with fal.ai and Cohere?
Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. See the documentation
Cancels a request in the queue. This allows you to stop a long-running task if it's no longer needed. See the documentation
This action makes a prediction about which label fits the specified text inputs best. See the documentation
Gets the response of a completed request in the queue. This retrieves the results of your asynchronous task. See the documentation
import { fal } from "@fal-ai/client"
export default defineComponent({
props: {
fal_ai: {
type: "app",
app: "fal_ai",
}
},
async run({ steps, $ }) {
fal.config({
credentials: `${this.fal_ai.$auth.api_key}`,
});
const result = await fal.subscribe("fal-ai/lora", {
input: {
model_name: "stabilityai/stable-diffusion-xl-base-1.0",
prompt:
"Photo of a rhino dressed suit and tie sitting at a table in a bar with a bar stools, award winning photography, Elke vogelsang",
},
logs: true,
});
return result;
},
})
The Cohere API enables the development of apps with advanced natural language understanding capabilities. Utilizing machine learning, it can help with tasks like text generation, summarization, sentiment analysis, and more. On Pipedream, you can seamlessly integrate Cohere's features into serverless workflows, triggering actions based on text input, processing large volumes of data, or even enhancing chatbots with more human-like responses.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
cohere_platform: {
type: "app",
app: "cohere_platform",
}
},
async run({steps, $}) {
const data = {
"text": `Tokenize this!`,
}
return await axios($, {
method: "post",
url: `https://api.cohere.ai/small/tokenize`,
headers: {
Authorization: `Bearer ${this.cohere_platform.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})