Gmail offers private and secure email by Google at no cost, for business and consumer accounts.
Emit new event for each attachment in a message received. This source is capped at 100 max new messages per run.
Emit new event when an email matching the search criteria is received. This source is capped at 100 max new messages per run.
Emit new event for each new email sent. (Maximum of 100 events emited per execution)
Create a draft from your Google Workspace email account. See the documentation
Generate embeddings using Google PaLM. See the docs here
Download an attachment by attachmentId to the /tmp directory. See the documentation
By connecting your personal Gmail account to Pipedream, you'll be able to incorporate email into whatever you're building with any of the thousands of apps that are available on Pipedream.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
gmail: {
type: "app",
app: "gmail",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.gmail.$auth.oauth_access_token}`,
},
})
},
})
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,
},
})
},
})