Levity
Train your own AI on documents, images, or text data to perform daily, repetitive tasks so your team can reach the next level of productivity
Integrate the Levity API with the Python API
Setup the Levity API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Levity and Python remarkably fast. Free for developers.
Popular Levity and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Levity#
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.
Connect Levity#
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,
})
},
})
Overview of Python#
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:
Connect Python#
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}}