=Ki jSSKJr SSKrSSKrSSKrSSKrSSKJr SSKJ r J r J r J r J r Jr SSKJr SSKJr SSKJr SSKJr SS KJrJrJr \ (aSS KJr \ "S \S \ 4S 9r\R<"\5r SSjr!SSjr"SSjr#S Sjr$S!Sjr%S"Sjr&S#Sjr'S$S%Sjjr("SS\SS9r)\SSS.S&Sjj5r*g)') annotationsN)Mapping) TYPE_CHECKINGAnyCallableOptionalTypeVarUnion) TypedDict)client) run_helpers) warn_beta)InputTokenDetailsOutputTokenDetails UsageMetadata)genaiCz genai.Client)boundcbUR5VVs0sH upUcM X_M snn$s snnf)z%Remove `None` values from dictionary.)items)dkvs \/var/www/html/dynamic-report/venv/lib/python3.13/site-packages/langsmith/wrappers/_gemini.py _strip_noners(WWY 8YTQ!DADY 88 8s ++cfSU;a+[US[5(d[US5US'ggg)zFConvert `GenerateContentConfig` to `dict` for LangSmith compatibility.configN) isinstancedictvars)kwargss r_convert_config_for_tracingr"$s86*VH-=t"D"Dx 01x#Ec URS5nU(dU$[U[5(aESUS./URS5S.UR5VVs0sHup#US;dM X#_M snnE$[U[5(Ga^[ SU55(aUUVs/sHnSUS.PM snURS5S.UR5VVs0sHup#US;dM X#_M snnE$/nUGHn[U[ 5(dMURSS5nURS /5n/n /n UGHn [U [ 5(GaS U ;a7U S (a-U RU S 5 U RS U S S .5 MWS U ;aU S n U RS S5n U RSS5n[U[5(a&[R"U5RS5nOUnU RSSU SU3SS.S.5 MSU ;a>U SnU RSURS5URS05S.S.5 GM&SU ;dSU ;aU RS5=(d U RS5nUbn[U[ 5(dUR5nU RSURS 5URS5URS!05S".S#.5 GMGMGM[U [5(dGMU RU 5 U RS U S .5 GM U (a)[ S$U 55(aS%RU 5nO U (aU OS&nURUUS.5 GM UURS5S.UR5VVs0sHup#US;dM X#_M snnE$U$s snnfs snfs snnfs snnf)'uProcess Gemini inputs to normalize them for LangSmith tracing. Example: ```txt {"contents": "Hello", "model": "gemini-pro"} → {"messages": [{"role": "user", "content": "Hello"}], "model": "gemini-pro"} {"contents": [{"role": "user", "parts": [{"text": "What is AI?"}]}], "model": "gemini-pro"} → {"messages": [{"role": "user", "content": "What is AI?"}], "model": "gemini-pro"} ``` contentsuser)rolecontentmodel)messagesr))r%r)c3B# UHn[U[5v M g7f)N)rstr).0items r )_process_gemini_inputs..Es:z$$$sr'partstexttyper2 inline_data mime_type image/jpegdatar#utf-8 image_urldata:;base64,highurldetailr4r:functionResponsefunction_responsenameresponse)rDrE)r4rC function_call functionCallidargsrHrD argumentsr4rFc3H# UHoRS5S:Hv M g7f)r4r2N)get)r-ps rr/r0s)5BEE&MV+]s " )rNrr,rlistallrappendbytesbase64 b64encodedecodeto_dictjoin)inputsr%rrr.r*r(r'r1 text_parts content_partspartr5r6r8data_b64rCrFmessage_contents r_process_gemini_inputsra*szz*%H  (C  "(X>?ZZ( "(R18TG,&,\\^V^TQq@U7UDAD^V  G'4(({{662 GR0 " !D!$--!T>d6l&--d6l;)00&$v,1WX*d2*.}*=K(3 \(RI#.??63#?D *$66+1+;+;D+A+H+H+Q+/)00,716yk(/T282&!"047045G0H-)00,?0A0E0Ef0M4E4I4I,65*:&!" -4$8N,0HH_,E- .JM -8'1-'F'F4A4I4I4KM - 4 40?2?2C2CD2I4A4E4Ef4M9F9J9J6SU9V:*%& !" 9 9O($D#.."))$/%,,fd-KLC"H!S)5B)&&IM "IO8Em"O/ JKm p!ZZ( "(R1 r#cURS5=(d SnURS5=(d SnURS5=(d SnURS5=(d SnURS5=(d X-n0nU(a(X6S'[SUS- 5US '[SUS- 5US '0nU(aXGS 'U(a[SUS- 5US '[UUU[S 0UR 5VV s0sH upU cM X_M sn nD6[ S 0UR 5VV s0sH upU cM X_M sn nD6S 9$s sn nfs sn nf)z2Convert Gemini usage metadata to LangSmith format.prompt_token_countrcandidates_token_countcached_content_token_countthoughts_token_counttotal_token_count cache_readi@ cache_read_over_200k over_200k reasoning) input_tokens output_tokens total_tokensinput_token_detailsoutput_token_details)rNmaxrrrr) gemini_usage_metadatarwrxryrzr{rrrrs r_create_usage_metadatars.223GHMA2667OPUTU!!">?D11445KLQPQ!!"56 7  6 !#!,FL)69 )F27 23,/q2Dv2M+NK(!#,@[),/3IF3R,S[) ',&- 3 9 9 ;M ;qtqt ;M 0 4 : : <N <tqt <N    NOs> E  E 0 E=Ec[US5(aUR5nO:[US5(aUR5nOS[US[ U550nSn/nSnSU;GaUS(GaUSSnSU;GaUSnS U;GaUS (GawUS GHmnSU;a*US(a X'S- nUR SUSS .5 M4S U;aUS bUS nUR S S 5n UR SS5n [U [5(a&[R"U 5RS5n OU n UR SSU SU 3SS.S.5 MSU;dSU;dMUR S5=(d UR S5n U cGM[U [5(dU R5n UR SU R S5U R S5U R S05S.S.5 GMp SU;aUS(aUSnOSU;aUSnUR SUS .5 UV s/sHoR S5S:XdMU PM nn U(avU=(d SS U[U5VVs/sHNunnUSR S5=(d S!U3S"UUSS[R"USS#5S$.S%.PMP snnS&.nO/[!U5S':dU(aUSSS:waUS US(.nOUS US(.nUR S)5n[#SSSS*9nU(a [%U5nUR S+5(aUSS UUS+US,.$[US[5(a USS UUS-.$USS UUS-.$s sn fs snnf![&a&n[(R+S.U35 S/U0sSnA$SnAff=f)0z$Process Gemini response for tracing.rY model_dumpr2rQN candidatesrr(r1r3r5r6r7r8r#r9r:r;r<r=r>rArFrGrHrDrIrJrL finish_reasonr4 assistantcall_functionrK)rDrK)rHr4indexr)r(r'r tool_calls)r(r'rusage_metadatarrrr)r(r'rrr)r(r'rrz"Error processing Gemini response: output)rorYrrpr,rTrNrrUrVrWrXr enumeratejsondumpslenrr Exceptionloggerdebug)rErdictcontent_resultr]r candidater(r^r5r6r8r_rFrOritcresultr usage_dictes r"_process_generate_content_responsersOR$ 8Y ' '$$&E X| , ,'')EWXvs8}EFE '+ 5 U<%8%8l+A.II%#I.g%''*:*: ' 0!T>d6l*6l:N)00&$v,1WX*d2tM7J7V*.}*=K(3 \(RI#.??63#?D *$66+1+;+;D+A+H+H+Q+/)00,716yk(/T282&!"-4$8N,0HH_,E- .JM -8'1-'F'F4A4I4I4KM - 4 40?2?2C2CD2I4A4E4Ef4M9F9J9J6SU9V:*%& !"K!1^#i/Io4N$-o$>M u_"6]N  &.!I J"/SA%%-?2Ra S *1T#!."+:!6 "72!155d;Jqc{ *!"$&$7$?)-B4G 4T)U% "7  F" ! # mA.v6&@)#!.F*#!.F#34$1!!%  /?J ::l # #"),#!.$\2",  &+S11%i0'%2&0  &i0'%2&0 ET B $ 9!=>(##$s]E.N%4*N%#B)N% N(N.#N%AN &BN%.!N% N% N%% O/O OOc U(dS[SSSS9S.$SnSnUH6n[US5(aUR(aXR- nUnM8 [SSSS9nU(Ga [US5(aUR (a[UR S 5(aUR R5nO[UR S 5(aUR R5nOq[UR S S5[UR S S5[UR S S5[UR SS5[UR SS5S.n[U5nUUS.$![a$n[R SU35 SnAGMSnAff=f![a"n[R SU35 SnAN]SnAff=f)z/Reduce streaming chunks into a single response.rQrr)r(rNr2zError processing chunk: rrYrrwrxryrzr{)rwrxryrzr{z+Error extracting metadata from last chunk: ) rror2rrrrrYrrpr) all_chunks full_text last_chunkchunkrrrs r_reduce_generate_content_chunksrs +aa  IJ 9uf%%%**ZZ' J %2aa%N Lz#3449R9R:44i@@!+!:!:!B!B!DJZ66 EE!+!:!:!E!E!GJ/6&557KQ/3:&557OQR37>&557SUV718&557Mq1.5&557JA."J$"8 !C( O 9 LL3A37 8 8 9F L LLFqcJ K K Ls02E9*D F*9 F'F""F'* G4GGFc^^^^^U=(d 0m[R"T5UUUUU4Sj5n[R"T5UUUUU4Sj5n[R"T5(aU$U$)z9Create a wrapper for Gemini's `generate_content` methods.c >[U5 [R"STST(a[OS[T(d[ OS[ R"[T5S.TD6nU"T5"U0UD6$Nllm)rDrun_type reduce_fnprocess_inputsprocess_outputs_invocation_params_fnr r"r traceablerrar functoolspartialrurIr! decorator is_streamingrDoriginal_generaterqtextras rgenerate_get_wrapper..generatesq $F+))  9E541:F2D"+"3"3(*H#    *+T# [U5 [R"STST(a[OS[T(d[ OS[ R"[T5S.TD6nU"T5"U0UD6IShvN $N7frrrs r agenerate_get_wrapper..ageneratesz $F+))  9E541:F2D"+"3"3(*H#    014B6BBBBsA1A;4A95A;)rwrapsr is_async)rrDrq tracing_extrarrrrs``` ` @r _get_wrapperrst bF__&'==(=(__&'CC(C($,,->??9MXMr#c4\rSrSr%S\S'S\S'S\S'Srg ) TracingExtraizOptional[Mapping[str, Any]]metadatazOptional[list[str]]tagszOptional[ls_client.Client]r rN)__name__ __module__ __qualname____firstlineno____annotations____static_attributes__rr#rrrs))  &&r#r)totalChatGoogleGenerativeAI)r chat_namec|U=(d 0n[URS5=(d 05nURS05nUR5VVs0sHupVUS:wdM XV_M nnnU(aX7S'[ US5(aK[ UR S5(a0[ UR R S5(a [S5e[ US5(aK[ UR S5(a0[UR R UUUSS9UR l[ US5(aK[ UR S 5(a0[UR RUUUS S9UR l [ US 5(a[ URS5(ai[ URR S5(aD[URR R UUUSS9URR l[ US 5(a[ URS5(ai[ URR S 5(aD[URR RUUUS S9URR l U$s snnf) a Patch the Google Gen AI client to make it traceable. !!! warning **BETA**: This wrapper is in beta. Supports: - `generate_content` and `generate_content_stream` methods - Sync and async clients - Streaming and non-streaming responses - Tool/function calling with proper UI rendering - Multimodal inputs (text + images) - Image generation with `inline_data` support - Token usage tracking including reasoning tokens Args: client: The Google Gen AI client to patch. tracing_extra: Extra tracing information. chat_name: The run name for the chat endpoint. Returns: The patched client. Example: ```python from google import genai from google.genai import types from langsmith import wrappers # Use Google Gen AI client same as you normally would. client = wrappers.wrap_gemini(genai.Client(api_key="your-api-key")) # Basic text generation: response = client.models.generate_content( model="gemini-2.5-flash", contents="Why is the sky blue?", ) print(response.text) # Streaming: for chunk in client.models.generate_content_stream( model="gemini-2.5-flash", contents="Tell me a story", ): print(chunk.text, end="") # Tool/Function calling: schedule_meeting_function = { "name": "schedule_meeting", "description": "Schedules a meeting with specified attendees.", "parameters": { "type": "object", "properties": { "attendees": {"type": "array", "items": {"type": "string"}}, "date": {"type": "string"}, "time": {"type": "string"}, "topic": {"type": "string"}, }, "required": ["attendees", "date", "time", "topic"], }, } tools = types.Tool(function_declarations=[schedule_meeting_function]) config = types.GenerateContentConfig(tools=[tools]) response = client.models.generate_content( model="gemini-2.5-flash", contents="Schedule a meeting with Bob and Alice tomorrow at 2 PM.", config=config, ) # Image generation: response = client.models.generate_content( model="gemini-2.5-flash-image", contents=["Create a picture of a futuristic city"], ) # Save generated image from io import BytesIO from PIL import Image for part in response.candidates[0].content.parts: if part.inline_data is not None: image = Image.open(BytesIO(part.inline_data.data)) image.save("generated_image.png") ``` !!! version-added "Added in `langsmith` 0.4.33" Initial beta release of Google Gemini wrapper. rrnmodelsgenerate_content __wrapped__zfThis Google Gen AI client has already been wrapped. Wrapping a client multiple times is not supported.F)rrgenerate_content_streamTaio) rrNpoprrorr ValueErrorrrr)r rrrrqrrtracing_extra_rests r wrap_geminirsFF"'RMM%%j17R8H%-\\2H"%M"',,.(.!z/.()1:& !! FMM#5 6 6 FMM22M B B A  vx  WV]]rsE"  #()!9RR Cu^S012   8 $9 2 BJ$(26 8&RT$n=H-1 4N4N 4N%)4N* 4N  4N  4Nn'9E'  -1- h h*h h  h hr#