From 5d87137fbb6898de76d5c8df8ec5ffb5bcb2f3c2 Mon Sep 17 00:00:00 2001 From: "github-merge-queue[bot]" Date: Fri, 9 May 2025 21:58:35 +0000 Subject: [PATCH] deploy: 06a74bdffd13940ec4490d7840213c2e8f57e227 --- 404.html | 2 +- agents-overview.html | 2 +- agents-tool-calling-agent-component.html | 2 +- api-reference-api-examples.html | 2 +- api.html | 2 +- api/add-user.html | 2 +- api/auto-login.html | 2 +- api/build-flow.html | 2 +- api/build-public-tmp.html | 2 +- api/build-vertex-stream.html | 2 +- api/build-vertex.html | 2 +- api/cancel-build.html | 2 +- api/check-if-store-has-api-key.html | 2 +- api/check-if-store-is-enabled.html | 2 +- api/create-api-key-route.html | 2 +- api/create-flow.html | 2 +- api/create-flows.html | 2 +- api/create-folder-redirect.html | 2 +- api/create-project.html | 2 +- api/create-upload-file.html | 2 +- api/create-variable.html | 2 +- api/custom-component-update.html | 2 +- api/custom-component.html | 2 +- api/delete-all-files-1.html | 2 +- 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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. Defaults to ",(0,d.jsx)(t.code,{children:"0.7"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Max Tokens"}),(0,d.jsx)(t.td,{children:"Max Tokens"}),(0,d.jsxs)(t.td,{children:["Specifies the maximum number of tokens to generate. Defaults to ",(0,d.jsx)(t.code,{children:"1000"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Input Value"}),(0,d.jsx)(t.td,{children:"Input Value"}),(0,d.jsx)(t.td,{children:"Specifies the input text for text generation."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Stream"}),(0,d.jsx)(t.td,{children:"Stream"}),(0,d.jsxs)(t.td,{children:["Specifies whether to stream the response from the model. Defaults to ",(0,d.jsx)(t.code,{children:"False"}),"."]})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-3",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 AzureOpenAI configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"cohere",children:"Cohere"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using Cohere's language models."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://cohere.ai/",children:"Cohere documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-4",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:"Cohere API Key"}),(0,d.jsx)(t.td,{children:"Cohere API Key"}),(0,d.jsx)(t.td,{children:"Your Cohere API key."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Max Tokens"}),(0,d.jsx)(t.td,{children:"Max Tokens"}),(0,d.jsxs)(t.td,{children:["Specifies the maximum number of tokens to generate. Defaults to ",(0,d.jsx)(t.code,{children:"256"}),"."]})]}),(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. Defaults to ",(0,d.jsx)(t.code,{children:"0.75"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"Input Value"}),(0,d.jsx)(t.td,{children:"Input Value"}),(0,d.jsx)(t.td,{children:"Specifies the input text for text generation."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-4",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 the Cohere model configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"deepseek",children:"DeepSeek"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using DeepSeek's language models."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://api-docs.deepseek.com/",children:"DeepSeek documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-5",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:["Maximum number of tokens to generate. 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Use the same seed integer for more reproducible results, and use a different seed number for more random results."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-5",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 ChatOpenAI configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"google-generative-ai",children:"Google Generative AI"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using Google's Generative AI models."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://cloud.google.com/vertex-ai/docs/",children:"Google Generative AI 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interfaces."]}),"\n",(0,d.jsxs)(t.li,{children:["In the ",(0,d.jsx)(t.strong,{children:"Prompt"})," component, enter:"]}),"\n"]}),"\n",(0,d.jsx)(a.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"You are a helpful assistant who supports their claims with sources.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,d.jsxs)(t.ol,{start:"5",children:["\n",(0,d.jsxs)(t.li,{children:["Click ",(0,d.jsx)(t.strong,{children:"Playground"})," and ask your Groq LLM a question.\nThe responses include a list of sources."]}),"\n"]}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://groq.com/",children:"Groq 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Default: ",(0,d.jsx)(t.code,{children:"https://api.groq.com"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"max_tokens"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsx)(t.td,{children:"The maximum number of tokens to generate."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"temperature"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Controls randomness in the output. Range: ",(0,d.jsx)(t.code,{children:"[0.0, 1.0]"}),". Default: ",(0,d.jsx)(t.code,{children:"0.1"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"n"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsx)(t.td,{children:"Number of chat completions to generate for each prompt."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"model_name"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"The name of the Groq model to use. Options are dynamically fetched from the Groq API."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"tool_mode_enabled"}),(0,d.jsx)(t.td,{children:"Bool"}),(0,d.jsx)(t.td,{children:"If enabled, the component only displays models that work with tools."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-7",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 ChatGroq configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"hugging-face-api",children:"Hugging Face API"}),"\n",(0,d.jsxs)(t.p,{children:["This component sends requests to the Hugging Face API to generate text using the model specified in the ",(0,d.jsx)(t.strong,{children:"Model ID"})," field."]}),"\n",(0,d.jsxs)(t.p,{children:["The Hugging Face API is a hosted inference API for models hosted on Hugging Face, and requires a ",(0,d.jsx)(t.a,{href:"https://huggingface.co/docs/hub/security-tokens",children:"Hugging Face API token"})," to authenticate."]}),"\n",(0,d.jsxs)(t.p,{children:["In this example based on the ",(0,d.jsx)(t.a,{href:"/starter-projects-basic-prompting",children:"Basic prompting flow"}),", the ",(0,d.jsx)(t.strong,{children:"Hugging Face API"})," model component replaces the ",(0,d.jsx)(t.strong,{children:"Open AI"})," model. By selecting different hosted models, you can see how different models return different results."]}),"\n",(0,d.jsxs)(t.ol,{children:["\n",(0,d.jsxs)(t.li,{children:["\n",(0,d.jsxs)(t.p,{children:["Create a ",(0,d.jsx)(t.a,{href:"/starter-projects-basic-prompting",children:"Basic prompting flow"}),"."]}),"\n"]}),"\n",(0,d.jsxs)(t.li,{children:["\n",(0,d.jsxs)(t.p,{children:["Replace the ",(0,d.jsx)(t.strong,{children:"OpenAI"})," model component with a ",(0,d.jsx)(t.strong,{children:"Hugging Face API"})," model component."]}),"\n"]}),"\n",(0,d.jsxs)(t.li,{children:["\n",(0,d.jsxs)(t.p,{children:["In the ",(0,d.jsx)(t.strong,{children:"Hugging Face API"})," component, add your Hugging Face API token to the ",(0,d.jsx)(t.strong,{children:"API Token"})," field."]}),"\n"]}),"\n",(0,d.jsxs)(t.li,{children:["\n",(0,d.jsxs)(t.p,{children:["Open the ",(0,d.jsx)(t.strong,{children:"Playground"})," and ask a question to the model, and see how it responds."]}),"\n"]}),"\n",(0,d.jsxs)(t.li,{children:["\n",(0,d.jsx)(t.p,{children:"Try different models, and see how they perform differently."}),"\n"]}),"\n"]}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://huggingface.co/",children:"Hugging Face documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-8",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:"model_id"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:'The model ID from Hugging Face Hub. For example, "gpt2", "facebook/bart-large".'})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"huggingfacehub_api_token"}),(0,d.jsx)(t.td,{children:"SecretString"}),(0,d.jsx)(t.td,{children:"Your Hugging Face API token for authentication."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"temperature"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsx)(t.td,{children:"Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.7."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"max_new_tokens"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsx)(t.td,{children:"Maximum number of tokens to generate. Default: 512."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"top_p"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsx)(t.td,{children:"Nucleus sampling parameter. Range: [0.0, 1.0]. Default: 0.95."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"top_k"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsx)(t.td,{children:"Top-k sampling parameter. Default: 50."})]}),(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 to pass to the model."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-8",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 HuggingFaceHub configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"ibm-watsonxai",children:"IBM watsonx.ai"}),"\n",(0,d.jsxs)(t.p,{children:["This component generates text using ",(0,d.jsx)(t.a,{href:"https://www.ibm.com/watsonx",children:"IBM watsonx.ai"})," foundation models."]}),"\n",(0,d.jsxs)(t.p,{children:["To use ",(0,d.jsx)(t.strong,{children:"IBM watsonx.ai"})," model components, replace a model component with the IBM watsonx.ai component in a flow."]}),"\n",(0,d.jsx)(t.p,{children:"An example flow looks like the following:"}),"\n",(0,d.jsx)(t.p,{children:(0,d.jsx)(t.img,{alt:"IBM watsonx model component in a basic prompting flow",src:n(68799).A+"",width:"2364",height:"1562"})}),"\n",(0,d.jsxs)(t.p,{children:["The values for ",(0,d.jsx)(t.strong,{children:"API endpoint"}),", ",(0,d.jsx)(t.strong,{children:"Project ID"}),", ",(0,d.jsx)(t.strong,{children:"API key"}),", and ",(0,d.jsx)(t.strong,{children:"Model Name"})," are found in your IBM watsonx.ai deployment.\nFor more information, see the ",(0,d.jsx)(t.a,{href:"https://python.langchain.com/docs/integrations/chat/ibm_watsonx/",children:"Langchain documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-9",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:"url"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"The base URL of the watsonx API."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"project_id"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"Your watsonx Project ID."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"api_key"}),(0,d.jsx)(t.td,{children:"SecretString"}),(0,d.jsx)(t.td,{children:"Your IBM watsonx API Key."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"model_name"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"The name of the watsonx model to use. 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Range: Default: ",(0,d.jsx)(t.code,{children:"0.9"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"frequency_penalty"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Controls frequency penalty. A positive value decreases the probability of repeating tokens, and a negative value increases the probability. Range: Default: ",(0,d.jsx)(t.code,{children:"0.5"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"presence_penalty"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Controls presence penalty. A positive value increases the likelihood of new topics being introduced. Default: ",(0,d.jsx)(t.code,{children:"0.3"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"seed"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsxs)(t.td,{children:["A random seed for the model. Default: ",(0,d.jsx)(t.code,{children:"8"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"logprobs"}),(0,d.jsx)(t.td,{children:"Boolean"}),(0,d.jsxs)(t.td,{children:["Whether to return log probabilities of output tokens or not. Default: ",(0,d.jsx)(t.code,{children:"True"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"top_logprobs"}),(0,d.jsx)(t.td,{children:"Integer"}),(0,d.jsxs)(t.td,{children:["The number of most likely tokens to return at each position. Default: ",(0,d.jsx)(t.code,{children:"3"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"logit_bias"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"A JSON string of token IDs to bias or suppress."})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-9",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.jsxs)(t.td,{children:["An instance of ",(0,d.jsx)(t.a,{href:"https://python.langchain.com/docs/integrations/chat/ibm_watsonx/",children:"ChatWatsonx"})," configured with the specified parameters."]})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"language-model",children:"Language model"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using either OpenAI or Anthropic language models."}),"\n",(0,d.jsx)(t.p,{children:"Use this component as a drop-in replacement for LLM models to switch between different model providers and models."}),"\n",(0,d.jsx)(t.p,{children:"Instead of swapping out model components when you want to try a different provider, like switching between OpenAI and Anthropic components, change the provider dropdown in this single component. This makes it easier to experiment with and compare different models while keeping the rest of your flow intact."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see the ",(0,d.jsx)(t.a,{href:"https://platform.openai.com/docs",children:"OpenAI documentation"})," and ",(0,d.jsx)(t.a,{href:"https://docs.anthropic.com/",children:"Anthropic documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-10",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:"provider"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:'The model provider to use. Options: "OpenAI", "Anthropic". Default: "OpenAI".'})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"model_name"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"The name of the model to use. Options depend on the selected provider."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"api_key"}),(0,d.jsx)(t.td,{children:"SecretString"}),(0,d.jsx)(t.td,{children:"The API Key for authentication with the selected provider."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"input_value"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"The input text to send to the model."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"system_message"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsx)(t.td,{children:"A system message that helps set the behavior of the assistant (advanced)."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"stream"}),(0,d.jsx)(t.td,{children:"Boolean"}),(0,d.jsxs)(t.td,{children:["Whether to stream the response. Default: ",(0,d.jsx)(t.code,{children:"False"})," (advanced)."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"temperature"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Controls randomness in responses. Range: ",(0,d.jsx)(t.code,{children:"[0.0, 1.0]"}),". Default: ",(0,d.jsx)(t.code,{children:"0.1"})," (advanced)."]})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-10",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 ChatOpenAI or ChatAnthropic configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"lmstudio",children:"LMStudio"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using LM Studio's local language models."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see ",(0,d.jsx)(t.a,{href:"https://lmstudio.ai/",children:"LM Studio documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-11",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:"base_url"}),(0,d.jsx)(t.td,{children:"String"}),(0,d.jsxs)(t.td,{children:["The URL where LM Studio is running. Default: ",(0,d.jsx)(t.code,{children:'"http://localhost:1234"'}),"."]})]}),(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:["Maximum number of tokens to generate in the response. Default: ",(0,d.jsx)(t.code,{children:"512"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"temperature"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Controls randomness in the output. Range: ",(0,d.jsx)(t.code,{children:"[0.0, 2.0]"}),". Default: ",(0,d.jsx)(t.code,{children:"0.7"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"top_p"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Controls diversity via nucleus sampling. Range: ",(0,d.jsx)(t.code,{children:"[0.0, 1.0]"}),". Default: ",(0,d.jsx)(t.code,{children:"1.0"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"stop"}),(0,d.jsx)(t.td,{children:"List[String]"}),(0,d.jsx)(t.td,{children:"List of strings that will stop generation when encountered (advanced)."})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"stream"}),(0,d.jsx)(t.td,{children:"Boolean"}),(0,d.jsxs)(t.td,{children:["Whether to stream the response. Default: ",(0,d.jsx)(t.code,{children:"False"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"presence_penalty"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Penalizes repeated tokens. Range: ",(0,d.jsx)(t.code,{children:"[-2.0, 2.0]"}),". Default: ",(0,d.jsx)(t.code,{children:"0.0"}),"."]})]}),(0,d.jsxs)(t.tr,{children:[(0,d.jsx)(t.td,{children:"frequency_penalty"}),(0,d.jsx)(t.td,{children:"Float"}),(0,d.jsxs)(t.td,{children:["Penalizes frequent tokens. Range: ",(0,d.jsx)(t.code,{children:"[-2.0, 2.0]"}),". Default: ",(0,d.jsx)(t.code,{children:"0.0"}),"."]})]})]})]}),"\n",(0,d.jsx)(t.h3,{id:"outputs-11",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 LMStudio configured with the specified parameters."})]})})]}),"\n",(0,d.jsx)(t.h2,{id:"maritalk",children:"Maritalk"}),"\n",(0,d.jsx)(t.p,{children:"This component generates text using Maritalk LLMs."}),"\n",(0,d.jsxs)(t.p,{children:["For more information, see ",(0,d.jsx)(t.a,{href:"https://www.maritalk.com/",children:"Maritalk documentation"}),"."]}),"\n",(0,d.jsx)(t.h3,{id:"inputs-12",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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Default: 50."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"model_kwargs"}),(0,r.jsx)(n.td,{children:"Dictionary"}),(0,r.jsx)(n.td,{children:"Additional keyword arguments to pass to the model."})]})]})]}),(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Outputs"})}),(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Name"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsx)(n.tbody,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"model"}),(0,r.jsx)(n.td,{children:"LanguageModel"}),(0,r.jsx)(n.td,{children:"An instance of HuggingFaceHub configured with the specified parameters."})]})})]})]}),"\n",(0,r.jsx)(n.h2,{id:"ibm-watsonxai",children:"IBM watsonx.ai"}),"\n",(0,r.jsxs)(n.p,{children:["This component generates text using ",(0,r.jsx)(n.a,{href:"https://www.ibm.com/watsonx",children:"IBM watsonx.ai"})," foundation models."]}),"\n",(0,r.jsxs)(n.p,{children:["To use ",(0,r.jsx)(n.strong,{children:"IBM watsonx.ai"})," model components, replace a model component with the IBM watsonx.ai component in a flow."]}),"\n",(0,r.jsx)(n.p,{children:"An example flow looks like the following:"}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.img,{alt:"IBM watsonx model component in a basic prompting flow",src:t(68799).A+"",width:"2364",height:"1562"})}),"\n",(0,r.jsxs)(n.p,{children:["The values for ",(0,r.jsx)(n.strong,{children:"API endpoint"}),", ",(0,r.jsx)(n.strong,{children:"Project ID"}),", ",(0,r.jsx)(n.strong,{children:"API key"}),", and ",(0,r.jsx)(n.strong,{children:"Model Name"})," are found in your IBM watsonx.ai deployment.\nFor more information, see the ",(0,r.jsx)(n.a,{href:"https://python.langchain.com/docs/integrations/chat/ibm_watsonx/",children:"Langchain documentation"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Inputs"})}),(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Name"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsxs)(n.tbody,{children:[(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"url"}),(0,r.jsx)(n.td,{children:"String"}),(0,r.jsx)(n.td,{children:"The base URL of the watsonx API."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"project_id"}),(0,r.jsx)(n.td,{children:"String"}),(0,r.jsx)(n.td,{children:"Your watsonx Project ID."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"api_key"}),(0,r.jsx)(n.td,{children:"SecretString"}),(0,r.jsx)(n.td,{children:"Your IBM watsonx API Key."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"model_name"}),(0,r.jsx)(n.td,{children:"String"}),(0,r.jsx)(n.td,{children:"The name of the watsonx model to use. 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This makes it easier to experiment with and compare different models while keeping the rest of your flow intact."}),"\n",(0,r.jsxs)(n.p,{children:["For more information, see the ",(0,r.jsx)(n.a,{href:"https://platform.openai.com/docs",children:"OpenAI documentation"})," and ",(0,r.jsx)(n.a,{href:"https://docs.anthropic.com/",children:"Anthropic documentation"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Inputs"})}),(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Name"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsxs)(n.tbody,{children:[(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"provider"}),(0,r.jsx)(n.td,{children:"String"}),(0,r.jsx)(n.td,{children:'The model provider to use. Options: "OpenAI", "Anthropic". 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Default: ",(0,r.jsx)(n.code,{children:"0.1"})," (advanced)."]})]})]})]}),(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Outputs"})}),(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Name"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsx)(n.tbody,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"model"}),(0,r.jsx)(n.td,{children:"LanguageModel"}),(0,r.jsx)(n.td,{children:"An instance of ChatOpenAI or ChatAnthropic configured with the specified parameters."})]})})]})]}),"\n",(0,r.jsx)(n.h2,{id:"lmstudio",children:"LMStudio"}),"\n",(0,r.jsx)(n.p,{children:"This component generates text using LM Studio's local language models."}),"\n",(0,r.jsxs)(n.p,{children:["For more information, see ",(0,r.jsx)(n.a,{href:"https://lmstudio.ai/",children:"LM Studio documentation"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Inputs"})}),(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Name"}),(0,r.jsx)(n.th,{children:"Type"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsxs)(n.tbody,{children:[(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"base_url"}),(0,r.jsx)(n.td,{children:"String"}),(0,r.jsxs)(n.td,{children:["The URL where LM Studio is running. 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If empty, the current session ID parameter is used."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"files"}),(0,o.jsx)(t.td,{children:"Files"}),(0,o.jsx)(t.td,{children:"The files to be sent with the message."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"background_color"}),(0,o.jsx)(t.td,{children:"Background Color"}),(0,o.jsx)(t.td,{children:"The background color of the icon."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"chat_icon"}),(0,o.jsx)(t.td,{children:"Icon"}),(0,o.jsx)(t.td,{children:"The icon of the message."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"text_color"}),(0,o.jsx)(t.td,{children:"Text Color"}),(0,o.jsx)(t.td,{children:"The text color of the name."})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display 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files",props:{style:{color:"#FFA657"}}},{content:"=",props:{style:{color:"#FF7B72"}}},{content:"self",props:{style:{color:"#79C0FF"}}},{content:".files,",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" properties",props:{style:{color:"#FFA657"}}},{content:"=",props:{style:{color:"#FF7B72"}}},{content:"{",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:' "background_color"',props:{style:{color:"#A5D6FF"}}},{content:": background_color,",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:' "text_color"',props:{style:{color:"#A5D6FF"}}},{content:": text_color,",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:' "icon"',props:{style:{color:"#A5D6FF"}}},{content:": icon,",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" },",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:")",props:{style:{color:"#C9D1D9"}}}]}],lang:"python"},annotations:[]}]}),"\n",(0,o.jsx)(t.h2,{id:"text-input",children:"Text Input"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"Text Input"})," component accepts a text string input and returns a ",(0,o.jsx)(t.code,{children:"Message"})," object containing only the input text."]}),"\n",(0,o.jsxs)(t.p,{children:["The output does not appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsx)(t.h3,{id:"inputs-1",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"input_value"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The text/content to be passed as output."})]})})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-1",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"text"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The resulting text message."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"chat-output",children:"Chat Output"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component creates a ",(0,o.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object that includes the input text, sender information, session ID, and styling properties."]}),"\n",(0,o.jsx)(t.p,{children:"The component accepts the following input types."}),"\n",(0,o.jsxs)(t.ul,{children:["\n",(0,o.jsx)(t.li,{children:(0,o.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})}),"\n",(0,o.jsx)(t.li,{children:(0,o.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})}),"\n",(0,o.jsx)(t.li,{children:(0,o.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})}),"\n"]}),"\n",(0,o.jsx)(t.h3,{id:"inputs-2",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"input_value"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The message to be passed as output."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"should_store_message"}),(0,o.jsx)(t.td,{children:"Store Messages"}),(0,o.jsx)(t.td,{children:"The flag to store the message in the history."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"sender"}),(0,o.jsx)(t.td,{children:"Sender Type"}),(0,o.jsx)(t.td,{children:"The type of sender."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"sender_name"}),(0,o.jsx)(t.td,{children:"Sender Name"}),(0,o.jsx)(t.td,{children:"The name of the sender."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"session_id"}),(0,o.jsx)(t.td,{children:"Session ID"}),(0,o.jsx)(t.td,{children:"The session ID of the chat. If empty, the current session ID parameter is used."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"data_template"}),(0,o.jsx)(t.td,{children:"Data Template"}),(0,o.jsx)(t.td,{children:"The template to convert Data to Text. If the option is left empty, it is dynamically set to the Data's text key."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"background_color"}),(0,o.jsx)(t.td,{children:"Background Color"}),(0,o.jsx)(t.td,{children:"The background color of the icon."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"chat_icon"}),(0,o.jsx)(t.td,{children:"Icon"}),(0,o.jsx)(t.td,{children:"The icon of the message."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"text_color"}),(0,o.jsx)(t.td,{children:"Text Color"}),(0,o.jsx)(t.td,{children:"The text color of the name."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"clean_data"}),(0,o.jsx)(t.td,{children:"Basic Clean Data"}),(0,o.jsxs)(t.td,{children:["When enabled, ",(0,o.jsx)(t.code,{children:"DataFrame"})," inputs are cleaned when converted to text. Cleaning removes empty rows, empty lines in cells, and multiple newlines."]})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-2",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"message"}),(0,o.jsx)(t.td,{children:"Message"}),(0,o.jsx)(t.td,{children:"The resulting chat message object with all specified properties."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"text-output",children:"Text Output"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"Text Output"})," takes a single input of text and returns a ",(0,o.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object containing that text."]}),"\n",(0,o.jsxs)(t.p,{children:["The output does not appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsx)(t.h3,{id:"inputs-3",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"input_value"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The text to be passed as output."})]})})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-3",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"text"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The resulting text message."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"chat-components-example-flow",children:"Chat components example flow"}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["To use the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," and ",(0,o.jsx)(t.strong,{children:"Chat Output"})," components in a flow, connect them to components that accept or send the ",(0,o.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," type."]}),"\n"]}),"\n",(0,o.jsxs)(t.p,{children:["For this example, connect a ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component to an ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component's ",(0,o.jsx)(t.strong,{children:"Input"})," port, and then connect the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component's ",(0,o.jsx)(t.strong,{children:"Message"})," port to the ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component."]}),"\n",(0,o.jsxs)(t.ol,{start:"2",children:["\n",(0,o.jsxs)(t.li,{children:["In the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component, in the ",(0,o.jsx)(t.strong,{children:"OpenAI API Key"})," field, add your ",(0,o.jsx)(t.strong,{children:"OpenAI API key"}),"."]}),"\n"]}),"\n",(0,o.jsx)(t.p,{children:"The flow looks like this:"}),"\n",(0,o.jsx)(t.p,{children:(0,o.jsx)(t.img,{alt:"Chat input and output components connected to an OpenAI model",src:n(6944).A+"",width:"4000",height:"2574"})}),"\n",(0,o.jsxs)(t.ol,{start:"3",children:["\n",(0,o.jsxs)(t.li,{children:["\n",(0,o.jsxs)(t.p,{children:["To send a message to your flow, open the ",(0,o.jsx)(t.strong,{children:"Playground"}),", and then enter a message.\nThe ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component responds.\nOptionally, in the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component, enter a ",(0,o.jsx)(t.strong,{children:"System Message"})," to control the model's response."]}),"\n"]}),"\n",(0,o.jsxs)(t.li,{children:["\n",(0,o.jsxs)(t.p,{children:["In the Langflow UI, click your flow name, and then click ",(0,o.jsx)(t.strong,{children:"Logs"}),".\nThe ",(0,o.jsx)(t.strong,{children:"Logs"})," pane opens.\nHere, you can inspect your component logs.\n",(0,o.jsx)(t.img,{alt:"Logs pane",src:n(77232).A+"",width:"3200",height:"1716"})]}),"\n"]}),"\n",(0,o.jsxs)(t.li,{children:["\n",(0,o.jsxs)(t.p,{children:["Your first message was sent by the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component to the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component.\nClick ",(0,o.jsx)(t.strong,{children:"Outputs"})," to view the sent message:"]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:' "messages": [',props:{}}]},{tokens:[{content:" {",props:{}}]},{tokens:[{content:' "message": "What\'s the recommended way to install Docker on Mac M1?",',props:{}}]},{tokens:[{content:' "sender": "User",',props:{}}]},{tokens:[{content:' "sender_name": "User",',props:{}}]},{tokens:[{content:' "session_id": "Session Apr 21, 17:37:04",',props:{}}]},{tokens:[{content:' "stream_url": null,',props:{}}]},{tokens:[{content:' "component_id": "ChatInput-4WKag",',props:{}}]},{tokens:[{content:' "files": [],',props:{}}]},{tokens:[{content:' "type": "text"',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:" ],",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.ol,{start:"6",children:["\n",(0,o.jsxs)(t.li,{children:["Your second message was sent by the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component to the ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component.\nThis is the raw text output of the model's response.\nThe ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component accepts this text as input and presents it as a formatted message.\nClick ",(0,o.jsx)(t.strong,{children:"Outputs"})," to view the sent message:"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:' "outputs":',props:{}}]},{tokens:[{content:' "text_output":',props:{}}]},{tokens:[{content:' "message": "To install Docker on a Mac with an M1 chip, you should use Docker Desktop for Mac, which is optimized for Apple Silicon. Here\u2019s a step-by-step guide to installing Docker on your M1 Mac:\\n\\n1.',props:{}}]},{tokens:[{content:" ...",props:{}}]},{tokens:[{content:' "type": "text"',props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(t.admonition,{type:"tip",children:(0,o.jsxs)(t.p,{children:["Optionally, to view the outputs of each component in the flow, click ",(0,o.jsx)(i.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]})}),"\n",(0,o.jsx)(t.h3,{id:"send-chat-messages-with-the-api",children:"Send chat messages with the API"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component is often the entry point for passing messages to the Langflow API.\nTo send the same example messages programmatically to your Langflow server, do the following:"]}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["To get your Langflow endpoint, click ",(0,o.jsx)(t.strong,{children:"Publish"}),", and then click ",(0,o.jsx)(t.strong,{children:"API access"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["Copy the command from the ",(0,o.jsx)(t.strong,{children:"cURL"})," tab, and then paste it in your terminal.\nIt looks similar to this:"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl --request POST \\",props:{}}]},{tokens:[{content:" --url 'http://127.0.0.1:7860/api/v1/run/51eed711-4530-4fdc-9bce-5db4351cc73a?stream=false' \\",props:{}}]},{tokens:[{content:" --header 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:" --data '{",props:{}}]},{tokens:[{content:' "input_value": "What\'s the recommended way to install Docker on Mac M1?",',props:{}}]},{tokens:[{content:' "output_type": "chat",',props:{}}]},{tokens:[{content:' "input_type": "chat"',props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.ol,{start:"3",children:["\n",(0,o.jsxs)(t.li,{children:["Modify ",(0,o.jsx)(t.code,{children:"input_value"})," so it contains the question, ",(0,o.jsx)(t.code,{children:"What's the recommended way to install Docker on Mac M1?"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(t.p,{children:["Note the ",(0,o.jsx)(t.code,{children:"output_type"})," and ",(0,o.jsx)(t.code,{children:"input_type"})," parameters that are passed with the message. The ",(0,o.jsx)(t.code,{children:"chat"})," type provides additional configuration options, and the messages appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),". The ",(0,o.jsx)(t.code,{children:"text"})," type returns only text strings, and does not appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsxs)(t.ol,{start:"4",children:["\n",(0,o.jsxs)(t.li,{children:["Add a custom ",(0,o.jsx)(t.code,{children:"session_id"})," to the message's ",(0,o.jsx)(t.code,{children:"data"})," object."]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl --request POST \\",props:{}}]},{tokens:[{content:" --url 'http://127.0.0.1:7860/api/v1/run/51eed711-4530-4fdc-9bce-5db4351cc73a?stream=false' \\",props:{}}]},{tokens:[{content:" --header 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:" --data '{",props:{}}]},{tokens:[{content:' "input_value": "Whats the recommended way to install Docker on Mac M1",',props:{}}]},{tokens:[{content:' "session_id": "docker-question-on-m1",',props:{}}]},{tokens:[{content:' "output_type": "chat",',props:{}}]},{tokens:[{content:' "input_type": "chat"',props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.p,{children:["The custom ",(0,o.jsx)(t.code,{children:"session_id"})," value starts a new chat session between your client and the Langflow server, and can be useful in keeping conversations and AI context separate."]}),"\n",(0,o.jsxs)(t.ol,{start:"5",children:["\n",(0,o.jsx)(t.li,{children:"Send the POST request.\nYour request is answered."}),"\n",(0,o.jsxs)(t.li,{children:["Navigate to the ",(0,o.jsx)(t.strong,{children:"Playground"}),".\nA new chat session called ",(0,o.jsx)(t.code,{children:"docker-question-on-m1"})," has appeared, using your unique ",(0,o.jsx)(t.code,{children:"session_id"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["To modify additional parameters with ",(0,o.jsx)(t.strong,{children:"Tweaks"})," for your ",(0,o.jsx)(t.strong,{children:"Chat Input"})," and ",(0,o.jsx)(t.strong,{children:"Chat Output"})," components, click ",(0,o.jsx)(t.strong,{children:"Publish"}),", and then click ",(0,o.jsx)(t.strong,{children:"API access"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["Click ",(0,o.jsx)(t.strong,{children:"Tweaks"})," to modify parameters in the component's ",(0,o.jsx)(t.code,{children:"data"})," object.\nFor example, disabling storing messages from the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component adds a ",(0,o.jsx)(t.strong,{children:"Tweak"})," to your command:"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl --request POST \\",props:{}}]},{tokens:[{content:" --url 'http://127.0.0.1:7860/api/v1/run/51eed711-4530-4fdc-9bce-5db4351cc73a?stream=false' \\",props:{}}]},{tokens:[{content:" --header 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:" --data '{",props:{}}]},{tokens:[{content:' "input_value": "Text to input to the flow",',props:{}}]},{tokens:[{content:' "output_type": "chat",',props:{}}]},{tokens:[{content:' "input_type": "chat",',props:{}}]},{tokens:[{content:' "tweaks": {',props:{}}]},{tokens:[{content:' "ChatInput-4WKag": {',props:{}}]},{tokens:[{content:' "should_store_message": false',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.p,{children:["To confirm your command is using the tweak, navigate to the ",(0,o.jsx)(t.strong,{children:"Logs"})," pane and view the request from the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component.\nThe value for ",(0,o.jsx)(t.code,{children:"should_store_message"})," is ",(0,o.jsx)(t.code,{children:"false"}),"."]})]})}function j(e={}){const{wrapper:t}={...(0,r.R)(),...e.components};return t?(0,o.jsx)(t,{...e,children:(0,o.jsx)(u,{...e})}):u(e)}function g(e,t){throw new Error("Expected "+(t?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}},77232:(e,t,n)=>{n.d(t,{A:()=>s});const s=n.p+"assets/images/logs-6ae22cc6a87b128cbc0c7f4559b47f10.png"},84443:(e,t,n)=>{n.d(t,{A:()=>r});n(96540);var s=n(64058),o=n(74848);function r(e){let{name:t,...n}=e;const r=s[t];return r?(0,o.jsx)(r,{...n}):null}}}]); 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If empty, the current session ID parameter is used."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"data_template"}),(0,o.jsx)(t.td,{children:"Data Template"}),(0,o.jsx)(t.td,{children:"The template to convert Data to Text. If the option is left empty, it is dynamically set to the Data's text key."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"background_color"}),(0,o.jsx)(t.td,{children:"Background Color"}),(0,o.jsx)(t.td,{children:"The background color of the icon."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"chat_icon"}),(0,o.jsx)(t.td,{children:"Icon"}),(0,o.jsx)(t.td,{children:"The icon of the message."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"text_color"}),(0,o.jsx)(t.td,{children:"Text Color"}),(0,o.jsx)(t.td,{children:"The text color of the name."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"clean_data"}),(0,o.jsx)(t.td,{children:"Basic Clean Data"}),(0,o.jsxs)(t.td,{children:["When enabled, ",(0,o.jsx)(t.code,{children:"DataFrame"})," inputs are cleaned when converted to text. Cleaning removes empty rows, empty lines in cells, and multiple newlines."]})]})]})]}),(0,o.jsx)(t.p,{children:(0,o.jsx)(t.strong,{children:"Outputs"})}),(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"message"}),(0,o.jsx)(t.td,{children:"Message"}),(0,o.jsx)(t.td,{children:"The resulting chat message object with all specified properties."})]})})]})]}),"\n",(0,o.jsx)(t.h2,{id:"text-output",children:"Text Output"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"Text Output"})," takes a single input of text and returns a ",(0,o.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object containing that text."]}),"\n",(0,o.jsxs)(t.p,{children:["The output does not appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Parameters"}),(0,o.jsx)(t.p,{children:(0,o.jsx)(t.strong,{children:"Inputs"})}),(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"input_value"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The text to be passed as output."})]})})]}),(0,o.jsx)(t.p,{children:(0,o.jsx)(t.strong,{children:"Outputs"})}),(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"text"}),(0,o.jsx)(t.td,{children:"Text"}),(0,o.jsx)(t.td,{children:"The resulting text message."})]})})]})]}),"\n",(0,o.jsx)(t.h2,{id:"chat-components-example-flow",children:"Chat components example flow"}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["To use the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," and ",(0,o.jsx)(t.strong,{children:"Chat Output"})," components in a flow, connect them to components that accept or send the ",(0,o.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," type."]}),"\n"]}),"\n",(0,o.jsxs)(t.p,{children:["For this example, connect a ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component to an ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component's ",(0,o.jsx)(t.strong,{children:"Input"})," port, and then connect the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component's ",(0,o.jsx)(t.strong,{children:"Message"})," port to the ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component."]}),"\n",(0,o.jsxs)(t.ol,{start:"2",children:["\n",(0,o.jsxs)(t.li,{children:["In the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component, in the ",(0,o.jsx)(t.strong,{children:"OpenAI API Key"})," field, add your ",(0,o.jsx)(t.strong,{children:"OpenAI API key"}),"."]}),"\n"]}),"\n",(0,o.jsx)(t.p,{children:"The flow looks like this:"}),"\n",(0,o.jsx)(t.p,{children:(0,o.jsx)(t.img,{alt:"Chat input and output components connected to an OpenAI model",src:n(6944).A+"",width:"4000",height:"2574"})}),"\n",(0,o.jsxs)(t.ol,{start:"3",children:["\n",(0,o.jsxs)(t.li,{children:["\n",(0,o.jsxs)(t.p,{children:["To send a message to your flow, open the ",(0,o.jsx)(t.strong,{children:"Playground"}),", and then enter a message.\nThe ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component responds.\nOptionally, in the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component, enter a ",(0,o.jsx)(t.strong,{children:"System Message"})," to control the model's response."]}),"\n"]}),"\n",(0,o.jsxs)(t.li,{children:["\n",(0,o.jsxs)(t.p,{children:["In the Langflow UI, click your flow name, and then click ",(0,o.jsx)(t.strong,{children:"Logs"}),".\nThe ",(0,o.jsx)(t.strong,{children:"Logs"})," pane opens.\nHere, you can inspect your component logs.\n",(0,o.jsx)(t.img,{alt:"Logs pane",src:n(77232).A+"",width:"3200",height:"1716"})]}),"\n"]}),"\n",(0,o.jsxs)(t.li,{children:["\n",(0,o.jsxs)(t.p,{children:["Your first message was sent by the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component to the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component.\nClick ",(0,o.jsx)(t.strong,{children:"Outputs"})," to view the sent message:"]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:' "messages": [',props:{}}]},{tokens:[{content:" {",props:{}}]},{tokens:[{content:' "message": "What\'s the recommended way to install Docker on Mac M1?",',props:{}}]},{tokens:[{content:' "sender": "User",',props:{}}]},{tokens:[{content:' "sender_name": "User",',props:{}}]},{tokens:[{content:' "session_id": "Session Apr 21, 17:37:04",',props:{}}]},{tokens:[{content:' "stream_url": null,',props:{}}]},{tokens:[{content:' "component_id": "ChatInput-4WKag",',props:{}}]},{tokens:[{content:' "files": [],',props:{}}]},{tokens:[{content:' "type": "text"',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:" ],",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.ol,{start:"6",children:["\n",(0,o.jsxs)(t.li,{children:["Your second message was sent by the ",(0,o.jsx)(t.strong,{children:"OpenAI"})," model component to the ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component.\nThis is the raw text output of the model's response.\nThe ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component accepts this text as input and presents it as a formatted message.\nClick ",(0,o.jsx)(t.strong,{children:"Outputs"})," to view the sent message:"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:' "outputs":',props:{}}]},{tokens:[{content:' "text_output":',props:{}}]},{tokens:[{content:' "message": "To install Docker on a Mac with an M1 chip, you should use Docker Desktop for Mac, which is optimized for Apple Silicon. Here\'s a step-by-step guide to installing Docker on your M1 Mac:\\n\\n1.',props:{}}]},{tokens:[{content:" ...",props:{}}]},{tokens:[{content:' "type": "text"',props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(t.admonition,{type:"tip",children:(0,o.jsxs)(t.p,{children:["Optionally, to view the outputs of each component in the flow, click ",(0,o.jsx)(d.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]})}),"\n",(0,o.jsx)(t.h3,{id:"send-chat-messages-with-the-api",children:"Send chat messages with the API"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component is often the entry point for passing messages to the Langflow API.\nTo send the same example messages programmatically to your Langflow server, do the following:"]}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["To get your Langflow endpoint, click ",(0,o.jsx)(t.strong,{children:"Publish"}),", and then click ",(0,o.jsx)(t.strong,{children:"API access"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["Copy the command from the ",(0,o.jsx)(t.strong,{children:"cURL"})," tab, and then paste it in your terminal.\nIt looks similar to this:"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl --request POST \\",props:{}}]},{tokens:[{content:" --url 'http://127.0.0.1:7860/api/v1/run/51eed711-4530-4fdc-9bce-5db4351cc73a?stream=false' \\",props:{}}]},{tokens:[{content:" --header 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:" --data '{",props:{}}]},{tokens:[{content:' "input_value": "What\'s the recommended way to install Docker on Mac M1?",',props:{}}]},{tokens:[{content:' "output_type": "chat",',props:{}}]},{tokens:[{content:' "input_type": "chat"',props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.ol,{start:"3",children:["\n",(0,o.jsxs)(t.li,{children:["Modify ",(0,o.jsx)(t.code,{children:"input_value"})," so it contains the question, ",(0,o.jsx)(t.code,{children:"What's the recommended way to install Docker on Mac M1?"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(t.p,{children:["Note the ",(0,o.jsx)(t.code,{children:"output_type"})," and ",(0,o.jsx)(t.code,{children:"input_type"})," parameters that are passed with the message. The ",(0,o.jsx)(t.code,{children:"chat"})," type provides additional configuration options, and the messages appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),". The ",(0,o.jsx)(t.code,{children:"text"})," type returns only text strings, and does not appear in the ",(0,o.jsx)(t.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsxs)(t.ol,{start:"4",children:["\n",(0,o.jsxs)(t.li,{children:["Add a custom ",(0,o.jsx)(t.code,{children:"session_id"})," to the message's ",(0,o.jsx)(t.code,{children:"data"})," object."]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl --request POST \\",props:{}}]},{tokens:[{content:" --url 'http://127.0.0.1:7860/api/v1/run/51eed711-4530-4fdc-9bce-5db4351cc73a?stream=false' \\",props:{}}]},{tokens:[{content:" --header 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:" --data '{",props:{}}]},{tokens:[{content:' "input_value": "Whats the recommended way to install Docker on Mac M1",',props:{}}]},{tokens:[{content:' "session_id": "docker-question-on-m1",',props:{}}]},{tokens:[{content:' "output_type": "chat",',props:{}}]},{tokens:[{content:' "input_type": "chat"',props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.p,{children:["The custom ",(0,o.jsx)(t.code,{children:"session_id"})," value starts a new chat session between your client and the Langflow server, and can be useful in keeping conversations and AI context separate."]}),"\n",(0,o.jsxs)(t.ol,{start:"5",children:["\n",(0,o.jsx)(t.li,{children:"Send the POST request.\nYour request is answered."}),"\n",(0,o.jsxs)(t.li,{children:["Navigate to the ",(0,o.jsx)(t.strong,{children:"Playground"}),".\nA new chat session called ",(0,o.jsx)(t.code,{children:"docker-question-on-m1"})," has appeared, using your unique ",(0,o.jsx)(t.code,{children:"session_id"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["To modify additional parameters with ",(0,o.jsx)(t.strong,{children:"Tweaks"})," for your ",(0,o.jsx)(t.strong,{children:"Chat Input"})," and ",(0,o.jsx)(t.strong,{children:"Chat Output"})," components, click ",(0,o.jsx)(t.strong,{children:"Publish"}),", and then click ",(0,o.jsx)(t.strong,{children:"API access"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["Click ",(0,o.jsx)(t.strong,{children:"Tweaks"})," to modify parameters in the component's ",(0,o.jsx)(t.code,{children:"data"})," object.\nFor example, disabling storing messages from the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component adds a ",(0,o.jsx)(t.strong,{children:"Tweak"})," to your command:"]}),"\n"]}),"\n",(0,o.jsx)(a.Code,{codeConfig:p,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl --request POST \\",props:{}}]},{tokens:[{content:" --url 'http://127.0.0.1:7860/api/v1/run/51eed711-4530-4fdc-9bce-5db4351cc73a?stream=false' \\",props:{}}]},{tokens:[{content:" --header 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:" --data '{",props:{}}]},{tokens:[{content:' "input_value": "Text to input to the flow",',props:{}}]},{tokens:[{content:' "output_type": "chat",',props:{}}]},{tokens:[{content:' "input_type": "chat",',props:{}}]},{tokens:[{content:' "tweaks": {',props:{}}]},{tokens:[{content:' "ChatInput-4WKag": {',props:{}}]},{tokens:[{content:' "should_store_message": false',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.p,{children:["To confirm your command is using the tweak, navigate to the ",(0,o.jsx)(t.strong,{children:"Logs"})," pane and view the request from the ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component.\nThe value for ",(0,o.jsx)(t.code,{children:"should_store_message"})," is ",(0,o.jsx)(t.code,{children:"false"}),"."]})]})}function u(e={}){const{wrapper:t}={...(0,r.R)(),...e.components};return t?(0,o.jsx)(t,{...e,children:(0,o.jsx)(j,{...e})}):j(e)}function g(e,t){throw new Error("Expected "+(t?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}},77232:(e,t,n)=>{n.d(t,{A:()=>s});const s=n.p+"assets/images/logs-6ae22cc6a87b128cbc0c7f4559b47f10.png"},84443:(e,t,n)=>{n.d(t,{A:()=>r});n(96540);var s=n(64058),o=n(74848);function r(e){let{name:t,...n}=e;const r=s[t];return r?(0,o.jsx)(r,{...n}):null}}}]); 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}'}}),"\n",(0,o.jsx)(n.header,{children:(0,o.jsx)(n.h1,{id:"logic-components-in-langflow",children:"Logic components in Langflow"})}),"\n",(0,o.jsx)(n.p,{children:"Logic components provide functionalities for routing, conditional processing, and flow management."}),"\n",(0,o.jsx)(n.h2,{id:"use-a-logic-component-in-a-flow",children:"Use a logic component in a flow"}),"\n",(0,o.jsxs)(n.p,{children:['This flow creates a summarizing "for each" loop with the ',(0,o.jsx)(n.a,{href:"/components-logic#loop",children:"Loop"})," component."]}),"\n",(0,o.jsxs)(n.p,{children:["The component iterates over a list of ",(0,o.jsx)(n.a,{href:"/concepts-objects#data-object",children:"Data"})," objects until it's completed, and then the ",(0,o.jsx)(n.strong,{children:"Done"})," loop aggregates the results."]}),"\n",(0,o.jsxs)(n.p,{children:["The ",(0,o.jsx)(n.strong,{children:"File"})," component loads text files from your local machine, and then the ",(0,o.jsx)(n.strong,{children:"Parse Data"})," component parses them into a list of structured ",(0,o.jsx)(n.code,{children:"Data"})," objects.\nThe ",(0,o.jsx)(n.strong,{children:"Loop"})," component passes each ",(0,o.jsx)(n.code,{children:"Data"})," object to a ",(0,o.jsx)(n.strong,{children:"Prompt"})," to be summarized."]}),"\n",(0,o.jsxs)(n.p,{children:["When the ",(0,o.jsx)(n.strong,{children:"Loop"})," component runs out of ",(0,o.jsx)(n.code,{children:"Data"}),", the ",(0,o.jsx)(n.strong,{children:"Done"})," loop activates, which counts the number of pages and summarizes their tone with another ",(0,o.jsx)(n.strong,{children:"Prompt"}),".\nThis is represented in Langflow by connecting the Parse Data component's ",(0,o.jsx)(n.strong,{children:"Data List"})," output to the Loop component's ",(0,o.jsx)(n.code,{children:"Data"})," loop input."]}),"\n",(0,o.jsx)(n.p,{children:(0,o.jsx)(n.img,{alt:"Sample Flow looping summarizer",src:t(19709).A+"",width:"2676",height:"1512"})}),"\n",(0,o.jsx)(n.p,{children:"The output is similar to this:"}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Document Summary",props:{}}]},{tokens:[{content:"Total Pages Processed",props:{}}]},{tokens:[{content:"Total Pages: 2",props:{}}]},{tokens:[{content:"Overall Tone of Document",props:{}}]},{tokens:[{content:"Tone: Informative and Instructional",props:{}}]},{tokens:[{content:"The documentation outlines microservices architecture patterns and best practices.",props:{}}]},{tokens:[{content:"It emphasizes service isolation and inter-service communication protocols.",props:{}}]},{tokens:[{content:"The use of asynchronous messaging patterns is recommended for system scalability.",props:{}}]},{tokens:[{content:"It includes code examples of REST and gRPC implementations to demonstrate integration approaches.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(n.h2,{id:"conditional-router-if-else-component",children:"Conditional router (If-Else component)"}),"\n",(0,o.jsxs)(n.p,{children:["This component routes messages by comparing two strings.\nIt evaluates a condition by comparing two text inputs using the specified operator and routes the message to ",(0,o.jsx)(n.code,{children:"true_result"})," or ",(0,o.jsx)(n.code,{children:"false_result"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["The operator looks for single strings based on your defined ",(0,o.jsx)(n.a,{href:"#operator-behavior",children:"operator behavior"}),", but it can also search for multiple words by regex matching."]}),"\n",(0,o.jsxs)(n.p,{children:["To use the ",(0,o.jsx)(n.strong,{children:"Conditional router"})," component to check incoming messages with regex matching, do the following:"]}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Connect the ",(0,o.jsx)(n.strong,{children:"If-Else"})," component's ",(0,o.jsx)(n.strong,{children:"Text Input"})," port to a ",(0,o.jsx)(n.strong,{children:"Chat Input"})," component."]}),"\n",(0,o.jsx)(n.li,{children:"In the If-Else component, enter the following values."}),"\n"]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["In the ",(0,o.jsx)(n.strong,{children:"Match Text"})," field, enter ",(0,o.jsx)(n.code,{children:".*(urgent|warning|caution).*"}),". The component looks for these values. The regex match is case sensitive, so to look for all permutations of ",(0,o.jsx)(n.code,{children:"warning"}),", enter ",(0,o.jsx)(n.code,{children:"warning|Warning|WARNING"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["In the ",(0,o.jsx)(n.strong,{children:"Operator"})," field, enter ",(0,o.jsx)(n.code,{children:"regex"}),". The component looks for the strings ",(0,o.jsx)(n.code,{children:"urgent"}),", ",(0,o.jsx)(n.code,{children:"warning"}),", and ",(0,o.jsx)(n.code,{children:"caution"}),". For more operators, see ",(0,o.jsx)(n.a,{href:"#operator-behavior",children:"Operator behavior"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["In the ",(0,o.jsx)(n.strong,{children:"Message"})," field, enter ",(0,o.jsx)(n.code,{children:"New Message Detected"}),". This field is optional. The message is sent to both the ",(0,o.jsx)(n.strong,{children:"True"})," and ",(0,o.jsx)(n.strong,{children:"False"})," ports.\nThe component is now set up to send a ",(0,o.jsx)(n.code,{children:"New Message Detected"})," message out of its ",(0,o.jsx)(n.strong,{children:"True"})," port if it matches any of the strings.\nIf no strings are detected, it sends a message out of the ",(0,o.jsx)(n.strong,{children:"False"})," port."]}),"\n"]}),"\n",(0,o.jsxs)(n.ol,{start:"3",children:["\n",(0,o.jsxs)(n.li,{children:["Create two identical flows to process the messages. Connect an ",(0,o.jsx)(n.strong,{children:"Open AI"})," component, a ",(0,o.jsx)(n.strong,{children:"Prompt"}),", and a ",(0,o.jsx)(n.strong,{children:"Chat Output"})," component together."]}),"\n",(0,o.jsxs)(n.li,{children:["Connect one chain to the ",(0,o.jsx)(n.strong,{children:"If-Else"})," component's ",(0,o.jsx)(n.strong,{children:"True"})," port, and one chain to the ",(0,o.jsx)(n.strong,{children:"False"})," port."]}),"\n"]}),"\n",(0,o.jsx)(n.p,{children:"The flow looks like this:"}),"\n",(0,o.jsx)(n.p,{children:(0,o.jsx)(n.img,{alt:"A conditional router connected to two OpenAI components",src:t(89329).A+"",width:"1888",height:"1754"})}),"\n",(0,o.jsxs)(n.ol,{start:"5",children:["\n",(0,o.jsxs)(n.li,{children:["Add your ",(0,o.jsx)(n.strong,{children:"OpenAI API key"})," to both ",(0,o.jsx)(n.strong,{children:"OpenAI"})," components."]}),"\n",(0,o.jsxs)(n.li,{children:["In both ",(0,o.jsx)(n.strong,{children:"Prompt"})," components, enter the behavior you want each route to take.\nWhen a match is found:"]}),"\n"]}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Send a message that a new message has been received and added to the Urgent queue.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(n.p,{children:"When a match is not found:"}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Send a message that a new message has been received and added to the backlog.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(n.ol,{start:"7",children:["\n",(0,o.jsxs)(n.li,{children:["Open the ",(0,o.jsx)(n.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsx)(n.li,{children:"Send the flow some messages. Your messages route differently based on the if-else component's evaluation."}),"\n"]}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"User",props:{}}]},{tokens:[{content:"A new user was created.",props:{}}]},{tokens:[{content:"",props:{}}]},{tokens:[{content:"AI",props:{}}]},{tokens:[{content:"A new message has been received and added to the backlog.",props:{}}]},{tokens:[{content:"",props:{}}]},{tokens:[{content:"User",props:{}}]},{tokens:[{content:"Sign-in warning: new user locked out.",props:{}}]},{tokens:[{content:"",props:{}}]},{tokens:[{content:"AI",props:{}}]},{tokens:[{content:"A new message has been received and added to the Urgent queue. Please review it at your earliest convenience.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Parameters"}),(0,o.jsx)(n.p,{children:(0,o.jsx)(n.strong,{children:"Inputs"})}),(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsxs)(n.tbody,{children:[(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"input_text"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:"The primary text input for the operation."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"match_text"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:"The text to compare against."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"operator"}),(0,o.jsx)(n.td,{children:"Dropdown"}),(0,o.jsx)(n.td,{children:"The operator used to compare texts. Options include equals, not equals, contains, starts with, ends with, and regex. The default is equals."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"case_sensitive"}),(0,o.jsx)(n.td,{children:"Boolean"}),(0,o.jsx)(n.td,{children:"When set to true, the comparison is case sensitive. This setting does not apply to regex comparison. The default is false."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"message"}),(0,o.jsx)(n.td,{children:"Message"}),(0,o.jsx)(n.td,{children:"The message to pass through either route."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"max_iterations"}),(0,o.jsx)(n.td,{children:"Integer"}),(0,o.jsx)(n.td,{children:"The maximum number of iterations allowed for the conditional router. The default is 10."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"default_route"}),(0,o.jsx)(n.td,{children:"Dropdown"}),(0,o.jsx)(n.td,{children:"The route to take when max iterations are reached. Options include true_result or false_result. The default is false_result."})]})]})]}),(0,o.jsx)(n.p,{children:(0,o.jsx)(n.strong,{children:"Outputs"})}),(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsxs)(n.tbody,{children:[(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"true_result"}),(0,o.jsx)(n.td,{children:"Message"}),(0,o.jsx)(n.td,{children:"The output produced when the condition is true."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"false_result"}),(0,o.jsx)(n.td,{children:"Message"}),(0,o.jsx)(n.td,{children:"The output produced when the condition is false."})]})]})]})]}),"\n",(0,o.jsx)(n.h3,{id:"operator-behavior",children:"Operator Behavior"}),"\n",(0,o.jsxs)(n.p,{children:["The ",(0,o.jsx)(n.strong,{children:"If-else"})," component includes a comparison operator to compare the values in ",(0,o.jsx)(n.code,{children:"input_text"})," and ",(0,o.jsx)(n.code,{children:"match_text"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["All options respect the ",(0,o.jsx)(n.code,{children:"case_sensitive"})," setting except ",(0,o.jsx)(n.strong,{children:"regex"}),"."]}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"equals"}),": Exact match comparison."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"not equals"}),": Inverse of exact match."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"contains"}),": Checks if match_text is found within input_text."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"starts with"}),": Checks if input_text begins with match_text."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"ends with"}),": Checks if input_text ends with match_text."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"regex"}),": Performs regular expression matching. It is always case sensitive and ignores the case_sensitive setting."]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"listen",children:"Listen"}),"\n",(0,o.jsx)(n.p,{children:"This component listens for a notification and retrieves its associated state."}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Parameters"}),(0,o.jsx)(n.p,{children:(0,o.jsx)(n.strong,{children:"Inputs"})}),(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsx)(n.tbody,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"name"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:"The name of the notification to listen for."})]})})]}),(0,o.jsx)(n.p,{children:(0,o.jsx)(n.strong,{children:"Outputs"})}),(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsx)(n.tbody,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"output"}),(0,o.jsx)(n.td,{children:"Data"}),(0,o.jsx)(n.td,{children:"The state associated with the notification."})]})})]})]}),"\n",(0,o.jsx)(n.h2,{id:"loop",children:"Loop"}),"\n",(0,o.jsxs)(n.p,{children:["This component iterates over a list of ",(0,o.jsx)(n.a,{href:"/concepts-objects#data-object",children:"Data"})," objects, outputting one item at a time and aggregating results from loop inputs."]}),"\n",(0,o.jsxs)(n.p,{children:["In this example, the ",(0,o.jsx)(n.strong,{children:"Loop"})," component iterates over a CSV file through the ",(0,o.jsx)(n.strong,{children:"Item"})," port until there are no rows left to process. Then, the ",(0,o.jsx)(n.strong,{children:"Loop"})," component performs the actions connected to the ",(0,o.jsx)(n.strong,{children:"Done"})," port, which in this case is loading the structured data into ",(0,o.jsx)(n.strong,{children:"Chroma DB"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["Think of it this way: the ",(0,o.jsx)(n.strong,{children:"Item"}),' port forms the "main" loop that repeats until a "complete" condition is reached.']}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["The ",(0,o.jsx)(n.strong,{children:"Loop"})," component accepts ",(0,o.jsx)(n.strong,{children:"Data"})," from the ",(0,o.jsx)(n.strong,{children:"Load CSV"})," component, and outputs the data from the ",(0,o.jsx)(n.strong,{children:"Item"})," port."]}),"\n",(0,o.jsxs)(n.li,{children:["Each CSV row is converted to a ",(0,o.jsx)(n.strong,{children:"Message"})," and processed into structured data with the ",(0,o.jsx)(n.strong,{children:"Structured Output"})," component.\nThe dotted line connected from the ",(0,o.jsx)(n.strong,{children:"Structured Output"})," component's ",(0,o.jsx)(n.strong,{children:"Looping"})," port tells you where the loop begins again."]}),"\n",(0,o.jsxs)(n.li,{children:["The ",(0,o.jsx)(n.strong,{children:"Loop"})," component repeatedly extracts rows by ",(0,o.jsx)(n.strong,{children:"Text Key"})," until there are no more rows to extract."]}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:["Once all items are processed, the action connected to the ",(0,o.jsx)(n.strong,{children:"Done"})," port is performed.\nIn this example, the data is loaded into ",(0,o.jsx)(n.strong,{children:"Chroma DB"}),"."]}),"\n",(0,o.jsx)(n.p,{children:(0,o.jsx)(n.img,{alt:"Loop CSV parser",src:t(91110).A+"",width:"3008",height:"3172"})}),"\n",(0,o.jsxs)(n.p,{children:["Follow along with this step-by-step video guide for creating this flow and adding agentic RAG: ",(0,o.jsx)(n.a,{href:"https://www.youtube.com/watch?v=9Wx7WODSKTo",children:"Mastering the Loop Component & Agentic 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unchanged."}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Parameters"}),(0,o.jsx)(n.p,{children:(0,o.jsx)(n.strong,{children:"Inputs"})}),(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Display Name"}),(0,o.jsx)(n.th,{children:"Info"})]})}),(0,o.jsxs)(n.tbody,{children:[(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"input_message"}),(0,o.jsx)(n.td,{children:"Input Message"}),(0,o.jsx)(n.td,{children:"The message to forward."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"ignored_message"}),(0,o.jsx)(n.td,{children:"Ignored Message"}),(0,o.jsx)(n.td,{children:"A second message that is ignored. 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The ",(0,o.jsx)(n.code,{children:"name"})," and ",(0,o.jsx)(n.code,{children:"description"})," metadata that the Agent uses to register the tool are created automatically."]}),"\n",(0,o.jsx)(n.p,{children:"When you select a flow, the component fetches the flow's graph structure and uses it to generate the inputs and outputs for the Run Flow component."}),"\n",(0,o.jsx)(n.p,{children:"To use the Run Flow component as a tool, do the following:"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Add the ",(0,o.jsx)(n.strong,{children:"Run Flow"})," component to the ",(0,o.jsx)(n.a,{href:"/starter-projects-simple-agent",children:"Simple Agent"})," flow."]}),"\n",(0,o.jsxs)(n.li,{children:["In the ",(0,o.jsx)(n.strong,{children:"Flow Name"})," menu, select the sub-flow you want to run.\nThe appearance of the ",(0,o.jsx)(n.strong,{children:"Run Flow"})," component changes to reflect the inputs and outputs of the selected flow."]}),"\n",(0,o.jsxs)(n.li,{children:["On the ",(0,o.jsx)(n.strong,{children:"Run Flow"})," component, enable ",(0,o.jsx)(n.strong,{children:"Tool Mode"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Connect the ",(0,o.jsx)(n.strong,{children:"Run Flow"})," component to the ",(0,o.jsx)(n.strong,{children:"Toolset"})," input of the Agent.\nYour flow should now look like this:\n",(0,o.jsx)(n.img,{alt:"Run Flow component",src:t(18111).A+"",width:"2036",height:"1582"})]}),"\n",(0,o.jsx)(n.li,{children:"Run the flow. 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It can process either a single Data object or a list of Data objects."]}),"\n",(0,o.jsx)(n.p,{children:"This component is particularly useful in workflows that require conditional routing of complex data structures, enabling dynamic decision-making based on data content."}),"\n",(0,o.jsx)(n.h4,{id:"inputs",children:"Inputs"}),"\n",(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsxs)(n.tbody,{children:[(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"data_input"}),(0,o.jsx)(n.td,{children:"Data"}),(0,o.jsx)(n.td,{children:"The Data object or list of Data objects to process. This input can handle both single items and lists."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"key_name"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:"The name of the key in the Data object to check."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"operator"}),(0,o.jsx)(n.td,{children:"Dropdown"}),(0,o.jsx)(n.td,{children:'The operator to apply. Options: "equals", "not equals", "contains", "starts with", "ends with", "boolean validator". Default: "equals".'})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"compare_value"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:'The value to compare against. Not shown/used when operator is "boolean validator".'})]})]})]}),"\n",(0,o.jsx)(n.h4,{id:"outputs",children:"Outputs"}),"\n",(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsxs)(n.tbody,{children:[(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"true_output"}),(0,o.jsx)(n.td,{children:"Data/List"}),(0,o.jsx)(n.td,{children:"Output when the condition is met."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"false_output"}),(0,o.jsx)(n.td,{children:"Data/List"}),(0,o.jsx)(n.td,{children:"Output when the condition is not met."})]})]})]}),"\n",(0,o.jsx)(n.h4,{id:"operator-behavior-1",children:"Operator behavior"}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"equals"}),": Exact match comparison between the key's value and compare_value."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"not equals"}),": Inverse of exact match."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"contains"}),": Checks if compare_value is found within the key's value."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"starts with"}),": Checks if the key's value begins with compare_value."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"ends with"}),": Checks if the key's value ends with compare_value."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"boolean validator"}),": Treats the key's value as a boolean. The following values are considered true:","\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["Boolean ",(0,o.jsx)(n.code,{children:"true"}),"."]}),"\n",(0,o.jsx)(n.li,{children:'Strings: "true", "1", "yes", "y", "on" (case-insensitive).'}),"\n",(0,o.jsxs)(n.li,{children:["Any other value is converted using Python's ",(0,o.jsx)(n.code,{children:"bool()"})," function."]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h4,{id:"list-processing",children:"List processing"}),"\n",(0,o.jsx)(n.p,{children:"The following actions occur when processing a list of Data objects:"}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsx)(n.li,{children:"Each object in the list is evaluated individually"}),"\n",(0,o.jsx)(n.li,{children:"Objects meeting the condition go to true_output"}),"\n",(0,o.jsx)(n.li,{children:"Objects not meeting the condition go to false_output"}),"\n",(0,o.jsx)(n.li,{children:"If all objects go to one output, the other output is empty"}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"deprecated-components",children:"Deprecated components"}),"\n",(0,o.jsx)(n.p,{children:"Deprecated components have been replaced by newer alternatives and should not be used in new projects."}),"\n",(0,o.jsx)(n.h3,{id:"flow-as-tool",children:"Flow as tool"}),"\n",(0,o.jsx)(n.admonition,{type:"important",children:(0,o.jsxs)(n.p,{children:["This component is deprecated as of Langflow version 1.1.2.\nInstead, use the ",(0,o.jsx)(n.a,{href:"/components-logic#run-flow",children:"Run flow component"})]})}),"\n",(0,o.jsx)(n.p,{children:"This component constructs a tool from a function that runs a loaded flow."}),"\n",(0,o.jsx)(n.h4,{id:"inputs-1",children:"Inputs"}),"\n",(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsxs)(n.tbody,{children:[(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"flow_name"}),(0,o.jsx)(n.td,{children:"Dropdown"}),(0,o.jsx)(n.td,{children:"The name of the flow to run."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"tool_name"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:"The name of the tool."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"tool_description"}),(0,o.jsx)(n.td,{children:"String"}),(0,o.jsx)(n.td,{children:"The description of the tool."})]}),(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"return_direct"}),(0,o.jsx)(n.td,{children:"Boolean"}),(0,o.jsx)(n.td,{children:"If true, returns the result directly from the tool."})]})]})]}),"\n",(0,o.jsx)(n.h4,{id:"outputs-1",children:"Outputs"}),"\n",(0,o.jsxs)(n.table,{children:[(0,o.jsx)(n.thead,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.th,{children:"Name"}),(0,o.jsx)(n.th,{children:"Type"}),(0,o.jsx)(n.th,{children:"Description"})]})}),(0,o.jsx)(n.tbody,{children:(0,o.jsxs)(n.tr,{children:[(0,o.jsx)(n.td,{children:"api_build_tool"}),(0,o.jsx)(n.td,{children:"Tool"}),(0,o.jsx)(n.td,{children:"The constructed tool from the flow."})]})})]}),"\n",(0,o.jsx)(n.h3,{id:"sub-flow",children:"Sub flow"}),"\n",(0,o.jsx)(n.admonition,{type:"important",children:(0,o.jsxs)(n.p,{children:["This component is deprecated as of Langflow version 1.1.2.\nInstead, use the ",(0,o.jsx)(n.a,{href:"/components-logic#run-flow",children:"Run flow component"})]})}),"\n",(0,o.jsxs)(n.p,{children:["This ",(0,o.jsx)(n.code,{children:"SubFlowComponent"})," generates a component from a flow with all of its inputs and outputs."]}),"\n",(0,o.jsx)(n.p,{children:"This component can integrate entire flows as components within a larger workflow. 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\ No newline at end of file diff --git a/assets/js/6aa941bb.ea2cd923.js b/assets/js/6aa941bb.ea2cd923.js deleted file mode 100644 index 3af633d09d..0000000000 --- a/assets/js/6aa941bb.ea2cd923.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunklangflow_docs=self.webpackChunklangflow_docs||[]).push([[3327],{18111:(e,t,n)=>{n.d(t,{A:()=>s});const s=n.p+"assets/images/component-run-flow-78e94e2ede1b4b853f0e4de6b9561f6f.png"},19054:(e,t,n)=>{n.r(t),n.d(t,{CH:()=>h,assets:()=>c,chCodeConfig:()=>a,contentTitle:()=>l,default:()=>j,frontMatter:()=>d,metadata:()=>s,toc:()=>p});const s=JSON.parse('{"id":"Components/components-logic","title":"Logic","description":"Logic components provide functionalities for routing, conditional processing, and flow management.","source":"@site/docs/Components/components-logic.md","sourceDirName":"Components","slug":"/components-logic","permalink":"/components-logic","draft":false,"unlisted":false,"tags":[],"version":"current","frontMatter":{"title":"Logic","slug":"/components-logic"},"sidebar":"docs","previous":{"title":"Loaders","permalink":"/components-loaders"},"next":{"title":"Memories","permalink":"/components-memories"}}');var o=n(74848),i=n(28453),r=n(24754);const d={title:"Logic",slug:"/components-logic"},l="Logic components in Langflow",c={},h={annotations:r.hk,Code:r.Cy},a={staticMediaQuery:"not screen, (max-width: 768px)",lineNumbers:!0,showCopyButton:!0,themeName:"github-dark"},p=[{value:"Use a logic component in a flow",id:"use-a-logic-component-in-a-flow",level:2},{value:"Conditional router (If-Else component)",id:"conditional-router-if-else-component",level:2},{value:"Inputs",id:"inputs",level:3},{value:"Outputs",id:"outputs",level:3},{value:"Operator Behavior",id:"operator-behavior",level:3},{value:"Listen",id:"listen",level:2},{value:"Inputs",id:"inputs-1",level:3},{value:"Outputs",id:"outputs-1",level:3},{value:"Loop",id:"loop",level:2},{value:"Inputs",id:"inputs-2",level:3},{value:"Outputs",id:"outputs-2",level:3},{value:"Notify",id:"notify",level:2},{value:"Inputs",id:"inputs-3",level:3},{value:"Outputs",id:"outputs-3",level:3},{value:"Pass message",id:"pass-message",level:2},{value:"Inputs",id:"inputs-4",level:3},{value:"Outputs",id:"outputs-4",level:3},{value:"Run flow",id:"run-flow",level:2},{value:"Inputs",id:"inputs-5",level:3},{value:"Outputs",id:"outputs-5",level:3},{value:"Legacy components",id:"legacy-components",level:2},{value:"Data Conditional Router",id:"data-conditional-router",level:3},{value:"Inputs",id:"inputs-6",level:4},{value:"Outputs",id:"outputs-6",level:4},{value:"Operator behavior",id:"operator-behavior-1",level:4},{value:"List processing",id:"list-processing",level:4},{value:"Deprecated components",id:"deprecated-components",level:2},{value:"Flow as tool",id:"flow-as-tool",level:3},{value:"Inputs",id:"inputs-7",level:4},{value:"Outputs",id:"outputs-7",level:4},{value:"Sub flow",id:"sub-flow",level:3},{value:"Inputs",id:"inputs-8",level:4},{value:"Outputs",id:"outputs-8",level:4}];function x(e){const t={a:"a",admonition:"admonition",code:"code",h1:"h1",h2:"h2",h3:"h3",h4:"h4",header:"header",img:"img",li:"li",ol:"ol",p:"p",strong:"strong",table:"table",tbody:"tbody",td:"td",th:"th",thead:"thead",tr:"tr",ul:"ul",...(0,i.R)(),...e.components};return h||u("CH",!1),h.Code||u("CH.Code",!0),(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)("style",{dangerouslySetInnerHTML:{__html:'[data-ch-theme="github-dark"] { --ch-t-colorScheme: dark;--ch-t-foreground: #c9d1d9;--ch-t-background: #0d1117;--ch-t-lighter-inlineBackground: #0d1117e6;--ch-t-editor-background: #0d1117;--ch-t-editor-foreground: #c9d1d9;--ch-t-editor-lineHighlightBackground: #6e76811a;--ch-t-editor-rangeHighlightBackground: #ffffff0b;--ch-t-editor-infoForeground: #3794FF;--ch-t-editor-selectionBackground: #264F78;--ch-t-focusBorder: #1f6feb;--ch-t-tab-activeBackground: #0d1117;--ch-t-tab-activeForeground: #c9d1d9;--ch-t-tab-inactiveBackground: #010409;--ch-t-tab-inactiveForeground: #8b949e;--ch-t-tab-border: #30363d;--ch-t-tab-activeBorder: #0d1117;--ch-t-editorGroup-border: #30363d;--ch-t-editorGroupHeader-tabsBackground: #010409;--ch-t-editorLineNumber-foreground: #6e7681;--ch-t-input-background: #0d1117;--ch-t-input-foreground: #c9d1d9;--ch-t-input-border: #30363d;--ch-t-icon-foreground: #8b949e;--ch-t-sideBar-background: #010409;--ch-t-sideBar-foreground: #c9d1d9;--ch-t-sideBar-border: #30363d;--ch-t-list-activeSelectionBackground: #6e768166;--ch-t-list-activeSelectionForeground: #c9d1d9;--ch-t-list-hoverBackground: #6e76811a;--ch-t-list-hoverForeground: #c9d1d9; }'}}),"\n",(0,o.jsx)(t.header,{children:(0,o.jsx)(t.h1,{id:"logic-components-in-langflow",children:"Logic components in Langflow"})}),"\n",(0,o.jsx)(t.p,{children:"Logic components provide functionalities for routing, conditional processing, and flow management."}),"\n",(0,o.jsx)(t.h2,{id:"use-a-logic-component-in-a-flow",children:"Use a logic component in a flow"}),"\n",(0,o.jsxs)(t.p,{children:['This flow creates a summarizing "for each" loop with the ',(0,o.jsx)(t.a,{href:"/components-logic#loop",children:"Loop"})," component."]}),"\n",(0,o.jsxs)(t.p,{children:["The component iterates over a list of ",(0,o.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects until it's completed, and then the ",(0,o.jsx)(t.strong,{children:"Done"})," loop aggregates the results."]}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"File"})," component loads text files from your local machine, and then the ",(0,o.jsx)(t.strong,{children:"Parse Data"})," component parses them into a list of structured ",(0,o.jsx)(t.code,{children:"Data"})," objects.\nThe ",(0,o.jsx)(t.strong,{children:"Loop"})," component passes each ",(0,o.jsx)(t.code,{children:"Data"})," object to a ",(0,o.jsx)(t.strong,{children:"Prompt"})," to be summarized."]}),"\n",(0,o.jsxs)(t.p,{children:["When the ",(0,o.jsx)(t.strong,{children:"Loop"})," component runs out of ",(0,o.jsx)(t.code,{children:"Data"}),", the ",(0,o.jsx)(t.strong,{children:"Done"})," loop activates, which counts the number of pages and summarizes their tone with another ",(0,o.jsx)(t.strong,{children:"Prompt"}),".\nThis is represented in Langflow by connecting the Parse Data component's ",(0,o.jsx)(t.strong,{children:"Data List"})," output to the Loop component's ",(0,o.jsx)(t.code,{children:"Data"})," loop input."]}),"\n",(0,o.jsx)(t.p,{children:(0,o.jsx)(t.img,{alt:"Sample Flow looping summarizer",src:n(19709).A+"",width:"2676",height:"1512"})}),"\n",(0,o.jsx)(t.p,{children:"The output will look similar to this:"}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Document Summary",props:{}}]},{tokens:[{content:"Total Pages Processed",props:{}}]},{tokens:[{content:"Total Pages: 2",props:{}}]},{tokens:[{content:"Overall Tone of Document",props:{}}]},{tokens:[{content:"Tone: Informative and Instructional",props:{}}]},{tokens:[{content:"The documentation outlines microservices architecture patterns and best practices.",props:{}}]},{tokens:[{content:"It emphasizes service isolation and inter-service communication protocols.",props:{}}]},{tokens:[{content:"The use of asynchronous messaging patterns is recommended for system scalability.",props:{}}]},{tokens:[{content:"It includes code examples of REST and gRPC implementations to demonstrate integration approaches.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(t.h2,{id:"conditional-router-if-else-component",children:"Conditional router (If-Else component)"}),"\n",(0,o.jsxs)(t.p,{children:["This component routes messages by comparing two strings.\nIt evaluates a condition by comparing two text inputs using the specified operator and routes the message to ",(0,o.jsx)(t.code,{children:"true_result"})," or ",(0,o.jsx)(t.code,{children:"false_result"}),"."]}),"\n",(0,o.jsxs)(t.p,{children:["The operator looks for single strings based on your defined ",(0,o.jsx)(t.a,{href:"#operator-behavior",children:"operator behavior"}),", but it can also search for multiple words by regex matching."]}),"\n",(0,o.jsxs)(t.p,{children:["To use the ",(0,o.jsx)(t.strong,{children:"Conditional router"})," component to check incoming messages with regex matching, do the following:"]}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["Connect the ",(0,o.jsx)(t.strong,{children:"If-Else"})," component's ",(0,o.jsx)(t.strong,{children:"Text Input"})," port to a ",(0,o.jsx)(t.strong,{children:"Chat Input"})," component."]}),"\n",(0,o.jsx)(t.li,{children:"In the If-Else component, enter the following values."}),"\n"]}),"\n",(0,o.jsxs)(t.ul,{children:["\n",(0,o.jsxs)(t.li,{children:["In the ",(0,o.jsx)(t.strong,{children:"Match Text"})," field, enter ",(0,o.jsx)(t.code,{children:".*(urgent|warning|caution).*"}),". The component looks for these values. The regex match is case sensitive, so to look for all permutations of ",(0,o.jsx)(t.code,{children:"warning"}),", enter ",(0,o.jsx)(t.code,{children:"warning|Warning|WARNING"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["In the ",(0,o.jsx)(t.strong,{children:"Operator"})," field, enter ",(0,o.jsx)(t.code,{children:"regex"}),". The component looks for the strings ",(0,o.jsx)(t.code,{children:"urgent"}),", ",(0,o.jsx)(t.code,{children:"warning"}),", and ",(0,o.jsx)(t.code,{children:"caution"}),". For more operators, see ",(0,o.jsx)(t.a,{href:"#operator-behavior",children:"Operator behavior"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["In the ",(0,o.jsx)(t.strong,{children:"Message"})," field, enter ",(0,o.jsx)(t.code,{children:"New Message Detected"}),". This field is optional. The message is sent to both the ",(0,o.jsx)(t.strong,{children:"True"})," and ",(0,o.jsx)(t.strong,{children:"False"})," ports.\nThe component is now set up to send a ",(0,o.jsx)(t.code,{children:"New Message Detected"})," message out of its ",(0,o.jsx)(t.strong,{children:"True"})," port if it matches any of the strings.\nIf no strings are detected, it sends a message out of the ",(0,o.jsx)(t.strong,{children:"False"})," port."]}),"\n"]}),"\n",(0,o.jsxs)(t.ol,{start:"3",children:["\n",(0,o.jsxs)(t.li,{children:["Create two identical flows to process the messages. Connect an ",(0,o.jsx)(t.strong,{children:"Open AI"})," component, a ",(0,o.jsx)(t.strong,{children:"Prompt"}),", and a ",(0,o.jsx)(t.strong,{children:"Chat Output"})," component together."]}),"\n",(0,o.jsxs)(t.li,{children:["Connect one chain to the ",(0,o.jsx)(t.strong,{children:"If-Else"})," component's ",(0,o.jsx)(t.strong,{children:"True"})," port, and one chain to the ",(0,o.jsx)(t.strong,{children:"False"})," port."]}),"\n"]}),"\n",(0,o.jsx)(t.p,{children:"The flow looks like this:"}),"\n",(0,o.jsx)(t.p,{children:(0,o.jsx)(t.img,{alt:"A conditional router connected to two OpenAI components",src:n(89329).A+"",width:"1888",height:"1754"})}),"\n",(0,o.jsxs)(t.ol,{start:"5",children:["\n",(0,o.jsxs)(t.li,{children:["Add your ",(0,o.jsx)(t.strong,{children:"OpenAI API key"})," to both ",(0,o.jsx)(t.strong,{children:"OpenAI"})," components."]}),"\n",(0,o.jsxs)(t.li,{children:["In both ",(0,o.jsx)(t.strong,{children:"Prompt"})," components, enter the behavior you want each route to take.\nWhen a match is found:"]}),"\n"]}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Send a message that a new message has been received and added to the Urgent queue.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(t.p,{children:"When a match is not found:"}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Send a message that a new message has been received and added to the backlog.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsxs)(t.ol,{start:"7",children:["\n",(0,o.jsxs)(t.li,{children:["Open the ",(0,o.jsx)(t.strong,{children:"Playground"}),"."]}),"\n",(0,o.jsx)(t.li,{children:"Send the flow some messages. Your messages route differently based on the if-else component's evaluation."}),"\n"]}),"\n",(0,o.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"User",props:{}}]},{tokens:[{content:"A new user was created.",props:{}}]},{tokens:[{content:"",props:{}}]},{tokens:[{content:"AI",props:{}}]},{tokens:[{content:"A new message has been received and added to the backlog.",props:{}}]},{tokens:[{content:"",props:{}}]},{tokens:[{content:"User",props:{}}]},{tokens:[{content:"Sign-in warning: new user locked out.",props:{}}]},{tokens:[{content:"",props:{}}]},{tokens:[{content:"AI",props:{}}]},{tokens:[{content:"A new message has been received and added to the Urgent queue. Please review it at your earliest convenience.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,o.jsx)(t.h3,{id:"inputs",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"input_text"}),(0,o.jsx)(t.td,{children:"String"}),(0,o.jsx)(t.td,{children:"The primary text input for the operation."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"match_text"}),(0,o.jsx)(t.td,{children:"String"}),(0,o.jsx)(t.td,{children:"The text input to compare against."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"operator"}),(0,o.jsx)(t.td,{children:"Dropdown"}),(0,o.jsx)(t.td,{children:'The operator to compare texts. Options: "equals", "not equals", "contains", "starts with", "ends with", "regex". Default: "equals".'})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"case_sensitive"}),(0,o.jsx)(t.td,{children:"Boolean"}),(0,o.jsx)(t.td,{children:"If true, the comparison is case sensitive. This setting is ignored for regex comparison. Default: false."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"message"}),(0,o.jsx)(t.td,{children:"Message"}),(0,o.jsx)(t.td,{children:"The message to pass through either route."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"max_iterations"}),(0,o.jsx)(t.td,{children:"Integer"}),(0,o.jsx)(t.td,{children:"The maximum number of iterations for the conditional router. Default: 10."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"default_route"}),(0,o.jsx)(t.td,{children:"Dropdown"}),(0,o.jsx)(t.td,{children:'The default route to take when max iterations are reached. Options: "true_result" or "false_result". Default: "false_result".'})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"true_result"}),(0,o.jsx)(t.td,{children:"Message"}),(0,o.jsx)(t.td,{children:"The output when the condition is true."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"false_result"}),(0,o.jsx)(t.td,{children:"Message"}),(0,o.jsx)(t.td,{children:"The output when the condition is false."})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"operator-behavior",children:"Operator Behavior"}),"\n",(0,o.jsxs)(t.p,{children:["The ",(0,o.jsx)(t.strong,{children:"If-else"})," component includes a comparison operator to compare the values in ",(0,o.jsx)(t.code,{children:"input_text"})," and ",(0,o.jsx)(t.code,{children:"match_text"}),"."]}),"\n",(0,o.jsxs)(t.p,{children:["All options respect the ",(0,o.jsx)(t.code,{children:"case_sensitive"})," setting except ",(0,o.jsx)(t.strong,{children:"regex"}),"."]}),"\n",(0,o.jsxs)(t.ul,{children:["\n",(0,o.jsxs)(t.li,{children:[(0,o.jsx)(t.strong,{children:"equals"}),": Exact match comparison."]}),"\n",(0,o.jsxs)(t.li,{children:[(0,o.jsx)(t.strong,{children:"not equals"}),": Inverse of exact match."]}),"\n",(0,o.jsxs)(t.li,{children:[(0,o.jsx)(t.strong,{children:"contains"}),": Checks if match_text is found within input_text."]}),"\n",(0,o.jsxs)(t.li,{children:[(0,o.jsx)(t.strong,{children:"starts with"}),": Checks if input_text begins with match_text."]}),"\n",(0,o.jsxs)(t.li,{children:[(0,o.jsx)(t.strong,{children:"ends with"}),": Checks if input_text ends with match_text."]}),"\n",(0,o.jsxs)(t.li,{children:[(0,o.jsx)(t.strong,{children:"regex"}),": Performs regular expression matching. It is always case sensitive and ignores the case_sensitive setting."]}),"\n"]}),"\n",(0,o.jsx)(t.h2,{id:"listen",children:"Listen"}),"\n",(0,o.jsx)(t.p,{children:"This component listens for a notification and retrieves its associated state."}),"\n",(0,o.jsx)(t.h3,{id:"inputs-1",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"name"}),(0,o.jsx)(t.td,{children:"String"}),(0,o.jsx)(t.td,{children:"The name of the notification to listen for."})]})})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-1",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"output"}),(0,o.jsx)(t.td,{children:"Data"}),(0,o.jsx)(t.td,{children:"The state associated with the notification."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"loop",children:"Loop"}),"\n",(0,o.jsxs)(t.p,{children:["This component iterates over a list of ",(0,o.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects, outputting one item at a time and aggregating results from loop inputs."]}),"\n",(0,o.jsxs)(t.p,{children:["In this example, the ",(0,o.jsx)(t.strong,{children:"Loop"})," component iterates over a CSV file through the ",(0,o.jsx)(t.strong,{children:"Item"})," port until there are no rows left to process. Then, the ",(0,o.jsx)(t.strong,{children:"Loop"})," component performs the actions connected to the ",(0,o.jsx)(t.strong,{children:"Done"})," port, which in this case is loading the structured data into ",(0,o.jsx)(t.strong,{children:"Chroma DB"}),"."]}),"\n",(0,o.jsxs)(t.p,{children:["Think of it this way: the ",(0,o.jsx)(t.strong,{children:"Item"}),' port forms the "main" loop that repeats until a "complete" condition is reached.']}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["The ",(0,o.jsx)(t.strong,{children:"Loop"})," component accepts ",(0,o.jsx)(t.strong,{children:"Data"})," from the ",(0,o.jsx)(t.strong,{children:"Load CSV"})," component, and outputs the data from the ",(0,o.jsx)(t.strong,{children:"Item"})," port."]}),"\n",(0,o.jsxs)(t.li,{children:["Each CSV row is converted to a ",(0,o.jsx)(t.strong,{children:"Message"})," and processed into structured data with the ",(0,o.jsx)(t.strong,{children:"Structured Output"})," component.\nThe dotted line connected from the ",(0,o.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,o.jsx)(t.strong,{children:"Looping"})," port tells you where the loop begins again."]}),"\n",(0,o.jsxs)(t.li,{children:["The ",(0,o.jsx)(t.strong,{children:"Loop"})," component repeatedly extracts rows by ",(0,o.jsx)(t.strong,{children:"Text Key"})," until there are no more rows to extract."]}),"\n"]}),"\n",(0,o.jsxs)(t.p,{children:["Once all items are processed, the action connected to the ",(0,o.jsx)(t.strong,{children:"Done"})," port is performed.\nIn this example, the data is loaded into ",(0,o.jsx)(t.strong,{children:"Chroma DB"}),"."]}),"\n",(0,o.jsx)(t.p,{children:(0,o.jsx)(t.img,{alt:"Loop CSV parser",src:n(91110).A+"",width:"3008",height:"3172"})}),"\n",(0,o.jsxs)(t.p,{children:["Follow along with this step-by-step video guide for creating this flow and adding agentic RAG: ",(0,o.jsx)(t.a,{href:"https://www.youtube.com/watch?v=9Wx7WODSKTo",children:"Mastering the Loop Component & Agentic RAG in Langflow"}),"."]}),"\n",(0,o.jsx)(t.h3,{id:"inputs-2",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"data"}),(0,o.jsx)(t.td,{children:"Data/List"}),(0,o.jsx)(t.td,{children:"The initial list of Data objects to iterate over."})]})})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-2",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"item"}),(0,o.jsx)(t.td,{children:"Data"}),(0,o.jsx)(t.td,{children:"Outputs one item at a time from the data list."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"done"}),(0,o.jsx)(t.td,{children:"Data"}),(0,o.jsx)(t.td,{children:"Triggered when iteration complete, returns aggregated results."})]})]})]}),"\n",(0,o.jsx)(t.h2,{id:"notify",children:"Notify"}),"\n",(0,o.jsx)(t.p,{children:"This component generates a notification for the Listen component to use."}),"\n",(0,o.jsx)(t.h3,{id:"inputs-3",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"name"}),(0,o.jsx)(t.td,{children:"String"}),(0,o.jsx)(t.td,{children:"The name of the notification."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"data"}),(0,o.jsx)(t.td,{children:"Data"}),(0,o.jsx)(t.td,{children:"The data to store in the notification."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"append"}),(0,o.jsx)(t.td,{children:"Boolean"}),(0,o.jsx)(t.td,{children:"If true, the record will be appended to the existing notification."})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-3",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"output"}),(0,o.jsx)(t.td,{children:"Data"}),(0,o.jsx)(t.td,{children:"The data stored in the notification."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"pass-message",children:"Pass message"}),"\n",(0,o.jsx)(t.p,{children:"This component forwards the input message, unchanged."}),"\n",(0,o.jsx)(t.h3,{id:"inputs-4",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"input_message"}),(0,o.jsx)(t.td,{children:"Input Message"}),(0,o.jsx)(t.td,{children:"The message to be passed forward."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"ignored_message"}),(0,o.jsx)(t.td,{children:"Ignored Message"}),(0,o.jsx)(t.td,{children:"A second message to be ignored. Used as a workaround for continuity."})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-4",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Display Name"}),(0,o.jsx)(t.th,{children:"Info"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"output_message"}),(0,o.jsx)(t.td,{children:"Output Message"}),(0,o.jsx)(t.td,{children:"The forwarded input message."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"run-flow",children:"Run flow"}),"\n",(0,o.jsx)(t.p,{children:"This component allows you to run any flow stored in your Langflow database without opening the flow editor."}),"\n",(0,o.jsxs)(t.p,{children:["The Run Flow component can also be used as a tool when connected to an ",(0,o.jsx)(t.a,{href:"/components-agents",children:"Agent"}),". The ",(0,o.jsx)(t.code,{children:"name"})," and ",(0,o.jsx)(t.code,{children:"description"})," metadata that the Agent uses to register the tool are created automatically."]}),"\n",(0,o.jsx)(t.p,{children:"When you select a flow, the component fetches the flow's graph structure and uses it to generate the inputs and outputs for the Run Flow component."}),"\n",(0,o.jsx)(t.p,{children:"To use the Run Flow component as a tool, do the following:"}),"\n",(0,o.jsxs)(t.ol,{children:["\n",(0,o.jsxs)(t.li,{children:["Add the ",(0,o.jsx)(t.strong,{children:"Run Flow"})," component to the ",(0,o.jsx)(t.a,{href:"/starter-projects-simple-agent",children:"Simple Agent"})," flow."]}),"\n",(0,o.jsxs)(t.li,{children:["In the ",(0,o.jsx)(t.strong,{children:"Flow Name"})," menu, select the sub-flow you want to run.\nThe appearance of the ",(0,o.jsx)(t.strong,{children:"Run Flow"})," component changes to reflect the inputs and outputs of the selected flow."]}),"\n",(0,o.jsxs)(t.li,{children:["On the ",(0,o.jsx)(t.strong,{children:"Run Flow"})," component, enable ",(0,o.jsx)(t.strong,{children:"Tool Mode"}),"."]}),"\n",(0,o.jsxs)(t.li,{children:["Connect the ",(0,o.jsx)(t.strong,{children:"Run Flow"})," component to the ",(0,o.jsx)(t.strong,{children:"Toolset"})," input of the Agent.\nYour flow should now look like this:\n",(0,o.jsx)(t.img,{alt:"Run Flow component",src:n(18111).A+"",width:"2036",height:"1582"})]}),"\n",(0,o.jsx)(t.li,{children:"Run the flow. The Agent uses the Run Flow component as a tool to run the selected sub-flow."}),"\n"]}),"\n",(0,o.jsx)(t.h3,{id:"inputs-5",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"flow_name_selected"}),(0,o.jsx)(t.td,{children:"Dropdown"}),(0,o.jsx)(t.td,{children:"The name of the flow to run."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"flow_tweak_data"}),(0,o.jsx)(t.td,{children:"Dict"}),(0,o.jsx)(t.td,{children:"Dictionary of tweaks to customize the flow's behavior."})]}),(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"dynamic inputs"}),(0,o.jsx)(t.td,{children:"Various"}),(0,o.jsx)(t.td,{children:"Additional inputs that are generated based on the selected flow."})]})]})]}),"\n",(0,o.jsx)(t.h3,{id:"outputs-5",children:"Outputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsx)(t.tbody,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"run_outputs"}),(0,o.jsxs)(t.td,{children:["A ",(0,o.jsx)(t.code,{children:"List"})," of types ",(0,o.jsx)(t.code,{children:"Data"}),", ",(0,o.jsx)(t.code,{children:"Message,"})," or ",(0,o.jsx)(t.code,{children:"DataFrame"})]}),(0,o.jsx)(t.td,{children:"All outputs are generated from running the flow."})]})})]}),"\n",(0,o.jsx)(t.h2,{id:"legacy-components",children:"Legacy components"}),"\n",(0,o.jsx)(t.p,{children:"Legacy components are available to use but no longer supported."}),"\n",(0,o.jsx)(t.h3,{id:"data-conditional-router",children:"Data Conditional Router"}),"\n",(0,o.jsx)(t.admonition,{type:"important",children:(0,o.jsxs)(t.p,{children:["This component is in ",(0,o.jsx)(t.strong,{children:"Legacy"}),", which means it is no longer in active development as of Langflow version 1.3."]})}),"\n",(0,o.jsxs)(t.p,{children:["This component routes ",(0,o.jsx)(t.code,{children:"Data"})," objects based on a condition applied to a specified key, including boolean validation. It can process either a single Data object or a list of Data objects."]}),"\n",(0,o.jsx)(t.p,{children:"This component is particularly useful in workflows that require conditional routing of complex data structures, enabling dynamic decision-making based on data content."}),"\n",(0,o.jsx)(t.h4,{id:"inputs-6",children:"Inputs"}),"\n",(0,o.jsxs)(t.table,{children:[(0,o.jsx)(t.thead,{children:(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.th,{children:"Name"}),(0,o.jsx)(t.th,{children:"Type"}),(0,o.jsx)(t.th,{children:"Description"})]})}),(0,o.jsxs)(t.tbody,{children:[(0,o.jsxs)(t.tr,{children:[(0,o.jsx)(t.td,{children:"data_input"}),(0,o.jsx)(t.td,{children:"Data"}),(0,o.jsx)(t.td,{children:"The Data object or list of Data objects to process. 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We'll see how combining text works.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-1",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"first_text"}),(0,r.jsx)(t.td,{children:"First Text"}),(0,r.jsx)(t.td,{children:"The first text input to concatenate."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"second_text"}),(0,r.jsx)(t.td,{children:"Second Text"}),(0,r.jsx)(t.td,{children:"The second text input to concatenate."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"delimiter"}),(0,r.jsx)(t.td,{children:"Delimiter"}),(0,r.jsx)(t.td,{children:"A string used to separate the two text inputs. Defaults to a space."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-1",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsxs)(t.td,{children:["A ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object containing the combined text."]})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"dataframe-operations",children:"DataFrame operations"}),"\n",(0,r.jsxs)(t.p,{children:["This component performs operations on ",(0,r.jsx)(t.a,{href:"https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html",children:"DataFrame"})," rows and columns."]}),"\n",(0,r.jsxs)(t.p,{children:["To use this component in a flow, connect a component that outputs ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," to the ",(0,r.jsx)(t.strong,{children:"DataFrame Operations"})," component."]}),"\n",(0,r.jsxs)(t.p,{children:["This example fetches JSON data from an API. The ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component extracts and flattens the results into a tabular DataFrame. The ",(0,r.jsx)(t.strong,{children:"DataFrame Operations"})," component can then work with the retrieved data."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Dataframe operations with flattened dataframe",src:n(13533).A+"",width:"983",height:"696"})}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["The ",(0,r.jsx)(t.strong,{children:"API Request"})," component retrieves data with only ",(0,r.jsx)(t.code,{children:"source"})," and ",(0,r.jsx)(t.code,{children:"result"})," fields.\nFor this example, the desired data is nested within the ",(0,r.jsx)(t.code,{children:"result"})," field."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Lambda Filter"})," to the API request component, and a ",(0,r.jsx)(t.strong,{children:"Language model"})," to the ",(0,r.jsx)(t.strong,{children:"Lambda Filter"}),". This example connects a ",(0,r.jsx)(t.strong,{children:"Groq"})," model component."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Groq"})," model component, add your ",(0,r.jsx)(t.strong,{children:"Groq"})," API key."]}),"\n",(0,r.jsxs)(t.li,{children:["To filter the data, in the ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component, in the ",(0,r.jsx)(t.strong,{children:"Instructions"})," field, use natural language to describe how the data should be filtered.\nFor this example, enter:"]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"I want to explode the result column out into a Data object",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.admonition,{type:"tip",children:(0,r.jsxs)(t.p,{children:["Avoid punctuation in the ",(0,r.jsx)(t.strong,{children:"Instructions"})," field, as it can cause errors."]})}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsxs)(t.li,{children:["To run the flow, in the ",(0,r.jsx)(t.strong,{children:"Lambda Filter"})," component, click ",(0,r.jsx)(a.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To inspect the filtered data, in the ",(0,r.jsx)(t.strong,{children:"Lambda Filter"})," component, click ",(0,r.jsx)(a.A,{name:"TextSearch","aria-label":"Inspect icon"}),".\nThe result is a structured DataFrame."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"id | name | company | username | email | address | zip",props:{}}]},{tokens:[{content:"---|------------------|----------------------|-----------------|------------------------------------|-------------------|-------",props:{}}]},{tokens:[{content:"1 | Emily Johnson | ABC Corporation | emily_johnson | emily.johnson@abccorporation.com | 123 Main St | 12345",props:{}}]},{tokens:[{content:"2 | Michael Williams | XYZ Corp | michael_williams| michael.williams@xyzcorp.com | 456 Elm Ave | 67890",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["Add the ",(0,r.jsx)(t.strong,{children:"DataFrame Operations"})," component, and a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to the flow."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"DataFrame Operations"})," component, in the ",(0,r.jsx)(t.strong,{children:"Operation"})," field, select ",(0,r.jsx)(t.strong,{children:"Filter"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To apply a filter, in the ",(0,r.jsx)(t.strong,{children:"Column Name"})," field, enter a column to filter on. This example filters by ",(0,r.jsx)(t.code,{children:"name"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Click ",(0,r.jsx)(t.strong,{children:"Playground"}),", and then click ",(0,r.jsx)(t.strong,{children:"Run Flow"}),".\nThe flow extracts the values from the ",(0,r.jsx)(t.code,{children:"name"})," column."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"name",props:{}}]},{tokens:[{content:"Emily Johnson",props:{}}]},{tokens:[{content:"Michael Williams",props:{}}]},{tokens:[{content:"John Smith",props:{}}]},{tokens:[{content:"...",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"operations",children:"Operations"}),"\n",(0,r.jsxs)(t.p,{children:["This component can perform the following operations on Pandas ",(0,r.jsx)(t.a,{href:"https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html",children:"DataFrame"}),"."]}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Operation"}),(0,r.jsx)(t.th,{children:"Description"}),(0,r.jsx)(t.th,{children:"Required Inputs"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Add Column"}),(0,r.jsx)(t.td,{children:"Adds a new column with a constant value"}),(0,r.jsx)(t.td,{children:"new_column_name, new_column_value"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Drop Column"}),(0,r.jsx)(t.td,{children:"Removes a specified column"}),(0,r.jsx)(t.td,{children:"column_name"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Filter"}),(0,r.jsx)(t.td,{children:"Filters rows based on column value"}),(0,r.jsx)(t.td,{children:"column_name, filter_value"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Head"}),(0,r.jsx)(t.td,{children:"Returns first n rows"}),(0,r.jsx)(t.td,{children:"num_rows"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Rename Column"}),(0,r.jsx)(t.td,{children:"Renames an existing column"}),(0,r.jsx)(t.td,{children:"column_name, new_column_name"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Replace Value"}),(0,r.jsx)(t.td,{children:"Replaces values in a column"}),(0,r.jsx)(t.td,{children:"column_name, replace_value, replacement_value"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Select Columns"}),(0,r.jsx)(t.td,{children:"Selects specific columns"}),(0,r.jsx)(t.td,{children:"columns_to_select"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Sort"}),(0,r.jsx)(t.td,{children:"Sorts DataFrame by column"}),(0,r.jsx)(t.td,{children:"column_name, ascending"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Tail"}),(0,r.jsx)(t.td,{children:"Returns last n rows"}),(0,r.jsx)(t.td,{children:"num_rows"})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-2",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"df"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"The input DataFrame to operate on."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"operation"}),(0,r.jsx)(t.td,{children:"Operation"}),(0,r.jsx)(t.td,{children:"Select the DataFrame operation to perform. Options: Add Column, Drop Column, Filter, Head, Rename Column, Replace Value, Select Columns, Sort, Tail"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"column_name"}),(0,r.jsx)(t.td,{children:"Column Name"}),(0,r.jsx)(t.td,{children:"The column name to use for the operation."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_value"}),(0,r.jsx)(t.td,{children:"Filter Value"}),(0,r.jsx)(t.td,{children:"The value to filter rows by."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"ascending"}),(0,r.jsx)(t.td,{children:"Sort Ascending"}),(0,r.jsx)(t.td,{children:"Whether to sort in ascending order."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"new_column_name"}),(0,r.jsx)(t.td,{children:"New Column Name"}),(0,r.jsx)(t.td,{children:"The new column name when renaming or adding a column."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"new_column_value"}),(0,r.jsx)(t.td,{children:"New Column Value"}),(0,r.jsx)(t.td,{children:"The value to populate the new column with."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"columns_to_select"}),(0,r.jsx)(t.td,{children:"Columns to Select"}),(0,r.jsx)(t.td,{children:"List of column names to select."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"num_rows"}),(0,r.jsx)(t.td,{children:"Number of Rows"}),(0,r.jsx)(t.td,{children:"Number of rows to return (for head/tail). Default: 5"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"replace_value"}),(0,r.jsx)(t.td,{children:"Value to Replace"}),(0,r.jsx)(t.td,{children:"The value to replace in the column."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"replacement_value"}),(0,r.jsx)(t.td,{children:"Replacement Value"}),(0,r.jsx)(t.td,{children:"The value to replace with."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-2",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"The resulting DataFrame after the operation."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"data-to-dataframe",children:"Data to DataFrame"}),"\n",(0,r.jsxs)(t.p,{children:["This component converts one or multiple ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects into a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"}),". Each Data object corresponds to one row in the resulting DataFrame. Fields from the ",(0,r.jsx)(t.code,{children:".data"})," attribute become columns, and the ",(0,r.jsx)(t.code,{children:".text"})," field (if present) is placed in a 'text' column."]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect a component that outputs ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," to the ",(0,r.jsx)(t.strong,{children:"Data to Dataframe"})," component's input.\nThis example connects a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component to convert ",(0,r.jsx)(t.code,{children:"text"})," and ",(0,r.jsx)(t.code,{children:"data"})," into a DataFrame."]}),"\n",(0,r.jsxs)(t.li,{children:["To view the flow's output, connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to the ",(0,r.jsx)(t.strong,{children:"Data to Dataframe"})," component."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"A webhook and data to dataframe",src:n(45709).A+"",width:"1221",height:"468"})}),"\n",(0,r.jsxs)(t.ol,{start:"3",children:["\n",(0,r.jsxs)(t.li,{children:["Send a POST request to the ",(0,r.jsx)(t.strong,{children:"Webhook"})," containing your JSON data.\nReplace ",(0,r.jsx)(t.code,{children:"YOUR_FLOW_ID"})," with your flow ID.\nThis example uses the default Langflow server address."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:'curl -X POST "http://127.0.0.1:7860/api/v1/webhook/YOUR_FLOW_ID" \\',props:{}}]},{tokens:[{content:"-H 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:"-d '{",props:{}}]},{tokens:[{content:' "text": "Alex Cruz - Employee Profile",',props:{}}]},{tokens:[{content:' "data": {',props:{}}]},{tokens:[{content:' "Name": "Alex Cruz",',props:{}}]},{tokens:[{content:' "Role": "Developer",',props:{}}]},{tokens:[{content:' "Department": "Engineering"',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"4",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Playground"}),", view the output of your flow.\nThe ",(0,r.jsx)(t.strong,{children:"Data to DataFrame"})," component converts the webhook request into a ",(0,r.jsx)(t.code,{children:"DataFrame"}),", with ",(0,r.jsx)(t.code,{children:"text"})," and ",(0,r.jsx)(t.code,{children:"data"})," fields as columns."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"| text | data |",props:{}}]},{tokens:[{content:"|:-----------------------------|:------------------------------------------------------------------------|",props:{}}]},{tokens:[{content:"| Alex Cruz - Employee Profile | {'Name': 'Alex Cruz', 'Role': 'Developer', 'Department': 'Engineering'} |",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsx)(t.li,{children:"Send another employee data object."}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:'curl -X POST "http://127.0.0.1:7860/api/v1/webhook/YOUR_FLOW_ID" \\',props:{}}]},{tokens:[{content:"-H 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:"-d '{",props:{}}]},{tokens:[{content:' "text": "Kalani Smith - Employee Profile",',props:{}}]},{tokens:[{content:' "data": {',props:{}}]},{tokens:[{content:' "Name": "Kalani Smith",',props:{}}]},{tokens:[{content:' "Role": "Designer",',props:{}}]},{tokens:[{content:' "Department": "Design"',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"6",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Playground"}),", this request is also converted to ",(0,r.jsx)(t.code,{children:"DataFrame"}),"."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"| text | data |",props:{}}]},{tokens:[{content:"|:--------------------------------|:---------------------------------------------------------------------|",props:{}}]},{tokens:[{content:"| Kalani Smith - Employee Profile | {'Name': 'Kalani Smith', 'Role': 'Designer', 'Department': 'Design'} |",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-3",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data_list"}),(0,r.jsx)(t.td,{children:"Data or Data List"}),(0,r.jsx)(t.td,{children:"One or multiple Data objects to transform into a DataFrame."})]})})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-3",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"A DataFrame built from each Data object's fields plus a 'text' column."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"filter-data",children:"Filter data"}),"\n",(0,r.jsx)(t.admonition,{type:"important",children:(0,r.jsxs)(t.p,{children:["This component is in ",(0,r.jsx)(t.strong,{children:"Beta"})," as of Langflow version 1.1.3, and is not yet fully supported."]})}),"\n",(0,r.jsxs)(t.p,{children:["This component filters a ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object based on a list of keys."]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-4",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"Data object to filter."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_criteria"}),(0,r.jsx)(t.td,{children:"Filter Criteria"}),(0,r.jsx)(t.td,{children:"List of keys to filter by."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-4",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filtered_data"}),(0,r.jsx)(t.td,{children:"Filtered Data"}),(0,r.jsxs)(t.td,{children:["A new ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object containing only the key-value pairs that match the filter criteria."]})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"filter-values",children:"Filter values"}),"\n",(0,r.jsx)(t.admonition,{type:"important",children:(0,r.jsxs)(t.p,{children:["This component is in ",(0,r.jsx)(t.strong,{children:"Beta"})," as of Langflow version 1.1.3, and is not yet fully supported."]})}),"\n",(0,r.jsx)(t.p,{children:"The Filter values component filters a list of data items based on a specified key, filter value, and comparison operator."}),"\n",(0,r.jsx)(t.h3,{id:"inputs-5",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_data"}),(0,r.jsx)(t.td,{children:"Input data"}),(0,r.jsx)(t.td,{children:"The list of data items to filter."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_key"}),(0,r.jsx)(t.td,{children:"Filter Key"}),(0,r.jsx)(t.td,{children:"The key to filter on, for example, 'route'."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_value"}),(0,r.jsx)(t.td,{children:"Filter Value"}),(0,r.jsx)(t.td,{children:"The value to filter by, for example, 'CMIP'."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"operator"}),(0,r.jsx)(t.td,{children:"Comparison Operator"}),(0,r.jsx)(t.td,{children:"The operator to apply for comparing the values."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-5",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filtered_data"}),(0,r.jsx)(t.td,{children:"Filtered data"}),(0,r.jsx)(t.td,{children:"The resulting list of filtered data items."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"lambda-filter",children:"Lambda filter"}),"\n",(0,r.jsx)(t.p,{children:"This component uses an LLM to generate a Lambda function for filtering or transforming structured data."}),"\n",(0,r.jsxs)(t.p,{children:["To use the ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component, you must connect it to a ",(0,r.jsx)(t.a,{href:"/components-models#language-model",children:"Language Model"})," component, which the component uses to generate a function based on the natural language instructions in the ",(0,r.jsx)(t.strong,{children:"Instructions"})," field."]}),"\n",(0,r.jsxs)(t.p,{children:["This example gets JSON data from the ",(0,r.jsx)(t.code,{children:"https://jsonplaceholder.typicode.com/users"})," API endpoint.\nThe ",(0,r.jsx)(t.strong,{children:"Instructions"})," field in the ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component specifies the task ",(0,r.jsx)(t.code,{children:"extract emails"}),".\nThe connected LLM creates a filter based on the instructions, and successfully extracts a list of email addresses from the JSON data."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{src:n(66539).A+"",width:"1742",height:"1622"})}),"\n",(0,r.jsx)(t.h3,{id:"inputs-6",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The structured data to filter or transform using a Lambda function."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"llm"}),(0,r.jsx)(t.td,{children:"Language Model"}),(0,r.jsxs)(t.td,{children:["The connection port for a ",(0,r.jsx)(t.a,{href:"/components-models",children:"Model"})," component."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_instruction"}),(0,r.jsx)(t.td,{children:"Instructions"}),(0,r.jsxs)(t.td,{children:["Natural language instructions for how to filter or transform the data using a Lambda function, such as ",(0,r.jsx)(t.code,{children:"Filter the data to only include items where the 'status' is 'active'."})]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sample_size"}),(0,r.jsx)(t.td,{children:"Sample Size"}),(0,r.jsx)(t.td,{children:"For large datasets, the number of characters to sample from the dataset head and tail."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"max_size"}),(0,r.jsx)(t.td,{children:"Max Size"}),(0,r.jsxs)(t.td,{children:['The number of characters for the data to be considered "large", which triggers sampling by the ',(0,r.jsx)(t.code,{children:"sample_size"})," value."]})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-6",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filtered_data"}),(0,r.jsx)(t.td,{children:"Filtered Data"}),(0,r.jsxs)(t.td,{children:["The filtered or transformed ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data object"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsxs)(t.td,{children:["The filtered data as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"}),"."]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"llm-router",children:"LLM router"}),"\n",(0,r.jsx)(t.p,{children:"This component routes requests to the most appropriate LLM based on OpenRouter model specifications."}),"\n",(0,r.jsx)(t.h3,{id:"inputs-7",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"models"}),(0,r.jsx)(t.td,{children:"Language Models"}),(0,r.jsx)(t.td,{children:"List of LLMs to route between"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_value"}),(0,r.jsx)(t.td,{children:"Input"}),(0,r.jsx)(t.td,{children:"The input message to be routed"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"judge_llm"}),(0,r.jsx)(t.td,{children:"Judge LLM"}),(0,r.jsx)(t.td,{children:"LLM that will evaluate and select the most appropriate model"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"optimization"}),(0,r.jsx)(t.td,{children:"Optimization"}),(0,r.jsx)(t.td,{children:"Optimization preference (quality/speed/cost/balanced)"})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-7",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output"}),(0,r.jsx)(t.td,{children:"Output"}),(0,r.jsx)(t.td,{children:"The response from the selected model"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"selected_model"}),(0,r.jsx)(t.td,{children:"Selected Model"}),(0,r.jsx)(t.td,{children:"Name of the chosen model"})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"message-to-data",children:"Message to data"}),"\n",(0,r.jsxs)(t.p,{children:["This component converts ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," objects to ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-8",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsxs)(t.td,{children:["The ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object to convert to a ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object."]})]})})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-8",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsxs)(t.td,{children:["The converted ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object."]})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"parser",children:"Parser"}),"\n",(0,r.jsxs)(t.p,{children:["This component formats ",(0,r.jsx)(t.code,{children:"DataFrame"})," or ",(0,r.jsx)(t.code,{children:"Data"})," objects into text using templates, with an option to convert inputs directly to strings using ",(0,r.jsx)(t.code,{children:"stringify"}),"."]}),"\n",(0,r.jsxs)(t.p,{children:["To use this component, create variables for values in the ",(0,r.jsx)(t.code,{children:"template"})," the same way you would in a ",(0,r.jsx)(t.a,{href:"/components-prompts",children:"Prompt"})," component. For ",(0,r.jsx)(t.code,{children:"DataFrames"}),", use column names, for example ",(0,r.jsx)(t.code,{children:"Name: {Name}"}),". For ",(0,r.jsx)(t.code,{children:"Data"})," objects, use ",(0,r.jsx)(t.code,{children:"{text}"}),"."]}),"\n",(0,r.jsxs)(t.p,{children:["To use the ",(0,r.jsx)(t.strong,{children:"Parser"})," component with a ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, do the following:"]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output to the ",(0,r.jsx)(t.strong,{children:"Parser"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," input."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"File"})," component to the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.strong,{children:"Message"})," input."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"OpenAI"})," model component's ",(0,r.jsx)(t.strong,{children:"Language Model"})," output to the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.strong,{children:"Language Model"})," input."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:"The flow looks like this:"}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"A parser component connected to OpenAI and structured output",src:n(96218).A+"",width:"2300",height:"1436"})}),"\n",(0,r.jsxs)(t.ol,{start:"4",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, click ",(0,r.jsx)(t.strong,{children:"Open Table"}),".\nThis opens a pane for structuring your table.\nThe table contains the rows ",(0,r.jsx)(t.strong,{children:"Name"}),", ",(0,r.jsx)(t.strong,{children:"Description"}),", ",(0,r.jsx)(t.strong,{children:"Type"}),", and ",(0,r.jsx)(t.strong,{children:"Multiple"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Create a table that maps to the data you're loading from the ",(0,r.jsx)(t.strong,{children:"File"})," loader.\nFor example, to create a table for employees, you might have the rows ",(0,r.jsx)(t.code,{children:"id"}),", ",(0,r.jsx)(t.code,{children:"name"}),", and ",(0,r.jsx)(t.code,{children:"email"}),", all of type ",(0,r.jsx)(t.code,{children:"string"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Template"})," field of the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, enter a template for parsing the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's DataFrame output into structured text.\nCreate variables for values in the ",(0,r.jsx)(t.code,{children:"template"})," the same way you would in a ",(0,r.jsx)(t.a,{href:"/components-prompts",children:"Prompt"})," component.\nFor example, to present a table of employees in Markdown:"]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"# Employee Profile",props:{}}]},{tokens:[{content:"## Personal Information",props:{}}]},{tokens:[{content:"- **Name:** {name}",props:{}}]},{tokens:[{content:"- **ID:** {id}",props:{}}]},{tokens:[{content:"- **Email:** {email}",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["To run the flow, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(a.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To view your parsed text, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(a.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Optionally, connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component, and open the ",(0,r.jsx)(t.strong,{children:"Playground"})," to see the output."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["For an additional example of using the ",(0,r.jsx)(t.strong,{children:"Parser"})," component to format a DataFrame from a ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, see the ",(0,r.jsx)(t.strong,{children:"Market Research"})," template flow."]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-9",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"mode"}),(0,r.jsx)(t.td,{children:"Mode"}),(0,r.jsx)(t.td,{children:'Tab selection between "Parser" and "Stringify" modes. "Stringify" converts input to a string instead of using a template.'})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"pattern"}),(0,r.jsx)(t.td,{children:"Template"}),(0,r.jsxs)(t.td,{children:["Template for formatting using variables in curly brackets. For DataFrames, use column names, such as ",(0,r.jsx)(t.code,{children:"Name: {Name}"}),". For Data objects, use ",(0,r.jsx)(t.code,{children:"{text}"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_data"}),(0,r.jsx)(t.td,{children:"Data or DataFrame"}),(0,r.jsx)(t.td,{children:"The input to parse - accepts either a DataFrame or Data object."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sep"}),(0,r.jsx)(t.td,{children:"Separator"}),(0,r.jsx)(t.td,{children:"String used to separate rows/items. Default: newline."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"clean_data"}),(0,r.jsx)(t.td,{children:"Clean Data"}),(0,r.jsx)(t.td,{children:"When stringify is enabled, cleans data by removing empty rows and lines."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-9",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"parsed_text"}),(0,r.jsx)(t.td,{children:"Parsed Text"}),(0,r.jsxs)(t.td,{children:["The resulting formatted text as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object."]})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"split-text",children:"Split text"}),"\n",(0,r.jsx)(t.p,{children:"This component splits text into chunks based on specified criteria. It's ideal for chunking data to be tokenized and embedded into vector databases."}),"\n",(0,r.jsxs)(t.p,{children:["The ",(0,r.jsx)(t.strong,{children:"Split Text"})," component outputs ",(0,r.jsx)(t.strong,{children:"Chunks"})," or ",(0,r.jsx)(t.strong,{children:"DataFrame"}),".\nThe ",(0,r.jsx)(t.strong,{children:"Chunks"})," output returns a list of individual text chunks.\nThe ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output returns a structured data format, with additional ",(0,r.jsx)(t.code,{children:"text"})," and ",(0,r.jsx)(t.code,{children:"metadata"})," columns applied."]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect a component that outputs ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data or DataFrame"})," to the ",(0,r.jsx)(t.strong,{children:"Split Text"})," component's ",(0,r.jsx)(t.strong,{children:"Data"})," port.\nThis example uses the ",(0,r.jsx)(t.strong,{children:"URL"})," component, which is fetching JSON placeholder data."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Split text component and chroma-db",src:n(49823).A+"",width:"2198",height:"1626"})}),"\n",(0,r.jsxs)(t.ol,{start:"2",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Split Text"})," component, define your data splitting parameters."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["This example splits incoming JSON data at the separator ",(0,r.jsx)(t.code,{children:"},"}),", so each chunk contains one JSON object."]}),"\n",(0,r.jsxs)(t.p,{children:["The order of precedence is ",(0,r.jsx)(t.strong,{children:"Separator"}),", then ",(0,r.jsx)(t.strong,{children:"Chunk Size"}),", and then ",(0,r.jsx)(t.strong,{children:"Chunk Overlap"}),".\nIf any segment after separator splitting is longer than ",(0,r.jsx)(t.code,{children:"chunk_size"}),", it is split again to fit within ",(0,r.jsx)(t.code,{children:"chunk_size"}),"."]}),"\n",(0,r.jsxs)(t.p,{children:["After ",(0,r.jsx)(t.code,{children:"chunk_size"}),", ",(0,r.jsx)(t.strong,{children:"Chunk Overlap"})," is applied between chunks to maintain context."]}),"\n",(0,r.jsxs)(t.ol,{start:"3",children:["\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to the ",(0,r.jsx)(t.strong,{children:"Split Text"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output to view its output."]}),"\n",(0,r.jsxs)(t.li,{children:["Click ",(0,r.jsx)(t.strong,{children:"Playground"}),", and then click ",(0,r.jsx)(t.strong,{children:"Run Flow"}),".\nThe output contains a table of JSON objects split at ",(0,r.jsx)(t.code,{children:"},"}),"."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"{",props:{}}]},{tokens:[{content:'"userId": 1,',props:{}}]},{tokens:[{content:'"id": 1,',props:{}}]},{tokens:[{content:'"title": "Introduction to Artificial Intelligence",',props:{}}]},{tokens:[{content:'"body": "Learn the basics of Artificial Intelligence and its applications in various industries.",',props:{}}]},{tokens:[{content:'"link": "https://example.com/article1",',props:{}}]},{tokens:[{content:'"comment_count": 8',props:{}}]},{tokens:[{content:"},",props:{}}]},{tokens:[{content:"{",props:{}}]},{tokens:[{content:'"userId": 2,',props:{}}]},{tokens:[{content:'"id": 2,',props:{}}]},{tokens:[{content:'"title": "Web Development with React",',props:{}}]},{tokens:[{content:'"body": "Build modern web applications using React.js and explore its powerful features.",',props:{}}]},{tokens:[{content:'"link": "https://example.com/article2",',props:{}}]},{tokens:[{content:'"comment_count": 12',props:{}}]},{tokens:[{content:"},",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsxs)(t.li,{children:["Clear the ",(0,r.jsx)(t.strong,{children:"Separator"})," field, and then run the flow again.\nInstead 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This example connects a ",(0,r.jsx)(t.strong,{children:"Groq"})," model component."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Groq"})," model component, add your ",(0,r.jsx)(t.strong,{children:"Groq"})," API key."]}),"\n",(0,r.jsxs)(t.li,{children:["To filter the data, in the ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component, in the ",(0,r.jsx)(t.strong,{children:"Instructions"})," field, use natural language to describe how the data should be filtered.\nFor this example, enter:"]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"I want to explode the result column out into a Data object",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.admonition,{type:"tip",children:(0,r.jsxs)(t.p,{children:["Avoid punctuation in the ",(0,r.jsx)(t.strong,{children:"Instructions"})," field, as it can cause errors."]})}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsxs)(t.li,{children:["To run the flow, in the ",(0,r.jsx)(t.strong,{children:"Lambda Filter"})," component, click ",(0,r.jsx)(o.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To inspect the filtered data, in the ",(0,r.jsx)(t.strong,{children:"Lambda Filter"})," component, click ",(0,r.jsx)(o.A,{name:"TextSearch","aria-label":"Inspect icon"}),".\nThe result is a structured DataFrame."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"id | name | company | username | email | address | zip",props:{}}]},{tokens:[{content:"---|------------------|----------------------|-----------------|------------------------------------|-------------------|-------",props:{}}]},{tokens:[{content:"1 | Emily Johnson | ABC Corporation | emily_johnson | emily.johnson@abccorporation.com | 123 Main St | 12345",props:{}}]},{tokens:[{content:"2 | Michael Williams | XYZ Corp | michael_williams| michael.williams@xyzcorp.com | 456 Elm Ave | 67890",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["Add the ",(0,r.jsx)(t.strong,{children:"DataFrame Operations"})," component, and a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to the flow."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"DataFrame Operations"})," component, in the ",(0,r.jsx)(t.strong,{children:"Operation"})," field, select ",(0,r.jsx)(t.strong,{children:"Filter"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To apply a filter, in the ",(0,r.jsx)(t.strong,{children:"Column Name"})," field, enter a column to filter on. This example filters by ",(0,r.jsx)(t.code,{children:"name"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Click ",(0,r.jsx)(t.strong,{children:"Playground"}),", and then click ",(0,r.jsx)(t.strong,{children:"Run Flow"}),".\nThe flow extracts the values from the ",(0,r.jsx)(t.code,{children:"name"})," column."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"name",props:{}}]},{tokens:[{content:"Emily Johnson",props:{}}]},{tokens:[{content:"Michael Williams",props:{}}]},{tokens:[{content:"John Smith",props:{}}]},{tokens:[{content:"...",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"operations",children:"Operations"}),"\n",(0,r.jsxs)(t.p,{children:["This component can perform the following operations on Pandas ",(0,r.jsx)(t.a,{href:"https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html",children:"DataFrame"}),"."]}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Operation"}),(0,r.jsx)(t.th,{children:"Description"}),(0,r.jsx)(t.th,{children:"Required Inputs"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Add Column"}),(0,r.jsx)(t.td,{children:"Adds a new column with a constant value"}),(0,r.jsx)(t.td,{children:"new_column_name, new_column_value"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Drop Column"}),(0,r.jsx)(t.td,{children:"Removes a specified column"}),(0,r.jsx)(t.td,{children:"column_name"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Filter"}),(0,r.jsx)(t.td,{children:"Filters rows based on column value"}),(0,r.jsx)(t.td,{children:"column_name, filter_value"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Head"}),(0,r.jsx)(t.td,{children:"Returns first n rows"}),(0,r.jsx)(t.td,{children:"num_rows"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Rename Column"}),(0,r.jsx)(t.td,{children:"Renames an existing column"}),(0,r.jsx)(t.td,{children:"column_name, new_column_name"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Replace Value"}),(0,r.jsx)(t.td,{children:"Replaces values in a column"}),(0,r.jsx)(t.td,{children:"column_name, replace_value, replacement_value"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Select Columns"}),(0,r.jsx)(t.td,{children:"Selects specific columns"}),(0,r.jsx)(t.td,{children:"columns_to_select"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Sort"}),(0,r.jsx)(t.td,{children:"Sorts DataFrame by column"}),(0,r.jsx)(t.td,{children:"column_name, ascending"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"Tail"}),(0,r.jsx)(t.td,{children:"Returns last n rows"}),(0,r.jsx)(t.td,{children:"num_rows"})]})]})]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"df"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"The input DataFrame to operate on."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"operation"}),(0,r.jsx)(t.td,{children:"Operation"}),(0,r.jsx)(t.td,{children:"The DataFrame operation to perform. Options include Add Column, Drop Column, Filter, Head, Rename Column, Replace Value, Select Columns, Sort, and Tail."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"column_name"}),(0,r.jsx)(t.td,{children:"Column Name"}),(0,r.jsx)(t.td,{children:"The column name to use for the operation."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_value"}),(0,r.jsx)(t.td,{children:"Filter Value"}),(0,r.jsx)(t.td,{children:"The value to filter rows by."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"ascending"}),(0,r.jsx)(t.td,{children:"Sort Ascending"}),(0,r.jsx)(t.td,{children:"Whether to sort in ascending order."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"new_column_name"}),(0,r.jsx)(t.td,{children:"New Column Name"}),(0,r.jsx)(t.td,{children:"The new column name when renaming or adding a column."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"new_column_value"}),(0,r.jsx)(t.td,{children:"New Column Value"}),(0,r.jsx)(t.td,{children:"The value to populate the new column with."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"columns_to_select"}),(0,r.jsx)(t.td,{children:"Columns to Select"}),(0,r.jsx)(t.td,{children:"A list of column names to select."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"num_rows"}),(0,r.jsx)(t.td,{children:"Number of Rows"}),(0,r.jsx)(t.td,{children:"The number of rows to return for head/tail operations. The default is 5."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"replace_value"}),(0,r.jsx)(t.td,{children:"Value to Replace"}),(0,r.jsx)(t.td,{children:"The value to replace in the column."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"replacement_value"}),(0,r.jsx)(t.td,{children:"Replacement Value"}),(0,r.jsx)(t.td,{children:"The value to replace with."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"The resulting DataFrame after the operation."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"data-to-dataframe",children:"Data to DataFrame"}),"\n",(0,r.jsxs)(t.p,{children:["This component converts one or multiple ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects into a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"}),". Each Data object corresponds to one row in the resulting DataFrame. Fields from the ",(0,r.jsx)(t.code,{children:".data"})," attribute become columns, and the ",(0,r.jsx)(t.code,{children:".text"})," field (if present) is placed in a 'text' column."]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect a component that outputs ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," to the ",(0,r.jsx)(t.strong,{children:"Data to Dataframe"})," component's input.\nThis example connects a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component to convert ",(0,r.jsx)(t.code,{children:"text"})," and ",(0,r.jsx)(t.code,{children:"data"})," into a DataFrame."]}),"\n",(0,r.jsxs)(t.li,{children:["To view the flow's output, connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to the ",(0,r.jsx)(t.strong,{children:"Data to Dataframe"})," component."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"A webhook and data to dataframe",src:n(45709).A+"",width:"1221",height:"468"})}),"\n",(0,r.jsxs)(t.ol,{start:"3",children:["\n",(0,r.jsxs)(t.li,{children:["Send a POST request to the ",(0,r.jsx)(t.strong,{children:"Webhook"})," containing your JSON data.\nReplace ",(0,r.jsx)(t.code,{children:"YOUR_FLOW_ID"})," with your flow ID.\nThis example uses the default Langflow server address."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:'curl -X POST "http://127.0.0.1:7860/api/v1/webhook/YOUR_FLOW_ID" \\',props:{}}]},{tokens:[{content:"-H 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:"-d '{",props:{}}]},{tokens:[{content:' "text": "Alex Cruz - Employee Profile",',props:{}}]},{tokens:[{content:' "data": {',props:{}}]},{tokens:[{content:' "Name": "Alex Cruz",',props:{}}]},{tokens:[{content:' "Role": "Developer",',props:{}}]},{tokens:[{content:' "Department": "Engineering"',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"4",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Playground"}),", view the output of your flow.\nThe ",(0,r.jsx)(t.strong,{children:"Data to DataFrame"})," component converts the webhook request into a ",(0,r.jsx)(t.code,{children:"DataFrame"}),", with ",(0,r.jsx)(t.code,{children:"text"})," and ",(0,r.jsx)(t.code,{children:"data"})," fields as columns."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"| text | data |",props:{}}]},{tokens:[{content:"|:-----------------------------|:------------------------------------------------------------------------|",props:{}}]},{tokens:[{content:"| Alex Cruz - Employee Profile | {'Name': 'Alex Cruz', 'Role': 'Developer', 'Department': 'Engineering'} |",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsx)(t.li,{children:"Send another employee data object."}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:'curl -X POST "http://127.0.0.1:7860/api/v1/webhook/YOUR_FLOW_ID" \\',props:{}}]},{tokens:[{content:"-H 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:"-d '{",props:{}}]},{tokens:[{content:' "text": "Kalani Smith - Employee Profile",',props:{}}]},{tokens:[{content:' "data": {',props:{}}]},{tokens:[{content:' "Name": "Kalani Smith",',props:{}}]},{tokens:[{content:' "Role": "Designer",',props:{}}]},{tokens:[{content:' "Department": "Design"',props:{}}]},{tokens:[{content:" }",props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"6",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Playground"}),", this request is also converted to ",(0,r.jsx)(t.code,{children:"DataFrame"}),"."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"| text | data |",props:{}}]},{tokens:[{content:"|:--------------------------------|:---------------------------------------------------------------------|",props:{}}]},{tokens:[{content:"| Kalani Smith - Employee Profile | {'Name': 'Kalani Smith', 'Role': 'Designer', 'Department': 'Design'} |",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display 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",(0,r.jsx)(t.strong,{children:"Beta"})," as of Langflow version 1.1.3, and is not yet fully supported."]})}),"\n",(0,r.jsxs)(t.p,{children:["This component filters a ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object based on a list of keys."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The Data object to filter."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_criteria"}),(0,r.jsx)(t.td,{children:"Filter Criteria"}),(0,r.jsx)(t.td,{children:"A list of keys to filter by."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filtered_data"}),(0,r.jsx)(t.td,{children:"Filtered Data"}),(0,r.jsx)(t.td,{children:"A new Data object containing only the key-value pairs that match the filter criteria."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"filter-values",children:"Filter values"}),"\n",(0,r.jsx)(t.admonition,{type:"important",children:(0,r.jsxs)(t.p,{children:["This component is in ",(0,r.jsx)(t.strong,{children:"Beta"})," as of Langflow version 1.1.3, and is not yet fully supported."]})}),"\n",(0,r.jsx)(t.p,{children:"The Filter values component filters a list of data items based on a specified key, filter value, and comparison operator."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_data"}),(0,r.jsx)(t.td,{children:"Input data"}),(0,r.jsx)(t.td,{children:"The list of data items to filter."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_key"}),(0,r.jsx)(t.td,{children:"Filter Key"}),(0,r.jsx)(t.td,{children:"The key to filter on."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_value"}),(0,r.jsx)(t.td,{children:"Filter Value"}),(0,r.jsx)(t.td,{children:"The value to filter by."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"operator"}),(0,r.jsx)(t.td,{children:"Comparison Operator"}),(0,r.jsx)(t.td,{children:"The operator to apply for comparing the values."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filtered_data"}),(0,r.jsx)(t.td,{children:"Filtered data"}),(0,r.jsx)(t.td,{children:"The resulting list of filtered data items."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"lambda-filter",children:"Lambda filter"}),"\n",(0,r.jsx)(t.p,{children:"This component uses an LLM to generate a Lambda function for filtering or transforming structured data."}),"\n",(0,r.jsxs)(t.p,{children:["To use the ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component, you must connect it to a ",(0,r.jsx)(t.a,{href:"/components-models#language-model",children:"Language Model"})," component, which the component uses to generate a function based on the natural language instructions in the ",(0,r.jsx)(t.strong,{children:"Instructions"})," field."]}),"\n",(0,r.jsxs)(t.p,{children:["This example gets JSON data from the ",(0,r.jsx)(t.code,{children:"https://jsonplaceholder.typicode.com/users"})," API endpoint.\nThe ",(0,r.jsx)(t.strong,{children:"Instructions"})," field in the ",(0,r.jsx)(t.strong,{children:"Lambda filter"})," component specifies the task ",(0,r.jsx)(t.code,{children:"extract emails"}),".\nThe connected LLM creates a filter based on the instructions, and successfully extracts a list of email addresses from the JSON data."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{src:n(66539).A+"",width:"1742",height:"1622"})}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The structured data to filter or transform using a Lambda function."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"llm"}),(0,r.jsx)(t.td,{children:"Language Model"}),(0,r.jsxs)(t.td,{children:["The connection port for a ",(0,r.jsx)(t.a,{href:"/components-models",children:"Model"})," component."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filter_instruction"}),(0,r.jsx)(t.td,{children:"Instructions"}),(0,r.jsxs)(t.td,{children:["The natural language instructions for how to filter or transform the data using a Lambda function, such as ",(0,r.jsx)(t.code,{children:"Filter the data to only include items where the 'status' is 'active'"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sample_size"}),(0,r.jsx)(t.td,{children:"Sample Size"}),(0,r.jsx)(t.td,{children:"For large datasets, the number of characters to sample from the dataset head and tail."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"max_size"}),(0,r.jsx)(t.td,{children:"Max Size"}),(0,r.jsxs)(t.td,{children:['The number of characters for the data to be considered "large", which triggers sampling by the ',(0,r.jsx)(t.code,{children:"sample_size"})," value."]})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"filtered_data"}),(0,r.jsx)(t.td,{children:"Filtered Data"}),(0,r.jsxs)(t.td,{children:["The filtered or transformed ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data object"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsxs)(t.td,{children:["The filtered data as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"}),"."]})]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"llm-router",children:"LLM router"}),"\n",(0,r.jsx)(t.p,{children:"This component routes requests to the most appropriate LLM based on OpenRouter model specifications."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"models"}),(0,r.jsx)(t.td,{children:"Language Models"}),(0,r.jsx)(t.td,{children:"A list of LLMs to route between."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_value"}),(0,r.jsx)(t.td,{children:"Input"}),(0,r.jsx)(t.td,{children:"The input message to be routed."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"judge_llm"}),(0,r.jsx)(t.td,{children:"Judge LLM"}),(0,r.jsx)(t.td,{children:"The LLM that evaluates and selects the most appropriate model."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"optimization"}),(0,r.jsx)(t.td,{children:"Optimization"}),(0,r.jsx)(t.td,{children:"The optimization preference between quality, speed, cost, or balanced."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output"}),(0,r.jsx)(t.td,{children:"Output"}),(0,r.jsx)(t.td,{children:"The response from the selected model."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"selected_model"}),(0,r.jsx)(t.td,{children:"Selected Model"}),(0,r.jsx)(t.td,{children:"The name of the chosen model."})]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"message-to-data",children:"Message to data"}),"\n",(0,r.jsxs)(t.p,{children:["This component converts ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," objects to ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsx)(t.td,{children:"The Message object to convert to a Data object."})]})})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The converted Data object."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"parser",children:"Parser"}),"\n",(0,r.jsxs)(t.p,{children:["This component formats ",(0,r.jsx)(t.code,{children:"DataFrame"})," or ",(0,r.jsx)(t.code,{children:"Data"})," objects into text using templates, with an option to convert inputs directly to strings using ",(0,r.jsx)(t.code,{children:"stringify"}),"."]}),"\n",(0,r.jsxs)(t.p,{children:["To use this component, create variables for values in the ",(0,r.jsx)(t.code,{children:"template"})," the same way you would in a ",(0,r.jsx)(t.a,{href:"/components-prompts",children:"Prompt"})," component. For ",(0,r.jsx)(t.code,{children:"DataFrames"}),", use column names, for example ",(0,r.jsx)(t.code,{children:"Name: {Name}"}),". For ",(0,r.jsx)(t.code,{children:"Data"})," objects, use ",(0,r.jsx)(t.code,{children:"{text}"}),"."]}),"\n",(0,r.jsxs)(t.p,{children:["To use the ",(0,r.jsx)(t.strong,{children:"Parser"})," component with a ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, do the following:"]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output to the ",(0,r.jsx)(t.strong,{children:"Parser"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," input."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"File"})," component to the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.strong,{children:"Message"})," input."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"OpenAI"})," model component's ",(0,r.jsx)(t.strong,{children:"Language Model"})," output to the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.strong,{children:"Language Model"})," input."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:"The flow looks like this:"}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"A parser component connected to OpenAI and structured output",src:n(96218).A+"",width:"2300",height:"1436"})}),"\n",(0,r.jsxs)(t.ol,{start:"4",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, click ",(0,r.jsx)(t.strong,{children:"Open Table"}),".\nThis opens a pane for structuring your table.\nThe table contains the rows ",(0,r.jsx)(t.strong,{children:"Name"}),", ",(0,r.jsx)(t.strong,{children:"Description"}),", ",(0,r.jsx)(t.strong,{children:"Type"}),", and ",(0,r.jsx)(t.strong,{children:"Multiple"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Create a table that maps to the data you're loading from the ",(0,r.jsx)(t.strong,{children:"File"})," loader.\nFor example, to create a table for employees, you might have the rows ",(0,r.jsx)(t.code,{children:"id"}),", ",(0,r.jsx)(t.code,{children:"name"}),", and ",(0,r.jsx)(t.code,{children:"email"}),", all of type ",(0,r.jsx)(t.code,{children:"string"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Template"})," field of the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, enter a template for parsing the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's DataFrame output into structured text.\nCreate variables for values in the ",(0,r.jsx)(t.code,{children:"template"})," the same way you would in a ",(0,r.jsx)(t.a,{href:"/components-prompts",children:"Prompt"})," component.\nFor example, to present a table of employees in Markdown:"]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"# Employee Profile",props:{}}]},{tokens:[{content:"## Personal Information",props:{}}]},{tokens:[{content:"- **Name:** {name}",props:{}}]},{tokens:[{content:"- **ID:** {id}",props:{}}]},{tokens:[{content:"- **Email:** {email}",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["To run the flow, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(o.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To view your parsed text, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(o.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Optionally, connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component, and open the ",(0,r.jsx)(t.strong,{children:"Playground"})," to see the output."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["For an additional example of using the ",(0,r.jsx)(t.strong,{children:"Parser"})," component to format a DataFrame from a ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, see the ",(0,r.jsx)(t.strong,{children:"Market Research"})," template flow."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"mode"}),(0,r.jsx)(t.td,{children:"Mode"}),(0,r.jsx)(t.td,{children:'The tab selection between "Parser" and "Stringify" modes. "Stringify" converts input to a string instead of using a template.'})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"pattern"}),(0,r.jsx)(t.td,{children:"Template"}),(0,r.jsxs)(t.td,{children:["The template for formatting using variables in curly brackets. For DataFrames, use column names, such as ",(0,r.jsx)(t.code,{children:"Name: {Name}"}),". For Data objects, use ",(0,r.jsx)(t.code,{children:"{text}"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_data"}),(0,r.jsx)(t.td,{children:"Data or DataFrame"}),(0,r.jsx)(t.td,{children:"The input to parse. Accepts either a DataFrame or Data object."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sep"}),(0,r.jsx)(t.td,{children:"Separator"}),(0,r.jsx)(t.td,{children:"The string used to separate rows or items. The default is a newline."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"clean_data"}),(0,r.jsx)(t.td,{children:"Clean Data"}),(0,r.jsx)(t.td,{children:"When stringify is enabled, this option cleans data by removing empty rows and lines."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"parsed_text"}),(0,r.jsx)(t.td,{children:"Parsed Text"}),(0,r.jsxs)(t.td,{children:["The resulting formatted text as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object."]})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"regex-extractor",children:"Regex extractor"}),"\n",(0,r.jsx)(t.p,{children:"This component extracts patterns from text using regular expressions. It can be used to find and extract specific patterns or information from text data."}),"\n",(0,r.jsx)(t.p,{children:"To use this component in a flow:"}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," to a ",(0,r.jsx)(t.strong,{children:"URL"})," component and a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Regex extractor connected to url component",src:n(8886).A+"",width:"1606",height:"848"})}),"\n",(0,r.jsxs)(t.ol,{start:"2",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," tool, enter a pattern to extract text from the ",(0,r.jsx)(t.strong,{children:"URL"}),' component\'s raw output.\nThis example extracts the first paragraph from the "In the News" section of ',(0,r.jsx)(t.code,{children:"https://en.wikipedia.org/wiki/Main_Page"}),":"]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"In the news\\s*\\n(.*?)(?=\\n\\n)",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.p,{children:"Result:"}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Peruvian writer and Nobel Prize in Literature laureate Mario Vargas Llosa (pictured) dies at the age of 89.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h2,{id:"save-to-file",children:"Save to File"}),"\n",(0,r.jsxs)(t.p,{children:["This component saves ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"DataFrames, Data, or Messages"})," to various file formats."]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect a component that outputs ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"DataFrames, Data, or Messages"})," to the ",(0,r.jsx)(t.strong,{children:"Save to File"})," component's input.\nThe following example connects a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component to two ",(0,r.jsx)(t.strong,{children:"Save to File"})," components to demonstrate the different outputs."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Two Save-to File components connected to a webhook",src:n(35073).A+"",width:"1458",height:"1732"})}),"\n",(0,r.jsxs)(t.ol,{start:"2",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Save to File"})," component's ",(0,r.jsx)(t.strong,{children:"Input Type"})," field, select the expected input type.\nThis example expects ",(0,r.jsx)(t.strong,{children:"Data"})," from the ",(0,r.jsx)(t.strong,{children:"Webhook"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"File Format"})," field, select the file type for your saved file.\nThis example uses ",(0,r.jsx)(t.code,{children:".md"})," in one ",(0,r.jsx)(t.strong,{children:"Save to File"})," component, and ",(0,r.jsx)(t.code,{children:".xlsx"})," in another."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"File Path"})," field, enter the path for your saved file.\nThis example uses ",(0,r.jsx)(t.code,{children:"./output/employees.xlsx"})," and ",(0,r.jsx)(t.code,{children:"./output/employees.md"})," to save the files in a directory relative to where Langflow is running.\nThe component accepts both relative and absolute paths, and creates any necessary directories if they don't exist."]}),"\n"]}),"\n",(0,r.jsx)(t.admonition,{type:"tip",children:(0,r.jsxs)(t.p,{children:["If you enter a format in the ",(0,r.jsx)(t.code,{children:"file_path"})," that is not accepted, the component appends the proper format to the file.\nFor example, if the selected ",(0,r.jsx)(t.code,{children:"file_format"})," is ",(0,r.jsx)(t.code,{children:"csv"}),", and you enter ",(0,r.jsx)(t.code,{children:"file_path"})," as ",(0,r.jsx)(t.code,{children:"./output/test.txt"}),", the file is saved as ",(0,r.jsx)(t.code,{children:"./output/test.txt.csv"})," so the file is not corrupted."]})}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsxs)(t.li,{children:["Send a POST request to the ",(0,r.jsx)(t.strong,{children:"Webhook"})," containing your JSON data.\nReplace ",(0,r.jsx)(t.code,{children:"YOUR_FLOW_ID"})," with your flow ID.\nThis example uses the default Langflow server address."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:'curl -X POST "http://127.0.0.1:7860/api/v1/webhook/YOUR_FLOW_ID" \\',props:{}}]},{tokens:[{content:"-H 'Content-Type: application/json' \\",props:{}}]},{tokens:[{content:"-d '{",props:{}}]},{tokens:[{content:' "Name": ["Alex Cruz", "Kalani Smith", "Noam Johnson"],',props:{}}]},{tokens:[{content:' "Role": ["Developer", "Designer", "Manager"],',props:{}}]},{tokens:[{content:' "Department": ["Engineering", "Design", "Management"]',props:{}}]},{tokens:[{content:"}'",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"6",children:["\n",(0,r.jsxs)(t.li,{children:["In your local filesystem, open the ",(0,r.jsx)(t.code,{children:"outputs"})," directory.\nYou should see two files created from the data you've sent: one in ",(0,r.jsx)(t.code,{children:".xlsx"})," for structured spreadsheets, and one in Markdown."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"| Name | Role | Department |",props:{}}]},{tokens:[{content:"|:-------------|:----------|:-------------|",props:{}}]},{tokens:[{content:"| Alex Cruz | Developer | Engineering |",props:{}}]},{tokens:[{content:"| Kalani Smith | Designer | Design |",props:{}}]},{tokens:[{content:"| Noam Johnson | Manager | Management |",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"file-input-format-options",children:"File input format options"}),"\n",(0,r.jsxs)(t.p,{children:["For ",(0,r.jsx)(t.code,{children:"DataFrame"})," and ",(0,r.jsx)(t.code,{children:"Data"})," inputs, the component can create:"]}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"csv"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"excel"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"json"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"markdown"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"pdf"})}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["For ",(0,r.jsx)(t.code,{children:"Message"})," inputs, the component can create:"]}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"txt"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"json"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"markdown"})}),"\n",(0,r.jsx)(t.li,{children:(0,r.jsx)(t.code,{children:"pdf"})}),"\n"]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_text"}),(0,r.jsx)(t.td,{children:"Input Text"}),(0,r.jsx)(t.td,{children:"The text to analyze and extract patterns from."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"pattern"}),(0,r.jsx)(t.td,{children:"Regex Pattern"}),(0,r.jsx)(t.td,{children:"The regular expression pattern to match in the text."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_type"}),(0,r.jsx)(t.td,{children:"Input Type"}),(0,r.jsx)(t.td,{children:"The type of input to save."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"df"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"The DataFrame to save."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The Data object to save."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsx)(t.td,{children:"The Message to save."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"file_format"}),(0,r.jsx)(t.td,{children:"File Format"}),(0,r.jsx)(t.td,{children:"The file format to save the input in."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"file_path"}),(0,r.jsx)(t.td,{children:"File Path"}),(0,r.jsx)(t.td,{children:"The full file path including filename and extension."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"A list of extracted matches as Data objects."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsx)(t.td,{children:"The extracted matches formatted as a Message object."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"confirmation"}),(0,r.jsx)(t.td,{children:"Confirmation"}),(0,r.jsx)(t.td,{children:"The confirmation message after saving the file."})]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"split-text",children:"Split text"}),"\n",(0,r.jsx)(t.p,{children:"This component splits text into chunks based on specified criteria. It's ideal for chunking data to be tokenized and embedded into vector databases."}),"\n",(0,r.jsxs)(t.p,{children:["The ",(0,r.jsx)(t.strong,{children:"Split Text"})," component outputs ",(0,r.jsx)(t.strong,{children:"Chunks"})," or ",(0,r.jsx)(t.strong,{children:"DataFrame"}),".\nThe ",(0,r.jsx)(t.strong,{children:"Chunks"})," output returns a list of individual text chunks.\nThe ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output returns a structured data format, with additional ",(0,r.jsx)(t.code,{children:"text"})," and ",(0,r.jsx)(t.code,{children:"metadata"})," columns applied."]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect a component that outputs ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data or DataFrame"})," to the ",(0,r.jsx)(t.strong,{children:"Split Text"})," component's ",(0,r.jsx)(t.strong,{children:"Data"})," port.\nThis example uses the ",(0,r.jsx)(t.strong,{children:"URL"})," component, which is fetching JSON placeholder data."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Split text component and chroma-db",src:n(49823).A+"",width:"2198",height:"1626"})}),"\n",(0,r.jsxs)(t.ol,{start:"2",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Split Text"})," component, define your data splitting parameters."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["This example splits incoming JSON data at the separator ",(0,r.jsx)(t.code,{children:"},"}),", so each chunk contains one JSON object."]}),"\n",(0,r.jsxs)(t.p,{children:["The order of precedence is ",(0,r.jsx)(t.strong,{children:"Separator"}),", then ",(0,r.jsx)(t.strong,{children:"Chunk Size"}),", and then ",(0,r.jsx)(t.strong,{children:"Chunk Overlap"}),".\nIf any segment after separator splitting is longer than ",(0,r.jsx)(t.code,{children:"chunk_size"}),", it is split again to fit within ",(0,r.jsx)(t.code,{children:"chunk_size"}),"."]}),"\n",(0,r.jsxs)(t.p,{children:["After ",(0,r.jsx)(t.code,{children:"chunk_size"}),", ",(0,r.jsx)(t.strong,{children:"Chunk Overlap"})," is applied between chunks to maintain context."]}),"\n",(0,r.jsxs)(t.ol,{start:"3",children:["\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to the ",(0,r.jsx)(t.strong,{children:"Split Text"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output to view its output."]}),"\n",(0,r.jsxs)(t.li,{children:["Click ",(0,r.jsx)(t.strong,{children:"Playground"}),", and then click ",(0,r.jsx)(t.strong,{children:"Run Flow"}),".\nThe output contains a table of JSON objects split at ",(0,r.jsx)(t.code,{children:"},"}),"."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"{",props:{}}]},{tokens:[{content:'"userId": 1,',props:{}}]},{tokens:[{content:'"id": 1,',props:{}}]},{tokens:[{content:'"title": "Introduction to Artificial Intelligence",',props:{}}]},{tokens:[{content:'"body": "Learn the basics of Artificial Intelligence and its applications in various industries.",',props:{}}]},{tokens:[{content:'"link": "https://example.com/article1",',props:{}}]},{tokens:[{content:'"comment_count": 8',props:{}}]},{tokens:[{content:"},",props:{}}]},{tokens:[{content:"{",props:{}}]},{tokens:[{content:'"userId": 2,',props:{}}]},{tokens:[{content:'"id": 2,',props:{}}]},{tokens:[{content:'"title": "Web Development with React",',props:{}}]},{tokens:[{content:'"body": "Build modern web applications using React.js and explore its powerful features.",',props:{}}]},{tokens:[{content:'"link": "https://example.com/article2",',props:{}}]},{tokens:[{content:'"comment_count": 12',props:{}}]},{tokens:[{content:"},",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"5",children:["\n",(0,r.jsxs)(t.li,{children:["Clear the ",(0,r.jsx)(t.strong,{children:"Separator"})," field, and then run the flow again.\nInstead of JSON objects, the output contains 50-character lines of text with 10 characters of overlap."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:'First chunk: "title": "Introduction to Artificial Intelligence""',props:{}}]},{tokens:[{content:'Second chunk: "elligence", "body": "Learn the basics of Artif"',props:{}}]},{tokens:[{content:'Third chunk: "s of Artificial Intelligence and its applications"',props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data_inputs"}),(0,r.jsx)(t.td,{children:"Input Documents"}),(0,r.jsxs)(t.td,{children:["The data to split. The component accepts ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," or ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," objects."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"chunk_overlap"}),(0,r.jsx)(t.td,{children:"Chunk Overlap"}),(0,r.jsxs)(t.td,{children:["The number of characters to overlap between chunks. Default: ",(0,r.jsx)(t.code,{children:"200"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"chunk_size"}),(0,r.jsx)(t.td,{children:"Chunk Size"}),(0,r.jsxs)(t.td,{children:["The maximum number of characters in each chunk. Default: ",(0,r.jsx)(t.code,{children:"1000"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"separator"}),(0,r.jsx)(t.td,{children:"Separator"}),(0,r.jsxs)(t.td,{children:["The character to split on. Default: ",(0,r.jsx)(t.code,{children:"newline"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_key"}),(0,r.jsx)(t.td,{children:"Text Key"}),(0,r.jsxs)(t.td,{children:["The key to use for the text column. Default: ",(0,r.jsx)(t.code,{children:"text"}),"."]})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"chunks"}),(0,r.jsx)(t.td,{children:"Chunks"}),(0,r.jsxs)(t.td,{children:["A list of split text chunks as ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsxs)(t.td,{children:["A list of split text chunks as ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," objects."]})]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"update-data",children:"Update data"}),"\n",(0,r.jsx)(t.p,{children:"This component dynamically updates or appends data with specified fields."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"old_data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The records to update."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"number_of_fields"}),(0,r.jsx)(t.td,{children:"Number of Fields"}),(0,r.jsx)(t.td,{children:"The number of fields to add. The maximum is 15."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_key"}),(0,r.jsx)(t.td,{children:"Text Key"}),(0,r.jsx)(t.td,{children:"The key for text content."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_key_validator"}),(0,r.jsx)(t.td,{children:"Text Key Validator"}),(0,r.jsx)(t.td,{children:"Validates the text key presence."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The updated Data objects."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"legacy-components",children:"Legacy components"}),"\n",(0,r.jsxs)(t.p,{children:[(0,r.jsx)(t.strong,{children:"Legacy"})," components are available for use but are no longer supported."]}),"\n",(0,r.jsx)(t.h3,{id:"alter-metadata",children:"Alter metadata"}),"\n",(0,r.jsxs)(t.p,{children:["This component modifies metadata of input objects. It can add new metadata, update existing metadata, and remove specified metadata fields. The component works with both ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," and ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects, and can also create a new Data object from user-provided text."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_value"}),(0,r.jsx)(t.td,{children:"Input"}),(0,r.jsx)(t.td,{children:"Objects to which Metadata should be added"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_in"}),(0,r.jsx)(t.td,{children:"User Text"}),(0,r.jsxs)(t.td,{children:["Text input; the value is contained in the 'text' attribute of the ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object. Empty text entries are ignored."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"metadata"}),(0,r.jsx)(t.td,{children:"Metadata"}),(0,r.jsx)(t.td,{children:"Metadata to add to each object"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"remove_fields"}),(0,r.jsx)(t.td,{children:"Fields to Remove"}),(0,r.jsx)(t.td,{children:"Metadata fields to remove"})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"List of Input objects, each with added metadata"})]})})]})]}),"\n",(0,r.jsx)(t.h3,{id:"create-data",children:"Create data"}),"\n",(0,r.jsx)(t.admonition,{type:"important",children:(0,r.jsxs)(t.p,{children:["This component is in ",(0,r.jsx)(t.strong,{children:"Legacy"}),", which means it is no longer in active development as of Langflow version 1.1.3."]})}),"\n",(0,r.jsxs)(t.p,{children:["This component dynamically creates a ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object with a specified number of fields."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"number_of_fields"}),(0,r.jsx)(t.td,{children:"Number of Fields"}),(0,r.jsx)(t.td,{children:"The number of fields to be added to the record."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_key"}),(0,r.jsx)(t.td,{children:"Text Key"}),(0,r.jsx)(t.td,{children:"Key that identifies the field to be used as the text content."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_key_validator"}),(0,r.jsx)(t.td,{children:"Text Key Validator"}),(0,r.jsxs)(t.td,{children:["If enabled, checks if the given ",(0,r.jsx)(t.code,{children:"Text Key"})," is present in the given ",(0,r.jsx)(t.code,{children:"Data"}),"."]})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsxs)(t.td,{children:["A ",(0,r.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," object created with the specified fields and text key."]})]})})]})]}),"\n",(0,r.jsx)(t.h3,{id:"json-cleaner",children:"JSON cleaner"}),"\n",(0,r.jsx)(t.p,{children:"The JSON cleaner component cleans JSON strings to ensure they are fully compliant with the JSON specification."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"json_str"}),(0,r.jsx)(t.td,{children:"JSON String"}),(0,r.jsx)(t.td,{children:"The JSON string to be cleaned. This can be a raw, potentially malformed JSON string produced by language models or other sources that may not fully comply with JSON specifications."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"remove_control_chars"}),(0,r.jsx)(t.td,{children:"Remove Control Characters"}),(0,r.jsx)(t.td,{children:"If set to True, this option removes control characters (ASCII characters 0-31 and 127) from the JSON string. This can help eliminate invisible characters that might cause parsing issues or make the JSON invalid."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"normalize_unicode"}),(0,r.jsx)(t.td,{children:"Normalize Unicode"}),(0,r.jsx)(t.td,{children:"When enabled, this option normalizes Unicode characters in the JSON string to their canonical composition form (NFC). 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",props:{style:{color:"#FF7B72"}}},{content:"build_text_splitter",props:{style:{color:"#D2A8FF"}}},{content:"(self) -> TextSplitter:",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" if not ",props:{style:{color:"#FF7B72"}}},{content:"self",props:{style:{color:"#79C0FF"}}},{content:".separators:",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" separators: list[",props:{style:{color:"#C9D1D9"}}},{content:"str",props:{style:{color:"#79C0FF"}}},{content:"] ",props:{style:{color:"#C9D1D9"}}},{content:"| ",props:{style:{color:"#FF7B72"}}},{content:"None ",props:{style:{color:"#79C0FF"}}},{content:"= ",props:{style:{color:"#FF7B72"}}},{content:"None",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:" else",props:{style:{color:"#FF7B72"}}},{content:":",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" # check if the separators list has escaped characters",props:{style:{color:"#8B949E"}}}]},{tokens:[{content:" # if there are escaped characters, unescape 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chunk_size",props:{style:{color:"#FFA657"}}},{content:"=",props:{style:{color:"#FF7B72"}}},{content:"self",props:{style:{color:"#79C0FF"}}},{content:".chunk_size,",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" chunk_overlap",props:{style:{color:"#FFA657"}}},{content:"=",props:{style:{color:"#FF7B72"}}},{content:"self",props:{style:{color:"#79C0FF"}}},{content:".chunk_overlap,",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:" )",props:{style:{color:"#C9D1D9"}}}]},{tokens:[{content:"",props:{style:{color:"#C9D1D9"}}}]}],lang:"python"},annotations:[]}]})]}),"\n",(0,s.jsx)(t.p,{children:"Components include definitions for inputs and outputs, which are represented in the UI with color-coded ports."}),"\n",(0,s.jsxs)(t.p,{children:[(0,s.jsx)(t.strong,{children:"Input Definition:"})," Each input (like ",(0,s.jsx)(t.code,{children:"IntInput"})," or ",(0,s.jsx)(t.code,{children:"DataInput"}),") specifies an input's type, name, and display properties, which appear as configurable fields in the component's UI panel."]}),"\n",(0,s.jsxs)(t.p,{children:[(0,s.jsx)(t.strong,{children:"Methods:"})," Components have methods or functions that handle their functionality. This component has two methods.\n",(0,s.jsx)(t.code,{children:"get_data_input"})," retrieves the text data to be split from the component's input. This makes the data available to the class.\n",(0,s.jsx)(t.code,{children:"build_text_splitter"})," creates a ",(0,s.jsx)(t.code,{children:"RecursiveCharacterTextSplitter"})," object by calling its parent class's ",(0,s.jsx)(t.code,{children:"build"})," method. The text is split with the created splitter and passed to the next component.\nWhen used in a flow, this component:"]}),"\n",(0,s.jsxs)(t.ol,{children:["\n",(0,s.jsx)(t.li,{children:"Displays its configuration options in the UI."}),"\n",(0,s.jsx)(t.li,{children:"Validates user inputs based on the input types."}),"\n",(0,s.jsx)(t.li,{children:"Processes data using the configured parameters."}),"\n",(0,s.jsx)(t.li,{children:"Passes results to the next component."}),"\n"]}),"\n",(0,s.jsx)(t.h2,{id:"freeze",children:"Freeze"}),"\n",(0,s.jsxs)(t.p,{children:["After a component runs, ",(0,s.jsx)(t.strong,{children:"Freeze"})," locks the component's previous output state to prevent it from re-running."]}),"\n",(0,s.jsxs)(t.p,{children:["If you\u2019re expecting consistent output from a component and don\u2019t need to re-run it, click ",(0,s.jsx)(t.strong,{children:"Freeze"}),"."]}),"\n",(0,s.jsxs)(t.p,{children:["Enabling ",(0,s.jsx)(t.strong,{children:"Freeze"})," freezes all components upstream of the selected component."]}),"\n",(0,s.jsx)(t.h2,{id:"additional-component-options",children:"Additional component options"}),"\n",(0,s.jsxs)(t.p,{children:["Click\xa0",(0,s.jsx)(l.A,{name:"Ellipsis","aria-label":"Horizontal ellipsis"})," ",(0,s.jsx)(t.strong,{children:"All"}),"\xa0to see additional options for a component."]}),"\n",(0,s.jsxs)(t.p,{children:["To modify a component's name or description, double-click in the ",(0,s.jsx)(t.strong,{children:"Name"})," or ",(0,s.jsx)(t.strong,{children:"Description"})," fields. Component descriptions accept Markdown syntax."]}),"\n",(0,s.jsx)(t.h3,{id:"component-shortcuts",children:"Component shortcuts"}),"\n",(0,s.jsx)(t.p,{children:"The following keyboard shortcuts are available when a component is selected."}),"\n",(0,s.jsxs)(t.table,{children:[(0,s.jsx)(t.thead,{children:(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.th,{children:"Menu item"}),(0,s.jsx)(t.th,{children:"Windows shortcut"}),(0,s.jsx)(t.th,{children:"Mac shortcut"}),(0,s.jsx)(t.th,{children:"Description"})]})}),(0,s.jsxs)(t.tbody,{children:[(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Code"}),(0,s.jsx)(t.td,{children:"Space"}),(0,s.jsx)(t.td,{children:"Space"}),(0,s.jsx)(t.td,{children:"Opens the code editor for the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Advanced Settings"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + A"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + A"}),(0,s.jsx)(t.td,{children:"Opens advanced settings for the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Save Changes"}),(0,s.jsx)(t.td,{children:"Ctrl + S"}),(0,s.jsx)(t.td,{children:"\u2318 + S"}),(0,s.jsx)(t.td,{children:"Saves changes to the current flow."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Save Component"}),(0,s.jsx)(t.td,{children:"Ctrl + Alt + S"}),(0,s.jsx)(t.td,{children:"\u2318 + Alt + S"}),(0,s.jsx)(t.td,{children:"Saves the current component to Saved components."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Duplicate"}),(0,s.jsx)(t.td,{children:"Ctrl + D"}),(0,s.jsx)(t.td,{children:"\u2318 + D"}),(0,s.jsx)(t.td,{children:"Creates a duplicate of the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Copy"}),(0,s.jsx)(t.td,{children:"Ctrl + C"}),(0,s.jsx)(t.td,{children:"\u2318 + C"}),(0,s.jsx)(t.td,{children:"Copies the selected component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Cut"}),(0,s.jsx)(t.td,{children:"Ctrl + X"}),(0,s.jsx)(t.td,{children:"\u2318 + X"}),(0,s.jsx)(t.td,{children:"Cuts the selected component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Paste"}),(0,s.jsx)(t.td,{children:"Ctrl + V"}),(0,s.jsx)(t.td,{children:"\u2318 + V"}),(0,s.jsx)(t.td,{children:"Pastes the copied/cut component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Docs"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + D"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + D"}),(0,s.jsx)(t.td,{children:"Opens related documentation."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Minimize"}),(0,s.jsx)(t.td,{children:"Ctrl + ."}),(0,s.jsx)(t.td,{children:"\u2318 + ."}),(0,s.jsx)(t.td,{children:"Minimizes the current component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Freeze"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + F"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + F"}),(0,s.jsx)(t.td,{children:"Freezes component state and upstream components."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Download"}),(0,s.jsx)(t.td,{children:"Ctrl + J"}),(0,s.jsx)(t.td,{children:"\u2318 + J"}),(0,s.jsx)(t.td,{children:"Downloads the component as JSON."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Delete"}),(0,s.jsx)(t.td,{children:"Backspace"}),(0,s.jsx)(t.td,{children:"Backspace"}),(0,s.jsx)(t.td,{children:"Deletes the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Group"}),(0,s.jsx)(t.td,{children:"Ctrl + G"}),(0,s.jsx)(t.td,{children:"\u2318 + G"}),(0,s.jsx)(t.td,{children:"Groups selected components."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Undo"}),(0,s.jsx)(t.td,{children:"Ctrl + Z"}),(0,s.jsx)(t.td,{children:"\u2318 + Z"}),(0,s.jsx)(t.td,{children:"Undoes the last action."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Redo"}),(0,s.jsx)(t.td,{children:"Ctrl + Y"}),(0,s.jsx)(t.td,{children:"\u2318 + Y"}),(0,s.jsx)(t.td,{children:"Redoes the last undone action."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Redo (alternative)"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + Z"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + Z"}),(0,s.jsx)(t.td,{children:"Alternative shortcut for redo."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Share Component"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + S"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + S"}),(0,s.jsx)(t.td,{children:"Shares the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Share Flow"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + B"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + B"}),(0,s.jsx)(t.td,{children:"Shares the entire flow."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Toggle Sidebar"}),(0,s.jsx)(t.td,{children:"Ctrl + B"}),(0,s.jsx)(t.td,{children:"\u2318 + B"}),(0,s.jsx)(t.td,{children:"Shows/hides the sidebar."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Search Components"}),(0,s.jsx)(t.td,{children:"/"}),(0,s.jsx)(t.td,{children:"/"}),(0,s.jsx)(t.td,{children:"Focuses the component search bar."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Tool Mode"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + M"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + M"}),(0,s.jsx)(t.td,{children:"Toggles tool mode."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Update"}),(0,s.jsx)(t.td,{children:"Ctrl + U"}),(0,s.jsx)(t.td,{children:"\u2318 + U"}),(0,s.jsx)(t.td,{children:"Updates the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Open Playground"}),(0,s.jsx)(t.td,{children:"Ctrl + K"}),(0,s.jsx)(t.td,{children:"\u2318 + K"}),(0,s.jsx)(t.td,{children:"Opens the playground."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Output Inspection"}),(0,s.jsx)(t.td,{children:"O"}),(0,s.jsx)(t.td,{children:"O"}),(0,s.jsx)(t.td,{children:"Opens output inspection."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Play"}),(0,s.jsx)(t.td,{children:"P"}),(0,s.jsx)(t.td,{children:"P"}),(0,s.jsx)(t.td,{children:"Plays/executes the flow."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"API"}),(0,s.jsx)(t.td,{children:"R"}),(0,s.jsx)(t.td,{children:"R"}),(0,s.jsx)(t.td,{children:"Opens the API view."})]})]})]}),"\n",(0,s.jsx)(t.h2,{id:"group-components-in-the-workspace",children:"Group components in the workspace"}),"\n",(0,s.jsx)(t.p,{children:"Multiple components can be grouped into a single component for reuse. This is useful when combining large flows into single components, for example RAG with a vector database, and saving space."}),"\n",(0,s.jsxs)(t.ol,{children:["\n",(0,s.jsxs)(t.li,{children:["Hold\xa0",(0,s.jsx)(t.strong,{children:"Shift"}),"\xa0and drag to select components."]}),"\n",(0,s.jsxs)(t.li,{children:["Select\xa0",(0,s.jsx)(t.strong,{children:"Group"}),".\nThe components merge into a single component."]}),"\n",(0,s.jsx)(t.li,{children:"Double-click the name and description to change them."}),"\n",(0,s.jsx)(t.li,{children:"Save your grouped component to the sidebar for later use."}),"\n"]}),"\n",(0,s.jsx)(t.h2,{id:"component-version",children:"Component version"}),"\n",(0,s.jsx)(t.p,{children:"A component's initial state is stored in a database. As soon as you drag a component from the sidebar to the workspace, the two components are no longer in parity."}),"\n",(0,s.jsxs)(t.p,{children:["A component keeps the version number it is initialized to the workspace with. If a component is at version ",(0,s.jsx)(t.code,{children:"1.0"})," when it is dragged to the workspace, it will stay at version ",(0,s.jsx)(t.code,{children:"1.0"})," until you update it."]}),"\n",(0,s.jsxs)(t.p,{children:["Langflow notifies you when a component's workspace version is behind the database version and an update is available.\nClick the ",(0,s.jsx)(l.A,{name:"AlertTriangle","aria-label":"Exclamation mark"})," ",(0,s.jsx)(t.strong,{children:"Update Component"}),"\xa0icon to update the component to the\xa0",(0,s.jsx)(t.code,{children:"latest"}),"\xa0version. This will change the code of the component in place so you can validate that the component was updated by checking its Python code before and after updating it."]}),"\n",(0,s.jsx)(t.h2,{id:"components-sidebar",children:"Components sidebar"}),"\n",(0,s.jsx)(t.p,{children:"Components are listed in the sidebar by component type."}),"\n",(0,s.jsxs)(t.p,{children:["Component ",(0,s.jsx)(t.strong,{children:"bundles"})," are components grouped by provider. 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This component has two methods.\n",(0,s.jsx)(t.code,{children:"get_data_input"})," retrieves the text data to be split from the component's input. This makes the data available to the class.\n",(0,s.jsx)(t.code,{children:"build_text_splitter"})," creates a ",(0,s.jsx)(t.code,{children:"RecursiveCharacterTextSplitter"})," object by calling its parent class's ",(0,s.jsx)(t.code,{children:"build"})," method. The text is split with the created splitter and passed to the next component.\nWhen used in a flow, this component:"]}),"\n",(0,s.jsxs)(t.ol,{children:["\n",(0,s.jsx)(t.li,{children:"Displays its configuration options in the UI."}),"\n",(0,s.jsx)(t.li,{children:"Validates user inputs based on the input types."}),"\n",(0,s.jsx)(t.li,{children:"Processes data using the configured parameters."}),"\n",(0,s.jsx)(t.li,{children:"Passes results to the next component."}),"\n"]}),"\n",(0,s.jsx)(t.h2,{id:"freeze",children:"Freeze"}),"\n",(0,s.jsxs)(t.p,{children:["After a component runs, ",(0,s.jsx)(t.strong,{children:"Freeze"})," locks the component's previous output state to prevent it from re-running."]}),"\n",(0,s.jsxs)(t.p,{children:["If you\u2019re expecting consistent output from a component and don\u2019t need to re-run it, click ",(0,s.jsx)(t.strong,{children:"Freeze"}),"."]}),"\n",(0,s.jsxs)(t.p,{children:["Enabling ",(0,s.jsx)(t.strong,{children:"Freeze"})," freezes all components upstream of the selected component."]}),"\n",(0,s.jsx)(t.h2,{id:"additional-component-options",children:"Additional component options"}),"\n",(0,s.jsxs)(t.p,{children:["Click\xa0",(0,s.jsx)(l.A,{name:"Ellipsis","aria-label":"Horizontal ellipsis"})," ",(0,s.jsx)(t.strong,{children:"All"}),"\xa0to see additional options for a component."]}),"\n",(0,s.jsxs)(t.p,{children:["To modify a component's name or description, double-click in the ",(0,s.jsx)(t.strong,{children:"Name"})," or ",(0,s.jsx)(t.strong,{children:"Description"})," fields. Component descriptions accept Markdown syntax."]}),"\n",(0,s.jsx)(t.h3,{id:"component-shortcuts",children:"Component shortcuts"}),"\n",(0,s.jsx)(t.p,{children:"The following keyboard shortcuts are available when a component is selected."}),"\n",(0,s.jsxs)(t.table,{children:[(0,s.jsx)(t.thead,{children:(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.th,{children:"Menu item"}),(0,s.jsx)(t.th,{children:"Windows shortcut"}),(0,s.jsx)(t.th,{children:"Mac shortcut"}),(0,s.jsx)(t.th,{children:"Description"})]})}),(0,s.jsxs)(t.tbody,{children:[(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Code"}),(0,s.jsx)(t.td,{children:"Space"}),(0,s.jsx)(t.td,{children:"Space"}),(0,s.jsx)(t.td,{children:"Opens the code editor for the component."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Advanced Settings"}),(0,s.jsx)(t.td,{children:"Ctrl + Shift + A"}),(0,s.jsx)(t.td,{children:"\u2318 + Shift + A"}),(0,s.jsx)(t.td,{children:"Opens advanced settings for the 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inspection."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"Play"}),(0,s.jsx)(t.td,{children:"P"}),(0,s.jsx)(t.td,{children:"P"}),(0,s.jsx)(t.td,{children:"Plays/executes the flow."})]}),(0,s.jsxs)(t.tr,{children:[(0,s.jsx)(t.td,{children:"API"}),(0,s.jsx)(t.td,{children:"R"}),(0,s.jsx)(t.td,{children:"R"}),(0,s.jsx)(t.td,{children:"Opens the API view."})]})]})]}),"\n",(0,s.jsx)(t.h2,{id:"group-components-in-the-workspace",children:"Group components in the workspace"}),"\n",(0,s.jsx)(t.p,{children:"Multiple components can be grouped into a single component for reuse. 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If a component is at version ",(0,s.jsx)(t.code,{children:"1.0"})," when it is dragged to the workspace, it will stay at version ",(0,s.jsx)(t.code,{children:"1.0"})," until you update it."]}),"\n",(0,s.jsxs)(t.p,{children:["Langflow notifies you when a component's workspace version is behind the database version and an update is available.\nClick the ",(0,s.jsx)(l.A,{name:"AlertTriangle","aria-label":"Exclamation mark"})," ",(0,s.jsx)(t.strong,{children:"Update Component"}),"\xa0icon to update the component to the\xa0",(0,s.jsx)(t.code,{children:"latest"}),"\xa0version. This will change the code of the component in place so you can validate that the component was updated by checking its Python code before and after updating it."]}),"\n",(0,s.jsx)(t.h2,{id:"components-sidebar",children:"Components sidebar"}),"\n",(0,s.jsx)(t.p,{children:"Components are listed in the sidebar by component type."}),"\n",(0,s.jsxs)(t.p,{children:["Component ",(0,s.jsx)(t.strong,{children:"bundles"})," are components grouped by provider. 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Required."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"model_name"}),(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:'The name of the embedding model to use. Default: "models/text-embedding-004".'})]})]})]}),(0,t.jsx)(n.p,{children:(0,t.jsx)(n.strong,{children:"Outputs"})}),(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsx)(n.tbody,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"embeddings"}),(0,t.jsx)(n.td,{children:"Embeddings"}),(0,t.jsx)(n.td,{children:"The built GoogleGenerativeAIEmbeddings object."})]})})]})]}),"\n",(0,t.jsx)(n.h2,{id:"hugging-face-embeddings",children:"Hugging Face Embeddings"}),"\n",(0,t.jsx)(n.admonition,{type:"note",children:(0,t.jsxs)(n.p,{children:["This component is deprecated as of Langflow version 1.0.18.\nInstead, use the ",(0,t.jsx)(n.a,{href:"#hugging-face-embeddings-inference",children:"Hugging Face Embeddings Inference component"}),"."]})}),"\n",(0,t.jsx)(n.p,{children:"This component loads embedding models from HuggingFace."}),"\n",(0,t.jsx)(n.p,{children:"Use this component to generate embeddings using locally downloaded Hugging Face models. Ensure you have sufficient computational resources to run the models."}),"\n",(0,t.jsxs)(d,{children:[(0,t.jsx)("summary",{children:"Parameters"}),(0,t.jsx)(n.p,{children:(0,t.jsx)(n.strong,{children:"Inputs"})}),(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsxs)(n.tbody,{children:[(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Cache Folder"}),(0,t.jsx)(n.td,{children:"Cache Folder"}),(0,t.jsx)(n.td,{children:"The folder path to cache HuggingFace models."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Encode Kwargs"}),(0,t.jsx)(n.td,{children:"Encoding Arguments"}),(0,t.jsx)(n.td,{children:"Additional arguments for the encoding process."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Model Kwargs"}),(0,t.jsx)(n.td,{children:"Model Arguments"}),(0,t.jsx)(n.td,{children:"Additional arguments for the model."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"The name of the HuggingFace model to use."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Multi Process"}),(0,t.jsx)(n.td,{children:"Multi-Process"}),(0,t.jsx)(n.td,{children:"Whether to use multiple processes."})]})]})]}),(0,t.jsx)(n.p,{children:(0,t.jsx)(n.strong,{children:"Outputs"})}),(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsx)(n.tbody,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"embeddings"}),(0,t.jsx)(n.td,{children:"Embeddings"}),(0,t.jsx)(n.td,{children:"The generated embeddings."})]})})]})]}),"\n",(0,t.jsx)(n.h2,{id:"hugging-face-embeddings-inference",children:"Hugging Face embeddings inference"}),"\n",(0,t.jsxs)(n.p,{children:["This component generates embeddings using ",(0,t.jsx)(n.a,{href:"https://huggingface.co/",children:"Hugging Face Inference API models"})," and requires a ",(0,t.jsx)(n.a,{href:"https://huggingface.co/docs/hub/security-tokens",children:"Hugging Face API token"})," to authenticate. Local inference models do not require an API key."]}),"\n",(0,t.jsx)(n.p,{children:"Use this component to create embeddings with Hugging Face's hosted models, or to connect to your own locally hosted models."}),"\n",(0,t.jsxs)(d,{children:[(0,t.jsx)("summary",{children:"Parameters"}),(0,t.jsx)(n.p,{children:(0,t.jsx)(n.strong,{children:"Inputs"})}),(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsxs)(n.tbody,{children:[(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"API Key"}),(0,t.jsx)(n.td,{children:"API Key"}),(0,t.jsx)(n.td,{children:"The API key for accessing the Hugging Face Inference API."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"API URL"}),(0,t.jsx)(n.td,{children:"API URL"}),(0,t.jsx)(n.td,{children:"The URL of the Hugging Face Inference API."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"The name of the model to use for embeddings."})]})]})]}),(0,t.jsx)(n.p,{children:(0,t.jsx)(n.strong,{children:"Outputs"})}),(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsx)(n.tbody,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"embeddings"}),(0,t.jsx)(n.td,{children:"Embeddings"}),(0,t.jsx)(n.td,{children:"The generated embeddings."})]})})]})]}),"\n",(0,t.jsx)(n.h3,{id:"connect-the-hugging-face-component-to-a-local-embeddings-model",children:"Connect the Hugging Face component to a local embeddings model"}),"\n",(0,t.jsxs)(n.p,{children:["To run an embeddings inference locally, see the ",(0,t.jsx)(n.a,{href:"https://huggingface.co/docs/text-embeddings-inference/local_cpu",children:"HuggingFace documentation"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["To connect the local Hugging Face model to the ",(0,t.jsx)(n.strong,{children:"Hugging Face embeddings inference"})," component and use it in a flow, follow these steps:"]}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["Create a ",(0,t.jsx)(n.a,{href:"/starter-projects-vector-store-rag",children:"Vector store RAG flow"}),".\nThere are two embeddings models in this flow that you can replace with ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," embeddings inference components."]}),"\n",(0,t.jsxs)(n.li,{children:["Replace both ",(0,t.jsx)(n.strong,{children:"OpenAI"})," embeddings model components with ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," model components."]}),"\n",(0,t.jsxs)(n.li,{children:["Connect both ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," components to the ",(0,t.jsx)(n.strong,{children:"Embeddings"})," ports of the ",(0,t.jsx)(n.strong,{children:"Astra DB vector store"})," components."]}),"\n",(0,t.jsxs)(n.li,{children:["In the ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," components, set the ",(0,t.jsx)(n.strong,{children:"Inference Endpoint"})," field to the URL of your local inference model. ",(0,t.jsxs)(n.strong,{children:["The ",(0,t.jsx)(n.strong,{children:"API Key"})," field is not required for local inference."]})]}),"\n",(0,t.jsx)(n.li,{children:"Run the flow. 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Local inference models do not require an API key."]}),"\n",(0,t.jsx)(n.p,{children:"Use this component to create embeddings with Hugging Face's hosted models, or to connect to your own locally hosted models."}),"\n",(0,t.jsx)(n.h3,{id:"inputs-9",children:"Inputs"}),"\n",(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsxs)(n.tbody,{children:[(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"API Key"}),(0,t.jsx)(n.td,{children:"API Key"}),(0,t.jsx)(n.td,{children:"The API key for accessing the Hugging Face Inference API."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"API URL"}),(0,t.jsx)(n.td,{children:"API URL"}),(0,t.jsx)(n.td,{children:"The URL of the Hugging Face Inference API."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"The name of the model to use for embeddings."})]})]})]}),"\n",(0,t.jsx)(n.h3,{id:"outputs-9",children:"Outputs"}),"\n",(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsx)(n.tbody,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"embeddings"}),(0,t.jsx)(n.td,{children:"Embeddings"}),(0,t.jsx)(n.td,{children:"The generated embeddings."})]})})]}),"\n",(0,t.jsx)(n.h3,{id:"connect-the-hugging-face-component-to-a-local-embeddings-model",children:"Connect the Hugging Face component to a local embeddings model"}),"\n",(0,t.jsxs)(n.p,{children:["To run an embeddings inference locally, see the ",(0,t.jsx)(n.a,{href:"https://huggingface.co/docs/text-embeddings-inference/local_cpu",children:"HuggingFace documentation"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["To connect the local Hugging Face model to the ",(0,t.jsx)(n.strong,{children:"Hugging Face embeddings inference"})," component and use it in a flow, follow these steps:"]}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["Create a ",(0,t.jsx)(n.a,{href:"/starter-projects-vector-store-rag",children:"Vector store RAG flow"}),".\nThere are two embeddings models in this flow that you can replace with ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," embeddings inference components."]}),"\n",(0,t.jsxs)(n.li,{children:["Replace both ",(0,t.jsx)(n.strong,{children:"OpenAI"})," embeddings model components with ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," model components."]}),"\n",(0,t.jsxs)(n.li,{children:["Connect both ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," components to the ",(0,t.jsx)(n.strong,{children:"Embeddings"})," ports of the ",(0,t.jsx)(n.strong,{children:"Astra DB vector store"})," components."]}),"\n",(0,t.jsxs)(n.li,{children:["In the ",(0,t.jsx)(n.strong,{children:"Hugging Face"})," components, set the ",(0,t.jsx)(n.strong,{children:"Inference Endpoint"})," field to the URL of your local inference model. ",(0,t.jsxs)(n.strong,{children:["The ",(0,t.jsx)(n.strong,{children:"API Key"})," field is not required for local inference."]})]}),"\n",(0,t.jsx)(n.li,{children:"Run the flow. The local inference models generate embeddings for the input text."}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"ibm-watsonx-embeddings",children:"IBM watsonx embeddings"}),"\n",(0,t.jsxs)(n.p,{children:["This component generates text using ",(0,t.jsx)(n.a,{href:"https://www.ibm.com/watsonx",children:"IBM watsonx.ai"})," foundation models."]}),"\n",(0,t.jsxs)(n.p,{children:["To use ",(0,t.jsx)(n.strong,{children:"IBM watsonx.ai"})," embeddings components, replace an embeddings component with the IBM watsonx.ai component in a flow."]}),"\n",(0,t.jsx)(n.p,{children:"An example document processing flow looks like the following:"}),"\n",(0,t.jsx)(n.p,{children:(0,t.jsx)(n.img,{alt:"IBM watsonx embeddings model loading a chroma-db with split text",src:d(96425).A+"",width:"1714",height:"1486"})}),"\n",(0,t.jsx)(n.p,{children:"This flow loads a PDF file from local storage and splits the text into chunks."}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"IBM watsonx"})," embeddings component converts the text chunks into embeddings, which are then stored in a Chroma DB vector store."]}),"\n",(0,t.jsxs)(n.p,{children:["The values for ",(0,t.jsx)(n.strong,{children:"API endpoint"}),", ",(0,t.jsx)(n.strong,{children:"Project ID"}),", ",(0,t.jsx)(n.strong,{children:"API key"}),", and ",(0,t.jsx)(n.strong,{children:"Model Name"})," are found in your IBM watsonx.ai deployment.\nFor more information, see the ",(0,t.jsx)(n.a,{href:"https://python.langchain.com/docs/integrations/text_embedding/ibm_watsonx/",children:"Langchain documentation"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"default-models",children:"Default models"}),"\n",(0,t.jsx)(n.p,{children:"The component supports several default models with the following vector dimensions:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.code,{children:"sentence-transformers/all-minilm-l12-v2"}),": 384-dimensional embeddings"]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.code,{children:"ibm/slate-125m-english-rtrvr-v2"}),": 768-dimensional embeddings"]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.code,{children:"ibm/slate-30m-english-rtrvr-v2"}),": 768-dimensional embeddings"]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.code,{children:"intfloat/multilingual-e5-large"}),": 1024-dimensional embeddings"]}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"The component automatically fetches and updates the list of available models from your watsonx.ai instance when you provide your API endpoint and credentials."}),"\n",(0,t.jsx)(n.h3,{id:"inputs-10",children:"Inputs"}),"\n",(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsxs)(n.tbody,{children:[(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"url"}),(0,t.jsx)(n.td,{children:"watsonx API Endpoint"}),(0,t.jsx)(n.td,{children:"The base URL of the API."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"project_id"}),(0,t.jsx)(n.td,{children:"watsonx project id"}),(0,t.jsx)(n.td,{children:"The project ID for your watsonx.ai instance."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"api_key"}),(0,t.jsx)(n.td,{children:"API Key"}),(0,t.jsx)(n.td,{children:"The API Key to use for the model."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"model_name"}),(0,t.jsx)(n.td,{children:"Model Name"}),(0,t.jsx)(n.td,{children:"The name of the embedding model to use."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"truncate_input_tokens"}),(0,t.jsx)(n.td,{children:"Truncate Input Tokens"}),(0,t.jsxs)(n.td,{children:["The maximum number of tokens to process. 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Default: ",(0,t.jsx)(n.code,{children:"True"}),"."]})]})]})]}),"\n",(0,t.jsx)(n.h3,{id:"outputs-10",children:"Outputs"}),"\n",(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Name"}),(0,t.jsx)(n.th,{children:"Display Name"}),(0,t.jsx)(n.th,{children:"Info"})]})}),(0,t.jsx)(n.tbody,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"embeddings"}),(0,t.jsx)(n.td,{children:"Embeddings"}),(0,t.jsx)(n.td,{children:"An instance for generating embeddings using watsonx.ai"})]})})]}),"\n",(0,t.jsx)(n.h2,{id:"lm-studio-embeddings",children:"LM Studio Embeddings"}),"\n",(0,t.jsxs)(n.p,{children:["This component generates embeddings using ",(0,t.jsx)(n.a,{href:"https://lmstudio.ai/docs",children:"LM Studio"})," 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",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," text column and returns a new DataFrame with the original text and an LLM response."]}),"\n",(0,r.jsx)(t.p,{children:"The response contains the following columns:"}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"text_input"}),": The original text from the input DataFrame."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"model_response"}),": The model's response for each input."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"batch_index"}),": The processing order, with a ",(0,r.jsx)(t.code,{children:"0"}),"-based index."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"metadata"})," (optional): Additional information about the processing."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["These columns, when connected to a ",(0,r.jsx)(t.strong,{children:"Parser"})," component, can be used as variables within curly braces."]}),"\n",(0,r.jsxs)(t.p,{children:["To use the Batch Run component with a ",(0,r.jsx)(t.strong,{children:"Parser"})," component, do the following:"]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Model"})," component to the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's ",(0,r.jsx)(t.strong,{children:"Language model"})," port."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect a component that outputs DataFrame, like ",(0,r.jsx)(t.strong,{children:"File"})," component, to the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," input."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's ",(0,r.jsx)(t.strong,{children:"Batch Results"})," output to a ",(0,r.jsx)(t.strong,{children:"Parser"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," input.\nThe flow looks like this:"]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"A batch run component connected to OpenAI and a Parser",src:n(88103).A+"",width:"1776",height:"1370"})}),"\n",(0,r.jsxs)(t.ol,{start:"4",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Column Name"})," field of the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component, enter a column name based on the data you're loading from the ",(0,r.jsx)(t.strong,{children:"File"})," loader. For example, to process a column of ",(0,r.jsx)(t.code,{children:"name"}),", enter ",(0,r.jsx)(t.code,{children:"name"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Optionally, in the ",(0,r.jsx)(t.strong,{children:"System Message"})," field of the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component, enter a ",(0,r.jsx)(t.strong,{children:"System Message"})," to instruct the connected LLM on how to process your file. For example, ",(0,r.jsx)(t.code,{children:"Create a business card for each name."})]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Template"})," field of the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, enter a template for using the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's new DataFrame columns.\nTo use all three columns from the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component, include them like this:"]}),"\n"]}),"\n",(0,r.jsx)(a.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"record_number: {batch_index}, name: {text_input}, summary: {model_response}",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["To run the flow, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(o.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To view your created DataFrame, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(o.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Optionally, connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component, and open the ",(0,r.jsx)(t.strong,{children:"Playground"})," to see the output."]}),"\n"]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"model"}),(0,r.jsx)(t.td,{children:"HandleInput"}),(0,r.jsx)(t.td,{children:"Connect the 'Language Model' output from your LLM component here. Required."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"system_message"}),(0,r.jsx)(t.td,{children:"MultilineInput"}),(0,r.jsx)(t.td,{children:"A multi-line system instruction for all rows in the DataFrame."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"df"}),(0,r.jsx)(t.td,{children:"DataFrameInput"}),(0,r.jsx)(t.td,{children:"The DataFrame whose column is treated as text messages, as specified by 'column_name'. Required."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"column_name"}),(0,r.jsx)(t.td,{children:"MessageTextInput"}),(0,r.jsx)(t.td,{children:"The name of the DataFrame column to treat as text messages. Default='text'. Required."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"enable_metadata"}),(0,r.jsx)(t.td,{children:"BoolInput"}),(0,r.jsx)(t.td,{children:"If True, add metadata to the output DataFrame."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"batch_results"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"A DataFrame with columns: 'text_input', 'model_response', 'batch_index', and optional 'metadata' containing processing information."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"current-date",children:"Current date"}),"\n",(0,r.jsx)(t.p,{children:"The Current Date component returns the current date and time in a selected timezone. This component provides a flexible way to obtain timezone-specific date and time information within a Langflow pipeline."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"timezone"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The timezone for the current date and time."})]})})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"current_date"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The resulting current date and time in the selected timezone."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"id-generator",children:"ID Generator"}),"\n",(0,r.jsx)(t.p,{children:"This component generates a unique ID."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"unique_id"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The generated unique ID."})]})})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"id"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The generated unique ID."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"message-history",children:"Message history"}),"\n",(0,r.jsx)(t.admonition,{type:"info",children:(0,r.jsx)(t.p,{children:"Prior to Langflow 1.1, this component was known as the Chat Memory component."})}),"\n",(0,r.jsx)(t.p,{children:"This component retrieves chat messages from Langflow tables or external memory."}),"\n",(0,r.jsxs)(t.p,{children:["In this example, the ",(0,r.jsx)(t.strong,{children:"Message Store"})," component stores the complete chat history in a local Langflow table, which the ",(0,r.jsx)(t.strong,{children:"Message History"})," component retrieves as context for the LLM to answer each question."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Message store and history components",src:n(77111).A+"",width:"2778",height:"1166"})}),"\n",(0,r.jsxs)(t.p,{children:["For more information on configuring memory in Langflow, see ",(0,r.jsx)(t.a,{href:"/memory",children:"Memory"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"memory"}),(0,r.jsx)(t.td,{children:"Memory"}),(0,r.jsx)(t.td,{children:"Retrieve messages from an external memory. If empty, the Langflow tables are used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"Filter by sender type."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender_name"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"Filter by sender name."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"n_messages"}),(0,r.jsx)(t.td,{children:"Integer"}),(0,r.jsx)(t.td,{children:"The number of messages to retrieve."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"session_id"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The session ID of the chat. If empty, the current session ID parameter is used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"order"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The order of the messages."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"template"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsxs)(t.td,{children:["The template to use for formatting the data. It can contain the keys ",(0,r.jsx)(t.code,{children:"{text}"}),", ",(0,r.jsx)(t.code,{children:"{sender}"})," or any other key in the message data."]})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"messages"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The retrieved messages as Data objects."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"messages_text"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The retrieved messages formatted as text."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"lc_memory"}),(0,r.jsx)(t.td,{children:"Memory"}),(0,r.jsxs)(t.td,{children:["A constructed Langchain ",(0,r.jsx)(t.a,{href:"https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer.ConversationBufferMemory.html",children:"ConversationBufferMemory"})," object."]})]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"message-store",children:"Message store"}),"\n",(0,r.jsx)(t.p,{children:"This component stores chat messages or text in Langflow tables or external memory."}),"\n",(0,r.jsxs)(t.p,{children:["In this example, the ",(0,r.jsx)(t.strong,{children:"Message Store"})," component stores the complete chat history in a local Langflow table, which the ",(0,r.jsx)(t.strong,{children:"Message History"})," component retrieves as context for the LLM to answer each question."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Message store and history components",src:n(77111).A+"",width:"2778",height:"1166"})}),"\n",(0,r.jsxs)(t.p,{children:["For more information on configuring memory in Langflow, see ",(0,r.jsx)(t.a,{href:"/memory",children:"Memory"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The chat message to be stored. (Required)"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"memory"}),(0,r.jsx)(t.td,{children:"Memory"}),(0,r.jsx)(t.td,{children:"The external memory to store the message. If empty, the Langflow tables are used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The sender of the message. Can be Machine or User. If empty, the current sender parameter is used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender_name"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The name of the sender. Can be AI or User. If empty, the current sender parameter is used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"session_id"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The session ID of the chat. If empty, the current session ID parameter is used."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"stored_messages"}),(0,r.jsx)(t.td,{children:"List[Data]"}),(0,r.jsx)(t.td,{children:"The list of stored messages after the current message has been added."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"structured-output",children:"Structured output"}),"\n",(0,r.jsx)(t.p,{children:"This component transforms LLM responses into structured data formats."}),"\n",(0,r.jsxs)(t.p,{children:["In this example from the ",(0,r.jsx)(t.strong,{children:"Financial Support Parser"})," template, the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component transforms unstructured financial reports into structured data."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Structured output example",src:n(82798).A+"",width:"2554",height:"1548"})}),"\n",(0,r.jsxs)(t.p,{children:["The connected LLM model is prompted by the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.code,{children:"Format Instructions"})," parameter to extract structured output from the unstructured text. ",(0,r.jsx)(t.code,{children:"Format Instructions"})," is utilized as the system prompt for the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component."]}),"\n",(0,r.jsxs)(t.p,{children:["In the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, click the ",(0,r.jsx)(t.strong,{children:"Open table"})," button to view the ",(0,r.jsx)(t.code,{children:"Output Schema"})," table.\nThe ",(0,r.jsx)(t.code,{children:"Output Schema"})," parameter defines the structure and data types for the model's output using a table with the following fields:"]}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Name"}),": The name of the output field."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Description"}),": The purpose of the output field."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Type"}),": The data type of the output field. The available types are ",(0,r.jsx)(t.code,{children:"str"}),", ",(0,r.jsx)(t.code,{children:"int"}),", ",(0,r.jsx)(t.code,{children:"float"}),", ",(0,r.jsx)(t.code,{children:"bool"}),", ",(0,r.jsx)(t.code,{children:"list"}),", or ",(0,r.jsx)(t.code,{children:"dict"}),". The default is ",(0,r.jsx)(t.code,{children:"text"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Multiple"}),": This feature is deprecated. Currently, it is set to ",(0,r.jsx)(t.code,{children:"True"})," by default if you expect multiple values for a single field. For example, a ",(0,r.jsx)(t.code,{children:"list"})," of ",(0,r.jsx)(t.code,{children:"features"})," is set to ",(0,r.jsx)(t.code,{children:"True"})," to contain multiple values, such as ",(0,r.jsx)(t.code,{children:'["waterproof", "durable", "lightweight"]'}),". Default: ",(0,r.jsx)(t.code,{children:"True"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["The ",(0,r.jsx)(t.strong,{children:"Parse DataFrame"})," component parses the structured output into a template for orderly presentation in chat output. The template receives the values from the ",(0,r.jsx)(t.code,{children:"output_schema"})," table with curly braces."]}),"\n",(0,r.jsxs)(t.p,{children:["For example, the template ",(0,r.jsx)(t.code,{children:"EBITDA: {EBITDA} , Net Income: {NET_INCOME} , GROSS_PROFIT: {GROSS_PROFIT}"})," presents the extracted values in the ",(0,r.jsx)(t.strong,{children:"Playground"})," as ",(0,r.jsx)(t.code,{children:"EBITDA: 900 million , Net Income: 500 million , GROSS_PROFIT: 1.2 billion"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"llm"}),(0,r.jsx)(t.td,{children:"LanguageModel"}),(0,r.jsx)(t.td,{children:"The language model to use to generate the structured output."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"input_value"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The input message to the language model."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"system_prompt"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The instructions to the language model for formatting the output."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"schema_name"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The name for the output data schema."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output_schema"}),(0,r.jsx)(t.td,{children:"Table"}),(0,r.jsx)(t.td,{children:"The structure and data types for the model's output."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"multiple"}),(0,r.jsx)(t.td,{children:"Boolean"}),(0,r.jsxs)(t.td,{children:["[Deprecated] Always set to ",(0,r.jsx)(t.code,{children:"True"}),"."]})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"structured_output"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The structured output is a Data object based on the defined schema."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"legacy-components",children:"Legacy components"}),"\n",(0,r.jsx)(t.p,{children:"Legacy components are available for use but are no longer supported."}),"\n",(0,r.jsx)(t.h3,{id:"create-list",children:"Create List"}),"\n",(0,r.jsx)(t.p,{children:"This component dynamically creates a record with a specified number of fields."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"n_fields"}),(0,r.jsx)(t.td,{children:"Integer"}),(0,r.jsx)(t.td,{children:"The number of fields to be added to the record."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text_key"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:"The key used as text."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"list"}),(0,r.jsx)(t.td,{children:"List"}),(0,r.jsx)(t.td,{children:"The dynamically created list with the specified number of fields."})]})})]})]}),"\n",(0,r.jsx)(t.h3,{id:"output-parser",children:"Output Parser"}),"\n",(0,r.jsxs)(t.p,{children:["This component transforms the output of a language model into a specified format. It supports CSV format parsing, which converts LLM responses into comma-separated lists using Langchain's ",(0,r.jsx)(t.code,{children:"CommaSeparatedListOutputParser"}),"."]}),"\n",(0,r.jsx)(t.admonition,{type:"note",children:(0,r.jsx)(t.p,{children:"This component only provides formatting instructions and parsing functionality. It does not include a prompt. You'll need to connect it to a separate Prompt component to create the actual prompt template for the LLM to use."})}),"\n",(0,r.jsxs)(t.p,{children:["Both the ",(0,r.jsx)(t.strong,{children:"Output Parser"})," and ",(0,r.jsx)(t.strong,{children:"Structured Output"})," components format LLM responses, but they have different use cases.\nThe ",(0,r.jsx)(t.strong,{children:"Output Parser"})," is simpler and focused on converting responses into comma-separated lists. Use this when you just need a list of items, for example ",(0,r.jsx)(t.code,{children:'["item1", "item2", "item3"]'}),".\nThe ",(0,r.jsx)(t.strong,{children:"Structured Output"})," is more complex and flexible, and allows you to define custom schemas with multiple fields of different types. Use this when you need to extract structured data with specific fields and types."]}),"\n",(0,r.jsx)(t.p,{children:"To use this component:"}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Create a Prompt component and connect the Output Parser's ",(0,r.jsx)(t.code,{children:"format_instructions"})," output to it. This ensures the LLM knows how to format its response."]}),"\n",(0,r.jsxs)(t.li,{children:["Write your actual prompt text in the Prompt component, including the ",(0,r.jsx)(t.code,{children:"{format_instructions}"})," variable.\nFor example, in your Prompt component, the template might look like:"]}),"\n"]}),"\n",(0,r.jsx)(a.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"{format_instructions}",props:{}}]},{tokens:[{content:"Please list three fruits.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"3",children:["\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Connect the ",(0,r.jsx)(t.code,{children:"output_parser"})," output to your LLM model."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["The output parser converts this into a Python list: ",(0,r.jsx)(t.code,{children:'["apple", "banana", "orange"]'}),"."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"parser_type"}),(0,r.jsx)(t.td,{children:"String"}),(0,r.jsx)(t.td,{children:'The parser type. 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}'}}),"\n","\n",(0,r.jsx)(t.header,{children:(0,r.jsx)(t.h1,{id:"helper-components-in-langflow",children:"Helper components in Langflow"})}),"\n",(0,r.jsx)(t.p,{children:"Helper components provide utility functions to help manage data, tasks, and other components in your flow."}),"\n",(0,r.jsx)(t.h2,{id:"use-a-helper-component-in-a-flow",children:"Use a helper component in a flow"}),"\n",(0,r.jsxs)(t.p,{children:["Chat memory in Langflow is stored either in local Langflow tables with ",(0,r.jsx)(t.code,{children:"LCBufferMemory"}),", or connected to an external database."]}),"\n",(0,r.jsxs)(t.p,{children:["The ",(0,r.jsx)(t.strong,{children:"Store Message"})," helper component stores chat memories as ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," objects, and the ",(0,r.jsx)(t.strong,{children:"Message History"})," helper component retrieves chat messages as data objects or strings."]}),"\n",(0,r.jsxs)(t.p,{children:["This example flow stores and retrieves chat history from an ",(0,r.jsx)(t.a,{href:"/components-memories#astradbchatmemory-component",children:"AstraDBChatMemory"})," component with ",(0,r.jsx)(t.strong,{children:"Store Message"})," and ",(0,r.jsx)(t.strong,{children:"Chat Memory"})," components."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Sample Flow storing Chat Memory in AstraDB",src:n(72654).A+"",width:"3178",height:"1228"})}),"\n",(0,r.jsx)(t.h2,{id:"batch-run",children:"Batch Run"}),"\n",(0,r.jsxs)(t.p,{children:["The ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component runs a language model over ",(0,r.jsx)(t.strong,{children:"each row"})," of a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," text column and returns a new DataFrame with the original text and an LLM response."]}),"\n",(0,r.jsx)(t.p,{children:"The response contains the following columns:"}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"text_input"}),": The original text from the input DataFrame."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"model_response"}),": The model's response for each input."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"batch_index"}),": The processing order, with a ",(0,r.jsx)(t.code,{children:"0"}),"-based index."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:"metadata"})," (optional): Additional information about the processing."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["These columns, when connected to a ",(0,r.jsx)(t.strong,{children:"Parser"})," component, can be used as variables within curly braces."]}),"\n",(0,r.jsxs)(t.p,{children:["To use the Batch Run component with a ",(0,r.jsx)(t.strong,{children:"Parser"})," component, do the following:"]}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Connect a ",(0,r.jsx)(t.strong,{children:"Model"})," component to the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's ",(0,r.jsx)(t.strong,{children:"Language model"})," port."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect a component that outputs DataFrame, like ",(0,r.jsx)(t.strong,{children:"File"})," component, to the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," input."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's ",(0,r.jsx)(t.strong,{children:"Batch Results"})," output to a ",(0,r.jsx)(t.strong,{children:"Parser"})," component's ",(0,r.jsx)(t.strong,{children:"DataFrame"})," input.\nThe flow looks like this:"]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"A batch run component connected to OpenAI and a Parser",src:n(88103).A+"",width:"1776",height:"1370"})}),"\n",(0,r.jsxs)(t.ol,{start:"4",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Column Name"})," field of the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component, enter a column name based on the data you're loading from the ",(0,r.jsx)(t.strong,{children:"File"})," loader. For example, to process a column of ",(0,r.jsx)(t.code,{children:"name"}),", enter ",(0,r.jsx)(t.code,{children:"name"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Optionally, in the ",(0,r.jsx)(t.strong,{children:"System Message"})," field of the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component, enter a ",(0,r.jsx)(t.strong,{children:"System Message"})," to instruct the connected LLM on how to process your file. For example, ",(0,r.jsx)(t.code,{children:"Create a business card for each name."})]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Template"})," field of the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, enter a template for using the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component's new DataFrame columns.\nTo use all three columns from the ",(0,r.jsx)(t.strong,{children:"Batch Run"})," component, include them like this:"]}),"\n"]}),"\n",(0,r.jsx)(a.Code,{codeConfig:u,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"record_number: {batch_index}, name: {text_input}, summary: {model_response}",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["To run the flow, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(o.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["To view your created DataFrame, in the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, click ",(0,r.jsx)(o.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:["Optionally, connect a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component, and open the ",(0,r.jsx)(t.strong,{children:"Playground"})," to see the output."]}),"\n"]}),"\n",(0,r.jsx)(t.h3,{id:"inputs",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"model"}),(0,r.jsx)(t.td,{children:"Language Model"}),(0,r.jsx)(t.td,{children:"HandleInput"}),(0,r.jsx)(t.td,{children:"Connect the 'Language Model' output from your LLM component here. Required."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"system_message"}),(0,r.jsx)(t.td,{children:"System Message"}),(0,r.jsx)(t.td,{children:"MultilineInput"}),(0,r.jsx)(t.td,{children:"Multi-line system instruction for all rows in the DataFrame."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"df"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"DataFrameInput"}),(0,r.jsx)(t.td,{children:"The DataFrame whose column is treated as text messages, as specified by 'column_name'. Required."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"column_name"}),(0,r.jsx)(t.td,{children:"Column Name"}),(0,r.jsx)(t.td,{children:"MessageTextInput"}),(0,r.jsx)(t.td,{children:"The name of the DataFrame column to treat as text messages. Default='text'. Required."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"enable_metadata"}),(0,r.jsx)(t.td,{children:"Enable Metadata"}),(0,r.jsx)(t.td,{children:"BoolInput"}),(0,r.jsx)(t.td,{children:"If True, add metadata to the output DataFrame."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Method"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"batch_results"}),(0,r.jsx)(t.td,{children:"Batch Results"}),(0,r.jsx)(t.td,{children:"run_batch"}),(0,r.jsx)(t.td,{children:"A DataFrame with columns: 'text_input', 'model_response', 'batch_index', and optional 'metadata' containing processing information."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"current-date",children:"Current date"}),"\n",(0,r.jsx)(t.p,{children:"The Current Date component returns the current date and time in a selected timezone. This component provides a flexible way to obtain timezone-specific date and time information within a Langflow pipeline."}),"\n",(0,r.jsx)(t.h3,{id:"inputs-1",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"timezone"}),(0,r.jsx)(t.td,{children:"Timezone"}),(0,r.jsx)(t.td,{children:"Select the timezone for the current date and time."})]})})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-1",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"current_date"}),(0,r.jsx)(t.td,{children:"Current Date"}),(0,r.jsx)(t.td,{children:"The resulting current date and time in the selected timezone."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"id-generator",children:"ID Generator"}),"\n",(0,r.jsx)(t.p,{children:"This component generates a unique ID."}),"\n",(0,r.jsx)(t.h3,{id:"inputs-2",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"unique_id"}),(0,r.jsx)(t.td,{children:"Value"}),(0,r.jsx)(t.td,{children:"The generated unique ID."})]})})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-2",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"id"}),(0,r.jsx)(t.td,{children:"ID"}),(0,r.jsx)(t.td,{children:"The generated unique ID."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"message-history",children:"Message history"}),"\n",(0,r.jsx)(t.admonition,{type:"info",children:(0,r.jsx)(t.p,{children:"Prior to Langflow 1.1, this component was known as the Chat Memory component."})}),"\n",(0,r.jsx)(t.p,{children:"This component retrieves chat messages from Langflow tables or external memory."}),"\n",(0,r.jsxs)(t.p,{children:["In this example, the ",(0,r.jsx)(t.strong,{children:"Message Store"})," component stores the complete chat history in a local Langflow table, which the ",(0,r.jsx)(t.strong,{children:"Message History"})," component retrieves as context for the LLM to answer each question."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Message store and history components",src:n(77111).A+"",width:"2778",height:"1166"})}),"\n",(0,r.jsxs)(t.p,{children:["For more information on configuring memory in Langflow, see ",(0,r.jsx)(t.a,{href:"/memory",children:"Memory"}),"."]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-3",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"memory"}),(0,r.jsx)(t.td,{children:"External Memory"}),(0,r.jsx)(t.td,{children:"Retrieve messages from an external memory. If empty, it will use the Langflow tables."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender"}),(0,r.jsx)(t.td,{children:"Sender Type"}),(0,r.jsx)(t.td,{children:"Filter by sender type."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender_name"}),(0,r.jsx)(t.td,{children:"Sender Name"}),(0,r.jsx)(t.td,{children:"Filter by sender name."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"n_messages"}),(0,r.jsx)(t.td,{children:"Number of Messages"}),(0,r.jsx)(t.td,{children:"Number of messages to retrieve."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"session_id"}),(0,r.jsx)(t.td,{children:"Session ID"}),(0,r.jsx)(t.td,{children:"The session ID of the chat. If empty, the current session ID parameter will be used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"order"}),(0,r.jsx)(t.td,{children:"Order"}),(0,r.jsx)(t.td,{children:"Order of the messages."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"template"}),(0,r.jsx)(t.td,{children:"Template"}),(0,r.jsxs)(t.td,{children:["The template to use for formatting the data. It can contain the keys ",(0,r.jsx)(t.code,{children:"{text}"}),", ",(0,r.jsx)(t.code,{children:"{sender}"})," or any other key in the message data."]})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-3",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"messages"}),(0,r.jsx)(t.td,{children:"Messages (Data)"}),(0,r.jsx)(t.td,{children:"Retrieved messages as Data objects."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"messages_text"}),(0,r.jsx)(t.td,{children:"Messages (Text)"}),(0,r.jsx)(t.td,{children:"Retrieved messages formatted as text."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"lc_memory"}),(0,r.jsx)(t.td,{children:"Memory"}),(0,r.jsxs)(t.td,{children:["A constructed Langchain ",(0,r.jsx)(t.a,{href:"https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer.ConversationBufferMemory.html",children:"ConversationBufferMemory"})," object"]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"message-store",children:"Message store"}),"\n",(0,r.jsx)(t.p,{children:"This component stores chat messages or text in Langflow tables or external memory."}),"\n",(0,r.jsxs)(t.p,{children:["In this example, the ",(0,r.jsx)(t.strong,{children:"Message Store"})," component stores the complete chat history in a local Langflow table, which the ",(0,r.jsx)(t.strong,{children:"Message History"})," component retrieves as context for the LLM to answer each question."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Message store and history components",src:n(77111).A+"",width:"2778",height:"1166"})}),"\n",(0,r.jsxs)(t.p,{children:["For more information on configuring memory in Langflow, see ",(0,r.jsx)(t.a,{href:"/memory",children:"Memory"}),"."]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-4",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsx)(t.td,{children:"The chat message to be stored. (Required)"})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"memory"}),(0,r.jsx)(t.td,{children:"External Memory"}),(0,r.jsx)(t.td,{children:"The external memory to store the message. If empty, it will use the Langflow tables."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender"}),(0,r.jsx)(t.td,{children:"Sender"}),(0,r.jsx)(t.td,{children:"The sender of the message. Can be Machine or User. If empty, the current sender parameter will be used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"sender_name"}),(0,r.jsx)(t.td,{children:"Sender Name"}),(0,r.jsx)(t.td,{children:"The name of the sender. Can be AI or User. If empty, the current sender parameter will be used."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"session_id"}),(0,r.jsx)(t.td,{children:"Session ID"}),(0,r.jsx)(t.td,{children:"The session ID of the chat. If empty, the current session ID parameter will be used."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-4",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"stored_messages"}),(0,r.jsx)(t.td,{children:"Stored Messages"}),(0,r.jsx)(t.td,{children:"The list of stored messages after the current message has been added."})]})})]}),"\n",(0,r.jsx)(t.h2,{id:"structured-output",children:"Structured output"}),"\n",(0,r.jsx)(t.p,{children:"This component transforms LLM responses into structured data formats."}),"\n",(0,r.jsxs)(t.p,{children:["In this example from the ",(0,r.jsx)(t.strong,{children:"Financial Support Parser"})," template, the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component transforms unstructured financial reports into structured data."]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Structured output example",src:n(82798).A+"",width:"2554",height:"1548"})}),"\n",(0,r.jsxs)(t.p,{children:["The connected LLM model is prompted by the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component's ",(0,r.jsx)(t.code,{children:"Format Instructions"})," parameter to extract structured output from the unstructured text. ",(0,r.jsx)(t.code,{children:"Format Instructions"})," is utilized as the system prompt for the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component."]}),"\n",(0,r.jsxs)(t.p,{children:["In the ",(0,r.jsx)(t.strong,{children:"Structured Output"})," component, click the ",(0,r.jsx)(t.strong,{children:"Open table"})," button to view the ",(0,r.jsx)(t.code,{children:"Output Schema"})," table.\nThe ",(0,r.jsx)(t.code,{children:"Output Schema"})," parameter defines the structure and data types for the model's output using a table with the following fields:"]}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Name"}),": The name of the output field."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Description"}),": The purpose of the output field."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Type"}),": The data type of the output field. The available types are ",(0,r.jsx)(t.code,{children:"str"}),", ",(0,r.jsx)(t.code,{children:"int"}),", ",(0,r.jsx)(t.code,{children:"float"}),", ",(0,r.jsx)(t.code,{children:"bool"}),", ",(0,r.jsx)(t.code,{children:"list"}),", or ",(0,r.jsx)(t.code,{children:"dict"}),". The default is ",(0,r.jsx)(t.code,{children:"text"}),"."]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.strong,{children:"Multiple"}),": This feature is deprecated. Currently, it is set to ",(0,r.jsx)(t.code,{children:"True"})," by default if you expect multiple values for a single field. For example, a ",(0,r.jsx)(t.code,{children:"list"})," of ",(0,r.jsx)(t.code,{children:"features"})," is set to ",(0,r.jsx)(t.code,{children:"True"})," to contain multiple values, such as ",(0,r.jsx)(t.code,{children:'["waterproof", "durable", "lightweight"]'}),". Default: ",(0,r.jsx)(t.code,{children:"True"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(t.p,{children:["The ",(0,r.jsx)(t.strong,{children:"Parse DataFrame"})," component parses the structured output into a template for orderly presentation in chat output. 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It supports CSV format parsing, which converts LLM responses into comma-separated lists using Langchain's ",(0,r.jsx)(t.code,{children:"CommaSeparatedListOutputParser"}),"."]}),"\n",(0,r.jsx)(t.admonition,{type:"note",children:(0,r.jsx)(t.p,{children:"This component only provides formatting instructions and parsing functionality. It does not include a prompt. You'll need to connect it to a separate Prompt component to create the actual prompt template for the LLM to use."})}),"\n",(0,r.jsxs)(t.p,{children:["Both the ",(0,r.jsx)(t.strong,{children:"Output Parser"})," and ",(0,r.jsx)(t.strong,{children:"Structured Output"})," components format LLM responses, but they have different use cases.\nThe ",(0,r.jsx)(t.strong,{children:"Output Parser"})," is simpler and focused on converting responses into comma-separated lists. 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This supersedes the database selection."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"collection_name"}),(0,n.jsx)(t.td,{children:"Collection"}),(0,n.jsx)(t.td,{children:"The name of the collection within Astra DB where the vectors are stored."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"keyspace"}),(0,n.jsx)(t.td,{children:"Keyspace"}),(0,n.jsx)(t.td,{children:"An optional keyspace within Astra DB to use for the collection."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding_choice"}),(0,n.jsx)(t.td,{children:"Embedding Model or Astra Vectorize"}),(0,n.jsx)(t.td,{children:"Choose an embedding model or use Astra vectorize."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding_model"}),(0,n.jsx)(t.td,{children:"Embedding Model"}),(0,n.jsx)(t.td,{children:"Specify the embedding model. 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The options are ",(0,n.jsx)(t.code,{children:"Similarity"}),", ",(0,n.jsx)(t.code,{children:"Similarity with score threshold"}),", and ",(0,n.jsx)(t.code,{children:"MMR (Max Marginal Relevance)"}),"."]})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_score_threshold"}),(0,n.jsx)(t.td,{children:"Search Score Threshold"}),(0,n.jsxs)(t.td,{children:["The minimum similarity score threshold for search results when using the ",(0,n.jsx)(t.code,{children:"Similarity with score threshold"})," option."]})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"advanced_search_filter"}),(0,n.jsx)(t.td,{children:"Search Metadata Filter"}),(0,n.jsx)(t.td,{children:"An optional dictionary of filters to apply to the search query."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"autodetect_collection"}),(0,n.jsx)(t.td,{children:"Autodetect Collection"}),(0,n.jsx)(t.td,{children:"A boolean flag to determine whether to autodetect the collection."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"content_field"}),(0,n.jsx)(t.td,{children:"Content Field"}),(0,n.jsx)(t.td,{children:"A field to use as the text content field for the vector store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"deletion_field"}),(0,n.jsx)(t.td,{children:"Deletion Based On Field"}),(0,n.jsx)(t.td,{children:"When provided, documents in the target collection with metadata field values matching the input metadata field value are deleted before new data is loaded."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ignore_invalid_documents"}),(0,n.jsx)(t.td,{children:"Ignore Invalid Documents"}),(0,n.jsx)(t.td,{children:"A boolean flag to determine whether to ignore invalid documents at runtime."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"astradb_vectorstore_kwargs"}),(0,n.jsx)(t.td,{children:"AstraDBVectorStore Parameters"}),(0,n.jsx)(t.td,{children:"An optional dictionary of additional parameters for the AstraDBVectorStore."})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Display Name"}),(0,n.jsx)(t.th,{children:"Info"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"Vector Store"}),(0,n.jsx)(t.td,{children:"Astra DB vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_results"}),(0,n.jsx)(t.td,{children:"Search Results"}),(0,n.jsxs)(t.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"generate-embeddings",children:"Generate embeddings"}),"\n",(0,n.jsxs)(t.p,{children:["The ",(0,n.jsx)(t.strong,{children:"Astra DB Vector Store"})," component offers two methods for generating embeddings."]}),"\n",(0,n.jsxs)(t.ol,{children:["\n",(0,n.jsxs)(t.li,{children:["\n",(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.strong,{children:"Embedding Model"}),": Use your own embedding model by connecting an ",(0,n.jsx)(t.a,{href:"/components-embedding-models",children:"Embeddings"})," component in Langflow."]}),"\n"]}),"\n",(0,n.jsxs)(t.li,{children:["\n",(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.strong,{children:"Astra Vectorize"}),": Use Astra DB's built-in embedding generation service. When creating a new collection, choose the embeddings provider and models, including NVIDIA's ",(0,n.jsx)(t.code,{children:"NV-Embed-QA"})," model hosted by Datastax."]}),"\n"]}),"\n"]}),"\n",(0,n.jsx)(t.admonition,{type:"important",children:(0,n.jsx)(t.p,{children:"The embedding model selection is made when creating a new collection and cannot be changed later."})}),"\n",(0,n.jsxs)(t.p,{children:["For an example of using the ",(0,n.jsx)(t.strong,{children:"Astra DB Vector Store"})," component with an embedding model, see the ",(0,n.jsx)(t.a,{href:"/starter-projects-vector-store-rag",children:"Vector Store RAG starter project"}),"."]}),"\n",(0,n.jsxs)(t.p,{children:["For more information, see the ",(0,n.jsx)(t.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html",children:"Astra DB Serverless documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"hybrid-search",children:"Hybrid search"}),"\n",(0,n.jsxs)(t.p,{children:["The ",(0,n.jsx)(t.strong,{children:"Astra DB"})," component includes ",(0,n.jsx)(t.strong,{children:"hybrid search"}),", which is enabled by default."]}),"\n",(0,n.jsxs)(t.p,{children:["The component fields related to hybrid search are ",(0,n.jsx)(t.strong,{children:"Search Query"}),", ",(0,n.jsx)(t.strong,{children:"Lexical Terms"}),", and ",(0,n.jsx)(t.strong,{children:"Reranker"}),"."]}),"\n",(0,n.jsxs)(t.ul,{children:["\n",(0,n.jsxs)(t.li,{children:[(0,n.jsx)(t.strong,{children:"Search Query"})," finds results by vector similarity."]}),"\n",(0,n.jsxs)(t.li,{children:[(0,n.jsx)(t.strong,{children:"Lexical Terms"})," is a comma-separated string of keywords, like ",(0,n.jsx)(t.code,{children:"features, data, attributes, characteristics"}),"."]}),"\n",(0,n.jsxs)(t.li,{children:[(0,n.jsx)(t.strong,{children:"Reranker"})," is the re-ranker model used in the hybrid search.\nThe re-ranker model is ",(0,n.jsx)(t.code,{children:"nvidia/llama-3.2-nv.reranker"}),"."]}),"\n"]}),"\n",(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/hybrid-search.html",children:"Hybrid search"})," performs a vector similarity search and a lexical search, compares the results of both searches, and then returns the most relevant results overall."]}),"\n",(0,n.jsx)(t.admonition,{type:"important",children:(0,n.jsxs)(t.p,{children:["To use hybrid search, your collection must be created with vector, lexical, and rerank capabilities enabled. These capabilities are enabled by default when you create a collection in a database in the AWS us-east-2 region.\nFor more information, see the ",(0,n.jsx)(t.a,{href:"https://docs.datastax.com/en/astra-db-serverless/api-reference/collection-methods/create-collection.html#example-hybrid",children:"DataStax documentation"}),"."]})}),"\n",(0,n.jsxs)(t.p,{children:["To use ",(0,n.jsx)(t.strong,{children:"Hybrid search"})," in the ",(0,n.jsx)(t.strong,{children:"Astra DB"})," component, do the following:"]}),"\n",(0,n.jsxs)(t.ol,{children:["\n",(0,n.jsxs)(t.li,{children:["Click ",(0,n.jsx)(t.strong,{children:"New Flow"})," > ",(0,n.jsx)(t.strong,{children:"RAG"})," > ",(0,n.jsx)(t.strong,{children:"Hybrid Search RAG"}),"."]}),"\n",(0,n.jsxs)(t.li,{children:["In the ",(0,n.jsx)(t.strong,{children:"OpenAI"})," model component, add your ",(0,n.jsx)(t.strong,{children:"OpenAI API key"}),"."]}),"\n",(0,n.jsxs)(t.li,{children:["In the ",(0,n.jsx)(t.strong,{children:"Astra DB"})," vector store component, add your ",(0,n.jsx)(t.strong,{children:"Astra DB Application Token"}),"."]}),"\n",(0,n.jsxs)(t.li,{children:["In the ",(0,n.jsx)(t.strong,{children:"Database"})," field, select your database."]}),"\n",(0,n.jsxs)(t.li,{children:["In the ",(0,n.jsx)(t.strong,{children:"Collection"})," field, select or create a collection with hybrid search capabilities enabled."]}),"\n",(0,n.jsxs)(t.li,{children:["In the ",(0,n.jsx)(t.strong,{children:"Playground"}),", enter a question about your data, such as ",(0,n.jsx)(t.code,{children:"What are the features of my data?"}),"\nYour query is sent to two components: an ",(0,n.jsx)(t.strong,{children:"OpenAI"})," model component and the ",(0,n.jsx)(t.strong,{children:"Astra DB"})," vector database component.\nThe ",(0,n.jsx)(t.strong,{children:"OpenAI"})," component contains a prompt for creating the lexical query from your input:"]}),"\n"]}),"\n",(0,n.jsx)(o.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"You are a database query planner that takes a user's requests, and then converts to a search against the subject matter in question.",props:{}}]},{tokens:[{content:"You should convert the query into:",props:{}}]},{tokens:[{content:"1. A list of keywords to use against a Lucene text analyzer index, no more than 4. Strictly unigrams.",props:{}}]},{tokens:[{content:"2. A question to use as the basis for a QA embedding engine.",props:{}}]},{tokens:[{content:"Avoid common keywords associated with the user's subject matter.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,n.jsxs)(t.ol,{start:"7",children:["\n",(0,n.jsxs)(t.li,{children:["To view the keywords and questions the ",(0,n.jsx)(t.strong,{children:"OpenAI"})," component generates from your collection, in the ",(0,n.jsx)(t.strong,{children:"OpenAI"})," component, click ",(0,n.jsx)(c.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n"]}),"\n",(0,n.jsx)(o.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"1. Keywords: features, data, attributes, characteristics",props:{}}]},{tokens:[{content:"2. Question: What characteristics can be identified in my data?",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,n.jsxs)(t.ol,{start:"8",children:["\n",(0,n.jsxs)(t.li,{children:["\n",(0,n.jsxs)(t.p,{children:["To view the ",(0,n.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," generated from the ",(0,n.jsx)(t.strong,{children:"OpenAI"})," component's response, in the ",(0,n.jsx)(t.strong,{children:"Structured Output"})," component, click ",(0,n.jsx)(c.A,{name:"TextSearch","aria-label":"Inspect icon"}),".\nThe DataFrame is passed to a ",(0,n.jsx)(t.strong,{children:"Parser"})," component, which parses the contents of the ",(0,n.jsx)(t.strong,{children:"Keywords"})," column into a string."]}),"\n",(0,n.jsxs)(t.p,{children:["This string of comma-separated words is passed to the ",(0,n.jsx)(t.strong,{children:"Lexical Terms"})," port of the ",(0,n.jsx)(t.strong,{children:"Astra DB"})," component.\nNote that the ",(0,n.jsx)(t.strong,{children:"Search Query"})," port of the Astra DB port is connected to the ",(0,n.jsx)(t.strong,{children:"Chat Input"})," component from step 6.\nThis ",(0,n.jsx)(t.strong,{children:"Search Query"})," is vectorized, and both the ",(0,n.jsx)(t.strong,{children:"Search Query"})," and ",(0,n.jsx)(t.strong,{children:"Lexical Terms"})," content are sent to the reranker at the ",(0,n.jsx)(t.code,{children:"find_and_rerank"})," endpoint."]}),"\n",(0,n.jsxs)(t.p,{children:["The reranker compares the vector search results against the string of terms from the lexical search.\nThe highest-ranked results of your hybrid search are returned to the ",(0,n.jsx)(t.strong,{children:"Playground"}),"."]}),"\n"]}),"\n"]}),"\n",(0,n.jsxs)(t.p,{children:["For more information, see the ",(0,n.jsx)(t.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/hybrid-search.html",children:"DataStax documentation"}),"."]}),"\n",(0,n.jsx)(t.h2,{id:"astradb-graph-vector-store",children:"AstraDB Graph vector store"}),"\n",(0,n.jsxs)(t.p,{children:["This component implements a Vector Store using AstraDB with graph capabilities.\nFor more information, see the ",(0,n.jsx)(t.a,{href:"https://docs.datastax.com/en/astra-db-serverless/tutorials/graph-rag.html",children:"Astra DB Serverless documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-1",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Display Name"}),(0,n.jsx)(t.th,{children:"Info"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"collection_name"}),(0,n.jsx)(t.td,{children:"Collection Name"}),(0,n.jsx)(t.td,{children:"The name of the collection within AstraDB where the vectors will be stored (required)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"token"}),(0,n.jsx)(t.td,{children:"Astra DB Application Token"}),(0,n.jsx)(t.td,{children:"Authentication token for accessing AstraDB (required)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"api_endpoint"}),(0,n.jsx)(t.td,{children:"API Endpoint"}),(0,n.jsx)(t.td,{children:"API endpoint URL for the AstraDB service (required)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_input"}),(0,n.jsx)(t.td,{children:"Search Input"}),(0,n.jsx)(t.td,{children:"Query string for similarity search"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ingest_data"}),(0,n.jsx)(t.td,{children:"Ingest Data"}),(0,n.jsx)(t.td,{children:"Data to be ingested into the vector store"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"namespace"}),(0,n.jsx)(t.td,{children:"Namespace"}),(0,n.jsx)(t.td,{children:"Optional namespace within AstraDB to use for the collection"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding"}),(0,n.jsx)(t.td,{children:"Embedding Model"}),(0,n.jsx)(t.td,{children:"Embedding model to use"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"metric"}),(0,n.jsx)(t.td,{children:"Metric"}),(0,n.jsx)(t.td,{children:'Distance metric for vector comparisons (options: "cosine", "euclidean", "dot_product")'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"setup_mode"}),(0,n.jsx)(t.td,{children:"Setup Mode"}),(0,n.jsx)(t.td,{children:'Configuration mode for setting up the vector store (options: "Sync", "Async", "Off")'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"pre_delete_collection"}),(0,n.jsx)(t.td,{children:"Pre Delete Collection"}),(0,n.jsx)(t.td,{children:"Boolean flag to determine whether to delete the collection before creating a new one"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"number_of_results"}),(0,n.jsx)(t.td,{children:"Number of Results"}),(0,n.jsx)(t.td,{children:"Number of results to return in similarity search (default: 4)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_type"}),(0,n.jsx)(t.td,{children:"Search Type"}),(0,n.jsx)(t.td,{children:'Search type to use (options: "Similarity", "Graph Traversal", "Hybrid")'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"traversal_depth"}),(0,n.jsx)(t.td,{children:"Traversal Depth"}),(0,n.jsx)(t.td,{children:"Maximum depth for graph traversal searches (default: 1)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_score_threshold"}),(0,n.jsx)(t.td,{children:"Search Score Threshold"}),(0,n.jsx)(t.td,{children:"Minimum similarity score threshold for search results"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_filter"}),(0,n.jsx)(t.td,{children:"Search Metadata Filter"}),(0,n.jsx)(t.td,{children:"Optional dictionary of filters to apply to the search query"})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs-1",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Display Name"}),(0,n.jsx)(t.th,{children:"Info"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"Vector Store"}),(0,n.jsx)(t.td,{children:"Astra DB graph vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_results"}),(0,n.jsx)(t.td,{children:"Search Results"}),(0,n.jsxs)(t.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(t.code,{children:"Data"})," objects."]})]})]})]}),"\n",(0,n.jsx)(t.h2,{id:"cassandra",children:"Cassandra"}),"\n",(0,n.jsxs)(t.p,{children:["This component creates a Cassandra Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(t.a,{href:"https://cassandra.apache.org/doc/latest/cassandra/vector-search/overview.html",children:"Cassandra documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-2",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"database_ref"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Contact points for the database or AstraDB database ID"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"username"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Username for the database (leave empty for AstraDB)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"token"}),(0,n.jsx)(t.td,{children:"SecretString"}),(0,n.jsx)(t.td,{children:"User password for the database or AstraDB token"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"keyspace"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Table Keyspace or AstraDB namespace"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"table_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Name of the table or AstraDB collection"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ttl_seconds"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Time-to-live for added texts"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"batch_size"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Number of data to process in a single batch"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"setup_mode"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Configuration mode for setting up the Cassandra table"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"cluster_kwargs"}),(0,n.jsx)(t.td,{children:"Dict"}),(0,n.jsx)(t.td,{children:"Additional keyword arguments for the Cassandra cluster"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_query"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Query for similarity search"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ingest_data"}),(0,n.jsx)(t.td,{children:"Data"}),(0,n.jsx)(t.td,{children:"Data to be ingested into the vector store"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding"}),(0,n.jsx)(t.td,{children:"Embeddings"}),(0,n.jsx)(t.td,{children:"Embedding function to use"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"number_of_results"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Number of results to return in search"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_type"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Type of search to perform"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_score_threshold"}),(0,n.jsx)(t.td,{children:"Float"}),(0,n.jsx)(t.td,{children:"Minimum similarity score for search results"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_filter"}),(0,n.jsx)(t.td,{children:"Dict"}),(0,n.jsx)(t.td,{children:"Metadata filters for search query"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"body_search"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Document textual search terms"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"enable_body_search"}),(0,n.jsx)(t.td,{children:"Boolean"}),(0,n.jsx)(t.td,{children:"Flag to enable body 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capabilities."}),"\n",(0,n.jsx)(t.h3,{id:"inputs-3",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Display Name"}),(0,n.jsx)(t.th,{children:"Info"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"database_ref"}),(0,n.jsx)(t.td,{children:"Contact Points / Astra Database ID"}),(0,n.jsx)(t.td,{children:"Contact points for the database or AstraDB database ID (required)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"username"}),(0,n.jsx)(t.td,{children:"Username"}),(0,n.jsx)(t.td,{children:"Username for the database (leave empty for AstraDB)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"token"}),(0,n.jsx)(t.td,{children:"Password / AstraDB Token"}),(0,n.jsx)(t.td,{children:"User password for the database or AstraDB token 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",(0,n.jsx)(t.strong,{children:"Data"})," or ",(0,n.jsx)(t.strong,{children:"DataFrame"}),".\nThis example splits text from a ",(0,n.jsx)(t.a,{href:"/components-data#url",children:"URL"})," component, and computes embeddings with the connected ",(0,n.jsx)(t.strong,{children:"OpenAI Embeddings"})," component. Chroma DB computes embeddings by default, but you can connect your own embeddings model, as seen in this example."]}),"\n"]}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.img,{alt:"ChromaDB receiving split text",src:r(88690).A+"",width:"1127",height:"811"})}),"\n",(0,n.jsxs)(t.ol,{start:"2",children:["\n",(0,n.jsxs)(t.li,{children:["In the ",(0,n.jsx)(t.strong,{children:"Chroma DB"})," component, in the ",(0,n.jsx)(t.strong,{children:"Collection"})," field, enter a name for your embeddings collection."]}),"\n",(0,n.jsxs)(t.li,{children:["Optionally, to persist the Chroma database, in the ",(0,n.jsx)(t.strong,{children:"Persist"})," field, enter a directory to store the ",(0,n.jsx)(t.code,{children:"chroma.sqlite3"})," file.\nThis example uses ",(0,n.jsx)(t.code,{children:"./chroma-db"})," to create a directory relative to where Langflow is running."]}),"\n",(0,n.jsxs)(t.li,{children:["To load data and embeddings into your Chroma database, in the ",(0,n.jsx)(t.strong,{children:"Chroma DB"})," component, click ",(0,n.jsx)(c.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n"]}),"\n",(0,n.jsx)(t.admonition,{type:"tip",children:(0,n.jsxs)(t.p,{children:["When loading duplicate documents, enable the ",(0,n.jsx)(t.strong,{children:"Allow Duplicates"})," option in Chroma DB if you want to store multiple copies of the same content, or disable it to automatically deduplicate your data."]})}),"\n",(0,n.jsxs)(t.ol,{start:"5",children:["\n",(0,n.jsxs)(t.li,{children:["To view the split data, in the ",(0,n.jsx)(t.strong,{children:"Split Text"})," component, click ",(0,n.jsx)(c.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n",(0,n.jsxs)(t.li,{children:["To query your loaded data, open the ",(0,n.jsx)(t.strong,{children:"Playground"})," and query your database.\nYour input is converted to vector data and compared to the stored vectors in a vector similarity search."]}),"\n"]}),"\n",(0,n.jsxs)(t.p,{children:["For more information, see the ",(0,n.jsx)(t.a,{href:"https://docs.trychroma.com/",children:"Chroma documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-4",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"collection_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:'The name of the Chroma collection. 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(required)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"bucket_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Name of the Couchbase bucket (required)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"scope_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Name of the Couchbase scope (required)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"collection_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Name of the Couchbase collection (required)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"index_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Name of the Couchbase index (required)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_query"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"The query to search for in the vector 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Default: 4 (advanced)."})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs-6",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsx)(t.tbody,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"CouchbaseVectorStore"}),(0,n.jsx)(t.td,{children:"A Couchbase vector store instance configured with the specified parameters."})]})})]}),"\n",(0,n.jsx)(t.h2,{id:"local-db",children:"Local DB"}),"\n",(0,n.jsxs)(t.p,{children:["The ",(0,n.jsx)(t.strong,{children:"Local DB"})," component is Langflow's enhanced version of Chroma DB."]}),"\n",(0,n.jsx)(t.p,{children:"The component adds a user-friendly interface with two modes (Ingest and Retrieve), automatic collection management, and built-in persistence in Langflow's cache directory."}),"\n",(0,n.jsxs)(t.p,{children:["Local DB includes ",(0,n.jsx)(t.strong,{children:"Ingest"})," and ",(0,n.jsx)(t.strong,{children:"Retrieve"})," modes."]}),"\n",(0,n.jsxs)(t.p,{children:["The ",(0,n.jsx)(t.strong,{children:"Ingest"})," mode works similarly to ",(0,n.jsx)(t.a,{href:"#chroma-db",children:"ChromaDB"}),", and persists your database to the Langflow cache directory. The Langflow cache directory location is specified in ",(0,n.jsx)(t.code,{children:"LANGFLOW_CONFIG_DIR"}),". For more information, see ",(0,n.jsx)(t.a,{href:"/environment-variables",children:"Environment variables"}),"."]}),"\n",(0,n.jsxs)(t.p,{children:["The ",(0,n.jsx)(t.strong,{children:"Retrieve"})," mode can query your ",(0,n.jsx)(t.strong,{children:"Chroma DB"})," collections."]}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.img,{alt:"Local DB retrieving vectors",src:r(60159).A+"",width:"1716",height:"960"})}),"\n",(0,n.jsxs)(t.p,{children:["For more information, see the ",(0,n.jsx)(t.a,{href:"https://docs.trychroma.com/",children:"Chroma documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-7",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"collection_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:'The name of the Chroma collection. Default: "langflow".'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"persist_directory"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsxs)(t.td,{children:["Custom base directory to save the vector store. Collections will be stored under ",(0,n.jsx)(t.code,{children:"{directory}/vector_stores/{collection_name}"}),". If not specified, it will use your system's cache folder."]})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"existing_collections"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Select a previously created collection to search through its stored data."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding"}),(0,n.jsx)(t.td,{children:"Embeddings"}),(0,n.jsx)(t.td,{children:"The embedding function to use for the vector store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"allow_duplicates"}),(0,n.jsx)(t.td,{children:"Boolean"}),(0,n.jsx)(t.td,{children:"If false, will not add documents that are already in the Vector Store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_type"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:'Type of search to perform: "Similarity" or "MMR".'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ingest_data"}),(0,n.jsx)(t.td,{children:"Data/DataFrame"}),(0,n.jsx)(t.td,{children:"Data to store. It will be embedded and indexed for semantic search."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_query"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Enter text to search for similar content in the selected collection."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"number_of_results"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Number of results to return. Default: 10."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"limit"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Limit the number of records to compare when Allow Duplicates is False."})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs-7",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"Chroma"}),(0,n.jsx)(t.td,{children:"A local Chroma vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_results"}),(0,n.jsxs)(t.td,{children:["List",(0,n.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})]}),(0,n.jsx)(t.td,{children:"Results of similarity search."})]})]})]}),"\n",(0,n.jsx)(t.h2,{id:"elasticsearch",children:"Elasticsearch"}),"\n",(0,n.jsxs)(t.p,{children:["This component creates an Elasticsearch Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(t.a,{href:"https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html",children:"Elasticsearch documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-8",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"es_url"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Elasticsearch server URL"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"es_user"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Username for Elasticsearch authentication"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"es_password"}),(0,n.jsx)(t.td,{children:"SecretString"}),(0,n.jsx)(t.td,{children:"Password for Elasticsearch authentication"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"index_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Name of the Elasticsearch index"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"strategy"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:'Strategy for vector search ("approximate_k_nearest_neighbors" or "script_scoring")'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"distance_strategy"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:'Strategy for distance calculation ("COSINE", "EUCLIDEAN_DISTANCE", "DOT_PRODUCT")'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_query"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Query for similarity search"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ingest_data"}),(0,n.jsx)(t.td,{children:"Data"}),(0,n.jsx)(t.td,{children:"Data to be ingested into the vector store"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding"}),(0,n.jsx)(t.td,{children:"Embeddings"}),(0,n.jsx)(t.td,{children:"Embedding function to use"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"number_of_results"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Number of results to return in search (default: 4)"})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs-8",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"ElasticsearchStore"}),(0,n.jsx)(t.td,{children:"Elasticsearch vector store instance"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_results"}),(0,n.jsx)(t.td,{children:"List[Data]"}),(0,n.jsx)(t.td,{children:"Results of similarity search"})]})]})]}),"\n",(0,n.jsx)(t.h2,{id:"faiss",children:"FAISS"}),"\n",(0,n.jsxs)(t.p,{children:["This component creates a FAISS Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(t.a,{href:"https://faiss.ai/index.html",children:"FAISS documentation"}),"."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-9",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"index_name"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:'The name of the FAISS index. Default: "langflow_index".'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"persist_directory"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"Path to save the FAISS index. It will be relative to where Langflow is running."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_query"}),(0,n.jsx)(t.td,{children:"String"}),(0,n.jsx)(t.td,{children:"The query to search for in the vector store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"ingest_data"}),(0,n.jsx)(t.td,{children:"Data"}),(0,n.jsx)(t.td,{children:"The data to ingest into the vector store (list of Data objects or documents)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"allow_dangerous_deserialization"}),(0,n.jsx)(t.td,{children:"Boolean"}),(0,n.jsx)(t.td,{children:"Set to True to allow loading pickle files from untrusted sources. Default: True (advanced)."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding"}),(0,n.jsx)(t.td,{children:"Embeddings"}),(0,n.jsx)(t.td,{children:"The embedding function to use for the vector store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"number_of_results"}),(0,n.jsx)(t.td,{children:"Integer"}),(0,n.jsx)(t.td,{children:"Number of results to return from the search. Default: 4 (advanced)."})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs-9",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsx)(t.tbody,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"FAISS"}),(0,n.jsx)(t.td,{children:"A FAISS vector store instance configured with the specified parameters."})]})})]}),"\n",(0,n.jsx)(t.h2,{id:"graph-rag",children:"Graph RAG"}),"\n",(0,n.jsxs)(t.p,{children:["This component performs Graph RAG (Retrieval Augmented Generation) traversal in a vector store, enabling graph-based document retrieval.\nFor more information, see the ",(0,n.jsx)(t.a,{href:"https://datastax.github.io/graph-rag/",children:"Graph RAG documentation"}),"."]}),"\n",(0,n.jsxs)(t.p,{children:["For an example flow, see the ",(0,n.jsx)(t.strong,{children:"Graph RAG"})," template."]}),"\n",(0,n.jsx)(t.h3,{id:"inputs-10",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Display Name"}),(0,n.jsx)(t.th,{children:"Info"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"embedding_model"}),(0,n.jsx)(t.td,{children:"Embedding Model"}),(0,n.jsxs)(t.td,{children:["Specify the embedding model. This is not required for collections embedded with ",(0,n.jsx)(t.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html",children:"Astra vectorize"}),"."]})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"vector_store"}),(0,n.jsx)(t.td,{children:"Vector Store Connection"}),(0,n.jsx)(t.td,{children:"Connection to the vector store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"edge_definition"}),(0,n.jsx)(t.td,{children:"Edge Definition"}),(0,n.jsxs)(t.td,{children:["Edge definition for the graph traversal. For more information, see the ",(0,n.jsx)(t.a,{href:"https://datastax.github.io/graph-rag/reference/graph_retriever/edges/",children:"GraphRAG documentation"}),"."]})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"strategy"}),(0,n.jsx)(t.td,{children:"Traversal Strategies"}),(0,n.jsx)(t.td,{children:"The strategy to use for graph traversal. Strategy options are dynamically loaded from available strategies."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_query"}),(0,n.jsx)(t.td,{children:"Search Query"}),(0,n.jsx)(t.td,{children:"The query to search for in the vector store."})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"graphrag_strategy_kwargs"}),(0,n.jsx)(t.td,{children:"Strategy Parameters"}),(0,n.jsxs)(t.td,{children:["Optional dictionary of additional parameters for the retrieval strategy. For more information, see the ",(0,n.jsx)(t.a,{href:"https://datastax.github.io/graph-rag/reference/graph_retriever/strategies/",children:"strategy documentation"}),"."]})]})]})]}),"\n",(0,n.jsx)(t.h3,{id:"outputs-10",children:"Outputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Type"}),(0,n.jsx)(t.th,{children:"Description"})]})}),(0,n.jsx)(t.tbody,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"search_results"}),(0,n.jsx)(t.td,{children:"List[Data]"}),(0,n.jsxs)(t.td,{children:["Results of the graph-based document retrieval as a list of ",(0,n.jsx)(t.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]})})]}),"\n",(0,n.jsx)(t.h2,{id:"hyper-converged-database-hcd-vector-store",children:"Hyper-Converged Database (HCD) Vector Store"}),"\n",(0,n.jsx)(t.p,{children:"This component implements a Vector Store using HCD."}),"\n",(0,n.jsxs)(t.p,{children:["To use the HCD vector store, add your deployment's collection name, username, password, and HCD Data API endpoint.\nThe endpoint must be formatted like ",(0,n.jsx)(t.code,{children:"http[s]://**DOMAIN_NAME** or **IP_ADDRESS**[:port]"}),", for example, ",(0,n.jsx)(t.code,{children:"http://192.0.2.250:8181"}),"."]}),"\n",(0,n.jsxs)(t.p,{children:["Replace ",(0,n.jsx)(t.strong,{children:"DOMAIN_NAME"})," or ",(0,n.jsx)(t.strong,{children:"IP_ADDRESS"})," with the domain name or IP address of your HCD Data API connection."]}),"\n",(0,n.jsx)(t.p,{children:"To use the HCD vector store for embeddings ingestion, connect it to an embeddings model and a file loader:"}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.img,{alt:"HCD vector store embeddings ingestion",src:r(42638).A+"",width:"2294",height:"1684"})}),"\n",(0,n.jsx)(t.h3,{id:"inputs-11",children:"Inputs"}),"\n",(0,n.jsxs)(t.table,{children:[(0,n.jsx)(t.thead,{children:(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.th,{children:"Name"}),(0,n.jsx)(t.th,{children:"Display Name"}),(0,n.jsx)(t.th,{children:"Info"})]})}),(0,n.jsxs)(t.tbody,{children:[(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"collection_name"}),(0,n.jsx)(t.td,{children:"Collection Name"}),(0,n.jsx)(t.td,{children:"The name of the collection within HCD where the vectors will be stored (required)"})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"username"}),(0,n.jsx)(t.td,{children:"HCD Username"}),(0,n.jsx)(t.td,{children:'Authentication username for accessing HCD (default: "hcd-superuser", required)'})]}),(0,n.jsxs)(t.tr,{children:[(0,n.jsx)(t.td,{children:"password"}),(0,n.jsx)(t.td,{children:"HCD Password"}),(0,n.jsx)(t.td,{children:"Authentication password for accessing HCD 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The options are ",(0,n.jsx)(r.code,{children:"Similarity"}),", ",(0,n.jsx)(r.code,{children:"Similarity with score threshold"}),", and ",(0,n.jsx)(r.code,{children:"MMR (Max Marginal Relevance)"}),"."]})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_score_threshold"}),(0,n.jsx)(r.td,{children:"Search Score Threshold"}),(0,n.jsxs)(r.td,{children:["The minimum similarity score threshold for search results when using the ",(0,n.jsx)(r.code,{children:"Similarity with score threshold"})," option."]})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"advanced_search_filter"}),(0,n.jsx)(r.td,{children:"Search Metadata Filter"}),(0,n.jsx)(r.td,{children:"An optional dictionary of filters to apply to the search query."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"autodetect_collection"}),(0,n.jsx)(r.td,{children:"Autodetect Collection"}),(0,n.jsx)(r.td,{children:"A boolean flag to determine whether to autodetect the collection."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"content_field"}),(0,n.jsx)(r.td,{children:"Content Field"}),(0,n.jsx)(r.td,{children:"A field to use as the text content field for the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"deletion_field"}),(0,n.jsx)(r.td,{children:"Deletion Based On Field"}),(0,n.jsx)(r.td,{children:"When provided, documents in the target collection with metadata field values matching the input metadata field value are deleted before new data is loaded."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ignore_invalid_documents"}),(0,n.jsx)(r.td,{children:"Ignore Invalid Documents"}),(0,n.jsx)(r.td,{children:"A boolean flag to determine whether to ignore invalid documents at runtime."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"astradb_vectorstore_kwargs"}),(0,n.jsx)(r.td,{children:"AstraDBVectorStore Parameters"}),(0,n.jsx)(r.td,{children:"An optional dictionary of additional parameters for the AstraDBVectorStore."})]})]})]}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Outputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"vector_store"}),(0,n.jsx)(r.td,{children:"Vector Store"}),(0,n.jsx)(r.td,{children:"The Astra DB vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_results"}),(0,n.jsx)(r.td,{children:"Search Results"}),(0,n.jsxs)(r.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(r.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]})]})]})]}),"\n",(0,n.jsx)(r.h3,{id:"generate-embeddings",children:"Generate embeddings"}),"\n",(0,n.jsxs)(r.p,{children:["The ",(0,n.jsx)(r.strong,{children:"Astra DB Vector Store"})," component offers two methods for generating embeddings."]}),"\n",(0,n.jsxs)(r.ol,{children:["\n",(0,n.jsxs)(r.li,{children:["\n",(0,n.jsxs)(r.p,{children:[(0,n.jsx)(r.strong,{children:"Embedding Model"}),": Use your own embedding model by connecting an ",(0,n.jsx)(r.a,{href:"/components-embedding-models",children:"Embeddings"})," component in Langflow."]}),"\n"]}),"\n",(0,n.jsxs)(r.li,{children:["\n",(0,n.jsxs)(r.p,{children:[(0,n.jsx)(r.strong,{children:"Astra Vectorize"}),": Use Astra DB's built-in embedding generation service. When creating a new collection, choose the embeddings provider and models, including NVIDIA's ",(0,n.jsx)(r.code,{children:"NV-Embed-QA"})," model hosted by Datastax."]}),"\n"]}),"\n"]}),"\n",(0,n.jsx)(r.admonition,{type:"important",children:(0,n.jsx)(r.p,{children:"The embedding model selection is made when creating a new collection and cannot be changed later."})}),"\n",(0,n.jsxs)(r.p,{children:["For an example of using the ",(0,n.jsx)(r.strong,{children:"Astra DB Vector Store"})," component with an embedding model, see the ",(0,n.jsx)(r.a,{href:"/starter-projects-vector-store-rag",children:"Vector Store RAG starter project"}),"."]}),"\n",(0,n.jsxs)(r.p,{children:["For more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html",children:"Astra DB Serverless documentation"}),"."]}),"\n",(0,n.jsx)(r.h3,{id:"hybrid-search",children:"Hybrid search"}),"\n",(0,n.jsxs)(r.p,{children:["The ",(0,n.jsx)(r.strong,{children:"Astra DB"})," component includes ",(0,n.jsx)(r.strong,{children:"hybrid search"}),", which is enabled by default."]}),"\n",(0,n.jsxs)(r.p,{children:["The component fields related to hybrid search are ",(0,n.jsx)(r.strong,{children:"Search Query"}),", ",(0,n.jsx)(r.strong,{children:"Lexical Terms"}),", and ",(0,n.jsx)(r.strong,{children:"Reranker"}),"."]}),"\n",(0,n.jsxs)(r.ul,{children:["\n",(0,n.jsxs)(r.li,{children:[(0,n.jsx)(r.strong,{children:"Search Query"})," finds results by vector similarity."]}),"\n",(0,n.jsxs)(r.li,{children:[(0,n.jsx)(r.strong,{children:"Lexical Terms"})," is a comma-separated string of keywords, like ",(0,n.jsx)(r.code,{children:"features, data, attributes, characteristics"}),"."]}),"\n",(0,n.jsxs)(r.li,{children:[(0,n.jsx)(r.strong,{children:"Reranker"})," is the re-ranker model used in the hybrid search.\nThe re-ranker model is ",(0,n.jsx)(r.code,{children:"nvidia/llama-3.2-nv.reranker"}),"."]}),"\n"]}),"\n",(0,n.jsxs)(r.p,{children:[(0,n.jsx)(r.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/hybrid-search.html",children:"Hybrid search"})," performs a vector similarity search and a lexical search, compares the results of both searches, and then returns the most relevant results overall."]}),"\n",(0,n.jsx)(r.admonition,{type:"important",children:(0,n.jsxs)(r.p,{children:["To use hybrid search, your collection must be created with vector, lexical, and rerank capabilities enabled. These capabilities are enabled by default when you create a collection in a database in the AWS us-east-2 region.\nFor more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.datastax.com/en/astra-db-serverless/api-reference/collection-methods/create-collection.html#example-hybrid",children:"DataStax documentation"}),"."]})}),"\n",(0,n.jsxs)(r.p,{children:["To use ",(0,n.jsx)(r.strong,{children:"Hybrid search"})," in the ",(0,n.jsx)(r.strong,{children:"Astra DB"})," component, do the following:"]}),"\n",(0,n.jsxs)(r.ol,{children:["\n",(0,n.jsxs)(r.li,{children:["Click ",(0,n.jsx)(r.strong,{children:"New Flow"})," > ",(0,n.jsx)(r.strong,{children:"RAG"})," > ",(0,n.jsx)(r.strong,{children:"Hybrid Search RAG"}),"."]}),"\n",(0,n.jsxs)(r.li,{children:["In the ",(0,n.jsx)(r.strong,{children:"OpenAI"})," model component, add your ",(0,n.jsx)(r.strong,{children:"OpenAI API key"}),"."]}),"\n",(0,n.jsxs)(r.li,{children:["In the ",(0,n.jsx)(r.strong,{children:"Astra DB"})," vector store component, add your ",(0,n.jsx)(r.strong,{children:"Astra DB Application Token"}),"."]}),"\n",(0,n.jsxs)(r.li,{children:["In the ",(0,n.jsx)(r.strong,{children:"Database"})," field, select your database."]}),"\n",(0,n.jsxs)(r.li,{children:["In the ",(0,n.jsx)(r.strong,{children:"Collection"})," field, select or create a collection with hybrid search capabilities enabled."]}),"\n",(0,n.jsxs)(r.li,{children:["In the ",(0,n.jsx)(r.strong,{children:"Playground"}),", enter a question about your data, such as ",(0,n.jsx)(r.code,{children:"What are the features of my data?"}),"\nYour query is sent to two components: an ",(0,n.jsx)(r.strong,{children:"OpenAI"})," model component and the ",(0,n.jsx)(r.strong,{children:"Astra DB"})," vector database component.\nThe ",(0,n.jsx)(r.strong,{children:"OpenAI"})," component contains a prompt for creating the lexical query from your input:"]}),"\n"]}),"\n",(0,n.jsx)(o.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"You are a database query planner that takes a user's requests, and then converts to a search against the subject matter in question.",props:{}}]},{tokens:[{content:"You should convert the query into:",props:{}}]},{tokens:[{content:"1. A list of keywords to use against a Lucene text analyzer index, no more than 4. Strictly unigrams.",props:{}}]},{tokens:[{content:"2. A question to use as the basis for a QA embedding engine.",props:{}}]},{tokens:[{content:"Avoid common keywords associated with the user's subject matter.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,n.jsxs)(r.ol,{start:"7",children:["\n",(0,n.jsxs)(r.li,{children:["To view the keywords and questions the ",(0,n.jsx)(r.strong,{children:"OpenAI"})," component generates from your collection, in the ",(0,n.jsx)(r.strong,{children:"OpenAI"})," component, click ",(0,n.jsx)(c.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n"]}),"\n",(0,n.jsx)(o.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"1. Keywords: features, data, attributes, characteristics",props:{}}]},{tokens:[{content:"2. Question: What characteristics can be identified in my data?",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,n.jsxs)(r.ol,{start:"8",children:["\n",(0,n.jsxs)(r.li,{children:["\n",(0,n.jsxs)(r.p,{children:["To view the ",(0,n.jsx)(r.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," generated from the ",(0,n.jsx)(r.strong,{children:"OpenAI"})," component's response, in the ",(0,n.jsx)(r.strong,{children:"Structured Output"})," component, click ",(0,n.jsx)(c.A,{name:"TextSearch","aria-label":"Inspect icon"}),".\nThe DataFrame is passed to a ",(0,n.jsx)(r.strong,{children:"Parser"})," component, which parses the contents of the ",(0,n.jsx)(r.strong,{children:"Keywords"})," column into a string."]}),"\n",(0,n.jsxs)(r.p,{children:["This string of comma-separated words is passed to the ",(0,n.jsx)(r.strong,{children:"Lexical Terms"})," port of the ",(0,n.jsx)(r.strong,{children:"Astra DB"})," component.\nNote that the ",(0,n.jsx)(r.strong,{children:"Search Query"})," port of the Astra DB port is connected to the ",(0,n.jsx)(r.strong,{children:"Chat Input"})," component from step 6.\nThis ",(0,n.jsx)(r.strong,{children:"Search Query"})," is vectorized, and both the ",(0,n.jsx)(r.strong,{children:"Search Query"})," and ",(0,n.jsx)(r.strong,{children:"Lexical Terms"})," content are sent to the reranker at the ",(0,n.jsx)(r.code,{children:"find_and_rerank"})," endpoint."]}),"\n",(0,n.jsxs)(r.p,{children:["The reranker compares the vector search results against the string of terms from the lexical search.\nThe highest-ranked results of your hybrid search are returned to the ",(0,n.jsx)(r.strong,{children:"Playground"}),"."]}),"\n"]}),"\n"]}),"\n",(0,n.jsxs)(r.p,{children:["For more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.datastax.com/en/astra-db-serverless/databases/hybrid-search.html",children:"DataStax documentation"}),"."]}),"\n",(0,n.jsx)(r.h2,{id:"astradb-graph-vector-store",children:"AstraDB Graph vector store"}),"\n",(0,n.jsxs)(r.p,{children:["This component implements a Vector Store using AstraDB with graph capabilities.\nFor more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.datastax.com/en/astra-db-serverless/tutorials/graph-rag.html",children:"Astra DB Serverless documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"collection_name"}),(0,n.jsx)(r.td,{children:"Collection Name"}),(0,n.jsx)(r.td,{children:"The name of the collection within AstraDB where the vectors are stored. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"token"}),(0,n.jsx)(r.td,{children:"Astra DB Application Token"}),(0,n.jsx)(r.td,{children:"Authentication token for accessing AstraDB. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"api_endpoint"}),(0,n.jsx)(r.td,{children:"API Endpoint"}),(0,n.jsx)(r.td,{children:"API endpoint URL for the AstraDB service. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_input"}),(0,n.jsx)(r.td,{children:"Search Input"}),(0,n.jsx)(r.td,{children:"Query string for similarity search."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ingest_data"}),(0,n.jsx)(r.td,{children:"Ingest Data"}),(0,n.jsx)(r.td,{children:"Data to be ingested into the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"namespace"}),(0,n.jsx)(r.td,{children:"Namespace"}),(0,n.jsx)(r.td,{children:"Optional namespace within AstraDB to use for the collection."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"embedding"}),(0,n.jsx)(r.td,{children:"Embedding Model"}),(0,n.jsx)(r.td,{children:"Embedding model to use."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"metric"}),(0,n.jsx)(r.td,{children:"Metric"}),(0,n.jsx)(r.td,{children:'Distance metric for vector comparisons. The options are "cosine", "euclidean", "dot_product".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"setup_mode"}),(0,n.jsx)(r.td,{children:"Setup Mode"}),(0,n.jsx)(r.td,{children:'Configuration mode for setting up the vector store. The options are "Sync", "Async", "Off".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"pre_delete_collection"}),(0,n.jsx)(r.td,{children:"Pre Delete Collection"}),(0,n.jsx)(r.td,{children:"Boolean flag to determine whether to delete the collection before creating a new one."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"number_of_results"}),(0,n.jsx)(r.td,{children:"Number of Results"}),(0,n.jsx)(r.td,{children:"Number of results to return in similarity search. Default: 4."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_type"}),(0,n.jsx)(r.td,{children:"Search Type"}),(0,n.jsx)(r.td,{children:'Search type to use. The options are "Similarity", "Graph Traversal", "Hybrid".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"traversal_depth"}),(0,n.jsx)(r.td,{children:"Traversal Depth"}),(0,n.jsx)(r.td,{children:"Maximum depth for graph traversal searches. Default: 1."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_score_threshold"}),(0,n.jsx)(r.td,{children:"Search Score Threshold"}),(0,n.jsx)(r.td,{children:"Minimum similarity score threshold for search results."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_filter"}),(0,n.jsx)(r.td,{children:"Search Metadata Filter"}),(0,n.jsx)(r.td,{children:"Optional dictionary of filters to apply to the search query."})]})]})]}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Outputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"vector_store"}),(0,n.jsx)(r.td,{children:"Vector Store"}),(0,n.jsx)(r.td,{children:"The Graph RAG vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_results"}),(0,n.jsx)(r.td,{children:"Search Results"}),(0,n.jsxs)(r.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(r.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]})]})]})]}),"\n",(0,n.jsx)(r.h2,{id:"cassandra",children:"Cassandra"}),"\n",(0,n.jsxs)(r.p,{children:["This component creates a Cassandra Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(r.a,{href:"https://cassandra.apache.org/doc/latest/cassandra/vector-search/overview.html",children:"Cassandra documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"database_ref"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Contact points for the database or AstraDB database ID."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"username"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Username for the database (leave empty for AstraDB)."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"token"}),(0,n.jsx)(r.td,{children:"SecretString"}),(0,n.jsx)(r.td,{children:"User password for the database or AstraDB token."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"keyspace"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Table Keyspace or AstraDB namespace."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"table_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Name of the table or AstraDB collection."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ttl_seconds"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsx)(r.td,{children:"Time-to-live for added texts."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"batch_size"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsx)(r.td,{children:"Number of data to process in a single batch."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"setup_mode"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Configuration mode for setting up the Cassandra table."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"cluster_kwargs"}),(0,n.jsx)(r.td,{children:"Dict"}),(0,n.jsx)(r.td,{children:"Additional keyword arguments for the Cassandra cluster."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_query"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Query for similarity search."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ingest_data"}),(0,n.jsx)(r.td,{children:"Data"}),(0,n.jsx)(r.td,{children:"Data to be ingested into the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"embedding"}),(0,n.jsx)(r.td,{children:"Embeddings"}),(0,n.jsx)(r.td,{children:"Embedding function to use."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"number_of_results"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsx)(r.td,{children:"Number of results to return in search."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_type"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Type of search to perform."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_score_threshold"}),(0,n.jsx)(r.td,{children:"Float"}),(0,n.jsx)(r.td,{children:"Minimum similarity score for search results."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_filter"}),(0,n.jsx)(r.td,{children:"Dict"}),(0,n.jsx)(r.td,{children:"Metadata filters for search query."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"body_search"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Document textual search terms."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"enable_body_search"}),(0,n.jsx)(r.td,{children:"Boolean"}),(0,n.jsx)(r.td,{children:"Flag to enable body search."})]})]})]}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Outputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"vector_store"}),(0,n.jsx)(r.td,{children:"Cassandra"}),(0,n.jsx)(r.td,{children:"The Cassandra vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_results"}),(0,n.jsx)(r.td,{children:"List[Data]"}),(0,n.jsxs)(r.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(r.code,{children:"Data"})," objects."]})]})]})]})]}),"\n",(0,n.jsx)(r.h2,{id:"cassandra-graph-vector-store",children:"Cassandra Graph Vector Store"}),"\n",(0,n.jsx)(r.p,{children:"This component implements a Cassandra Graph Vector Store with search capabilities."}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"database_ref"}),(0,n.jsx)(r.td,{children:"Contact Points / Astra Database ID"}),(0,n.jsx)(r.td,{children:"The contact points for the database or AstraDB database ID. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"username"}),(0,n.jsx)(r.td,{children:"Username"}),(0,n.jsx)(r.td,{children:"The username for the database. Leave this field empty for AstraDB."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"token"}),(0,n.jsx)(r.td,{children:"Password / AstraDB Token"}),(0,n.jsx)(r.td,{children:"The user password for the database or AstraDB token. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"keyspace"}),(0,n.jsx)(r.td,{children:"Keyspace"}),(0,n.jsx)(r.td,{children:"The table Keyspace or AstraDB namespace. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"table_name"}),(0,n.jsx)(r.td,{children:"Table Name"}),(0,n.jsx)(r.td,{children:"The name of the table or AstraDB collection where vectors are stored. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"setup_mode"}),(0,n.jsx)(r.td,{children:"Setup Mode"}),(0,n.jsx)(r.td,{children:'The configuration mode for setting up the Cassandra table. The options are "Sync" or "Off". Default: "Sync".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"cluster_kwargs"}),(0,n.jsx)(r.td,{children:"Cluster arguments"}),(0,n.jsx)(r.td,{children:"An optional dictionary of additional keyword arguments for the Cassandra cluster."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_query"}),(0,n.jsx)(r.td,{children:"Search Query"}),(0,n.jsx)(r.td,{children:"The query string for similarity search."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ingest_data"}),(0,n.jsx)(r.td,{children:"Ingest Data"}),(0,n.jsx)(r.td,{children:"The list of data to be ingested into the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"embedding"}),(0,n.jsx)(r.td,{children:"Embedding"}),(0,n.jsx)(r.td,{children:"The embedding model to use."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"number_of_results"}),(0,n.jsx)(r.td,{children:"Number of Results"}),(0,n.jsx)(r.td,{children:"The number of results to return in similarity search. Default: 4."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_type"}),(0,n.jsx)(r.td,{children:"Search Type"}),(0,n.jsx)(r.td,{children:'The search type to use. The options are "Traversal", "MMR traversal", "Similarity", "Similarity with score threshold", or "MMR (Max Marginal Relevance)". Default: "Traversal".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"depth"}),(0,n.jsx)(r.td,{children:"Depth of traversal"}),(0,n.jsx)(r.td,{children:'The maximum depth of edges to traverse. Used for "Traversal" or "MMR traversal" search types. Default: 1.'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_score_threshold"}),(0,n.jsx)(r.td,{children:"Search Score Threshold"}),(0,n.jsx)(r.td,{children:'The minimum similarity score threshold for search results. Used for "Similarity with score threshold" search types.'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_filter"}),(0,n.jsx)(r.td,{children:"Search Metadata Filter"}),(0,n.jsx)(r.td,{children:"An optional dictionary of filters to apply to the search query."})]})]})]}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Outputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"vector_store"}),(0,n.jsx)(r.td,{children:"Vector Store"}),(0,n.jsx)(r.td,{children:"The Cassandra Graph vector store instance configured with the specified parameters."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_results"}),(0,n.jsx)(r.td,{children:"Search Results"}),(0,n.jsxs)(r.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(r.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]})]})]})]}),"\n",(0,n.jsx)(r.h2,{id:"chroma-db",children:"Chroma DB"}),"\n",(0,n.jsx)(r.p,{children:"This component creates a Chroma Vector Store with search capabilities."}),"\n",(0,n.jsx)(r.p,{children:"The Chroma DB component creates an ephemeral vector database for experimentation and vector storage."}),"\n",(0,n.jsxs)(r.ol,{children:["\n",(0,n.jsxs)(r.li,{children:["To use this component in a flow, connect it to a component that outputs ",(0,n.jsx)(r.strong,{children:"Data"})," or ",(0,n.jsx)(r.strong,{children:"DataFrame"}),".\nThis example splits text from a ",(0,n.jsx)(r.a,{href:"/components-data#url",children:"URL"})," component, and computes embeddings with the connected ",(0,n.jsx)(r.strong,{children:"OpenAI Embeddings"})," component. Chroma DB computes embeddings by default, but you can connect your own embeddings model, as seen in this example."]}),"\n"]}),"\n",(0,n.jsx)(r.p,{children:(0,n.jsx)(r.img,{alt:"ChromaDB receiving split text",src:t(88690).A+"",width:"1127",height:"811"})}),"\n",(0,n.jsxs)(r.ol,{start:"2",children:["\n",(0,n.jsxs)(r.li,{children:["In the ",(0,n.jsx)(r.strong,{children:"Chroma DB"})," component, in the ",(0,n.jsx)(r.strong,{children:"Collection"})," field, enter a name for your embeddings collection."]}),"\n",(0,n.jsxs)(r.li,{children:["Optionally, to persist the Chroma database, in the ",(0,n.jsx)(r.strong,{children:"Persist"})," field, enter a directory to store the ",(0,n.jsx)(r.code,{children:"chroma.sqlite3"})," file.\nThis example uses ",(0,n.jsx)(r.code,{children:"./chroma-db"})," to create a directory relative to where Langflow is running."]}),"\n",(0,n.jsxs)(r.li,{children:["To load data and embeddings into your Chroma database, in the ",(0,n.jsx)(r.strong,{children:"Chroma DB"})," component, click ",(0,n.jsx)(c.A,{name:"Play","aria-label":"Play icon"}),"."]}),"\n"]}),"\n",(0,n.jsx)(r.admonition,{type:"tip",children:(0,n.jsxs)(r.p,{children:["When loading duplicate documents, enable the ",(0,n.jsx)(r.strong,{children:"Allow Duplicates"})," option in Chroma DB if you want to store multiple copies of the same content, or disable it to automatically deduplicate your data."]})}),"\n",(0,n.jsxs)(r.ol,{start:"5",children:["\n",(0,n.jsxs)(r.li,{children:["To view the split data, in the ",(0,n.jsx)(r.strong,{children:"Split Text"})," component, click ",(0,n.jsx)(c.A,{name:"TextSearch","aria-label":"Inspect icon"}),"."]}),"\n",(0,n.jsxs)(r.li,{children:["To query your loaded data, open the ",(0,n.jsx)(r.strong,{children:"Playground"})," and query your database.\nYour input is converted to vector data and compared to the stored vectors in a vector similarity search."]}),"\n"]}),"\n",(0,n.jsxs)(r.p,{children:["For more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.trychroma.com/",children:"Chroma documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"collection_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:'The name of the Chroma collection. Default: "langflow".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"persist_directory"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"The directory to persist the Chroma database."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_query"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"The query to search for in the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ingest_data"}),(0,n.jsx)(r.td,{children:"Data"}),(0,n.jsxs)(r.td,{children:["The data to ingest into the vector store (list of ",(0,n.jsx)(r.code,{children:"Data"})," objects)."]})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"embedding"}),(0,n.jsx)(r.td,{children:"Embeddings"}),(0,n.jsx)(r.td,{children:"The embedding function to use for the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"chroma_server_cors_allow_origins"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"The CORS allow origins for the Chroma server."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"chroma_server_host"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"The host for the Chroma server."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"chroma_server_http_port"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsx)(r.td,{children:"The HTTP port for the Chroma server."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"chroma_server_grpc_port"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsx)(r.td,{children:"The gRPC port for the Chroma server."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"chroma_server_ssl_enabled"}),(0,n.jsx)(r.td,{children:"Boolean"}),(0,n.jsx)(r.td,{children:"Enable SSL for the Chroma server."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"allow_duplicates"}),(0,n.jsx)(r.td,{children:"Boolean"}),(0,n.jsx)(r.td,{children:"Allow duplicate documents in the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_type"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:'The type of search to perform: "Similarity" or "MMR".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"number_of_results"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsxs)(r.td,{children:["The number of results to return from the search. Default: ",(0,n.jsx)(r.code,{children:"10"}),"."]})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"limit"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsxs)(r.td,{children:["The limit of the number of records to compare when ",(0,n.jsx)(r.code,{children:"Allow Duplicates"})," is ",(0,n.jsx)(r.code,{children:"False"}),"."]})]})]})]}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Outputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"vector_store"}),(0,n.jsx)(r.td,{children:"Chroma"}),(0,n.jsx)(r.td,{children:"The Chroma vector store instance."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_results"}),(0,n.jsx)(r.td,{children:"List[Data]"}),(0,n.jsxs)(r.td,{children:["The results of the similarity search as a list of ",(0,n.jsx)(r.a,{href:"/concepts-objects#data-object",children:"Data"})," objects."]})]})]})]})]}),"\n",(0,n.jsx)(r.h2,{id:"clickhouse",children:"Clickhouse"}),"\n",(0,n.jsxs)(r.p,{children:["This component implements a Clickhouse Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(r.a,{href:"https://clickhouse.com/docs/en/intro",children:"Clickhouse Documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"host"}),(0,n.jsx)(r.td,{children:"hostname"}),(0,n.jsx)(r.td,{children:'The Clickhouse server hostname. Required. Default: "localhost".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"port"}),(0,n.jsx)(r.td,{children:"port"}),(0,n.jsx)(r.td,{children:"The Clickhouse server port. Required. Default: 8123."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"database"}),(0,n.jsx)(r.td,{children:"database"}),(0,n.jsx)(r.td,{children:"The Clickhouse database name. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"table"}),(0,n.jsx)(r.td,{children:"Table name"}),(0,n.jsx)(r.td,{children:"The Clickhouse table name. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"username"}),(0,n.jsx)(r.td,{children:"The ClickHouse user name."}),(0,n.jsx)(r.td,{children:"Username for authentication. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"password"}),(0,n.jsx)(r.td,{children:"The password for username."}),(0,n.jsx)(r.td,{children:"Password for authentication. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"index_type"}),(0,n.jsx)(r.td,{children:"index_type"}),(0,n.jsx)(r.td,{children:'Type of the index. The options are "annoy" and "vector_similarity". Default: "annoy".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"metric"}),(0,n.jsx)(r.td,{children:"metric"}),(0,n.jsx)(r.td,{children:'Metric to compute distance. The options are "angular", "euclidean", "manhattan", "hamming", "dot". Default: "angular".'})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"secure"}),(0,n.jsx)(r.td,{children:"Use https/TLS"}),(0,n.jsx)(r.td,{children:"Overrides inferred values from the interface or port arguments. Default: false."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"index_param"}),(0,n.jsx)(r.td,{children:"Param of the index"}),(0,n.jsx)(r.td,{children:"Index parameters. Default: \"'L2Distance',100\"."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"index_query_params"}),(0,n.jsx)(r.td,{children:"index query params"}),(0,n.jsx)(r.td,{children:"Additional index query parameters."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_query"}),(0,n.jsx)(r.td,{children:"Search Query"}),(0,n.jsx)(r.td,{children:"The query string for similarity search."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"ingest_data"}),(0,n.jsx)(r.td,{children:"Ingest Data"}),(0,n.jsx)(r.td,{children:"The data to be ingested into the vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"embedding"}),(0,n.jsx)(r.td,{children:"Embedding"}),(0,n.jsx)(r.td,{children:"The embedding model to use."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"number_of_results"}),(0,n.jsx)(r.td,{children:"Number of Results"}),(0,n.jsx)(r.td,{children:"The number of results to return in similarity search. Default: 4."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"score_threshold"}),(0,n.jsx)(r.td,{children:"Score threshold"}),(0,n.jsx)(r.td,{children:"The threshold for similarity scores."})]})]})]}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Outputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Display Name"}),(0,n.jsx)(r.th,{children:"Info"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"vector_store"}),(0,n.jsx)(r.td,{children:"Vector Store"}),(0,n.jsx)(r.td,{children:"The Clickhouse vector store."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_results"}),(0,n.jsx)(r.td,{children:"Search Results"}),(0,n.jsx)(r.td,{children:"The results of the similarity search as a list of Data objects."})]})]})]})]}),"\n",(0,n.jsx)(r.h2,{id:"couchbase",children:"Couchbase"}),"\n",(0,n.jsxs)(r.p,{children:["This component creates a Couchbase Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.couchbase.com/home/index.html",children:"Couchbase documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"couchbase_connection_string"}),(0,n.jsx)(r.td,{children:"SecretString"}),(0,n.jsx)(r.td,{children:"Couchbase Cluster connection string. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"couchbase_username"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Couchbase username. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"couchbase_password"}),(0,n.jsx)(r.td,{children:"SecretString"}),(0,n.jsx)(r.td,{children:"Couchbase password. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"bucket_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Name of the Couchbase bucket. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"scope_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Name of the Couchbase scope. Required."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"collection_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Name of the Couchbase collection. 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The Langflow cache directory location is specified in ",(0,n.jsx)(r.code,{children:"LANGFLOW_CONFIG_DIR"}),". For more information, see ",(0,n.jsx)(r.a,{href:"/environment-variables",children:"Environment variables"}),"."]}),"\n",(0,n.jsxs)(r.p,{children:["The ",(0,n.jsx)(r.strong,{children:"Retrieve"})," mode can query your ",(0,n.jsx)(r.strong,{children:"Chroma DB"})," collections."]}),"\n",(0,n.jsx)(r.p,{children:(0,n.jsx)(r.img,{alt:"Local DB retrieving vectors",src:t(60159).A+"",width:"1716",height:"960"})}),"\n",(0,n.jsxs)(r.p,{children:["For more information, see the ",(0,n.jsx)(r.a,{href:"https://docs.trychroma.com/",children:"Chroma documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"collection_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:'The name of the Chroma collection. 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It is embedded and indexed for semantic search."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"search_query"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Enter text to search for similar content in the selected collection."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"number_of_results"}),(0,n.jsx)(r.td,{children:"Integer"}),(0,n.jsx)(r.td,{children:"Number of results to return. 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objects."]})]})]})]})]}),"\n",(0,n.jsx)(r.h2,{id:"milvus",children:"Milvus"}),"\n",(0,n.jsxs)(r.p,{children:["This component creates a Milvus Vector Store with search capabilities.\nFor more information, see the ",(0,n.jsx)(r.a,{href:"https://milvus.io/docs",children:"Milvus documentation"}),"."]}),"\n",(0,n.jsxs)(s,{children:[(0,n.jsx)("summary",{children:"Parameters"}),(0,n.jsx)(r.p,{children:(0,n.jsx)(r.strong,{children:"Inputs"})}),(0,n.jsxs)(r.table,{children:[(0,n.jsx)(r.thead,{children:(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.th,{children:"Name"}),(0,n.jsx)(r.th,{children:"Type"}),(0,n.jsx)(r.th,{children:"Description"})]})}),(0,n.jsxs)(r.tbody,{children:[(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"collection_name"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Name of the Milvus collection."})]}),(0,n.jsxs)(r.tr,{children:[(0,n.jsx)(r.td,{children:"collection_description"}),(0,n.jsx)(r.td,{children:"String"}),(0,n.jsx)(r.td,{children:"Description of the 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Returns a Data object containing source URL and results."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsx)(t.td,{children:"Converts the API response data into a tabular DataFrame format."})]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"directory",children:"Directory"}),"\n",(0,r.jsx)(t.p,{children:"This component recursively loads files from a directory, with options for file types, depth, and concurrency."}),"\n",(0,r.jsxs)(n,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Input"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"path"}),(0,r.jsx)(t.td,{children:"MessageTextInput"}),(0,r.jsx)(t.td,{children:"The path to the directory to load files from."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"types"}),(0,r.jsx)(t.td,{children:"MessageTextInput"}),(0,r.jsx)(t.td,{children:"The file types to load (leave empty to load all types)."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"depth"}),(0,r.jsx)(t.td,{children:"IntInput"}),(0,r.jsx)(t.td,{children:"The depth to search for files."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"max_concurrency"}),(0,r.jsx)(t.td,{children:"IntInput"}),(0,r.jsx)(t.td,{children:"The maximum concurrency for loading files."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"load_hidden"}),(0,r.jsx)(t.td,{children:"BoolInput"}),(0,r.jsx)(t.td,{children:"If true, hidden files are loaded."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"recursive"}),(0,r.jsx)(t.td,{children:"BoolInput"}),(0,r.jsx)(t.td,{children:"If true, the search is recursive."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"silent_errors"}),(0,r.jsx)(t.td,{children:"BoolInput"}),(0,r.jsx)(t.td,{children:"If true, errors do not raise an exception."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"use_multithreading"}),(0,r.jsx)(t.td,{children:"BoolInput"}),(0,r.jsx)(t.td,{children:"If true, multithreading is used."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Output"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"List[Data]"}),(0,r.jsx)(t.td,{children:"The loaded file data from the directory."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"file",children:"File"}),"\n",(0,r.jsxs)(t.p,{children:["This component loads and parses files of various supported formats and converts the content into a ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," object. It supports multiple file types and provides options for parallel processing and error handling."]}),"\n",(0,r.jsx)(t.p,{children:"To load a document, follow these steps:"}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Click the ",(0,r.jsx)(t.strong,{children:"Select files"})," button."]}),"\n",(0,r.jsxs)(t.li,{children:["Select a local file or a file loaded with ",(0,r.jsx)(t.a,{href:"/concepts-file-management",children:"File management"}),", and then click ",(0,r.jsx)(t.strong,{children:"Select file"}),"."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:"The loaded file name appears in the component."}),"\n",(0,r.jsxs)(t.p,{children:["The default maximum supported file size is 100 MB.\nTo modify this value, see ",(0,r.jsx)(t.a,{href:"/environment-variables#LANGFLOW_MAX_FILE_SIZE_UPLOAD",children:"--max-file-size-upload"}),"."]}),"\n",(0,r.jsxs)(n,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"path"}),(0,r.jsx)(t.td,{children:"Files"}),(0,r.jsx)(t.td,{children:"The path to files to load. 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This option is deprecated."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"concurrency_multithreading"}),(0,r.jsx)(t.td,{children:"Processing Concurrency"}),(0,r.jsx)(t.td,{children:"When multiple files are being processed, the number of files to process concurrently. Default is 1. Values greater than 1 enable parallel processing for 2 or more files."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsxs)(t.td,{children:["The parsed content of the file as a ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," object."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsxs)(t.td,{children:["The file content as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," object."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"message"}),(0,r.jsx)(t.td,{children:"Message"}),(0,r.jsxs)(t.td,{children:["The file content as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#message-object",children:"Message"})," object."]})]})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"supported-file-types",children:"Supported File Types"}),"\n",(0,r.jsx)(t.p,{children:"Text files:"}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".txt"})," - Text files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".md"}),", ",(0,r.jsx)(t.code,{children:".mdx"})," - Markdown files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".csv"})," - CSV files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".json"})," - JSON files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".yaml"}),", ",(0,r.jsx)(t.code,{children:".yml"})," - YAML files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".xml"})," - XML files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".html"}),", ",(0,r.jsx)(t.code,{children:".htm"})," - HTML files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".pdf"})," - PDF files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".docx"})," - Word documents"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".py"})," - Python files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".sh"})," - Shell scripts"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".sql"})," - SQL files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".js"})," - JavaScript files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".ts"}),", ",(0,r.jsx)(t.code,{children:".tsx"})," - TypeScript files"]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:"Archive formats (for bundling multiple files):"}),"\n",(0,r.jsxs)(t.ul,{children:["\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".zip"})," - ZIP archives"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".tar"})," - TAR archives"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".tgz"})," - Gzipped TAR archives"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".bz2"})," - Bzip2 compressed files"]}),"\n",(0,r.jsxs)(t.li,{children:[(0,r.jsx)(t.code,{children:".gz"})," - Gzip compressed files"]}),"\n"]}),"\n",(0,r.jsx)(t.h2,{id:"sql-query",children:"SQL Query"}),"\n",(0,r.jsx)(t.p,{children:"This component executes SQL queries on a specified database."}),"\n",(0,r.jsxs)(n,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"query"}),(0,r.jsx)(t.td,{children:"Query"}),(0,r.jsx)(t.td,{children:"The SQL query to execute."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"database_url"}),(0,r.jsx)(t.td,{children:"Database URL"}),(0,r.jsx)(t.td,{children:"The URL of the database."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"include_columns"}),(0,r.jsx)(t.td,{children:"Include Columns"}),(0,r.jsx)(t.td,{children:"Include columns in the result."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"passthrough"}),(0,r.jsx)(t.td,{children:"Passthrough"}),(0,r.jsx)(t.td,{children:"If an error occurs, return the query instead of raising an exception."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"add_error"}),(0,r.jsx)(t.td,{children:"Add Error"}),(0,r.jsx)(t.td,{children:"Add the error to the result."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"result"}),(0,r.jsx)(t.td,{children:"Result"}),(0,r.jsx)(t.td,{children:"The result of the SQL query execution."})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"url",children:"URL"}),"\n",(0,r.jsx)(t.p,{children:"This component fetches content from one or more URLs, processes the content, and returns it in various formats. It supports output in plain text, raw HTML, or JSON, with options for cleaning and separating multiple outputs."}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect the ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output to a component that accepts the input.\nFor example, connect the ",(0,r.jsx)(t.strong,{children:"URL"})," component to a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"URL request into a chat output component",src:s(55228).A+"",width:"1578",height:"1086"})}),"\n",(0,r.jsxs)(t.ol,{start:"2",children:["\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["In the URL component's ",(0,r.jsx)(t.strong,{children:"URLs"})," field, enter the URL for your request.\nThis example uses ",(0,r.jsx)(t.code,{children:"langflow.org"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Optionally, in the ",(0,r.jsx)(t.strong,{children:"Max Depth"})," field, enter how many pages away from the initial URL you want to crawl.\nSelect ",(0,r.jsx)(t.code,{children:"1"})," to crawl only the page specified in the ",(0,r.jsx)(t.strong,{children:"URLs"})," field.\nSelect ",(0,r.jsx)(t.code,{children:"2"})," to crawl all pages linked from that page.\nThe component crawls by link traversal, not by URL path depth."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Click ",(0,r.jsx)(t.strong,{children:"Playground"}),", and then click ",(0,r.jsx)(t.strong,{children:"Run Flow"}),".\nThe text contents of the URL are returned to the Playground as a structured DataFrame."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["In the ",(0,r.jsx)(t.strong,{children:"URL"})," component, change the output port to ",(0,r.jsx)(t.strong,{children:"Message"}),", and then run the flow again.\nThe text contents of the URL are returned as unstructured raw text, which you can extract patterns from with the ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," tool."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"URL"})," component to a ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," and ",(0,r.jsx)(t.strong,{children:"Chat Output"}),"."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Regex extractor connected to url component",src:s(8886).A+"",width:"1606",height:"848"})}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," tool, enter a pattern to extract text from the ",(0,r.jsx)(t.strong,{children:"URL"}),' component\'s raw output.\nThis example extracts the first paragraph from the "In the News" section of ',(0,r.jsx)(t.code,{children:"https://en.wikipedia.org/wiki/Main_Page"}),"."]}),"\n"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"In the news\\s*\\n(.*?)(?=\\n\\n)",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.p,{children:"Result:"}),"\n",(0,r.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Peruvian writer and Nobel Prize in Literature laureate Mario Vargas Llosa (pictured) dies at the age of 89.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsxs)(n,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"urls"}),(0,r.jsx)(t.td,{children:"URLs"}),(0,r.jsx)(t.td,{children:"Enter one or more URLs. URLs are automatically validated and cleaned."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"format"}),(0,r.jsx)(t.td,{children:"Output Format"}),(0,r.jsxs)(t.td,{children:["The output format. Use ",(0,r.jsx)(t.strong,{children:"Text"})," to extract text from the HTML, ",(0,r.jsx)(t.strong,{children:"Raw HTML"})," for the raw HTML content, or ",(0,r.jsx)(t.strong,{children:"JSON"})," to extract JSON from the HTML."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"separator"}),(0,r.jsx)(t.td,{children:"Separator"}),(0,r.jsxs)(t.td,{children:["The separator to use between multiple outputs. Default for ",(0,r.jsx)(t.strong,{children:"Text"})," is ",(0,r.jsx)(t.code,{children:"\\n\\n"}),". 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The component does not require an API key."]}),"\n",(0,r.jsxs)(t.p,{children:["When a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component is added to the workspace, a new ",(0,r.jsx)(t.strong,{children:"Webhook cURL"})," tab becomes available in the ",(0,r.jsx)(t.strong,{children:"API"})," pane that contains an HTTP POST request for triggering the webhook component. For example:"]}),"\n",(0,r.jsx)(h.Code,{codeConfig:a,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl ",props:{style:{color:"#FFA657"}}},{content:"-X ",props:{style:{color:"#79C0FF"}}},{content:"POST ",props:{style:{color:"#A5D6FF"}}},{content:"\\",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:' "http://127.0.0.1:7860/api/v1/webhook/**YOUR_FLOW_ID**" ',props:{style:{color:"#A5D6FF"}}},{content:"\\",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:" -H ",props:{style:{color:"#79C0FF"}}},{content:"'Content-Type: application/json'",props:{style:{color:"#A5D6FF"}}},{content:"\\",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:" -d ",props:{style:{color:"#79C0FF"}}},{content:'\'{"any": "data"}\'',props:{style:{color:"#A5D6FF"}}}]}],lang:"bash"},annotations:[]}]}),"\n",(0,r.jsx)(t.p,{children:"To test the webhook component:"}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Add a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component to the flow."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Webhook"})," component's ",(0,r.jsx)(t.strong,{children:"Data"})," output to the ",(0,r.jsx)(t.strong,{children:"Data"})," input of a ",(0,r.jsx)(t.a,{href:"/components-processing#parser",children:"Parser"})," component."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Parser"})," component's ",(0,r.jsx)(t.strong,{children:"Parsed Text"})," output to the ",(0,r.jsx)(t.strong,{children:"Text"})," input of a ",(0,r.jsx)(t.a,{href:"/components-io#chat-output",children:"Chat Output"})," component."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, under ",(0,r.jsx)(t.strong,{children:"Mode"}),", select ",(0,r.jsx)(t.strong,{children:"Stringify"}),".\nThis mode passes the webhook's data as a string for the ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to print."]}),"\n",(0,r.jsxs)(t.li,{children:["To send a POST request, copy the code from the ",(0,r.jsx)(t.strong,{children:"Webhook cURL"})," tab in the ",(0,r.jsx)(t.strong,{children:"API"})," pane and paste it into a terminal."]}),"\n",(0,r.jsx)(t.li,{children:"Send the POST request."}),"\n",(0,r.jsxs)(t.li,{children:["Open the ",(0,r.jsx)(t.strong,{children:"Playground"}),".\nYour JSON data is posted to the ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component, which indicates that the webhook component is correctly triggering the flow."]}),"\n"]}),"\n",(0,r.jsxs)(n,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Payload"}),(0,r.jsx)(t.td,{children:"Receives a payload from external systems through HTTP POST requests."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"curl"}),(0,r.jsx)(t.td,{children:"cURL"}),(0,r.jsx)(t.td,{children:"The cURL command template for making requests to this webhook."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"endpoint"}),(0,r.jsx)(t.td,{children:"Endpoint"}),(0,r.jsx)(t.td,{children:"The endpoint URL where this webhook receives requests."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output_data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsxs)(t.td,{children:["Outputs processed data from the webhook input, and returns an empty ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," object if no input is provided. If the input is not valid JSON, the component wraps it in a ",(0,r.jsx)(t.code,{children:"payload"})," object."]})]})})]})]}),"\n",(0,r.jsx)(t.h2,{id:"legacy-components",children:"Legacy components"}),"\n",(0,r.jsx)(t.p,{children:"Legacy components are available for use but are no longer supported."}),"\n",(0,r.jsx)(t.h3,{id:"gmail-loader",children:"Gmail Loader"}),"\n",(0,r.jsx)(t.p,{children:"This component loads emails from Gmail using provided credentials and filters."}),"\n",(0,r.jsxs)(t.p,{children:["For more information about creating a service account JSON, see ",(0,r.jsx)(t.a,{href:"https://developers.google.com/identity/protocols/oauth2/service-account",children:"Service Account JSON"}),"."]}),"\n",(0,r.jsxs)(n,{children:[(0,r.jsx)("summary",{children:"Parameters"}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Inputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Input"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"json_string"}),(0,r.jsx)(t.td,{children:"SecretStrInput"}),(0,r.jsx)(t.td,{children:"A JSON string containing OAuth 2.0 access token information for service account access."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"label_ids"}),(0,r.jsx)(t.td,{children:"MessageTextInput"}),(0,r.jsx)(t.td,{children:"A comma-separated list of label IDs to filter emails."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"max_results"}),(0,r.jsx)(t.td,{children:"MessageTextInput"}),(0,r.jsx)(t.td,{children:"The maximum number of emails to load."})]})]})]}),(0,r.jsx)(t.p,{children:(0,r.jsx)(t.strong,{children:"Outputs"})}),(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Output"}),(0,r.jsx)(t.th,{children:"Type"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsx)(t.td,{children:"The loaded email data."})]})})]})]}),"\n",(0,r.jsx)(t.h3,{id:"google-drive-loader",children:"Google Drive Loader"}),"\n",(0,r.jsx)(t.p,{children:"This component loads documents from Google Drive using provided credentials and a single document ID."}),"\n",(0,r.jsxs)(t.p,{children:["For more information about creating a service account JSON, see ",(0,r.jsx)(t.a,{href:"https://developers.google.com/identity/protocols/oauth2/service-account",children:"Service Account 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modern web applications ...| https://example.com/article2 | 12 |",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"inputs",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"urls"}),(0,r.jsx)(t.td,{children:"URLs"}),(0,r.jsx)(t.td,{children:"Enter one or more URLs, separated by commas."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"curl"}),(0,r.jsx)(t.td,{children:"cURL"}),(0,r.jsx)(t.td,{children:"Paste a curl command to populate the dictionary fields for headers and body."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"method"}),(0,r.jsx)(t.td,{children:"Method"}),(0,r.jsx)(t.td,{children:"The HTTP method to 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processes the content, and returns it in various formats. It supports output in plain text, raw HTML, or JSON, with options for cleaning and separating multiple outputs."}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["To use this component in a flow, connect the ",(0,r.jsx)(t.strong,{children:"DataFrame"})," output to a component that accepts the input.\nFor example, connect the ",(0,r.jsx)(t.strong,{children:"URL"})," component to a ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component."]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"URL request into a chat output component",src:n(55228).A+"",width:"1578",height:"1086"})}),"\n",(0,r.jsxs)(t.ol,{start:"2",children:["\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["In the URL component's ",(0,r.jsx)(t.strong,{children:"URLs"})," field, enter the URL for your request.\nThis example uses ",(0,r.jsx)(t.code,{children:"langflow.org"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Optionally, in the ",(0,r.jsx)(t.strong,{children:"Max Depth"})," field, enter how many pages away from the initial URL you want to crawl.\nSelect ",(0,r.jsx)(t.code,{children:"1"})," to crawl only the page specified in the ",(0,r.jsx)(t.strong,{children:"URLs"})," field.\nSelect ",(0,r.jsx)(t.code,{children:"2"})," to crawl all pages linked from that page.\nThe component crawls by link traversal, not by URL path depth."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Click ",(0,r.jsx)(t.strong,{children:"Playground"}),", and then click ",(0,r.jsx)(t.strong,{children:"Run Flow"}),".\nThe text contents of the URL are returned to the Playground as a structured DataFrame."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["In the ",(0,r.jsx)(t.strong,{children:"URL"})," component, change the output port to ",(0,r.jsx)(t.strong,{children:"Message"}),", and then run the flow again.\nThe text contents of the URL are returned as unstructured raw text, which you can extract patterns from with the ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," tool."]}),"\n"]}),"\n",(0,r.jsxs)(t.li,{children:["\n",(0,r.jsxs)(t.p,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"URL"})," component to a ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," and ",(0,r.jsx)(t.strong,{children:"Chat Output"}),"."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(t.p,{children:(0,r.jsx)(t.img,{alt:"Regex extractor connected to url component",src:n(8886).A+"",width:"1606",height:"848"})}),"\n",(0,r.jsxs)(t.ol,{start:"7",children:["\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Regex Extractor"})," tool, enter a pattern to extract text from the ",(0,r.jsx)(t.strong,{children:"URL"}),' component\'s raw output.\nThis example extracts the first paragraph from the "In the News" section of ',(0,r.jsx)(t.code,{children:"https://en.wikipedia.org/wiki/Main_Page"}),"."]}),"\n"]}),"\n",(0,r.jsx)(a.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"In the news\\s*\\n(.*?)(?=\\n\\n)",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.p,{children:"Result:"}),"\n",(0,r.jsx)(a.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"Peruvian writer and Nobel Prize in Literature laureate Mario Vargas Llosa (pictured) dies at the age of 89.",props:{}}]}],lang:"text"},annotations:[]}]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-7",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"urls"}),(0,r.jsx)(t.td,{children:"URLs"}),(0,r.jsx)(t.td,{children:"Enter one or more URLs. URLs are automatically validated and cleaned."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"format"}),(0,r.jsx)(t.td,{children:"Output Format"}),(0,r.jsxs)(t.td,{children:["Output Format. Use ",(0,r.jsx)(t.strong,{children:"Text"})," to extract text from the HTML, ",(0,r.jsx)(t.strong,{children:"Raw HTML"})," for the raw HTML content, or ",(0,r.jsx)(t.strong,{children:"JSON"})," to extract JSON from the HTML."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"separator"}),(0,r.jsx)(t.td,{children:"Separator"}),(0,r.jsxs)(t.td,{children:["Specify the separator to use between multiple outputs. Default for ",(0,r.jsx)(t.strong,{children:"Text"})," is ",(0,r.jsx)(t.code,{children:"\\n\\n"}),". Default for ",(0,r.jsx)(t.strong,{children:"Raw HTML"})," is ",(0,r.jsx)(t.code,{children:"\\n\x3c!-- Separator --\x3e\\n"}),"."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"clean_extra_whitespace"}),(0,r.jsx)(t.td,{children:"Clean Extra Whitespace"}),(0,r.jsxs)(t.td,{children:["Whether to clean excessive blank lines in the text output. Only applies to ",(0,r.jsx)(t.code,{children:"Text"})," format."]})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-7",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Info"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsxs)(t.td,{children:["List of ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," objects containing fetched content and metadata."]})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"text"}),(0,r.jsx)(t.td,{children:"Text"}),(0,r.jsx)(t.td,{children:"Fetched content as formatted text, with applied separators and cleaning."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"dataframe"}),(0,r.jsx)(t.td,{children:"DataFrame"}),(0,r.jsxs)(t.td,{children:["Content formatted as a ",(0,r.jsx)(t.a,{href:"/concepts-objects#dataframe-object",children:"DataFrame"})," object."]})]})]})]}),"\n",(0,r.jsx)(t.h2,{id:"webhook",children:"Webhook"}),"\n",(0,r.jsx)(t.p,{children:"This component defines a webhook trigger that runs a flow when it receives an HTTP POST request."}),"\n",(0,r.jsxs)(t.p,{children:["If the input is not valid JSON, the component wraps it in a ",(0,r.jsx)(t.code,{children:"payload"})," object so that it can be processed and still trigger the flow. The component does not require an API key."]}),"\n",(0,r.jsxs)(t.p,{children:["When a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component is added to the workspace, a new ",(0,r.jsx)(t.strong,{children:"Webhook cURL"})," tab becomes available in the ",(0,r.jsx)(t.strong,{children:"API"})," pane that contains an HTTP POST request for triggering the webhook component. For example:"]}),"\n",(0,r.jsx)(a.Code,{codeConfig:x,northPanel:{tabs:[""],active:"",heightRatio:1},files:[{name:"",focus:"",code:{lines:[{tokens:[{content:"curl ",props:{style:{color:"#FFA657"}}},{content:"-X ",props:{style:{color:"#79C0FF"}}},{content:"POST ",props:{style:{color:"#A5D6FF"}}},{content:"\\",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:' "http://127.0.0.1:7860/api/v1/webhook/**YOUR_FLOW_ID**" ',props:{style:{color:"#A5D6FF"}}},{content:"\\",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:" -H ",props:{style:{color:"#79C0FF"}}},{content:"'Content-Type: application/json'",props:{style:{color:"#A5D6FF"}}},{content:"\\",props:{style:{color:"#79C0FF"}}}]},{tokens:[{content:" -d ",props:{style:{color:"#79C0FF"}}},{content:'\'{"any": "data"}\'',props:{style:{color:"#A5D6FF"}}}]}],lang:"bash"},annotations:[]}]}),"\n",(0,r.jsx)(t.p,{children:"To test the webhook component:"}),"\n",(0,r.jsxs)(t.ol,{children:["\n",(0,r.jsxs)(t.li,{children:["Add a ",(0,r.jsx)(t.strong,{children:"Webhook"})," component to the flow."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Webhook"})," component's ",(0,r.jsx)(t.strong,{children:"Data"})," output to the ",(0,r.jsx)(t.strong,{children:"Data"})," input of a ",(0,r.jsx)(t.a,{href:"/components-processing#parser",children:"Parser"})," component."]}),"\n",(0,r.jsxs)(t.li,{children:["Connect the ",(0,r.jsx)(t.strong,{children:"Parser"})," component's ",(0,r.jsx)(t.strong,{children:"Parsed Text"})," output to the ",(0,r.jsx)(t.strong,{children:"Text"})," input of a ",(0,r.jsx)(t.a,{href:"/components-io#chat-output",children:"Chat Output"})," component."]}),"\n",(0,r.jsxs)(t.li,{children:["In the ",(0,r.jsx)(t.strong,{children:"Parser"})," component, under ",(0,r.jsx)(t.strong,{children:"Mode"}),", select ",(0,r.jsx)(t.strong,{children:"Stringify"}),".\nThis mode passes the webhook's data as a string for the ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component to print."]}),"\n",(0,r.jsxs)(t.li,{children:["To send a POST request, copy the code from the ",(0,r.jsx)(t.strong,{children:"Webhook cURL"})," tab in the ",(0,r.jsx)(t.strong,{children:"API"})," pane and paste it into a terminal."]}),"\n",(0,r.jsx)(t.li,{children:"Send the POST request."}),"\n",(0,r.jsxs)(t.li,{children:["Open the ",(0,r.jsx)(t.strong,{children:"Playground"}),".\nYour JSON data is posted to the ",(0,r.jsx)(t.strong,{children:"Chat Output"})," component, which indicates that the webhook component is correctly triggering the flow."]}),"\n"]}),"\n",(0,r.jsx)(t.h3,{id:"inputs-8",children:"Inputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsxs)(t.tbody,{children:[(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"data"}),(0,r.jsx)(t.td,{children:"Payload"}),(0,r.jsx)(t.td,{children:"Receives a payload from external systems through HTTP POST requests."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"curl"}),(0,r.jsx)(t.td,{children:"cURL"}),(0,r.jsx)(t.td,{children:"The cURL command template for making requests to this webhook."})]}),(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"endpoint"}),(0,r.jsx)(t.td,{children:"Endpoint"}),(0,r.jsx)(t.td,{children:"The endpoint URL where this webhook receives requests."})]})]})]}),"\n",(0,r.jsx)(t.h3,{id:"outputs-8",children:"Outputs"}),"\n",(0,r.jsxs)(t.table,{children:[(0,r.jsx)(t.thead,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.th,{children:"Name"}),(0,r.jsx)(t.th,{children:"Display Name"}),(0,r.jsx)(t.th,{children:"Description"})]})}),(0,r.jsx)(t.tbody,{children:(0,r.jsxs)(t.tr,{children:[(0,r.jsx)(t.td,{children:"output_data"}),(0,r.jsx)(t.td,{children:"Data"}),(0,r.jsxs)(t.td,{children:["Outputs processed data from the webhook input, and returns an empty ",(0,r.jsx)(t.a,{href:"/concepts-objects",children:"Data"})," object if no input is provided. If the input is not valid JSON, the component wraps it in a ",(0,r.jsx)(t.code,{children:"payload"})," object."]})]})})]})]})}function u(e={}){const{wrapper:t}={...(0,i.R)(),...e.components};return t?(0,r.jsx)(t,{...e,children:(0,r.jsx)(p,{...e})}):p(e)}function m(e,t){throw new Error("Expected "+(t?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}},55228:(e,t,n)=>{n.d(t,{A:()=>s});const s=n.p+"assets/images/component-url-11d5306d5c7a52a376fab32344eab7a2.png"},80352:(e,t,n)=>{n.d(t,{A:()=>s});const s=n.p+"assets/images/url-component-fb712df73581345c0f344013ce6ff2fd.png"},84443:(e,t,n)=>{n.d(t,{A:()=>i});n(96540);var s=n(64058),r=n(74848);function i(e){let{name:t,...n}=e;const i=s[t];return i?(0,r.jsx)(i,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/runtime~main.aa121d7a.js b/assets/js/runtime~main.ac9da146.js similarity index 93% rename from assets/js/runtime~main.aa121d7a.js rename to 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Agent components in Langflow

Agent components define the behavior and capabilities of AI agents in your flow.

Agents use LLMs as a reasoning engine to decide which of the connected tool components to use to solve a problem.

-

Tools in agentic functions are, essentially, functions that the agent can call to perform tasks or access external resources. -A function is wrapped as a Tool object, with a common interface the agent understands. -Agents become aware of tools through tool registration, where the agent is provided a list of available tools, typically at agent initialization. The Tool object's description tells the agent what the tool can do.

+

Tools in agentic functions are essentially functions that the agent can call to perform tasks or access external resources. +A function is wrapped as a Tool object with a common interface the agent understands. +Agents become aware of tools through tool registration where the agent is provided a list of available tools typically at agent initialization. The Tool object's description tells the agent what the tool can do.

The agent then uses a connected LLM to reason through the problem to decide which tool is best for the job.

Use an agent in a flow​

The simple agent starter project uses an agent component connected to URL and Calculator tools to answer a user's questions. The OpenAI LLM acts as a brain for the agent to decide which tool to use. Tools are connected to agent components at the Tools port.

Simple agent starter flow

-

For a multi-agent example, see Create a problem-solving agent.

+

For a multi-agent example see, Create a problem-solving agent.

Agent component​

This component creates an agent that can use tools to answer questions and perform tasks based on given instructions.

The component includes an LLM model integration, a system message prompt, and a Tools port to connect tools to extend its capabilities.

For more information on this component, see the tool calling agent documentation.

-

Inputs​

-
NameTypeDescription
agent_llmDropdownThe provider of the language model that the agent will use to generate responses. Options include OpenAI and other providers, or Custom.
system_promptStringSystem Prompt: Initial instructions and context provided to guide the agent's behavior.
toolsListList of tools available for the agent to use.
input_valueStringThe input task or question for the agent to process.
add_current_date_toolBooleanIf true, adds a tool to the agent that returns the current date.
memoryMemoryOptional memory configuration for maintaining conversation history.
max_iterationsIntegerMaximum number of iterations the agent can perform.
handle_parsing_errorsBooleanWhether to handle parsing errors during agent execution.
verboseBooleanEnables verbose output for detailed logging.
-

Outputs​

-
NameTypeDescription
responseMessageThe agent's response to the given input task.
-

CSV Agent​

-

This component creates a CSV agent from a CSV file and LLM.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
pathFilePath to the CSV file
agent_typeStringType of agent to create (zero-shot-react-description, openai-functions, or openai-tools)
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Outputs​

-
NameTypeDescription
agentAgentExecutorCSV agent instance
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CrewAI Agent​

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This component represents an Agent of CrewAI, allowing for the creation of specialized AI agents with defined roles, goals, and capabilities within a crew.

-

For more information, see the CrewAI documentation.

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Inputs​

-
NameDisplay NameInfo
roleRoleThe role of the agent
goalGoalThe objective of the agent
backstoryBackstoryThe backstory of the agent
toolsToolsTools at agent's disposal
llmLanguage ModelLanguage model that will run the agent
memoryMemoryWhether the agent should have memory or not
verboseVerboseEnables verbose output
allow_delegationAllow DelegationWhether the agent is allowed to delegate tasks to other agents
allow_code_executionAllow Code ExecutionWhether the agent is allowed to execute code
kwargskwargsAdditional keyword arguments for the agent
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Outputs​

-
NameDisplay NameInfo
outputAgentThe constructed CrewAI Agent object
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Hierarchical Crew​

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This component represents a group of agents, managing how they should collaborate and the tasks they should perform in a hierarchical structure. This component allows for the creation of a crew with a manager overseeing the task execution.

-

For more information, see the CrewAI documentation.

-

Inputs​

-
NameDisplay NameInfo
agentsAgentsList of Agent objects representing the crew members
tasksTasksList of HierarchicalTask objects representing the tasks to be executed
manager_llmManager LLMLanguage model for the manager agent (optional)
manager_agentManager AgentSpecific agent to act as the manager (optional)
verboseVerboseEnables verbose output for detailed logging
memoryMemorySpecifies the memory configuration for the crew
use_cacheUse CacheEnables caching of results
max_rpmMax RPMSets the maximum requests per minute
share_crewShare CrewDetermines if the crew information is shared among agents
function_calling_llmFunction Calling LLMSpecifies the language model for function calling
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Outputs​

-
NameDisplay NameInfo
crewCrewThe constructed Crew object with hierarchical task execution
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JSON Agent​

+
Parameters

Inputs

NameTypeDescription
agent_llmDropdownThe provider of the language model that the agent uses to generate responses. Options include OpenAI and other providers or Custom.
system_promptStringThe system prompt provides initial instructions and context to guide the agent's behavior.
toolsListThe list of tools available for the agent to use.
input_valueStringThe input task or question for the agent to process.
add_current_date_toolBooleanWhen true this adds a tool to the agent that returns the current date.
memoryMemoryAn optional memory configuration for maintaining conversation history.
max_iterationsIntegerThe maximum number of iterations the agent can perform.
handle_parsing_errorsBooleanThis determines whether to handle parsing errors during agent execution.
verboseBooleanThis enables verbose output for detailed logging.

Outputs

NameTypeDescription
responseMessageThe agent's response to the given input task.
+

Legacy components​

+

Legacy components are available for use but are no longer supported.

+

JSON Agent​

This component creates a JSON agent from a JSON or YAML file and an LLM.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
pathFilePath to the JSON or YAML file
-

Outputs​

-
NameTypeDescription
agentAgentExecutorJSON agent instance
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OpenAI Tools Agent​

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This component creates an OpenAI Tools Agent using LangChain.

-

For more information, see the LangChain documentation.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent (must be tool-enabled)
system_promptStringSystem prompt for the agent
user_promptStringUser prompt template (must contain 'input' key)
chat_historyList[Data]Optional chat history for the agent
toolsList[Tool]List of tools available to the agent
-

Outputs​

-
NameTypeDescription
agentAgentExecutorOpenAI Tools Agent instance
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OpenAPI Agent​

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This component creates an OpenAPI Agent to interact with APIs defined by OpenAPI specifications.

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For more information, see the LangChain documentation on OpenAPI Agents.

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Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
pathFilePath to the OpenAPI specification file (JSON or YAML)
allow_dangerous_requestsBooleanWhether to allow potentially dangerous API requests
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Outputs​

-
NameTypeDescription
agentAgentExecutorOpenAPI Agent instance
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SQL Agent​

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This component creates a SQL Agent to interact with SQL databases.

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Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
database_uriStringURI of the SQL database to connect to
extra_toolsList[Tool]Additional tools to provide to the agent (optional)
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Outputs​

-
NameTypeDescription
agentAgentExecutorSQL Agent instance
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Sequential Crew​

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use for the agent.
pathFileThe path to the JSON or YAML file.

Outputs

NameTypeDescription
agentAgentExecutorThe JSON agent instance.
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Vector Store Agent​

+

This component creates a Vector Store Agent using LangChain.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use for the agent.
vectorstoreVectorStoreInfoThe vector store information for the agent to use.

Outputs

NameTypeDescription
agentAgentExecutorThe Vector Store Agent instance.
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Vector Store Router Agent​

+

This component creates a Vector Store Router Agent using LangChain.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use for the agent.
vectorstoresList[VectorStoreInfo]The list of vector store information for the agent to route between.

Outputs

NameTypeDescription
agentAgentExecutorThe Vector Store Router Agent instance.
+

Moved components​

+

The following components are available under Bundles.

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CrewAI Agent​

+

This component represents an Agent of CrewAI allowing for the creation of specialized AI agents with defined roles goals and capabilities within a crew.

+

For more information, see the CrewAI documentation.

+
Parameters

Inputs

NameDisplay NameInfo
roleRoleThe role of the agent.
goalGoalThe objective of the agent.
backstoryBackstoryThe backstory of the agent.
toolsToolsThe tools at the agent's disposal.
llmLanguage ModelThe language model that runs the agent.
memoryMemoryThis determines whether the agent should have memory or not.
verboseVerboseThis enables verbose output.
allow_delegationAllow DelegationThis determines whether the agent is allowed to delegate tasks to other agents.
allow_code_executionAllow Code ExecutionThis determines whether the agent is allowed to execute code.
kwargskwargsAdditional keyword arguments for the agent.

Outputs

NameDisplay NameInfo
outputAgentThe constructed CrewAI Agent object.
+

Hierarchical Crew​

+

This component represents a group of agents managing how they should collaborate and the tasks they should perform in a hierarchical structure. This component allows for the creation of a crew with a manager overseeing the task execution.

+

For more information, see the CrewAI documentation.

+
Parameters

Inputs

NameDisplay NameInfo
agentsAgentsThe list of Agent objects representing the crew members.
tasksTasksThe list of HierarchicalTask objects representing the tasks to be executed.
manager_llmManager LLMThe language model for the manager agent.
manager_agentManager AgentThe specific agent to act as the manager.
verboseVerboseThis enables verbose output for detailed logging.
memoryMemoryThe memory configuration for the crew.
use_cacheUse CacheThis enables caching of results.
max_rpmMax RPMThis sets the maximum requests per minute.
share_crewShare CrewThis determines if the crew information is shared among agents.
function_calling_llmFunction Calling LLMThe language model for function calling.

Outputs

NameDisplay NameInfo
crewCrewThe constructed Crew object with hierarchical task execution.
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CSV Agent​

+

This component creates a CSV agent from a CSV file and LLM.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use for the agent.
pathFileThe path to the CSV file.
agent_typeStringThe type of agent to create.

Outputs

NameTypeDescription
agentAgentExecutorThe CSV agent instance.
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OpenAI Tools Agent​

+

This component creates an OpenAI Tools Agent.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use.
toolsList of ToolsThe tools to give the agent access to.
system_promptStringThe system prompt to provide context to the agent.
input_valueStringThe user's input to the agent.
memoryMemoryThe memory for the agent to use for context persistence.
max_iterationsIntegerThe maximum number of iterations to allow the agent to execute.
verboseBooleanThis determines whether to print out the agent's intermediate steps.
handle_parsing_errorsBooleanThis determines whether to handle parsing errors in the agent.

Outputs

NameTypeDescription
agentAgentExecutorThe OpenAI Tools agent instance.
outputStringThe output from executing the agent on the input.
+

OpenAPI Agent​

+

This component creates an agent for interacting with OpenAPI services.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use.
openapi_specStringThe OpenAPI specification for the service.
base_urlStringThe base URL for the API.
headersDictThe optional headers for API requests.
agent_executor_kwargsDictThe optional parameters for the agent executor.

Outputs

NameTypeDescription
agentAgentExecutorThe OpenAPI agent instance.
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Sequential Crew​

This component represents a group of agents with tasks that are executed sequentially. This component allows for the creation of a crew that performs tasks in a specific order.

For more information, see the CrewAI documentation.

-

Inputs​

-
NameDisplay NameInfo
tasksTasksList of SequentialTask objects representing the tasks to be executed
verboseVerboseEnables verbose output for detailed logging
memoryMemorySpecifies the memory configuration for the crew
use_cacheUse CacheEnables caching of results
max_rpmMax RPMSets the maximum requests per minute
share_crewShare CrewDetermines if the crew information is shared among agents
function_calling_llmFunction Calling LLMSpecifies the language model for function calling
-

Outputs​

-
NameDisplay NameInfo
crewCrewThe constructed Crew object with sequential task execution
-

Sequential task agent​

-

This component creates a CrewAI Task and its associated Agent, allowing for the definition of sequential tasks with specific agent roles and capabilities.

+
Parameters

Inputs

NameDisplay NameInfo
tasksTasksThe list of SequentialTask objects representing the tasks to be executed.
verboseVerboseThis enables verbose output for detailed logging.
memoryMemoryThe memory configuration for the crew.
use_cacheUse CacheThis enables caching of results.
max_rpmMax RPMThis sets the maximum requests per minute.
share_crewShare CrewThis determines if the crew information is shared among agents.
function_calling_llmFunction Calling LLMThe language model for function calling.

Outputs

NameDisplay NameInfo
crewCrewThe constructed Crew object with sequential task execution.
+

Sequential task agent​

+

This component creates a CrewAI Task and its associated Agent allowing for the definition of sequential tasks with specific agent roles and capabilities.

For more information, see the CrewAI documentation.

-

Inputs​

-
NameDisplay NameInfo
roleRoleThe role of the agent
goalGoalThe objective of the agent
backstoryBackstoryThe backstory of the agent
toolsToolsTools at agent's disposal
llmLanguage ModelLanguage model that will run the agent
memoryMemoryWhether the agent should have memory or not
verboseVerboseEnables verbose output
allow_delegationAllow DelegationWhether the agent is allowed to delegate tasks to other agents
allow_code_executionAllow Code ExecutionWhether the agent is allowed to execute code
agent_kwargsAgent kwargsAdditional kwargs for the agent
task_descriptionTask DescriptionDescriptive text detailing task's purpose and execution
expected_outputExpected Task OutputClear definition of expected task outcome
async_executionAsync ExecutionBoolean flag indicating asynchronous task execution
previous_taskPrevious TaskThe previous task in the sequence (for chaining)
-

Outputs​

-
NameDisplay NameInfo
task_outputSequential TaskList of SequentialTask objects representing the created tasks
-

Tool Calling Agent​

-

This component creates a Tool Calling Agent using LangChain.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
system_promptStringSystem prompt for the agent
user_promptStringUser prompt template (must contain 'input' key)
chat_historyList[Data]Optional chat history for the agent
toolsList[Tool]List of tools available to the agent
-

Outputs​

-
NameTypeDescription
agentAgentExecutorTool Calling Agent instance
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Vector Store Agent​

-

This component creates a Vector Store Agent using LangChain.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
vectorstoreVectorStoreInfoVector store information for the agent to use
-

Outputs​

-
NameTypeDescription
agentAgentExecutorVector Store Agent instance
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Vector Store Router Agent​

-

This component creates a Vector Store Router Agent using LangChain.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
vectorstoresList[VectorStoreInfo]List of vector store information for the agent to route between
-

Outputs​

-
NameTypeDescription
agentAgentExecutorVector Store Router Agent instance
-

XML Agent​

+
Parameters

Inputs

NameDisplay NameInfo
roleRoleThe role of the agent.
goalGoalThe objective of the agent.
backstoryBackstoryThe backstory of the agent.
toolsToolsThe tools at the agent's disposal.
llmLanguage ModelThe language model that runs the agent.
memoryMemoryThis determines whether the agent should have memory or not.
verboseVerboseThis enables verbose output.
allow_delegationAllow DelegationThis determines whether the agent is allowed to delegate tasks to other agents.
allow_code_executionAllow Code ExecutionThis determines whether the agent is allowed to execute code.
agent_kwargsAgent kwargsThe additional kwargs for the agent.
task_descriptionTask DescriptionThe descriptive text detailing the task's purpose and execution.
expected_outputExpected Task OutputThe clear definition of the expected task outcome.
async_executionAsync ExecutionThe boolean flag indicating asynchronous task execution.
previous_taskPrevious TaskThe previous task in the sequence for chaining.

Outputs

NameDisplay NameInfo
task_outputSequential TaskThe list of SequentialTask objects representing the created tasks.
+

SQL Agent​

+

This component creates an agent for interacting with SQL databases.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use.
databaseDatabaseThe SQL database connection.
top_kIntegerThe number of results to return from a SELECT query.
use_toolsBooleanThis determines whether to use tools for query execution.
return_intermediate_stepsBooleanThis determines whether to return the agent's intermediate steps.
max_iterationsIntegerThe maximum number of iterations to run the agent.
max_execution_timeIntegerThe maximum execution time in seconds.
early_stopping_methodStringThe method to use for early stopping.
verboseBooleanThis determines whether to print the agent's thoughts.

Outputs

NameTypeDescription
agentAgentExecutorThe SQL agent instance.
+

Tool Calling Agent​

+

This component creates an agent for structured tool calling with various language models.

+
Parameters

Inputs

NameTypeDescription
llmLanguageModelThe language model to use.
toolsList[Tool]The list of tools available to the agent.
system_messageStringThe system message to use for the agent.
return_intermediate_stepsBooleanThis determines whether to return the agent's intermediate steps.
max_iterationsIntegerThe maximum number of iterations to run the agent.
max_execution_timeIntegerThe maximum execution time in seconds.
early_stopping_methodStringThe method to use for early stopping.
verboseBooleanThis determines whether to print the agent's thoughts.

Outputs

NameTypeDescription
agentAgentExecutorThe tool calling agent instance.
+

XML Agent​

This component creates an XML Agent using LangChain.

The agent uses XML formatting for tool instructions to the Language Model.

-

Inputs​

-
NameTypeDescription
llmLanguageModelLanguage model to use for the agent
user_promptStringCustom prompt template for the agent (includes XML formatting instructions)
toolsList[Tool]List of tools available to the agent
-

Outputs​

-
NameTypeDescription
agentAgentExecutorXML Agent instance