Release v3.0.2

Fixes

Create indexes using source_collection option in PodSpec

This release resolves a bug when passing source_collection as part of the PodSpec. This option is used when creating a new index from vector data stored in a collection. The value of this field should be a collection you have created previously from an index and that shows with pc.list_collections(). Currently collections and pod-based indexes are not portable across environments.

from pinecone import Pinecone

pc = Pinecone(api_key='YOUR_API_KEY')

pc.create_index(
    name='my-index', 
    dimension=1536, 
    metric='cosine', 
    spec=PodSpec(
        environment='us-east1-gcp', 
        source_collection='collection-2024jan16',
    )
)

Pass optional GRPCClientConfig when using PineconeGRPC

This could be considered as a fix for a UX bug or a micro-feature, depending on your perspective. In 3.0.2 we updated the pc.Index helper method that is used to build instances of the GRPCIndex class. It now accepts an optional keyword param grpc_config. Before this fix, you would need to import GRPCIndex and instantiate GRPCIndex yourself in order to pass this configuration and customize some settings, which was a bit clunky.

from pinecone.grpc import PineconeGRPC, GRPCClientConfig

pc = PineconeGRPC(api_key='YOUR_API_KEY')
grpc_config = GRPCClientConfig(
    timeout=10, 
    secure=True,
    reuse_channel=True
)
index = pc.Index(
   name='my-index', 
   host='host', 
   grpc_config=grpc_config
)

# Now do data operations
index.upsert(...)

Pass optional pool_threads config on the index.

Similar to the grpc_config option, some people requested the ability to pass pool_threads when targeting an index rather than in the initial client initialization. Now the optional configuration is accepted in both places, with the value passed to .Index() taking precedence.

Now these are both valid approaches:

from pinecone import Pinecone

pc = Pinecone(api_key='key', pool_threads=5)
pc.Index(host='host')
pc.upsert(...)

from pinecone import Pinecone

pc = Pinecone(api_key='key')
index = pc.Index(host='host', pool_threads=5)
index.upsert(...)

Debugging

This is probably only relevant for internal Pinecone employees or support agents, but the index client now accepts configuration to attach additional headers to each data plane request. This can help with tracing requests in logs.

from pinecone import Pinecone

pc = Pinecone(api_key='xxx')
index = pc.Index(
    host='hosturl', 
    additional_headers={ 'header-1': 'header-1-value' }
)

# Now do things
index.upsert(...)

The equivalent concept for PineconeGRPC is to pass additional_metadata. gRPC metadata fill a similar role as HTTP request headers, and should not be confused with metadata associated with vectors stored in your Pinecone indexes.

from pinecone.grpc import PineconeGRPC, GRPCClientConfig

pc = PineconeGRPC(api_key='YOUR_API_KEY')

grpc_config = GRPCClientConfig(additional_metadata={'extra-header': 'value123'})
index = pc.Index(
    name='my-index', 
    host='host', 
    grpc_config=grpc_config
)

# do stuff
index.upsert(...)

Changelog

• README.md: Update install steps to escape brackets by @daverigby in #298
• Expose missing configurations for grpc_config and pool_threads by @jhamon in #296
• Integration tests for collections by @jhamon in #299
• Optional configs to pass additional_headers/additional_metadata to indexes by @jhamon in #297

New Contributors

• @daverigby made their first contribution in #298

Full Changelog: v3.0.1...v3.0.2