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- DALL-E (OpenAI) images to Elasticsearch
Connect DALL-E (OpenAI) images and Elasticsearch in our serverless environment
Use this template to Generate DALL-E (OpenAI) images using them to insert rows into Elasticsearch table.
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Generate DALL-E (OpenAI) images
Used integrations:
JavaScript
Python
class OpenaiSourceGenerateImages {
async init() {
// TODO: Create your OpenAI credential
// More info at https://yepcode.io/docs/integrations/openai/#credential-configuration
this.openai = yepcode.integration.openai("your-openai-credential-name");
}
async fetch(publish, done) {
// TODO: Configure your prompt
const prompts = [
"A cute baby sea otter",
"A happy little cloud",
"A grumpy potato",
"A sleepy owl",
"A mischievous kitten",
"A nerdy giraffe",
"A hipster penguin",
"A jolly llama",
"A clumsy elephant",
"A sassy flamingo",
"A quirky squirrel"
];
for (const prompt of prompts) {
// More info at: https://platform.openai.com/docs/api-reference/images
const response = await this.openai.createImage({
prompt: prompt,
n: 1,
size: "1024x1024",
});
await publish(response.data.data);
}
done();
}
async close() {}
}
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Let's talkInsert rows into Elasticsearch table
Used integrations:
JavaScript
Python
class ElasticsearchTargetInsert {
async init() {
// TODO: Create your clickhouse credential
// More info at https://yepcode.io/docs/integrations/elasticsearch/#credential-configuration
this.elasticsearch = yepcode.integration.elasticsearch(
"your-elasticsearch-credential-name"
);
}
async consume(item) {
// TODO: Map your item to row
await this.elasticsearch.index({
index: "your_table_name",
document: item,
});
}
async close() {}
}
class ElasticsearchTargetInsert:
def setup(self):
# TODO: Create your elasticsearch credential
# More info at https://yepcode.io/docs/integrations/elasticsearch/#credential-configuration
self.elasticsearch = yepcode.integration.elasticsearch("your-elasticsearch-credential-name")
def consume(self, generator, done):
for item in generator:
self.process(item)
done()
def process(self, item):
# TODO: Customize your index name
self.elasticsearch.index(index="index-name", document=item)
def close(self):
pass
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