Home of cutting edge, explainable AI software that turns unstructured content into meaningful insights.
Analyze text for language, entities, sentiment, and other insights. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python 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}`,
},
})
},
})
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt
file or running pip
.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}