Mythosia.AI.Rag.Abstractions
3.1.0
dotnet add package Mythosia.AI.Rag.Abstractions --version 3.1.0
NuGet\Install-Package Mythosia.AI.Rag.Abstractions -Version 3.1.0
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="Mythosia.AI.Rag.Abstractions" Version="3.1.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Mythosia.AI.Rag.Abstractions" Version="3.1.0" />
<PackageReference Include="Mythosia.AI.Rag.Abstractions" />
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add Mythosia.AI.Rag.Abstractions --version 3.1.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Mythosia.AI.Rag.Abstractions, 3.1.0"
#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.
#:package Mythosia.AI.Rag.Abstractions@3.1.0
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package.
#addin nuget:?package=Mythosia.AI.Rag.Abstractions&version=3.1.0
#tool nuget:?package=Mythosia.AI.Rag.Abstractions&version=3.1.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
Mythosia.AI.Rag.Abstractions
Package Summary
Core interfaces and models for the Mythosia.AI RAG ecosystem.
This package defines the contracts that all RAG components implement — you only need this directly if you're building a custom implementation.
Interfaces
| Interface | Description |
|---|---|
IRagPipeline |
Main pipeline contract: ProcessAsync(query) → RagProcessedQuery |
IEmbeddingProvider |
Text → vector embedding (GetEmbeddingAsync, GetEmbeddingsAsync) |
IVectorStore |
Vector storage & search (UpsertAsync, SearchAsync, DeleteAsync) |
IRagDiagnosticsStore |
Optional diagnostics contract (ListAllRecordsAsync, ScoredListAsync) |
ITextSplitter |
Document → chunks (Split(RagDocument)) |
IContextBuilder |
Search results → LLM prompt (BuildContext(query, results)) |
IQueryRewriter |
Rewrites follow-up queries into standalone queries using conversation history |
Models
| Model | Description |
|---|---|
RagChunk |
A chunk of text with ID, content, document ID, index, and metadata |
RagProcessedQuery |
Pipeline output: original query, rewritten query, augmented prompt, references, HasReferences flag, and Diagnostics |
ConversationTurn |
Lightweight DTO representing a single conversation turn (role + content) for IQueryRewriter |
RagQueryDiagnostics |
Applied retrieval metadata (AppliedNamespace, AppliedTopK, AppliedMinScore, ElapsedMs) |
RagPipelineOptions |
Configuration: TopK, MinScore, DefaultCollection |
RagQueryOptions |
Per-request overrides: TopK, MinScore, Namespace |
VectorRecord |
Stored vector with ID, content, embedding, metadata, namespace |
VectorSearchResult |
Search result with record and similarity score |
VectorFilter |
Filter by namespace, metadata, or minimum score |
Custom Implementation Example
public class MyEmbeddingProvider : IEmbeddingProvider
{
public int Dimensions => 768;
public Task<float[]> GetEmbeddingAsync(string text, CancellationToken ct = default)
{
// Your embedding logic here
}
public Task<IReadOnlyList<float[]>> GetEmbeddingsAsync(
IEnumerable<string> texts, CancellationToken ct = default)
{
// Batch embedding logic here
}
}
Then register via the builder:
.WithRag(rag => rag.UseEmbedding(new MyEmbeddingProvider()))
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 was computed. net5.0-windows was computed. net6.0 was computed. 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 was computed. 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 was computed. 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. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. net10.0 was computed. net10.0-android was computed. net10.0-browser was computed. net10.0-ios was computed. net10.0-maccatalyst was computed. net10.0-macos was computed. net10.0-tvos was computed. net10.0-windows was computed. |
| .NET Core | netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.1 is compatible. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| Tizen | 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)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
.NETStandard 2.1
- Mythosia.AI.Loaders.Abstractions (>= 3.1.0)
- Mythosia.VectorDb.Abstractions (>= 3.1.0)
NuGet packages (3)
Showing the top 3 NuGet packages that depend on Mythosia.AI.Rag.Abstractions:
| Package | Downloads |
|---|---|
|
Mythosia.AI.Rag
RAG (Retrieval Augmented Generation) orchestration for Mythosia.AI. Includes RagPipeline, text splitters, context builder, and OpenAI embedding provider. |
|
|
Mythosia.AI.VectorDB
In-memory vector store implementation for Mythosia.AI RAG pipeline. Provides InMemoryVectorStore with cosine similarity TopK search, metadata filtering, namespace/collection support, and upsert/delete operations. |
|
|
Mythosia.VectorDb.InMemory
In-memory vector store implementation for Mythosia VectorDb. Provides InMemoryVectorStore with cosine similarity TopK search, metadata filtering, namespace/scope support, and upsert/delete operations. |
GitHub repositories
This package is not used by any popular GitHub repositories.