Pinecone.NET 2.1.0

There is a newer version of this package available.
See the version list below for details.
dotnet add package Pinecone.NET --version 2.1.0                
NuGet\Install-Package Pinecone.NET -Version 2.1.0                
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="2.1.0" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Pinecone.NET --version 2.1.0                
#r "nuget: Pinecone.NET, 2.1.0"                
#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=2.1.0

// Install Pinecone.NET as a Cake Tool
#tool nuget:?package=Pinecone.NET&version=2.1.0                

Pinecone.NET

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#.

Features

  • 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)

Installation

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

Usage

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");

Contributing

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.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on Pinecone.NET:

Package Downloads
Microsoft.SemanticKernel.Connectors.Pinecone

Pinecone connector for Semantic Kernel plugins and semantic memory

Squidex.AI

Squidex Internal Libraries

OBotService

OBase Framework

GitHub repositories (2)

Showing the top 2 popular GitHub repositories that depend on Pinecone.NET:

Repository Stars
microsoft/semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
Azure-Samples/azure-search-openai-demo-csharp
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.
Version Downloads Last updated
3.0.0 714 9/27/2024
2.1.1 40,935 6/21/2024
2.1.0 2,641 6/5/2024
2.0.0 670 5/18/2024
1.4.0 6,627 12/17/2023
1.3.2 8,697 11/21/2023
1.3.1 640 11/14/2023
1.3.0 24,605 8/15/2023
1.2.2 2,411 7/27/2023
1.2.1 4,860 7/7/2023
1.2.0 2,384 5/15/2023
1.1.0 103 5/13/2023
1.0.0 301 5/10/2023