Pinecone.NET 2.1.1

dotnet add package Pinecone.NET --version 2.1.1                
NuGet\Install-Package Pinecone.NET -Version 2.1.1                
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="2.1.1" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Pinecone.NET --version 2.1.1                
#r "nuget: Pinecone.NET, 2.1.1"                
#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=2.1.1

// Install Pinecone.NET as a Cake Tool
#tool nuget:?package=Pinecone.NET&version=2.1.1                


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 operations on pod-based and serverless indexes
  • gRPC and REST transports for vector operations
  • Sparse-dense vectors
  • Parallel vector upsert and fetch
  • 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 net5.0 was computed.  net5.0-windows was computed.  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. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
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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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