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README.md

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# Pinecone Python SDK
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# Pinecone Python SDK
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![License](https://img.shields.io/github/license/pinecone-io/pinecone-python-client?color=orange) [![CI](https://github.com/pinecone-io/pinecone-python-client/actions/workflows/pr.yaml/badge.svg)](https://github.com/pinecone-io/pinecone-python-client/actions/workflows/pr.yaml)
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The official Pinecone Python SDK.
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index.query(vector=[...], top_key=10)
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```
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# Indexes
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## Create Index
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## Indexes
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### Create a serverless index
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```
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## List indexes
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### List indexes
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The following example returns all indexes in your project.
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print(index['name'])
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```
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## Describe index
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### Describe index
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The following example returns information about the index `example-index`.
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index_description = pc.describe_index("example-index")
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```
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## Delete an index
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### Delete an index
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The following example deletes the index named `example-index`. Only indexes which are not protected by deletion protection may be deleted.
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pc.delete_index("example-index")
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```
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## Scale replicas
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### Scale replicas
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The following example changes the number of replicas for `example-index`.
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pc.configure_index("example-index", replicas=new_number_of_replicas)
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```
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## Configuring deletion protection
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### Configuring deletion protection
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If you would like to enable deletion protection, which prevents an index from being deleted, the `configure_index` method also handles that via an optional `deletion_protection` keyword argument.
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print(desc.deletion_protection)
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```
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## Describe index statistics
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### Describe index statistics
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The following example returns statistics about the index `example-index`.
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index_stats_response = index.describe_index_stats()
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```
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## Upsert vectors
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### Upsert vectors
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The following example upserts vectors to `example-index`.
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```
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## Query an index
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### Query an index
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The following example queries the index `example-index` with metadata
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filtering.
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```
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## Delete vectors
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### Delete vectors
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The following example deletes vectors by ID.
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delete_response = index.delete(ids=["vec1", "vec2"], namespace="example-namespace")
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```
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## Fetch vectors
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### Fetch vectors
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The following example fetches vectors by ID.
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fetch_response = index.fetch(ids=["vec1", "vec2"], namespace="example-namespace")
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```
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## Update vectors
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### Update vectors
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The following example updates vectors by ID.
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```
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## List vectors
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### List vectors
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The `list` and `list_paginated` methods can be used to list vector ids matching a particular id prefix.
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With clever assignment of vector ids, this can be used to help model hierarchical relationships between
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print(results.usage) # { 'read_units': 1 }
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```
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# Collections
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## Collections
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## Create collection
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### Create collection
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The following example creates the collection `example-collection` from
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`example-index`.
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```
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## List collections
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### List collections
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The following example returns a list of the collections in the current project.
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active_collections = pc.list_collections()
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```
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## Describe a collection
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### Describe a collection
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The following example returns a description of the collection
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`example-collection`.
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collection_description = pc.describe_collection("example-collection")
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```
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## Delete a collection
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### Delete a collection
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The following example deletes the collection `example-collection`.
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```
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# Inference API
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## Inference API
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The Pinecone SDK now supports creating embeddings via the [Inference API](https://docs.pinecone.io/guides/inference/understanding-inference).
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# Send query to Pinecone index to retrieve similar documents
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```
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# Contributing
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## Contributing
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If you'd like to make a contribution, or get setup locally to develop the Pinecone Python SDK, please see our [contributing guide](https://github.com/pinecone-io/pinecone-python-client/blob/main/CONTRIBUTING.md)

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