AI Detector - the Original AI Checker for ChatGPT & More
This endpoint takes in file(s) input and returns the model's result. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
This endpoint takes in a single text input and runs AI detection. The document will be truncated to 50,000 characters. See the documentation
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
gptzero_detect_ai: {
type: "app",
app: "gptzero_detect_ai",
}
},
async run({steps, $}) {
const data = {
"document": `Pipedream is the fastest way to automate any process that connects APIs. Build and run workflows with code-level control when you need it, and no code when you don't.`,
"multilingual": `false`,
}
return await axios($, {
method: "post",
url: `https://api.gptzero.me/v2/predict/text`,
headers: {
"Accept": `application/json`,
"Content-Type": `application/json`,
"x-api-key": `${this.gptzero_detect_ai.$auth.api_key}`,
},
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}}