- Recipes
- Tinybird to OpenAI prompt
Connect Tinybird and OpenAI prompt in our serverless environment
Use this template to Get Tinybird CSV endpoint entries using them to send a prompt to OpenAI and generate completions.
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Get Tinybird CSV endpoint entries
Used integrations:
- JavaScript
- Python
class HttpSourceTinybirdGetEndpoint {
async init() {
// TODO: Create your http credential with tynibird information:
// More info at https://yepcode.io/docs/integrations/http/#credential-configuration
// baseUrl: https://api.tinybird.co/v0
// HTTP Headers: { "Authorization": "Bearer <your-read-token>" }
this.httpClient = yepcode.integration.http(
"your-http-tinybird-credential-name"
);
}
async fetch(publish, done) {
// TODO: Customize your request checking the API documentation:
// https://www.tinybird.co/docs/api-reference/query-api.html
this.httpClient
.get("/pipes/your_end_point_name.csv", {
responseType: "stream",
})
.then(({
data
}) => {
data
.pipe(
csv.parse({
trim: true,
columns: true,
delimiter: ",",
skip_empty_lines: true,
})
)
.on("data", publish)
.on("end", done);
});
}
async close() {}
}
import csv
class HttpSourceTinybirdGetEndpoint:
def setup(self):
# TODO: Create your http credential with tynibird information:
# More info at https://yepcode.io/docs/integrations/http/#credential-configuration
# baseUrl: https://api.tinybird.co/v0
# HTTP Headers: { "Authorization": "Bearer <your-read-token>" }
self.session = yepcode.integration.http("your-http-tinybird-credential-name")
def generator(self):
# TODO: Customize your request checking the API documentation:
# https://www.tinybird.co/docs/api-reference/query-api.html
response = self.session.get("/pipes/your_end_point_name.csv", stream=True)
response.raise_for_status()
lines = response.iter_lines(decode_unicode=True)
reader = csv.DictReader(lines)
for row in reader:
yield row
lines.close()
response.close()
def close(self):
pass
Do you need help solving this integration with YepCode?
Let's talkSend a prompt to OpenAI and generate completions
Used integrations:
- JavaScript
- Python
class OpenaiTargetSendPrompt {
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 consume(item) {
// TODO: Configure your prompt
// More info at: https://platform.openai.com/docs/api-reference/completions/create
const completion = await this.openai.completions.create({
model: item.model,
prompt: item.prompt,
max_tokens: item.maxTokens,
temperature: item.temperature,
});
// Use the completion for whatever you want
console.log(completion.data.choices[0].text);
}
async close() {}
}
class OpenaiTargetSendPrompt:
def setup(self):
# TODO: Create your OpenAI credential
# More info at https://yepcode.io/docs/integrations/openai/#credential-configuration
self.openai = yepcode.integration.openai("your-openai-credential-name")
def consume(self, generator, done):
# TODO: Configure your prompt
# More info at: https://platform.openai.com/docs/api-reference/completions/create
for item in generator:
completion = self.openai.completions.create(
model="text-davinci-003",
prompt=item.get("prompt"),
max_tokens=7,
temperature=0,
)
# Use the completion for whatever you want
print(completion.choices)
done()
def close(self):
pass
FAQs
YepCode is a SaaS platform that enables the creation, execution and monitoring of integrations and automations using source code in a serverless environment.
We like to call it the Zapier for developers, since we bring all the agility and benefits of NoCode tools (avoid server provisioning, environment configuration, deployments,...), but with all the power of being able to use a programming language like JavaScript or Python.
These recipes are an excellent starting point for creating your own YepCode processes and solving complex integration and automation problems.
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YepCode has been created with a clear enterprise focus, offering a multi-tenant environment, team management capabilities, high security and auditing standards, Identity Provider (IdP) integrations, and on-premise options. It serves as the Swiss army knife for engineering teams, especially those requiring the extraction or transmission of information to external systems. It excels in scenarios demanding flexibility and adaptability to change within the process.
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