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On this page
  • Use a model component in a flow​
  • AI/ML API​
  • Amazon Bedrock​
  • Anthropic​
  • Azure OpenAI​
  • Cohere​
  • DeepSeek​
  • Google Generative AI​
  • Groq​
  • Hugging Face API​
  • IBM watsonx.ai​
  • Language model​
  • LMStudio​
  • Maritalk​
  • Mistral​
  • Novita AI​
  • NVIDIA​
  • Ollama​
  • OpenAI​
  • OpenRouter​
  • Perplexity​
  • Qianfan​
  • SambaNova​
  • VertexAI​
  • xAI​
  1. Components

AI Models

Model components generate text using large language models. Refer to your specific component's documentation for more information on parameters.

PreviousAgentsNextData

Last updated 12 days ago

Use a model component in a flow

Model components receive inputs and prompts for generating text, and the generated text is sent to an output component.

The model output can also be sent to the Language Model port and on to a Parse Data component, where the output can be parsed into structured objects.

This component creates a ChatOpenAI model instance using the AIML API.

Name
Type
Description

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens. Range: 0-128000.

model_kwargs

Dictionary

Additional keyword arguments for the model.

model_name

String

The name of the AIML model to use. Options are predefined in AIML_CHAT_MODELS.

aiml_api_base

String

The base URL of the AIML API. Defaults to https://api.aimlapi.com.

api_key

SecretString

The AIML API Key to use for the model.

temperature

Float

Controls randomness in the output. Default: 0.1.

seed

Integer

Controls reproducibility of the job.

Name
Type
Description

model

LanguageModel

An instance of ChatOpenAI configured with the specified parameters.

This component generates text using Amazon Bedrock LLMs.

Name
Type
Description

model_id

String

The ID of the Amazon Bedrock model to use. Options include various models.

aws_access_key

SecretString

AWS Access Key for authentication.

aws_secret_key

SecretString

AWS Secret Key for authentication.

credentials_profile_name

String

Name of the AWS credentials profile to use (advanced).

region_name

String

AWS region name. Default: us-east-1.

model_kwargs

Dictionary

Additional keyword arguments for the model (advanced).

endpoint_url

String

Custom endpoint URL for the Bedrock service (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatBedrock configured with the specified parameters.

This component allows the generation of text using Anthropic Chat and Language models.

Name
Type
Description

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens. Default: 4096.

model

String

The name of the Anthropic model to use. Options include various Claude 3 models.

anthropic_api_key

SecretString

Your Anthropic API key for authentication.

temperature

Float

Controls randomness in the output. Default: 0.1.

anthropic_api_url

String

Endpoint of the Anthropic API. Defaults to https://api.anthropic.com if not specified (advanced).

prefill

String

Prefill text to guide the model's response (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatAnthropic configured with the specified parameters.

This component generates text using Azure OpenAI LLM.

Name
Display Name
Info

Model Name

Model Name

Specifies the name of the Azure OpenAI model to be used for text generation.

Azure Endpoint

Azure Endpoint

Your Azure endpoint, including the resource.

Deployment Name

Deployment Name

Specifies the name of the deployment.

API Version

API Version

Specifies the version of the Azure OpenAI API to be used.

API Key

API Key

Your Azure OpenAI API key.

Temperature

Temperature

Specifies the sampling temperature. Defaults to 0.7.

Max Tokens

Max Tokens

Specifies the maximum number of tokens to generate. Defaults to 1000.

Input Value

Input Value

Specifies the input text for text generation.

Stream

Stream

Specifies whether to stream the response from the model. Defaults to False.

Name
Type
Description

model

LanguageModel

An instance of AzureOpenAI configured with the specified parameters.

This component generates text using Cohere's language models.

Name
Display Name
Info

Cohere API Key

Cohere API Key

Your Cohere API key.

Max Tokens

Max Tokens

Specifies the maximum number of tokens to generate. Defaults to 256.

Temperature

Temperature

Specifies the sampling temperature. Defaults to 0.75.

Input Value

Input Value

Specifies the input text for text generation.

Name
Type
Description

model

LanguageModel

An instance of the Cohere model configured with the specified parameters.

This component generates text using DeepSeek's language models.

Name
Type
Description

max_tokens

Integer

Maximum number of tokens to generate. Set to 0 for unlimited. Range: 0-128000.

model_kwargs

Dictionary

Additional keyword arguments for the model.

json_mode

Boolean

If True, outputs JSON regardless of passing a schema.

model_name

String

The DeepSeek model to use. Default: deepseek-chat.

api_base

String

Base URL for API requests. Default: https://api.deepseek.com.

api_key

SecretString

Your DeepSeek API key for authentication.

temperature

Float

Controls randomness in responses. Range: [0.0, 2.0]. Default: 1.0.

seed

Integer

Number initialized for random number generation. Use the same seed integer for more reproducible results, and use a different seed number for more random results.

Name
Type
Description

model

LanguageModel

An instance of ChatOpenAI configured with the specified parameters.

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

Name
Display Name
Info

Google API Key

Google API Key

Your Google API key to use for the Google Generative AI.

Model

Model

The name of the model to use, such as "gemini-pro".

Max Output Tokens

Max Output Tokens

The maximum number of tokens to generate.

Temperature

Temperature

Run inference with this temperature.

Top K

Top K

Consider the set of top K most probable tokens.

Top P

Top P

The maximum cumulative probability of tokens to consider when sampling.

N

N

Number of chat completions to generate for each prompt.

Name
Type
Description

model

LanguageModel

An instance of ChatGoogleGenerativeAI configured with the specified parameters.

This component generates text using Groq's language models.

  1. To use this component in a flow, connect it as a Model in a flow like the Basic prompting flow, or select it as the Model Provider if you're using an Agent component.

  1. In the Groq API Key field, paste your Groq API key. The Groq model component automatically retrieves a list of the latest models. To refresh your list of models, click .

  2. In the Prompt component, enter:

You are a helpful assistant who supports their claims with sources.

  1. Click Playground and ask your Groq LLM a question. The responses include a list of sources.

Name
Type
Description

groq_api_key

SecretString

API key for the Groq API.

groq_api_base

String

Base URL path for API requests. Default: https://api.groq.com.

max_tokens

Integer

The maximum number of tokens to generate.

temperature

Float

Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.1.

n

Integer

Number of chat completions to generate for each prompt.

model_name

String

The name of the Groq model to use. Options are dynamically fetched from the Groq API.

tool_mode_enabled

Bool

If enabled, the component only displays models that work with tools.

Name
Type
Description

model

LanguageModel

An instance of ChatGroq configured with the specified parameters.

This component sends requests to the Hugging Face API to generate text using the model specified in the Model ID field.

In this example based on the Basic prompting flow, the Hugging Face API model component replaces the Open AI model. By selecting different hosted models, you can see how different models return different results.

  1. Create a Basic prompting flow.

  2. Replace the OpenAI model component with a Hugging Face API model component.

  3. In the Hugging Face API component, add your Hugging Face API token to the API Token field.

  4. Open the Playground and ask a question to the model, and see how it responds.

  5. Try different models, and see how they perform differently.

Name
Type
Description

model_id

String

The model ID from Hugging Face Hub. For example, "gpt2", "facebook/bart-large".

huggingfacehub_api_token

SecretString

Your Hugging Face API token for authentication.

temperature

Float

Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.7.

max_new_tokens

Integer

Maximum number of tokens to generate. Default: 512.

top_p

Float

Nucleus sampling parameter. Range: [0.0, 1.0]. Default: 0.95.

top_k

Integer

Top-k sampling parameter. Default: 50.

model_kwargs

Dictionary

Additional keyword arguments to pass to the model.

Name
Type
Description

model

LanguageModel

An instance of HuggingFaceHub configured with the specified parameters.

To use IBM watsonx.ai model components, replace a model component with the IBM watsonx.ai component in a flow.

An example flow looks like the following:

Name
Type
Description

url

String

The base URL of the watsonx API.

project_id

String

Your watsonx Project ID.

api_key

SecretString

Your IBM watsonx API Key.

model_name

String

The name of the watsonx model to use. Options are dynamically fetched from the API.

max_tokens

Integer

The maximum number of tokens to generate. Default: 1000.

stop_sequence

String

The sequence where generation should stop.

temperature

Float

Controls randomness in the output. Default: 0.1.

top_p

Float

Controls nucleus sampling, which limits the model to tokens whose probability is below the top_p value. Range: Default: 0.9.

frequency_penalty

Float

Controls frequency penalty. A positive value decreases the probability of repeating tokens, and a negative value increases the probability. Range: Default: 0.5.

presence_penalty

Float

Controls presence penalty. A positive value increases the likelihood of new topics being introduced. Default: 0.3.

seed

Integer

A random seed for the model. Default: 8.

logprobs

Boolean

Whether to return log probabilities of output tokens or not. Default: True.

top_logprobs

Integer

The number of most likely tokens to return at each position. Default: 3.

logit_bias

String

A JSON string of token IDs to bias or suppress.

Name
Type
Description

model

LanguageModel

This component generates text using either OpenAI or Anthropic language models.

Use this component as a drop-in replacement for LLM models to switch between different model providers and models.

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.

Name
Type
Description

provider

String

The model provider to use. Options: "OpenAI", "Anthropic". Default: "OpenAI".

model_name

String

The name of the model to use. Options depend on the selected provider.

api_key

SecretString

The API Key for authentication with the selected provider.

input_value

String

The input text to send to the model.

system_message

String

A system message that helps set the behavior of the assistant (advanced).

stream

Boolean

Whether to stream the response. Default: False (advanced).

temperature

Float

Controls randomness in responses. Range: [0.0, 1.0]. Default: 0.1 (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatOpenAI or ChatAnthropic configured with the specified parameters.

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

Name
Type
Description

base_url

String

The URL where LM Studio is running. Default: "http://localhost:1234".

max_tokens

Integer

Maximum number of tokens to generate in the response. Default: 512.

temperature

Float

Controls randomness in the output. Range: [0.0, 2.0]. Default: 0.7.

top_p

Float

Controls diversity via nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.

stop

List[String]

List of strings that will stop generation when encountered (advanced).

stream

Boolean

Whether to stream the response. Default: False.

presence_penalty

Float

Penalizes repeated tokens. Range: [-2.0, 2.0]. Default: 0.0.

frequency_penalty

Float

Penalizes frequent tokens. Range: [-2.0, 2.0]. Default: 0.0.

Name
Type
Description

model

LanguageModel

An instance of LMStudio configured with the specified parameters.

This component generates text using Maritalk LLMs.

Name
Type
Description

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens. Default: 512.

model_name

String

The name of the Maritalk model to use. Options: sabia-2-small, sabia-2-medium. Default: sabia-2-small.

api_key

SecretString

The Maritalk API Key to use for authentication.

temperature

Float

Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.5.

endpoint_url

String

The Maritalk API endpoint. Default: https://api.maritalk.com.

Name
Type
Description

model

LanguageModel

An instance of ChatMaritalk configured with the specified parameters.

This component generates text using MistralAI LLMs.

Name
Type
Description

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens (advanced).

model_name

String

The name of the Mistral AI model to use. Options include open-mixtral-8x7b, open-mixtral-8x22b, mistral-small-latest, mistral-medium-latest, mistral-large-latest, and codestral-latest. Default: codestral-latest.

mistral_api_base

String

The base URL of the Mistral API. Defaults to https://api.mistral.ai/v1 (advanced).

api_key

SecretString

The Mistral API Key to use for authentication.

temperature

Float

Controls randomness in the output. Default: 0.5.

max_retries

Integer

Maximum number of retries for API calls. Default: 5 (advanced).

timeout

Integer

Timeout for API calls in seconds. Default: 60 (advanced).

max_concurrent_requests

Integer

Maximum number of concurrent API requests. Default: 3 (advanced).

top_p

Float

Nucleus sampling parameter. Default: 1 (advanced).

random_seed

Integer

Seed for random number generation. Default: 1 (advanced).

safe_mode

Boolean

Enables safe mode for content generation (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatMistralAI configured with the specified parameters.

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

Name
Type
Description

api_key

SecretString

Your Novita AI API Key.

model

String

The id of the Novita AI model to use.

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens.

temperature

Float

Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.7.

top_p

Float

Controls the nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.

frequency_penalty

Float

Controls the frequency penalty. Range: [0.0, 2.0]. Default: 0.0.

presence_penalty

Float

Controls the presence penalty. Range: [0.0, 2.0]. Default: 0.0.

Name
Type
Description

model

LanguageModel

An instance of Novita AI model configured with the specified parameters.

This component generates text using NVIDIA LLMs.

Name
Type
Description

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens (advanced).

model_name

String

The name of the NVIDIA model to use. Default: mistralai/mixtral-8x7b-instruct-v0.1.

base_url

String

The base URL of the NVIDIA API. Default: https://integrate.api.nvidia.com/v1.

nvidia_api_key

SecretString

The NVIDIA API Key for authentication.

temperature

Float

Controls randomness in the output. Default: 0.1.

seed

Integer

The seed controls the reproducibility of the job (advanced). Default: 1.

Name
Type
Description

model

LanguageModel

An instance of ChatNVIDIA configured with the specified parameters.

This component generates text using Ollama's language models.

To use this component in a flow, connect BroxiAI to your locally running Ollama server and select a model.

  1. In the Ollama component, in the Base URL field, enter the address for your locally running Ollama server. This value is set as the OLLAMA_HOST environment variable in Ollama. The default base URL is http://127.0.0.1:11434.

  2. To refresh the server's list of models, click .

  3. In the Model Name field, select a model. This example uses llama3.2:latest.

Name
Display Name
Info

Base URL

Base URL

Endpoint of the Ollama API.

Model Name

Model Name

The model name to use.

Temperature

Temperature

Controls the creativity of model responses.

Name
Type
Description

model

LanguageModel

An instance of an Ollama model configured with the specified parameters.

This component generates text using OpenAI's language models.

Name
Type
Description

api_key

SecretString

Your OpenAI API Key.

model

String

The name of the OpenAI model to use. Options include "gpt-3.5-turbo" and "gpt-4".

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens.

temperature

Float

Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.7.

top_p

Float

Controls the nucleus sampling. Range: [0.0, 1.0]. Default: 1.0.

frequency_penalty

Float

Controls the frequency penalty. Range: [0.0, 2.0]. Default: 0.0.

presence_penalty

Float

Controls the presence penalty. Range: [0.0, 2.0]. Default: 0.0.

Name
Type
Description

model

LanguageModel

An instance of OpenAI model configured with the specified parameters.

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

Name
Type
Description

api_key

SecretString

Your OpenRouter API key for authentication.

site_url

String

Your site URL for OpenRouter rankings (advanced).

app_name

String

Your app name for OpenRouter rankings (advanced).

provider

String

The AI model provider to use.

model_name

String

The specific model to use for chat completion.

temperature

Float

Controls randomness in the output. Range: [0.0, 2.0]. Default: 0.7.

max_tokens

Integer

The maximum number of tokens to generate (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatOpenAI configured with the specified parameters.

This component generates text using Perplexity's language models.

Name
Type
Description

model_name

String

The name of the Perplexity model to use. Options include various Llama 3.1 models.

max_output_tokens

Integer

The maximum number of tokens to generate.

api_key

SecretString

The Perplexity API Key for authentication.

temperature

Float

Controls randomness in the output. Default: 0.75.

top_p

Float

The maximum cumulative probability of tokens to consider when sampling (advanced).

n

Integer

Number of chat completions to generate for each prompt (advanced).

top_k

Integer

Number of top tokens to consider for top-k sampling. Must be positive (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatPerplexity configured with the specified parameters.

This component generates text using Qianfan's language models.

This component generates text using SambaNova LLMs.

Name
Type
Description

sambanova_url

String

Base URL path for API requests. Default: https://api.sambanova.ai/v1/chat/completions.

sambanova_api_key

SecretString

Your SambaNova API Key.

model_name

String

The name of the Sambanova model to use. Options include various Llama models.

max_tokens

Integer

The maximum number of tokens to generate. Set to 0 for unlimited tokens.

temperature

Float

Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.07.

Name
Type
Description

model

LanguageModel

An instance of SambaNova model configured with the specified parameters.

This component generates text using Vertex AI LLMs.

Name
Type
Description

credentials

File

JSON credentials file. Leave empty to fallback to environment variables. File type: JSON.

model_name

String

The name of the Vertex AI model to use. Default: "gemini-1.5-pro".

project

String

The project ID (advanced).

location

String

The location for the Vertex AI API. Default: "us-central1" (advanced).

max_output_tokens

Integer

The maximum number of tokens to generate (advanced).

max_retries

Integer

Maximum number of retries for API calls. Default: 1 (advanced).

temperature

Float

Controls randomness in the output. Default: 0.0.

top_k

Integer

The number of highest probability vocabulary tokens to keep for top-k-filtering (advanced).

top_p

Float

The cumulative probability of parameter highest probability vocabulary tokens to keep for nucleus sampling. Default: 0.95 (advanced).

verbose

Boolean

Whether to print verbose output. Default: False (advanced).

Name
Type
Description

model

LanguageModel

An instance of ChatVertexAI configured with the specified parameters.

Name
Type
Description

max_tokens

Integer

Maximum number of tokens to generate. Set to 0 for unlimited. Range: 0-128000.

model_kwargs

Dictionary

Additional keyword arguments for the model.

json_mode

Boolean

If True, outputs JSON regardless of passing a schema.

model_name

String

The xAI model to use. Default: grok-2-latest.

base_url

String

Base URL for API requests. Default: https://api.x.ai/v1.

api_key

SecretString

Your xAI API key for authentication.

temperature

Float

Controls randomness in the output. Range: [0.0, 2.0]. Default: 0.1.

seed

Integer

Controls reproducibility of the job.

Name
Type
Description

model

LanguageModel

An instance of ChatOpenAI configured with the specified parameters.

AI/ML API

For more information, see .

Inputs

Outputs

Amazon Bedrock

For more information, see .

Inputs

Outputs

Anthropic

For more information, see the .

Inputs

Outputs

Azure OpenAI

For more information, see the .

Inputs

Outputs

Cohere

For more information, see the .

Inputs

Outputs

DeepSeek

For more information, see the .

Inputs

Outputs

Google Generative AI

For more information, see the .

Inputs

Outputs

Groq

Groq component in a basic prompting flow

In the Model field, select the model you want to use for your LLM. This example uses , which Groq recommends for real-time conversational interfaces.

For more information, see the .

Inputs

Outputs

Hugging Face API

The Hugging Face API is a hosted inference API for models hosted on Hugging Face, and requires a to authenticate.

For more information, see the .

Inputs

Outputs

IBM watsonx.ai

This component generates text using foundation models.

IBM watsonx model component in a basic prompting flow

The values for API endpoint, Project ID, API key, and Model Name are found in your IBM watsonx.ai deployment. For more information, see the .

Inputs

Outputs

An instance of configured with the specified parameters.

Language model

For more information, see the and .

Inputs

Outputs

LMStudio

For more information, see .

Inputs

Outputs

Maritalk

For more information, see .

Inputs

Outputs

Mistral

For more information, see .

Inputs

Outputs

Novita AI

For more information, see .

Inputs

Outputs

NVIDIA

For more information, see .

Inputs

Outputs

Ollama

Connect the Ollama model component to a flow. For example, this flow connects a local Ollama server running a Llama 3.2 model as the custom model for an component.

Ollama model as Agent custom model

For more information, see the .

Inputs

Outputs

OpenAI

For more information, see .

Inputs

Outputs

OpenRouter

For more information, see .

Inputs

Outputs

Perplexity

For more information, see .

Inputs

Outputs

Qianfan

For more information, see .

SambaNova

For more information, see .

Inputs

Outputs

VertexAI

For more information, see .

Inputs

Outputs

xAI

This component generates text using xAI models like .

For more information, see the .

Inputs

Outputs

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AIML documentation
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Amazon Bedrock documentation
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Anthropic documentation
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Azure OpenAI documentation
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Cohere documentation
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DeepSeek documentation
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Google Generative AI documentation
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llama-3.1-8b-instant
Groq documentation
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Hugging Face API token
Hugging Face documentation
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IBM watsonx.ai
Langchain documentation
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OpenAI documentation
Anthropic documentation
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LM Studio documentation
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Maritalk documentation
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Mistral AI documentation
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Novita AI documentation
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NVIDIA AI documentation
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Agent
Ollama documentation
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OpenAI documentation
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OpenRouter documentation
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Perplexity documentation
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Qianfan documentation
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Sambanova Cloud documentation
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Google Vertex AI documentation
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Grok
xAI documentation
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ChatWatsonx
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Data