👁 Image
LangChain.Databases.Mongo 0.17.1

LangChain.Databases

Database abstractions and vector store backends for the LangChain.NET ecosystem.

Philosophy

This project aligns with the Microsoft.Extensions ecosystem. For vector search, we use Microsoft.Extensions.VectorData.Abstractions (MEVA) — the industry-standard .NET vector data abstraction. For backends that have official Semantic Kernel connectors, consumers should reference those packages directly rather than using wrappers.

Packages

Vector stores (MEVA implementations)

These packages implement VectorStore / VectorStoreCollection<TKey, TRecord> from Microsoft.Extensions.VectorData:

Chat message history

Use SK connectors for other backends

For backends with official Semantic Kernel connectors, use those packages directly:

Quick start

1. Define a record type

using Microsoft.Extensions.VectorData;

public class DocumentRecord
{
 [VectorStoreKey]
 public string Id { get; set; } = Guid.NewGuid().ToString();

 [VectorStoreData]
 public string Text { get; set; } = string.Empty;

 [VectorStoreVector(1536)]
 public ReadOnlyMemory<float> Embedding { get; set; }
}

2. Create a store and collection

// PostgreSQL + pgvector
var store = new PostgresVectorStore(connectionString);

// Or OpenSearch
var store = new OpenSearchVectorStore(new OpenSearchVectorDatabaseOptions
{
 ConnectionUri = new Uri("http://localhost:9200"),
});

// Or SK InMemory
var store = new InMemoryVectorStore();

var collection = store.GetCollection<string, DocumentRecord>("my_collection");
await collection.EnsureCollectionExistsAsync();

3. Upsert and search

await collection.UpsertAsync(new DocumentRecord
{
 Text = "hello world",
 Embedding = embedding,
});

await foreach (var result in collection.SearchAsync(
 new ReadOnlyMemory<float>(queryEmbedding), top: 5))
{
 Console.WriteLine($"{result.Record.Text} (score: {result.Score})");
}

Migration from IVectorDatabase

The legacy IVectorDatabase / IVectorCollection interfaces have been removed in favor of MEVA. See the for detailed before/after examples.

License

This project is licensed under the .