Start using Pinecone

Pinecone is free and fully managed for early access customers. Get started quickly with zero cost. No need to provision hardware, configure open-source software, or set up infrastructure. Running your first application should take roughly 10 minutes.

These steps will get you started with Pinecone Teams. If you are interested in Pinecone Enterprise, contact us to request a demo.

1. Get an Early Access API key

Early access for Pinecone Teams is currently available for free. Complete this form to request an API key.

2. Install the lightweight python client

Once you have your API key, you’re ready to install and configure the lightweight python client.

pip install pinecone-client

3. Import Pinecone and set your API key

import pinecone

4. Load your data

Here we’ll use some synthetic data for illustration.

import numpy as np
items = list(enumerate(np.random.randn(1000, 128)))
queries = np.random.randn(100, 128)

5. Define ingress paths

Define arbitrary pre-processing steps (DAGs) to transform inputs and outputs.

graph = pinecone.graph.IndexGraph()
# you can do things like
# graph.add_read_preprocessor('my_item_transformer_image_uri')
# graph.add_write_preprocessor('my_query_transformer_image_uri')
# graph.add_postprocessor('my_postprocessor_image_uri')

6. Start the service

Start the live service. Pinecone will run it on a managed, distributed container cluster.

pinecone.service.deploy(service_name="hello-pinecone", graph=graph)

7. Connect to your live service

conn = pinecone.connector.connect("hello-pinecone")

8. Add data

Data is transformed into high-dimensional vectors using the pre-processors defined in Step 5, and the index is updated within 100ms.

acks = conn.upsert(items=items).collect()

9. Query the database

Find similar or top-ranking items in milliseconds.

results = conn.query(queries=queries).collect()

What’s next? Read the documentation or contact with questions.

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