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Dxj$AB + ~&2 () [<.)  +()*6 ' [+,- r#c i}t|dg.t|ddgtj|t|dgt|dgt|ddgt|dgt|dgt t|dg||SNrUrVrrr)r3r4rXrYrQrs r!"_GenerateImagesParameters_to_mldevrW1s !) +y!-  *d; :;  +z".^X.[8*0MN +z"."4 hZ#@)L r#c i}t|dg.t|ddgtj|t|dgt|dgt|ddgt|dgt|dgt t|dg||SrV)r3r4rXrYrTrs r!#_GenerateImagesParameters_to_vertexrYGs !) +y!-  *d; :;  +z".^X.[8*0MN +z".#Dxj$A9M r#c <i}t|dgt|dgt|dgt|dg1t|dgt|dgDcgc]}t||c}t|dg#t|dgtt|dg||Scc}wNr^r_rrpositivePromptSafetyAttributes!positive_prompt_safety_attributes)r3r4_GeneratedImage_from_mldev_SafetyAttributes_from_mldevrLs r!"_GenerateImagesResponse_from_mldevr`]s!) +)*+7'(${=N*+  + ~&2 |$ [<.)  ++,-9 )* [./0  +'(4 M NN +)*+7 '( [,-.  +()*6 ' [+,-  +()*6 O PP + ~&2 %[<.99E  +*+,8 *+[+=*>?  4D) D  +x , E FF +-./; G   s"H. c Li}t|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|d gt|dd gt|d gt|d gt|dd gt|d gt|d gt|dd gt|d gt|d gt|ddgt|d gt|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dg$t|ddgtt|dg|t|dg2t|ddgt|dgDcgc]}t||c}t|dg$t|ddgt t|dg|t|dgt|ddgt|dg|Scc}w)Nrfrrrrrgrhrirrrrjrrrk pubsubTopicrrrPrSrl generateAudiormrrnrrrorpr)r3r4_Image_to_vertex(_VideoGenerationReferenceImage_to_vertex_VideoGenerationMask_to_vertexrLs r!_GenerateVideosConfig_to_vertexrzs]!) +*+,8 }% [-./  +()*6 |$ [+,-  +w+u-tK%/IJ +*+,8 () [-./  +x ,v.[6(0KL +'(4 }% [>*+  + ~&2 |$ [<.)  ++,-9 )* [./0  +'(4 }% [>*+  +)*+7 '( [,-.  +()*6 ' [+,-  +()*6 ' [+,-  + ~&2 %kL>:IF  +*+,8 *+[+=*>?  5T9 E  +x ,  &tK&'BIN  +-./; +, [012 ) s-J! c i}t|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|ddg$t|dgtt|ddg|t|ddg$t|dgtt|ddg||S)NrrdoneerrorrgenerateVideoResponseresult)r3r4"_GenerateVideosResponse_from_mldevr5s r!#_GenerateVideosOperation_from_mldevrss%!) +x ,VHd;9: + |$0ZL${ZL"AB +x ,VHd;9: +y!-WItK';< + $;<=I  * z+BC Di  + $;<=I  * z+BC Di  r#c i}t|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dg#t|dgtt|dg|t|dg#t|dgtt|dg||S)Nrrr|r}rr)r3r4#_GenerateVideosResponse_from_vertexr5s r!$_GenerateVideosOperation_from_vertexrs!) +x ,VHd;9: + |$0ZL${ZL"AB +x ,VHd;9: +y!-WItK';< + |$0  + zl +Y  + |$0  + zl +Y  r#c "i}t|dg.t|ddgtj|t|dgt|dgt|ddgt|dgt|dg$t|ddgt t|dg|t|dg$t|ddgt t|dg|t|dgt t|dg|t|dgtt|dg||S NrUrVrrimagevideosourcer)r3r4rXrYrq_Video_to_mldev_GenerateVideosSource_to_mldevrsrs r!"_GenerateVideosParameters_to_mldevrs% !) +y!-  *d; :;  +z".^X.[8*0MN +y!- ![7)4i@  +y!- ![7)4i@  +z"."4 hZ#@)L +z"."4 hZ#@)L r#c "i}t|dg.t|ddgtj|t|dgt|dgt|ddgt|dgt|dg$t|ddgt t|dg|t|dg$t|ddgt t|dg|t|dgt t|dg|t|dgtt|dg||Sr)r3r4rXrYrw_Video_to_vertex_GenerateVideosSource_to_vertexrzrs r!#_GenerateVideosParameters_to_vertexrs% !) +y!-  *d; :;  +z".^X.[8*0MN +y!- !kG95yA  +y!- !kG95yA  +z".#Dxj$A9M +z".#Dxj$A9M r#c (i}t|dg1t|dgt|dgDcgc]}t||c}t|dgt|dgt|dgt|dgt|dgt|dg|Scc}w)NgeneratedSamplesgenerated_videosraiMediaFilteredCountrai_media_filtered_countraiMediaFilteredReasonsrai_media_filtered_reasons)r3r4_GeneratedVideo_from_mldevrLs r!rr s!) +*+,8 [+=*>?  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[8*5  (i 8  +/01= #$ [234  +123? %& [456 ) rc i}t|dgt|ddgt|dgt|dg$t|ddgtt|dg|t|dg$t|ddgtt|dg||SNrrrr)r3r4rqrr5s r!rrMs!) +z".14 hZ3P +y!- ![7)4i@  +y!- ![7)4i@ r#c i}t|dgt|ddgt|dgt|dg$t|ddgtt|dg|t|dg$t|ddgtt|dg||Sr)r3r4rwrr5s r!rrhs!) +z".14 hZ3P +y!- !kG95yA  +y!- !kG95yA r#c i}t|dg#t|dgtt|dg|t|dg't|dgt|dgDcgc]}|c}|Scc}w)N_selfror)r3r4_Image_from_vertexrLs r!_GeneratedImageMask_from_vertexrs!) +y!- 4 gY7C  +z".H:kH:1NOO  Ps A) c i}t|dg#t|dgtt|dg|t|dgt|dgt|dgt|dg#t|dgtt|dg||S)NrrraiFilteredReasonrai_filtered_reasonsafety_attributes)r3r4_Image_from_mldevr_r5s r!r^r^s!) +y!-  ${WI6 B  ++,-9  [./0  +y!- $T+y%A9M r#c bi}t|dg#t|dgtt|dg|t|dgt|dgt|dgt|dg#t|dgtt|dg|t|dgt|dgt|dg|S)Nrrrrrrenhanced_prompt)r3r4rrcr5s r!rrs!) +y!-  4 gY7C  ++,-9  [./0  +y!- %d; &BIN  +z".&'kH:)FG r#c ji}t|dg#t|dgtt|dg||S)Nr)r3r4_Video_from_mldevr5s r!rrsC!) +y!-  ${WI6 B r#c ji}t|dg#t|dgtt|dg||S)Nrr)r3r4_Video_from_vertexr5s r!rrsC!) +y!-  4 gY7C r#c i}t|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|d gt|d gt|d gt|d gt|d gt|d gt|d gt|d gt|d gt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dg#t|d gtt|dg|t|d!gt|d"gt|d!gt|d#gt|d#gt|d#gt|d$gt|d%gt|d$gt|d&gt|d'gt|d&gt|d(gt|d)gt|d(gt|d*g td+|S),Nrr3rrr$r4rrenable_affective_dialogenableAffectiveDialogrrr rrr r!r rr r rrrrrrrr2rr"r#rr rr%r&rrrrenable_enhanced_civic_answerszFenable_enhanced_civic_answers parameter is not supported in Vertex AI.)r3r4r5rr5s r!rrs !) +012>  [345  +./0<  [123  +)*+7%&[;L:M(NO +)*+7%&[;L:M(NO +123? ! [456  ++,-9  [./0  + |$0ZL${ZL"AB ++,-9%&[;N:O(P +*+,8%&[;M:N(O +*+,8%&[;M:N(O ++,-9  [./0  +,-.:  [/01  +-./;  [012  +)*+7%&[;L:M(NO +()*6_%tK:J9K'LM +x ,VHd;9: +()5  / 0)  +()*6_%tK:J9K'LM + '3]OT+ %GH +)*+7%&[;L:M(NO +y!-VHd; :; +y!-VHd; :; +789E P  r#c i}t|dg.t|ddgtj|t|dg|Srrrs r!_GetModelParameters_to_mldevri rr#c i}t|dg.t|ddgtj|t|dg|Srrrs r!_GetModelParameters_to_vertexry rr#ci}t|dg tdt|dgt|dgt|dg|S)N auth_configz5auth_config parameter is not supported in Gemini API. enable_widget enableWidgetrr5s r!_GoogleMaps_to_mldevr sS!) + '3 L MM +()5^$d;8I&JK r#ci}t|dg tdt|dg tdt|dgt|dgt|dg|S)Nexclude_domainsz9exclude_domains parameter is not supported in Gemini API.blocking_confidencez=blocking_confidence parameter is not supported in Gemini API.time_range_filtertimeRangeFilterrr5s r!_GoogleSearch_to_mldevr s!) +)*+7 C  +-./; G  ++,-9%&[;N:O(P r#c i}t|dg,t|dgtjt|dgt|dgt|dgt|dg|S)NbytesBase64Encoded image_bytesr1r0r3r4base_tt_bytesr5s r!rr so!) +,-.: tK*>)?@A  + |$0[M4 j\#BC r#c i}t|dgt|dgt|dgt|dg,t|dgtjt|dgt|dgt|dgt|dg|S)NgcsUrigcs_urirrr1r0rr5s r!rr s!) +z".YKkH:!>? +,-.: tK*>)?@A  + |$0[M4 j\#BC r#c i}t|dg tdt|dg,t|dgtjt|dgt|dgt|dgt|dg|S)Nrz1gcs_uri parameter is not supported in Gemini API.rrr0r1)r3rr4rrr5s r!rqrq s!) + {#/ H II + '3 tK-9:  + }%1ZL${[M"BC r#c i}t|dgt|dgt|dgt|dg,t|dgtjt|dgt|dgt|dgt|dg|S)Nrrrrr0r1rr5s r!rwrw s!) + {#/XJ[9+ >? + '3 tK-9:  + }%1ZL${[M"BC r#c ji}t|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dg.t|dd gtj|t|dg|S N page_size_querypageSize page_token pageTokenfilter query_baserV models_urlr3r4rX t_models_urlrs r!_ListModelsConfig_to_mldevr !) + }%1*-tK+/O + ~&2 ; [<.)  +z".8,d; .KL + ~&2  z4 l^#DE r#c ji}t|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dg.t|dd gtj|t|dg|Srrrs r!_ListModelsConfig_to_vertexr rr#cTi}t|dgt|t|dg||SNr)r3rrs r!_ListModelsParameters_to_mldevr@ s8 !) +z".Dxj19 r#cTi}t|dgt|t|dg||Sr)r3rrs r!_ListModelsParameters_to_vertexrN s8 !) +z".Dxj19 r#c Ni}t|dgt|dgt|dgt|dgt|dgt|dgt|dgDt|dgtjt|dgDcgc]}t ||c}|Scc}wNr^r_ nextPageTokennext_page_tokenrmodels)r3r4rXt_extract_models_Model_from_mldevrLs r!_ListModelsResponse_from_mldevr\ s!) +)*+7'(${=N +y!- #Dwi$@)L  +-./; ! [012  + '3 {]O<=$= = 6 >s ?F 9 F c *i}t|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dg#t|dgtt|dg|t|d gt|d gt|d gt|d g#t|d gtt|d g|t|d gt|d gt|d gt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dgt|dg|S)N function_call functionCallcode_execution_resultcodeExecutionResultexecutable_codeexecutableCode file_datafileDatafunction_responsefunctionResponse inline_data inlineDatatextthoughtthought_signaturethoughtSignaturevideo_metadata videoMetadata)r3r4rr7r5s r!rmrm s!) +()5^$d;8I&JK +/01=  [234  +)*+7%&[;L:M(NO + }%1  4 k];YG  ++,-9  [./0  + '3 tK-99E  +x ,VHd;9: + {#/YKkI;!?@ ++,-9  [./0  +()*6_%tK:J9K'LM r#c ji}t|dg#t|dgtt|dg||S)N product_imagerr3r4rwr5s r!_ProductImage_to_vertexr!L sE!) +()5  kO+<=yI r#cbi}t|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|d gt|dd gt|d gt|d gt|dd gt|d gt|d gt|ddgt|d gt|dgt|gdt|dgt|dgt|gdt|dgt|dgt|ddgt|dgt|dgt|dgt|dg|S)NrrrrrrrrrrrrrrrrrrrPrSrrRr5s r!_RecontextImageConfig_to_vertexr#[ s#!) +*+,8 }% [-./  + ~&2 {# [<.)  +()*6 |$ [+,-  +x ,v.[6(0KL +-./; ' [012  ++,-9 )* [./0  +()5 ~& [?+,  +*+,83 [-./  +456B= [789  +()*6 ' [+,-  +z". Dxj$AB r#c i}t|dg.t|ddgtj|t|dgt|dgt t|dg|t|dgt t|dg||SNrUrVrr)r3r4rXrY_RecontextImageSource_to_vertexr#rs r!#_RecontextImageParameters_to_vertexr' s !) +y!-  *d; :;  +z".#Dxj$A9M +z".#Dxj$A9M r#c i}t|dg1t|dgt|dgDcgc]}t||c}|Scc}w)NrrrrLs r!#_RecontextImageResponse_from_vertexr) s^!) + '3 [=/:  (i 8    A c Bi}t|dgt|ddgt|dgt|dg$t|gdtt|dg|t|dg2t|ddgt|dgDcgc]}t||c}|Scc}w)Nrr person_image)r personImagerproduct_images productImages)r3r4rwr!rLs r!r&r& s!) +z".14 hZ3P +'(40kN+;?K  +'(4]OT+7G%HI +()*6_%tK:J9K'LM ++,-9 & 23 4i  +./0< ) 56 7  +,-.:  [/01  +./0<  [123 r#c i}t|ddgt|dgt|ddgt|ddgt|dgt|ddgt|dgt|dgt|dg|SNsafetyAttributes categoriesscores contentType content_typerRr5s r!r_r_$ !) +*L9:F  [-|<=  +*H56BH:tK2Dh1OP + '3^$d;&HI r#c i}t|ddgt|dgt|ddgt|ddgt|dgt|ddgt|dgt|dgt|dg|Sr@rRr5s r!rcrc; rFr#ci}t|dgt|dgt|dgt|dg tdt|dgt|dgt|dg|S)Ncategorymethodz0method parameter is not supported in Gemini API. thresholdr2r5s r!r*r*R sv!) + |$0ZL${ZL"AB +z". G HH + }%1[M4 k]#CD r#c ji}t|dg#t|dgtt|dg||S)Nrr r5s r!_ScribbleImage_to_vertexrMc sC!) +y!-  kG95yA r#ci}t|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|dgt|ddgt|dgt|d gt|dd gt|d gt|d gt|d gt|d g|S) Nmodermax_predictionsmaxPredictionsconfidence_thresholdconfidenceThresholdr maskDilationbinary_color_thresholdbinaryColorThresholdrrRr5s r!_SegmentImageConfig_to_vertexrWr s/!) +x ,v.[6(0KL +)*+7 '( [,-.  +./0< ,- [123  +()5 ~& [?+,  +012> -. [345  +z". Dxj$AB r#c i}t|dg.t|ddgtj|t|dgt|dgt t|dg|t|dgt t|dg||Sr%)r3r4rXrY_SegmentImageSource_to_vertexrWrs r!!_SegmentImageParameters_to_vertexrZ s !) +y!-  *d; :;  +z".!${XJ"?K +z".!${XJ"?K r#c i}t|dg1t|dgt|dgDcgc]}t||c}|Scc}w)Nrgenerated_masks)r3r4rrLs r!!_SegmentImageResponse_from_vertexr] s^!) + '3 [=/:  ,D) <    r*c i}t|dgt|ddgt|dgt|dg$t|ddgtt|dg|t|dg$t|ddgtt|dg||S)Nrrrscribble_imagescribble)r3r4rwrMr5s r!rYrY s!) +z".14 hZ3P +y!- !kG95yA  +()*6 $ /0 19  r#ci}t|dgt|dgt|dgt|dgt|dgt|dgt|dg td|S)N language_code languageCode voice_config voiceConfigmulti_speaker_voice_configzCmulti_speaker_voice_config parameter is not supported in Vertex AI.r2r5s r!r5r5 s!) +()5^$d;8I&JK +'(4]OT+7G%HI +456B M  r#c i}t|dg't|dgt|dgDcgc]}|c}t|dg tdt|dgt|dgt|dgt|dgt|dgt|dgt|d gt|d gt|d gt|d gt|d gt|d gt|d g tdt|dg#t|dgtt|dg|t|dg#t|dgt t|dg|t|dgt|dgt|dg|Scc}w)Nfunction_declarationsfunctionDeclarations retrievalz3retrieval parameter is not supported in Gemini API.google_search_retrievalgoogleSearchRetrieval computer_use computerUse file_search fileSearchcode_execution codeExecutionenterprise_web_searchz?enterprise_web_search parameter is not supported in Gemini API. google_maps googleMaps google_search googleSearch url_context urlContext)r3r4rrrrLs r!r,r, s!) +/01=  {-D,EFG$G  + }%1 J KK +123? ! 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Only text is supported. Args: model (str): The model to use. contents (list[Content]): The contents to embed. config (EmbedContentConfig): Optional configuration for embeddings. Usage: .. code-block:: python embeddings = client.models.embed_content( model= 'text-embedding-004', contents=[ 'What is your name?', 'What is your favorite color?', ], config={ 'output_dimensionality': 64 }, ) rrV{model}:predict{model}:batchEmbedContentsrrrNrrr)r_EmbedContentParametersrrrrrrr rrrr rrrrrrrrEmbedContentResponserrrrr_rrs r! embed_contentzModels.embed_contents <33O   6   Ol&))&1  ++,<= 5   Ol&))&1 +667GH+##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   7 Fm    $ $6}Em--<<'A'A'C=L&+%7%7  &L" %%l3 r#rctj|||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd||| } | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S) z%Private method for generating images.rUrrrVrrrrNrrr)r_GenerateImagesParametersrrrYrrrWr rrrr rrrrrrrdr`GenerateImagesResponserrrrr_r rrUrrrrrrrrrrrs r!_generate_imageszModels._generate_imagess 55O   8   Ol&))&1  ++,<= 7   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   9-Hm    $ $8Gm//>>'A'A'C?L&+%7%7  &L" %%l3 r#rctj||||}|jjs t dt |j|}|j d}|rdj|}nd}|j d} | r|dt| }|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| } | j sint#j$| j } |jjr t'| } tj(j+| |j- } tj.| j0 | _|jj5| | S) z$Private method for editing an image.rUrrr6This method is only supported in the Vertex AI client.rVrrrrNrrr)r_EditImageParametersrrrrrrr rrrr rrrrrrrEditImageResponserrrrr_rrrUrrrrrrrrrrrrs r! _edit_imagezModels._edit_image%s00) O    $ $ O PP3   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   4]Cm**99'A'A'C:L&+%7%7  &L" %%l3 r#rrctj||||}|jjs t dt |j|}|j d}|rdj|}nd}|j d} | r|dt| }|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| } | j sint#j$| j } |jjr t'| } tj(j+| |j- } tj.| j0 | _|jj5| | S) z&Private method for upscaling an image.rUrrrrrVrrrrNrrr)r_UpscaleImageAPIParametersrrrrrrr rrrr rrrrrrrUpscaleImageResponserrrrr_rrrUrrrrrrrrrrrrs r!_upscale_imagezModels._upscale_imagees66% O    $ $ O PP9   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   7 Fm--<<'A'A'C=L&+%7%7  &L" %%l3 r#rctj|||}|jjs t dt |j|}|j d}|rdj|}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| } | j sint#j$| j } |jjr t'| } tj(j+| |j- } |jj/| | S aRecontextualizes an image. There are two types of recontextualization currently supported: 1) Imagen Product Recontext - Generate images of products in new scenes and contexts. 2) Virtual Try-On: Generate images of persons modeling fashion products. Args: model (str): The model to use. source (RecontextImageSource): An object containing the source inputs (prompt, person_image, product_images) for image recontext. prompt is optional for product recontext and disallowed for virtual try-on. person_image is required for virtual try-on, disallowed for product recontext. product_images is required for both product recontext and virtual try-on. Only one product image is supported for virtual try-on, and up to 3 product images (different angles of the same product) are supported for product recontext. config (RecontextImageConfig): Configuration for recontextualization. Usage: ``` product_recontext_response = client.models.recontext_image( model="imagen-product-recontext-preview-06-30", source=types.RecontextImageSource( prompt="In a modern kitchen setting.", product_images=[types.ProductImage.from_file(IMAGE_FILE_PATH)], ), config=types.RecontextImageConfig( number_of_images=1, ), ) image = product_recontext_response.generated_images[0].image virtual_try_on_response = client.models.recontext_image( model="virtual-try-on-preview-08-04", source=types.RecontextImageSource( person_image=types.Image.from_file(IMAGE1_FILE_PATH), product_images=[types.ProductImage.from_file(IMAGE2_FILE_PATH)], ), config=types.RecontextImageConfig( number_of_images=1, ), ) image = virtual_try_on_response.generated_images[0].image ``` rUrrrrVrrrrNrr)r_RecontextImageParametersrrrr'rrr rrrr rrrrrrr)RecontextImageResponserrr rrUrrrrrrrrrrrs r!recontext_imagezModels.recontext_imagesn55O    $ $ O PP8   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   9-Hm//>>'A'A'C?L %%l3 r#ctj|||}|jjs t dt |j|}|j d}|rdj|}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| } | j sint#j$| j } |jjr t'| } tj(j+| |j- } |jj/| | S) a"Segments an image, creating a mask of a specified area. Args: model (str): The model to use. source (SegmentImageSource): An object containing the source inputs (prompt, image, scribble_image) for image segmentation. The prompt is required for prompt mode and semantic mode, disallowed for other modes. scribble_image is required for the interactive mode, disallowed for other modes. config (SegmentImageConfig): Configuration for segmentation. Usage: ``` response = client.models.segment_image( model="image-segmentation-001", source=types.SegmentImageSource( image=types.Image.from_file(IMAGE_FILE_PATH), ), ) mask_image = response.generated_masks[0].mask ``` rrrVrrrrNrr)r_SegmentImageParametersrrrrZrrr rrrr rrrrrrr]SegmentImageResponserrrrs r! segment_imagezModels.segment_images@33O    $ $ O PP6   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   7 Fm--<<'A'A'C=L %%l3 r#c6tj||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd}|j,|jj|jj}tj|}tj|}|jjd|||} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/} |jj1| | S NrUrrV{name}rrrrr)r_GetModelParametersrrrrrrr rrrr rrrrrrrrModelrrr rrUrrrrrrrrrrs r!rz Models.getbs//O   2   Ol&))&1 ""#341   Ol&))&1 ""#34##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''t\<PH&mmBHMM1JM   (7m    $ $' 6m;;--'A'A'C.L %%l3 r#ctj|}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r=|j dr,|jd}|d|}|r$|dt|z }n|r|dt|}|jd dd}|j,|jj|jj}tj|}tj|}|jjd |||} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S NrrVz {models_url}rrz?filter=&rrrrr)r_ListModelsParametersrrrrrrrr rrr rrrrrrrrListModelsResponserrrrr_r rrrrrrrquery_param_filterrrrrs r!_listz Models._listsO11O    4   Ol&))&1 (()9:3   Ol&))&1 (()9:##H-L ((2'++H5vX01 2d  !Il+,-- vQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''t\<PH&mmBHMM1JM   5mDm    $ $4]Cm++::'A'A'C;L&+%7%7  &L" %%l3 r#c6tj||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd}|j,|jj|jj}tj|}tj|}|jjd|||} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } |jj1| | S NrrVz{model}rrrrpatchr)r_UpdateModelParametersrrrrrrr rrrr rrrrrrrrrrrrrs r!updatez Models.updates 22O   5   Ol&))&1 ##$454   Ol&))&1 ""#34##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''|\H'mmBHMM1JM   (7m    $ $' 6m;;--'A'A'C.L %%l3 r#ctj||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd}|j,|jj|jj}tj|}tj|}|jjd|||} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/} tj0| j2 | _|jj7| | S NrrVrrrrdeleterr)r_DeleteModelParametersrrrrrrr rrrr rrrrrrrrDeleteModelResponserrrrr_rrs r!r z Models.delete$s  22O   5   Ol&))&1 ""#344   Ol&))&1 ""#34##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''$ lH'mmBHMM1JM   6}Em    $ $5mDm,,;;'A'A'C<L&+%7%7  &L" %%l3 r#ctj|||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd||| } | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S) a8Counts the number of tokens in the given content. Multimodal input is supported for Gemini models. Args: model (str): The model to use for counting tokens. contents (list[types.Content]): The content to count tokens for. config (CountTokensConfig): The configuration for counting tokens. Usage: .. code-block:: python response = client.models.count_tokens( model='gemini-2.0-flash', contents='What is your name?', ) print(response) # total_tokens=5 cached_content_token_count=None rrV{model}:countTokensrrrNrrr)r_CountTokensParametersrrrrrrr rrrr rrrrrrrrCountTokensResponserrrrr_rrs r! count_tokenszModels.count_tokenshs 822O   5   Ol&))&1 $//0@A$4   Ol&))&1 $//0@A$##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   6}Em    $ $5mDm,,;;'A'A'C<L&+%7%7  &L" %%l3 r#ctj|||}|jjs t dt |j|}|j d}|rdj|}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| } | j sint#j$| j } |jjr t'| } tj(j+| |j- } tj.| j0 | _|jj5| | S) azGiven a list of contents, returns a corresponding TokensInfo containing the list of tokens and list of token ids. This method is not supported by the Gemini Developer API. Args: model (str): The model to use. contents (list[shared.Content]): The content to compute tokens for. Usage: .. code-block:: python response = client.models.compute_tokens( model='gemini-2.0-flash', contents='What is your name?', ) print(response) # tokens_info=[TokensInfo(role='user', token_ids=['1841', ...], # tokens=[b'What', b' is', b' your', b' name', b'?'])] rrrV{model}:computeTokensrrrNrrr)r_ComputeTokensParametersrrrr\rrr rrrr rrrrrrrbComputeTokensResponserrrrr_rrs r!compute_tokenszModels.compute_tokenss<44O    $ $ O PP7   Ol&))&1 &112BC&##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   8Gm..=='A'A'C>L&+%7%7  &L" %%l3 r#rrrrrrc>tj||||||}|jjr>t |j|}|j d} | rdj | } n@d} n=t|j|}|j d} | rdj | } nd} |j d} | r| dt| } |jddd} |j,|jj|jj} tj|}tj|}|jjd| || } | j sint#j$| j }|jjr t'|}|jjs t)|}tj*j-||j/ }|jj1||S) z%Private method for generating videos.rUrrrrrrV{model}:predictLongRunningrrrNrr)r_GenerateVideosParametersrrrrrrr rrrr rrrrrrrrGenerateVideosOperationrrrrrUrrrrrrrrrrrrrrs r!_generate_videoszModels._generate_videoss55 O   8   Ol&))&1 +667GH+7   Ol&))&1 +667GH+##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL''lLH'mmBHMM1JM   :=Im    $ $9-Hm00??'A'A'C@L %%l3 r#ctj|}tj|}|r@|jr4t j |jrt jdtj|r|j|||S|rd}t|tjr"|jrEt|j}n/t|tr|jdg}|r t|}t||k7r5dj!t#t$|}t&j)d||j|||Stj*|} t&j-d| dg} tj.} d} | dkDr| d z } |j|||} tj0|} | snR| snN| j2r<| j2dj4r#| j2dj4j6sntj8| | }|snt&j-d | d | d z} | dk(rt&j-d | j2dj4}tj:d |}t=j>|}| s| jA|t|tBr"|jE||jE|| jE|| jE|| dkDrtjF|r | | | _$| S)aMakes an API request to generate content using a model. For the `model` parameter, supported formats for Vertex AI API include: - The Gemini model ID, for example: 'gemini-2.0-flash' - The full resource name starts with 'projects/', for example: 'projects/my-project-id/locations/us-central1/publishers/google/models/gemini-2.0-flash' - The partial resource name with 'publishers/', for example: 'publishers/google/models/gemini-2.0-flash' or - `/` separated publisher and model name, for example: 'google/gemini-2.0-flash' For the `model` parameter, supported formats for Gemini API include: - The Gemini model ID, for example: 'gemini-2.0-flash' - The model name starts with 'models/', for example: 'models/gemini-2.0-flash' - For tuned models, the model name starts with 'tunedModels/', for example: 'tunedModels/1234567890123456789' Some models support multimodal input and output. Built-in MCP support is an experimental feature. Usage: .. code-block:: python from google.genai import types from google import genai client = genai.Client( vertexai=True, project='my-project-id', location='us-central1' ) response = client.models.generate_content( model='gemini-2.0-flash', contents='''What is a good name for a flower shop that specializes in selling bouquets of dried flowers?''' ) print(response.text) # **Elegant & Classic:** # * The Dried Bloom # * Everlasting Florals # * Timeless Petals response = client.models.generate_content( model='gemini-2.0-flash', contents=[ types.Part.from_text(text='What is shown in this image?'), types.Part.from_uri(file_uri='gs://generativeai-downloads/images/scones.jpg', mime_type='image/jpeg') ] ) print(response.text) # The image shows a flat lay arrangement of freshly baked blueberry # scones. 6MCP sessions are not supported in synchronous methods.rrrw, Tools at indices [%s] are not compatible with automatic function calling (AFC). AFC is disabled. If AFC is intended, please include python callables in the tool list, and do not include function declaration in the tool list.&AFC is enabled with max remote calls: .r AFC remote call is done.8Reached max remote calls for automatic function calling.userrlrk)%r"find_afc_incompatible_tool_indexesparse_config_for_mcp_usagerwrhas_mcp_session_usagerUnsupportedFunctionErrorshould_disable_afcr isinstancerGenerateContentConfiglendictrjoinmapstrloggerwarningget_max_remote_calls_afcinforget_function_mapr=r9rkget_function_response_partsContentrXrZextendlistappendshould_append_afc_history"automatic_function_calling_history)rrUrWrincompatible_tools_indexes parsed_configoriginal_tools_lengthrw indices_strremaining_remote_calls_afcrDri function_mapfunc_response_partsfunc_call_contentfunc_response_contents r!generate_contentzModels.generate_contentbs/D 77?!;;FCM     , ,]-@-@ A  + + B &&}5  # #$" FE77 8 <<"%fll"3  fd # 7B' "%e*  ' (,A AiiC)C DE  5    # #$".!F!F" KK 01K0LAN?A&,,.H A $q (1fa''(h"22=Al   !!$$Q'//$$Q'//55 (DD L!  kk$QCy12 A% #q ( NO"--a088#mm#h'h /*11(; Hd #)*-.(//0AB(//0EFO %q (R ..}=   -1 Or#c#XKtj|}tj|}|r@|jr4t j |jrt jdtj|r|j|||Ed{y|rd}t|tjr"|jrEt|j}n/t|tr|jdg}|r t|}t||k7r5dj!t#t$|}t&j)d||j|||Ed{ytj*|} t&j-d| d g} d} d} d} | dkDrw| d z } |j|||}tj.|}| d k(r|D]} |stj0|| }|  | j2r<| j2dj4r#| j2dj4j6sntj8| |} | rtj0|| }| n|D]8} tj:|r| | _tj0|| }| :| H| j2r<| j2dj4r#| j2dj4j6sytj8| |} |sy| syt&j-d | d | d z} | dk(rt&j-d | | j2| j2dj4}tj>d| }tAjB|}| s| jE|t|tFr$|"|jI||jI||| jI|| jI|| dkDrvyy77w)aMakes an API request to generate content using a model and yields the model's response in chunks. For the `model` parameter, supported formats for Vertex AI API include: - The Gemini model ID, for example: 'gemini-2.0-flash' - The full resource name starts with 'projects/', for example: 'projects/my-project-id/locations/us-central1/publishers/google/models/gemini-2.0-flash' - The partial resource name with 'publishers/', for example: 'publishers/google/models/gemini-2.0-flash' or - `/` separated publisher and model name, for example: 'google/gemini-2.0-flash' For the `model` parameter, supported formats for Gemini API include: - The Gemini model ID, for example: 'gemini-2.0-flash' - The model name starts with 'models/', for example: 'models/gemini-2.0-flash' - For tuned models, the model name starts with 'tunedModels/', for example: 'tunedModels/1234567890123456789' Some models support multimodal input and output. Built-in MCP support is an experimental feature. Usage: .. code-block:: python from google.genai import types from google import genai client = genai.Client( vertexai=True, project='my-project-id', location='us-central1' ) for chunk in client.models.generate_content_stream( model='gemini-2.0-flash', contents='''What is a good name for a flower shop that specializes in selling bouquets of dried flowers?''' ): print(chunk.text) # **Elegant & Classic:** # * The Dried Bloom # * Everlasting Florals # * Timeless Petals for chunk in client.models.generate_content_stream( model='gemini-2.0-flash', contents=[ types.Part.from_text('What is shown in this image?'), types.Part.from_uri('gs://generativeai-downloads/images/scones.jpg', 'image/jpeg') ] ): print(chunk.text) # The image shows a flat lay arrangement of freshly baked blueberry # scones. r#rNrrwr$z_Tools at indices [%s] are not compatible with automatic function calling. AFC will be disabled.r&r'r r(r)r*r+r,)%rr-r.rwrr/rr0r1rr2rr3r4r5rr6r7r8r9r:r;r<r=append_chunk_contentsr=r9rkr>rCrDr?rXrZr@rArB)rrUrWrrErFrGrwrHrIrDchunkrLrJrrKrMrNs r!generate_content_streamzModels.generate_content_streams"D 77?!;;FCM     , ,]-@-@ A  + + B &&}5../ ! FE77 8 <<"%fll"3  fd # 7B' "%e*  ' (,A AiiC)C DE  -  ../ !-!F!F" KK 01K0LAN?A& E A $q (1fa../h"22=Al a E#99(EJHK$$''*22''*2288"."J"J|# '%;;HeLhk! ( E  3 3M B2  4"77%H(+   M####A&..##A&..44 *FF <    kk$QCy12 A% #q ( NO  u//;!,,Q/77 % %! <<)1 , 3 3H = h %*;*G //+ , /// 0  ( , 3 34E F*112GHU %q (I*s3BP*P$CP**P'+C8P*$F>*>E#(:DA#->> ($$ 'NN+@$G",.. '# ~~h-J$#Jv%&J!"   %  r#c D|s|s|r |r tdi}|jjs|rt|tj r|j }n t|}|jdr|jdrt j |jd|jd}nL|jjs5|r2t|tjr#|j }|jdi}nht|}t|jdtj r4|jdt j } | j }|r|jdrz|jdrit j|jd|jdt j |jd|jd }|j|||||| S) Generates videos based on an input (text, image, or video) and configuration. The following use cases are supported: 1. Text to video generation. 2a. Image to video generation (additional text prompt is optional). 2b. Image to video generation with frame interpolation (specify last_frame in config). 3. Video extension (additional text prompt is optional) Args: model: The model to use. prompt: The text prompt for generating the videos. Optional for image to video and video extension use cases. This argument is deprecated, please use source instead. image: The input image for generating the videos. Optional if prompt is provided. This argument is deprecated, please use source instead. video: The input video for video extension use cases. Optional if prompt or image is provided. This argument is deprecated, please use source instead. source: The input source for generating the videos (prompt, image, and/or video) config: Configuration for generation. Usage: ``` operation = client.models.generate_videos( model="veo-2.0-generate-001", source=types.GenerateVideosSource( prompt="A neon hologram of a cat driving at top speed", ), ) while not operation.done: time.sleep(10) operation = client.operations.get(operation) operation.result.generated_videos[0].video.uri ``` MSource and prompt/image/video are mutually exclusive. Please only use source.rrr0rr0rrrrrrr rrrr2rVideorr5rGenerateVideosSourcer! rrUrrrrr video_dct source_dct video_objs r!generate_videoszModels.generate_videoszsb %5f  '  !#I    $ $ E5;; '$$& K u )-- ">  e$ k0J    & &6 FE66 7&&( NN7B/ &\ jnnW-u{{ ;#->>'5;;=#I)**,) y}}U+ m0L++>>(+..)++MM%(#-- 4    ! r#c|tj|jxstj}|jd|_|j j r6|j}|js|j}|r|dznd|_td|j|j||S)aMakes an API request to list the available models. If `query_base` is set to True in the config or not set (default), the API will return all available base models. If set to False, it will return all tuned models. Args: config (ListModelsConfigOrDict): Configuration for retrieving models. Usage: .. code-block:: python response=client.models.list(config={'page_size': 5}) print(response.page) # [Model(name='projects/./locations/./models/123', display_name='my_model' response=client.models.list(config={'page_size': 5, 'query_base': True}) print(response.page) # [Model(name='publishers/google/models/gemini-2.0-flash-exp' ... rT&filter=labels.tune-type:*labels.tune-type:*r) rrrListModelsConfigrrrcopyrrrrr filter_values r!rAz Models.lists8 ##6299 $  ! ! #  f   {{}f   }}  7 7%    & !  r#)C__name__ __module__ __qualname__r8rrContentListUnionContentListUnionDictrGenerateContentConfigOrDictrrrrEmbedContentConfigOrDictrrGenerateImagesConfigOrDictrrrA_ReferenceImageAPIOrDictEditImageConfigOrDictrr ImageOrDict_UpscaleImageAPIConfigOrDictrrRecontextImageSourceOrDictRecontextImageConfigOrDictrrSegmentImageSourceOrDictSegmentImageConfigOrDictrrGetModelConfigOrDictrrListModelsConfigOrDictrrUpdateModelConfigOrDictr DeleteModelConfigOrDictrr CountTokensConfigOrDictrrComputeTokensConfigOrDictrr VideoOrDictGenerateVideosSourceOrDictGenerateVideosConfigOrDictrr!rOrSr[r_UpscaleImageConfigOrDictrjrwrr#r!rrsd=A KKe,,e.H.HHI K u889 K  $$ Kd=A PPe,,e.H.HHI P u889 P --. Pn:> [[e,,e.H.HHI [ u556 [  !! [D<@ FF F u778 F  ## F\7; >> > U;;< > u223 > >L>B >>   >  > u99: > !!>J<@ hh.. h u778 h  ## h^:> QQ,, Q u556 Q  !! QhKO;;#+E,F,F#G; {{;|AEA < <=A AN9= @@u445 @  {{ @L9= BBu445 B    BR9= YYe,,e.H.HHI Y u445 Y    Y@;? QQe,,e.H.HHI Q u667 Q  "" Qn#+/+/;?;?JJsm J e'' ( J e'' ( Ju778Ju778J $$Jb=A __** _ u889 _  $$ _L=A |I|I** |I u889 |I --. |IF<@ 55 5 u778 5  ## 5z7; 66 6 U;;< 6 u223 6 6|:> HH   H  H u556 H !!H\#+/+/;?;?[[sm [ e'' ( [ e'' ( [u778[u778[ $$[@8<0u3340 U[[ 0r#rcR eZdZdddedeej ejfdeejdejfdZ dddedeej ejfdeejde e ejfdZdddedeej ejfdeejdej fd Zddded edeej$dej&fd Zddded ed eej,deej.dej0f d Zdddedej4dedeej6dej8f dZdddedej<deej>dej@fdZ!dddedejDdeejFdejHfdZ%dddedeejLdejNfdZ(dddeejRdejTfdZ+dddedeejXdejNfdZ-dddedeej\dej^fdZ0dddedeej ejfdeejbdejdfdZ3dddedeej ejfdeejhdejjfdZ6ddddddded eedeej4deejndeejpdeejrdejtfdZ;dddedeej ejfdeejdejfdZdddeejRde?ejNfd Zddded edeej$dej&fd!Z@dddedej4dedeejdej8f d"ZBddddddded eedeej4deejndeejpdeejrdejtfd#ZCy)$ AsyncModelsNrrUrWrrc$Ktj|||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd||| d{} |@t!|ddr3tj"| } |jj%| | S| j&sint)j*| j&} |jjr t-| } |jjs t/| } tj"j1| |j3 } tj4| j6 | _|jj%| | S7'wr)rrrrr;rrr9r rrrr rr async_requestrrrrrrrJrFrrrrr_rs r!rzAsyncModels._generate_content s]66O   9   Ol&))&1 (334DE(8   Ol&))&1 (334DE(##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLHg-t22XNl '' 5 &mmBHMM1JM   :=Im    $ $9-Hm00??'A'A'C@L&+%7%7  &L" %%l3 5sE$J&J 'D'Jc4 Ktj||| jjr>t j }|j d}|rdj |}n@d}n=tj }|j d}|rdj |}nd}|j d}|r|dt|}|jddd} j, jj jj}tj|}tj|}|t|ddr t!djj#d |||d{ fd } | S7w) NrrVrrrrrrrcK23d{}|jsintj|j}jjr t |}jjs t |}tjj|j}tj|j|_ jj||76yw)Nrr)rrrrrrJrFrrrrrrr_r)rrrrresponse_streamrs r!async_generatorz=AsyncModels._generate_content_stream..async_generators+"*--TZZ 5N    $ $>}M-((=mL-44CC"?+E+E+GD */););$$* & )),7#Os&C7C5C3C5C%C73C55C7)rrrrr;rrr9r rrrr rrrrasync_request_streamed) rrUrWrrrrrrrrrs ` @@r!rz$AsyncModels._generate_content_streamYs66O   9   Ol&))&1 6AA  78   Ol&))&1 6AA  7##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL g-t    !,,CClLO(  1sE>FFFcKtj|||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S7w) aKCalculates embeddings for the given contents. Only text is supported. Args: model (str): The model to use. contents (list[Content]): The contents to embed. config (EmbedContentConfig): Optional configuration for embeddings. Usage: .. code-block:: python embeddings = await client.aio.models.embed_content( model= 'text-embedding-004', contents=[ 'What is your name?', 'What is your favorite color?', ], config={ 'output_dimensionality': 64 }, ) rrVrrrrrNrrr)rrrrrrrrr rrrr rrrrrrrrrrrrrr_rrs r!rzAsyncModels.embed_contents<33O   6   Ol&))&1  ++,<= 5   Ol&))&1 +667GH+##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   7 Fm    $ $6}Em--<<'A'A'C=L&+%7%7  &L" %%l3 'E$I &I 'C%I rcKtj|||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd||| d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S7w) z4Private method for generating images asynchronously.rrVrrrrNrrr)rrrrrYrrrWr rrrr rrrrrrrdr`rrrrrr_rrs r!rzAsyncModels._generate_images s55O   8   Ol&))&1  ++,<= 7   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   9-Hm    $ $8Gm//>>'A'A'C?L&+%7%7  &L" %%l3 'rrcKtj||||}|jjs t dt |j|}|j d}|rdj|}nd}|j d} | r|dt| }|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| d{} | j sint#j$| j } |jjr t'| } tj(j+| |j- } tj.| j0 | _|jj5| | S7íw) z3Private method for editing an image asynchronously.rrrVrrrrNrrr)rrrrrrrrr rrrr rrrrrrrrrrrrr_rrs r!rzAsyncModels._edit_imageUs00) O    $ $ O PP3   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   4]Cm**99'A'A'C:L&+%7%7  &L" %%l3 !D2G:4G85CG:rrcKtj||||}|jjs t dt |j|}|j d}|rdj|}nd}|j d} | r|dt| }|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| d{} | j sint#j$| j } |jjr t'| } tj(j+| |j- } tj.| j0 | _|jj5| | S7íw) z5Private method for upscaling an image asynchronously.rrrVrrrrNrrr)rrrrrrrrr rrrr rrrrrrrrrrrrr_rrs r!rzAsyncModels._upscale_images66% O    $ $ O PP9   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   7 Fm--<<'A'A'C=L&+%7%7  &L" %%l3 !rrcKtj|||}|jjs t dt |j|}|j d}|rdj|}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| d{} | j sint#j$| j } |jjr t'| } tj(j+| |j- } |jj/| | S7wr)rrrrrr'rrr rrrr rrrrrrr)rrrrrs r!rzAsyncModels.recontext_imagesn55O    $ $ O PP8   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   9-Hm//>>'A'A'C?L %%l3 D1G3G4BGcKtj|||}|jjs t dt |j|}|j d}|rdj|}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| d{} | j sint#j$| j } |jjr t'| } tj(j+| |j- } |jj/| | S7w) aSegments an image, creating a mask of a specified area. Args: model (str): The model to use. source (SegmentImageSource): An object containing the source inputs (prompt, image, scribble_image) for image segmentation. The prompt is required for prompt mode and semantic mode, disallowed for other modes. scribble_image is required for the interactive mode, disallowed for other modes. config (SegmentImageConfig): Configuration for segmentation. Usage: ``` response = client.models.segment_image( model="image-segmentation-001", source=types.SegmentImageSource( image=types.Image.from_file(IMAGE_FILE_PATH), ), config=types.SegmentImageConfig( mode=types.SegmentMode.foreground, ), ) mask_image = response.generated_masks[0].mask ``` rrrVrrrrNrr)rrrrrrZrrr rrrr rrrrrrr]rrrrrs r!rzAsyncModels.segment_image?sF33O    $ $ O PP6   Ol&))&1  ++,<= ##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   7 Fm--<<'A'A'C=L %%l3 rcRKtj||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd}|j,|jj|jj}tj|}tj|}|jjd|||d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/} |jj1| | S7wr)rrrrrrrrr rrrr rrrrrrrrrrrrrs r!rzAsyncModels.gets//O   2   Ol&))&1 ""#341   Ol&))&1 ""#34##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33 t\<H'mmBHMM1JM   (7m    $ $' 6m;;--'A'A'C.L %%l3 #E#H'%H%&CH'cKtj|}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r=|j dr,|jd}|d|}|r$|dt|z }n|r|dt|}|jd dd}|j,|jj|jj}tj|}tj|}|jjd |||d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S7wr)rrrrrrrrrr rrr rrrrrrrrrrrrrr_rrs r!rzAsyncModels._listsb11O    4   Ol&))&1 (()9:3   Ol&))&1 (()9:##H-L ((2'++H5vX01 2d  !Il+,-- vQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33 t\<H'mmBHMM1JM   5mDm    $ $4]Cm++::'A'A'C;L&+%7%7  &L" %%l3 'sF!J #J$C%J cRKtj||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd}|j,|jj|jj}tj|}tj|}|jjd|||d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } |jj1| | S7wr)rr rrrrrrr rrrr rrrrrrrrrrrrrs r!r zAsyncModels.updates 22O   5   Ol&))&1 ##$454   Ol&))&1 ""#34##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33|\H'mmBHMM1JM   (7m    $ $' 6m;;--'A'A'C.L %%l3 #rcKtj||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd}|j,|jj|jj}tj|}tj|}|jjd|||d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/} tj0| j2 | _|jj7| | S7wr )rrrrrrrrr rrrr rrrrrrrrrrrrrr_rrs r!r zAsyncModels.delete[s 22O   5   Ol&))&1 ""#344   Ol&))&1 ""#34##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33$ lH'mmBHMM1JM   6}Em    $ $5mDm,,;;'A'A'C<L&+%7%7  &L" %%l3 'sE#I %I &C%I cKtj|||}|jjr>t |j|}|j d}|rdj |}n@d}n=t|j|}|j d}|rdj |}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd||| d{} | j sint#j$| j } |jjr t'| } |jjs t)| } tj*j-| |j/ } tj0| j2 | _|jj7| | S7w) aBCounts the number of tokens in the given content. Multimodal input is supported for Gemini models. Args: model (str): The model to use for counting tokens. contents (list[types.Content]): The content to count tokens for. config (CountTokensConfig): The configuration for counting tokens. Usage: .. code-block:: python response = await client.aio.models.count_tokens( model='gemini-2.0-flash', contents='What is your name?', ) print(response) # total_tokens=5 cached_content_token_count=None rrVrrrrNrrr)rrrrrrrrr rrrr rrrrrrrrrrrrrr_rrs r!rzAsyncModels.count_tokenss822O   5   Ol&))&1 $//0@A$4   Ol&))&1 $//0@A$##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   6}Em    $ $5mDm,,;;'A'A'C<L&+%7%7  &L" %%l3 'rcKtj|||}|jjs t dt |j|}|j d}|rdj|}nd}|j d}|r|dt|}|jddd} |j,|jj|jj} tj|}tj|}|jjd ||| d{} | j sint#j$| j } |jjr t'| } tj(j+| |j- } tj.| j0 | _|jj5| | S7íw) aFGiven a list of contents, returns a corresponding TokensInfo containing the list of tokens and list of token ids. Args: model (str): The model to use. contents (list[shared.Content]): The content to compute tokens for. Usage: .. code-block:: python response = await client.aio.models.compute_tokens( model='gemini-2.0-flash', contents='What is your name?', ) print(response) # tokens_info=[TokensInfo(role='user', token_ids=['1841', ...], # tokens=[b'What', b' is', b' your', b' name', b'?'])] rrrVrrrrNrrr)rrrrrr\rrr rrrr rrrrrrrbrrrrrr_rrs r!rzAsyncModels.compute_tokenss:44O    $ $ O PP7   Ol&))&1 &112BC&##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   8Gm..=='A'A'C>L&+%7%7  &L" %%l3 !sD1G93G74CG9rrcZKtj||||||}|jjr>t |j|}|j d} | rdj | } n@d} n=t|j|}|j d} | rdj | } nd} |j d} | r| dt| } |jddd} |j,|jj|jj} tj|}tj|}|jjd| || d{} | j sint#j$| j }|jjr t'|}|jjs t)|}tj*j-||j/ }|jj1||S7w) z4Private method for generating videos asynchronously.rrVrrrrNrr)rrrrrrrrr rrrr rrrrrrrrrrrrr s r!r!zAsyncModels._generate_videosLs55 O   8   Ol&))&1 +667GH+7   Ol&))&1 +667GH+##H-LvQy./ 0dXt$04L*  " " / / ;$++88l**<8L66|DL%%33lLH'mmBHMM1JM   :=Im    $ $9-Hm00??'A'A'C@L %%l3 #sE'H+)H)*CH+cRKtj|}tj|d{\}}tj|r|j |||d{S|rd}t |t jr"|jrEt|j}n/t |tr|jdg}|r t|}t||k7r5djtt|} tj!d| |j |||d{Stj"|} tj%d| dg} t j&} | dkDrx|j |||d{} | d z} | dk(rtj%d tj(||d } | sn!| sn| j*r<| j*dj,r#| j*dj,j.sntj0| | d{}|sn| j*dj,}t j2d |}t5j6|}| s| j9|t |t:r"|j=||j=|| j=|| j=|| dkDrxtj>|r | | | _ | S77777w)adMakes an API request to generate content using a model. Some models support multimodal input and output. Built-in MCP support is an experimental feature. Usage: .. code-block:: python from google.genai import types from google import genai client = genai.Client( vertexai=True, project='my-project-id', location='us-central1' ) response = await client.aio.models.generate_content( model='gemini-2.0-flash', contents='User input: I like bagels. Answer:', config=types.GenerateContentConfig( system_instruction= [ 'You are a helpful language translator.', 'Your mission is to translate text in English to French.' ] ), ) print(response.text) # J'aime les bagels. Nrrrwr$r%r&r'r r*Tis_caller_method_asyncr+r,)!rr-parse_config_for_mcp_sessionsr1rr2rr3rwr4r5rr6r7r8r9r:r;r<rr=r=r9rk!get_function_response_parts_asyncr?rXrZr@rArBrCrD)rrUrWrrErFmcp_to_genai_tool_adaptersrGrwrHrIrDrrKrLrMrNs r!rOzAsyncModels.generate_contents#P 77?88@@.M-&&}5))*" FE77 8 <<"%fll"3  fd # 7B' "%e*  ' (,A AiiC)C DE  5   ))*".!F!F" KK 01K0LAN?A&,,.H $q (--.h!A% #q ( NO!22 3Dl  !!$$Q'//$$Q'//55 >>    ! "--a088#mm#h'h /*11(; Hd #)*-.(//0AB(//0EFQ %q (V ..}=   -1 Oi A** sa.L'L3L'$L%C L'2L3A%L'L"B%L'>L%?B8L'9!L'L'L'"L'%L'c Ktj|}tj|d{\} tj|r+j |||d{ fd}||||S|rd}t |t jr"|jrEt|j}n/t |tr|jdg}|r t|}t||k7r5djtt|} tj!d| j |||d{ fd}||||S fd } | |||S7577)w) a2Makes an API request to generate content using a model and yields the model's response in chunks. For the `model` parameter, supported formats for Vertex AI API include: - The Gemini model ID, for example: 'gemini-2.0-flash' - The full resource name starts with 'projects/', for example: 'projects/my-project-id/locations/us-central1/publishers/google/models/gemini-2.0-flash' - The partial resource name with 'publishers/', for example: 'publishers/google/models/gemini-2.0-flash' or - `/` separated publisher and model name, for example: 'google/gemini-2.0-flash' For the `model` parameter, supported formats for Gemini API include: - The Gemini model ID, for example: 'gemini-2.0-flash' - The model name starts with 'models/', for example: 'models/gemini-2.0-flash' - For tuned models, the model name starts with 'tunedModels/', for example: 'tunedModels/1234567890123456789' Some models support multimodal input and output. Built-in MCP support is an experimental feature. Usage: .. code-block:: python from google.genai import types from google import genai client = genai.Client( vertexai=True, project='my-project-id', location='us-central1' ) async for chunk in await client.aio.models.generate_content_stream( model='gemini-2.0-flash', contents='''What is a good name for a flower shop that specializes in selling bouquets of dried flowers?''' ): print(chunk.text) # **Elegant & Classic:** # * The Dried Bloom # * Everlasting Florals # * Timeless Petals async for chunk in await client.aio.models.generate_content_stream( model='gemini-2.0-flash', contents=[ types.Part.from_text('What is shown in this image?'), types.Part.from_uri('gs://generativeai-downloads/images/scones.jpg', 'image/jpeg') ] ): print(chunk.text) # The image shows a flat lay arrangement of freshly baked blueberry # scones. Nrc6K23d{}|7 6ywNrrUrWrrRrs r!base_async_generatorzAAsyncModels.generate_content_stream..base_async_generatorg##  %+ 8rrwr$r%c6K23d{}|7 6ywrrrs r!rzAAsyncModels.generate_content_stream..base_async_generatorrrcKtj|}tjd|dg}d}d}d}|dkDr5|dz } j |||d{}|dkDrtjd|d|dz}|dkDr|dk(rtjdtj | d } |dk(r|23d{}| stj ||}|'|jr<|jdjr#|jdjjsntj|| d{}|rtj ||}||23d{}tj|r||_ tj ||}|A| sy|sy||jdj} tjd | } tj |}|s|j#|t%|t&r$| "|j)| |j)| | |j)| |j)| |dkDr4yy777067 6|H|jr<|jdjr#|jdjjsytj|| d{7}>w) Nr&r'rr rr(r)r*Trr+r,)rr;r9r<rr=rQr=r9rkrrCrDrr?rXrZr@r2rArB)rUrWrrIrDrLrRrJrrKrMrNrrs r!rz.async_generators #/#H#H#P  kk 23M2Na PAC( e a & * Q66(67   q5 ++(95 6"a'" q5/14 ++H $44 .t  6&  E%;;HeLhk&&))!,44))!,44::$FF\" )'==hN &  E55f=46$99(EJHK "  = !,,Q/77 % %! <<)1 , 3 3H = h %*;*G //+ , /// 0  ( , 3 34E F*112GHm ' * ( &, Xm%%%%a(00%%a(0066  BB sAK1I6A%K1I?I9I? BK1 I< K1K12J6J7J:C8K14K19I?<K1?K1JA%K1)K,*K1)rr-rr1rr2rr3rwr4r5rr6r7r8r9r:) rrUrWrrErFrrGrwrHrrrs ` @@r!rSz#AsyncModels.generate_content_streamswF 77? 88@@.M-&&}5445h"%= AA! FE77 8 <<"%fll"3  fd # 7B' "%e*  ' (,A AiiC)C DE  5   445h"%= AA_IB 5(M ::U A8s4.E0E(3E0'E+(CE0E.$E0+E0.E0cHK|j||||d{S7w)aVEdits an image based on a text description and configuration. Args: model (str): The model to use. prompt (str): A text description of the edit to apply to the image. reference_images (list[Union[RawReferenceImage, MaskReferenceImage, ControlReferenceImage, StyleReferenceImage, SubjectReferenceImage]): The reference images for editing. config (EditImageConfig): Configuration for editing. Usage: .. code-block:: python from google.genai.types import RawReferenceImage, MaskReferenceImage raw_ref_image = RawReferenceImage( reference_id=1, reference_image=types.Image.from_file(IMAGE_FILE_PATH), ) mask_ref_image = MaskReferenceImage( reference_id=2, config=types.MaskReferenceConfig( mask_mode='MASK_MODE_FOREGROUND', mask_dilation=0.06, ), ) response = await client.aio.models.edit_image( model='imagen-3.0-capability-001', prompt='man with dog', reference_images=[raw_ref_image, mask_ref_image], config=types.EditImageConfig( edit_mode= "EDIT_MODE_INPAINT_INSERTION", number_of_images= 1, include_rai_reason= True, ) ) response.generated_images[0].image.show() # Shows a man with a dog instead of a cat. rNr]r^s r!r_zAsyncModels.edit_images7b!!) "  s " "cKtj|jxstj}|jd|_|j j r6|j}|js|j}|r|dznd|_td|j|j|d{|S7 w)aMakes an API request to list the available models. If `query_base` is set to True in the config or not set (default), the API will return all available base models. If set to False, it will return all tuned models. Args: config (ListModelsConfigOrDict): Configuration for retrieving models. Usage: .. code-block:: python response = await client.aio.models.list(config={'page_size': 5}) print(response.page) # [Model(name='projects/./locations/./models/123', display_name='my_model' response = await client.aio.models.list( config={'page_size': 5, 'query_base': True} ) print(response.page) # [Model(name='publishers/google/models/gemini-2.0-flash-exp' ... rNTryrzr) rrrr{rrrr|rrrr}s r!rAzAsyncModels.list$s< ##6299 $  ! ! #  f   {{}f   }}  7 7%   jjj''   (sBC ? C cHK|j|||d{}d}g}|r |js|S|jD]E}|jr&|jjdk(r |j}5|j |Gt j ||}|S7w)azGenerates images based on a text description and configuration. Args: model (str): The model to use. prompt (str): A text description of the images to generate. config (GenerateImagesConfig): Configuration for generation. Usage: .. code-block:: python response = await client.aio.models.generate_images( model='imagen-3.0-generate-002', prompt='Man with a dog', config=types.GenerateImagesConfig( number_of_images= 1, include_rai_reason= True, ) ) response.generated_images[0].image.show() # Shows a man with a dog. rNrUrVrWrXs r!r[zAsyncModels.generate_imagesXs:../L )-% |<< '881  + +//<< -<,M,M)01++)*KH O1sB"B BB"cKtj|||||xsi}t|tjr|j }n t |}tj |jdd|jdd|jdd|jdd|jdd|jdd|jd d|jd d|jd d|jd d }d|d<d|d<|j||||d{S7w)aMakes an API request to upscale a provided image. Args: model (str): The model to use. image (Image): The input image for upscaling. upscale_factor (str): The factor to upscale the image (x2 or x4). config (UpscaleImageConfig): Configuration for upscaling. Usage: .. code-block:: python from google.genai.types import Image IMAGE_FILE_PATH="my-image.png" response = await client.aio.models.upscale_image( model='imagen-3.0-generate-001', image=types.Image.from_file(IMAGE_FILE_PATH), upscale_factor='x2', ) response.generated_images[0].image.show() # Opens my-image.png which is upscaled by a factor of 2. rrNrrrrrrrrrrarbrOr rrcrgs r!rjzAsyncModels.upscale_imagesFB   % \rF&%223$$&j>*>E#(:DA#->> ($$ 'NN+@$G",.. 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