api4ai offers a multitude of ready-to-use AI APIs to extract information from your images.
Accurately identifies alcohol labels using advanced intelligent technologies. Powered by API4AI.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Automatically and quickly remove image background with high accuracy. Powered by API4AI.
The service processes input image and responds with a list of found brand logos. Powered by API4AI.
Remove Background for car images. Powered by API4AI.
API4AI offers a range of artificial intelligence solutions and APIs for diverse applications, including content moderation, image recognition, and text analysis. Built on a robust cloud technology stack, our APIs guarantee seamless operability, scalability, and reliable uptime. Our aim is to provide standalone AI solutions that effortlessly integrate into any application with minimal setup required.
All API4AI APIs are subscription-based and managed through RapidAPI.
👉️️ Website: https://api4.ai
📩 Email: hello@api4.ai
💬 Chat: https://t.me/a4a_support_bot
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
api4ai: {
type: "app",
app: "api4ai",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://general-detection.p.rapidapi.com/v1/algos`,
headers: {
"X-RapidAPI-Key": `${this.api4ai.$auth.api_key}`,
"X-RapidAPI-Host": `general-detection.p.rapidapi.com`,
},
})
},
})
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}}