bi jddlmZddlZddlZddlZddlZddlmZddlm Z m Z m Z m Z m Z mZddlmZddlmZddlmZddlmZdd lmZmZmZe rdd lmZe d ed e f Zej<eZ ddZ!ddZ"ddZ# d dZ$d!dZ%d"dZ&d#dZ' d$ d%dZ(GddedZ)eddd d&dZ*y)') annotationsN)Mapping) TYPE_CHECKINGAnyCallableOptionalTypeVarUnion) TypedDict)client) run_helpers) warn_beta)InputTokenDetailsOutputTokenDetails UsageMetadata)genaiCz genai.Client)boundc\|jDcic] \}}| || c}}Scc}}w)z%Remove `None` values from dictionary.)items)dkvs d/home/obispo/Crisostomo_bridge/mision_env/lib/python3.12/site-packages/langsmith/wrappers/_gemini.py _strip_noners(WWY 8TQ!-AqD 88 8s ((cXd|vr&t|dtst|d|d<yyy)zFConvert `GenerateContentConfig` to `dict` for LangSmith compatibility.configN) isinstancedictvars)kwargss r_convert_config_for_tracingr"$s56*VH-=t"Dx 01x#Ec *|jd}|s|St|trAd|dg|jdd|jDcic] \}}|dvs ||c}}St|trt d|DrN|Dcgc]}d|d c}|jdd|jDcic] \}}|dvs ||c}}Sg}|D]_}t|t s|jdd}|jd g}g} g} |D]} t| t rd | vr1| d r,| j| d | jd | d d Jd | vr~| d } | jd d} | jdd}t|tr%tj|jd}n|}| jdd| d|dddd| vr=| d}| jd|jd|jdidd d| vsd| vs| jdxs| jd}|?t|t s|j}| jd|jd |jd|jd!id"d#t| ts| j| | jd | d | r$t d$| Drd%j| }n| r| nd&}|j||db||jdd|jDcic] \}}|dvs ||c}}S|Scc}}wcc}wcc}}wcc}}w)'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)c3<K|]}t|tyw)N)rstr).0items r z)_process_gemini_inputs..Es:z$$:sr'partstexttyper1 inline_data mime_type image/jpegdatar#utf-8 image_urldata:;base64,highurldetailr3r9functionResponsefunction_responsenameresponse)rCrD)r3rB function_call functionCallidargsrGrC argumentsr3rEc3DK|]}|jddk(yw)r3r1N)get)r-ps rr/z)_process_gemini_inputs..s")01AEE&MV+)s  )rMrr,rlistallrappendbytesbase64 b64encodedecodeto_dictjoin)inputsr%rrr.r*r(r'r0 text_parts content_partspartr4r5r7data_b64rBrEmessage_contents r_process_gemini_inputsr`*szz*%H  (C "(X>?ZZ( "(RA1TG,&,\\^VTQq@U7UAqDV  V LG'4({{662 GR0 " !AMD!$-!T>d6l&--d6l;)00&$v,1WX*d2*.}*=K(3 \(RI#.??63#?D *$6+1+;+;D+A+H+H+Q+/)00,716yk(/T282&!"047045G0H-)00,?0A0E0Ef0M4E4I4I,65*:&!" -4$8N,0HH_,E- .JM -8'1-'F4A4I4I4KM - 4 40?2?2C2CD2I4A4E4Ef4M9F9J9J6SU9V:*%& !"$D#."))$/%,,fd-KLCAMH!S)5B)&IM "IO8Em"O/ JKmV Lp!ZZ( "(RA1M> N N N % N2Nc:t|}|jdi}t|dr'|j}t |dd}t |dd}n3|jd}|jd}|jd}dd|jd||||d S) z*Extract invocation parameters for tracing.r temperaturemax_output_tokensNstop_sequencesgooglechatr)) ls_provider ls_model_type ls_model_namels_temperature ls_max_tokensls_stopls_invocation_params)rrMhasattrrbgetattr)prepopulated_invocation_paramsr!strippedrrb max_tokensstops r_infer_invocation_paramsrts6"H \\(B 'Fv}%(( V%8$? v/6jj/ ZZ 34 zz*+ !g.%# > r#c^|jdxsd}|jdxsd}|jdxsd}|jdxsd}|jdxs||z}i}|r)||d<td|dz |d <td|dz |d <i}|r||d <|rtd|dz |d <t|||td i|j D cic] \}} |  ||  c} }t d i|j D cic] \}} |  ||  c} } Scc} }wcc} }w)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)rMmaxrrrr) gemini_usage_metadatarvrwrxryrzrrrrs r_create_usage_metadatars.223GHMA2667OPUTU!!">?D11445KLQPQ!!"56 7  6 6 !#!,FL)69 )F27 23,/q2Dv2M+NK(!#,@[),/3IF3R,S[) ',&- 3 9 9 ;M1q}q!tM 0 4 : : <N1 q!tN    NOs D#$D# D)D)c t|dr|j}n5t|dr|j}ndt|dt |i}d}g}d}d|vr|dr~|dd}d|vr|d}d |vrX|d rR|d D]I}d|vr%|dr ||dz }|j d|dd -d |vr|d ~|d }|j d d } |j dd} t| tr%tj| jd} n| } |j dd| d| dddd|vsd|vs|j dxs|j d} | t| ts| j} |j d| j d| j d| j diddLd|vr(|dr#|d}nd|vr|d}|j d|d |D cgc]} | j ddk(s| }} |rh|xsdd |t|Dcgc]G\}}|dj dxsd!|d"||ddtj|dd#d$d%Ic}}d&}n(t!|d'kDs |r|dddk7r|d |d(}n|d |d(}|j d)}t#ddd*}|r t%|}|j d+r|dd ||d+|d,St|dtr |dd ||d-S|dd ||d-Scc} wcc}}w#t&$r&}t(j+d.|d/|icYd}~Sd}~wwxYw)0z$Process Gemini response for tracing.rX model_dumpr1rPN candidatesrr(r0r2r4r5r6r7r#r8r9r:r;r<r=r@rErFrGrCrHrIrK finish_reasonr3 assistantcall_functionrJ)rCrJ)rGr3indexr)r(r'r tool_calls)r(r'rusage_metadatarrrr)r(r'rrr)r(r'rrz"Error processing Gemini response: output)rnrXrror,rSrMrrTrUrVrWr enumeratejsondumpslenrr Exceptionloggerdebug)rDrdictcontent_resultr\r candidater(r]r4r5r7r^rErNritcresultr usage_dictes r"_process_generate_content_responsers7R$ 8Y '$$&E X| ,'')EWXvs8}EFE '+ 5 U<%8l+A.II%#I.g%''*: ' 0."!T>d6l*d6l:N)00&$v,1WX*d2tM7J7V*.}*=K(3 \(RI#.??63#?D *$6+1+;+;D+A+H+H+Q+/)00,716yk(/T282&!"-4$8N,0HH_,E- .JM -8'1-'F4A4I4I4KM - 4 40?2?2C2CD2I4A4E4Ef4M9F9J9J6SU9V:*%& !"K."^#i/Io4N$-o$>M u_"6]N  &.!I J"/SA!%%-?2RaS S *1T#!."+:!6 2!155d;Jqc{ *!"$&$7$?)-B4G 4T)U%   F" ! # mA.v6&@)#!.F*#!.F#34$1!!%  /?J ::l #"),#!.$\2",  &+S1%i0'%2&0  &i0'%2&0 ET B $ 9!=>(##$s]EL3&L3+BL3L(L("L3;A L- A9L3L3 L3( L33 M"<MM"M"c d|sdtddddSd}d}|D],} t|dr|jr||jz }|}.tddd}|r t|dr|j rt|j d r|j j}nt|j d r|j j}nqt|j d dt|j d dt|j d dt|j ddt|j ddd}t|}||dS#t$r#}tj d|Yd}~bd}~wwxYw#t$r"}tj d|Yd}~Zd}~wwxYw)z/Reduce streaming chunks into a single response.rPrr)r(rNr1zError processing chunk: rrXrrvrwrxryrz)rvrwrxryrzz+Error extracting metadata from last chunk: ) rrnr1rrrrrXrror) all_chunks full_text last_chunkchunkrrrs r_reduce_generate_content_chunksrs +aa  IJ9 9uf%%**UZZ' J 9%2aa%N Lz#349R9R:44i@!+!:!:!B!B!DJZ66 E!+!:!:!E!E!GJ/6&557KQ/3:&557OQR37>&557SUV718&557Mq1.5&557JA."J$"8 !C( O 9 LL3A37 8 8 9F L LLFqcJ K K Ls0)EC6F FE<<F F/ F**F/Fc|xsitjfd}tjfd}tjr|S|S)z9Create a wrapper for Gemini's `generate_content` methods.c t|tjddrtndtst ndt jtd}||i|SNllm)rCrun_type reduce_fnprocess_inputsprocess_outputs_invocation_params_fnr r"r traceablerr`r functoolspartialrtrHr! decorator is_streamingrCoriginal_generaterptextras rgeneratez_get_wrapper..generatess $F+))  9E541:F2D"+"3"3(*H#    ,y*+T.agenerates} $F+))  9E541:F2D"+"3"3(*H#    2Y014B6BBBBsA%A/(A-)A/)rwrapsr is_async)rrCrp tracing_extrarrrrs``` ` @r _get_wrapperrsf bF__&'=(=(__&'C(C($,,->?9MXMr#c,eZdZUded<ded<ded<y) TracingExtrazOptional[Mapping[str, Any]]metadatazOptional[list[str]]tagszOptional[ls_client.Client]r N)__name__ __module__ __qualname____annotations__rr#rrrs))  &&r#r)totalChatGoogleGenerativeAI)r chat_namec|xsi}t|jdxsi}|jdi}|jDcic]\}}|dk7s ||}}}|r||d<t |drAt |j dr+t |j j dr tdt |drIt |j dr3t|j j |||d|j _t |drIt |j d r3t|j j|||d |j _ t |d r}t |jdrgt |jj drGt|jj j |||d|jj _t |d r}t |jdrgt |jj d rGt|jj j|||d |jj _ |Scc}}w) 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. rrmmodelsgenerate_content __wrapped__zfThis Google Gen AI client has already been wrapped. Wrapping a client multiple times is not supported.F)rrgenerate_content_streamTaio) rrMpoprrnrr ValueErrorrrr)r rrrrprrtracing_extra_rests r wrap_geminirs"F"'RMM%%j17R8H%-\\2H"%M"',,.(A!z/1(()1:& ! FMM#5 6 FMM22M B A  vx WV]]rsG"  #()!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#