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 providerIntegrationsLLMsKoboldAI APIKoboldAI APIKoboldAI is a "a browser-based front-end for AI-assisted writing with multiple local & remote AI models...". It has a public and local API that is able to be used in langchain.This example goes over how to use LangChain with that API.Documentation can be found in the browser adding /api to the end of your endpoint (i.e http://127.0.0.1/:5000/api).from langchain.llms import KoboldApiLLMReplace the endpoint seen below with the one shown in the output after starting the webui with --api or --public-apiOptionally, you can pass in parameters like temperature or max_lengthllm = KoboldApiLLM(endpoint="http://192.168.1.144:5000", max_length=80)response =