with Tisane Labs and Go?
Analyze text for language, entities, sentiment, and other insights. See the documentation
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Detects languages used in the specified text fragment. See the documentation
Finds and returns a URL of an image (Creative Commons) best describing the text. See the documentation
Translate text between supported languages. See the documentation
The Tisane Labs API offers advanced text analysis capabilities, focusing on abusive content detection and linguistic insights. With it, you can automate content moderation, extract entities, detect the sentiment, and identify the language of the text. In Pipedream, Tisane Labs API can be integrated into workflows to process text from various sources such as user comments, support tickets, or social media posts. By leveraging Pipedream's serverless platform, you can create real-time, event-driven applications that respond to text analyses, connect with other services, and perform actions based on the insights gained from the Tisane Labs API.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
tisane_labs: {
type: "app",
app: "tisane_labs",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.tisane.ai/languages`,
headers: {
"Ocp-Apim-Subscription-Key": `${this.tisane_labs.$auth.api_key}`,
},
})
},
})
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
package main
import (
"fmt"
pd "github.com/PipedreamHQ/pipedream-go"
)
func main() {
// Access previous step data using pd.Steps
fmt.Println(pd.Steps)
// Export data using pd.Export
data := make(map[string]interface{})
data["name"] = "Luke"
pd.Export("data", data)
}