with Azure OpenAI and Go?
Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
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
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,
})
},
})
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
package main
import (
"fmt"
pd "github.com/PipedreamHQ/pipedream-go"
)
func main() {
// Access previous step data using pd.Steps
fmt.Println(pd.Steps)
// Export data using pd.Export
data := make(map[string]interface{})
data["name"] = "Luke"
pd.Export("data", data)
}