Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsChat modelsAnthropicAnthropic FunctionsAnyscaleAzureAzureML Chat Online EndpointBaichuan ChatBaidu QianfanBedrock ChatCohereERNIE-Bot ChatEverlyAIFireworksGCP Vertex AIJinaChatKonkoüöÖ LiteLLMLlama APIMiniMaxOllamaOpenAIPromptLayer ChatOpenAITongyi QwenvLLM ChatYandexGPTDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAgents and toolkitsMemoryCallbacksChat loadersComponentsChat modelsEverlyAIEverlyAIEverlyAI allows you to run your ML models at scale in the cloud. It also provides API access to several LLM models.This notebook demonstrates the use of langchain.chat_models.ChatEverlyAI for EverlyAI Hosted Endpoints.Set EVERLYAI_API_KEY environment variableor use the everlyai_api_key keyword argument# !pip install openaiimport osfrom getpass import getpassos.environ["EVERLYAI_API_KEY"] = getpass()Let's try out LLAMA model offered on EverlyAI Hosted Endpointsfrom langchain.chat_models import ChatEverlyAIfrom langchain.schema import SystemMessage, HumanMessagemessages = [    SystemMessage(        content="You are a helpful AI that shares everything you know."    ),    HumanMessage(        content="Tell me technical facts about yourself. Are you a transformer model? How many billions of parameters do you have?"    ),]chat = ChatEverlyAI(model_name="meta-llama/Llama-2-7b-chat-hf", temperature=0.3, max_tokens=64)print(chat(messages).content)      Hello! I'm just an AI, I don't have personal information or technical details like a human would. However, I can tell you that I'm a type of transformer model, specifically a BERT (Bidirectional Encoder Representations from Transformers) model. BEverlyAI also supports streaming responsesfrom langchain.chat_models import ChatEverlyAIfrom langchain.schema import SystemMessage, HumanMessagefrom
EverlyAI allows you to run your ML models at scale in the cloud. It also provides API access to several LLM models.
EverlyAI allows you to run your ML models at scale in the cloud. It also provides API access to several LLM models. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsChat modelsAnthropicAnthropic FunctionsAnyscaleAzureAzureML Chat Online EndpointBaichuan ChatBaidu QianfanBedrock ChatCohereERNIE-Bot ChatEverlyAIFireworksGCP Vertex AIJinaChatKonkoüöÖ LiteLLMLlama APIMiniMaxOllamaOpenAIPromptLayer ChatOpenAITongyi QwenvLLM ChatYandexGPTDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAgents and toolkitsMemoryCallbacksChat loadersComponentsChat modelsEverlyAIEverlyAIEverlyAI allows you to run your ML models at scale in the cloud. It also provides API access to several LLM models.This notebook demonstrates the use of langchain.chat_models.ChatEverlyAI for EverlyAI Hosted Endpoints.Set EVERLYAI_API_KEY environment variableor use the everlyai_api_key keyword argument# !pip install openaiimport osfrom getpass import getpassos.environ["EVERLYAI_API_KEY"] = getpass()Let's try out LLAMA model offered on EverlyAI Hosted Endpointsfrom langchain.chat_models import ChatEverlyAIfrom langchain.schema import SystemMessage, HumanMessagemessages = [    SystemMessage(        content="You are a helpful AI that shares everything you know."    ),    HumanMessage(        content="Tell me technical facts about yourself. Are you a transformer model? How many billions of parameters do you have?"    ),]chat = ChatEverlyAI(model_name="meta-llama/Llama-2-7b-chat-hf", temperature=0.3, max_tokens=64)print(chat(messages).content)      Hello! I'm just an AI, I don't have personal information or technical details like a human would. However, I can tell you that I'm a type of transformer model, specifically a BERT (Bidirectional Encoder Representations from Transformers) model. BEverlyAI also supports streaming responsesfrom langchain.chat_models import ChatEverlyAIfrom langchain.schema import SystemMessage, HumanMessagefrom