text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsAI21Aleph AlphaAmazon API GatewayAnyscaleAzure OpenAIAzureML Online EndpointBananaBasetenBeamBedrockCerebriumAIChatGLMClarifaiCohereC TransformersDatabricksDeepInfraForefrontAIGoogle Cloud Platform Vertex AI PaLMGooseAIGPT4AllHugging Face HubHugging Face Local PipelinesHuggingface TextGen InferenceJSONFormerKoboldAI APILlama-cppCaching integrationsManifestModalMosaicMLNLP CloudoctoaiOpenAIOpenLLMOpenLMPetalsPipelineAIPredibasePrediction GuardPromptLayer OpenAIRELLMReplicateRunhouseSageMakerEndpointStochasticAITextGenTongyi QwenWriterMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsLLMsPipelineAIOn this pagePipelineAIPipelineAI allows you to run your ML models at scale in the cloud. It also provides API access to several LLM models.This notebook goes over how to use Langchain with PipelineAI.Install pipeline-aiâ€‹The pipeline-ai library is required to use the PipelineAI API, AKA Pipeline Cloud. Install pipeline-ai using pip install pipeline-ai.# Install the packagepip install pipeline-aiImportsâ€‹import osfrom langchain.llms import PipelineAIfrom langchain import PromptTemplate, LLMChainSet the Environment API Keyâ€‹Make sure to get your API key from PipelineAI. Check out the cloud quickstart guide. You'll be given a 30 day free trial with 10 hours of serverless GPU compute to test different models.os.environ["PIPELINE_API_KEY"] =