Pinecone is a fully managed vector database.
Learn to use Pinecone for semantic search and RAG.
Getting Started
1. Create Pinecone account
2. Get API key
3. Create an index
4. Start adding vectors
Installation
pip install pinecone-client
Example
import pinecone
pinecone.init(api_key=”your-key”, environment=”us-west1″)
pinecone.create_index(“my-index”, dimension=1536)
index = pinecone.Index(“my-index”)
index.upsert([(“id1”, embedding1, {“text”: “hello”})])
results = index.query(vector=query_embedding, top_k=5)
Pricing
Free tier available. Paid plans scale with usage.
Conclusion
Pinecone is easy to use and scalable!