Cohesive.AI 0.1.0-alpha.30

This is a prerelease version of Cohesive.AI.
dotnet add package Cohesive.AI --version 0.1.0-alpha.30
                    
NuGet\Install-Package Cohesive.AI -Version 0.1.0-alpha.30
                    
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="Cohesive.AI" Version="0.1.0-alpha.30" />
                    
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Cohesive.AI" Version="0.1.0-alpha.30" />
                    
Directory.Packages.props
<PackageReference Include="Cohesive.AI" />
                    
Project file
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 Cohesive.AI --version 0.1.0-alpha.30
                    
#r "nuget: Cohesive.AI, 0.1.0-alpha.30"
                    
#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 Cohesive.AI@0.1.0-alpha.30
                    
#: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=Cohesive.AI&version=0.1.0-alpha.30&prerelease
                    
Install as a Cake Addin
#tool nuget:?package=Cohesive.AI&version=0.1.0-alpha.30&prerelease
                    
Install as a Cake Tool

Cohesive.AI

AI-oriented semantic contracts for inference, training, vector storage, text processing, tokenization, ontology modeling, and model registries.

Install

dotnet add package Cohesive.AI

Use When

  • You need provider-neutral contracts for embeddings, pair scoring, graph scoring, feature-vector scoring, or model training.
  • You want to model semantic concepts, ontologies, closure rules, and concept grounding.
  • You need reusable text/token utilities or vector store abstractions without taking a specific cloud or model runtime dependency.

Example

using Cohesive.AI.Semantics;

var ontology = new OntologyBuilder()
    .AddConcept(new("party.role", "Party Role"))
    .AddConcept(new("party.ship-to", "Ship To"))
    .AddParent(childConceptId: "party.ship-to", parentConceptId: "party.role")
    .AddScopedMeaning(scope: "edi.n101", symbol: "ST", conceptId: "party.ship-to")
    .Build();

var closure = OntologyClosure.Create(ontology);
var isPartyRole = closure.IsSubConceptOf("party.ship-to", "party.role");

Reconciliable training submissions

Training submission is identified independently of any physical attempt. Bind the workflow's stable logical identity to the exact request once, then use the same submission for dispatch and ambiguity recovery:

using Cohesive.AI.Training;

var submission = new TrainingJobSubmission(
    submissionId: "tenant/acme/training-run/42/submission",
    request: trainingRequest);

var job = await trainer.SubmitAsync(submission, cancellationToken);
var reconciliation = await trainer.ReconcileSubmissionAsync(submission, cancellationToken);

TrainingJobSubmission snapshots dataset bindings and derives a versioned request fingerprint. Dataset bindings are canonicalized by their ordinal names because list order is not provider meaning; duplicate names are rejected. Every other request value, including provider configuration text, participates exactly. An adapter must return the same provider job for a repeated identity and fingerprint, and must throw TrainingJobSubmissionConflictException when the identity is already bound to different or missing request evidence.

Reconciliation returns one closed result: Accepted, ConfirmedAbsent, or Unresolved. A workflow may safely retry only according to its durable recovery policy and the returned evidence; physical attempt identity must not replace the stable logical submission identity.

  • Cohesive.Adapters.AzureML for Azure Machine Learning training integration.
  • Cohesive.Adapters.AzureStorage for training artifacts and dataset output streams backed by Azure Blob Storage.
  • Cohesive.Adapters.ONNX and Cohesive.Adapters.MicrosoftML for concrete inference/tokenization integrations.
Product Compatible and additional computed target framework versions.
.NET net10.0 is compatible.  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. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (6)

Showing the top 5 NuGet packages that depend on Cohesive.AI:

Package Downloads
Cohesive.Adapters.AzureStorage

Cohesive semantic system definition and orchestration building blocks.

Cohesive.Adapters.GitHub

Cohesive semantic system definition and orchestration building blocks.

Cohesive.Adapters.Cosmos

Cohesive semantic system definition and orchestration building blocks.

Cohesive.Adapters.AzureML

Cohesive semantic system definition and orchestration building blocks.

Cohesive.Adapters.ONNX

Cohesive semantic system definition and orchestration building blocks.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
0.1.0-alpha.30 0 8/18/2026
0.1.0-alpha.29 51 8/17/2026
0.1.0-alpha.28 68 8/17/2026
0.1.0-alpha.27 57 8/17/2026
0.1.0-alpha.26 71 8/16/2026
0.1.0-alpha.25 60 8/16/2026
0.1.0-alpha.24 63 8/16/2026
0.1.0-alpha.23 69 8/16/2026
0.1.0-alpha.22 67 8/16/2026
0.1.0-alpha.21 61 8/16/2026
0.1.0-alpha.20 84 8/15/2026
0.1.0-alpha.19 67 8/15/2026
0.1.0-alpha.18 70 8/15/2026
0.1.0-alpha.17 81 8/14/2026
0.1.0-alpha.16 79 8/13/2026
0.1.0-alpha.15 83 8/13/2026
0.1.0-alpha.14 73 8/13/2026
0.1.0-alpha.13 82 8/12/2026
0.1.0-alpha.12 81 8/12/2026
0.1.0-alpha.11 82 8/12/2026
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