Εκπαίδευση
Λειτουργική μονάδα
Create a knowledge store with Azure AI Search - Training
Create a knowledge store with Azure AI Search
Αυτό το πρόγραμμα περιήγησης δεν υποστηρίζεται πλέον.
Κάντε αναβάθμιση σε Microsoft Edge για να επωφεληθείτε από τις τελευταίες δυνατότητες, τις ενημερώσεις ασφαλείας και την τεχνική υποστήριξη.
Προειδοποίηση
The C# VolatileVectorStore is obsolete and has been replaced with a new package. See InMemory Connector
Προειδοποίηση
The Semantic Kernel Vector Store functionality is in preview, and improvements that require breaking changes may still occur in limited circumstances before release.
Προειδοποίηση
The Semantic Kernel Vector Store functionality is in preview, and improvements that require breaking changes may still occur in limited circumstances before release.
The Volatile Vector Store connector is a Vector Store implementation provided by Semantic Kernel that uses no external database and stores data in memory. This Vector Store is useful for prototyping scenarios or where high-speed in-memory operations are required.
The connector has the following characteristics.
Feature Area | Support |
---|---|
Collection maps to | In-memory dictionary |
Supported key property types | Any type that can be compared |
Supported data property types | Any type |
Supported vector property types | ReadOnlyMemory<float> |
Supported index types | N/A |
Supported distance functions | N/A |
Supports multiple vectors in a record | Yes |
IsFilterable supported? | Yes |
IsFullTextSearchable supported? | Yes |
StoragePropertyName supported? | No, since storage is volatile and data reuse is therefore not possible, custom naming is not useful and not supported. |
Add the Semantic Kernel Core nuget package to your project.
dotnet add package Microsoft.SemanticKernel.Core
You can add the vector store to the dependency injection container available on the KernelBuilder
or to the IServiceCollection
dependency injection container using extension methods provided by Semantic Kernel.
using Microsoft.SemanticKernel;
// Using Kernel Builder.
var kernelBuilder = Kernel
.CreateBuilder()
.AddVolatileVectorStore();
using Microsoft.SemanticKernel;
// Using IServiceCollection with ASP.NET Core.
var builder = WebApplication.CreateBuilder(args);
builder.Services.AddVolatileVectorStore();
You can construct a Volatile Vector Store instance directly.
using Microsoft.SemanticKernel.Data;
var vectorStore = new VolatileVectorStore();
It is possible to construct a direct reference to a named collection.
using Microsoft.SemanticKernel.Data;
var collection = new VolatileVectorStoreRecordCollection<string, Hotel>("skhotels");
Install semantic kernel.
pip install semantic-kernel
You can then create a vector store instance using the VolatileStore
class.
from semantic_kernel.connectors.memory.volatile import VolatileStore
vector_store = VolatileStore()
You can also create a collection directly.
from semantic_kernel.connectors.memory.volatile import VolatileCollection
collection = VolatileCollection(collection_name="skhotels", data_model_type=Hotel)
Since the Volatile connector has a simple dict as the internal storage mechanism it can store any data model that can be serialized to a dict.
For more details on this concept see the serialization documentation.
Include the latest version of the Semantic Kernel API in your Maven project, add the following dependency to your pom.xml
:
<dependency>
<groupId>com.microsoft.semantic-kernel</groupId>
<artifactId>semantickernel-api</artifactId>
<version>[LATEST]</version>
</dependency>
You can then create a vector store instance using the VolatileVectorStore
class.
import com.microsoft.semantickernel.data.VolatileVectorStore;
import com.microsoft.semantickernel.data.VolatileVectorStoreRecordCollection;
import com.microsoft.semantickernel.data.VolatileVectorStoreRecordCollectionOptions;
public class Main {
public static void main(String[] args) {
// Build an Azure AI Search Vector Store
var vectorStore = new VolatileVectorStore();
}
}
You can also create a collection directly.
var collection = new VolatileVectorStoreRecordCollection<>("skhotels",
VolatileVectorStoreRecordCollectionOptions.<Hotel>builder()
.withRecordClass(Hotel.class)
.build());
Εκπαίδευση
Λειτουργική μονάδα
Create a knowledge store with Azure AI Search - Training
Create a knowledge store with Azure AI Search
Τεκμηρίωση
Using the Semantic Kernel In-Memory Vector Store connector (Preview)
Contains information on how to use a Semantic Kernel Vector store connector to access and manipulate data in an in-memory Semantic Kernel supplied vector store.
Using the Semantic Kernel SQLite Vector Store connector (Preview)
Contains information on how to use a Semantic Kernel Vector store connector to access and manipulate data in SQLite.
Using the Semantic Kernel MongoDB Vector Store connector (Preview)
Contains information on how to use a Semantic Kernel Vector store connector to access and manipulate data in MongoDB.