AICentral 0.20.3

There is a newer version of this package available.
See the version list below for details.
dotnet add package AICentral --version 0.20.3                
NuGet\Install-Package AICentral -Version 0.20.3                
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="AICentral" Version="0.20.3" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add AICentral --version 0.20.3                
#r "nuget: AICentral, 0.20.3"                
#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 AICentral as a Cake Addin
#addin nuget:?package=AICentral&version=0.20.3

// Install AICentral as a Cake Tool
#tool nuget:?package=AICentral&version=0.20.3                

AI Central

AI Central gives you control over your AI services.

  • Minimal overhead - written on Asp.Net Core, on dotnet 8. One of the fastest web-servers in the business.
  • Enable advanced Azure APIm scenarios such as passing a Subscription Key, and a JWT from libraries like PromptFlow that don't support that out-of-the-box.
  • PII Stripping logging to Cosmos DB
    • Powered by graemefoster/aicentral.logging.piistripping
  • Lightweight out-the-box token metrics surfaced through Open Telemetry
    • Does not buffer and block streaming
    • Use for PTU Chargeback scenarios
    • Gain quick insights into who's using what, how much, and how often
    • Standard Open Telemetry format to surface Dashboards in you monitoring solution of choice
  • Prompt and usage logging to Azure Monitor
    • Works for streaming endpoints as-well as non-streaming
  • Intelligent Routing
    • Endpoint Selector that favours endpoints reporting higher available capacity
    • Random endpoint selector
    • Prioritised endpoint selector with fallback
    • Lowest Latency endpoint selector
  • Can proxy asynchronous requests such as Azure OpenAI DALLE2 Image Generation across fleets of servers
  • Custom consumer OAuth2 authorisation
  • Can mint JWT time-bound and consumer-bound JWT tokens to make it easy to run events like Hackathons without blowing your budget
  • Circuit breakers and backoff-retry over downstream AI services
  • Local token rate limiting
    • By consumer / by endpoint
    • By number of tokens (including streaming by estimated token count)
  • Local request rate limiting
    • By consumer / by endpoint
  • Bulkhead support for buffering requests to backend
  • Distributed token rate limiting (using Redis)
    • Powered by an extension graemefoster/aicentral.ratelimiting.distributedredis
  • AI Search Vectorization endpoint
    • Powered by an extension graemefoster/aicentral.azureaisearchvectorizer

Configuration

See docs on Github for more details.

Minimal

This sample produces a AI-Central proxy that

  • Listens on a hostname of your choosing
  • Proxies directly through to a back-end Open AI server
  • Can be accessed using standard SDKs
  • Outputs open-telemetry metrics to capture usage information
{
  "AICentral": {
    "Endpoints": [
      {
        "Type": "AzureOpenAIEndpoint",
        "Name": "openai-1",
        "Properties": {
          "LanguageEndpoint": "https://<my-ai>.openai.azure.com",
          "AuthenticationType": "ApiKey",
          "ApiKey": "<key>"
        }
      }
    ],
    "EndpointSelectors": [
      {
        "Type": "SingleEndpoint",
        "Name": "default",
        "Properties": {
          "Endpoint": "openai-1"
        }
      }
    ],
    "AuthProviders": [
      {
        "Type": "ApiKey",
        "Name": "apikey",
        "Properties": {
          "Clients": [
            {
              "ClientName": "Consumer-1",
              "Key1": "<random-key>",
              "Key2": "<random-key>"
            }
          ]
        }
      }
    ],
    "Pipelines": [
      {
        "Name": "OpenAIPipeline",
        "Host": "mypipeline.mydomain.com",
        "EndpointSelector": "default",
        "AuthProvider": "apikey",
        "OpenTelemetryConfig": {
          "AddClientNameTag": true,
          "Transmit": true
        }
      }
    ]
  }
}

Full example

This pipeline will:

  • Present an Azure Open AI, and an Open AI downstream as a single upstream endpoint
    • maps the incoming deployment Name "GPT35Turbo0613" to the downstream Azure Open AI deployment "MyGptModel"
    • maps incoming Azure Open AI deployments to Open AI models
  • Present it as an Azure Open AI style endpoint
  • Protect the front-end by requiring an AAD token issued for your own AAD application
  • Put a local Asp.Net core rate-limiting policy over the endpoint
  • Emit Open Telemetry to be picked up by your OTel collector
  • Add rich logging to Azure monitor
    • Logs quota, client caller information (IP and identity name), and in this case the Prompt but not the response.
  • Publish the client-name as a tag in Open Telemetry
{
  "AICentral": {
    "Endpoints": [
      {
        "Type": "AzureOpenAIEndpoint",
        "Name": "openai-priority",
        "Properties": {
          "LanguageEndpoint": "https://<my-ai>.openai.azure.com",
          "AuthenticationType": "Entra|EntraPassThrough|ApiKey",
          "MaxConcurrency": 10,
          "ModelMappings": {
            "Gpt35Turbo0613": "MyGptModel"
          }
        }
      },
      {
        "Type": "OpenAIEndpoint",
        "Name": "openai-fallback",
        "Properties": {
          "LanguageEndpoint": "https://api.openai.com",
          "ModelMappings": {
            "Gpt35Turbo0613": "gpt-3.5-turbo",
            "Ada002Embedding": "text-embedding-ada-002"
          },
          "ApiKey": "<my-api-key>",
          "Organization": "<optional-organisation>"
        }
      }
    ],
    "AuthProviders": [
      {
        "Type": "Entra",
        "Name": "simple-aad",
        "Properties": {
          "Entra": {
            "ClientId": "<my-client-id>",
            "TenantId": "<my-tenant-id>",
            "Instance": "https://login.microsoftonline.com/",
            "Audience": "<custom-audience>"
          }
        }
      }
    ],
    "EndpointSelectors": [
      {
        "Type": "Prioritised",
        "Name": "my-endpoint-selector",
        "Properties": {
          "PriorityEndpoints": ["openai-1"],
          "FallbackEndpoints": ["openai-fallback"]
        }
      }
    ],
    "GenericSteps": [
      {
        "Type": "AspNetCoreFixedWindowRateLimiting",
        "Name": "token-rate-limiter",
        "Properties": {
          "LimitType": "PerConsumer|PerAICentralEndpoint",
          "MetricType": "Tokens",
          "Options": {
            "Window": "00:01:00",
            "PermitLimit": 1000
          }
        }
      },
      {
        "Type": "AspNetCoreFixedWindowRateLimiting",
        "Name": "window-rate-limiter",
        "Properties": {
          "LimitType": "PerConsumer|PerAICentralEndpoint",
          "MetricType": "Requests",
          "Options": {
            "Window": "00:00:10",
            "PermitLimit": 100
          }
        }
      },
      {
        "Type": "AzureMonitorLogger",
        "Name": "azure-monitor-logger",
        "Properties": {
          "WorkspaceId": "<workspace-id>",
          "Key": "<key>",
          "LogPrompt": true,
          "LogResponse": false,
          "LogClient": true
        }
      },
      {
        "Type": "BulkHead",
        "Name": "bulk-head",
        "Properties": {
          "MaxConcurrency": 20
        }
      }
    ],
    "Pipelines": [
      {
        "Name": "MyPipeline",
        "Host": "prioritypipeline.mydomain.com",
        "EndpointSelector": "my-endpoint-selector",
        "AuthProvider": "simple-aad",
        "Steps": [
          "window-rate-limiter",
          "bulk-head",
          "azure-monitor-logger"
        ],
        "OpenTelemetryConfig": {
          "AddClientNameTag": true,
          "Transmit": true
        }
      }
    ]
  }
}

Product Compatible and additional computed target framework versions.
.NET 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

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

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releasenotes.md