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from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.inputs import MessageTextInput, SecretStrInput
from langflow.io import DictInput, DropdownInput


class AmazonBedrockComponent(LCModelComponent):
    display_name: str = "Amazon Bedrock"
    description: str = "Generate text using Amazon Bedrock LLMs."
    icon = "Amazon"

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from langchain_community.embeddings import BedrockEmbeddings

from langflow.base.models.model import LCModelComponent
from langflow.field_typing import Embeddings
from langflow.inputs import SecretStrInput
from langflow.io import DropdownInput, MessageTextInput, Output


class AmazonBedrockEmbeddingsComponent(LCModelComponent):
    display_name: str = "Amazon Bedrock Embeddings"

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const http = require('http');
const ADS1115 = require('ads1115')
 
const proxy = require('http-proxy');
const gpio = require('rpi-gpio');
const ws = require('ws');

drem = 'd1vy159ra4kdv0.cloudfront.net';

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import boto3

redshift = boto3.client('redshift')
credentials = redshift.get_cluster_credentials(
    DbUser='demouser', 
    DbName='dev', 
    ClusterIdentifier='redshiftml', 
    DurationSeconds=3600,
    AutoCreate=False
)

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import os
import argparse
import tensorflow as tf

# global variables
width = 28
height = 28
n_class = 10

# tfrecord parser