Create and manage machines that read and write.
Determine the sentiment of the given text (positive, negative, or neutral). See the documentation
Convert an object to a JSON format string
Identify and extract significant keywords from the given text. See the documentation
Generate a blog post based on the given prompt. See the documentation
The Metatext.AI Pre-built AI Models API offers various artificial intelligence capabilities such as natural language processing, image recognition, and sentiment analysis. This API enables users to add AI features to their applications without the need for extensive machine learning expertise. Utilizing this API in Pipedream workflows allows for automation and integration with other services, making it possible to process and analyze text and images within a serverless environment efficiently.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
metatext_ai_pre_build_ai_models_api: {
type: "app",
app: "metatext_ai_pre_build_ai_models_api",
}
},
async run({steps, $}) {
const data = {
"text": `{your_text}`,
}
return await axios($, {
method: "post",
url: `https://api.metatext.ai/hub-inference/sentiment-analysis`,
headers: {
"Content-Type": `application/json`,
"x-api-key": `${this.metatext_ai_pre_build_ai_models_api.$auth.api_key}`,
},
data,
})
},
})
The Pipedream Utils app is a set of pre-built functions that streamline common tasks in your workflows. It acts like a Swiss Army knife for developers, providing essential tools such as format conversion, date manipulation, and text processing. By leveraging these functions, you can reduce the boilerplate code needed for routine operations, speeding up the development of intricate automations. The Helper Functions API can be a game changer when it comes to tasks like parsing dates in user-friendly formats, encoding and decoding data, or generating UUIDs, making them more efficient and less error-prone.
export default defineComponent({
props: {
pipedream_utils: {
type: "app",
app: "pipedream_utils",
}
},
async run({steps, $}) {
},
})