with Levity and Python?
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The Levity API provides a platform for creating AI-powered workflows that can classify images, text, and data with ease. Using this API in Pipedream, you can automate decision-making processes, enhance data categorization, and streamline content moderation by leveraging machine learning models. It integrates smoothly within Pipedream's serverless environment, allowing you to build complex workflows without spinning up a single server.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
levity: {
type: "app",
app: "levity",
}
},
async run({steps, $}) {
const data = {
"url": `{replace_with_image_url}`,
}
return await axios($, {
method: "post",
url: `https://api.levity.ai/v1/classifiers/{your_classifier_id}/classify/`,
headers: {
"Authorization": `Token ${this.levity.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
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}}