Pinecone
Long-term Memory for AI. The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.
Go to sitePinecone API Integrations
Build and run workflows using the Pinecone API. Use 1000s of source-available triggers and actions across 2,000+ apps. Or write custom code to integrate any app or API in seconds.
Overview#
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://controller.${this.pinecone.$auth.environment}.pinecone.io/collections`,
headers: {
"Api-Key": `${this.pinecone.$auth.api_key}`,
},
})
},
})
Choose an API to Connect with Pinecone API#
1-24of2,000+apps by most popular
Example Use Cases#
Customer Support Ticket Routing: Automate the categorization and routing of customer support tickets by integrating Pinecone with a customer support platform like Zendesk. Use machine learning models to encode ticket text into vectors and query Pinecone to find similar past tickets for quick resolution.
Real-time Product Recommendations: Build a workflow that triggers when users view products on an e-commerce platform like Shopify. Capture viewing events, process product descriptions through ML models to obtain vectors, and query Pinecone to generate real-time personalized product recommendations for users.
Content Discovery and Matching: Connect Pinecone with a content management system like WordPress. When new content is published, convert it to a vector representation and upload it to Pinecone. Set up a workflow that responds to user queries by searching Pinecone for the most relevant content vectors, enhancing content discoverability.
Popular Pinecone Integrations#
Popular Pinecone Actions#
Deletes one or more vectors by ID, from a single namespace. See the docs.
Looks up and returns vectors by ID, from a single namespace.. See the docs.
Searches a namespace, using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. See the docs.
Updates vector in a namespace. If a value is included, it will overwrite the previous value. See the docs.
Writes vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. See the docs.
Authentication#
Pinecone uses API keys for authentication. When you connect your Pinecone account, Pipedream securely stores the keys so you can easily authenticate to Pinecone APIs in both code and no-code steps.
To connect your Pinecone account to Pipedream,
- Open the Pinecone console and click "API Keys"
- Copy the API key and Environment values and paste each below