ڰj/9-2SrSSKJr SSKJr SSKJr SSKJr SSKJ r SSKJ r SS KJr SSKJr SS KJr SSKJ r SS KJr SES \\S \4SjjrSES\S \\S \4SjjrSES \\S \4SjjrSFS\S\S \\4SjjrSES \\S \4SjjrSES\S \\4SjjrSGS\S\\S\\S\S\S\S\\S\\S \S!\S"\\S#\S$\S%\S&\\S'\S(\\S)\\S*\\S+\\S,\\S \4,S-jjr S\4S.jr!S\S \4S/jr"S\4S0jr#SHS\S\S1\S"\S!\S'\S&\S(\S2\S3\4S4jjr$S \4S5jr%SIS\S)\S6\S*\S7\S8\S9\S:\S;\S<\S+\S \4S=jjr&S>\S)\4S?jr'S\S@\SA\4SBjr(S3\S@\SA\4SCjr)S3\4SDjr*g )Jz% Runpod | API Wrapper | CTL Commands )Optional)run_graphql_query)container_register_auth) endpoints)pods) templates)user)gpusNapi_keyreturncF[[RUS9nUSSnU$)zr Get the current user with optional API key override. Args: api_key: Optional API key to use for this query. r datamyself)r user_queries QUERY_USERr raw_responsecleaned_returns T/home/mande/repo/quber/.venv/lib/python3.13/site-packages/runpod/api/ctl_commands.pyget_userrs+%\%<%?N rcF[[RUS9nUSSnU$)zO Get all GPU types Args: api_key: Optional API key to use for this query. rrgpuTypes)rr QUERY_GPU_TYPESrs rget_gpusr#1s+%T%9%97KL!&)*5N rgpu_id gpu_quantityc[[R"X5US9nUSSn[U5S:a [ S5eUS$)z Get a specific GPU type Args: gpu_id: the id of the gpu gpu_quantity: how many of the gpu should be returned api_key: Optional API key to use for this query. rrr!rzSNo GPU found with the specified ID, run runpod.get_gpus() to get a list of all GPUsr)rr generate_gpu_querylen ValueError)r$r%r rrs rget_gpur*=s\% 5L "&)*5N >Q >  ! rcL[[RUS9nUSSSnU$)zJ Get all pods Args: api_key: Optional API key to use for this query. rrrr)r pod_queries QUERY_POD)r raw_returnrs rget_podsr/Vs0#;#8#8'JJ'1&9N rpod_idcN[[R"U5US9nUSS$)zn Get a specific pod Args: pod_id: the id of the pod api_key: Optional API key to use for this query. rrpod)rr,generate_pod_query)r0r rs rget_podr4bs1%&&v.L   &&rname image_name gpu_type_id cloud_typesupport_public_ip start_sshdata_center_id country_code gpu_count volume_in_gbcontainer_disk_in_gbmin_vcpu_countmin_memory_in_gb docker_argsportsvolume_mount_pathenv template_idnetwork_volume_idallowed_cuda_versions instance_idcU(dU(d [S5eUb [U5 US;a [S5eU(a)Uc&[5nUSHnUSU:XdMUSn O U cUcSn [[R "UUUUUUUUUbUOSU U U U U UUUUUUUUU55nUb US S nU$US S nU$) a Create a pod :param name: the name of the pod :param image_name: the name of the docker image to be used by the pod :param gpu_type_id: the gpu type wanted by the pod (retrievable by get_gpus). If None, creates a CPU-only pod :param cloud_type: if secure cloud, community cloud or all is wanted :param data_center_id: the id of the data center :param country_code: the code for country to start the pod in :param gpu_count: how many gpus should be attached to the pod (ignored for CPU-only pods) :param volume_in_gb: how big should the pod volume be :param ports: the ports to open in the pod, example format - "8888/http,666/tcp" :param volume_mount_path: where to mount the volume? :param env: the environment variables to inject into the pod, for example {EXAMPLE_VAR:"example_value", EXAMPLE_VAR2:"example_value 2"}, will inject EXAMPLE_VAR and EXAMPLE_VAR2 into the pod with the mentioned values :param template_id: the id of the template to use for the pod :param min_download: minimum download speed in Mbps :param min_upload: minimum upload speed in Mbps :param instance_id: the id of a specific instance to deploy to (for CPU pods) :example: >>> # Create GPU pod >>> pod_id = runpod.create_pod("test", "runpod/stack", "NVIDIA GeForce RTX 3070") >>> # Create CPU pod >>> pod_id = runpod.create_pod("test", "runpod/stack") >>> # Create CPU pod on specific instance >>> pod_id = runpod.create_pod("test", "runpod/stack", instance_id="cpu3c-2-4") z1Either image_name or template_id must be providedN)ALL COMMUNITYSECUREz2cloud_type must be one of ALL, COMMUNITY or SECUREnetworkVolumesid dataCenterId rpodFindAndDeployOnDemand deployCpuPod)r)r*rr pod_mutations generate_pod_deployment_mutation)r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFrGrH min_download min_uploadrI user_infonetwork_volumercleaned_responses r create_podr[qs#p kLMM 77MNN^3J '(89Nd#'88!/!?: # (;!$66        $0Id          !   / L8'/0JK (/? rcT[[R"U55nUSSnU$)z Stop a pod :param pod_id: the id of the pod :example: >>> pod_id = runpod.create_pod("test", "runpod/stack", "NVIDIA GeForce RTX 3070") >>> runpod.stop_pod(pod_id) rpodStop)rrTgenerate_pod_stop_mutation)r0rrZs rstop_podr_s/%]%M%Mf%UVL#F+I6 rcT[[R"X55nUSSnU$)a Resume a pod :param pod_id: the id of the pod :param gpu_count: the number of GPUs to attach to the pod :example: >>> pod_id = runpod.create_pod("test", "runpod/stack", "NVIDIA GeForce RTX 3070") >>> runpod.stop_pod(pod_id) >>> runpod.resume_pod(pod_id) r podResume)rrTgenerate_pod_resume_mutation)r0r=rrZs r resume_podrcs4%226EL$F+K8 rcB[[R"U55 g)z Terminate a pod :param pod_id: the id of the pod :example: >>> pod_id = runpod.create_pod("test", "runpod/stack", "NVIDIA GeForce RTX 3070") >>> runpod.terminate_pod(pod_id) N)rrTgenerate_pod_terminate_mutation)r0s r terminate_podrfsmCCFKLrdocker_start_cmd is_serverlessregistry_auth_idc ^[[R"UUUUUUUUUU S9 5n U SS$)a Create a template :param name: the name of the template :param image_name: the name of the docker image to be used by the template :param docker_start_cmd: the command to start the docker container with :param container_disk_in_gb: how big should the container disk be :param volume_in_gb: how big should the volume be :param ports: the ports to open in the pod, example format - "8888/http,666/tcp" :param volume_mount_path: where to mount the volume? :param env: the environment variables to inject into the pod, for example {EXAMPLE_VAR:"example_value", EXAMPLE_VAR2:"example_value 2"}, will inject EXAMPLE_VAR and EXAMPLE_VAR2 into the pod with the mentioned values :param is_serverless: is the template serverless? :param registry_auth_id: the id of the registry auth :example: >>> template_id = runpod.create_template("test", "runpod/stack", "python3 main.py") ) r5r6rgr?r>rDrCrErhrir saveTemplate)rtemplate_mutationsgenerate_pod_template) r5r6rgr?r>rDrCrErhrirs rcreate_templaternsM@%00!-!5%/'-  L   //rcN[[R5nUSSSnU$)z Get all endpoints rrr)rendpoint_queriesQUERY_ENDPOINT)r.rs r get_endpointsrrDs/##3#B#BCJ'1+>N rgpu_ids locations idle_timeout scaler_type scaler_value workers_min workers_maxc h[[R"UUUUUUUUUU U U U 5 5n U SS$)aY Create an endpoint :param name: the name of the endpoint :param template_id: the id of the template to use for the endpoint :param gpu_ids: the ids of the GPUs to use for the endpoint :param network_volume_id: the id of the network volume to use for the endpoint :param locations: the locations to use for the endpoint :param idle_timeout: the idle timeout for the endpoint :param scaler_type: the scaler type for the endpoint :param scaler_value: the scaler value for the endpoint :param workers_min: the minimum number of workers for the endpoint :param workers_max: the maximum number of workers for the endpoint :param allowed_cuda_versions: Comma-separated list of allowed CUDA versions (e.g., ["12.4", "12.5"]). :param gpu_count: the number of GPUs to use for the endpoint :example: >>> endpoint_id = runpod.create_endpoint("test", "template_id") r saveEndpoint)rendpoint_mutationsgenerate_endpoint_mutation)r5rFrsrGrtrurvrwrxry flashbootrHr=rs rcreate_endpointrMsVF%55            !  L$   //r endpoint_idcP[[R"X55nUSS$)z Update an endpoint template :param endpoint_id: the id of the endpoint :param template_id: the id of the template to use for the endpoint :example: >>> endpoint_id = runpod.update_endpoint_template("test", "template_id") rupdateEndpointTemplate)rr|!update_endpoint_template_mutation)rrFrs rupdate_endpoint_templaters/%<<[VL   8 99rusernamepasswordcR[[R"XU55nUSS$)a0 Create a container registry authentication. Args: name (str): The name of the container registry. username (str): The username for authentication. password (str): The password for authentication. Returns: dict: The response data containing the saved container registry authentication. rsaveRegistryAuth)r!container_register_auth_mutations generate_container_registry_auth)r5rrrs rcreate_container_registry_authrs4%)JJ H L   2 33rcR[[R"XU55nUSS$)aJ Update a container registry authentication. Args: registry_auth_id (str): The id of the container registry authentication username (str): The username for authentication. password (str): The password for authentication. Returns: dict: The response data containing the updated container registry authentication. rupdateRegistryAuth)rrupdate_container_registry_auth)rirrrs rrrs4%)HH  L   4 55rcP[[R"U55nUSS$)z Delete a container registry authentication. Args: registry_auth_id (str): The id of the container registry authentication rdeleteRegistryAuth)rrdelete_container_registry_auth)rirs rrrs2%)HH  L   4 55r)N)rN)NrKTTNNrrNrrrNz/runpod-volumeNNNNNNN)NrQNNNNFN) AMPERE_16NN QUEUE_DELAYrFNr)+__doc__typingrgraphqlr mutationsrrrr|rrTr rlr rqueriesrpr r,rstrdictrrr#intr*r/r4boollistr[r_rcrfrnrrrrrrrrrrs &S6,6-2() hsm t   x}   hsm t Cs#2 hsm t  'C '(3- '"!#!%"$("&*.-!%'+,0!%/j j j#j j  j  jSMj3-jjj#3-jjjj C=j !j" $#j$#%j& }'j($D>)j.#/j0 1jZS"ss* M# M"! "! /0 /0/0/0 /0  /0  /0 /0 /0/0/0dt!$!%50 505050 50  50  50505050505050p:#:C:$444s4(6S6C6SV6( 6S 6r