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+ diff --git a/assets/js/0be1d5fe.47b01dee.js b/assets/js/0be1d5fe.47b01dee.js deleted file mode 100644 index ed8e79cd0b..0000000000 --- a/assets/js/0be1d5fe.47b01dee.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunklangflow_docs=self.webpackChunklangflow_docs||[]).push([[145],{73630:(e,t,n)=>{n.r(t),n.d(t,{assets:()=>h,contentTitle:()=>l,default:()=>a,frontMatter:()=>i,metadata:()=>s,toc:()=>c});const s=JSON.parse('{"id":"Components/components-models","title":"Models","description":"Model components generate text using large language models.","source":"@site/docs/Components/components-models.md","sourceDirName":"Components","slug":"/components-models","permalink":"/components-models","draft":false,"unlisted":false,"tags":[],"version":"current","frontMatter":{"title":"Models","slug":"/components-models"},"sidebar":"docs","previous":{"title":"Memories","permalink":"/components-memories"},"next":{"title":"Processing","permalink":"/components-processing"}}');var d=n(74848),r=n(28453);const i={title:"Models",slug:"/components-models"},l="Model components in Langflow",h={},c=[{value:"Use a model component in a flow",id:"use-a-model-component-in-a-flow",level:2},{value:"AI/ML API",id:"aiml-api",level:2},{value:"Inputs",id:"inputs",level:3},{value:"Outputs",id:"outputs",level:3},{value:"Amazon Bedrock",id:"amazon-bedrock",level:2},{value:"Inputs",id:"inputs-1",level:3},{value:"Outputs",id:"outputs-1",level:3},{value:"Anthropic",id:"anthropic",level:2},{value:"Inputs",id:"inputs-2",level:3},{value:"Outputs",id:"outputs-2",level:3},{value:"Azure OpenAI",id:"azure-openai",level:2},{value:"Inputs",id:"inputs-3",level:3},{value:"Cohere",id:"cohere",level:2},{value:"Inputs",id:"inputs-4",level:3},{value:"Outputs",id:"outputs-3",level:3},{value:"Google Generative AI",id:"google-generative-ai",level:2},{value:"Inputs",id:"inputs-5",level:3},{value:"Groq",id:"groq",level:2},{value:"Inputs",id:"inputs-6",level:3},{value:"Outputs",id:"outputs-4",level:3},{value:"Hugging Face API",id:"hugging-face-api",level:2},{value:"Inputs",id:"inputs-7",level:3},{value:"Maritalk",id:"maritalk",level:2},{value:"Inputs",id:"inputs-8",level:3},{value:"Outputs",id:"outputs-5",level:3},{value:"Mistral",id:"mistral",level:2},{value:"Inputs",id:"inputs-9",level:3},{value:"Outputs",id:"outputs-6",level:3},{value:"NVIDIA",id:"nvidia",level:2},{value:"Inputs",id:"inputs-10",level:3},{value:"Outputs",id:"outputs-7",level:3},{value:"Ollama",id:"ollama",level:2},{value:"Inputs",id:"inputs-11",level:3},{value:"Outputs",id:"outputs-8",level:3},{value:"OpenAI",id:"openai",level:2},{value:"Inputs",id:"inputs-12",level:3},{value:"Outputs",id:"outputs-9",level:3},{value:"Qianfan",id:"qianfan",level:2},{value:"OpenRouter",id:"openrouter",level:2},{value:"Inputs",id:"inputs-13",level:3},{value:"Outputs",id:"outputs-10",level:3},{value:"Perplexity",id:"perplexity",level:2},{value:"Inputs",id:"inputs-14",level:3},{value:"Outputs",id:"outputs-11",level:3},{value:"SambaNova",id:"sambanova",level:2},{value:"Inputs",id:"inputs-15",level:3},{value:"Outputs",id:"outputs-12",level:3},{value:"VertexAI",id:"vertexai",level:2},{value:"Inputs",id:"inputs-16",level:3},{value:"Outputs",id:"outputs-13",level:3},{value:"Novita AI",id:"novita-ai",level:2},{value:"Parameters",id:"parameters",level:3},{value:"Inputs",id:"inputs-17",level:4}];function o(e){const t={a:"a",code:"code",h1:"h1",h2:"h2",h3:"h3",h4:"h4",header:"header",img:"img",p:"p",strong:"strong",table:"table",tbody:"tbody",td:"td",th:"th",thead:"thead",tr:"tr",...(0,r.R)(),...e.components};return(0,d.jsxs)(d.Fragment,{children:[(0,d.jsx)(t.header,{children:(0,d.jsx)(t.h1,{id:"model-components-in-langflow",children:"Model components in Langflow"})}),"\n",(0,d.jsx)(t.p,{children:"Model components generate text using large language models."}),"\n",(0,d.jsx)(t.p,{children:"Refer to your specific component's documentation for more information on parameters."}),"\n",(0,d.jsx)(t.h2,{id:"use-a-model-component-in-a-flow",children:"Use a model component in a flow"}),"\n",(0,d.jsx)(t.p,{children:"Model components receive inputs and prompts for generating text, and the generated text is sent to an output component."}),"\n",(0,d.jsxs)(t.p,{children:["The model output can also be sent to the ",(0,d.jsx)(t.strong,{children:"Language Model"})," port and on to a ",(0,d.jsx)(t.strong,{children:"Parse Data"})," component, where the output can be parsed into structured ",(0,d.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," objects."]}),"\n",(0,d.jsxs)(t.p,{children:["This example has the OpenAI model in a chatbot flow. 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Options include various models."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"aws_access_key"}),(0,d.jsx)(t.td,{children:"SecretString"}),(0,d.jsx)(t.td,{children:"AWS Access Key for authentication."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"aws_secret_key"}),(0,d.jsx)(t.td,{children:"SecretString"}),(0,d.jsx)(t.td,{children:"AWS Secret Key for authentication."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"credentials_profile_name"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"Name of the AWS credentials profile to use (advanced)."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"region_name"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsxs)(t.td,{children:["AWS region name. Default: ",(0,d.jsx)(t.code,{children:"us-east-1"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"model_kwargs"}),(0,d.jsx)(t.td,{children:"Dictionary"}),(0,d.jsx)(t.td,{children:"Additional keyword arguments for the model (advanced)."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"endpoint_url"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"Custom endpoint URL for the Bedrock service (advanced)."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-1",children:"Outputs"}),"\n",(0,d.jsxs)(t.table,{children:[(0,d.jsx)(t.thead,{children:(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.th,{children:"Name"}),(0,d.jsx)(t.th,{children:"Type"}),(0,d.jsx)(t.th,{children:"Description"})]})}),(0,d.jsx)(t.tbody,{children:(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"model"}),(0,d.jsx)(t.td,{children:"LanguageModel"}),(0,d.jsx)(t.td,{children:"An instance of ChatBedrock configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"anthropic",children:"Anthropic"}),"\n",(0,d.jsx)(t.p,{children:"This component allows the generation of text using Anthropic Chat and Language models."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://docs.anthropic.com/en/docs/welcome",children:"Anthropic documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-2",children:"Inputs"}),"\n",(0,d.jsxs)(t.table,{children:[(0,d.jsx)(t.thead,{children:(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.th,{children:"Name"}),(0,d.jsx)(t.th,{children:"Type"}),(0,d.jsx)(t.th,{children:"Description"})]})}),(0,d.jsxs)(t.tbody,{children:[(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"max_tokens"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsxs)(t.td,{children:["The maximum number of tokens to generate. 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Defaults to ",(0,d.jsx)(t.code,{children:"https://api.anthropic.com"})," if not specified (advanced)."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"prefill"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"Prefill text to guide the model's response (advanced)."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-2",children:"Outputs"}),"\n",(0,d.jsxs)(t.table,{children:[(0,d.jsx)(t.thead,{children:(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.th,{children:"Name"}),(0,d.jsx)(t.th,{children:"Type"}),(0,d.jsx)(t.th,{children:"Description"})]})}),(0,d.jsx)(t.tbody,{children:(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"model"}),(0,d.jsx)(t.td,{children:"LanguageModel"}),(0,d.jsx)(t.td,{children:"An instance of ChatAnthropic configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"azure-openai",children:"Azure OpenAI"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using Azure OpenAI LLM."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://learn.microsoft.com/en-us/azure/ai-services/openai/",children:"Azure OpenAI documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-3",children:"Inputs"}),"\n",(0,d.jsxs)(t.table,{children:[(0,d.jsx)(t.thead,{children:(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.th,{children:"Name"}),(0,d.jsx)(t.th,{children:"Display Name"}),(0,d.jsx)(t.th,{children:"Info"})]})}),(0,d.jsxs)(t.tbody,{children:[(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Model Name"}),(0,d.jsx)(t.td,{children:"Model Name"}),(0,d.jsx)(t.td,{children:"Specifies the name of the Azure OpenAI model to be used for text generation."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Azure Endpoint"}),(0,d.jsx)(t.td,{children:"Azure Endpoint"}),(0,d.jsx)(t.td,{children:"Your Azure endpoint, including the resource."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Deployment Name"}),(0,d.jsx)(t.td,{children:"Deployment Name"}),(0,d.jsx)(t.td,{children:"Specifies the name of the deployment."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"API Version"}),(0,d.jsx)(t.td,{children:"API Version"}),(0,d.jsx)(t.td,{children:"Specifies the version of the Azure OpenAI API to be used."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"API Key"}),(0,d.jsx)(t.td,{children:"API Key"}),(0,d.jsx)(t.td,{children:"Your Azure OpenAI API key."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Temperature"}),(0,d.jsx)(t.td,{children:"Temperature"}),(0,d.jsxs)(t.td,{children:["Specifies the sampling temperature. 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e={5354:0,1869:0};r.f.j=(a,d)=>{var c=r.o(e,a)?e[a]:void 0;if(0!==c)if(c)d.push(c[2]);else if(/^(1869|5354)$/.test(a))e[a]=0;else{var f=new Promise(((d,f)=>c=e[a]=[d,f]));d.push(c[2]=f);var b=r.p+r.u(a),t=new Error;r.l(b,(d=>{if(r.o(e,a)&&(0!==(c=e[a])&&(e[a]=void 0),c)){var f=d&&("load"===d.type?"missing":d.type),b=d&&d.target&&d.target.src;t.message="Loading chunk "+a+" failed.\n("+f+": "+b+")",t.name="ChunkLoadError",t.type=f,t.request=b,c[1](t)}}),"chunk-"+a,a)}},r.O.j=a=>0===e[a];var a=(a,d)=>{var c,f,b=d[0],t=d[1],o=d[2],n=0;if(b.some((a=>0!==e[a]))){for(c in t)r.o(t,c)&&(r.m[c]=t[c]);if(o)var i=o(r)}for(a&&a(d);n - + diff --git a/components-custom-components.html b/components-custom-components.html index 6839a12ada..eb99f229d7 100644 --- a/components-custom-components.html +++ b/components-custom-components.html @@ -10,7 +10,7 @@ - + diff --git a/components-data.html b/components-data.html index ef860dde46..fbe8a20f0b 100644 --- a/components-data.html +++ b/components-data.html @@ -10,7 +10,7 @@ - + diff --git a/components-embedding-models.html b/components-embedding-models.html index d379878fc8..23e13d3df6 100644 --- a/components-embedding-models.html +++ b/components-embedding-models.html @@ -10,7 +10,7 @@ - + diff --git a/components-helpers.html b/components-helpers.html index 748edfa77a..bb126a92f5 100644 --- a/components-helpers.html +++ b/components-helpers.html @@ -10,7 +10,7 @@ - + diff --git a/components-io.html b/components-io.html index 1ff06a4cc1..f7e38bb849 100644 --- a/components-io.html +++ b/components-io.html @@ -10,7 +10,7 @@ - + diff --git a/components-loaders.html b/components-loaders.html index d841392b4a..13b63d6773 100644 --- a/components-loaders.html +++ b/components-loaders.html @@ -10,7 +10,7 @@ - + diff --git a/components-logic.html b/components-logic.html index 183a40f0ed..29a367d319 100644 --- a/components-logic.html +++ b/components-logic.html @@ -10,7 +10,7 @@ - + diff --git a/components-memories.html b/components-memories.html index 2bf87bed22..6f8cc31d3c 100644 --- a/components-memories.html +++ b/components-memories.html @@ -10,7 +10,7 @@ - + diff --git a/components-models.html b/components-models.html index ac23369950..31e53bec9d 100644 --- a/components-models.html +++ b/components-models.html @@ -10,7 +10,7 @@ - + @@ -53,101 +53,120 @@

For more information, see the Azure OpenAI documentation.

Inputs​

NameDisplay NameInfo
Model NameModel NameSpecifies the name of the Azure OpenAI model to be used for text generation.
Azure EndpointAzure EndpointYour Azure endpoint, including the resource.
Deployment NameDeployment NameSpecifies the name of the deployment.
API VersionAPI VersionSpecifies the version of the Azure OpenAI API to be used.
API KeyAPI KeyYour Azure OpenAI API key.
TemperatureTemperatureSpecifies the sampling temperature. Defaults to 0.7.
Max TokensMax TokensSpecifies the maximum number of tokens to generate. Defaults to 1000.
Input ValueInput ValueSpecifies the input text for text generation.
StreamStreamSpecifies whether to stream the response from the model. Defaults to False.
+

Outputs​

+
NameTypeDescription
modelLanguageModelAn instance of AzureOpenAI configured with the specified parameters.

Cohere​

This component generates text using Cohere's language models.

For more information, see the Cohere documentation.

Inputs​

NameDisplay NameInfo
Cohere API KeyCohere API KeyYour Cohere API key.
Max TokensMax TokensSpecifies the maximum number of tokens to generate. Defaults to 256.
TemperatureTemperatureSpecifies the sampling temperature. Defaults to 0.75.
Input ValueInput ValueSpecifies the input text for text generation.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of the Cohere model configured with the specified parameters.
+

DeepSeek​

+

This component generates text using DeepSeek's language models.

+

For more information, see the DeepSeek documentation.

+

Inputs​

+
NameTypeDescription
max_tokensIntegerMaximum number of tokens to generate. Set to 0 for unlimited. Range: 0-128000.
model_kwargsDictionaryAdditional keyword arguments for the model.
json_modeBooleanIf True, outputs JSON regardless of passing a schema.
model_nameStringThe DeepSeek model to use. Default: deepseek-chat.
api_baseStringBase URL for API requests. Default: https://api.deepseek.com.
api_keySecretStringYour DeepSeek API key for authentication.
temperatureFloatControls randomness in responses. Range: [0.0, 2.0]. Default: 1.0.
seedIntegerNumber initialized for random number generation. Use the same seed integer for more reproducible results, and use a different seed number for more random results.
+

Outputs​

+
NameTypeDescription
modelLanguageModelAn instance of ChatOpenAI configured with the specified parameters.

Google Generative AI​

This component generates text using Google's Generative AI models.

For more information, see the Google Generative AI documentation.

-

Inputs​

+

Inputs​

NameDisplay NameInfo
Google API KeyGoogle API KeyYour Google API key to use for the Google Generative AI.
ModelModelThe name of the model to use, such as "gemini-pro".
Max Output TokensMax Output TokensThe maximum number of tokens to generate.
TemperatureTemperatureRun inference with this temperature.
Top KTop KConsider the set of top K most probable tokens.
Top PTop PThe maximum cumulative probability of tokens to consider when sampling.
NNNumber of chat completions to generate for each prompt.
+

Outputs​

+
NameTypeDescription
modelLanguageModelAn instance of ChatGoogleGenerativeAI configured with the specified parameters.

Groq​

This component generates text using Groq's language models.

For more information, see the Groq documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
groq_api_keySecretStringAPI key for the Groq API.
groq_api_baseStringBase URL path for API requests. Default: https://api.groq.com (advanced).
max_tokensIntegerThe maximum number of tokens to generate (advanced).
temperatureFloatControls randomness in the output. Range: [0.0, 1.0]. Default: 0.1.
nIntegerNumber of chat completions to generate for each prompt (advanced).
model_nameStringThe name of the Groq model to use. Options are dynamically fetched from the Groq API.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of ChatGroq configured with the specified parameters.

Hugging Face API​

This component generates text using Hugging Face's language models.

For more information, see the Hugging Face documentation.

-

Inputs​

+

Inputs​

NameDisplay NameInfo
Endpoint URLEndpoint URLThe URL of the Hugging Face Inference API endpoint.
TaskTaskSpecifies the task for text generation.
API TokenAPI TokenThe API token required for authentication.
Model KwargsModel KwargsAdditional keyword arguments for the model.
Input ValueInput ValueThe input text for text generation.
+

LMStudio​

+

This component generates text using LM Studio's local language models.

+

For more information, see LM Studio documentation.

+

Inputs​

+
NameTypeDescription
base_urlStringThe URL where LM Studio is running. Default: "http://localhost:1234".
max_tokensIntegerMaximum number of tokens to generate in the response. Default: 512.
temperatureFloatControls randomness in the output. Range: [0.0, 2.0]. Default: 0.7.
top_pFloatControls diversity via nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.
stopList[String]List of strings that will stop generation when encountered (advanced).
streamBooleanWhether to stream the response. Default: False.
presence_penaltyFloatPenalizes repeated tokens. Range: [-2.0, 2.0]. Default: 0.0.
frequency_penaltyFloatPenalizes frequent tokens. Range: [-2.0, 2.0]. Default: 0.0.
+

Outputs​

+
NameTypeDescription
modelLanguageModelAn instance of LMStudio configured with the specified parameters.

Maritalk​

This component generates text using Maritalk LLMs.

For more information, see Maritalk documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens. Default: 512.
model_nameStringThe name of the Maritalk model to use. Options: sabia-2-small, sabia-2-medium. Default: sabia-2-small.
api_keySecretStringThe Maritalk API Key to use for authentication.
temperatureFloatControls randomness in the output. Range: [0.0, 1.0]. Default: 0.5.
endpoint_urlStringThe Maritalk API endpoint. Default: https://api.maritalk.com.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of ChatMaritalk configured with the specified parameters.

Mistral​

This component generates text using MistralAI LLMs.

For more information, see Mistral AI documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens (advanced).
model_nameStringThe name of the Mistral AI model to use. Options include open-mixtral-8x7b, open-mixtral-8x22b, mistral-small-latest, mistral-medium-latest, mistral-large-latest, and codestral-latest. Default: codestral-latest.
mistral_api_baseStringThe base URL of the Mistral API. Defaults to https://api.mistral.ai/v1 (advanced).
api_keySecretStringThe Mistral API Key to use for authentication.
temperatureFloatControls randomness in the output. Default: 0.5.
max_retriesIntegerMaximum number of retries for API calls. Default: 5 (advanced).
timeoutIntegerTimeout for API calls in seconds. Default: 60 (advanced).
max_concurrent_requestsIntegerMaximum number of concurrent API requests. Default: 3 (advanced).
top_pFloatNucleus sampling parameter. Default: 1 (advanced).
random_seedIntegerSeed for random number generation. Default: 1 (advanced).
safe_modeBooleanEnables safe mode for content generation (advanced).
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of ChatMistralAI configured with the specified parameters.
+

Novita AI​

+

This component generates text using Novita AI's language models.

+

For more information, see Novita AI documentation.

+

Inputs​

+
NameTypeDescription
api_keySecretStringYour Novita AI API Key.
modelStringThe id of the Novita AI model to use.
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens.
temperatureFloatControls randomness in the output. Range: [0.0, 1.0]. Default: 0.7.
top_pFloatControls the nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.
frequency_penaltyFloatControls the frequency penalty. Range: [0.0, 2.0]. Default: 0.0.
presence_penaltyFloatControls the presence penalty. Range: [0.0, 2.0]. Default: 0.0.
+

Outputs​

+
NameTypeDescription
modelLanguageModelAn instance of Novita AI model configured with the specified parameters.

NVIDIA​

This component generates text using NVIDIA LLMs.

For more information, see NVIDIA AI documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens (advanced).
model_nameStringThe name of the NVIDIA model to use. Default: mistralai/mixtral-8x7b-instruct-v0.1.
base_urlStringThe base URL of the NVIDIA API. Default: https://integrate.api.nvidia.com/v1.
nvidia_api_keySecretStringThe NVIDIA API Key for authentication.
temperatureFloatControls randomness in the output. Default: 0.1.
seedIntegerThe seed controls the reproducibility of the job (advanced). Default: 1.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of ChatNVIDIA configured with the specified parameters.

Ollama​

This component generates text using Ollama's language models.

For more information, see Ollama documentation.

-

Inputs​

+

Inputs​

NameDisplay NameInfo
Base URLBase URLEndpoint of the Ollama API.
Model NameModel NameThe model name to use.
TemperatureTemperatureControls the creativity of model responses.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of an Ollama model configured with the specified parameters.

OpenAI​

This component generates text using OpenAI's language models.

For more information, see OpenAI documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
api_keySecretStringYour OpenAI API Key.
modelStringThe name of the OpenAI model to use. Options include "gpt-3.5-turbo" and "gpt-4".
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens.
temperatureFloatControls randomness in the output. Range: [0.0, 1.0]. Default: 0.7.
top_pFloatControls the nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.
frequency_penaltyFloatControls the frequency penalty. Range: [0.0, 2.0]. Default: 0.0.
presence_penaltyFloatControls the presence penalty. Range: [0.0, 2.0]. Default: 0.0.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of OpenAI model configured with the specified parameters.
-

Qianfan​

-

This component generates text using Qianfan's language models.

-

For more information, see Qianfan documentation.

OpenRouter​

This component generates text using OpenRouter's unified API for multiple AI models from different providers.

For more information, see OpenRouter documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
api_keySecretStringYour OpenRouter API key for authentication.
site_urlStringYour site URL for OpenRouter rankings (advanced).
app_nameStringYour app name for OpenRouter rankings (advanced).
providerStringThe AI model provider to use.
model_nameStringThe specific model to use for chat completion.
temperatureFloatControls randomness in the output. Range: [0.0, 2.0]. Default: 0.7.
max_tokensIntegerThe maximum number of tokens to generate (advanced).
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of ChatOpenAI configured with the specified parameters.

Perplexity​

This component generates text using Perplexity's language models.

For more information, see Perplexity documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
model_nameStringThe name of the Perplexity model to use. Options include various Llama 3.1 models.
max_output_tokensIntegerThe maximum number of tokens to generate.
api_keySecretStringThe Perplexity API Key for authentication.
temperatureFloatControls randomness in the output. Default: 0.75.
top_pFloatThe maximum cumulative probability of tokens to consider when sampling (advanced).
nIntegerNumber of chat completions to generate for each prompt (advanced).
top_kIntegerNumber of top tokens to consider for top-k sampling. Must be positive (advanced).
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of ChatPerplexity configured with the specified parameters.
+

Qianfan​

+

This component generates text using Qianfan's language models.

+

For more information, see Qianfan documentation.

SambaNova​

This component generates text using SambaNova LLMs.

For more information, see Sambanova Cloud documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
sambanova_urlStringBase URL path for API requests. Default: https://api.sambanova.ai/v1/chat/completions.
sambanova_api_keySecretStringYour SambaNova API Key.
model_nameStringThe name of the Sambanova model to use. Options include various Llama models.
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens.
temperatureFloatControls randomness in the output. Range: [0.0, 1.0]. Default: 0.07.
-

Outputs​

+

Outputs​

NameTypeDescription
modelLanguageModelAn instance of SambaNova model configured with the specified parameters.

VertexAI​

This component generates text using Vertex AI LLMs.

For more information, see Google Vertex AI documentation.

-

Inputs​

+

Inputs​

NameTypeDescription
credentialsFileJSON credentials file. Leave empty to fallback to environment variables. File type: JSON.
model_nameStringThe name of the Vertex AI model to use. Default: "gemini-1.5-pro".
projectStringThe project ID (advanced).
locationStringThe location for the Vertex AI API. Default: "us-central1" (advanced).
max_output_tokensIntegerThe maximum number of tokens to generate (advanced).
max_retriesIntegerMaximum number of retries for API calls. Default: 1 (advanced).
temperatureFloatControls randomness in the output. Default: 0.0.
top_kIntegerThe number of highest probability vocabulary tokens to keep for top-k-filtering (advanced).
top_pFloatThe cumulative probability of parameter highest probability vocabulary tokens to keep for nucleus sampling. Default: 0.95 (advanced).
verboseBooleanWhether to print verbose output. Default: False (advanced).
-

Outputs​

-
NameTypeDescription
modelLanguageModelAn instance of ChatVertexAI configured with the specified parameters.
-

Novita AI​

-

This component generates text using Novita AI's language models.

-

For more information, see Novita AI documentation.

-

Parameters​

-

Inputs​

-
NameTypeDescription
api_keySecretStringYour Novita AI API Key.
modelStringThe id of the Novita AI model to use.
max_tokensIntegerThe maximum number of tokens to generate. Set to 0 for unlimited tokens.
temperatureFloatControls randomness in the output. Range: [0.0, 1.0]. Default: 0.7.
top_pFloatControls the nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.
frequency_penaltyFloatControls the frequency penalty. Range: [0.0, 2.0]. Default: 0.0.
presence_penaltyFloatControls the presence penalty. Range: [0.0, 2.0]. Default: 0.0.

Hi, how can I help you?

+

Outputs​

+
NameTypeDescription
modelLanguageModelAn instance of ChatVertexAI configured with the specified parameters.

Hi, how can I help you?

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