELAttributessafe_set_attribute)should_redact_message_logging) safe_dumps) CallTypesStandardLoggingMCPToolCallStandardLoggingPayload)Span) AudioAttributesEmbeddingAttributesImageAttributesMessageAttributesMessageContentAttributesOpenInferenceMimeTypeValuesOpenInferenceSpanKindValuesSpanAttributesToolCallAttributesc:eZdZeedddeeeffdZy)ArizeOTELAttributesspanrkwargsc |jd}|r|d}t|tj|jddt |D]\}}tj d|}t||dt j|jdt||dt j|jddtd|dt|||yy) Nmessagescontent.rolezinput message extras (idx=)) getr r INPUT_VALUE enumerateLLM_INPUT_MESSAGESr MESSAGE_ROLEMESSAGE_CONTENT _safe_emit_emit_input_message_extras)rrr last_messageidxmsgprefixs f/home/oem/CyberBrain26-unified/.venv/lib/python3.12/site-packages/litellm/integrations/arize/_utils.py set_messagesz ArizeOTELAttributes.set_messages"s!**Z0 "*2,L **  B/ &h/ S*==>auE"4F815F5S5S4T)UWZW^W^_eWfg"ha 1 A ABCGGIr*0Q7. !  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K 4!8!8,G2231SE: ha ../ 0   (  ha 112 3   %cU! , $     9" r4c4|jdg}t|D]x\}}|jd}|%|jdrd|jd}|sA|dk(rt||j|t||jd||zy)Ndataurlb64_jsonzdata:image/png;base64,rr#)r&r(r rL IMAGE_URL)rrE image_attrsrPimagesiimageimg_urls r2r?r?s $$VR0Ff% J5))E" ?uyy4.uyy/D.EFG  6 tZ%<%as%CY O^^K0  t (C(C'DAaS%I: V%>>,7  t (D(D'EQqc%JL\ ]!^r4cz|jdg}t|D]\}}|jd}|rJ|dk(r t||jt |t||j d|t ||jd}|swt||j d|t |y)NrV embeddingrr#text)r&r(r rLr:EMBEDDING_VECTOREMBEDDING_TEXT) rrEembedding_attrsrP embeddingsr\embedding_itemembedding_vectorembedding_texts r2rArAs$((4J&z2>)--k: Av"++() "334AaS9$%  (++F3  "112!A37N# %r4c|jdg}t|D]%\}}|jd|}t|ds%|j}|dk(rQt|drE|j D]5} t| dst ||d|j| j7|dk(st|dsd } |j} | r t| d kDr| d } t| dd } t|d d } t ||j| t ||d|j| t ||d|j| (y) Noutputr#type reasoningsummaryrmrIr!r"rr$ assistant)r&r(rMr=rwryr MESSAGE_REASONING_SUMMARYrmr!lengetattrrLr+r*)rrErOrP output_itemsr\itemr1 item_typerymessage_content content_list first_content message_roles r2rBrBsS&**8R8L\*Y42231QC8tV$ II  #i(@<< 7F+&!(!I$G$G#HI  ) #i(@ O<z2_infer_open_inference_span_kind..Os   7 ) completionchatr]r`speech transcriptiongenerate_contentresponsevideosrealtime pass_through passthroughanthropic_messagesocrc3&K|]}|v ywrr;rs r2rz2_infer_open_inference_span_kind..gs _'7g  _r)filebatch containerfine_tuning_job)rUNKNOWNvaluer:lower EMBEDDINGRERANKER RETRIEVER GUARDRAILendswithTOOLAGENTanyLLMCHAINrrs @r2_infer_open_inference_span_kindr3sO *22888^))+G'*44:::7*339997*44:::w+"8*44:::/!W%59I9I&9Q*//555'!Ug%59O*00666    ,+..444 _-^ __*00666 & . . 4 44r4optional_toolsmetadata_toolsc^|r t|D]\}}t|tst|jdtr|jdnd}|sL|jd}|r!t |t j d|d||jd}|r!t |t j d|d||jd}|t |t j d|d tj||rt|trt|D]\}}t|ts|jd}|r!t |t jd |d||jd}|s_t |t jd |d|yyy) zFset tool attributes on span from optional_params or tool call metadatafunctionNnamer#z.name descriptionz .description parametersz .parametersz.tools.) r( isinstancer9r&r r LLM_TOOLSjsondumpslistLLM_INVOCATION_PARAMETERS) rrrr/rr tool_nametool_descriptionparamss r2_set_tool_attributesrms">2 ICdD)/9$((::NPT/Utxx +[_H V,I"4N,D,D+EQse5)QS\]'||M: "%//0#lC$ \\,/F!"%//0#kBJJv&% 0*^T:">2 ICdD)(I"%??@uER $xx 6 "%??@uLY$ ;~r4 attributesc tt|}tdt|| t|j d}|j dixsi}|j d}| t d|r|j dnd}t ||tt|} t|} t||||||tt|| | |j|||r|j d nd} t|| tt|| |j d} td t(||| tdt*|| tdt,||||| tdt.||| |y#t$r=} t!j"d | t%|d r|j'| Yd} ~ d} ~ wwxYw)zc Populates span with OpenInference-compliant LLM attributes for Arize and Phoenix tracing. zearly span kindoptional_paramslitellm_paramsstandard_logging_objectNz+standard_logging_object not found in kwargsmetadatarrstandard_logging_payloadrrrErPmodel_parametersrDz?[Arize/Phoenix] Failed to set OpenInference span attributes: %srecord_exceptionzsession/user attrsz response costzpassthrough normalizationzmcp tool attrs)_coerce_response_obj_for_attrsr,_set_early_span_kind_sanitize_optional_paramsr& ValueError_set_metadata_attributesr_extract_metadata_tools_extract_optional_tools_set_request_attributesrr3_set_model_paramsrF Exceptionrerrorr=r_set_session_and_user_attrs_set_response_cost_attr_maybe_normalize_passthrough_maybe_set_mcp_tool_attrs)rrrErresponse_obj_for_attrsrrrrrr model_paramseslps r2set_attributesr s%C<$P  "6fE'%!:6::FW;X!Y & +;R @ FBIOTmIn # +JK KF^266zBdh x@ 7 A 7 H%=+)/%  T>>Bf-Rj6::;MNpt $ n= d9OP56C#%@$PST 7sC#$  !:D&#Oef) %^`ab 4+ ,  ! !! $%sC2E11 F7:3F22F7rcNt|tsiS|jdd|S)N secret_fields)rr9poprs r2rrs' ot , . r4rcJ|!t||jt|yyr)r METADATAr )rrrPs r2rrs$4!4!4j6JKr4ct|tsy|jd}t|tr|jdSy)Nllmtoolsrr9r&)rllm_objs r2rrs9 h %\\%(G'4 {{7## r4cHt|tr|jdSdS)Nrrrs r2rrs"+5ot+L?  w 'VRVVr4rrc ||jdr&t||j|jdt|d|jdt||j|jdd|jdrt|d|jd|jdrt|d |jd|jd rt|d |jd t|d t |jd d|jdrt|d|jdt |dsy|jdrt|d|jd|jdrt|d|jdyy)Nmodelzllm.request.typercustom_llm_providerUnknown max_tokenszllm.request.max_tokens temperaturezllm.request.temperaturetop_pzllm.request.top_pzllm.is_streamingstreamFuserzllm.userr&idzllm.response.idzllm.response.model)r&r LLM_MODEL_NAME LLM_PROVIDERr:r=rs r2rrszz'4!:!:FJJwwxYw) a3Normalize a single tool_call (dict or Pydantic) into a stable shape: {"id": str|None, "type": str, "function": {"name": str|None, "arguments": str|None}} Arguments are coerced to a JSON string per OpenInference convention. Returns ``None`` when ``raw_tc`` cannot be coerced to a dict. Nrr argumentsr"rw)rr@)r"rwr)r0rr9r&r:rrr)raw_tctcrrr,s r2_normalize_tool_callrCsv&B b$ $RVVJ%78H*4Xt*D(,,v&$D(28T(B8<< $D  4 5 ::d#DffTlvz*!5  t9D sC C$#C$c d|DDcgc]}|s| }}tjd|iScc}w#t$rt|cYSwxYw)zRender a tool_calls list as a compact JSON string for OUTPUT_VALUE. Best-effort: returns ``str(tool_calls)`` if anything unexpected happens so OUTPUT_VALUE is never blanked on a malformed payload. c32K|]}t|ywr)rC)rrBs r2rz3_summarize_tool_calls_for_output..s(Wb)=b)A(WsrT)rrrr:)rTn normalizeds r2rKrKsU (WJ(W]1[\Q] ]zz<455^ :s 72277A Ar1ct|}|syt|D]\}}t|}||dtjd|}|dr#t ||dt j|d|d}|dr#t ||dt j|d|dt ||dt j|dy)aEmit ``MESSAGE_TOOL_CALLS.*`` for an assistant message that requested tool calls. Pure addition: only writes when ``tool_calls`` is non-empty. Accepts dicts or Pydantic message objects (e.g. ``litellm.Message``); the same applies to each tool_call entry. Nr#r"rrr@) rJr(rCrMESSAGE_TOOL_CALLSr r TOOL_CALL_IDTOOL_CALL_FUNCTION_NAME!TOOL_CALL_FUNCTION_ARGUMENTS_JSON) rr1rIrTtc_idxrArB tc_prefixr+s r2rNrNs(0J #J/ !& ) : ha 1 D DEQvhO d8 t {!4F4S4S3T%UWYZ^W_ `  ^ f: +Q1IIJK6   k? & +Q1SSTU; r4rIct|tsy|jd}|r t||dtj ||jd}|r t||dtj |t||||jd}t|tr|dtj}t|D]\}}t|ts|d|} |jd} | dvrc|jd} t| tsVt|| dtjdt|| dtj| | d vsd} |jd } t| tr| jd } nt| tr| } | st|jd }t|tr/|jd r|jdd}d|d|d } n$t|jd tr|d } | s]t|| dtjdt|| d| yy)aEmit additive attributes for an input message: - `MESSAGE_NAME` and `MESSAGE_TOOL_CALL_ID` (commonly set on tool-result messages so traces show which tool produced which result). - `MESSAGE_TOOL_CALLS.*` when an assistant message requested tools. - `MESSAGE_CONTENTS.*` structured content for list-shaped content (multimodal text + image parts). The plain `MESSAGE_CONTENT` write is still performed by the caller, so renderers that only read the legacy key continue to work. Nrr# tool_call_idr!rw)rmr5rm) image_urlr] input_imagerQrWsourcerV media_typez image/jpegzdata:z;base64,r]z .message_content.image.image.url)rr9r&r r MESSAGE_NAMEMESSAGE_TOOL_CALL_IDrNrMESSAGE_CONTENTSr(r:rMESSAGE_CONTENT_TYPEMESSAGE_CONTENT_TEXT)rr1rIrrPr!contents_prefixpart_idxr: part_prefix part_typermrWr]rSrTs r2r-r-sX gt $++f%D 4F81->-K-K,L!MtT!++n5L ha)>>? @  T673[[+G'4 $*81->-O-O,P!Q'0+ NHddD),-Qxj9K(I22xx'dC(&&-q)A)V)V(WX '&-q)A)V)V(WX CC-eT*))E*Cs+C!XXh/F!&$/FJJv4F%+ZZ l%K %j\&.9IJ#DHHUOS9"5k&&-q)A)V)V(WX '&-'GHO+ !r4ct|tsy|jdxsi}t|tsy|jd}|r$t|tj t ||jd}|rt|dt ||jdxsi}|jdxsi}tt|txr|jdxs#t|txr|jd}|s7|jd } | r$t|tjt | |jd } | rt|d t | |jd } | rt|d t | |jd} | rt|dt | yy)aEmit `SESSION_ID` / `USER_ID` / team metadata when source data exists. `SESSION_ID` is emitted only when an explicit end-user identifier exists (`metadata.user_api_key_end_user_id`). We deliberately do NOT fall back to `trace_id`, because that would create a distinct "session" for every single request and distort Arize's Session-grouping analytics. The `trace_id` is still emitted under its own `litellm.trace_id` key so spans remain filterable by trace. USER_ID is *only* emitted when no upstream path (model_params.user or optional_params.user) has already set it, to avoid overwriting an existing value with a possibly-different one from API-key metadata. Nruser_api_key_end_user_idtrace_idzlitellm.trace_idrrr!user_api_key_user_iduser_api_key_team_idzlitellm.team_iduser_api_key_team_aliaszlitellm.team_aliasuser_api_key_aliaszlitellm.key_alias) rr9r&r r SESSION_IDr:boolr&) rrrr session_idr`rr has_user_alreadyr'team_id team_alias key_aliass r2rr5s . 5.22:>D"H h % %?@J4!:!:C OL.22:>H4!3S]C#ZZ(9:@bO2667IJPbL" OT * J/B/B6/J I |T * G|/?/?/G !&<=  t^%;%;S\ J\\"89G4!2CLA %>?J4!5s:G||$89I4!4c)nEr4ct|tsy|jd}|y t|}t |d|t |d|y#tt f$rYywxYw)aEmit cost attributes from the StandardLoggingPayload when present. Uses the OpenInference `llm.cost.total` key so Arize / Phoenix can surface the cost in their "Total Cost" column. LiteLLM only tracks a single total in `StandardLoggingPayload.response_cost`, so we cannot split it into prompt/completion. We also keep the legacy `llm.response.cost` key for back-compat with any consumer querying it. N response_costzllm.cost.totalzllm.response.cost)rr9r&floatrrr )rrcost cost_values r2rrgsm . 5*..?D |!$K t-z:t0*= z "s A AAcN|syt|j}d|vxsd|vS)NFrr)r:rrs r2_is_passthrough_call_typerr}s/ ^))+G G # @~'@@r4ct|tr|jdnd}t|syt |ry|jdxsi}t|tr|jdnd}t|trt ||jdt |||}t|tsyt||y)amSurface input/output text for passthrough routes (e.g. Bedrock InvokeModel) so the parent span renders as more than `usage` numbers. Only runs when `call_type` is a passthrough variant. Reads from: - `kwargs["additional_args"]["complete_input_dict"]` for input - the coerced response (or `kwargs["original_response"]`) for output All emits are best-effort: if the provider shape isn't recognized the helper exits silently. Existing chat/completion paths never enter this helper because their call_type doesn't contain "passthrough". TEMPORARY BRIDGE: passthrough handlers don't populate the StandardLoggingPayload `messages` field today (they call `transform_response(messages=[])`), so the input is only available via `additional_args.complete_input_dict`. The proper fix is upstream in `base_passthrough_logging_handler._create_response_logging_payload()`: once that populates SLP `messages`/`response`, every callback gets passthrough I/O (with central redaction) for free and this helper's `complete_input_dict` fallback can be deleted. See follow-up issue. rNadditional_argscomplete_input_dictr)rr9r&rrr !_set_passthrough_input_attributes_parse_passthrough_response"_set_passthrough_output_attributes) rrraw_response_objcoerced_response_objrrrtruparsed_responses r2rrs6EOOgimDn/33K@txI $Y /%V,$ZZ(9:@bOHRSbdhHi/--.CDos%t,)$0C0G0G 0ST99IK_aghO ot ,&t_=r4c8t|tr|syd}t|D]1}t|tst |j d}|s1n|rt |tj|t|D]\}}t|tstjd|}|j d}|r t ||dtj|t |j d}||t ||dtj|y)zJRender passthrough request messages into INPUT_VALUE + LLM_INPUT_MESSAGES.Nr!r#r$)rrreversedr9r;r&r rr'r(r)rr*r+)rr last_textr0r/r1r$rms r2rvrvs x &8I! c4 $SWWY%78I  4!;!;YGh'S#t$ "556au=wwv  (!-::;<  CGGI./   (!-==>? r4r{c|jd}t|tr|rg}|D]G}t|tst|jdts4|j |dIdj d|D}|r~t|tj|tjd}t||dtj|jddt||dtj||jd }t|tr|r|d }t|tr|jd } t| trt| jd} | rt|tj| tjd}t||dtj| jddt||dtj| y y y y y y ) zDRender passthrough response into OUTPUT_VALUE + LLM_OUTPUT_MESSAGES.r!rmz c3&K|] }|s| ywrr;)rts r2rz5_set_passthrough_output_attributes..s#:!A#:sz.0r#r$rzrHrrIN)r&rrr9r:r7r8r rrLrMrr*r+r;) rr{rtextsr:joinedr1rHfirstr0rms r2rxrxs*--i8L,%,  +D$%*TXXf5Es*K T&\* + #:u#::  t^%@%@& I&::;2>F (!-::;<##FK8  (!-==>? %((3G'4 Wqz eT "9-C#t$*3779+=>&t^-H-H$O . B BC2FF&!(!$5$B$B#CD 4 '!(!$5$E$E#FG% #&- r4cg}t|tr|j|t|tr||ur|j||D]r}d|vrid|vred|vra|jd}t|tr+ t j |}t|tr|cS t|tsl|cS|cSt|tr|jdnd}t|tr|St|tr* t j |}t|tr|S yy#t$rYwxYw#t$rYywxYw)zCReturn a dict view of the provider response for passthrough routes.rr!rHoriginal_responseN)rr9r7r&r:rr1r)ryrzr candidates candidateinnerr3originals r2rwrw sLJ&-./"D).>FZ.Z*+  "y 'AiW`F`MM*-E%%!ZZ.F!&$/% 0%&  ":DFD9Qfjj!45W[H(D!(C  ZZ)F&$' ( %!   s$<&D0&D?0 D<;D<? E  E rzc<|y|jdtjjk7ry|jd}|r|jdnd}|y|jdxs|jd}|rt |t j |t|ry|jd}|Wt |t jt|t |t jtjjt||y)aWRender `call_mcp_tool` spans as OpenInference TOOL spans. MCP tool calls carry neither `messages` nor `choices`, so the generic extraction paths leave Input/Output blank. The tool name and arguments live in `metadata.mcp_tool_call_metadata`; the result is an MCP `CallToolResult` whose `content` is a list of typed parts. Nrrmcp_tool_call_metadatarnamespaced_tool_namer@)r&r rrr r TOOL_NAMEr r'r INPUT_MIME_TYPErJSON_set_mcp_tool_output)rrrrzrmcp_metarr@s r2rr2s '##K0I4K4K4Q4QQ.22:>HckF^9_quH||F+Sx||.Ys/eUY dV0DD0P/es)rrall)r!s r2_has_only_text_partsrXs#'4( ( eC/e]d/e,eer4ct|tsy|jd}t|}|rZt |rOt |t j|t |t jtjjy|jd}|r|n||n|}|yt |t jt|t |t jtjjy)Nr!structuredContent)rrr&r;rr rrLOUTPUT_MIME_TYPErTEXTrr r)rrzr!rm structuredpayloads r2rr\s *G 4155i@G*73D $W-4!Y>^>^>d>der4)rrr)rrrN)Nrcollections.abcrtypingrrrtyping_extensionsrlitellm._loggingrElitellm.integrations.opentelemetry_utils.base_otel_llm_obs_attributesr r *litellm.litellm_core_utils.redact_messagesr *litellm.litellm_core_utils.safe_json_dumpsr litellm.types.utilsr rropentelemetry.tracer*litellm.integrations._types.open_inferencerrrrrrrrrrrFr>r?r@rArBrrCr:rrrrwr r9rrrrrrr,rrr;r0rJrCrKrNr-rrrfrrrrvrxrwobjectrrrr;r4r2rs\ #,,&+B]](   '2'` ;# L J ^*6Y8&,9 x75sTz75c75t-v-td{-TX[_T_-`HgHg4H`CaHgVtd{tL6LS4ZLPTL cDjTD[WTWdTkW%R %R5%R %R  %RPBFB$+BdB"AcA4Avt:3:6"Ot ODcNT$94 C 63D@JVJSJ4JDJZ/Ff/Fd/FY]/Fd>,AtAA3> 3> 3>  3>lD,V,d,t,^$N#5 #5 CK #55t;#5! #5  #5Lf&fTffvfVffr4