Skip to content

Release v7.0.0
Compare
Choose a tag to compare
@jhamon jhamon released this 20 May 19:31
· 24 commits to main since this release
v7.0.0
12b0bfa

Upgrading from 6.x to 7.x

The v7 release of the Pinecone Python SDK has been published as pinecone to PyPI.

There are no intentional breaking changes between v6 and v7 of the SDK. The major version bump reflects the move from calling the 2025-01 to the 2025-04 version of the underlying API.

Some internals of the client have been reorganized or moved, but we've made an effort to alias everything and show warning messages when appropriate. If you experience any unexpected breaking changes that cause you friction while upgrading, let us know and we'll try to smooth it out.

Note

The official SDK package was renamed from pinecone-client to pinecone beginning in version 5.1.0.
Please remove pinecone-client from your project dependencies and add pinecone instead to get
the latest updates if upgrading from earlier versions.

What's new in 7.x

New Features:

  • Pinecone Assistant: The assistant plugin is now bundled by default. You can simply start using it without installing anything additional.
  • Inference API: List/view models from the model gallery via API
  • Backups:
    • Create backup from serverless index
    • Create serverless index from backup
    • List/view backups
    • List/view backup restore jobs
  • Bring Your Own Cloud (BYOC):
    • Create, list, describe, and delete BYOC indexes

Other useful improvements:

  • ~70% faster client instantiation time thanks to extensive refactoring to implement lazy loading. This means your app won't waste time loading code for features you're not using.
  • Retries with exponential backoff are now enabled by default for REST calls (implemented for both urllib3 and aiohttp).
  • We're following PEP 561 and adding a py.typed marker file to indicate inline type information is present in the package. We're still working toward reaching full coverage with our type hints, but including this file allows some tools to find the inline definitions we have already implemented.
  • @yorickvP contributed a fix for PineconeGrpcFuture objects blocking during construction

Backups for Serverless Indexes

You can create backups from your Serverless indexes and use these backups to create new indexes. Some fields such as record_count are initially empty but will be populated by the time a backup is ready for use.

from pinecone import Pinecone

pc = Pinecone()

index_name = 'example-index'
if not pc.has_index(name=index_name):
    raise Exception('An index must exist before backing it up')

backup = pc.create_backup(
    index_name=index_name,
    backup_name='example-backup',
    description='testing out backups'
)
# {
#     "backup_id": "4698a618-7e56-4a44-93bc-fc8f1371aa36",
#     "source_index_name": "example-index",
#     "source_index_id": "ec6fd44c-ab45-4873-97f3-f6b44b67e9bc",
#     "status": "Initializing",
#     "cloud": "aws",
#     "region": "us-east-1",
#     "tags": {},
#     "name": "example-backup",
#     "description": "testing out backups",
#     "dimension": null,
#     "record_count": null,
#     "namespace_count": null,
#     "size_bytes": null,
#     "created_at": "2025-05-16T18:44:28.480671533Z"
# }

Check the status of a backup

from pinecone import Pinecone

pc = Pinecone()

pc.describe_backup(backup_id='4698a618-7e56-4a44-93bc-fc8f1371aa36')
# {
#     "backup_id": "4698a618-7e56-4a44-93bc-fc8f1371aa36",
#     "source_index_name": "example-index",
#     "source_index_id": "ec6fd44c-ab45-4873-97f3-f6b44b67e9bc",
#     "status": "Ready",
#     "cloud": "aws",
#     "region": "us-east-1",
#     "tags": {},
#     "name": "example-backup",
#     "description": "testing out backups",
#     "dimension": 768,
#     "record_count": 1000,
#     "namespace_count": 1,
#     "size_bytes": 289656,
#     "created_at": "2025-05-16T18:44:28.480691Z"
# }

You can use list_backups to see all of your backups and their current status. If you have a large number of backups, results will be paginated. You can control the pagination with optional parameters for limit and pagination_token.

from pinecone import Pinecone

pc = Pinecone()

# All backups
pc.list_backups()

# Only backups associated with a particular index
pc.list_backups(index_name='my-index')

To create an index from a backup, use create_index_from_backup.

from pinecone import Pinecone

pc = Pinecone()

pc.create_index_from_backup(
    name='index-from-backup',
    backup_id='4698a618-7e56-4a44-93bc-fc8f1371aa36',
    deletion_protection = "disabled",
    tags={'env': 'testing'},
)

Under the hood, a restore job is created to handle taking data from your backup and loading it into the newly created serverless index. You can check status of pending restore jobs with pc.list_restore_jobs() or pc.describe_restore_job()

Explore and discover models available in our Inference API

You can now fetch a dynamic list of models supported by the Inference API.

from pinecone import Pinecone

pc = Pinecone()

# List all models
models = pc.inference.list_models()

# List models, with model type filtering
models = pc.inference.list_models(type="embed")
models = pc.inference.list_models(type="rerank")

# List models, with vector type filtering
models = pc.inference.list_models(vector_type="dense")
models = pc.inference.list_models(vector_type="sparse")

# List models, with both type and vector type filtering
models = pc.inference.list_models(type="rerank", vector_type="dense")

Or, if you know the name of a model, you can get just those details

pc.inference.get_model(model_name='pinecone-rerank-v0')
# {
#     "model": "pinecone-rerank-v0",
#     "short_description": "A state of the art reranking model that out-performs competitors on widely accepted benchmarks. It can handle chunks up to 512 tokens (1-2 paragraphs)",
#     "type": "rerank",
#     "supported_parameters": [
#         {
#             "parameter": "truncate",
#             "type": "one_of",
#             "value_type": "string",
#             "required": false,
#             "default": "END",
#             "allowed_values": [
#                 "END",
#                 "NONE"
#             ]
#         }
#     ],
#     "modality": "text",
#     "max_sequence_length": 512,
#     "max_batch_size": 100,
#     "provider_name": "Pinecone",
#     "supported_metrics": []
# }

Client support for BYOC (Bring Your Own Cloud)

For customers using our BYOC offering, you can now create indexes and list/describe indexes you have created in your cloud.

from pinecone import Pinecone, ByocSpec

pc = Pinecone()

pc.create_index(
    name='example-byoc-index',
    dimension=768,
    metric='cosine',
    spec=ByocSpec(environment='my-private-env'),
    tags={
        'env': 'testing'
    },
    deletion_protection='enabled'
)

Contributors

yorickvP
Assets 2
Loading