with InfluxDB Cloud and Azure OpenAI?
Emit new event when a new bucket is created. See the documentation
Emit new event when a new script is created. See the documentation
Emit new event when a new task is completed. See the documentation
Runs a script and returns the result. See the documentation
Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation
Classify items into specific categories. See the documentation
Creates an image given a prompt, and returns a URL to the image. See the documentation
Summarizes a text message with the GPT-35-Turbo and GPT-4 models. See the documentation
Harness the power of InfluxDB Cloud API on Pipedream to build robust data workflows. InfluxDB Cloud, a time-series database, is ideal for managing high-velocity data and extracting insights in real-time. On Pipedream, you can easily trigger workflows based on InfluxDB data, automate data ingestion, and connect with countless other services to analyze, visualize, and act upon your data.
import { InfluxDB } from '@influxdata/influxdb-client';
import { HealthAPI } from '@influxdata/influxdb-client-apis';
export default defineComponent({
props: {
influxdb_cloud: {
type: "app",
app: "influxdb_cloud",
}
},
async run({steps, $}) {
// See the Node.js client docs at
// https://github.com/influxdata/influxdb-client-js
const influxDB = new InfluxDB(this.influxdb_cloud.$auth.url);
const healthAPI = new HealthAPI(influxDB)
// Execute a health check to test our credentials
return await healthAPI.getHealth()
},
})
The Azure OpenAI Service API provides access to powerful AI models that can understand and generate human-like text. With Pipedream, you can harness this capability to create a variety of serverless workflows, automating tasks like content creation, code generation, and language translation. By integrating the API with other apps on Pipedream, you can streamline processes, analyze sentiment, and even automate customer support.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
azure_openai_service: {
type: "app",
app: "azure_openai_service",
}
},
async run({steps, $}) {
const data = {
"messages": [{ role: 'user', content: "Hello, world!" }],
}
return await axios($, {
method: "post",
url: `https://${this.azure_openai_service.$auth.resource_name}.openai.azure.com/openai/deployments/${this.azure_openai_service.$auth.deployment_name}/chat/completions?api-version=2023-05-15`,
headers: {
"Content-Type": `application/json`,
"api-key": `${this.azure_openai_service.$auth.api_key}`,
},
data,
})
},
})