with Filter and Azure OpenAI?
Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation
Classify items into specific categories. See the documentation
Creates an image given a prompt, and returns a URL to the image. See the documentation
Summarizes a text message with the GPT-35-Turbo and GPT-4 models. See the documentation
Translate text from one language to another. See the documentation
The Filter API in Pipedream allows for real-time data processing within workflows. It's designed to evaluate data against predefined conditions, enabling workflows to branch or perform specific actions based on those conditions. This API is instrumental in creating efficient, targeted automations that respond dynamically to diverse datasets. Using the Filter API, you can refine streams of data, ensuring that subsequent steps in your Pipedream workflow only execute when the data meets your specified criteria. This cuts down on unnecessary processing and facilitates the creation of more intelligent, context-aware systems.
export default defineComponent({
async run({ steps, $ }) {
let condition = false
if (condition == false) {
$.flow.exit("Ending workflow early because the condition is false")
} else {
$.export("$summary", "Continuing workflow, since condition for ending was not met.")
}
},
})
The Azure OpenAI Service API provides access to powerful AI models that can understand and generate human-like text. With Pipedream, you can harness this capability to create a variety of serverless workflows, automating tasks like content creation, code generation, and language translation. By integrating the API with other apps on Pipedream, you can streamline processes, analyze sentiment, and even automate customer support.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
azure_openai_service: {
type: "app",
app: "azure_openai_service",
}
},
async run({steps, $}) {
const data = {
"messages": [{ role: 'user', content: "Hello, world!" }],
}
return await axios($, {
method: "post",
url: `https://${this.azure_openai_service.$auth.resource_name}.openai.azure.com/openai/deployments/${this.azure_openai_service.$auth.deployment_name}/chat/completions?api-version=2023-05-15`,
headers: {
"Content-Type": `application/json`,
"api-key": `${this.azure_openai_service.$auth.api_key}`,
},
data,
})
},
})