tni[9-fdZddlmZddlmZddlmZddlmZ ddlm Z ddlm Z dd lmZddlmZdd lmZddlm Zdd lmZdPd eed efdZdPded eed efdZdPd eed efdZdQdeded eefdZdPd eed efdZdPded eefdZ dRdedeedeeded ed!ed"eed#eed$ed%ed&eed'ed(ed)ed*eed+ed,eed-eed.eed/eed0eed ef,d1Z defd2Z!ded$efd3Z"defd4Z# dSdeded7ed&ed%ed+ed*ed,ed8ed9efd:Z$d efd;Z% dTded-edAed.edBedCedDedEedFedGed/ed$efdHZ&dIed-efdJZ'dedKedLefdMZ(d9edKedLefdNZ)d9efdOZ*d S)Uz% Runpod | API Wrapper | CTL Commands )Optional)run_graphql_query)container_register_auth) endpoints)pods) templates)user)gpusNapi_keyreturncXttj|}|dd}|S)z 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/var/www/html/gpu-tools/venv/lib/python3.11/site-packages/runpod/api/ctl_commands.pyget_userrs.%\%?N rcXttj|}|dd}|S)zc Get all GPU types Args: api_key: Optional API key to use for this query. rrgpuTypes)rr QUERY_GPU_TYPESrs rget_gpusr#1s.%T%97KKKL!&)*5N rgpu_id gpu_quantitycttj|||}|dd}t|dkrt d|dS)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*=ss%  55L "&)*5N >Q >   ! rcdttj|}|ddd}|S)z^ 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/Vs3#;#8'JJJJ'1&9N rpod_idcdttj||}|ddS)z 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_podr4bs;%&v..L   &&rALLT/runpod-volumename 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_idc|s|std|t||dvrtd|r1|/t}|dD]}|d|kr |d}n| |d} tt j||||||||||nd| | | | | |||||||||}t d |||d d }n|d d }|S) 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)r6 COMMUNITYSECUREz2cloud_type must be one of ALL, COMMUNITY or SECUREnetworkVolumesid dataCenterId zraw_response: rpodFindAndDeployOnDemand deployCpuPod)r)r*rr pod_mutations generate_pod_deployment_mutationprint)r8r9r:r;r<r=r>r?r@rArBrCrDrErFrGrHrIrJrK min_download min_uploadrL user_infonetwork_volumercleaned_responses r create_podr^qsmp NkNLMMM 777MNNN^3JJ '(89  Nd#'888!/!?9# (;!$6        $0IId          !   /  L8 )< ) )***'/0JK'/? rcdttj|}|dd}|S)z Stop a pod :param pod_id: the id of the pod :example: >>> pod_id = runpod.create_pod("test", "runpod/stack", "NVIDIA GeForce RTX 3070") >>> runpod.stop_pod(pod_id) rpodStop)rrVgenerate_pod_stop_mutation)r0rr]s rstop_podrbs2%]%Mf%U%UVVL#F+I6 rcfttj||}|dd}|S)a" Resume a pod :param pod_id: the id of the pod :param gpu_count: the number of GPUs to attach to the pod :example: >>> pod_id = runpod.create_pod("test", "runpod/stack", "NVIDIA GeForce RTX 3070") >>> runpod.stop_pod(pod_id) >>> runpod.resume_pod(pod_id) r podResume)rrVgenerate_pod_resume_mutation)r0r@rr]s r resume_podrfs;%269EEL$F+K8 rcHttj|dS)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)rrVgenerate_pod_terminate_mutation)r0s r terminate_podris#mCFKKLLLLLrrSFdocker_start_cmd is_serverlessregistry_auth_idc tttj||||||||||  } | ddS)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") ) r8r9rjrBrArGrFrHrkrlr saveTemplate)rtemplate_mutationsgenerate_pod_template) r8r9rjrBrArGrFrHrkrlrs rcreate_templaterqsY@%0!-!5%/'-   L   //rc`ttj}|ddd}|S)z Get all endpoints rrr)rendpoint_queriesQUERY_ENDPOINT)r.rs r get_endpointsruFs/##3#BCCJ'1+>N r AMPERE_16 QUEUE_DELAYgpu_ids locations idle_timeout scaler_type scaler_value workers_min workers_maxc xttj|||||||||| | | | } | ddS)a 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)r8rIr{rJr|r}r~rrr flashbootrKr@rs rcreate_endpointrOs]F%5            !   L$   //r endpoint_idcbttj||}|ddS)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)rrIrs rupdate_endpoint_templaters6%<[+VVL   8 99rusernamepasswordcdttj|||}|ddS)aP 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)r8rrrs rcreate_container_registry_authrs=%)J (H  L   2 33rcdttj|||}|ddS)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)rlrrrs rrrs=%)H h  L   4 55rc`ttj|}|ddS)z Delete a container registry authentication. Args: registry_auth_id (str): The id of the container registry authentication rdeleteRegistryAuth)rrdelete_container_registry_auth)rlrs rrrs9%)H   L   4 55r)N)rN)r5Nr6TTNNrrNrrr5Nr7NNNNNNN)NrSNNNNFN) rvNNrwrxryrrzFNr)+__doc__typingrgraphqlr mutationsrrrrrrVr ror rqueriesrsr r,rstrdictrrr#intr*r/r4boollistr^rbrfrirqrurrrrrrrrs &&&&&&SSSSSS666666,,,,,,666666------222222(((((())))))  hsm t       x}       hsm t    Cs#2  hsm t     ' 'C '(3- ' ' ' '"!#!%"$("&*.-!%'+,0!%/ll l l#l l  l  lSMl3-lll#3-llll C=l !l" $#l$#%l& }'l($D>)l.#/l0 1llll^S"ss* M# M M M M"! "! /0/0 /0/0/0 /0  /0  /0 /0 /0/0/0/0/0/0dt!$!%5050 505050 50  50  50505050505050505050p:#:C::::$444s4444(6S6C6SV6666( 6S 6 6 6 6 6 6r