Pinecone.NET 2.0.0

There is a newer version of this package available.
See the version list below for details.
dotnet add package Pinecone.NET --version 2.0.0
NuGet\Install-Package Pinecone.NET -Version 2.0.0
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Pinecone.NET" Version="2.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Pinecone.NET --version 2.0.0
#r "nuget: Pinecone.NET, 2.0.0"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install Pinecone.NET as a Cake Addin
#addin nuget:?package=Pinecone.NET&version=2.0.0

// Install Pinecone.NET as a Cake Tool
#tool nuget:?package=Pinecone.NET&version=2.0.0


Pinecone.NET is a fully-fledged C# library for the Pinecone vector database.
In the absence of an official SDK, it provides first-class support for Pinecone in C# and F#.


  • Standard Index operations
  • gRPC and REST transports for vector operations
  • Sparse-dense vectors
  • Efficient vector serialization
  • Metadata support
  • NativeAOT compatibility (e.g. for AWS Lambda)


dotnet add package Pinecone.NET or Install-Package Pinecone.NET


Working with indexes

using Pinecone;

// Initialize the client with your API key
using var pinecone = new PineconeClient("your-api-key");

// List all indexes
var indexes = await pinecone.ListIndexes();

// Create a new index if it doesn't exist
var indexName = "myIndex";
if (!indexes.Contains(indexName))
    await pinecone.CreateServerlessIndex(indexName, 1536, Metric.Cosine, "aws", "us-east-1");

// Get the Pinecone index by name (uses gRPC by default).
// The index client is thread-safe, consider caching and/or
// injecting it as a singleton into your DI container.
using var index = await pinecone.GetIndex(indexName);

// Configure an index
await pinecone.ConfigureIndex(indexName, replicas: 2, podType: "p2");

// Delete an index
await pinecone.DeleteIndex(indexName);

Working with vectors

// Assuming you have an instance of `index`
// Create and upsert vectors
var vectors = new[]
    new Vector
        Id = "vector1",
        Values = new float[] { 0.1f, 0.2f, 0.3f },
        Metadata = new MetadataMap
            ["genre"] = "horror",
            ["duration"] = 120
await index.Upsert(vectors);

// Fetch vectors by IDs
var fetched = await index.Fetch(["vector1"]);

// Query scored vectors by ID
var scored = await index.Query("vector1", topK: 10);

// Query scored vectors by a new, previously unseen vector
var vector = new[] { 0.1f, 0.2f, 0.3f, ... };
var scored = await index.Query(vector, topK: 10);

// Query scored vectors by ID with metadata filter
var filter = new MetadataMap
    ["genre"] = new MetadataMap
        ["$in"] = new[] { "documentary", "action" }
var scored = await index.Query("birds", topK: 10, filter);

// Delete vectors by vector IDs
await index.Delete(new[] { "vector1" });

// Delete vectors by metadata filter
await index.Delete(new MetadataMap
  ["genre"] = new MetadataMap
     ["$in"] = new[] { "documentary", "action" }

// Delete all vectors in the index
await index.DeleteAll();

Working with Collections

using Pinecone;

// Assuming you have an instance of `PineconeClient` named `pinecone`
// List all collections
var collections = await pinecone.ListCollections();

// Create a new collection
await pinecone.CreateCollection("myCollection", "myIndex");

// Describe a collection
var details = await pinecone.DescribeCollection("myCollection");

// Delete a collection
await pinecone.DeleteCollection("myCollection");


Contributions are welcome! Feel free open an issue or a PR.

Product Compatible and additional computed target framework versions.
.NET net6.0 is compatible.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 is compatible.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 is compatible.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

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A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
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