LLMWhisperer is a technology that presents data from complex documents to LLMs in a way that they can best understand.
Emit new event when a new column is added to a table. See the documentation
Emit new event when a row is added or modified. See the documentation
Emit new event when a new row is added to a table. See the documentation
Emit new event when new rows are returned from a custom query that you provide. See the documentation
Emit new event when a new table is added to the database. See the documentation
Convert your PDF/scanned documents to text format which can be used by LLMs. See the documentation
Get the status of the whisper process. This can be used to check the status of the conversion process when the conversion is done in async mode. See the documentation
Generate highlight locations for a search term in the document. See the documentation
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
llmwhisperer: {
type: "app",
app: "llmwhisperer",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://llmwhisperer-api.unstract.com/v1/get-usage-info`,
headers: {
"unstract-key": `${this.llmwhisperer.$auth.api_key}`,
},
})
},
})
On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.
import postgresql from "@pipedream/postgresql"
export default defineComponent({
props: {
postgresql,
},
async run({ steps, $ }) {
// Component source code:
// https://github.com/PipedreamHQ/pipedream/tree/master/components/postgresql
const queryObj = {
text: "SELECT NOW()",
values: [], // Ignored since query does not contain placeholders
};
return await this.postgresql.executeQuery(queryObj);
},
})