with Google Gemini and Pinecone?
Generates content from text input using the Google Gemini API. See the documentation
Deletes one or more vectors by ID, from a single namespace. See the documentation
Generates content from both text and image input using the Gemini API. See the documentation
Looks up and returns vectors by ID, from a single namespace.. See the documentation
Generate embeddings from text input using Google Gemini. See the documentation
The Google Gemini API is a cutting-edge tool from Google that enables developers to leverage AI models like Imagen and MusicLM to create and manipulate images and music based on textual descriptions. With Pipedream, you can harness this API to automate workflows that integrate AI-generated content into a variety of applications, from generating visuals for social media posts to composing background music for videos. Pipedream's serverless platform allows you to connect Google Gemini API with other apps to create complex, event-driven workflows without managing infrastructure.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_gemini: {
type: "app",
app: "google_gemini",
}
},
async run({steps, $}) {
const data = `{{your_promptt}}`;
//E.g. {"contents":[{"parts":[{"text":"Write a story about a magic backpack"}]}]}
return await axios($, {
method: "POST",
url: `https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent`,
headers: {
"Content-Type": "application/json",
},
params: {
key: `${this.google_gemini.$auth.api_key}`,
},
data
})
},
})
The Pinecone API enables you to work with vector databases, which are essential for building and scaling applications with AI features like recommendation systems, image recognition, and natural language processing. On Pipedream, you can create serverless workflows integrating Pinecone with other apps, automate data ingestion, query vector databases in response to events, and orchestrate complex data processing pipelines that leverage Pinecone's similarity search.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinecone: {
type: "app",
app: "pinecone",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinecone.io/collections`,
headers: {
"Api-Key": `${this.pinecone.$auth.api_key}`,
},
})
},
})