Where the world builds software. Millions of developers and companies build, ship, and maintain their software on GitHub—the largest and most advanced development platform in the world.
Find issues and pull requests by state and keyword. See the documentation
Generate embeddings using Google PaLM. See the docs here
The GitHub API is a powerful gateway to interaction with GitHub's vast web of data and services, offering a suite of endpoints to manipulate and retrieve information on repositories, pull requests, issues, and more. Harnessing this API on Pipedream, you can orchestrate automated workflows that respond to events in real-time, manage repository data, streamline collaborative processes, and connect GitHub with other services for a more integrated development lifecycle.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
github: {
type: "app",
app: "github",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.github.com/user`,
headers: {
Authorization: `Bearer ${this.github.$auth.oauth_access_token}`,
"X-GitHub-Api-Version": `2022-11-28`,
},
})
},
})
The Google PaLM API is a cutting-edge language model that allows developers to integrate advanced natural language understanding into their applications. On Pipedream, you can harness this power to create serverless workflows that react to various triggers and perform actions based on the insights and outputs from PaLM. Whether it's generating content, summarizing text, or understanding user intent, PaLM's capabilities can be integrated into Pipedream workflows to automate complex tasks involving language.
import { v1beta2 } from "@google-ai/generativelanguage";
import { GoogleAuth } from "google-auth-library";
export default defineComponent({
props: {
google_palm_api: {
type: "app",
app: "google_palm_api",
}
},
async run({ steps, $ }) {
const client = new v1beta2.TextServiceClient({
authClient: new GoogleAuth().fromAPIKey(this.google_palm_api.$auth.palm_api_key),
});
const text = "Repeat after me: one, two,";
const model = "models/text-bison-001";
return await client
.generateText({
model,
prompt: {
text,
},
})
},
})