with Rasa 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
Rasa is an open-source platform for building conversational AI applications, including chatbots and voice assistants. It offers robust API endpoints for training models, managing conversations, and interpreting user messages, thus enabling the development of sophisticated AI-driven communication tools. When used with Pipedream, Rasa can automate dialogue flow, extract insights from conversation data, or trigger actions in other apps based on conversational cues.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
rasa: {
type: "app",
app: "rasa",
}
},
async run({steps, $}) {
const data = {
"key": `${this.rasa.$auth.key}`,
}
return await axios($, {
method: "post",
url: `https://api.rasa.io/v1/tokens`,
headers: {
"accept": `application/json`,
"Content-type": `application/json`,
},
auth: {
username: `${this.rasa.$auth.username}`,
password: `${this.rasa.$auth.password}`,
},
data,
})
},
})
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,
})
},
})